WO2024020572A1 - Methods and compositions for the treatment of ptsd - Google Patents

Methods and compositions for the treatment of ptsd Download PDF

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Publication number
WO2024020572A1
WO2024020572A1 PCT/US2023/070761 US2023070761W WO2024020572A1 WO 2024020572 A1 WO2024020572 A1 WO 2024020572A1 US 2023070761 W US2023070761 W US 2023070761W WO 2024020572 A1 WO2024020572 A1 WO 2024020572A1
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glucocorticoid
ptsd
individual
expression
gene
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PCT/US2023/070761
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French (fr)
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Rachel Yehuda
Kristen Brennand
Daniel John PAULL
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New York Stem Cell Foundation, Inc.
Icahn School Of Medicine At Mount Sinai
The United States Government As Represented By The Department Of Veteran Affairs
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Publication of WO2024020572A1 publication Critical patent/WO2024020572A1/en

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    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61K—PREPARATIONS FOR MEDICAL, DENTAL OR TOILETRY PURPOSES
    • A61K31/00—Medicinal preparations containing organic active ingredients
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61K—PREPARATIONS FOR MEDICAL, DENTAL OR TOILETRY PURPOSES
    • A61K31/00—Medicinal preparations containing organic active ingredients
    • A61K31/56—Compounds containing cyclopenta[a]hydrophenanthrene ring systems; Derivatives thereof, e.g. steroids
    • A61K31/57—Compounds containing cyclopenta[a]hydrophenanthrene ring systems; Derivatives thereof, e.g. steroids substituted in position 17 beta by a chain of two carbon atoms, e.g. pregnane or progesterone
    • A61K31/573—Compounds containing cyclopenta[a]hydrophenanthrene ring systems; Derivatives thereof, e.g. steroids substituted in position 17 beta by a chain of two carbon atoms, e.g. pregnane or progesterone substituted in position 21, e.g. cortisone, dexamethasone, prednisone or aldosterone
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61P—SPECIFIC THERAPEUTIC ACTIVITY OF CHEMICAL COMPOUNDS OR MEDICINAL PREPARATIONS
    • A61P25/00—Drugs for disorders of the nervous system
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61P—SPECIFIC THERAPEUTIC ACTIVITY OF CHEMICAL COMPOUNDS OR MEDICINAL PREPARATIONS
    • A61P25/00—Drugs for disorders of the nervous system
    • A61P25/18—Antipsychotics, i.e. neuroleptics; Drugs for mania or schizophrenia
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61P—SPECIFIC THERAPEUTIC ACTIVITY OF CHEMICAL COMPOUNDS OR MEDICINAL PREPARATIONS
    • A61P25/00—Drugs for disorders of the nervous system
    • A61P25/20—Hypnotics; Sedatives
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61P—SPECIFIC THERAPEUTIC ACTIVITY OF CHEMICAL COMPOUNDS OR MEDICINAL PREPARATIONS
    • A61P25/00—Drugs for disorders of the nervous system
    • A61P25/22—Anxiolytics
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/5005—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving human or animal cells
    • G01N33/5008—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving human or animal cells for testing or evaluating the effect of chemical or biological compounds, e.g. drugs, cosmetics
    • G01N33/5044—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving human or animal cells for testing or evaluating the effect of chemical or biological compounds, e.g. drugs, cosmetics involving specific cell types
    • G01N33/5058—Neurological cells
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/68—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving proteins, peptides or amino acids
    • G01N33/6893—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving proteins, peptides or amino acids related to diseases not provided for elsewhere
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2333/00—Assays involving biological materials from specific organisms or of a specific nature
    • G01N2333/435—Assays involving biological materials from specific organisms or of a specific nature from animals; from humans
    • G01N2333/705—Assays involving receptors, cell surface antigens or cell surface determinants
    • G01N2333/72—Assays involving receptors, cell surface antigens or cell surface determinants for hormones
    • G01N2333/723—Steroid/thyroid hormone superfamily, e.g. GR, EcR, androgen receptor, oestrogen receptor
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2800/00—Detection or diagnosis of diseases
    • G01N2800/30—Psychoses; Psychiatry
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2800/00—Detection or diagnosis of diseases
    • G01N2800/60—Complex ways of combining multiple protein biomarkers for diagnosis

Definitions

  • PTSD Post-Traumatic Stress Disorder
  • agents that modify the glucocorticoid response e.g., glucocorticoid rector antagonists
  • psychedelic agents e.g., glucocorticoid rector antagonists
  • BACKGROUND Post-Traumatic Stress Disorder (PTSD) affects 7-8% of the general population of the United States and approximately 15% of veterans returning from combat. The symptoms can persist for months or decades. Unfortunately, PTSD is often misdiagnosed and left untreated in affected civilian and military individuals, disrupting the quality of their lives, their families, and children. Even when diagnosed, the severity of PTSD progression remains difficult to treat.
  • PTSD diagnosis in monozygotic and dizygotic twins, and genome-wide association studies (GWAS) estimate single nucleotide polymorphism (SNP)-based heritability from 5-30% and identify loci significantly associated with PTSD.
  • SNP single nucleotide polymorphism
  • PBMCs peripheral blood mononuclear cells
  • the present disclosure includes the disclosure that the expression and activity of particular biomarkers (e.g., one or more genes of the glucocorticoid response (e.g., a gene from Table 1 and/or Table 2) in biological samples can be utilized to diagnose, prognose, and treat post-traumatic stress disorder (PTSD) in individuals, and further to select individuals who would benefit from a therapy in which one or more psychedelic agents and/or agents that modify the glucocorticoid response are administered. Accordingly, the present disclosure encompasses methods that utilize genes of the glucocorticoid response for the diagnosis, prognosis, and/or treatment of PTSD.
  • biomarkers e.g., one or more genes of the glucocorticoid response (e.g., a gene from Table 1 and/or Table 2) in biological samples
  • PTSD post-traumatic stress disorder
  • the present disclosure encompasses methods that utilize genes of the glucocorticoid response for the diagnosis, prognosis, and/or treatment of
  • psychedelic agents for use in the treatment of post- traumatic stress disorder (PTSD), wherein the individual has modified expression and/or activity of MYC, PAX6, YY1, LEF1, or NFKB1 relative to a suitable control.
  • the individual has modified expression and/or activity of MYC, PAX6, YY1, and LEF1 relative to a suitable control.
  • the individual has increased expression and/or activity of MYC, increased expression and/or activity of PAX6, increased expression and/or activity of YY1, and/or increased expression and/or activity of LEF1.
  • kits for treating an individual having modified expression and/or activity of MYC, PAX6, YY1, LEF1, or NFKB1 relative to a suitable control for post-traumatic stress disorder comprising administering to the individual a therapeutically effective amount of a psychedelic agent.
  • the individual has modified expression and/or activity of MYC, PAX6, YY1, and LEF1 relative to a suitable control.
  • the individual has increased expression and/or activity of MYC, increased expression and/or activity of PAX6, increased expression and/or activity of YY1, and/or increased expression and/or activity of LEF1.
  • the disclosure provides a method of treating an individual diagnosed with PTSD including administering to the individual diagnosed with PTSD a therapeutically effective amount of a psychedelic agent and/or glucocorticoid receptor antagonist.
  • the individual diagnosed with PTSD is diagnosed with PTSD by a the method including: i) obtaining a biological sample from the individual suspected of being at risk for PTSD; ii) processing a cell obtained from the biological sample to produce a test cell; iii) contacting the test cell with a glucocorticoid to produce a glucocorticoid-induced response; iv) detecting the expression and/or activity of one or more gene(s) of the glucocorticoid-induced response; and v) diagnosing the individual with PTSD if the expression and/or activity of the one or more gene(s) of the glucocorticoid- induced response are modified relative to a suitable control
  • the disclosure provides a method of preventing PTSD in an individual at risk for PTSD comprising administering to the indivusualg a therapeutically effective amount of a glucocorticoid receptor antagonist and/or a psychedelic agent.
  • an individual at risk for PTSD is identified as an individual at risk for PTSD by the method including: i) obtaining a biological sample from the individual suspected of being at risk for PTSD; ii) processing a cell obtained from the biological sample to produce a test cell; iii) contacting the test cell with a glucocorticoid to produce a glucocorticoid-induced response; iv) detecting the expression and/or activity of one or more gene(s) of the glucocorticoid-induced response; and v) identifying the individual as at risk for PTSD or if the expression and/or activity of the one or more gene(s) of the glucocorticoid-induced response are modified relative to a suitable control.
  • the disclosure provides a method of treating an individual at risk for PTSD, suffering from one or more symptoms associated with PTSD, and/or diagnosed with PTSD, the method including: i) obtaining a biological sample from the individual suspected of being at risk for PTSD, suffering from one or more symptoms associated with PTSD, or diagnosed with PTSD; ii) processing a cell obtained from the biological sample to produce a test cell; iii) contacting the test cell with a glucocorticoid to produce a glucocorticoid-induced response; iv) detecting the expression and/or activity of one or more gene(s) of the glucocorticoid-induced response; v) identifying the individual as at risk for PTSD or diagnosing the individual with PTSD when the expression and/or activity of the one or more gene(s) of the glucocorticoid-induced response are modified relative to a suitable control; and vi) administering to the individual identified as at risk for PTSD or diagnosed with PTSD
  • the one or more gene(s) of the glucocorticoid-induced response are increased relative to a suitable control.
  • the one or more gene(s) of the glucocorticoid-induced response are decreased relative to a suitable control.
  • the disclosure provides a method for identifying an individual at risk for PTSD or diagnosed with PTSD, the method including: i) obtaining a biological sample from the individual suspected of being at risk for PTSD or diagnosed with PTSD; ii) processing a cell obtained from the biological sample to produce a test cell; iii) contacting the test cell with a glucocorticoid to produce a glucocorticoid-induced response; iv) detecting the expression and/or activity of one or more gene(s) of the glucocorticoid-induced response; and v) identifying the individual as at risk for PTSD or diagnosing the individual with PTSD if the expression and/or activity of the one or more gene(s) of the glucocorticoid-induced response are modified relative to a suitable control.
  • the disclosure provides a method of treating an individual at risk for developing PTSD, diagnosed with PTSD, or experiencing one or more symptoms associated with PTSD, the method including administering one more psychedelic agent(s) and/or agent(s) that modify the glucocorticoid-induced response.
  • the one or more agent(s) that modify the glucocorticoid-induced response includes a glucocorticoid receptor antagonist.
  • the one or more agent(s) is administered via a parenteral or a non-parenteral route.
  • the disclosure provides a method for screening compounds that reduce the risk of an individual developing PTSD, reduce the risk of an individual developing one or more symptoms of PTSD, and/or alleviate one or more symptoms of PTSD in an individual, the method including: i) obtaining a biological sample from the individual at risk for PTSD or suffering from PTSD; ii) processing a cell obtained from the biological sample to produce a test cell; iii) contacting the test cell with a glucocorticoid to produce a glucocorticoid-induced response; iv) contacting the test cell with one or more test agent(s); detecting the expression and/or activity of one or more gene(s) of the glucocorticoid-induced response; and v) if the one or more test agent(s) modifies the expression and/or activity of one or more gene(s) of the glucocorticoid-induced response compared to a suitable control, identifying the test agent as a compound that does reduce
  • the one or more gene(s) of the glucocorticoid-induced response include one or more genes selected from the group consisting of MAN1A2, CD1D, CEP350, DISP1, USP37, NPHP3, GOLGA4, KIAA1109, DKK4, BMI1, NEDD4, NF1, CEACAM19, ZNF235, KRCC1, KCTD16, RP11-664D7.4, C8orf87, ANO1, PACS1, UBQLNL, LRRC56, DPYSL4, HMBS, SNRNP35, TM2D3, C17orf75, GATA5, ZNF443, ZC3H12B, RSF1, KPNA4, C12orf57, ATP6V0B, ANAPC11, KCNK2, OR7D2, NUDT16, ANKRD17, ERGIC3, KLF7, PEAK1, ASAP1, MIAT, SGPP2, RPS11, A1
  • the one or more test agent(s) increases the expression and/or activity of one or more gene(s) of the glucocorticoid- induced response.
  • the one or more gene(s) include one or more genes selected from the group consisting of ZC3H12B, RSF1, ANKRD17, KLF7, PEAK1, ASAP1, MIAT, SGPP2, RPS11, A1L2, CSMD1, PEX6, PDE11A, DCTN3, TIMP3, ZNF587, and combinations thereof.
  • the one or more test agent(s) decreases the expression and/or activity of one or more gene(s) of the glucocorticoid-induced response.
  • the one or more gene(s) include one or more genes selected from the group consisting of KPNA4, C12orf57, ATP6V0B, ANAPC11, KCNK2, OR7D2, NUDT16, ERGIC3, MASP1, IL1RAPL2, MRPL11, RBX1, TMEM98, IFT27, PPIB, TOMM22, CALCB, RNF152, and combinations thereof.
  • the suitable control includes a prior biological sample taken from the same individual, a biological sample from a healthy individual not having a risk for PTSD, a biological sample from an individual not having one or more symptoms associated with PTSD, or a biological sample from an individual that is diagnosed with PTSD that has been treated for PTSD.
  • the biological sample includes blood cells and/or fibroblasts.
  • processing the cell obtained from the biological sample includes dedifferentiating the cell to produce an induced pluripotent stem cell (iPSC).
  • iPSC induced pluripotent stem cell
  • the iPSC is differentiated to produce the test cell.
  • the differentiated iPSC includes an induced neuron or an induced peripheral blood mononuclear cell.
  • the test cell includes a neuron or a peripheral blood mononuclear cell.
  • the neuron is a glutamatergic neuron.
  • the glucocorticoid includes a glucocorticoid receptor agonist.
  • the glucocorticoid receptor agonist is dexamethasone or hydrocortisone.
  • the detecting includes sequencing RNA derived from the biological sample.
  • the detecting includes detecting a transcriptional profile of a glucocorticoid-induced response.
  • the detecting includes assessing epigenetic changes of the one or more gene(s) of the glucocorticoid-induced response.
  • the assessing of epigenetic changes includes performing a chromatin immunoprecipitation assay.
  • the expression and/or activity of the one or more gene(s) of the glucocorticoid-induced response is increased for a first subset of genes and decreased for a second subset of genes to produce a glucocorticoid- induced response signature.
  • the suitable control includes substantially no test agent.
  • the processing includes automated reprogramming of the cell obtained from the biological sample.
  • contacting the test cell with a glucocorticoid is performed for a duration of from about 1 hour to about 96 hours (e.g., about 2 hours to about 95 hours, about 3 hours to about 90 hours, about 4 hours to about 80 hours, about 5 hours to about 70 hours, about 10 hours to about 60 hours, about 20 hours to about 50 hours, or about 30 hours to about 40 hours).
  • the glucocorticoid has a concentration of from about 1 nM to about 10 ⁇ M (e.g., about 10 nM to about 9 ⁇ M, about 50 nM to about 8 ⁇ M, about 100 nM to about 7 ⁇ M, about 1 ⁇ M to about 6 ⁇ M, about 2 ⁇ M to about 5 ⁇ M, about 3 ⁇ M to about 4 ⁇ M).
  • contacting the test cell with one or more test agent(s) is performed for a duration of from about 1 hour to about 96 hours (e.g., about 2 hours to about 95 hours, about 3 hours to about 90 hours, about 4 hours to about 80 hours, about 5 hours to about 70 hours, about 10 hours to about 60 hours, about 20 hours to about 50 hours, or about 30 hours to about 40 hours).
  • the test agent has a concentration of from about 1 nM to about 10 ⁇ M (e.g., about 10 nM to about 9 ⁇ M, about 50 nM to about 8 ⁇ M, about 100 nM to about 7 ⁇ M, about 1 ⁇ M to about 6 ⁇ M, about 2 ⁇ M to about 5 ⁇ M, about 3 ⁇ M to about 4 ⁇ M).
  • the disclosure provides a method of identifying a PTSD- dependent glucocorticoid response gene signature, the method including: i) obtaining a biological sample from an individual suspected of being at risk for PTSD, suffering from one or more symptoms associated with PTSD, or diagnosed with PTSD; ii) processing a cell obtained from the biological sample to produce a test cell; iii) contacting the test cell with a glucocorticoid to produce a glucocorticoid-induced response; iv) detecting the expression and/or activity of a plurality of genes; and v) comparing the expression and/or activity of the plurality of genes with the expression and/or activity of the plurality of genes from a suitable control sample obtained from a healthy individual.
  • the individual is a juvenile.
  • methods of treating an individual at risk for PTSD, suffering from one or more symptoms associated with PTSD, or diagnosed with PTSD comprising: administering to the individual one or more psychedelic agent(s) and/or agent(s) that modify the glucocorticoid-induced response, wherein expression and/or activity of one or more gene(s) of the glucocorticoid-induced response in test cells produced from a biological sample obtained from the individual were modified relative to a suitable control when such test cells were contacted with a glucocorticoid.
  • psychedelic agents for use in a method of treating an individual at risk for PTSD, suffering from one or more symptoms associated with PTSD, or diagnosed with PTSD, wherein expression and/or activity of one or more gene(s) of the glucocorticoid-induced response in test cells produced from a biological sample obtained from the individual were modified relative to a suitable control when such test cells were contacted with a glucocorticoid.
  • agents that modify the glucocorticoid response for use in a method of treating an individual at risk for PTSD, suffering from one or more symptoms associated with PTSD, or diagnosed with PTSD, wherein expression and/or activity of one or more gene(s) of the glucocorticoid-induced response in test cells produced from a biological sample obtained from the individual were modified relative to a suitable control when such test cells were contacted with a glucocorticoid.
  • the present disclosure is based, at least in part, on the surprising finding that glucocorticoid-induced (e.g., to dexamethasone (DEX) and hydrocortisone (HCort)) blood and neuronal responses were significantly enriched for immune response, brain development, and neurodevelopmental disorder genes, with specific upregulation of PTSD-associated genes in neurons only.
  • DEX dexamethasone
  • HCort hydrocortisone
  • the present disclosure is also based, at least in part, on the finding that glucocorticoid hypersensitivity occurred in samples from PTSD cases, with diagnosis- specific effects greatest at low doses, and significantly more robust in neurons than peripheral blood mononuclear cells (PBMCs).
  • PBMCs peripheral blood mononuclear cells
  • a baseline PTSD diagnosis-specific signature was undetectable in either human neurons or PBMCs.
  • This glucocorticoid-response signature was enriched for transcriptomic patterns observed in post-mortem brain tissue from PTSD cases.
  • FIGs.1A-1E are an experimental schematic and a set of graphs, respectively, showing the transcriptional response to dexamethasone (DEX) in peripheral blood mononuclear cells (PBMCs).
  • FIG.1A is a schematic showing the experimental design. PBMCs from 20 post-traumatic stress disorder (PTSD) cases and 20 combat-exposed controls were treated with DEX for 72 hours and RNAseq was performed.
  • PTSD post-traumatic stress disorder
  • RNAseq was performed.
  • FIG.1C is a set of graphs showing the meta-analysis of expression LogFC (differences observed between vehicle and DEX exposure), which was plotted against -log(P value) for each gene. Gray points indicate significantly differentially expressed genes in the meta-analysis.
  • FIG.1D is a set of graphs showing Module eigengene (ME) values from modules identified by weighted gene co-expression network analysis (WGCNA) were correlated with increasing DEX concentrations. Top correlated modules with DEX concentration are shown here (p-values are labeled above each boxplot). Each module was subjected to gene ontology enrichment analysis and the topmost significant enrichment terms and their associated Benjamini-Hochberg adjusted P-values are displayed.
  • FIG.1E is a graph showing the gene set enrichment of DEX-dependent differentially expressed genes across psychiatric disorder and neurodevelopmental gene sets.
  • FIGs.2A-2F are an experimental schematic and a set of graphs, respectively, showing gene expression changes to hydrocortisone (HCort) in human induced pluripotent stem cell (hiPSC)-derived neurons.
  • FIG.2A is a schematic showing the experimental design.
  • hiPSC-derived neurogenin 2 (NGN2) neurons were treated with HCort for 24 hours and RNAseq was performed.
  • FIG.2B depicts a set of photomicrographs of NGN2 neurons stained for neuronal markers NESTIN and MAP2, nucleic marker HOECHST, and green fluorescent protein (GFP) to confirm neuronal identity and morphology across all conditions.
  • GFP green fluorescent protein
  • FIG.2C is a set of graphs showing meta-analyzed differentially expressed genes (DEGs) in response to increasing concentrations of HCort shows robust changes in NGN2-neurons.
  • DEGs differentially expressed genes
  • a comparative analysis of transcriptome-wide log2 fold-changes in response to different concentrations of HCort in NGN2-neurons shows similar responses, indicating a conserved response across all donors to HCort in NGN2-neurons.
  • FIG.2D is a set of graphs showing the meta-analysis of expression LogFC (differences observed between vehicle and HCort exposure), which was plotted against -log(P value) for each gene. Gray points indicate significantly differentially expressed genes in the meta-analysis.
  • FIG.2E is a graph and respective photomicrograph showing the morphological analysis of neurite outgrowth on day 7 in NGN2-neurons showing a dose-dependent decrease in neurite outgrowth with HCort exposure. Representative images of neurite morphology to HCort exposure are shown below.
  • FIG.2F is a graph showing the gene set enrichment of HCort-dependent differentially expressed genes across psychiatric disorder and neurodevelopmental gene sets.
  • FIGs.3A-3B are a set of graphs showing the HCort stimulated co-expression modules in NGN2-neurons.
  • FIG.3A is a set of graphs showing the weighted gene co- expression network analysis (WGCNA), which identified three groups of co-regulated gene modules.
  • WGCNA weighted gene co- expression network analysis
  • FIG.3B is a set of graphs showing the network visualization of protein-protein interactions within modules indicating clusters and network hubs.
  • FIGs.4A-4F are a set of graphs showing the PTSD-positive specific responses to HCort in NGN2-neurons.
  • FIG.4A is a graph showing genes that differ in their response to HCort in PTSD-positive donors compared to PTSD-negative donors, here termed “differential response genes (DRGs),” which were detected in both the 100 nM and 1000 nM dose, indicating PTSD diagnosis-specific responses to HCort.
  • FIG.4B is a set of heat maps showing that significant NGN2-DRGs correctly classify PTSD-positive from PTSD-negative participants using an unsupervised approach.
  • FIG.4C is a set of graphs showing the meta- analysis of Expression LogFC DRGs (differences observed between PTSD-positive and PTSD-negative) was plotted against -log(P value).
  • FIG.4D is a graph showing the gene set enrichment of significant DRGs across psychiatric disorder gene sets (epilepsy, developmental delay, autism spectrum disorder, intellectual disability, schizophrenia, and fragile X messenger ribonucleoprotein (FMRP) targets).
  • FIG.4E is a set of graphs showing the interactive effect of PTSD diagnosis and HCort exposure on gene expression, which are modeled, and three major observed patterns of direction of effect in significantly interactive genes are represented.
  • FIG.4F is a graph showing the logFC of all significantly interactive diagnosis by HCort genes plotted against the P-value of their interaction term, with most significant genes representing those with most significant interactive effects.
  • FIGs.5A-5D are a set of graphs and a schematic, respectively, showing transcription factors driving PTSD hyper-responsivity.
  • FIG.5A is a set of graphs showing PTSD hyper-responsive genes were shown to be enriched for several transcription factor targets.
  • FIG.5B is a schematic of a network visualization of protein-protein interactions amongst identified transcription factors mediating PTSD hyper-responsivity.
  • FIG.5C is a graph showing the overlap of transcription factors (dashed) and their targets (white) identified in the study with significantly differentially expressed genes in other PTSD studies.
  • FIG.5D is a set of Manhattan plots of significantly interactive genes in the study compared to Manhattan plot of imputed expression from PTSD genome-wide association studies (GWAS) indicating spatial orientation of significantly interactive genes.
  • FIG.6 is a set of photomicrographs showing the immunostaining of hiPSC- derived NGN2-neurons. Immunostaining of Hoechst, GFP, MAP2, and NESTIN across all participants.
  • FIGs.7A-7B are a set of graphs showing adjustment of Batch effects.
  • FIG.7A is a set of graphs showing VariancePartition (left), primary component analysis (PCA; middle), and an example gene after batch correction (right). This analysis on uncorrected data indicate a large batch effect.
  • FIG.7B is a set of graphs showing VariancePartition (left), PCA (middle), and an example gene after batch correction (right).
  • FIGs.8A-8B are a set of graphs showing a developmental specificity analysis.
  • FIG.8A is a graph showing pair-wise correlation between NGN2s from the study with cell types across 16 independent studies
  • FIG.8B is a graph showing the PCA analysis of cell types within all 16 studies with the NGN2 neurons.
  • FIGs.9A-9C are a set of graphs showing a neuronal fate specificity analysis.
  • FIG.9A is a heat map showing the expression of hallmark pan-neuronal and neuronal subtype specific genes in NGN2 neurons and PBMCs.
  • FIG.9B is a graph showing the average log2CPM expression of vesicular glutamate transporter 1 (VGLUT1) and vesicular glutamate transporter 2 (VGLUT2) in NGN2 neurons and PBMCs.
  • FIG.9C is a graph showing the expression of GR and mineralocorticoid (MR) in NGN2 neurons and PBMCs.
  • FIGs.10A-10D are a set of graphs showing the comparison of PBMC batches.
  • FIG.10A is a graph showing pair-wise correlations between PBMC batches.
  • FIG.10B is a graph showing the transcriptome-wide correlation between batches at the 50 nM DEX dose.
  • FIG.10C is a graph showing the pair-wise correlations between PBMC batches and Breen, M. S. et al. Translational Psychiatry 9, 201, doi:10.1038/s41398-019-0539-x (2019).
  • FIG. 10D is a graph showing the transcriptome-wide correlation between the study and Breen et al. 2019 at the 50 nM DEX dose.
  • FIGs.11A-11B are a set of graphs showing a comparison of NGN2 batches.
  • FIG. 11A is a set of graphs showing HCort-responsive DEGs across independent batches. Transcriptome-wide concordance is plotted between dosages for each batch.
  • FIG.11B is a graph showing the quantification of cell number with HCort treatment showing no significant cell density between doses.
  • FIGs.12A-12B are a set of graphs showing a weighted gene co-expression network analysis of PBMCs (FIG.12A) and NGN2 neurons (FIG.12B).
  • Hierarchical gene cluster tree, module structure, and gene-treatment are denoted by gray bands. The first band underneath the tree indicates the detected modules and subsequent bands indicate treatment correlation, where lighter gray indicates a strong relationship and darker gray indicates a strong negative relationship.
  • FIGs.13A-13B are a set of graphs showing analysis of unsigned modules.
  • FIG.13B is a set of network visualization of protein- protein interactions within unsigned modules indicating clusters and network hubs.
  • FIGs.14A-14B are a set of graphs showing PTSD-positive-specific responses to DEX in PBMCs.
  • FIG.14A is a graph showing genes that differ in their response to DEX in PTSD-positive donors compared to PTSD-negative donors, here termed “differential response genes (DRGs),” at a false discovery rate (FDR) threshold of 20% (non-significant).
  • FIG.14B is a set of graphs showing unsupervised clustering of nominally significant PTSD DRGs.
  • FIG.15 is a graph (left) and Venn diagram (right), respectively, showing the concordance of PBMC signature with NGN2 signature. Pair-wise correlations between transcriptome-wide signatures of PBMC and NGN2 batches are shown.
  • the term “about” means within 5%, 4%, 3%, 2%, 1%, 0.5%, or 0.05% of a given value or range.
  • “activity” refers to form(s) of a gene or respectively encoded protein which retains a biological activity of the native or naturally-occurring gene or polypeptide, respectively.
  • the term “administering,” or a grammatical derivative thereof, as described herein, refers to the delivery of an agent, e.g., an agent that modifies the glucocorticoid response and/or a psychedelic agent to an individual in need thereof. Any suitable method of administration can be selected by one of skill in the art, in view of this disclosure.
  • an agent is administered via a parenteral route. In some embodiments, an agent is administered via a non-parenteral route.
  • biological sample or “sample” is meant a fluid or solid sample from an individual. Biological samples may include cells (e.g., neurons (e.g., glutamatergic neurons), blood cells (e.g., peripheral blood mononuclear cells), human induced pluripotent cells (hIPSc); nucleic acid, protein, or membrane extracts of cells; or blood or biological fluids including (e.g., plasma, serum, saliva, urine, bile).
  • cells e.g., neurons (e.g., glutamatergic neurons), blood cells (e.g., peripheral blood mononuclear cells), human induced pluripotent cells (hIPSc); nucleic acid, protein, or membrane extracts of cells; or blood or biological fluids including (e.g., plasma, serum, saliva, urine, bile).
  • Solid biological samples include samples taken from feces, the rectum, central nervous system, bone, breast tissue, renal tissue, the uterine cervix, the endometrium, the head or neck, the gallbladder, parotid tissue, the prostate, the brain, the pituitary gland, kidney tissue, muscle, the esophagus, the stomach, the small intestine, the colon, the liver, the spleen, the pancreas, thyroid tissue, heart tissue, lung tissue, the bladder, adipose tissue, lymph node tissue, the uterus, ovarian tissue, adrenal tissue, testis tissue, the tonsils, and the thymus.
  • Fluid biological samples include samples taken from the blood, serum, plasma, pancreatic fluid, CSF, semen, prostate fluid, seminal fluid, urine, saliva, sputum, mucus, bone marrow, lymph, and tears.
  • the biological sample is a blood, plasma, or serum sample.
  • the biological sample includes blood cells (e.g., peripheral blood mononuclear cells), neurons (e.g., glutamatergic neurons), fibroblasts, or cells later derived into hiPSC. Samples may be obtained by standard methods including, e.g., skin puncture and surgical biopsy.
  • a biological sample includes one or more cells, which are processed to produce a test cell.
  • control means any useful reference used to compare the expression and/or activity of the one or more genes of the glucocorticoid response.
  • the baseline can be any sample, standard, standard curve, or level that is used for comparison purposes.
  • the baseline can be a normal reference sample or a reference standard or level.
  • a “suitable control” can be, for example, a control, e.g., a predetermined negative control value such as a “normal control” or a prior sample taken from the same individual; a sample from a normal healthy individual, a sample from an individual not having PTSD; or a sample from an individual that has been treated for PTSD.
  • reference standard or level is meant a value or number derived from a reference sample.
  • a “normal control value” is a pre-determined value indicative of non-disease state, e.g., a value expected in a healthy control individual. Typically, a normal control value is expressed as a range (“between X and Y”), a high threshold (“no higher than X”), or a low threshold (“no lower than X”).
  • An individual having a measured value within the normal control value for a particular assay is typically referred to as “within normal limits” for that assay.
  • a normal reference standard or level can be a value or number derived from a normal individual not having PTSD; or an individual that has been treated for PTSD.
  • the reference sample, standard, or level is matched to the sample individual sample by at least one of the following criteria: age, weight, sex, disease stage, and overall health.
  • a “suitable control” refers to the expression and/or activity levels of one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) genes of the glucocorticoid response against which the expression and/or activity levels of the respective genes are compared, e.g., to make a diagnostic, predictive, prognostic, and/or therapeutic determination.
  • a suitable control includes substantially no test agent administered to an individual.
  • the word “comprise,” or variations such as “comprises” or “comprising,” will be understood to imply the inclusion of a stated word or group of words but not the exclusion of any other word or group of words.
  • the term “detection” includes any means of detecting, including direct and indirect detection.
  • determining the level of a nucleic acid is meant the detection of a nucleic acid (e.g., mRNA) by methods known in the art.
  • Methods to measure mRNA levels generally include, but are not limited to, northern blotting, nuclease protection assays (NPA), in situ hybridization (ISH), reverse transcription-polymerase chain reaction (RT-PCR), and RNA sequencing (RNA-Seq).
  • NPA nuclease protection assays
  • ISH in situ hybridization
  • RT-PCR reverse transcription-polymerase chain reaction
  • RNA-Seq RNA sequencing
  • Methods to measure protein levels generally include, but are not limited to, western blotting, immunoblotting, enzyme-linked immunosorbent assay (ELISA), radioimmunoassay (RIA), immunoprecipitation, immunofluorescence, surface plasmon resonance, chemiluminescence, florescent polarization, phosphorescence, immunohistochemical analyses, matrix-associated laser desorption/ionization time of light (MALDI-TOF) mass spectrometry, liquid chromatography (LC)-mass spectrometry, microcytometry, microscopy, fluorescence activated cell sorting (FACS), and flow cytometry, as well as assays based on a property of a protein including, but not limited to, enzymatic activity or interaction with other protein partners.
  • MALDI-TOF matrix-associated laser desorption/ionization time of light
  • LC liquid chromatography
  • FACS fluorescence activated cell sorting
  • flow cytometry as well assays based on a property of a
  • diagnosis refers to the identification or classification of a genetic, molecular, or pathological state, disease, or condition (e.g., PTSD).
  • diagnosis may refer to identification of an individual with PTSD.
  • effective amount refers to a quantity sufficient to, when administered to an individual, including human, effect beneficial or desired results (e.g., alleviate one or more symptoms of PTSD), which may include clinical results.
  • an effective amount of one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) agents described herein may alleviate one or more symptoms of PTSD as compared to the alleviation of said symptom without administration of the agent of interest.
  • agents described herein e.g., agents that modify the glucocorticoid response or psychedelic agents
  • An “effective amount,” “therapeutically effective amount,” and the like, of an agent, such as a glucocorticoid receptor antagonist or a psychedelic agent also include an amount that results in a beneficial or desired result in an individual as compared to a control.
  • glucocorticoid receptor antagonist is a molecule that decreases, blocks, inhibits, abrogates or interferes with signal transduction resulting from the interaction of a glucocorticoid receptor with either one or more of its binding partners.
  • glucocorticoid receptor antagonist is a molecule that inhibits the binding of a glucocorticoid receptor to its binding partners.
  • glucocorticoid receptor antagonists include small molecule antagonists, polynucleotide antagonists, antibodies and antigen-binding fragments thereof, fusion proteins, oligopeptides, and other molecules that decrease, block, inhibit, abrogate or interfere with signal transduction resulting from the interaction of a glucocorticoid receptor with one or more of its binding partners.
  • identifying an individual or “identifies an individual,” as used herein, refers to using the information or data generated related to the expression and/or activity of the one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) genes of the glucocorticoid response to identify or select an individual as likely to benefit or less likely to benefit from a therapy including one or more psychedelic agents and/or agents that modify the glucocorticoid response, including a glucocorticoid receptor antagonist.
  • the information or data used or generated may by be in any form, written, oral, or electronic.
  • using the information or data generated includes communicating, presenting, reporting, storing, sending, transferring, supplying, transmitting, dispensing, or combinations thereof.
  • communicating, presenting, reporting, storing, sending, transferring, supplying, transmitting, dispensing, or combinations thereof are performed by a computing device, analyzer unit, or combination thereof.
  • the information or data includes a comparison of the expression and/or activity of the one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) genes of the glucocorticoid response to a reference level (e.g., a level from a suitable control).
  • the information or data includes an indication that the expression and/or activity of the one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) genes of the glucocorticoid response are elevated relative to a suitable control (e.g., a control with substantially no test agent).
  • a suitable control e.g., a control with substantially no test agent.
  • the information or data includes an indication that the individual has or does not have an elevated risk for PTSD.
  • the terms “induced pluripotent stem cell,” “iPS cell,” and “iPSC” refer to a pluripotent stem cell that can be derived directly from a differentiated somatic cell.
  • Human iPS cells can be generated by introducing specific sets of reprogramming factors into a non-pluripotent cell (e.g., fibroblasts) that can include, for example, Oct-3/4, Sox family, Klf family, Myc family, Nanog, LIN28, and Glis1 genes.
  • Human iPS cells can also be generated, for example, by the use of miRNAs, small molecules that mimic the actions of transcription factors, or lineage specifiers.
  • Human iPS cells are characterized by their ability to differentiate into any cell of the three vertebrate germ layers, e.g., the endoderm, the ectoderm, or the mesoderm.
  • Human iPS cells are also charactered by their ability to propagate indefinitely under suitable in vitro culture conditions. See, for example, Takahashi and Yamanaka, Cell 126:663 (2006).
  • a cell obtained from a biological sample is dedifferentiated to produce an iPSC.
  • the iPSC is then differentiated to produce a test cell.
  • the iPSC may be differentiated into an induced neuron or an induced peripheral blood mononuclear cell.
  • a cell obtained from a biological sample is processed by automated reprogramming.
  • level is meant a level of a genes expression or activity as compared to a reference.
  • the reference can be any useful reference, as defined herein.
  • a “decreased level” or an “increased level” of a gene is meant a decrease or increase in gene expression or activity, as compared to a reference (e.g., a decrease or an increase by about 5%, about 10%, about 15%, about 20%, about 25%, about 30%, about 35%, about 40%, about 45%, about 50%, about 55%, about 60%, about 65%, about 70%, about 75%, about 80%, about 85%, about 90%, about 95%, about 100%, about 150%, about 200%, about 300%, about 400%, about 500%, or more; a decrease or an increase of more than about 10%, about 15%, about 20%, about 50%, about 75%, about 100%, or about 200%, as compared to a reference; a decrease or an increase by less than about 0.01-fold, about 0.02-fold, about 0.1-fold, about 0.3-fold, about 0.5-fold, about 0.8-fold, or less; or an increase by more than about 1.2-fold, about 1.4-fold, about 1.5
  • level of expression or “expression level” in general are used interchangeably and generally refer to the amount of a biomarker (e.g., one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) genes of the glucocorticoid response) in a biological sample). “Expression” generally refers to the process by which information (e.g., gene-encoded and/or epigenetic information) is converted into the structures present and operating in a cell.
  • expression may refer to transcription into a polynucleotide translation into a polypeptide, or even polynucleotide and/or polypeptide modifications (e.g., posttranslational modification of a polypeptide). Fragments of the transcribed polynucleotide, the translated polypeptide, or polynucleotide and/or polypeptide modifications (e.g., post-translational modifications of a polypeptide) shall also be regarded as expressed whether they originate from a transcript generated by alternative splicing or a degraded transcript, or from post-translational processing of a polypeptide, e.g., by proteolysis.
  • modified refers to an observable difference in the level of a marker, such as the expression and/or activity of one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) gene(s), in a sample (e.g., a biological sample from an individual e.g., an individual suspected of being at risk for PTSD or diagnosed with PTSD), as determined using techniques and methods known in the art for the measurement of the marker.
  • a sample e.g., a biological sample from an individual e.g., an individual suspected of being at risk for PTSD or diagnosed with PTSD
  • a marker level that is changed in an individual may result in a difference of at least 1% (e.g., at least 5%, 10%, 25%, 50%, or 100% or at least 2.5-fold, 3-fold, 4-fold, 5-fold, 6- fold, 7-fold or more) compared to a reference level, e.g., a level from a suitable control.
  • the change is an increased level of the expression or activity of the one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) genes of the glucocorticoid response in a biological sample from an individual.
  • the change is a decreased level of the expression or activity of the one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) genes of the glucocorticoid response in a biological sample from an individual.
  • the one or more e.g., two, three, four, five, ten, fifteen, or twenty or more
  • post-traumatic stress disorder and “PTSD” are defined for the purposes of the present disclosure as a potentially debilitating anxiety disorder triggered by exposure to trauma or a traumatic experience (e.g., a catastrophic or threatening event, e.g., a natural disaster, a wartime situation, an accident, domestic abuse, or a violent crime), such as an interpersonal event associated with actual or threatening death or severe death, such as, for example, physical or sexual assault; exposure to disaster or accidents; combat; or witnessing a traumatic event.
  • trauma or a traumatic experience e.g., a catastrophic or threatening event, e.g., a natural disaster, a wartime situation, an accident, domestic abuse, or a violent crime
  • an interpersonal event associated with actual or threatening death or severe death such as, for example, physical or sexual assault
  • exposure to disaster or accidents combat
  • combat or witnessing a traumatic event.
  • PTSD symptoms There are three main clusters of PTSD symptoms: firstly, those related to re-experiencing the event; secondly, those related to avoidance and arousal; and thirdly, the distress and impairment caused by the first two symptom clusters.
  • the terms “individual,” “subject,” and “patient” are used interchangeably and are meant as a human .
  • An individual to be treated with a pharmaceutical composition described herein may be one who has been diagnosed by a medical practitioner as having PTSD or one at risk for developing PTSD.
  • the terms “treat,” “treatment,” “treating,” and the like are used herein to generally mean obtaining a desired pharmacological and/or physiological effect.
  • treatment covers any treatment of PTSD in a human, and includes: (a) inhibiting the disorder, i.e., preventing the disorder from increasing in severity or scope; (b) relieving the disorder, i.e., causing partial or complete amelioration of the disorder; or (c) preventing relapse of the disorder, i.e., preventing the disorder from returning to an active state following previous successful treatment of symptoms of the disorder or treatment of the disorder.
  • the term “reference level” refers to the level as determined in a suitable control as further described herein, e.g., a level from a prior biological sample taken from the same individual, a biological sample from a healthy individual not having a risk for PTSD, a biological sample from an individual not having one or more symptoms associated with PTSD, or a biological sample from an individual that is diagnosed with PTSD that has been treated for PTSD.
  • Post-Traumatic Stress Disorder [0089] The methods described herein can be used to diagnose, prognose, and treat post- traumatic stress disorder (PTSD). PTSD is a dominant and highly debilitating psychiatric disorder that is notoriously difficult to treat.
  • PTSD can be characterized by intrusive recall, emotional numbness, and insomnia and is associated with functional deficiencies, physical health problems, and mental health comorbidities such as depression, with a six-fold increased risk of suicide.
  • PTSD can result from a catastrophic or threatening event, e.g., a natural disaster, a wartime situation, an accident, domestic abuse, or a violent crime. Symptoms normally develop over the course of three months, but may emerge years after the initial trauma.
  • DSM-IV-TR ® describes post-traumatic stress disorder (PTSD) as developing characteristic symptoms after exposure to extreme traumatic stressors, including direct personal experience of events associated with actual or threatening death or severe death.
  • a person with PTSD can be a witness of an event that includes the death, injury, or threat to physical integrity of another person. Human reactions to events include, but are not limited to, intense fear, lethargy, or fear.
  • a person with PTSD can have a persistent memory of an event, including images, thoughts, or perceptions, or can have a recurring painful dream of the event.
  • Genes of the Glucocorticoid Response [0091] Applicants have discovered that the mRNA expression levels and/or activity of certain genes can be utilized to diagnose, prognose, and treat PTSD, as well as to select individuals who would benefit from a treatment that modifies the glucocorticoid response.
  • genes can also be used for screening compounds that reduce the risk of an individual developing PTSD, reduce the risk of an individual developing one or more symptoms of PTSD, and/or alleviate one or more symptoms of PTSD.
  • biomarkers e.g., one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) genes of the glucocorticoid response (e.g., genes of Table 1 and/or Table 2) that identify individuals at risk for PTSD, suffering from one or more symptoms associated with PTSD, or diagnosed with PTSD.
  • the differential expression and/or activity levels of genes of the glucocorticoid response e.g., genes of PTSD-dependent glucocorticoid response gene signature
  • suitable controls e.g., healthy controls.
  • the methods described herein are useful for treating or diagnosing PTSD.
  • Diagnostic and Classification Methods [0093]
  • the present disclosure features methods to diagnose PTSD. Methods of the present disclosure may be used alone or as a companion diagnostics with other diagnostic or therapeutic approaches, as an early molecular screen to distinguish PTSD.
  • alterations in the expression level and/or activity of one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) genes of the glucocorticoid response exemplified herein (e.g., one or more genes (e.g., genes of Table 1 and/or Table 2) in a biological sample (e.g., blood cell (e.g., peripheral blood mononuclear cell), neuron (e.g., glutamatergic neuron), fibroblast, or hiPSC) from the individual suspected of being at risk for PTSD, suffering from one or more symptoms associated with PTSD, or diagnosed with PTSD as compared to a suitable control (e.g., a normal reference such as a control with substantially no test agent) can be used to diagnose PTSD from diseases or disorders with similar symptoms, thereby allowing individual classification.
  • a biological sample e.g., blood cell (e.g., peripheral blood mononuclear cell), neuron (e.g., glutamatergic
  • the method includes processing a cell obtained from the biological sample to produce a test cell.
  • the method further includes contacting the biological sample or cells with a glucocorticoid (e.g., dexamethasone or hydrocortisone) prior to detecting the expression level and/or activity of one or more genes of the glucocorticoid response.
  • a glucocorticoid e.g., dexamethasone or hydrocortisone
  • the method includes identifying an individual at risk for PTSD or diagnosed with PTSD by obtaining a biological sample from the individual suspected of being at risk for PTSD or diagnosed with PTSD; processing a cell obtained from the biological sample to produce a test cell; contacting the test cell with a glucocorticoid (e.g., dexamethasone or hydrocortisone) to produce a glucocorticoid-induced response; detecting the expression and/or activity of one or more (e.g., (e.g., two, three, four, five, ten, fifteen, or twenty or more) genes of the glucocorticoid-induced response (e.g., one or more genes of Table 1 and/or Table 2); and identifying the individual as at risk for PTSD or diagnosing the individual with PTSD if the expression and/or activity of the one or more genes of the glucocorticoid-induced response are modified relative to a suitable control (e.g.,
  • Methods of the present disclosure can be used to diagnose, prognose, or classify an individual, for example, an increase in the expression and/or activity (e.g., an increase by 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%, 90%, 95%, 100%, 150%, 200%, 300%, 400%, 500%, or more, or an increase by more than 1.2-fold, 1.4-fold, 1.5-fold, 1.8-fold, 2.0-fold, 3.0-fold, 3.5-fold, 4.5-fold, 5.0-fold, 10- fold, 15-fold, 20-fold, 30-fold, 40-fold, 50-fold, 100-fold, 1000-fold, or more, as compared to a reference) of the biomarkers (e.g., one or more genes of Table 1 and/or Table 2) may identify an individual as being at risk for PTSD, suffering from one or more symptoms associated with PTSD, or diagnosed with PTSD and
  • a decrease in the level e.g., a decrease by 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%, 90%, 95%, 100%, 150%, 200%, 300%, 400%, 500%, or more; or a decrease by less than 0.01-fold, 0.02-fold, 0.1-fold, 0.3-fold, 0.5-fold, 0.8-fold, or less, as compared to a reference) of the biomarkers (e.g., one or more genes of Table 1 and/or Table 2) may identify an individual as being at risk for PTSD, suffering from one or more symptoms associated with PTSD, or diagnosed with PTSD and/or may benefit from one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) agents that modify the glucocorticoid response (e.g., a glucocorticoid receptor antagonist) and/or psych
  • the present disclosure further features methods for predicting response to one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) agents that modify the glucocorticoid response (e.g., a glucocorticoid receptor antagonist) in cells from individuals at risk for PTSD, suffering from one or more symptoms associated with PTSD, or diagnosed with PTSD, before or after administration of one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) agents that modify the glucocorticoid response (e.g., a glucocorticoid receptor antagonist).
  • agents that modify the glucocorticoid response e.g., a glucocorticoid receptor antagonist
  • the method includes screening compounds that reduce the risk of an individual developing PTSD, reduce the risk of an individual developing one or more symptoms of PTSD, and/or alleviate one or more symptoms of PTSD in an individual by obtaining a biological sample from the individual at risk for PTSD or suffering from PTSD; processing a cell obtained from the biological sample to produce a test cell; contacting the test cell with a glucocorticoid to produce a glucocorticoid-induced response; contacting the test cell with one or more test agents; detecting the expression and/or activity of one or more genes of the glucocorticoid-induced response (e.g., genes of Table 1 and/or Table 2); and if the one or more test agents modifies the expression and/or activity of one or more genes of the glucocorticoid-induced response (e.g., genes of Table 1 and/or Table 2) compared to a suitable control (e.g., a control with substantially no test agent), identifying the test agent as
  • these methods may be carried out generally as described above or as known in the art with respect to sample collection and assay format.
  • these methods may be carried out by obtaining cells from individuals at risk for PTSD or suffering from PTSD; contacting the cells with one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) test agents; detecting the expression and/or activity of one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) genes of the glucocorticoid response (e.g., genes of Table 1 and/or Table 2) in the sample and/or determining if the test agent reduces the transcriptional profile of the PTSD- dependent glucocorticoid response gene signature; and making a prediction about whether a test agent may reduce the risk of an individual developing PTSD, reduce the risk of an individual developing one or more symptoms of PTSD, and/or alleviate one or more symptoms of PTSD in an individual.
  • one or more e.g., two, three,
  • the method also can be used to predict whether an individual, who has been diagnosed with PTSD, will respond positively to one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) agents that modify the glucocorticoid response (e.g., a glucocorticoid receptor antagonist).
  • the method includes processing a cell obtained from the biological sample to produce a test cell.
  • the method further includes contacting the biological sample or cells with a glucocorticoid (e.g., dexamethasone or hydrocortisone) prior to detecting the expression level and/or activity of the one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) genes of the glucocorticoid response.
  • a glucocorticoid e.g., dexamethasone or hydrocortisone
  • a prediction of a positive response refers to a case where the PTSD symptoms will be alleviated as a result of the one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) agents that modify the glucocorticoid response (e.g., a glucocorticoid receptor antagonist).
  • agents that modify the glucocorticoid response e.g., a glucocorticoid receptor antagonist
  • the transcriptional profile of the PTSD-dependent glucocorticoid response gene signature can be determined relative to a control value.
  • a control value can be a range or average value from a normal individual or a population of normal individuals; a value from a sample from an individual or population of individuals who have undergone one or more agents that modify the glucocorticoid response (e.g., a glucocorticoid receptor antagonist) and have reduced symptoms following therapy; or a value from the same individual before the individual was diagnosed or before the individual started treatment.
  • agents that modify the glucocorticoid response e.g., a glucocorticoid receptor antagonist
  • Methods of the present disclosure can be used to predict whether an individual will be responsive to one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) agents that modify the glucocorticoid response (e.g., a glucocorticoid receptor antagonist), for example, an increase in the level (e.g., an increase by 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%, 90%, 95%, 100%, 150%, 200%, 300%, 400%, 500%, or more, or an increase by more than 1.2-fold, 1.4-fold, 1.5-fold, 1.8- fold, 2.0-fold, 3.0-fold, 3.5-fold, 4.5-fold, 5.0-fold, 10-fold, 15-fold, 20-fold, 30-fold, 40-fold, 50-fold, 100-fold, 1000-fold, or more, as compared to a reference) of
  • a decrease in the level may indicate a positive response to one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) agents that modify the glucocorticoid response (e.g., a glucocorticoid receptor antagonist).
  • Methods of the present disclosure can be used to predict an individual’s response to one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) agents that modify the glucocorticoid response (e.g., a glucocorticoid receptor antagonist) and classify the individual as a “responder,” e.g., an individual with a glucocorticoid response gene signature indicative of a positive response to one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) agents that modify the glucocorticoid response (e.g., a glucocorticoid receptor antagonist), or a “non-responder,” e.g., an individual with a glucocorticoid response gene signature indicative of a poor response to one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) agents that modify the glucocortic
  • the prediction can be made prior to administration of a first agent that modifies the glucocorticoid response (e.g., a glucocorticoid receptor antagonist). Alternatively, the prediction can be made after administration of the first agent that modifies the glucocorticoid response (e.g., a glucocorticoid receptor antagonist), or after administration of a first agent that modifies the glucocorticoid response (e.g., a glucocorticoid receptor antagonist) but before a second agent that modifies the glucocorticoid response.
  • a first agent that modifies the glucocorticoid response e.g., a glucocorticoid receptor antagonist
  • the prediction can be made at any time during the course of one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) agents that modify the glucocorticoid response (e.g., a glucocorticoid receptor antagonist).
  • agents that modify the glucocorticoid response e.g., a glucocorticoid receptor antagonist.
  • the methods described herein can also be used to monitor PTSD status (e.g., progression or regression) during therapy or to optimize dosage of one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) therapeutic agents for an individual.
  • alterations e.g., an increase or a decrease as compared to either the positive reference sample or the level diagnostic for PTSD
  • the levels of the glucocorticoid response gene signature may be measured repeatedly as a method of not only diagnosing disorder, but also monitoring the treatment, prevention, or management of the disorder.
  • individual samples may be compared to reference samples taken early in the diagnosis of the disorder. Such monitoring may be useful, for example, in assessing the efficacy of a particular therapeutic agent (e.g., a glucocorticoid receptor antagonist) in an individual, determining dosages, or in assessing disease progression or status.
  • a particular therapeutic agent e.g., a glucocorticoid receptor antagonist
  • the expression and/or activity of any of the genes described herein, or any combination thereof can be monitored in an individual, and as the expression levels or activities increase or decrease, relative to control, the dosage or administration of therapeutic agents may be adjusted.
  • the methods can also be used to determine the proper dosage (e.g., the therapeutically effective amount) of a therapeutic agent for the individual, the proper type of therapeutic agent, or whether a therapy should be administered.
  • Methods of Treatment [00110] The present disclosure also features a method of treating an individual diagnosed with PTSD including administering to the individual diagnosed with PTSD a therapeutically effective amount of a psychedelic agent and/or a glucocorticoid receptor antagonist.
  • the present disclosure also features a method for treatment of PTSD in an individual by obtaining a biological sample (e.g., blood cell (e.g., peripheral blood mononuclear cell), neuron (e.g., glutamatergic neuron), fibroblast, or hiPSC) from the individual suspected of being at risk for PTSD, suffering from one or more symptoms associated with PTSD, or diagnosed with PTSD; detecting the expression and/or activity of one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) genes of the glucocorticoid response (e.g., one or more genes of Table 1 and/or Table 2); identifying an individual at risk for PTSD or diagnosed with PTSD when the expression and/or activity of the one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) genes of the glucocorticoid response are modified relative to a suitable control (e.g., a control with substantially no test agent);
  • the method includes processing a cell obtained from the biological sample to produce a test cell.
  • the method further includes contacting the biological sample or cells with a glucocorticoid (e.g., dexamethasone or hydrocortisone) prior to detecting the expression level and/or activity of one or more genes of the glucocorticoid response.
  • a glucocorticoid e.g., dexamethasone or hydrocortisone
  • the method includes treating an individual at risk for PTSD, suffering from one or more symptoms associated with PTSD, and/or diagnosed with PTSD by obtaining a biological sample from the individual suspected of being at risk for PTSD, suffering from one or more symptoms associated with PTSD, or diagnosed with PTSD; processing a cell obtained from the biological sample to produce a test cell; contacting the test cell with a glucocorticoid (e.g., dexamethasone or hydrocortisone) to produce a glucocorticoid-induced response; detecting the expression and/or activity of one or more genes of the glucocorticoid-induced response (e.g., one or more genes of Table 1 and/or Table 2); identifying the individual as at risk for PTSD or diagnosing the individual with PTSD when the expression and/or activity of the one or more genes of the glucocorticoid- induced response are modified relative to a suitable control (e.g., a control with substantially no
  • the method includes treating an individual at risk for developing PTSD, diagnosed with PTSD, or experiencing one or more symptoms associated with PTSD by administering to the individual one more psychedelic agents and/or agents that modify the glucocorticoid-induced response (e.g., a glucocorticoid receptor antagonist).
  • the methods of the disclosure also include prophylactic treatments.
  • the disclosure also provides a method of preventing PTSD in an individual at risk for PTSD including a therapeutically effective amount of a psychedelic agent and/or glucocorticoid receptor antagonist.
  • suitable routes of administration of agents include systemic and local routes of administration, including parenteral and non-parenteral routs.
  • suitable routes of administration may include intravenous (IV), intradermal, inhalation, transdermal, topical, transmucosal, intrathecal, and rectal administration.
  • a biological sample e.g., blood cell (e.g., peripheral blood mononuclear cell), neuron (e.g., glutamatergic neuron), fibroblast, or hiPSC
  • samples from an individual may be obtained by biopsy collection, skin punch, venipuncture, resection, bronchoscopy, fine needle aspiration, bronchial brushings, or from sputum, pleural fluid, urine, or blood, such as serum or plasma. Genes or the proteins encoded by such can be detected in these samples. Samples may also include, but are not limited to, neurons and blood cells.
  • the biological sample e.g., blood cell (e.g., peripheral blood mononuclear cell), neuron (e.g., glutamatergic neuron), fibroblast, or hiPSCs
  • biopsy collection which may include a skin punch and/or blood processing.
  • a biological sample such as skin fibroblasts, may be induced into pluripotency.
  • a neuron e.g., glutamatergic neuron
  • a blood cell e.g., peripheral blood mononuclear cell
  • hiPSC human induced pluripotent stem cell
  • a cell obtained from the biological sample may be processed to produce a test cell.
  • processing the cell obtained from the biological sample includes dedifferentiating the cell to produce an iPSC.
  • the iPSC is differentiated to produce a test cell.
  • processing the cell obtained from the biological sample includes automated reprogramming of the cell obtained from the biological sample, such as with an automated system for automating one or more steps including: isolating somatic cells from tissue samples, producing iPSC lines from adult differentiated cells by reprogramming such cells, identifying the pluripotent reprogrammed adult cells among other cells, and expanding the identified reprogrammed cells (see e.g., U.S. Patent Number US 10,968,435 incorporated herein in its entirety).
  • an automated system for automating including: isolating somatic cells from tissue samples, producing iPSC lines from adult differentiated cells by reprogramming such cells, identifying the pluripotent reprogrammed adult cells among other cells, and expanding the identified reprogrammed cells (see e.g., U.S. Patent Number US 10,968,435 incorporated herein in its entirety).
  • the progress of therapy can be monitored by testing such biological samples for the expression and/or activity of one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) genes of the glucocorticoid response.
  • the prediction of outcome or response to therapy can similarly be tested using such biological samples for the transcriptional profile of a PTSD-dependent glucocorticoid response gene signature.
  • the methods herein include detecting the expression and/or activity of one or more genes of the glucocorticoid-induced response (e.g., one or more genes of Table 1 and/or Table 2).
  • Nucleic acid expression and/or activity above can be characterized using a variety of assays known to those skilled in the art.
  • a gene can be characterized by conventional assays, including but not limited to those assays described below, to determine whether it is expressed.
  • Nucleic acid-based datasets suitable for analysis in conjunction with the compositions and methods of the present disclosure include gene expression profiles. Such profiles may include whole transcriptome sequencing data (e.g., RNA-Seq data), panels of mRNAs, noncoding RNAs, or any other nucleic acid sequence that may be expressed from genomic DNA.
  • nucleic acid datasets suitable for use with the compositions and methods of the present disclosure may include expression data collected by imaging-based techniques (e.g., Northern blotting or Southern blotting).
  • Northern blot analysis is a conventional technique well known in the art and is described, for example, in Molecular Cloning, a Laboratory Manual, second edition, 1989, Sambrook, Fritch, Maniatis, Cold Spring Harbor Press, 10 Skyline Drive, Plainview, N.Y.11803-2500.
  • Gene expression profiles to be analyzed in conjunction with evaluating the compositions described herein may include, for example, microarray data or nucleic acid sequencing data produced by a sequencing method known in the art (e.g., Sanger sequencing and next-generation sequencing methods, also known as high-throughput sequencing or deep sequencing).
  • exemplary next generation sequencing technologies include, without limitation, Illumina sequencing, Ion Torrent sequencing, 454 sequencing, SOLiD sequencing, and nanopore sequencing platforms.
  • RNA-Seq is a robust technology for monitoring expression by direct sequencing the RNA molecules in a sample. Briefly, this methodology may involve fragmentation of RNA to an average length of 200 nucleotides, conversion to cDNA by random priming, and synthesis of double-stranded cDNA (e.g., using the Just cDNA DoubleStranded cDNA Synthesis Kit from Agilent Technology).
  • the cDNA is converted into a molecular library for sequencing by addition of sequence adapters for each library (e.g., from Illumina®/Solexa), and the resulting 50-100 nucleotide reads are mapped onto the genome.
  • sequence adapters for each library e.g., from Illumina®/Solexa
  • Gene expression levels may be determined using microarray-based platforms, as microarray technology offers high resolution. Details of various microarray methods can be found in the literature. See, for example, U.S. Pat. No.6,232,068 and Pollack et al., Nat. Genet.23:41-46, 1999, the disclosures of each of which are incorporated herein by reference in their entirety.
  • nucleic acid microarrays Using nucleic acid microarrays, mRNA samples are reverse transcribed and labeled to generate cDNA. The probes can then hybridize to one or more complementary nucleic acids arrayed and immobilized on a solid support.
  • the array can be configured, for example, such that the sequence and position of each member of the array is known. Hybridization of a labeled probe with a particular array member indicates that the sample from which the probe was derived expresses that gene. Expression level may be quantified according to the amount of signal detected from hybridized probe-sample complexes.
  • a typical microarray experiment involves the following steps: 1) preparation of fluorescently labeled target from RNA isolated from the sample, 2) hybridization of the labeled target to the microarray, 3) washing, staining, and scanning of the array, 4) analysis of the scanned image and 5) generation of gene expression profiles.
  • a microarray processor is the Affymetrix GENECHIP® system, which is commercially available and includes arrays fabricated by direct synthesis of oligonucleotides on a glass surface. Other systems may be used as known to one skilled in the art.
  • Amplification-based assays also can be used to measure the expression level of one or more markers (e.g., genes).
  • the nucleic acid sequences of the gene act as a template in an amplification reaction (for example, PCR, such as qPCR).
  • an amplification reaction for example, PCR, such as qPCR.
  • the amount of amplification product is proportional to the amount of template in the original sample.
  • Comparison to appropriate controls provides a measure of the expression level of the gene, corresponding to the specific probe used, according to the principles described herein. Methods of real-time qPCR using TaqMan probes are well known in the art.
  • RNA DNA sequence complementary metal-oxide-semiconductor
  • a detectable marker such as, for example, a radioisotope, fluorescent compound, bioluminescent compound, a chemiluminescent compound, metal chelator, or enzyme.
  • the method includes sequencing RNA.
  • RNA used for sequencing may be derived from a biological sample.
  • RNA is derived from a biological sample (e.g., blood cell (e.g., peripheral blood mononuclear cell), neuron (e.g., glutamatergic neuron), fibroblast, or hiPSC).
  • a biological sample e.g., blood cell (e.g., peripheral blood mononuclear cell), neuron (e.g., glutamatergic neuron), fibroblast, or hiPSC).
  • the method further includes prior to determining the expression level, extracting mRNA from the biological sample (e.g., blood cell (e.g., peripheral blood mononuclear cell), neuron (e.g., glutamatergic neuron), fibroblast, or hiPSC) and reverse transcribing the mRNA into cDNA to obtain a treated biological sample (e.g., blood cell (e.g., peripheral blood mononuclear cell), neuron (e.g., glutamatergic neuron), fibroblast, or hiPSC).
  • mRNA from the biological sample e.g., blood cell (e.g., peripheral blood mononuclear cell), neuron (e.g., glutamatergic neuron), fibroblast, or hiPSC).
  • the mRNA level is determined by an amplification-based assay (e.g., PCR, quantitative PCR, or real-time quantitative PCR), amplification-free assay (e.g., Nanostring), microdroplet based assay, nanopore based assay, or bead based assays (e.g., Luminex, nanoparticles, Nanosphere).
  • amplification-based assay e.g., PCR, quantitative PCR, or real-time quantitative PCR
  • amplification-free assay e.g., Nanostring
  • microdroplet based assay e.g., nanopore based assay
  • bead based assays e.g., Luminex, nanoparticles, Nanosphere.
  • Next generation sequencing methods may also be used with the methods of the present disclosure.
  • Next generation sequencing methods are sequencing technologies that parallelize the sequencing process, producing thousands or millions of sequences concurrently (see, for example, Hall, J. Exp. Biol.209(Pt
  • Next generation sequencing methods include, but are not limited to, polony sequencing, 454 pyrosequencing, Illumina (Solexa) sequencing, SOLiD sequencing, Ion Torrent semiconductor sequencing, DNA nanoball sequencing, Heliscope single molecule sequencing, single molecule real time sequencing, nanopore DNA sequencing (see, for example, Dela Torre et al. Nanotechnology, 23(38):385308, 2012), tunneling currents DNA sequencing (see, for example, Massimiliano, Nanotechnology, 24:342501, 2013), sequencing by hybridization (see, for example, Qin et al. PLoS One, 7(5):e35819, 2012), sequencing with mass spectrometry (see, for example, Edwards et al.
  • the method includes sequencing RNA derived from the biological sample.
  • the method incudes detecting a transcriptional profile of a glucocorticoid-induced response.
  • the method includes assessing epigenetic changes of the one or more genes of the glucocorticoid-induced response (e.g., one or more genes of Table 1 and/or Table 2). Assessing epigenetic changes may be performed by methods known in the art, such as by a chromatin immunoprecipitation assay (ChiP), among others (for a review, see e.g., DeAngelis, J. Tyson, Woodrow J. Farrington, and Trygve O. Tollefsbol.
  • ChiP chromatin immunoprecipitation assay
  • MSPs methylation-sensitive primers
  • DNA sequencing and the use of methylation-sensitive primers are two commonly used techniques to analyze bisulfite-treated DNA for assessing epigenetic changes, as bisulfite modification of DNA enables the analysis of changes in methylation patterns.
  • the differences in bisulfite-based methylation assays arise from the manner in which bisulfite-modified DNA is analyzed.
  • Bisulfite modification converts nonmethylated cytosines to uracils, which are then converted to thymines during DNA amplification by PCR, whereas methylated cytosines are protected from bisulfite modification.
  • Sequencing analysis of bisulfite-modified DNA can be used to reveal the methylation status of specific cytosines, whereas MSPs can be used to quickly assess a large number of CpG islands.
  • single nucleotide primer extension (SnuPE) provide yet another means to analyze bisulfite-modified DNA. The extension of an oligonucleotide to the 5’ end of a CpG site using dideoxycytidines (ddCTP) or dideoxythymidine (ddTTP) followed by real-time PCR, allows for a quantitative assessment of methylation patterns and can be applied to multiple sites simultaneously.
  • MS-SSCA methylation sensitive-single strand conformation analysis
  • MS-SSCA can also be used to obtain an overall picture of DNA methylation.
  • MS-SSCA can be applied across a broad range of samples and can be used to assess the ratio of methylated to nonmethylated DNA.
  • Digestion of genomic DNA with endonucleases that differ in their methylation sensitivities is yet another method for obtaining a rough estimate of the totality of methylation.
  • there are many additional techniques to analyze changes in DNA methylation with the optimal method depending on factors including, but not limited to, the availability of the DNA, total number of targets being analyzed, or the desired specificity.
  • ChIP assay which assesses changes in chromatin structure, comprises one of the most utilized assays in epigenetic research. ChIP assays monitor DNA-protein interactions and allow the chromatin structure surrounding a specific DNA sequence to be analyzed.
  • a conventional ChIP xChIP
  • xChIP formaldehyde
  • nChIP native ChIP
  • nChIP uses micrococcal nuclease digestion to prepare the chromatin for analysis. nChIP allows for modifications of histones, such as methylation or acetylation, to be assessed more accurately than with formaldehyde fixation; however, nChIP does not usually allow for assessment of proteins with a weak binding affinity for DNA. Most ChIP assays are semi-quantitative, although combining either ChIP assay with real-time PCR (Q-ChIP) can achieve a quantitative measurement of the amount of DNA bound to a specific protein. [00138] ChIP assays can also be combined with other epigenetic assays such as DNA bisulfite modification.
  • DNA harvested from a ChIP assay can be treated with bisulfite, while MSPs can be used to assess changes in DNA methylation in a ChIP-MSP.
  • Other useful techniques to assess genome-wide epigenetic changes includes the ChIP-on-Chip assay that utilizes traditional ChIP protocols combined with microarray analysis.
  • ChIP many other assays exist that can be used to assess chromatin structure.
  • DnaseI hypersensitivity assays can be used if a more general determination of the changes chromatin has undergone is desired. DnaseI hypersensitivity sites are usually located in or around promoter regions thereby allowing for mapping of transcriptionally active versus inactive chromatin.
  • RNA is derived from cells.
  • the cell is a neuronal cell (e.g., glutamatergic neuron) or a blood cell (e.g., peripheral blood mononuclear cell).
  • the RNA is isolated from a neuronal cell (e.g., glutamatergic neuron).
  • the RNA is isolated from a blood cell (e.g., peripheral blood mononuclear cell).
  • the RNA is isolated from a human induced pluripotent stem cell (hiPSC).
  • RNA may be isolated from a hiPSC induced glutamatergic neuron.
  • Protein Detection Gene expression can additionally be determined by measuring the concentration or relative abundance of a corresponding protein product encoded by a gene of interest. Protein levels can be assessed using standard detection techniques known in the art. Examples of protein expression analysis that generate data suitable for use with the methods described herein include, without limitation, proteomics approaches, immunohistochemical and/or western blot analysis, immunoprecipitation, molecular binding assays, ELISA, enzyme-linked immunofiltration assay (ELIFA), mass spectrometry, mass spectrometric immunoassay, and biochemical enzymatic activity assays.
  • proteomics approaches immunohistochemical and/or western blot analysis, immunoprecipitation, molecular binding assays, ELISA, enzyme-linked immunofiltration assay (ELIFA), mass spectrometry, mass spectrometric immunoassay, and biochemical enzymatic activity assays.
  • ELIFA enzyme-linked immunofiltration assay
  • proteomics methods can be used to generate large-scale protein expression datasets in multiplex.
  • Proteomics methods may utilize mass spectrometry to detect and quantify polypeptides (e.g., proteins) and/or peptide microarrays utilizing capture reagents (e.g., antibodies) specific to a panel of target proteins to identify and measure expression levels of proteins expressed in a sample (e.g., a single cell sample or a multi-cell population).
  • a sample e.g., a single cell sample or a multi-cell population.
  • the sample may be contacted with an antibody specific for the target protein under conditions sufficient for an antibody-protein complex to form, and detection of the complex.
  • the presence of the biomarker may be detected in a number of ways, such as by Western blotting or ELISA procedures using any of a wide variety of tissues or samples, including plasma or serum.
  • a wide range of immunoassay techniques using such an assay format are available, see, e.g., U.S. Pat. Nos. 4,016,043, 4,424,279, and 4,018,653. These include both single-site and two-site or “sandwich” assays of the noncompetitive types, as well as traditional competitive binding assays. These assays also include direct binding of a labeled antibody to a target biomarker.
  • Another method involves immobilizing the target biomarkers (e.g., on a solid support) and then exposing the immobilized target to a specific antibody, which may or may not contain a label. Depending on the amount of target and the strength of the label’s signal, a bound target may be detectable by direct labeling with the antibody. Alternatively, a second labeled antibody, specific to the first antibody is exposed to the target-first antibody complex to form a target-first antibody-second antibody tertiary complex.
  • the complex is detected by the signal emitted by a label, e.g., an enzyme, a fluorescent label, a chromogenic label, a radionuclide containing molecule (i.e., a radioisotope), or a chemiluminescent molecule.
  • a label e.g., an enzyme, a fluorescent label, a chromogenic label, a radionuclide containing molecule (i.e., a radioisotope), or a chemiluminescent molecule.
  • a label e.g., an enzyme, a fluorescent label, a chromogenic label, a radionuclide containing molecule (i.e., a radioisotope), or a chemiluminescent molecule.
  • Variations on the forward assay include a simultaneous assay, in which both sample and labeled antibody are added simultaneously to a bound antibody.
  • a first antibody having specificity for the biomarker is either covalently or passively bound to a solid surface (e.g., a glass or a polymer surface, such as those with solid supports in the form of tubes, beads, discs, or microplates), and a second antibody is linked to a label that is used to indicate the binding of the second antibody to the molecular marker.
  • a solid surface e.g., a glass or a polymer surface, such as those with solid supports in the form of tubes, beads, discs, or microplates
  • a second antibody is linked to a label that is used to indicate the binding of the second antibody to the molecular marker.
  • IHC and immunofluorescence techniques use an antibody to probe and visualize cellular antigens in situ, generally by chromogenic or fluorescent methods.
  • the tissue sample may be fixed (i.e., preserved) by conventional methodology (see, e.g., “Manual of Histological Staining Method of the Armed Forces Institute of Pathology,” 3 rd edition (1960) Lee G. Luna, HT (ASCP) Editor, The Blakston Division McGraw-Hill Book Company, New York; The Armed Forces Institute of Pathology Advanced Laboratory Methods in Histology and Pathology (1994) Ulreka V. Mikel, Editor, Armed Forces Institute of Pathology, American Registry of Pathology, Washington, D.C.).
  • fixative is determined by the purpose for which the sample is to be histologically stained or otherwise analyzed.
  • neutral buffered formalin, Bouin’s or formaldehyde may be used to fix a sample.
  • the sample is first fixed and is then dehydrated through an ascending series of alcohols, infiltrated and embedded with paraffin or other sectioning media so that the tissue sample may be sectioned. Alternatively, one may section the tissue and fix the sections obtained.
  • the primary and/or secondary antibody used for immunohistochemistry typically will be labeled with a detectable moiety, such as a radioisotope, a colloidal gold particle, a fluorescent label, a chromogenic label, or an enzyme-substrate label.
  • a detectable moiety such as a radioisotope, a colloidal gold particle, a fluorescent label, a chromogenic label, or an enzyme-substrate label.
  • Exemplary peptide microarrays have a substrate-bound plurality of polypeptides, the binding of an oligonucleotide, a peptide, or a protein to each of the plurality of bound polypeptides being separately detectable.
  • the peptide microarray may include a plurality of binders, including but not limited to monoclonal antibodies, polyclonal antibodies, phage display binders, yeast two-hybrid binders, aptamers, which can specifically detect the binding of specific oligonucleotides, peptides, or proteins.
  • binders including but not limited to monoclonal antibodies, polyclonal antibodies, phage display binders, yeast two-hybrid binders, aptamers, which can specifically detect the binding of specific oligonucleotides, peptides, or proteins.
  • Examples of peptide arrays may be found in U.S. Pat. Nos.6,268,210, 5,766,960, and 5,143,854, the disclosures of each of which are incorporated herein by reference in their entirety.
  • the levels of biomarkers may be detected without the use of binding agents.
  • biological sample e.g., blood cell (e.g., peripheral blood mononuclear cell), neuron (e.g., glutamatergic neuron), fibroblast, or hiPSCs
  • biological sample e.g., blood cell (e.g., peripheral blood mononuclear cell), neuron (e.g., glutamatergic neuron), fibroblast, or hiPSCs
  • enzymatic methods e.g., blood cell (e.g., peripheral blood mononuclear cell), neuron (e.g., glutamatergic neuron), fibroblast, or hiPSCs
  • MS mass spectrometry
  • MS electrophoretic methods
  • electrophoretic methods followed by MS e.g., electrophoretic methods followed by MS
  • nuclear magnetic resonance (NMR) methods e.g., nuclear magnetic resonance
  • the biological sample e.g., blood cell (e.g., peripheral blood mononuclear cell), neuron (e.g., glutamatergic neuron), fibroblast, or hiPSC
  • one or more enzymes e.g., trypsin
  • Exemplary chromatographic methods include, but are not limited to, Strong Anion Exchange chromatography using Pulsed Amperometric Detection (SAX-PAD), liquid chromatography (LC), high performance liquid chromatography (HPLC), ultra performance liquid chromatography (U PLC), thin layer chromatography (TLC), amide column chromatography, and combinations thereof.
  • SAX-PAD Pulsed Amperometric Detection
  • LC liquid chromatography
  • HPLC high performance liquid chromatography
  • U PLC ultra performance liquid chromatography
  • TLC thin layer chromatography
  • amide column chromatography and combinations thereof.
  • MS mass spectrometry
  • MALDI-MS matrix assisted laser desorption ionisation mass spectrometry
  • FTMS Fourier transform mass spectrometry
  • IMS-MS ion mobility separation with mass spectrometry
  • ETD-MS electron transfer dissociation
  • MRM Multiple Reaction Monitoring
  • Exemplary electrophoretic methods include, but are not limited to, capillary electrophoresis (CE), CE-MS, gel electrophoresis, agarose gel electrophoresis, acrylamide gel electrophoresis, SDS- polyacrylamide gel electrophoresis (SDS-PAGE) followed by Western blotting using antibodies that recognize specific glycan structures, and combinations thereof.
  • CE capillary electrophoresis
  • CE-MS gel electrophoresis
  • agarose gel electrophoresis agarose gel electrophoresis
  • acrylamide gel electrophoresis acrylamide gel electrophoresis
  • SDS-PAGE SDS- polyacrylamide gel electrophoresis
  • Exemplary nuclear magnetic resonance include, but are not limited to, one-dimensional NMR (1 D-NMR), two-dimensional NMR (2D-NMR), correlation spectroscopy magnetic-angle spinning NMR (COSY-NMR), total correlated spectroscopy NMR (TOCSY-NMR), heteronuclear single-quantum coherence NMR (HSQC-NM R), heteronuclear multiple quantum coherence (HMQC-NMR), rotational nuclear overhauser effect spectroscopy NMR (ROESY-NMR), nuclear overhauser effect spectroscopy (NOESY-NMR), and combinations thereof.
  • NMR nuclear magnetic resonance
  • Mass spectrometry may be used in conjunction with the methods described herein to identify and characterize the gene expression profile of a single cell or multi-cell population. Any method of MS known in the art may be used to determine, detect, and/or measure a peptide or peptides of interest, e.g., LC-MS, ESI-MS, ESI-MS/MS, MALDI-TOF- MS, MALDI-TOF/TOF-MS, tandem MS, and the like.
  • Mass spectrometers generally contain an ion source and optics, mass analyzer, and data processing electronics.
  • Mass analyzers include scanning and ion-beam mass spectrometers, such as time-of-flight (TOF) and quadruple (Q), and trapping mass spectrometers, such as ion trap (IT), Orbitrap, and Fourier transform ion cyclotron resonance (FT-ICR), may be used in the methods described herein. Details of various MS methods can be found in the literature. See, for example, Yates et al., Annu. Rev. Biomed. Eng.11:49-79, 2009, the disclosure of which is incorporated herein by reference in its entirety.
  • TOF time-of-flight
  • Q quadruple
  • trapping mass spectrometers such as ion trap (IT), Orbitrap, and Fourier transform ion cyclotron resonance (FT-ICR)
  • proteins in a sample can be first digested into smaller peptides by chemical (e.g., via cyanogen bromide cleavage) or enzymatic (e.g., trypsin) digestion.
  • Complex peptide samples also benefit from the use of front-end separation techniques, e.g., 2D-PAGE, HPLC, RPLC, and affinity chromatography.
  • the digested, and optionally separated, sample is then ionized using an ion source to create charged molecules for further analysis.
  • Ionization of the sample may be performed, e.g., by electrospray ionization (ESI), atmospheric pressure chemical ionization (APCI), photoionization, electron ionization, fast atom bombardment (FAB)/liquid secondary ionization (LSIMS), matrix assisted laser desorption/ionization (MALDI), field ionization, field desorption, thermospray/plasmaspray ionization, and particle beam ionization. Additional information relating to the choice of ionization method is known to those of skill in the art. [00151] After ionization, digested peptides may then be fragmented to generate signature MS/MS spectra.
  • ESI electrospray ionization
  • APCI atmospheric pressure chemical ionization
  • FAB fast atom bombardment
  • LIMS liquid secondary ionization
  • MALDI matrix assisted laser desorption/ionization
  • field ionization field desorption
  • Tandem MS also known as MS/MS, may be particularly useful for methods described herein allowing for ionization followed by fragmentation of a complex peptide sample, such as a sample obtained from a multi-cell population described herein.
  • Tandem MS involves multiple steps of MS selection, with some form of ion fragmentation occurring in between the stages, which may be accomplished with individual mass spectrometer elements separated in space or using a single mass spectrometer with the MS steps separated in time.
  • spatially separated tandem MS the elements are physically separated and distinct, with a physical connection between the elements to maintain high vacuum.
  • temporally separated tandem MS separation is accomplished with ions trapped in the same place, with multiple separation steps taking place over time.
  • Signature MS/MS spectra may then be compared against a peptide sequence database (e.g., SEQUEST). Post-translational modifications to peptides may also be determined, for exampleby, by searching spectra against a database while allowing for specific peptide modifications.
  • a peptide sequence database e.g., SEQUEST
  • Post-translational modifications to peptides may also be determined, for exampleby, by searching spectra against a database while allowing for specific peptide modifications.
  • Any of the methods herein that rely upon protein measurement can also be adapted for use with the measurement of mRNA levels for the protein.
  • the level of mRNA can be determined using methods known in the art. Methods to measure mRNA levels generally include, but are not limited to, sequencing, northern blotting, RT-PCR, gene array technology, and RNAse protection assays, as described above.
  • the methods herein include contacting a test cell with a glucocorticoid (e.g., a glucocorticoid receptor agonist e.g., beclomethasone, betamethasone, budesonide, cortisone, dexamethasone, hydrocortisone, methylprednisolone, prednisolone, prednisone, and triamcinolone) to produce a glucocorticoid-induced response.
  • a glucocorticoid e.g., a glucocorticoid receptor agonist e.g., beclomethasone, betamethasone, budesonide, cortisone, dexamethasone, hydrocortisone, methylprednisolone, prednisolone, prednisone, and triamcinolone
  • the method includes contacting a test cell with a glucocorticoid receptor agonist.
  • the method includes contacting a test cell with beclomethasone to produce a glucocorticoid-induced response. In some embodiments, the method includes contacting a test cell with betamethasone to produce a glucocorticoid- induced response. In some embodiments, the method includes contacting a test cell with budesonide to produce a glucocorticoid-induced response. In some embodiments, the method includes contacting a test cell with cortisone to produce a glucocorticoid-induced response. In some embodiments, the method includes contacting a test cell with dexamethasone to produce a glucocorticoid-induced response.
  • the method includes contacting a test cell with hydrocortisone to produce a glucocorticoid-induced response. In some embodiments, the method includes contacting a test cell with methylprednisolone to produce a glucocorticoid-induced response. In some embodiments, the method includes contacting a test cell with prednisolone to produce a glucocorticoid-induced response. In some embodiments, the method includes contacting a test cell with prednisone to produce a glucocorticoid-induced response. In some embodiments, the method includes contacting a test cell with triamcinolone to produce a glucocorticoid-induced response.
  • the glucocorticoid is dexamethasone or hydrocortisone.
  • the glucocorticoid is dexamethasone.
  • the glucocorticoid is hydrocortisone.
  • contacting the test cell with a glucocorticoid is performed for a duration of from about 1 hour to about 96 hours (e.g., about 2 hours to about 95 hours, about 3 hours to about 90 hours, about 4 hours to about 80 hours, about 5 hours to about 70 hours, about 10 hours to about 60 hours, about 20 hours to about 50 hours, or about 30 hours to about 40 hours).
  • contacting the test cell with a glucocorticoid is performed for a duration of from about 2 hours to about 95 hours. In some embodiments, contacting the test cell with a glucocorticoid is performed for a duration of from about 3 hours to about 90 hours. In some embodiments, contacting the test cell with a glucocorticoid is performed for a duration of from about 4 hours to about 80 hours. In some embodiments, contacting the test cell with a glucocorticoid is performed for a duration of from about 5 hours to about 70 hours. In some embodiments, contacting the test cell with a glucocorticoid is performed for a duration of from about 10 hours to about 60 hours.
  • contacting the test cell with a glucocorticoid is performed for a duration of from about 20 hours to about 50 hours. In some embodiments, contacting the test cell with a glucocorticoid is performed for a duration of from about 30 hours to about 40 hours.
  • the glucocorticoid has a concentration of from about 1 nM to about 10 ⁇ M (e.g., about 10 nM to about 9 ⁇ M, about 50 nM to about 8 ⁇ M, about 100 nM to about 7 ⁇ M, about 1 ⁇ M to about 6 ⁇ M, about 2 ⁇ M to about 5 ⁇ M, about 3 ⁇ M to about 4 ⁇ M).
  • the glucocorticoid has a concentration of from about 10 nM to about 9 ⁇ M. In some embodiments, the glucocorticoid has a concentration of from about 50 nM to about 8 ⁇ M. In some embodiments, the glucocorticoid has a concentration of from about 100 nM to about 7 ⁇ M. In some embodiments, the glucocorticoid has a concentration of from about 1 ⁇ M to about 6 ⁇ M. In some embodiments, the glucocorticoid has a concentration of from about 2 ⁇ M to about 5 ⁇ M.
  • the glucocorticoid has a concentration of from about 3 ⁇ M to about 4 ⁇ M.
  • Modifiers of the Glucocorticoid Response refers to modifying the formation or function of one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) gene products in the glucocorticoid response pathway.
  • a gene product is functional if it fulfills its normal (wild-type) functions. Disruption of the gene product prevents expression or function.
  • the gene product in the glucocorticoid response pathway may be inhibited by, e.g., removal of at least a portion of the gene from a genome of the individual, alternation of the gene to prevent expression of a gene product encoded by the gene, an interfering RNA, antagonism, or expression of a dominant negative factor by an exogenous gene.
  • This inhibition can be achieved, for example by using nucleic acid molecules, siRNA, shRNA, miRNA, antisense oligonucleotides, nucleases, meganucleases, transcription activator-like effector nucleases, zinc-finger nucleases, a CRISPR associated protein, or an antagonist.
  • Exemplary materials and methods for genetically modifying cells so as to disrupt the expression of one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) gene are detailed in US 8,518,701; US 9,499,808; and US 2021/0222143, the disclosures of which are incorporated herein by reference in their entirety.
  • the modifier of the glucocorticoid response is an agent that modifies the activity and/or expression of the glucocorticoid receptor, such as, but not limited to a glucocorticoid receptor antagonist.
  • the glucocorticoid response is inhibited by a glucocorticoid receptor antagonist.
  • a glucocorticoid receptor antagonist Exemplary, non-limiting, antagonists for inhibiting the glucocorticoid response are known in the art.
  • provided methods include contacting a test cell with one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) agents that modify the glucocorticoid response (e.g., a glucocorticoid receptor antagonist).
  • contacting a test cell with one or more test agents may be performed for a duration of from about 1 hour to about 96 hours (e.g., about 2 hours to about 95 hours, about 3 hours to about 90 hours, about 4 hours to about 80 hours, about 5 hours to about 70 hours, about 10 hours to about 60 hours, about 20 hours to about 50 hours, or about 30 hours to about 40 hours).
  • contacting the test cell with one or more agents that modify the glucocorticoid response is performed for a duration of from about 2 hours to about 95 hours.
  • contacting the test cell with one or more agents that modify the glucocorticoid response is performed for a duration of from about 3 hours to about 90 hours.
  • contacting the test cell with one or more agents that modify the glucocorticoid response is performed for a duration of from about 4 hours to about 80 hours. In some embodiments, contacting the test cell with one or more agents that modify the glucocorticoid response is performed for a duration of from about 5 hours to about 70 hours. In some embodiments, contacting the test cell with one or more agents that modify the glucocorticoid response is performed for a duration of from about 10 hours to about 60 hours. In some embodiments, contacting the test cell with one or more agents that modify the glucocorticoid response is performed for a duration of from about 20 hours to about 50 hours.
  • contacting the test cell with one or more agents that modify the glucocorticoid response is performed for a duration of from about 30 hours to about 40 hours.
  • the agent that modifies the glucocorticoid response has a concentration of from about 1 nM to about 10 ⁇ M (e.g., about 10 nM to about 9 ⁇ M, about 50 nM to about 8 ⁇ M, about 100 nM to about 7 ⁇ M, about 1 ⁇ M to about 6 ⁇ M, about 2 ⁇ M to about 5 ⁇ M, about 3 ⁇ M to about 4 ⁇ M).
  • the agent that modifies the glucocorticoid response has a concentration of from about 10 nM to about 9 ⁇ M. In some embodiments, the agent that modifies the glucocorticoid response has a concentration of from about 50 nM to about 8 ⁇ M. In some embodiments, the agent that modifies the glucocorticoid response has a concentration of from about 100 nM to about 7 ⁇ M. In some embodiments, the agent that modifies the glucocorticoid response has a concentration of from about 1 ⁇ M to about 6 ⁇ M.
  • the agent that modifies the glucocorticoid response has a concentration of from about 2 ⁇ M to about 5 ⁇ M. In some embodiments, the agent that modifies the glucocorticoid response has a concentration of from about 3 ⁇ M to about 4 ⁇ M. [00160] In some embodiments, an agent that modifies the glucocorticoid response is administered via a parenteral or a non-parenteral route. For example, in some embodiments, an agent that modifies the glucocorticoid response is administered via a parenteral route. In some embodiments, an agent that modifies the glucocorticoid response is administered via a non-parenteral route.
  • compositions and methods of the present disclosure may make use of glucocorticoid receptor antagonists.
  • Glucocorticoid receptor (GR) antagonists bind to the receptor and prevent glucocorticoid receptor agonists from binding and eliciting GR mediated events, including transcription.
  • the glucocorticoid receptor antagonist is a steroidal glucocorticoid receptor antagonist, such as, for example, mifepristone, monodemethylated mifepristone, didemethylated mifepristone, 17- ⁇ -[3'-hydroxy-propynyl] mifepristone, ulipristal, CDB-3877, CDB-3963, CDB-3236, CDB-4183, cortexolone, dexamethasone- oxetanone, 19-nordeoxycorticosterone, 19-norprogesterone, cortisol-21-mesylate; dexamethasone-21-mesylate, 11(-(4-dimethylaminoethoxyphenyl)-17(-propynyl-17(- hydroxy-4,9-estradien-3one, and 17(-hydroxy-17(-19-(4-methylphenyl)androsta-4,9(11)-
  • mifepristone
  • the glucocorticoid receptor antagonist is mifepristone. In some embodiments, the glucocorticoid receptor antagonist is monodemethylated mifepristone. In some embodiments, the glucocorticoid receptor antagonist is didemethylated mifepristone. In some embodiments, the glucocorticoid receptor antagonist is 17- ⁇ -[3'-hydroxy-propynyl] mifepristone. In some embodiments, the glucocorticoid receptor antagonist is ulipristal. In some embodiments, the glucocorticoid receptor antagonist is CDB-3877. In some embodiments, the glucocorticoid receptor antagonist is CDB-3963.
  • the glucocorticoid receptor antagonist is CDB-3236. In some embodiments, the glucocorticoid receptor antagonist is CDB-4183. In some embodiments, the glucocorticoid receptor antagonist is cortexolone. In some embodiments, the glucocorticoid receptor antagonist is dexamethasone-oxetanone. In some embodiments, the glucocorticoid receptor antagonist is 19-nordeoxycorticosterone. In some embodiments, the glucocorticoid receptor antagonist is 19-norprogesterone. In some embodiments, the glucocorticoid receptor antagonist is cortisol-21-mesylate.
  • the glucocorticoid receptor antagonist is dexamethasone-21-mesylate. In some embodiments, the glucocorticoid receptor antagonist is 11(-(4-dimethylaminoethoxyphenyl)- 17(-propynyl-17(-hydroxy-4,9-estradien-3one. In some embodiments, the glucocorticoid receptor antagonist is 17(-hydroxy-17(-19-(4-methylphenyl)androsta-4,9(11)-dien-3-one.
  • the glucocorticoid receptor antagonist is a non-steroidal glucocorticoid receptor antagonist, such as, for example, N-(2-[4,4',441 - trichlorotrityl]oxyethyl)morpholine; 1-(2[4,4',4"-trichlorotrityl]oxyethyl)-4-(2- hydroxyethyl)piperazine dimaleate; N-([4,4',4"]-trichlorotrityl)imidazole; 9-(3-mercapto- 1,2,4-triazolyl)-9-phenyl-2,7-difluorofluorenone; 1-(2-chlorotrityl)-3,5-dimethylpyrazole; 4- (morpholinomethyl)-A-(2-pyridyl)benzhydrol; 5-(5-methoxy-2-(N-methylcarbamoyl)- phenyl)di
  • the glucocorticoid receptor antagonist is N-(2- [4,4',441 - trichlorotrityl]oxyethyl)morpholine.
  • the glucocorticoid receptor antagonist is 1-(2[4,4',4"-trichlorotrityl]oxyethyl)-4-(2-hydroxyethyl)piperazine dimaleate.
  • the glucocorticoid receptor antagonist is N-([4,4',4"]- trichlorotrityl)imidazole.
  • the glucocorticoid receptor antagonist is 9- (3-mercapto- 1,2,4-triazolyl)-9-phenyl-2,7-difluorofluorenone.
  • the glucocorticoid receptor antagonist is 1-(2-chlorotrityl)-3,5-dimethylpyrazole.
  • the glucocorticoid receptor antagonist is 4-(morpholinomethyl)-A-(2- pyridyl)benzhydrol.
  • the glucocorticoid receptor antagonist is 5-(5- methoxy-2-(N-methylcarbamoyl)-phenyl)dibenzosuberol.
  • the glucocorticoid receptor antagonist is N-(2-chlorotrityl)-L-prolinol acetate. In some embodiments, the glucocorticoid receptor antagonist is 1-(2-chlorotrityl)-1,2,4-triazole. In some embodiments, the glucocorticoid receptor antagonist is 1,S-bis(4,4', 4"-trichlorotrityl)- 1,2,4-triazole-3-thiol. In some embodiments, the glucocorticoid receptor antagonist is 4.alpha.(S)-Benzyl-2(R)-chloroethynyl-1,2,3,4,4.alpha.,9,10,10.alpha.
  • the glucocorticoid receptor antagonist is (R)-octahydro-phenanthrene-2,7-diol (CP 394531) , 4.alpha. In some embodiments, the glucocorticoid receptor antagonist is (S)-Benzyl-2(R)- prop-1-ynyl-1,2,3,4,4.alpha.,9,10,10.alpha. In some embodiments, the glucocorticoid receptor antagonist is (R)-octahydro-phenanthrene-2,7-diol (CP-409069).
  • the glucocorticoid receptor antagonist is trans-(1 R,2R)-3,4-dichloro-N-methyl-N-[2-1 pyrrolidinyl)cyclohexyl]benzeneacetamide.
  • the glucocorticoid receptor antagonist is bremazocine.
  • the glucocorticoid receptor antagonist is ethylketocyclazocine.
  • the glucocorticoid receptor antagonist is naloxone.
  • Psychedelic Agents [00164] The compositions and methods of the present disclosure may make use of psychedelic agents.
  • Psychedelics are a subclass of hallucinogenic drugs that trigger non- ordinary mental states (known as psychedelic experiences) and/or an apparent expansion of consciousness. Sometimes, psychedelic agents are called classic hallucinogens, serotonergic hallucinogens, or serotonergic psychedelics. Many psychedelic drugs fall into one of the three families of chemical compounds: tryptamines, phenethylamines, and lysergamides.
  • psychedelic agents of the disclosure include indoles (e.g., tryptamines (e.g., psilocin, psilocybin, bufotenin, baeocystin, aeruginascin, 5-MeO-DMT, N,N-dimethyltryptamine,5-bromo-DMT, N-methyl-N-ethyltryptamine, N-methyl-N- isopropyltryptamine, N-methyl-N-propyltryptamine, N,N-diethyltryptamine, N-ethyl-N- isopropyltryptamine, N-methyl-N-butyltryptamine, N-propyl-N-isopropyltryptamine, N,N- dipropyltryptamine, N,N-diisopropyltryptamine, N,N-diallyltrypt
  • tryptamines
  • Example 1 Modeling gene x environment interactions: PTSD-specific glucocorticoid- induced transcriptomics in human neurons
  • hiPSC human induced pluripotent stem cell
  • PBMCs peripheral blood mononuclear cells
  • glucocorticoid hypersensitivity is demonstrated for PTSD neurons, and specific genes are identified that contribute to the PTSD-dependent glucocorticoid response.
  • the findings show that induced neurons represent a new platform in which glucocorticoid response signatures can be used to test the molecular mechanisms underlying PTSD, identify biomarkers of stress response in PTSD, and conduct drug- screening to identify novel therapeutics to prevent or ameliorate PTSD-related clinical phenotypes.
  • Eligibility criteria and thresholds were based on CAPS for DSM-IV; PTSD-positive had a current CAPS-IV total score above 40 (frequency + intensity), whereas PTSD-negative participants were combat-exposed veterans had a total score below 40.
  • DSM-IV criteria for PTSD were used for inclusion, note that PTSD+ participants also met criteria for PTSD based on DSM-5.
  • Diagnostic and clinical exclusions included: i) presence of moderate or severe substance use disorder within the past 6 months, ii) lifetime history of primary psychotic or Bipolar I disorders, iii) self-reported history of moderate or severe traumatic brain injury, iv) neurological disorder or major systemic illness, v) treatment with systemic steroids, and for PTSD-negative only, vi) current or recurrent major depressive disorder.
  • Psychotropic medication was permitted, but dosage stabilization for at least two weeks was required. ⁇ 20% of individuals across both groups are currently treated with psychiatric medications.
  • Current oral steroid treatment was an exclusion based on the impact of systemic steroids on the hypothalamic-pituitary-adrenal axis (HPA) axis.
  • HPA hypothalamic-pituitary-adrenal axis
  • Biological samples blood and fibroblast were collected from eligible participants at the James J. Peters VAMC. Blood processing occurred at the JJP VAMC and fibroblasts were transferred to New York Stem Cell Foundation (NYSCF). All human induced pluripotent stem cells (hiPSCs) were reprogrammed together in randomized batches as fibroblast biopsies were obtained over time. Skin fibroblasts of PTSD and non-PTSD participants were collected via skin punch biopsy taken from the upper buttocks.
  • hiPSCs human induced pluripotent stem cells
  • Biopsy Collection Media (Cascade Biologics Medium 106 (Life Technologies, M-106-500), 1X Antibiotic-Antimycotic (Life Technologies, 15240-062), LSGS (Life Technologies, S-003- 10)) and stored at 4 °C for a maximum of 24 hours.
  • Biopsies were dissected into ⁇ 1 mm 3 pieces and plated in Biopsy Plating Media (Knockout-DMEM (Life Technologies, 10829- 018), 10% FBS (Life Technologies, 100821-147), 2 mM GlutaMAX (Life Technologies, 35050-061), 0.1 mM MEM Non-Essential Amino Acids (Life Technologies, 11140-050), 1X Antibiotic-Antimycotic (Life Technologies, 15240-062), 0.1 mM 2-Mercaptoethanol (Life Technologies, 21985-023)). Upon the outgrowth of fibroblasts, samples were entered into an automated pipeline producing vials of cells for both hiPSC reprogramming and backup stock.
  • a cell pellet was collected, with DNA isolated using an EPMotion and the ReliaPrepTM 96 gDNA Miniprep HT System (A2671, Promega). This DNA was used to confirm sample identity throughout the reprogramming process.
  • Fibroblasts were reprogrammed using modified mRNA (Reprocell, 000076) and enriched using anti-fibroblast meads (Miltentyi Biotec, 130-050-601) in automated procedures. Reprogrammed hiPSCs were then expanded using PSC Feeder Free Media (Thermo Fisher Scientific: A14577SA) and grown on Cultrex coated plates (R&D Systems, 3434-010-02).
  • PBMCs peripheral blood mononuclear cells
  • DEX dexamethasone
  • EDTA ethylenediaminetetraacetic acid
  • VWR West Chester, Pennsylvania
  • PBMCs were isolated by density gradient centrifugation using Ficoll-Paque (GE Healthcare) and washed twice in HBSS.
  • Mononuclear cells were then counted manually using a Cellometer Disposable Counting Chambers (Nexcelom Bioscience LLC. Lawrence, MA). The cells were re- suspended in complete RPMI, containing RPMI-1640 (Gibco), 10% fetal bovine serum, 50 U/mL penicillin-streptomycin mixture (Gibco) at a density of 1.75-2.00 x 10 6 cells/mL of the medium. PBMCs were prepared at 2.5 x 10 6 cells/mL in complete RPMI for DEX treatment experiments.
  • RNA isolation Following incubation at 37 °C, 5% (vol/vol) CO 2 for 72 hours, the plates were centrifuged at 900 ⁇ g for 15 min at 4 °C and supernatant was collected and pooled from each DEX concentration well. The cell pellet on the bottom of each well was re-suspended in TRIzol reagent. Cell lysates for each DEX dose were pooled, aliquoted and stored at -80 °C until RNA isolation.
  • hiPSCs were single cell passaged after a 20-minute dissociation with Accutase (STEMCELL Technologies) at 37 °C and 5% CO 2 .1 million cells per well were plated in 12- well Cultrex coated (R&D Systems, 3434-010-02) tissue culture plates (Corning Costar) in PSC Feeder Free Media (Thermo Fisher Scientific: A14577SA) with 1 ⁇ M thiazovivin (Sigma-Aldrich: SML1045).
  • NIM Neural Induction Medium
  • NCM Neural Coating Medium
  • Neural Medium including Brainphys medium with 1X B27+Vit.A, 1 ⁇ M thiazovivin, 5 ⁇ g/mL puromycin, 250 ⁇ M dbcAMP, 40 ng/mL BDNF, 40 ng/mL GDNF, 200 ⁇ M ascorbic acid and 1 ⁇ g/mL natural mouse laminin.24 hours after seeding medium was exchanged to Neural Selection Medium (NSM) including Brainphys medium with 1X B27+Vit.A, 250 ⁇ M dbcAMP, 40 ng/mL BDNF, 40 ng/mL GDNF, 200 ⁇ M ascorbic acid, 1 ⁇ M
  • HBSS Thermo Fisher Scientific
  • mouse anti-Nestin 1:3000 Millipore: 09-0024
  • chicken anti-MAP21:3000 Abcam: 09-0006
  • Normal Goat Serum Jackson ImmunoResearch
  • Triton x-100 Thermo Fisher Scientific
  • Primary antibodies were counterstained with Goat anti-Mouse Alexa Fluor 555 and Goat anti-chicken Alexa Fluor 647 and 10 ⁇ g/mL Hoechst for 1 hour at room temp. Cells were washed three times with HBSS.
  • Batch 1 Nine fields (40x magnification) were imaged per well (one well per condition per line) using the Perkin Elmer Opera Phenix microscope.
  • Batch 2 Nine fields (20x magnification) were imaged per well (two wells per hiPSC line) using the ArrayScan automated microscope (Thermo Fisher Scientific). Inter-well variability in neuronal identity and maturity was assessed using automated image analyses: NESTIN- positive neural progenitor cells (NPCs) were demarcated from microtubule associated protein 2 (MAP2)-positive post-mitotic neurons (FIG.6). Variation between batches may reflect discrepancies in imaging methods, rather than biological differences in neuronal morphology or maturity.
  • Glucocorticoid treatment [00174] Preliminary studies were conducted to identify optimal culture and glucocorticoid stimulation conditions. These pilot studies sought to evaluate the transcriptional effects of hydrocortisone (HCort) and DEX on NGN2 neurons, and optimize the length of glucocorticoid treatment and concentrations. Neither qPCR for six glucocorticoid regulatory genes (covering ten concentrations of DEX) nor RNAseq (covering three concentrations of DEX) revealed significant gene expression differences following 72 hours of exposure, consistent with minimal upregulation of FKBP5 mRNA expression following DEX treatment of hiPSC neurons. This is consistent DEX treatment of primary cultures being significantly less responsive than astrocytes.
  • HCort treatment for neuronal glucocorticoid exposure. Serum measurements of cortisol in patients with and without PTSD have been found to average around 492.52 nM, intermediate between the 100 and 1000 nM doses.
  • HCort treatment medium was prepared by first dissolving HCort (Sigma-Aldrich: H0888) in ethanol to make a 2.8 mM stock. HCort ethanol stock was then diluted to 0.2 mM in HBSS.
  • DEX treatment medium was prepared by dissolving DEX (Sigma-Aldrich, D1156) in HBSS Solution (ThermoFisher, 14175). The final treatment medium was prepared by diluting HCort or DEX stocks into NMM/RPMI, prior to applying to cells by fully exchanging medium. Neurons were treated with HCort for 24 hours (baseline, 100 nM, 1000 nM, 2500 nM), PBMCs with DEX for 72 hours (baseline, 2.5 nM, 5 nM, 50 nM).
  • Baseline media conditions are estimated to contain 58 nM of corticosterone from neuronal supplement B27 (Thermo Fisher), which may predispose neurons to a higher effective concentration for glucocorticoid stimulation, and may bias responsive genes towards those that respond to severe stressors, rather than homeostatic or regulatory changes, such as circadian rhythms.
  • RNA extraction and quality control [00175] For NGN2-neurons, RNA was harvested with RNeasy plus micro kit (Qiagen). For PBMCs, RNA was extracted from TRIzol-lysed PBMCs using the miRNAeasy Mini Kit (Qiagen).
  • RNA quantity was measured on the Nano Drop 2000 Spectrophotometer (Thermo Scientific) and the quality and integrity measured with the Agilent 2100 Bioanalyzer (Agilent, Santa Clara, CA, USA). All RNA integrity numbers (RINs) were high in the current study: NGN2-neurons (8.8 ⁇ 0.53) and PBMCs (7.5 ⁇ 0.95).
  • RINs RNA integrity numbers
  • NGN2-neurons 8.8 ⁇ 0.53
  • PBMCs 7.5 ⁇ 0.95.
  • RNA-sequencing data generation [00176] A low-input RNA-sequencing protocol was applied for the generation of RNA- sequencing data from NGN2-neurons.
  • RNA-sequencing library preparation using the SMART-Seq v4 Kit (SSv4; Takara) and sequenced using a paired-end 150 bp configuration with 30 M supporting reads per sample.
  • Ribo-zero rRNA deleted RNAs were subjected to RNA-sequencing library preparation using the Illumina TruSeq Stranded Total RNA kit (Illumina) and sequenced using a paired-end 150 bp configuration with 20 M supporting reads per sample.
  • RNA-sequencing data pre-processing All RNA-sequencing FASTQ files underwent matching analytical procedures, as described previously. In brief, resulting short reads with Illumina adapters were trimmed and low-quality reads were filtered using TrimGalore (see Bolger, A. M., Lohse, M. & Usadel, B. Bioinformatics 30, 2114-2120, doi:10.1093/bioinformatics/btu170 (2014);--illumina option). All high-quality reads were then processed for alignment using the hg38 reference and the ultrafast universal RNA-seq aligner STAR with default parameters (see Dobin, A. et al.
  • Raw count data was subjected to non-specific filtering to remove low-expressed genes that did not meet the requirement of a minimum of two counts per million (cpm) in at least ⁇ 40% of samples.
  • This filtering threshold was applied to NGN2- neurons and PBMCs separately. All expression values were converted to log 2 RPKM and subjected to unsupervised principal component analysis (PCA) to identify and remove outlier samples that lay outside 95% confidence intervals from the grand averages. This identified two outlier samples in NGN2-neuron batch 1 and one outlier sample in batch 2 that were excluded from the analysis.
  • PCA principal component analysis
  • RNA-seq datasets from existing postmortem brain tissue and hiPSC models were integrated to validate the developmental specificity of the samples using a previously described approach (see Hoffman, G. E. et al. Nat Commun 8, 2225, doi:10.1038/s41467- 017-02330-5 (2017)).
  • a total of 16 independent studies were collected covering 2716 independent samples and 12,140 genes. These samples cover a broad range of hiPSCs, NPCs, mature neurons, prenatal and postnatal brain tissues. All expression values were converted to log 2 RPKM and collectively normalized using quantile normalization using the limma R package.
  • FIG.7A-7B A significant batch effect was observed (FIG.7A-7B), which was corrected for by constructing a linear model of batch and extracting the residuals.
  • differential gene expression analyses were conducted using a moderated t test from the R package limma (see Ritchie, M. E. et al. Nucleic Acids Res 43, e47, doi:10.1093/nar/gkv007 (2015)).
  • Models examining the HCort-dependent, PTSD-independent effect included adjustment for the possible confounding influence of PSTD diagnosis and RIN, while PTSD-dependent models (FIG.s 4-5) included diagnosis as a main outcome. Due to the repeated measures study design, where individuals are represented by multiple independent technical replicates, the duplicate.
  • NGN2-neurons were seeded as 1.5 x 10 4 cells/well in a 96-well plate coated with 4x Matrigel at day 5.
  • NGN2-neurons were treated with HCort for 24 hours (0 nM (vehicle), 100 nM, 1000 nM, 2500 nM) as in prior experiments.
  • cultures were fixed using 4% formaldehyde/sucrose in PBS with Ca 2+ and Mg 2+ for 10 minutes at room temperature (RT). Fixed cultures were washed twice in PBS and permeabilized and blocked using 0.1% Triton/2% Normal Donkey Serum (NDS) in PBS for two hours.
  • NDS Normal Donkey Serum
  • Cultures were then incubated with primary antibody solution (1:1000 MAP2 anti chicken (Abcam, ab5392) in PBS with 2% NDS) overnight at 4 degrees. Cultures were then washed 3 times with PBS and incubated with secondary antibody solution (1:500 donkey anti chicken Alexa 647 (Life technologies, A10042) in PBS with 2% NDS) for 1 hour at RT. Cultures were washed a further 3 times with PBS with the second wash containing 1 ⁇ g/mL DAPI.
  • primary antibody solution 1:1000 MAP2 anti chicken (Abcam, ab5392) in PBS with 2% NDS
  • secondary antibody solution (1:500 donkey anti chicken Alexa 647 (Life technologies, A10042) in PBS with 2% NDS) for 1 hour at RT. Cultures were washed a further 3 times with PBS with the second wash containing 1 ⁇ g/mL DAPI.
  • Weighted gene co-expression network analysis and functional annotation [00181] Signed co-expression networks were built for PBMCs and NGN2-neurons using weighted gene co-expression network analysis (WGCNA; see Zhang, B. & Horvath, S. A. Stat Appl Genet Mol Biol 4, Article17 (2005)). To construct a global weighted network for each cell type, a total of 20,101 and 16,146 post quality control (QC) genes were used in PBMCs and NGN2-neurons respectively.
  • WGCNA weighted gene co-expression network analysis
  • Each module was enriched for Gene Ontology (GO) biological processes, molecular factors, cellular components and molecular pathways using ToppGene. All genes passing non-specific filtering in the current data set were used as a genomic background. Only gene sets that passed a multiple test adjustment using the Benjamini Hochberg procedure (Adj. P ⁇ 0.05) were deemed significant. ME values were correlated with dosage by Pearson correlation. Protein-protein association networks were constructed using STRING. For protein-protein association analysis of WGCNA modules, genes with high module membership (MM>0.8) were selected for STRING analysis and computation of PPI enrichment p-values. Networks were visualized by cytoscape.
  • Gene co-expression module preservation analysis [00182] Gene co-expression modules that were disrupted or created in response to glucocorticoids across NGN2-neurons and PBMCs, a permutation-based preservation statistic (Z summary ) 2 with 200 random permutations was used to measure the (dis)similarity in correlation patterns for the genes within these gene sets: Z summary > 10 indicates strong evidence of preservation, 2 ⁇ Z summary ⁇ 10 indicates weak-to-moderate evidence of preservation and Z summary ⁇ 2 indicates minimal-to-no evidence of preservation. For this analysis, we specifically focused on dynamically regulated, glucocorticoid responsive functional modules that were identified in either NGN2-neurons or PBMCs, respectively.
  • FIGs.1E and 2E Concordance of observed PBMC and neuron transcriptomic signatures to glucocorticoid stimulation (FIGs.1E and 2E), or between PTSD cases and controls (FIG. 4D) and previously reported psychiatric disorder and neurodevelopmental expression patterns was determined.
  • Psychiatric disorder enrichment was determined using genetic and genomic disease-related gene lists for PTSD, major depressive disorder, schizophrenia, bipolar disorder, autism spectrum disorder, alcohol use disorder, and inflammatory bowel disease.
  • Glucocorticoid dysregulation of neurodevelopmental genes was examined using risk genes associated with epilepsy, developmental delay, autism spectrum disorder, intellectual disability, schizophrenia, and FMRP target genes.
  • RNA-sequencing was generated from cultured PBMCs treated for 72-hours with three concentrations of DEX (2.5 nM, 5 nM, 50 nM), and analyzed relative to baseline samples. To identify reliable markers of glucocorticoid activation independent of PTSD, diagnosis as well as other confounds were adjusted for (see Methods). Incubation with increasing concentrations of DEX (2.5 nM, 5 nM, 50 nM, respectively) identified 6,153; 8,114; and 15,128 differentially expressed genes (DEGs) in batch A, and 4,880; 13,297; and 18,856 DEGs in batch B, respectively (q-value ⁇ 0.05) (FIG.1B).
  • DEX 2,153; 8,114; and 15,128 differentially expressed genes
  • glucocorticoid treatment of PBMCs alone is insufficient to recapitulate PTSD signatures.
  • glucocorticoid treatment of PBMCs (batch A) was highly correlated to the DEX-induced gene responses previously reported (batch B) (FIG.10A), the larger meta-analysis did not identify PTSD-specific DEX-induced differential response genes (PBMC-DRGs) at an FDR-corrected threshold (FIGs.14A-14B and FIG.15).
  • NGN2-neurons Hydrocortisone-stimulated transcriptional responses in hiPSC-neurons
  • We and others have demonstrated that NGN2-neurons are > 95% pure glutamatergic neurons, robustly express glutamatergic genes, release neurotransmitters, produce spontaneous synaptic activity, and recapitulate the impact of psychiatric disease associated genes.
  • Glucocorticoid and mineralocorticoid receptor (MR) expression was additionally confirmed for each cell type (FIG.9C), with PBMCs demonstrating higher expression of both receptors, consistent with heightened glucocorticoid transcriptional response in PBMCs.
  • Immunostaining of a parallel well demonstrated consistent cell number (4,307 +/- 1,313) and neuronal marker expression (78.5 +/- 6 % MAP2-positive and 0.4 +/- 0.6 % NESTIN-positive) (FIG.2B, FIG.6) that did not significantly differ by diagnosis or glucocorticoid treatment.
  • HCort dose-dependent transcriptional responses were resolved relative to those in baseline untreated NGN2-neurons.
  • protein degradation such as ubiquitin protein ligase binding
  • skin regulation such as regulation of keratinocyte differentiation
  • Glucocorticoid-acetylcholine signaling interactions occur in pathways affecting memory consolidation, and alter glutamatergic synapses and synaptic stability, suggesting that glucocorticoid exposure alters acetylcholine signaling to impact glutamatergic synaptic biology.
  • Remaining ME values for modules M4-7 significantly increased with HCort treatment.
  • HCort treatment of NGN2-neurons independent of diagnosis, resulted in robust down-regulation of acetylcholine signaling and skin development, and up-regulation of inflammation-modulating and cell-signaling genes.
  • transcriptomic responses to HCort exposure enriched in neuronal projection and signaling terms, we sought to validate these functional measures of HCort exposure in NGN2-neurons.
  • neurite tracing analysis on NGN2-neurons treated with HCort, finding a dose- dependent decrease in neurite length per neuron after stimulation with 100 nM, 1000 nM and 2500 nM of HCort (FIG.2E).
  • DRGs differential response genes
  • FIG.4A The significant DRGs in NGN2-neurons predicted PTSD; for each individual, unsupervised classification revealed a clear pattern of HCort response dysregulation that correctly classified NGN2-neurons from PTSD-positive and PTSD-negative groups (FIG.4B).
  • Meta- analysis revealed shared DRGs across batches (FIG.4C), demonstrating the validity of this PTSD signature.
  • PTSD-specific neuronal DEGs are not detectable at baseline, most significant in response to low (100 nM) glucocorticoid exposure, and enriched for post-mortem PTSD transcriptomic signatures.
  • Example 2 A method of treating PTSD [00199] Using the methods of the disclosure, an individual diagnosed with PTSD may be treated with a therapeutically effective amount of a glucocorticoid receptor antagonist.
  • Example 3 A method of preventing PTSD [00200] Using the methods of the disclosure, an individual at risk for PTSD may be administered a therapeutically effective amount of a glucocorticoid receptor antagonist and/or a psychedelic agent. Such administration may serve as a prophylactic treatment for one or more symptoms of PTSD or for the development of PTSD.
  • Example 4 A method of treating PTSD [00201] Using the methods of the disclosure, an individual at risk for PTSD, suffering from one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) symptoms associated with PTSD, or diagnosed with PTSD may be treated with one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) agents that modify the glucocorticoid response (e.g., a glucocorticoid receptor antagonist) and/or psychedelic agents.
  • agents that modify the glucocorticoid response e.g., a glucocorticoid receptor antagonist
  • psychedelic agents e.g., a glucocorticoid receptor antagonist
  • the method includes obtaining a biological sample (e.g., blood cells (e.g., peripheral blood mononuclear cells), neurons (e.g., glutamatergic neurons), fibroblasts, or hiPSCs) from the individual suspected of being at risk for PTSD, suffering from one or more symptoms associated with PTSD, or diagnosed with PTSD; processing a cell obtained from the biological sample to produce a test cell; contacting the test cell with a glucocorticoid to produce a glucocorticoid-induced response; detecting the expression and/or activity of one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) genes of the glucocorticoid response (e.g., one or more genes of Table 1 and/or Table 2); identifying an individual as at risk for PTSD or diagnosing the individual with PTSD when the expression or activity of the one or more (genes of the glucocorticoid response
  • a biological sample e.g.
  • the individual may be identified as being at risk for PTSD when the expression of two genes of Table 1 are increased relative to a suitable control (e.g., a control with substantially no test agent).
  • a suitable control e.g., a control with substantially no test agent
  • the individual may be identified as having PTSD when the activity of three genes of Table 1 are decreased relative to a suitable control (e.g., a control with substantially no test agent).
  • the individual identified as at risk for PTSD or diagnosed with PTSD, respectively may be administered a glucocorticoid receptor antagonist and/or a psychedelic agent.
  • an individual at risk for developing PTSD, diagnosed with PTSD, or experiencing one or more symptoms associated with PTSD may be administered one more agents that modify the glucocorticoid-induced response (e.g., a glucocorticoid receptor antagonist) or one or pyschedelic agents.
  • agents that modify the glucocorticoid-induced response e.g., a glucocorticoid receptor antagonist
  • Such a method may serve as a method of treatment.
  • Example 5 Identifying individuals at risk for PTSD [00205] Using the methods of the disclosure, an individual at risk for PTSD or diagnosed with PTSD may be identified.
  • the method includes obtaining a biological sample (e.g., blood cell (e.g., peripheral blood mononuclear cell), neuron (e.g., glutamatergic neuron), fibroblast, or hiPSC) from the individual suspected of being at risk for PTSD or diagnosed with PTSD, processing a cell obtained from the biological sample to produce a test cell, contacting the test cell with a glucocorticoid to produce a glucocorticoid-induced response, detecting the expression and/or activity of the one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) genes of the glucocorticoid response (e.g., one or more genes of Table 1 and/or Table 2), and identifying an individual as having an elevated risk for PTSD or diagnosing the individual with PTSD if the expression and/or activity of the one or more genes of the glucocorticoid response are elevated relative to a suitable control (e.g., blood cell (e.
  • an individual may be identified as not having an elevated risk for PTSD or not having PTSD if the expression and/or activity of the one or more genes of the glucocorticoid response are not found to be elevated relative to a suitable control (e.g., a control with substantially no test agent).
  • a suitable control e.g., a control with substantially no test agent.
  • fibroblasts from an individual suspected of being at risk for PTSD may be obtained, a cell from the biological sample may be processed to produce a test cell, the test cell may be contacted with a glucocorticoid to produce a glucocorticoid-induced response, expression of the one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) genes of the glucocorticoid response of Table 1 may be detected, and the individual may be identified as having an elevated risk for PTSD if the expression of the one or more genes of the glucocorticoid response are elevated relative to a suitable control (e.g., a control with substantially no test agent).
  • a suitable control e.g., a control with substantially no test agent
  • Example 6 A Method of screening compounds for treating PTSD [00207] Using the methods of the disclosure, compounds may be screened for their ability to reduce the risk of an individual developing PTSD, reduce the risk of an individual developing one or more symptoms of PTSD, or alleviate one or more symptoms of PTSD.
  • hiPSCs e.g., a hiPSC induced glutamatergic neuron
  • the cells may be contacted with a test agent
  • the expression of three genes of the glucocorticoid response of Table 1 may be detected by RNA sequencing
  • the test agent may be found to reduce the transcriptional profile of the PTSD- dependent glucocorticoid response gene signature
  • the test agent may be identified as a compound that does reduce the risk of an individual developing PTSD.
  • Example 7 A method for monitoring PTSD status [00209] One can measure PTSD status (e.g., progression or regression) during therapy using the methods of the disclosure.
  • individual samples may be compared to reference samples taken early in the diagnosis of the disorder.
  • Such monitoring may be useful, for example, in assessing the efficacy of a particular therapeutic agent (e.g., a glucocorticoid receptor antagonist) in an individual, determining dosages, or in assessing disease progression or status.
  • a particular therapeutic agent e.g., a glucocorticoid receptor antagonist
  • the expression and/or activity of any of the genes described herein e.g., one or more genes from Table 1 and/or Table 2
  • the expression levels or activities increase or decrease, relative to control, the dosage or administration of therapeutic agents may be adjusted.
  • Example 8 A method for optimizing the dosage of a compound for the treatment of PTSD [00210] Using the methods of the disclosure, on can determine the proper dosage (e.g., the therapeutically effective amount) of a therapeutic agent for an individual, the proper duration of dosage of a therapeutic agent for an individual, the proper type of therapeutic agent, or whether a therapy should be administered.
  • the proper dosage e.g., the therapeutically effective amount
  • one or more genes of the glucocorticoid response e.g., one or more genes of Table 1 and/or Table 2
  • hiPSCs e.g., a hiPSC induced glutamatergic neuron
  • the cells may be contacted with a test agent, with a dose of a glucocorticoid receptor antagonist the expression of three genes of the glucocorticoid response of Table 1 may be detected by RNA sequencing, the dose of the test agent may have been found to reduce the transcriptional profile of the PTSD-dependent glucocorticoid response gene signature, and the dose of the test agent may be identified as a dose that is therapeutically effective.

Abstract

Use of particular biomarkers in biological samples with altered expression or activity levels to diagnose, prognose, and treat post-traumatic stress disorder (PTSD) in individuals, and further to select individuals who would benefit from a PTSD therapy such as treatment with a glucocorticoid receptor antagonist. Methods that utilize these biomarkers for the diagnosis, prognosis, and/or treatment of PTSD as well as screening for compounds that reduce the risk of an individual developing PTSD, reduce the risk of an individual developing one or more symptoms of PTSD, and alleviate one or more symptoms of PTSD in an individual.

Description

METHODS AND COMPOSITIONS FOR THE TREATMENT OF PTSD CROSS REFERENCE TO RELATED APPLICATIONS [0001] This application claims the benefit of and priority to U.S. Provisional Application No.63/391,557, filed July 22, 2022, the entire disclosure of which is hereby incorporated by reference in its entirety for all purposes. GOVERNMENT SUPPORT [0002] This invention was made with government support under W81XWH-15-1-0706 awarded by the U.S. Department of the Army. The government has certain rights in the invention. FIELD OF THE INVENTION [0003] Provided herein are diagnostic and therapeutic methods for the treatment of post- traumatic stress disorder using agents that modify the glucocorticoid response (e.g., glucocorticoid rector antagonists) and/or psychedelic agents. BACKGROUND [0004] Post-Traumatic Stress Disorder (PTSD) affects 7-8% of the general population of the United States and approximately 15% of veterans returning from combat. The symptoms can persist for months or decades. Unfortunately, PTSD is often misdiagnosed and left untreated in affected civilian and military individuals, disrupting the quality of their lives, their families, and children. Even when diagnosed, the severity of PTSD progression remains difficult to treat. The cellular and molecular mechanisms of this condition are still poorly understood despite extensive study of the neurobiological correlates of this disorder. [0005] Current diagnosis of PTSD is established on the basis of clinical history and subjective mental status examination, using a clinically structured interview, symptom checklists, or patient self-reports. However, with these subjective tests it remains difficult to distinguish PTSD from other psychiatric disorders, resulting in difficult treatment decisions regarding both treatment interventions and a definitive understanding of the etiology. The existing limitations of current clinical assessment of PTSD would benefit substantially from a more objective means to enhance the ability to identify the PTSD patient, and therefore be able to differentiate PTSD from other psychiatric disorders. [0006] Convergent lines of evidence are consistent with a heritable component to PTSD risk. There is a concordance between PTSD diagnosis in monozygotic and dizygotic twins, and genome-wide association studies (GWAS) estimate single nucleotide polymorphism (SNP)-based heritability from 5-30% and identify loci significantly associated with PTSD. This highlights the necessity of developing paradigms that examine the impact of PTSD genetic risk factors. However, insights into the gene and environment (GxE) interactions underlying the psychiatric symptoms of PTSD remain poorly resolved, reflecting the lack of a cohesive neurobiological framework to investigate these mechanisms. To date, most studies of PTSD pathophysiology have focused on peripheral blood mononuclear cells (PBMCs), with PTSD patients showing lower ambient cortisol and heightened glucocorticoid sensitivity relative to healthy controls, coupled with increased expression of innate immune genes. It is therefore critical to deconvolve the impact of stress in a cell-specific manner, including determinants of stress responses across brain and blood cells. [0007] Although there has been an effort to develop a clinical strategy to identify patients with PTSD, there is currently no biological assay for detecting such risk in patients. Therefore, diagnosis of patients with PTSD is only established on the basis of clinical history and mental status examination, often using a clinically structured interview, symptom checklist, and patient self-report. The current clinical assessment would benefit from a more objective test. SUMMARY [0008] The present disclosure includes the disclosure that the expression and activity of particular biomarkers (e.g., one or more genes of the glucocorticoid response (e.g., a gene from Table 1 and/or Table 2) in biological samples can be utilized to diagnose, prognose, and treat post-traumatic stress disorder (PTSD) in individuals, and further to select individuals who would benefit from a therapy in which one or more psychedelic agents and/or agents that modify the glucocorticoid response are administered. Accordingly, the present disclosure encompasses methods that utilize genes of the glucocorticoid response for the diagnosis, prognosis, and/or treatment of PTSD. [0009] In one aspect, provided are psychedelic agents for use in the treatment of post- traumatic stress disorder (PTSD), wherein the individual has modified expression and/or activity of MYC, PAX6, YY1, LEF1, or NFKB1 relative to a suitable control. In some embodiments, the individual has modified expression and/or activity of MYC, PAX6, YY1, and LEF1 relative to a suitable control. In some embodiments, the individual has increased expression and/or activity of MYC, increased expression and/or activity of PAX6, increased expression and/or activity of YY1, and/or increased expression and/or activity of LEF1. [0010] In one aspect, provided are methods of treating an individual having modified expression and/or activity of MYC, PAX6, YY1, LEF1, or NFKB1 relative to a suitable control for post-traumatic stress disorder, the method comprising administering to the individual a therapeutically effective amount of a psychedelic agent. In some embodiments, the individual has modified expression and/or activity of MYC, PAX6, YY1, and LEF1 relative to a suitable control. In some embodiments, the individual has increased expression and/or activity of MYC, increased expression and/or activity of PAX6, increased expression and/or activity of YY1, and/or increased expression and/or activity of LEF1. [0011] In one aspect, the disclosure provides a method of treating an individual diagnosed with PTSD including administering to the individual diagnosed with PTSD a therapeutically effective amount of a psychedelic agent and/or glucocorticoid receptor antagonist. [0012] In some embodiments of the foregoing aspect, the individual diagnosed with PTSD is diagnosed with PTSD by a the method including: i) obtaining a biological sample from the individual suspected of being at risk for PTSD; ii) processing a cell obtained from the biological sample to produce a test cell; iii) contacting the test cell with a glucocorticoid to produce a glucocorticoid-induced response; iv) detecting the expression and/or activity of one or more gene(s) of the glucocorticoid-induced response; and v) diagnosing the individual with PTSD if the expression and/or activity of the one or more gene(s) of the glucocorticoid- induced response are modified relative to a suitable control. [0013] In another aspect, the disclosure provides a method of preventing PTSD in an individual at risk for PTSD comprising administering to the indivusualg a therapeutically effective amount of a glucocorticoid receptor antagonist and/or a psychedelic agent. [0014] In some embodiments of any of the foregoing aspects, an individual at risk for PTSD is identified as an individual at risk for PTSD by the method including: i) obtaining a biological sample from the individual suspected of being at risk for PTSD; ii) processing a cell obtained from the biological sample to produce a test cell; iii) contacting the test cell with a glucocorticoid to produce a glucocorticoid-induced response; iv) detecting the expression and/or activity of one or more gene(s) of the glucocorticoid-induced response; and v) identifying the individual as at risk for PTSD or if the expression and/or activity of the one or more gene(s) of the glucocorticoid-induced response are modified relative to a suitable control. [0015] In another aspect, the disclosure provides a method of treating an individual at risk for PTSD, suffering from one or more symptoms associated with PTSD, and/or diagnosed with PTSD, the method including: i) obtaining a biological sample from the individual suspected of being at risk for PTSD, suffering from one or more symptoms associated with PTSD, or diagnosed with PTSD; ii) processing a cell obtained from the biological sample to produce a test cell; iii) contacting the test cell with a glucocorticoid to produce a glucocorticoid-induced response; iv) detecting the expression and/or activity of one or more gene(s) of the glucocorticoid-induced response; v) identifying the individual as at risk for PTSD or diagnosing the individual with PTSD when the expression and/or activity of the one or more gene(s) of the glucocorticoid-induced response are modified relative to a suitable control; and vi) administering to the individual identified as at risk for PTSD or diagnosed with PTSD one or more psychedelic agent(s) and/or agent(s) that modify the glucocorticoid- induced response. [0016] In some embodiments of any of the foregoing aspects, the one or more gene(s) of the glucocorticoid-induced response are increased relative to a suitable control. [0017] In some embodiments of any of the foregoing aspects, the one or more gene(s) of the glucocorticoid-induced response are decreased relative to a suitable control. [0018] In another aspect, the disclosure provides a method for identifying an individual at risk for PTSD or diagnosed with PTSD, the method including: i) obtaining a biological sample from the individual suspected of being at risk for PTSD or diagnosed with PTSD; ii) processing a cell obtained from the biological sample to produce a test cell; iii) contacting the test cell with a glucocorticoid to produce a glucocorticoid-induced response; iv) detecting the expression and/or activity of one or more gene(s) of the glucocorticoid-induced response; and v) identifying the individual as at risk for PTSD or diagnosing the individual with PTSD if the expression and/or activity of the one or more gene(s) of the glucocorticoid-induced response are modified relative to a suitable control. [0019] In another aspect, the disclosure provides a method of treating an individual at risk for developing PTSD, diagnosed with PTSD, or experiencing one or more symptoms associated with PTSD, the method including administering one more psychedelic agent(s) and/or agent(s) that modify the glucocorticoid-induced response. [0020] In some embodiments of any of the foregoing aspects, the one or more agent(s) that modify the glucocorticoid-induced response includes a glucocorticoid receptor antagonist. [0021] In some embodiments of any of the foregoing aspects, the one or more agent(s) is administered via a parenteral or a non-parenteral route. [0022] In another aspect, the disclosure provides a method for screening compounds that reduce the risk of an individual developing PTSD, reduce the risk of an individual developing one or more symptoms of PTSD, and/or alleviate one or more symptoms of PTSD in an individual, the method including: i) obtaining a biological sample from the individual at risk for PTSD or suffering from PTSD; ii) processing a cell obtained from the biological sample to produce a test cell; iii) contacting the test cell with a glucocorticoid to produce a glucocorticoid-induced response; iv) contacting the test cell with one or more test agent(s); detecting the expression and/or activity of one or more gene(s) of the glucocorticoid-induced response; and v) if the one or more test agent(s) modifies the expression and/or activity of one or more gene(s) of the glucocorticoid-induced response compared to a suitable control, identifying the test agent as a compound that does reduce the risk of an individual developing PTSD, reduce the risk of an individual developing one or more symptoms of PTSD, and/or alleviate one or more symptoms of PTSD in an individual. [0023] In some embodiments of any of the foregoing aspects, the one or more gene(s) of the glucocorticoid-induced response include one or more genes selected from the group consisting of MAN1A2, CD1D, CEP350, DISP1, USP37, NPHP3, GOLGA4, KIAA1109, DKK4, BMI1, NEDD4, NF1, CEACAM19, ZNF235, KRCC1, KCTD16, RP11-664D7.4, C8orf87, ANO1, PACS1, UBQLNL, LRRC56, DPYSL4, HMBS, SNRNP35, TM2D3, C17orf75, GATA5, ZNF443, ZC3H12B, RSF1, KPNA4, C12orf57, ATP6V0B, ANAPC11, KCNK2, OR7D2, NUDT16, ANKRD17, ERGIC3, KLF7, PEAK1, ASAP1, MIAT, SGPP2, RPS11, A1L2, CSMD1, PEX6, PDE11A, MASP1, IL1RAPL2, MRPL11, RBX1, TMEM98, IFT27, PPIB, DCTN3, TOMM22, CALCB, RNF152, TIMP3, ZNF587, FGD5, NTAN1P2, C9orf169, GJA10, ZNF385C, MAN1A2, BMI1, CTC-448F2.6, CORO6, TTLL6, YY1, XBP1, USF2, USF1, TEF, STAT1, SRF, SREBF1, SP1, SOX5, SMAD3, POU3F2, PAX6, NRF1, NFKB1, MYC, MEIS1, MEF2A, MAF, LEF1, HSF1, HLF, FOXO1, ETS2, ETF1, ELK1, ELF1, EGR1, E4F1, E2F4, E2F3, E2F1, CREB1, CEBPG, CDPF1, ATF4, ATF3, and combinations thereof. [0024] In some embodiments of any of the foregoing aspects, the one or more test agent(s) increases the expression and/or activity of one or more gene(s) of the glucocorticoid- induced response. For example, in some embodiments of any of the foregoing aspects, the one or more gene(s) include one or more genes selected from the group consisting of ZC3H12B, RSF1, ANKRD17, KLF7, PEAK1, ASAP1, MIAT, SGPP2, RPS11, A1L2, CSMD1, PEX6, PDE11A, DCTN3, TIMP3, ZNF587, and combinations thereof. [0025] In some embodiments of any of the foregoing aspects, the one or more test agent(s) decreases the expression and/or activity of one or more gene(s) of the glucocorticoid-induced response. For example, in some embodiments of any of the foregoing aspects, the one or more gene(s) include one or more genes selected from the group consisting of KPNA4, C12orf57, ATP6V0B, ANAPC11, KCNK2, OR7D2, NUDT16, ERGIC3, MASP1, IL1RAPL2, MRPL11, RBX1, TMEM98, IFT27, PPIB, TOMM22, CALCB, RNF152, and combinations thereof. [0026] In some embodiments of any of the foregoing aspects, the suitable control includes a prior biological sample taken from the same individual, a biological sample from a healthy individual not having a risk for PTSD, a biological sample from an individual not having one or more symptoms associated with PTSD, or a biological sample from an individual that is diagnosed with PTSD that has been treated for PTSD. [0027] In some embodiments of any of the foregoing aspects, the biological sample includes blood cells and/or fibroblasts. [0028] In some embodiments of any of the foregoing aspects, processing the cell obtained from the biological sample includes dedifferentiating the cell to produce an induced pluripotent stem cell (iPSC). [0029] In some embodiments of any of the foregoing aspects, the iPSC is differentiated to produce the test cell. [0030] In some embodiments of any of the foregoing aspects, the differentiated iPSC includes an induced neuron or an induced peripheral blood mononuclear cell. [0031] In some embodiments of any of the foregoing aspects, the test cell includes a neuron or a peripheral blood mononuclear cell. [0032] In some embodiments of any of the foregoing aspects, the neuron is a glutamatergic neuron. [0033] In some embodiments of any of the foregoing aspects, the glucocorticoid includes a glucocorticoid receptor agonist. [0034] In some embodiments of any of the foregoing aspects, the glucocorticoid receptor agonist is dexamethasone or hydrocortisone. [0035] In some embodiments of any of the foregoing aspects, the detecting includes sequencing RNA derived from the biological sample. [0036] In some embodiments of any of the foregoing aspects, the detecting includes detecting a transcriptional profile of a glucocorticoid-induced response. [0037] In some embodiments of any of the foregoing aspects, the detecting includes assessing epigenetic changes of the one or more gene(s) of the glucocorticoid-induced response. [0038] In some embodiments of any of the foregoing aspects, the assessing of epigenetic changes includes performing a chromatin immunoprecipitation assay. [0039] In some embodiments of any of the foregoing aspects, the expression and/or activity of the one or more gene(s) of the glucocorticoid-induced response is increased for a first subset of genes and decreased for a second subset of genes to produce a glucocorticoid- induced response signature. [0040] In some embodiments of any of the foregoing aspects, the suitable control includes substantially no test agent. [0041] In some embodiments of any of the foregoing aspects, the processing includes automated reprogramming of the cell obtained from the biological sample. [0042] In some embodiments of any of the foregoing aspects, contacting the test cell with a glucocorticoid is performed for a duration of from about 1 hour to about 96 hours (e.g., about 2 hours to about 95 hours, about 3 hours to about 90 hours, about 4 hours to about 80 hours, about 5 hours to about 70 hours, about 10 hours to about 60 hours, about 20 hours to about 50 hours, or about 30 hours to about 40 hours). [0043] In some embodiments of any of the foregoing aspects, the glucocorticoid has a concentration of from about 1 nM to about 10 µM (e.g., about 10 nM to about 9 µM, about 50 nM to about 8 µM, about 100 nM to about 7 µM, about 1 µM to about 6 µM, about 2 µM to about 5 µM, about 3 µM to about 4 µM). [0044] In some embodiments of any of the foregoing aspects, contacting the test cell with one or more test agent(s) is performed for a duration of from about 1 hour to about 96 hours (e.g., about 2 hours to about 95 hours, about 3 hours to about 90 hours, about 4 hours to about 80 hours, about 5 hours to about 70 hours, about 10 hours to about 60 hours, about 20 hours to about 50 hours, or about 30 hours to about 40 hours). [0045] In some embodiments of any of the foregoing aspects, the test agent has a concentration of from about 1 nM to about 10 µM (e.g., about 10 nM to about 9 µM, about 50 nM to about 8 µM, about 100 nM to about 7 µM, about 1 µM to about 6 µM, about 2 µM to about 5 µM, about 3 µM to about 4 µM). [0046] In another aspect, the disclosure provides a method of identifying a PTSD- dependent glucocorticoid response gene signature, the method including: i) obtaining a biological sample from an individual suspected of being at risk for PTSD, suffering from one or more symptoms associated with PTSD, or diagnosed with PTSD; ii) processing a cell obtained from the biological sample to produce a test cell; iii) contacting the test cell with a glucocorticoid to produce a glucocorticoid-induced response; iv) detecting the expression and/or activity of a plurality of genes; and v) comparing the expression and/or activity of the plurality of genes with the expression and/or activity of the plurality of genes from a suitable control sample obtained from a healthy individual. [0047] In some embodiments of any of the foregoing aspects, the individual is a juvenile. [0048] In one aspect, provided are methods of treating an individual at risk for PTSD, suffering from one or more symptoms associated with PTSD, or diagnosed with PTSD, the method comprising: administering to the individual one or more psychedelic agent(s) and/or agent(s) that modify the glucocorticoid-induced response, wherein expression and/or activity of one or more gene(s) of the glucocorticoid-induced response in test cells produced from a biological sample obtained from the individual were modified relative to a suitable control when such test cells were contacted with a glucocorticoid. [0049] In one aspect, provided are psychedelic agents for use in a method of treating an individual at risk for PTSD, suffering from one or more symptoms associated with PTSD, or diagnosed with PTSD, wherein expression and/or activity of one or more gene(s) of the glucocorticoid-induced response in test cells produced from a biological sample obtained from the individual were modified relative to a suitable control when such test cells were contacted with a glucocorticoid. [0050] In one aspect, provided are agents that modify the glucocorticoid response for use in a method of treating an individual at risk for PTSD, suffering from one or more symptoms associated with PTSD, or diagnosed with PTSD, wherein expression and/or activity of one or more gene(s) of the glucocorticoid-induced response in test cells produced from a biological sample obtained from the individual were modified relative to a suitable control when such test cells were contacted with a glucocorticoid. [0051] The present disclosure is based, at least in part, on the surprising finding that glucocorticoid-induced (e.g., to dexamethasone (DEX) and hydrocortisone (HCort)) blood and neuronal responses were significantly enriched for immune response, brain development, and neurodevelopmental disorder genes, with specific upregulation of PTSD-associated genes in neurons only. These discoveries were based upon the comparison of glutamatergic neurons derived from human induced pluripotent stem cell (hiPSC) from combat veterans with and without PTSD. The present disclosure is also based, at least in part, on the finding that glucocorticoid hypersensitivity occurred in samples from PTSD cases, with diagnosis- specific effects greatest at low doses, and significantly more robust in neurons than peripheral blood mononuclear cells (PBMCs). A baseline PTSD diagnosis-specific signature was undetectable in either human neurons or PBMCs. This glucocorticoid-response signature was enriched for transcriptomic patterns observed in post-mortem brain tissue from PTSD cases. Together, these surprising findings provide a PTSD-dependent glucocorticoid response gene signature and demonstrate that the glucocorticoid response is encoded in PTSD patient genetics, consistent with a clear genetic predisposition to PTSD. Based upon the surprising elucidation of a PTSD-dependent glucocorticoid response gene signature, the methods described herein can be used to diagnose, prognose, and treat PTSD. BRIEF DESCRIPTION OF THE DRAWINGS [0052] FIGs.1A-1E are an experimental schematic and a set of graphs, respectively, showing the transcriptional response to dexamethasone (DEX) in peripheral blood mononuclear cells (PBMCs). FIG.1A is a schematic showing the experimental design. PBMCs from 20 post-traumatic stress disorder (PTSD) cases and 20 combat-exposed controls were treated with DEX for 72 hours and RNAseq was performed. FIG.1B is a graph showing that the number of differentially expressed genes observed in batch A (n = 10 vs.10) (squares) and batch B (n = 10 vs.10) (circles) are up-regulated and down-regulated (y-axis) across three different concentrations of DEX conditioning (x-axis) at a Bonferroni-corrected p-value threshold. FIG.1C is a set of graphs showing the meta-analysis of expression LogFC (differences observed between vehicle and DEX exposure), which was plotted against -log(P value) for each gene. Gray points indicate significantly differentially expressed genes in the meta-analysis. FIG.1D is a set of graphs showing Module eigengene (ME) values from modules identified by weighted gene co-expression network analysis (WGCNA) were correlated with increasing DEX concentrations. Top correlated modules with DEX concentration are shown here (p-values are labeled above each boxplot). Each module was subjected to gene ontology enrichment analysis and the topmost significant enrichment terms and their associated Benjamini-Hochberg adjusted P-values are displayed. FIG.1E is a graph showing the gene set enrichment of DEX-dependent differentially expressed genes across psychiatric disorder and neurodevelopmental gene sets. [0053] FIGs.2A-2F are an experimental schematic and a set of graphs, respectively, showing gene expression changes to hydrocortisone (HCort) in human induced pluripotent stem cell (hiPSC)-derived neurons. FIG.2A is a schematic showing the experimental design. hiPSC-derived neurogenin 2 (NGN2) neurons were treated with HCort for 24 hours and RNAseq was performed. FIG.2B depicts a set of photomicrographs of NGN2 neurons stained for neuronal markers NESTIN and MAP2, nucleic marker HOECHST, and green fluorescent protein (GFP) to confirm neuronal identity and morphology across all conditions. FIG.2C is a set of graphs showing meta-analyzed differentially expressed genes (DEGs) in response to increasing concentrations of HCort shows robust changes in NGN2-neurons. A comparative analysis of transcriptome-wide log2 fold-changes in response to different concentrations of HCort in NGN2-neurons shows similar responses, indicating a conserved response across all donors to HCort in NGN2-neurons. FIG.2D is a set of graphs showing the meta-analysis of expression LogFC (differences observed between vehicle and HCort exposure), which was plotted against -log(P value) for each gene. Gray points indicate significantly differentially expressed genes in the meta-analysis. FIG.2E is a graph and respective photomicrograph showing the morphological analysis of neurite outgrowth on day 7 in NGN2-neurons showing a dose-dependent decrease in neurite outgrowth with HCort exposure. Representative images of neurite morphology to HCort exposure are shown below. FIG.2F is a graph showing the gene set enrichment of HCort-dependent differentially expressed genes across psychiatric disorder and neurodevelopmental gene sets. [0054] FIGs.3A-3B are a set of graphs showing the HCort stimulated co-expression modules in NGN2-neurons. FIG.3A is a set of graphs showing the weighted gene co- expression network analysis (WGCNA), which identified three groups of co-regulated gene modules. Pearson correlation was used to assess changes in module eigengene (ME) values with increasing concentration of HCort (p-values are labeled above each boxplot). Each module was subjected to gene ontology enrichment analysis and the topmost significant enrichment terms and their associated Benjamini-Hochberg adjusted P-values are displayed. Top hub genes (kME > 0.6) within each module are displayed for quick interpretation of glucocorticoid (GR)-stimulated gene co-expression modules and candidate individual genes. FIG.3B is a set of graphs showing the network visualization of protein-protein interactions within modules indicating clusters and network hubs. [0055] FIGs.4A-4F are a set of graphs showing the PTSD-positive specific responses to HCort in NGN2-neurons. FIG.4A is a graph showing genes that differ in their response to HCort in PTSD-positive donors compared to PTSD-negative donors, here termed “differential response genes (DRGs),” which were detected in both the 100 nM and 1000 nM dose, indicating PTSD diagnosis-specific responses to HCort. FIG.4B is a set of heat maps showing that significant NGN2-DRGs correctly classify PTSD-positive from PTSD-negative participants using an unsupervised approach. FIG.4C is a set of graphs showing the meta- analysis of Expression LogFC DRGs (differences observed between PTSD-positive and PTSD-negative) was plotted against -log(P value). Gray points indicate significantly differentially expressed genes in the meta-analysis, representing PTSD case-specific response genes to HCort. FIG.4D is a graph showing the gene set enrichment of significant DRGs across psychiatric disorder gene sets (epilepsy, developmental delay, autism spectrum disorder, intellectual disability, schizophrenia, and fragile X messenger ribonucleoprotein (FMRP) targets). FIG.4E is a set of graphs showing the interactive effect of PTSD diagnosis and HCort exposure on gene expression, which are modeled, and three major observed patterns of direction of effect in significantly interactive genes are represented. The patterns of three representative genes that indicate patterns of PTSD x HCort interaction, PTSD hyper-responsivity, and PTSD hypo-responsivity, respectively from left-to-right, are plotted, demonstrating examples of three biologically meaningful patterns of diagnosis by HCort interaction. FIG.4F is a graph showing the logFC of all significantly interactive diagnosis by HCort genes plotted against the P-value of their interaction term, with most significant genes representing those with most significant interactive effects. [0056] FIGs.5A-5D are a set of graphs and a schematic, respectively, showing transcription factors driving PTSD hyper-responsivity. FIG.5A is a set of graphs showing PTSD hyper-responsive genes were shown to be enriched for several transcription factor targets. Four of the enriched transcription factors driving hyper-responsivity in PTSD cases are shown for exemplary purposes. Normalized expression of the transcription factor is graphed on the x-axis with average expression of the transcription factor targets on the y-axis in PTSD-positive and control NGN2 neurons stimulated with HCort, demonstrating differential regulation in stimulated PTSD-positive patients vs. controls. FIG.5B is a schematic of a network visualization of protein-protein interactions amongst identified transcription factors mediating PTSD hyper-responsivity. FIG.5C is a graph showing the overlap of transcription factors (dashed) and their targets (white) identified in the study with significantly differentially expressed genes in other PTSD studies. FIG.5D is a set of Manhattan plots of significantly interactive genes in the study compared to Manhattan plot of imputed expression from PTSD genome-wide association studies (GWAS) indicating spatial orientation of significantly interactive genes. [0057] FIG.6 is a set of photomicrographs showing the immunostaining of hiPSC- derived NGN2-neurons. Immunostaining of Hoechst, GFP, MAP2, and NESTIN across all participants. [0058] FIGs.7A-7B are a set of graphs showing adjustment of Batch effects. FIG.7A is a set of graphs showing VariancePartition (left), primary component analysis (PCA; middle), and an example gene after batch correction (right). This analysis on uncorrected data indicate a large batch effect. FIG.7B is a set of graphs showing VariancePartition (left), PCA (middle), and an example gene after batch correction (right). [0059] FIGs.8A-8B are a set of graphs showing a developmental specificity analysis. FIG.8A is a graph showing pair-wise correlation between NGN2s from the study with cell types across 16 independent studies FIG.8B is a graph showing the PCA analysis of cell types within all 16 studies with the NGN2 neurons. [0060] FIGs.9A-9C are a set of graphs showing a neuronal fate specificity analysis. FIG.9A is a heat map showing the expression of hallmark pan-neuronal and neuronal subtype specific genes in NGN2 neurons and PBMCs. FIG.9B is a graph showing the average log2CPM expression of vesicular glutamate transporter 1 (VGLUT1) and vesicular glutamate transporter 2 (VGLUT2) in NGN2 neurons and PBMCs. FIG.9C is a graph showing the expression of GR and mineralocorticoid (MR) in NGN2 neurons and PBMCs. [0061] FIGs.10A-10D are a set of graphs showing the comparison of PBMC batches. FIG.10A is a graph showing pair-wise correlations between PBMC batches. FIG.10B is a graph showing the transcriptome-wide correlation between batches at the 50 nM DEX dose. FIG.10C is a graph showing the pair-wise correlations between PBMC batches and Breen, M. S. et al. Translational Psychiatry 9, 201, doi:10.1038/s41398-019-0539-x (2019). FIG. 10D is a graph showing the transcriptome-wide correlation between the study and Breen et al. 2019 at the 50 nM DEX dose. [0062] FIGs.11A-11B are a set of graphs showing a comparison of NGN2 batches. FIG. 11A is a set of graphs showing HCort-responsive DEGs across independent batches. Transcriptome-wide concordance is plotted between dosages for each batch. FIG.11B is a graph showing the quantification of cell number with HCort treatment showing no significant cell density between doses. [0063] FIGs.12A-12B are a set of graphs showing a weighted gene co-expression network analysis of PBMCs (FIG.12A) and NGN2 neurons (FIG.12B). The β-power required to satisfy scale free topology (SFT) and corresponding mean connectivity for gene co-expression network construction. Hierarchical gene cluster tree, module structure, and gene-treatment are denoted by gray bands. The first band underneath the tree indicates the detected modules and subsequent bands indicate treatment correlation, where lighter gray indicates a strong relationship and darker gray indicates a strong negative relationship. [0064] FIGs.13A-13B are a set of graphs showing analysis of unsigned modules. FIG. 13A is a set of graphs showing unsigned modules significantly associated with neural projection terms, such as neural crest cell differentiation (p = 3.96e-04) and regulation of neuron projection development (p = 1.04e-03), and immune terms, such as regulation of acute inflammatory response (p = 1.83e-03). FIG.13B is a set of network visualization of protein- protein interactions within unsigned modules indicating clusters and network hubs. [0065] FIGs.14A-14B are a set of graphs showing PTSD-positive-specific responses to DEX in PBMCs. FIG.14A is a graph showing genes that differ in their response to DEX in PTSD-positive donors compared to PTSD-negative donors, here termed “differential response genes (DRGs),” at a false discovery rate (FDR) threshold of 20% (non-significant). FIG.14B is a set of graphs showing unsupervised clustering of nominally significant PTSD DRGs. [0066] FIG.15 is a graph (left) and Venn diagram (right), respectively, showing the concordance of PBMC signature with NGN2 signature. Pair-wise correlations between transcriptome-wide signatures of PBMC and NGN2 batches are shown. DETAILED DESCRIPTION OF CERTAIN EMBODIMENTS Definitions [0067] The features and other details of the disclosure will now be more particularly described. Certain terms employed in the specification, examples and appended claims are collected here. These definitions should be read in light of the remainder of the disclosure and understood as by a person of skill in the art. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by a person of ordinary skill in the art. [0068] As used herein, the singular form “a,” “an,” and “the” includes plural references unless indicated otherwise. [0069] The term “about” means an acceptable error for a particular value as determined by one of ordinary skill in the art, which depends in part on how the value is measured or determined. In certain embodiments, the term “about” means within 5%, 4%, 3%, 2%, 1%, 0.5%, or 0.05% of a given value or range. [0070] As used herein, “activity” refers to form(s) of a gene or respectively encoded protein which retains a biological activity of the native or naturally-occurring gene or polypeptide, respectively. [0071] The term “administering,” or a grammatical derivative thereof, as described herein, refers to the delivery of an agent, e.g., an agent that modifies the glucocorticoid response and/or a psychedelic agent to an individual in need thereof. Any suitable method of administration can be selected by one of skill in the art, in view of this disclosure. In some embodiments, an agent is administered via a parenteral route. In some embodiments, an agent is administered via a non-parenteral route. [0072] By “biological sample” or “sample” is meant a fluid or solid sample from an individual. Biological samples may include cells (e.g., neurons (e.g., glutamatergic neurons), blood cells (e.g., peripheral blood mononuclear cells), human induced pluripotent cells (hIPSc); nucleic acid, protein, or membrane extracts of cells; or blood or biological fluids including (e.g., plasma, serum, saliva, urine, bile). Solid biological samples include samples taken from feces, the rectum, central nervous system, bone, breast tissue, renal tissue, the uterine cervix, the endometrium, the head or neck, the gallbladder, parotid tissue, the prostate, the brain, the pituitary gland, kidney tissue, muscle, the esophagus, the stomach, the small intestine, the colon, the liver, the spleen, the pancreas, thyroid tissue, heart tissue, lung tissue, the bladder, adipose tissue, lymph node tissue, the uterus, ovarian tissue, adrenal tissue, testis tissue, the tonsils, and the thymus. Fluid biological samples include samples taken from the blood, serum, plasma, pancreatic fluid, CSF, semen, prostate fluid, seminal fluid, urine, saliva, sputum, mucus, bone marrow, lymph, and tears. In some embodiments, the biological sample is a blood, plasma, or serum sample. In some embodiments, the biological sample includes blood cells (e.g., peripheral blood mononuclear cells), neurons (e.g., glutamatergic neurons), fibroblasts, or cells later derived into hiPSC. Samples may be obtained by standard methods including, e.g., skin puncture and surgical biopsy. In some embodiments, a biological sample includes one or more cells, which are processed to produce a test cell. [0073] The terms “control,” “reference,” and “suitable control” are meant to mean any useful reference used to compare the expression and/or activity of the one or more genes of the glucocorticoid response. The baseline can be any sample, standard, standard curve, or level that is used for comparison purposes. The baseline can be a normal reference sample or a reference standard or level. A “suitable control” can be, for example, a control, e.g., a predetermined negative control value such as a “normal control” or a prior sample taken from the same individual; a sample from a normal healthy individual, a sample from an individual not having PTSD; or a sample from an individual that has been treated for PTSD. By “reference standard or level” is meant a value or number derived from a reference sample. A “normal control value” is a pre-determined value indicative of non-disease state, e.g., a value expected in a healthy control individual. Typically, a normal control value is expressed as a range (“between X and Y”), a high threshold (“no higher than X”), or a low threshold (“no lower than X”). An individual having a measured value within the normal control value for a particular assay is typically referred to as “within normal limits” for that assay. A normal reference standard or level can be a value or number derived from a normal individual not having PTSD; or an individual that has been treated for PTSD. In some embodiments, the reference sample, standard, or level is matched to the sample individual sample by at least one of the following criteria: age, weight, sex, disease stage, and overall health. As used herein, a “suitable control” refers to the expression and/or activity levels of one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) genes of the glucocorticoid response against which the expression and/or activity levels of the respective genes are compared, e.g., to make a diagnostic, predictive, prognostic, and/or therapeutic determination. In some embodiments, a suitable control includes substantially no test agent administered to an individual. [0074] Throughout the specification and claims, the word “comprise,” or variations such as “comprises” or “comprising,” will be understood to imply the inclusion of a stated word or group of words but not the exclusion of any other word or group of words. [0075] The term “detection” includes any means of detecting, including direct and indirect detection. [0076] By “determining the level of a nucleic acid” is meant the detection of a nucleic acid (e.g., mRNA) by methods known in the art. Methods to measure mRNA levels generally include, but are not limited to, northern blotting, nuclease protection assays (NPA), in situ hybridization (ISH), reverse transcription-polymerase chain reaction (RT-PCR), and RNA sequencing (RNA-Seq). [0077] By “determining the level of a protein” is meant the detection of a protein by methods known in the art. Methods to measure protein levels generally include, but are not limited to, western blotting, immunoblotting, enzyme-linked immunosorbent assay (ELISA), radioimmunoassay (RIA), immunoprecipitation, immunofluorescence, surface plasmon resonance, chemiluminescence, florescent polarization, phosphorescence, immunohistochemical analyses, matrix-associated laser desorption/ionization time of light (MALDI-TOF) mass spectrometry, liquid chromatography (LC)-mass spectrometry, microcytometry, microscopy, fluorescence activated cell sorting (FACS), and flow cytometry, as well as assays based on a property of a protein including, but not limited to, enzymatic activity or interaction with other protein partners. [0078] The terms “diagnose, “diagnosing,” “diagnosis,” and “diagnosed” are used herein to refer to the identification or classification of a genetic, molecular, or pathological state, disease, or condition (e.g., PTSD). For example, “diagnosed” may refer to identification of an individual with PTSD. [0079] As used herein, the terms “effective amount,” “therapeutically effective amount,” and the like, when used in reference to a method described herein, refer to a quantity sufficient to, when administered to an individual, including human, effect beneficial or desired results (e.g., alleviate one or more symptoms of PTSD), which may include clinical results. For example, an effective amount of one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) agents described herein (e.g., agents that modify the glucocorticoid response or psychedelic agents) may alleviate one or more symptoms of PTSD as compared to the alleviation of said symptom without administration of the agent of interest. An “effective amount,” “therapeutically effective amount,” and the like, of an agent, such as a glucocorticoid receptor antagonist or a psychedelic agent, also include an amount that results in a beneficial or desired result in an individual as compared to a control. [0080] As used herein, a “glucocorticoid receptor antagonist” is a molecule that decreases, blocks, inhibits, abrogates or interferes with signal transduction resulting from the interaction of a glucocorticoid receptor with either one or more of its binding partners. In some embodiments, glucocorticoid receptor antagonist is a molecule that inhibits the binding of a glucocorticoid receptor to its binding partners. In some embodiments, glucocorticoid receptor antagonists include small molecule antagonists, polynucleotide antagonists, antibodies and antigen-binding fragments thereof, fusion proteins, oligopeptides, and other molecules that decrease, block, inhibit, abrogate or interfere with signal transduction resulting from the interaction of a glucocorticoid receptor with one or more of its binding partners. [0081] The phrase “identifying an individual” or “identifies an individual,” as used herein, refers to using the information or data generated related to the expression and/or activity of the one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) genes of the glucocorticoid response to identify or select an individual as likely to benefit or less likely to benefit from a therapy including one or more psychedelic agents and/or agents that modify the glucocorticoid response, including a glucocorticoid receptor antagonist. The information or data used or generated may by be in any form, written, oral, or electronic. In some embodiments, using the information or data generated includes communicating, presenting, reporting, storing, sending, transferring, supplying, transmitting, dispensing, or combinations thereof. In some embodiments, communicating, presenting, reporting, storing, sending, transferring, supplying, transmitting, dispensing, or combinations thereof are performed by a computing device, analyzer unit, or combination thereof. In some embodiments, the information or data includes a comparison of the expression and/or activity of the one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) genes of the glucocorticoid response to a reference level (e.g., a level from a suitable control). In some embodiments, the information or data includes an indication that the expression and/or activity of the one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) genes of the glucocorticoid response are elevated relative to a suitable control (e.g., a control with substantially no test agent). In some embodiments, the information or data includes an indication that the individual has or does not have an elevated risk for PTSD. [0082] As used herein, the terms “induced pluripotent stem cell,” “iPS cell,” and “iPSC” refer to a pluripotent stem cell that can be derived directly from a differentiated somatic cell. Human iPS cells can be generated by introducing specific sets of reprogramming factors into a non-pluripotent cell (e.g., fibroblasts) that can include, for example, Oct-3/4, Sox family, Klf family, Myc family, Nanog, LIN28, and Glis1 genes. Human iPS cells can also be generated, for example, by the use of miRNAs, small molecules that mimic the actions of transcription factors, or lineage specifiers. Human iPS cells are characterized by their ability to differentiate into any cell of the three vertebrate germ layers, e.g., the endoderm, the ectoderm, or the mesoderm. Human iPS cells are also charactered by their ability to propagate indefinitely under suitable in vitro culture conditions. See, for example, Takahashi and Yamanaka, Cell 126:663 (2006). In some embodiments, a cell obtained from a biological sample is dedifferentiated to produce an iPSC. In some embodiments, the iPSC is then differentiated to produce a test cell. The iPSC may be differentiated into an induced neuron or an induced peripheral blood mononuclear cell. In some embodiments, a cell obtained from a biological sample is processed by automated reprogramming. [0083] By “level” is meant a level of a genes expression or activity as compared to a reference. The reference can be any useful reference, as defined herein. By a “decreased level” or an “increased level” of a gene is meant a decrease or increase in gene expression or activity, as compared to a reference (e.g., a decrease or an increase by about 5%, about 10%, about 15%, about 20%, about 25%, about 30%, about 35%, about 40%, about 45%, about 50%, about 55%, about 60%, about 65%, about 70%, about 75%, about 80%, about 85%, about 90%, about 95%, about 100%, about 150%, about 200%, about 300%, about 400%, about 500%, or more; a decrease or an increase of more than about 10%, about 15%, about 20%, about 50%, about 75%, about 100%, or about 200%, as compared to a reference; a decrease or an increase by less than about 0.01-fold, about 0.02-fold, about 0.1-fold, about 0.3-fold, about 0.5-fold, about 0.8-fold, or less; or an increase by more than about 1.2-fold, about 1.4-fold, about 1.5-fold, about 1.8-fold, about 2.0-fold, about 3.0-fold, about 3.5-fold, about 4.5-fold, about 5.0-fold, about 10-fold, about 15-fold, about 20-fold, about 30-fold, about 40-fold, about 50-fold, about 60-fold, about 70-fold, about 80-fold, about 90-fold, about 100-fold, about 125-fold, about 150-fold, about 175-fold, about 200-fold, about 225- fold, about 250-fold, about 275-fold, about 300-fold, about 325-fold, about 350-fold, about 375-fold, about 400-fold, about 425-fold, about 450-fold, about 475-fold, about 500-fold, about 525-fold, about 550-fold, about 575-fold, about 600-fold, about 625-fold, about 650- fold, about 675-fold, about 700-fold, about 725-fold, about 750-fold, about 775-fold, about 800-fold, about 825-fold, about 850-fold, about 875-fold, about 900-fold, about 925-fold, about 950-fold, about 975-fold, about 1000-fold, or more). The terms “level of expression” or “expression level” in general are used interchangeably and generally refer to the amount of a biomarker (e.g., one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) genes of the glucocorticoid response) in a biological sample). “Expression” generally refers to the process by which information (e.g., gene-encoded and/or epigenetic information) is converted into the structures present and operating in a cell. Therefore, as used herein, “expression” may refer to transcription into a polynucleotide translation into a polypeptide, or even polynucleotide and/or polypeptide modifications (e.g., posttranslational modification of a polypeptide). Fragments of the transcribed polynucleotide, the translated polypeptide, or polynucleotide and/or polypeptide modifications (e.g., post-translational modifications of a polypeptide) shall also be regarded as expressed whether they originate from a transcript generated by alternative splicing or a degraded transcript, or from post-translational processing of a polypeptide, e.g., by proteolysis. [0084] The term “modified” as used herein, refers to an observable difference in the level of a marker, such as the expression and/or activity of one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) gene(s), in a sample (e.g., a biological sample from an individual e.g., an individual suspected of being at risk for PTSD or diagnosed with PTSD), as determined using techniques and methods known in the art for the measurement of the marker. A marker level that is changed in an individual may result in a difference of at least 1% (e.g., at least 5%, 10%, 25%, 50%, or 100% or at least 2.5-fold, 3-fold, 4-fold, 5-fold, 6- fold, 7-fold or more) compared to a reference level, e.g., a level from a suitable control. In some embodiments, the change is an increased level of the expression or activity of the one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) genes of the glucocorticoid response in a biological sample from an individual. In some embodiments, the change is a decreased level of the expression or activity of the one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) genes of the glucocorticoid response in a biological sample from an individual. [0085] The terms “post-traumatic stress disorder” and “PTSD” are defined for the purposes of the present disclosure as a potentially debilitating anxiety disorder triggered by exposure to trauma or a traumatic experience (e.g., a catastrophic or threatening event, e.g., a natural disaster, a wartime situation, an accident, domestic abuse, or a violent crime), such as an interpersonal event associated with actual or threatening death or severe death, such as, for example, physical or sexual assault; exposure to disaster or accidents; combat; or witnessing a traumatic event. There are three main clusters of PTSD symptoms: firstly, those related to re-experiencing the event; secondly, those related to avoidance and arousal; and thirdly, the distress and impairment caused by the first two symptom clusters. [0086] As used herein, the terms “individual,” “subject,” and “patient” are used interchangeably and are meant as a human . An individual to be treated with a pharmaceutical composition described herein may be one who has been diagnosed by a medical practitioner as having PTSD or one at risk for developing PTSD. [0087] The terms “treat,” “treatment,” “treating,” and the like are used herein to generally mean obtaining a desired pharmacological and/or physiological effect. The effect may be therapeutic in terms of partially or completely curing a disease and/or symptom(s) of the disease. The term “treatment” as used herein covers any treatment of PTSD in a human, and includes: (a) inhibiting the disorder, i.e., preventing the disorder from increasing in severity or scope; (b) relieving the disorder, i.e., causing partial or complete amelioration of the disorder; or (c) preventing relapse of the disorder, i.e., preventing the disorder from returning to an active state following previous successful treatment of symptoms of the disorder or treatment of the disorder. [0088] The term “reference level” refers to the level as determined in a suitable control as further described herein, e.g., a level from a prior biological sample taken from the same individual, a biological sample from a healthy individual not having a risk for PTSD, a biological sample from an individual not having one or more symptoms associated with PTSD, or a biological sample from an individual that is diagnosed with PTSD that has been treated for PTSD. Post-Traumatic Stress Disorder [0089] The methods described herein can be used to diagnose, prognose, and treat post- traumatic stress disorder (PTSD). PTSD is a dominant and highly debilitating psychiatric disorder that is notoriously difficult to treat. PTSD can be characterized by intrusive recall, emotional numbness, and insomnia and is associated with functional deficiencies, physical health problems, and mental health comorbidities such as depression, with a six-fold increased risk of suicide. PTSD can result from a catastrophic or threatening event, e.g., a natural disaster, a wartime situation, an accident, domestic abuse, or a violent crime. Symptoms normally develop over the course of three months, but may emerge years after the initial trauma. [0090] DSM-IV-TR ® describes post-traumatic stress disorder (PTSD) as developing characteristic symptoms after exposure to extreme traumatic stressors, including direct personal experience of events associated with actual or threatening death or severe death. A person with PTSD can be a witness of an event that includes the death, injury, or threat to physical integrity of another person. Human reactions to events include, but are not limited to, intense fear, lethargy, or fear. A person with PTSD can have a persistent memory of an event, including images, thoughts, or perceptions, or can have a recurring painful dream of the event. Genes of the Glucocorticoid Response [0091] Applicants have discovered that the mRNA expression levels and/or activity of certain genes can be utilized to diagnose, prognose, and treat PTSD, as well as to select individuals who would benefit from a treatment that modifies the glucocorticoid response. The expression and/or activity levels of such genes can also be used for screening compounds that reduce the risk of an individual developing PTSD, reduce the risk of an individual developing one or more symptoms of PTSD, and/or alleviate one or more symptoms of PTSD. Exemplary, non-limiting genes, whose expression and/or activity which are of interest in the methods of the present disclosure, include those exemplified in Table 1, below. Table 1: Exemplary Genes of the Glucocorticoid Response
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Table 2: Potential Genes of the Glucocorticoid Response
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Methods of the Disclosure [0092] The present disclosure relates to the identification of biomarkers (e.g., one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) genes of the glucocorticoid response (e.g., genes of Table 1 and/or Table 2) that identify individuals at risk for PTSD, suffering from one or more symptoms associated with PTSD, or diagnosed with PTSD. The differential expression and/or activity levels of genes of the glucocorticoid response (e.g., genes of PTSD-dependent glucocorticoid response gene signature) can be used to diagnose, prognose, and classify individuals with PTSD from suitable controls (e.g., healthy controls). Accordingly, the methods described herein are useful for treating or diagnosing PTSD. Diagnostic and Classification Methods [0093] The present disclosure features methods to diagnose PTSD. Methods of the present disclosure may be used alone or as a companion diagnostics with other diagnostic or therapeutic approaches, as an early molecular screen to distinguish PTSD. More specifically, alterations in the expression level and/or activity of one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) genes of the glucocorticoid response, exemplified herein (e.g., one or more genes (e.g., genes of Table 1 and/or Table 2) in a biological sample (e.g., blood cell (e.g., peripheral blood mononuclear cell), neuron (e.g., glutamatergic neuron), fibroblast, or hiPSC) from the individual suspected of being at risk for PTSD, suffering from one or more symptoms associated with PTSD, or diagnosed with PTSD as compared to a suitable control (e.g., a normal reference such as a control with substantially no test agent) can be used to diagnose PTSD from diseases or disorders with similar symptoms, thereby allowing individual classification. [0094] In some embodiments, the method includes processing a cell obtained from the biological sample to produce a test cell. [0095] In some embodiments, the method further includes contacting the biological sample or cells with a glucocorticoid (e.g., dexamethasone or hydrocortisone) prior to detecting the expression level and/or activity of one or more genes of the glucocorticoid response. [0096] For example, in some embodiments, the method includes identifying an individual at risk for PTSD or diagnosed with PTSD by obtaining a biological sample from the individual suspected of being at risk for PTSD or diagnosed with PTSD; processing a cell obtained from the biological sample to produce a test cell; contacting the test cell with a glucocorticoid (e.g., dexamethasone or hydrocortisone) to produce a glucocorticoid-induced response; detecting the expression and/or activity of one or more (e.g., (e.g., two, three, four, five, ten, fifteen, or twenty or more) genes of the glucocorticoid-induced response (e.g., one or more genes of Table 1 and/or Table 2); and identifying the individual as at risk for PTSD or diagnosing the individual with PTSD if the expression and/or activity of the one or more genes of the glucocorticoid-induced response are modified relative to a suitable control (e.g., a control with substantially no test agent). [0097] Methods of the present disclosure can be used to diagnose, prognose, or classify an individual, for example, an increase in the expression and/or activity (e.g., an increase by 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%, 90%, 95%, 100%, 150%, 200%, 300%, 400%, 500%, or more, or an increase by more than 1.2-fold, 1.4-fold, 1.5-fold, 1.8-fold, 2.0-fold, 3.0-fold, 3.5-fold, 4.5-fold, 5.0-fold, 10- fold, 15-fold, 20-fold, 30-fold, 40-fold, 50-fold, 100-fold, 1000-fold, or more, as compared to a reference) of the biomarkers (e.g., one or more genes of Table 1 and/or Table 2) may identify an individual as being at risk for PTSD, suffering from one or more symptoms associated with PTSD, or diagnosed with PTSD and/or may benefit from one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) agents that modify the glucocorticoid response (e.g., a glucocorticoid receptor antagonist) and/or psychedelic agents. Similarly, a decrease in the level (e.g., a decrease by 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%, 90%, 95%, 100%, 150%, 200%, 300%, 400%, 500%, or more; or a decrease by less than 0.01-fold, 0.02-fold, 0.1-fold, 0.3-fold, 0.5-fold, 0.8-fold, or less, as compared to a reference) of the biomarkers (e.g., one or more genes of Table 1 and/or Table 2) may identify an individual as being at risk for PTSD, suffering from one or more symptoms associated with PTSD, or diagnosed with PTSD and/or may benefit from one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) agents that modify the glucocorticoid response (e.g., a glucocorticoid receptor antagonist) and/or psychedelic agents. Methods for Predicting and Monitoring Response to Agents that Modify the Glucocorticoid Response [0098] The present disclosure further features methods for predicting response to one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) agents that modify the glucocorticoid response (e.g., a glucocorticoid receptor antagonist) in cells from individuals at risk for PTSD, suffering from one or more symptoms associated with PTSD, or diagnosed with PTSD, before or after administration of one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) agents that modify the glucocorticoid response (e.g., a glucocorticoid receptor antagonist). For example, in some embodiments, the method includes screening compounds that reduce the risk of an individual developing PTSD, reduce the risk of an individual developing one or more symptoms of PTSD, and/or alleviate one or more symptoms of PTSD in an individual by obtaining a biological sample from the individual at risk for PTSD or suffering from PTSD; processing a cell obtained from the biological sample to produce a test cell; contacting the test cell with a glucocorticoid to produce a glucocorticoid-induced response; contacting the test cell with one or more test agents; detecting the expression and/or activity of one or more genes of the glucocorticoid-induced response (e.g., genes of Table 1 and/or Table 2); and if the one or more test agents modifies the expression and/or activity of one or more genes of the glucocorticoid-induced response (e.g., genes of Table 1 and/or Table 2) compared to a suitable control (e.g., a control with substantially no test agent), identifying the test agent as a compound that does reduce the risk of an individual developing PTSD, reduce the risk of an individual developing one or more symptoms of PTSD, and/or alleviate one or more symptoms of PTSD in an individual. [0099] These methods may be carried out generally as described above or as known in the art with respect to sample collection and assay format. [00100] Alternatively, for example, these methods may be carried out by obtaining cells from individuals at risk for PTSD or suffering from PTSD; contacting the cells with one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) test agents; detecting the expression and/or activity of one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) genes of the glucocorticoid response (e.g., genes of Table 1 and/or Table 2) in the sample and/or determining if the test agent reduces the transcriptional profile of the PTSD- dependent glucocorticoid response gene signature; and making a prediction about whether a test agent may reduce the risk of an individual developing PTSD, reduce the risk of an individual developing one or more symptoms of PTSD, and/or alleviate one or more symptoms of PTSD in an individual. The method also can be used to predict whether an individual, who has been diagnosed with PTSD, will respond positively to one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) agents that modify the glucocorticoid response (e.g., a glucocorticoid receptor antagonist). [00101] In some embodiments, the method includes processing a cell obtained from the biological sample to produce a test cell. [00102] In some embodiments, the method further includes contacting the biological sample or cells with a glucocorticoid (e.g., dexamethasone or hydrocortisone) prior to detecting the expression level and/or activity of the one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) genes of the glucocorticoid response. [00103] A prediction of a positive response refers to a case where the PTSD symptoms will be alleviated as a result of the one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) agents that modify the glucocorticoid response (e.g., a glucocorticoid receptor antagonist).In the methods of predicting response to one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) agents that modify the glucocorticoid response (e.g., a glucocorticoid receptor antagonist), the transcriptional profile of the PTSD-dependent glucocorticoid response gene signature can be determined relative to a control value. A control value can be a range or average value from a normal individual or a population of normal individuals; a value from a sample from an individual or population of individuals who have undergone one or more agents that modify the glucocorticoid response (e.g., a glucocorticoid receptor antagonist) and have reduced symptoms following therapy; or a value from the same individual before the individual was diagnosed or before the individual started treatment. [00104] Methods of the present disclosure can be used to predict whether an individual will be responsive to one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) agents that modify the glucocorticoid response (e.g., a glucocorticoid receptor antagonist), for example, an increase in the level (e.g., an increase by 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%, 90%, 95%, 100%, 150%, 200%, 300%, 400%, 500%, or more, or an increase by more than 1.2-fold, 1.4-fold, 1.5-fold, 1.8- fold, 2.0-fold, 3.0-fold, 3.5-fold, 4.5-fold, 5.0-fold, 10-fold, 15-fold, 20-fold, 30-fold, 40-fold, 50-fold, 100-fold, 1000-fold, or more, as compared to a reference) of the expression and/or activity of biomarker(s) (e.g., a gene of Table 1 and/or Table 2) may indicate a positive response to one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) agents that modify the glucocorticoid response (e.g., a glucocorticoid receptor antagonist). Similarly, a decrease in the level (e.g., a decrease by 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%, 90%, 95%, 100%, 150%, 200%, 300%, 400%, 500%, or more; or a decrease by less than 0.01-fold, 0.02-fold, 0.1-fold, 0.3-fold, 0.5-fold, 0.8-fold, or less, as compared to a reference) of the expression and/or activity of biomarker(s) (e.g., a gene of Table 1 and/or Table 2) may indicate a positive response to one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) agents that modify the glucocorticoid response (e.g., a glucocorticoid receptor antagonist). [00105] Methods of the present disclosure can be used to predict an individual’s response to one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) agents that modify the glucocorticoid response (e.g., a glucocorticoid receptor antagonist) and classify the individual as a “responder,” e.g., an individual with a glucocorticoid response gene signature indicative of a positive response to one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) agents that modify the glucocorticoid response (e.g., a glucocorticoid receptor antagonist), or a “non-responder,” e.g., an individual with a glucocorticoid response gene signature indicative of a poor response to one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) agents that modify the glucocorticoid response (e.g., a glucocorticoid receptor antagonist) (e.g., an individual that may benefit from a different therapy other than, or in addition to, the respective one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) agents that modify the glucocorticoid response). [00106] The prediction can be made prior to administration of a first agent that modifies the glucocorticoid response (e.g., a glucocorticoid receptor antagonist). Alternatively, the prediction can be made after administration of the first agent that modifies the glucocorticoid response (e.g., a glucocorticoid receptor antagonist), or after administration of a first agent that modifies the glucocorticoid response (e.g., a glucocorticoid receptor antagonist) but before a second agent that modifies the glucocorticoid response. Furthermore, the prediction can be made at any time during the course of one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) agents that modify the glucocorticoid response (e.g., a glucocorticoid receptor antagonist). [00107] The methods described herein can also be used to monitor PTSD status (e.g., progression or regression) during therapy or to optimize dosage of one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) therapeutic agents for an individual. For example, alterations (e.g., an increase or a decrease as compared to either the positive reference sample or the level diagnostic for PTSD) can be detected to indicate an improvement in PTSD status. In this embodiment, the levels of the glucocorticoid response gene signature may be measured repeatedly as a method of not only diagnosing disorder, but also monitoring the treatment, prevention, or management of the disorder. [00108] In order to monitor the status of PTSD in an individual, individual samples may be compared to reference samples taken early in the diagnosis of the disorder. Such monitoring may be useful, for example, in assessing the efficacy of a particular therapeutic agent (e.g., a glucocorticoid receptor antagonist) in an individual, determining dosages, or in assessing disease progression or status. For example, the expression and/or activity of any of the genes described herein, or any combination thereof can be monitored in an individual, and as the expression levels or activities increase or decrease, relative to control, the dosage or administration of therapeutic agents may be adjusted. [00109] The methods can also be used to determine the proper dosage (e.g., the therapeutically effective amount) of a therapeutic agent for the individual, the proper type of therapeutic agent, or whether a therapy should be administered. Methods of Treatment [00110] The present disclosure also features a method of treating an individual diagnosed with PTSD including administering to the individual diagnosed with PTSD a therapeutically effective amount of a psychedelic agent and/or a glucocorticoid receptor antagonist. [00111] The present disclosure also features a method for treatment of PTSD in an individual by obtaining a biological sample (e.g., blood cell (e.g., peripheral blood mononuclear cell), neuron (e.g., glutamatergic neuron), fibroblast, or hiPSC) from the individual suspected of being at risk for PTSD, suffering from one or more symptoms associated with PTSD, or diagnosed with PTSD; detecting the expression and/or activity of one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) genes of the glucocorticoid response (e.g., one or more genes of Table 1 and/or Table 2); identifying an individual at risk for PTSD or diagnosed with PTSD when the expression and/or activity of the one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) genes of the glucocorticoid response are modified relative to a suitable control (e.g., a control with substantially no test agent); and administering to the individual identified as at risk for PTSD or diagnosed with PTSD one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) psychedelic agents and/or agents that modify the glucocorticoid response (e.g., a glucocorticoid receptor antagonist). [00112] In some embodiments, the method includes processing a cell obtained from the biological sample to produce a test cell. [00113] In some embodiments, the method further includes contacting the biological sample or cells with a glucocorticoid (e.g., dexamethasone or hydrocortisone) prior to detecting the expression level and/or activity of one or more genes of the glucocorticoid response. [00114] For example, in some embodiments, the method includes treating an individual at risk for PTSD, suffering from one or more symptoms associated with PTSD, and/or diagnosed with PTSD by obtaining a biological sample from the individual suspected of being at risk for PTSD, suffering from one or more symptoms associated with PTSD, or diagnosed with PTSD; processing a cell obtained from the biological sample to produce a test cell; contacting the test cell with a glucocorticoid (e.g., dexamethasone or hydrocortisone) to produce a glucocorticoid-induced response; detecting the expression and/or activity of one or more genes of the glucocorticoid-induced response (e.g., one or more genes of Table 1 and/or Table 2); identifying the individual as at risk for PTSD or diagnosing the individual with PTSD when the expression and/or activity of the one or more genes of the glucocorticoid- induced response are modified relative to a suitable control (e.g., a control with substantially no test agent); and administering to the individual identified as at risk for PTSD or diagnosed with PTSD one or more psychedelic agents and/or agents that modify the glucocorticoid- induced response (e.g., a glucocorticoid receptor antagonist). [00115] In some embodiments, the method includes treating an individual at risk for developing PTSD, diagnosed with PTSD, or experiencing one or more symptoms associated with PTSD by administering to the individual one more psychedelic agents and/or agents that modify the glucocorticoid-induced response (e.g., a glucocorticoid receptor antagonist). [00116] The methods of the disclosure also include prophylactic treatments. For example, the disclosure also provides a method of preventing PTSD in an individual at risk for PTSD including a therapeutically effective amount of a psychedelic agent and/or glucocorticoid receptor antagonist. [00117] Examples of suitable routes of administration of agents (e.g., psychedelic agents and/or glucocorticoid receptor antagonist) include systemic and local routes of administration, including parenteral and non-parenteral routs. For example, suitable routes of administration may include intravenous (IV), intradermal, inhalation, transdermal, topical, transmucosal, intrathecal, and rectal administration. Samples and gene expression analyses Nucleic Acid Detection [00118] To carry out certain methods of the disclosure, a biological sample (e.g., blood cell (e.g., peripheral blood mononuclear cell), neuron (e.g., glutamatergic neuron), fibroblast, or hiPSC) can be obtained by any method known in the art. For instance, samples from an individual may be obtained by biopsy collection, skin punch, venipuncture, resection, bronchoscopy, fine needle aspiration, bronchial brushings, or from sputum, pleural fluid, urine, or blood, such as serum or plasma. Genes or the proteins encoded by such can be detected in these samples. Samples may also include, but are not limited to, neurons and blood cells. For example, in some embodiments, the biological sample (e.g., blood cell (e.g., peripheral blood mononuclear cell), neuron (e.g., glutamatergic neuron), fibroblast, or hiPSCs) is collected by biopsy collection, which may include a skin punch and/or blood processing. Following collection, a biological sample, such as skin fibroblasts, may be induced into pluripotency. Following the collection of a sample, such as a neuron (e.g., glutamatergic neuron), a blood cell (e.g., peripheral blood mononuclear cell), or a human induced pluripotent stem cell (hiPSC), screening of the sample can be conducted. [00119] In some embodiments, a cell obtained from the biological sample may be processed to produce a test cell. [00120] In some embodiments, processing the cell obtained from the biological sample includes dedifferentiating the cell to produce an iPSC. In certain embodiments, the iPSC is differentiated to produce a test cell. [00121] In some embodiments, processing the cell obtained from the biological sample includes automated reprogramming of the cell obtained from the biological sample, such as with an automated system for automating one or more steps including: isolating somatic cells from tissue samples, producing iPSC lines from adult differentiated cells by reprogramming such cells, identifying the pluripotent reprogrammed adult cells among other cells, and expanding the identified reprogrammed cells (see e.g., U.S. Patent Number US 10,968,435 incorporated herein in its entirety). [00122] By screening such biological samples (e.g., hiPSC), a simple early diagnosis or differential diagnosis can be achieved for PTSD. In addition, the progress of therapy can be monitored by testing such biological samples for the expression and/or activity of one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) genes of the glucocorticoid response. Furthermore, the prediction of outcome or response to therapy can similarly be tested using such biological samples for the transcriptional profile of a PTSD-dependent glucocorticoid response gene signature. For example, in some embodiments, the methods herein include detecting the expression and/or activity of one or more genes of the glucocorticoid-induced response (e.g., one or more genes of Table 1 and/or Table 2). [00123] Nucleic acid expression and/or activity above can be characterized using a variety of assays known to those skilled in the art. For example, a gene can be characterized by conventional assays, including but not limited to those assays described below, to determine whether it is expressed. [00124] Nucleic acid-based datasets suitable for analysis in conjunction with the compositions and methods of the present disclosure include gene expression profiles. Such profiles may include whole transcriptome sequencing data (e.g., RNA-Seq data), panels of mRNAs, noncoding RNAs, or any other nucleic acid sequence that may be expressed from genomic DNA. Other nucleic acid datasets suitable for use with the compositions and methods of the present disclosure may include expression data collected by imaging-based techniques (e.g., Northern blotting or Southern blotting). Northern blot analysis is a conventional technique well known in the art and is described, for example, in Molecular Cloning, a Laboratory Manual, second edition, 1989, Sambrook, Fritch, Maniatis, Cold Spring Harbor Press, 10 Skyline Drive, Plainview, N.Y.11803-2500. Typical protocols for evaluating the status of genes and gene products are found, for example in Ausubel et al., eds., 1995, Current Protocols In Molecular Biology, Units 2 (Northern Blotting), 4 (Southern Blotting), 15 (Immunoblotting) and 18 (PCR Analysis). [00125] Gene expression profiles to be analyzed in conjunction with evaluating the compositions described herein may include, for example, microarray data or nucleic acid sequencing data produced by a sequencing method known in the art (e.g., Sanger sequencing and next-generation sequencing methods, also known as high-throughput sequencing or deep sequencing). Exemplary next generation sequencing technologies include, without limitation, Illumina sequencing, Ion Torrent sequencing, 454 sequencing, SOLiD sequencing, and nanopore sequencing platforms. Additional methods of sequencing known in the art can also be used. For instance, mRNA expression levels may be determined using RNA-Seq (e.g., as described in Mortazavi et al., Nat. Methods 5:621-628, 2008, the disclosure of which is incorporated herein by reference in their entirety). RNA-Seq is a robust technology for monitoring expression by direct sequencing the RNA molecules in a sample. Briefly, this methodology may involve fragmentation of RNA to an average length of 200 nucleotides, conversion to cDNA by random priming, and synthesis of double-stranded cDNA (e.g., using the Just cDNA DoubleStranded cDNA Synthesis Kit from Agilent Technology). Then, the cDNA is converted into a molecular library for sequencing by addition of sequence adapters for each library (e.g., from Illumina®/Solexa), and the resulting 50-100 nucleotide reads are mapped onto the genome. [00126] Gene expression levels may be determined using microarray-based platforms, as microarray technology offers high resolution. Details of various microarray methods can be found in the literature. See, for example, U.S. Pat. No.6,232,068 and Pollack et al., Nat. Genet.23:41-46, 1999, the disclosures of each of which are incorporated herein by reference in their entirety. Using nucleic acid microarrays, mRNA samples are reverse transcribed and labeled to generate cDNA. The probes can then hybridize to one or more complementary nucleic acids arrayed and immobilized on a solid support. The array can be configured, for example, such that the sequence and position of each member of the array is known. Hybridization of a labeled probe with a particular array member indicates that the sample from which the probe was derived expresses that gene. Expression level may be quantified according to the amount of signal detected from hybridized probe-sample complexes. A typical microarray experiment involves the following steps: 1) preparation of fluorescently labeled target from RNA isolated from the sample, 2) hybridization of the labeled target to the microarray, 3) washing, staining, and scanning of the array, 4) analysis of the scanned image and 5) generation of gene expression profiles. One example of a microarray processor is the Affymetrix GENECHIP® system, which is commercially available and includes arrays fabricated by direct synthesis of oligonucleotides on a glass surface. Other systems may be used as known to one skilled in the art. [00127] Amplification-based assays also can be used to measure the expression level of one or more markers (e.g., genes). In such assays, the nucleic acid sequences of the gene act as a template in an amplification reaction (for example, PCR, such as qPCR). In a quantitative amplification, the amount of amplification product is proportional to the amount of template in the original sample. Comparison to appropriate controls provides a measure of the expression level of the gene, corresponding to the specific probe used, according to the principles described herein. Methods of real-time qPCR using TaqMan probes are well known in the art. Detailed protocols for real-time qPCR are provided, for example, in Gibson et al., Genome Res.6:995-1001, 1996, and in Heid et al., Genome Res.6:986-994, 1996, the disclosures of each of which are incorporated herein by reference in their entirety. Levels of gene expression as described herein can be determined by RT-PCR technology. Probes used for PCR may be labeled with a detectable marker, such as, for example, a radioisotope, fluorescent compound, bioluminescent compound, a chemiluminescent compound, metal chelator, or enzyme. [00128] In some embodiments, the method includes sequencing RNA. Any suitable RNA sequencing method may be used, such as, for example, mRNA-Seq, total RNA-Seq, strand- specific RNA-Seq, small RNA-Seq, ultra-low input RNA-Seq, single-cell RNA-Seq, and Iso- Seq. RNA used for sequencing may be derived from a biological sample. In some embodiments, RNA is derived from a biological sample (e.g., blood cell (e.g., peripheral blood mononuclear cell), neuron (e.g., glutamatergic neuron), fibroblast, or hiPSC). [00129] In some embodiments, the method further includes prior to determining the expression level, extracting mRNA from the biological sample (e.g., blood cell (e.g., peripheral blood mononuclear cell), neuron (e.g., glutamatergic neuron), fibroblast, or hiPSC) and reverse transcribing the mRNA into cDNA to obtain a treated biological sample (e.g., blood cell (e.g., peripheral blood mononuclear cell), neuron (e.g., glutamatergic neuron), fibroblast, or hiPSC). [00130] In certain embodiments, the mRNA level is determined by an amplification-based assay (e.g., PCR, quantitative PCR, or real-time quantitative PCR), amplification-free assay (e.g., Nanostring), microdroplet based assay, nanopore based assay, or bead based assays (e.g., Luminex, nanoparticles, Nanosphere). [00131] Next generation sequencing methods may also be used with the methods of the present disclosure. Next generation sequencing methods are sequencing technologies that parallelize the sequencing process, producing thousands or millions of sequences concurrently (see, for example, Hall, J. Exp. Biol.209(Pt.9):1518-1525 (2007) for a review of next generation methods). Next generation sequencing methods include, but are not limited to, polony sequencing, 454 pyrosequencing, Illumina (Solexa) sequencing, SOLiD sequencing, Ion Torrent semiconductor sequencing, DNA nanoball sequencing, Heliscope single molecule sequencing, single molecule real time sequencing, nanopore DNA sequencing (see, for example, Dela Torre et al. Nanotechnology, 23(38):385308, 2012), tunneling currents DNA sequencing (see, for example, Massimiliano, Nanotechnology, 24:342501, 2013), sequencing by hybridization (see, for example, Qin et al. PLoS One, 7(5):e35819, 2012), sequencing with mass spectrometry (see, for example, Edwards et al. Mutation Research, 573(1-2):3-12, 2005), microfluidic Sanger sequencing (see, for example, Kan et al. Electrophoresis, 25(21-22):3564-3588, 2004), microscopy-based sequencing (see, for example, Bell et al. Microscopy and microanalysis: the official journal of Microscopy Society of America, Microbeam Analysis Society, Microscopical Society of Canada, 18(5):1-5, 2012), and RNA polymerase sequencing (see, for example, Pareek et al. J. Applied Genetics, 52(4):413-415, 2011). [00132] In some embodiments, the method includes sequencing RNA derived from the biological sample. For example, in some embodiments, the method incudes detecting a transcriptional profile of a glucocorticoid-induced response. In some embodiments, the method includes assessing epigenetic changes of the one or more genes of the glucocorticoid-induced response (e.g., one or more genes of Table 1 and/or Table 2). Assessing epigenetic changes may be performed by methods known in the art, such as by a chromatin immunoprecipitation assay (ChiP), among others (for a review, see e.g., DeAngelis, J. Tyson, Woodrow J. Farrington, and Trygve O. Tollefsbol. Molecular biotechnology 38.2 (2008): 179-183, incorporated herein in its entirety by reference). [00133] For example, DNA sequencing and the use of methylation-sensitive primers (MSPs) are two commonly used techniques to analyze bisulfite-treated DNA for assessing epigenetic changes, as bisulfite modification of DNA enables the analysis of changes in methylation patterns. The differences in bisulfite-based methylation assays arise from the manner in which bisulfite-modified DNA is analyzed. Bisulfite modification converts nonmethylated cytosines to uracils, which are then converted to thymines during DNA amplification by PCR, whereas methylated cytosines are protected from bisulfite modification. Sequencing analysis of bisulfite-modified DNA can be used to reveal the methylation status of specific cytosines, whereas MSPs can be used to quickly assess a large number of CpG islands. [00134] Additionally, single nucleotide primer extension (SnuPE) provide yet another means to analyze bisulfite-modified DNA. The extension of an oligonucleotide to the 5’ end of a CpG site using dideoxycytidines (ddCTP) or dideoxythymidine (ddTTP) followed by real-time PCR, allows for a quantitative assessment of methylation patterns and can be applied to multiple sites simultaneously. A semi-quantitative method known as methylation sensitive-single strand conformation analysis (MS-SSCA) can also be used to obtain an overall picture of DNA methylation. MS-SSCA can be applied across a broad range of samples and can be used to assess the ratio of methylated to nonmethylated DNA. [00135] Digestion of genomic DNA with endonucleases that differ in their methylation sensitivities is yet another method for obtaining a rough estimate of the totality of methylation. [00136] Alternatively, for example, there are many additional techniques to analyze changes in DNA methylation, with the optimal method depending on factors including, but not limited to, the availability of the DNA, total number of targets being analyzed, or the desired specificity. One assay to assess a large number of CpG islands is restriction landmark genomic scanning (RLGS). This method involves the radioactive labeling of nonmethylated sequences that are targets of methylation sensitive restriction enzymes [00137] The ChIP assay, which assesses changes in chromatin structure, comprises one of the most utilized assays in epigenetic research. ChIP assays monitor DNA-protein interactions and allow the chromatin structure surrounding a specific DNA sequence to be analyzed. A conventional ChIP (xChIP) uses formaldehyde to crosslink DNA and protein, followed by immunoprecipitation of DNA-protein complexes. Once the crosslinks are reversed, recovered DNA can then be analyzed using PCR. Another commonly used form of the ChIP assay is the native ChIP (nChIP). nChIP uses micrococcal nuclease digestion to prepare the chromatin for analysis. nChIP allows for modifications of histones, such as methylation or acetylation, to be assessed more accurately than with formaldehyde fixation; however, nChIP does not usually allow for assessment of proteins with a weak binding affinity for DNA. Most ChIP assays are semi-quantitative, although combining either ChIP assay with real-time PCR (Q-ChIP) can achieve a quantitative measurement of the amount of DNA bound to a specific protein. [00138] ChIP assays can also be combined with other epigenetic assays such as DNA bisulfite modification. DNA harvested from a ChIP assay can be treated with bisulfite, while MSPs can be used to assess changes in DNA methylation in a ChIP-MSP. Other useful techniques to assess genome-wide epigenetic changes includes the ChIP-on-Chip assay that utilizes traditional ChIP protocols combined with microarray analysis. [00139] In addition to ChIP, many other assays exist that can be used to assess chromatin structure. For example, DnaseI hypersensitivity assays can be used if a more general determination of the changes chromatin has undergone is desired. DnaseI hypersensitivity sites are usually located in or around promoter regions thereby allowing for mapping of transcriptionally active versus inactive chromatin. One useful technique to assess changes in chromatin structure is the use of the deacetylating agent trichostatin A (TSA). [00140] In some embodiments, RNA is derived from cells. In some embodiments, the cell is a neuronal cell (e.g., glutamatergic neuron) or a blood cell (e.g., peripheral blood mononuclear cell). For example, in some embodiments, the RNA is isolated from a neuronal cell (e.g., glutamatergic neuron). In some embodiments, the RNA is isolated from a blood cell (e.g., peripheral blood mononuclear cell). [00141] In some embodiments, the RNA is isolated from a human induced pluripotent stem cell (hiPSC). For instance, RNA may be isolated from a hiPSC induced glutamatergic neuron. Protein Detection [00142] Gene expression can additionally be determined by measuring the concentration or relative abundance of a corresponding protein product encoded by a gene of interest. Protein levels can be assessed using standard detection techniques known in the art. Examples of protein expression analysis that generate data suitable for use with the methods described herein include, without limitation, proteomics approaches, immunohistochemical and/or western blot analysis, immunoprecipitation, molecular binding assays, ELISA, enzyme-linked immunofiltration assay (ELIFA), mass spectrometry, mass spectrometric immunoassay, and biochemical enzymatic activity assays. In particular, proteomics methods can be used to generate large-scale protein expression datasets in multiplex. Proteomics methods may utilize mass spectrometry to detect and quantify polypeptides (e.g., proteins) and/or peptide microarrays utilizing capture reagents (e.g., antibodies) specific to a panel of target proteins to identify and measure expression levels of proteins expressed in a sample (e.g., a single cell sample or a multi-cell population). [00143] For example, in some embodiments, the sample may be contacted with an antibody specific for the target protein under conditions sufficient for an antibody-protein complex to form, and detection of the complex. The presence of the biomarker may be detected in a number of ways, such as by Western blotting or ELISA procedures using any of a wide variety of tissues or samples, including plasma or serum. A wide range of immunoassay techniques using such an assay format are available, see, e.g., U.S. Pat. Nos. 4,016,043, 4,424,279, and 4,018,653. These include both single-site and two-site or “sandwich” assays of the noncompetitive types, as well as traditional competitive binding assays. These assays also include direct binding of a labeled antibody to a target biomarker. [00144] Another method involves immobilizing the target biomarkers (e.g., on a solid support) and then exposing the immobilized target to a specific antibody, which may or may not contain a label. Depending on the amount of target and the strength of the label’s signal, a bound target may be detectable by direct labeling with the antibody. Alternatively, a second labeled antibody, specific to the first antibody is exposed to the target-first antibody complex to form a target-first antibody-second antibody tertiary complex. The complex is detected by the signal emitted by a label, e.g., an enzyme, a fluorescent label, a chromogenic label, a radionuclide containing molecule (i.e., a radioisotope), or a chemiluminescent molecule. [00145] Variations on the forward assay include a simultaneous assay, in which both sample and labeled antibody are added simultaneously to a bound antibody. These techniques are well known to those skilled in the art, including any minor variations as will be readily apparent. In a typical forward sandwich assay, a first antibody having specificity for the biomarker is either covalently or passively bound to a solid surface (e.g., a glass or a polymer surface, such as those with solid supports in the form of tubes, beads, discs, or microplates), and a second antibody is linked to a label that is used to indicate the binding of the second antibody to the molecular marker. [00146] In alternative methods, the expression of a protein in a sample may be examined using immunohistochemistry (“IHC”) and staining protocols. IHC staining of tissue sections has been shown to be a reliable method of assessing or detecting presence of proteins in a sample. IHC and immunofluorescence techniques use an antibody to probe and visualize cellular antigens in situ, generally by chromogenic or fluorescent methods. The tissue sample may be fixed (i.e., preserved) by conventional methodology (see, e.g., “Manual of Histological Staining Method of the Armed Forces Institute of Pathology,” 3rd edition (1960) Lee G. Luna, HT (ASCP) Editor, The Blakston Division McGraw-Hill Book Company, New York; The Armed Forces Institute of Pathology Advanced Laboratory Methods in Histology and Pathology (1994) Ulreka V. Mikel, Editor, Armed Forces Institute of Pathology, American Registry of Pathology, Washington, D.C.). One of skill in the art will appreciate that the choice of a fixative is determined by the purpose for which the sample is to be histologically stained or otherwise analyzed. By way of example, neutral buffered formalin, Bouin’s or formaldehyde, may be used to fix a sample. Generally, the sample is first fixed and is then dehydrated through an ascending series of alcohols, infiltrated and embedded with paraffin or other sectioning media so that the tissue sample may be sectioned. Alternatively, one may section the tissue and fix the sections obtained. The primary and/or secondary antibody used for immunohistochemistry typically will be labeled with a detectable moiety, such as a radioisotope, a colloidal gold particle, a fluorescent label, a chromogenic label, or an enzyme-substrate label. [00147] Exemplary peptide microarrays have a substrate-bound plurality of polypeptides, the binding of an oligonucleotide, a peptide, or a protein to each of the plurality of bound polypeptides being separately detectable. Alternatively, the peptide microarray may include a plurality of binders, including but not limited to monoclonal antibodies, polyclonal antibodies, phage display binders, yeast two-hybrid binders, aptamers, which can specifically detect the binding of specific oligonucleotides, peptides, or proteins. Examples of peptide arrays may be found in U.S. Pat. Nos.6,268,210, 5,766,960, and 5,143,854, the disclosures of each of which are incorporated herein by reference in their entirety. [00148] Alternatively, the levels of biomarkers may be detected without the use of binding agents. In some instances, biological sample (e.g., blood cell (e.g., peripheral blood mononuclear cell), neuron (e.g., glutamatergic neuron), fibroblast, or hiPSCs) as described herein are analyzed, for example, by one or more, enzymatic methods, chromatographic methods, mass spectrometry (MS) methods, chromatographic methods followed by MS, electrophoretic methods, electrophoretic methods followed by MS, nuclear magnetic resonance (NMR) methods, and combinations thereof. In some instances, the biological sample (e.g., blood cell (e.g., peripheral blood mononuclear cell), neuron (e.g., glutamatergic neuron), fibroblast, or hiPSC) is treated with one or more enzymes (e.g., trypsin). Exemplary chromatographic methods include, but are not limited to, Strong Anion Exchange chromatography using Pulsed Amperometric Detection (SAX-PAD), liquid chromatography (LC), high performance liquid chromatography (HPLC), ultra performance liquid chromatography (U PLC), thin layer chromatography (TLC), amide column chromatography, and combinations thereof. Exemplary mass spectrometry (MS) include, but are not limited to, tandem MS, LC-MS, LC-MS/MS, matrix assisted laser desorption ionisation mass spectrometry (MALDI-MS), Fourier transform mass spectrometry (FTMS), ion mobility separation with mass spectrometry (IMS-MS), electron transfer dissociation (ETD-MS), Multiple Reaction Monitoring (MRM), and combinations thereof. Exemplary electrophoretic methods include, but are not limited to, capillary electrophoresis (CE), CE-MS, gel electrophoresis, agarose gel electrophoresis, acrylamide gel electrophoresis, SDS- polyacrylamide gel electrophoresis (SDS-PAGE) followed by Western blotting using antibodies that recognize specific glycan structures, and combinations thereof. Exemplary nuclear magnetic resonance (NMR) include, but are not limited to, one-dimensional NMR (1 D-NMR), two-dimensional NMR (2D-NMR), correlation spectroscopy magnetic-angle spinning NMR (COSY-NMR), total correlated spectroscopy NMR (TOCSY-NMR), heteronuclear single-quantum coherence NMR (HSQC-NM R), heteronuclear multiple quantum coherence (HMQC-NMR), rotational nuclear overhauser effect spectroscopy NMR (ROESY-NMR), nuclear overhauser effect spectroscopy (NOESY-NMR), and combinations thereof. [00149] Mass spectrometry (MS) may be used in conjunction with the methods described herein to identify and characterize the gene expression profile of a single cell or multi-cell population. Any method of MS known in the art may be used to determine, detect, and/or measure a peptide or peptides of interest, e.g., LC-MS, ESI-MS, ESI-MS/MS, MALDI-TOF- MS, MALDI-TOF/TOF-MS, tandem MS, and the like. Mass spectrometers generally contain an ion source and optics, mass analyzer, and data processing electronics. Mass analyzers include scanning and ion-beam mass spectrometers, such as time-of-flight (TOF) and quadruple (Q), and trapping mass spectrometers, such as ion trap (IT), Orbitrap, and Fourier transform ion cyclotron resonance (FT-ICR), may be used in the methods described herein. Details of various MS methods can be found in the literature. See, for example, Yates et al., Annu. Rev. Biomed. Eng.11:49-79, 2009, the disclosure of which is incorporated herein by reference in its entirety. [00150] Prior to MS analysis, proteins in a sample can be first digested into smaller peptides by chemical (e.g., via cyanogen bromide cleavage) or enzymatic (e.g., trypsin) digestion. Complex peptide samples also benefit from the use of front-end separation techniques, e.g., 2D-PAGE, HPLC, RPLC, and affinity chromatography. The digested, and optionally separated, sample is then ionized using an ion source to create charged molecules for further analysis. Ionization of the sample may be performed, e.g., by electrospray ionization (ESI), atmospheric pressure chemical ionization (APCI), photoionization, electron ionization, fast atom bombardment (FAB)/liquid secondary ionization (LSIMS), matrix assisted laser desorption/ionization (MALDI), field ionization, field desorption, thermospray/plasmaspray ionization, and particle beam ionization. Additional information relating to the choice of ionization method is known to those of skill in the art. [00151] After ionization, digested peptides may then be fragmented to generate signature MS/MS spectra. Tandem MS, also known as MS/MS, may be particularly useful for methods described herein allowing for ionization followed by fragmentation of a complex peptide sample, such as a sample obtained from a multi-cell population described herein. Tandem MS involves multiple steps of MS selection, with some form of ion fragmentation occurring in between the stages, which may be accomplished with individual mass spectrometer elements separated in space or using a single mass spectrometer with the MS steps separated in time. In spatially separated tandem MS, the elements are physically separated and distinct, with a physical connection between the elements to maintain high vacuum. In temporally separated tandem MS, separation is accomplished with ions trapped in the same place, with multiple separation steps taking place over time. Signature MS/MS spectra may then be compared against a peptide sequence database (e.g., SEQUEST). Post-translational modifications to peptides may also be determined, for exampleby, by searching spectra against a database while allowing for specific peptide modifications. [00152] Any of the methods herein that rely upon protein measurement can also be adapted for use with the measurement of mRNA levels for the protein. The level of mRNA can be determined using methods known in the art. Methods to measure mRNA levels generally include, but are not limited to, sequencing, northern blotting, RT-PCR, gene array technology, and RNAse protection assays, as described above. Methods of contacting a test cell [00153] In some embodiments, the methods herein include contacting a test cell with a glucocorticoid (e.g., a glucocorticoid receptor agonist e.g., beclomethasone, betamethasone, budesonide, cortisone, dexamethasone, hydrocortisone, methylprednisolone, prednisolone, prednisone, and triamcinolone) to produce a glucocorticoid-induced response. For example, in some embodiments, the method includes contacting a test cell with a glucocorticoid receptor agonist. In some embodiments, the method includes contacting a test cell with beclomethasone to produce a glucocorticoid-induced response. In some embodiments, the method includes contacting a test cell with betamethasone to produce a glucocorticoid- induced response. In some embodiments, the method includes contacting a test cell with budesonide to produce a glucocorticoid-induced response. In some embodiments, the method includes contacting a test cell with cortisone to produce a glucocorticoid-induced response. In some embodiments, the method includes contacting a test cell with dexamethasone to produce a glucocorticoid-induced response. In some embodiments, the method includes contacting a test cell with hydrocortisone to produce a glucocorticoid-induced response. In some embodiments, the method includes contacting a test cell with methylprednisolone to produce a glucocorticoid-induced response. In some embodiments, the method includes contacting a test cell with prednisolone to produce a glucocorticoid-induced response. In some embodiments, the method includes contacting a test cell with prednisone to produce a glucocorticoid-induced response. In some embodiments, the method includes contacting a test cell with triamcinolone to produce a glucocorticoid-induced response. [00154] In some embodiments, the glucocorticoid is dexamethasone or hydrocortisone. For example, in some embodiments, the glucocorticoid is dexamethasone. In some embodiments, the glucocorticoid is hydrocortisone. [00155] In some embodiments, contacting the test cell with a glucocorticoid is performed for a duration of from about 1 hour to about 96 hours (e.g., about 2 hours to about 95 hours, about 3 hours to about 90 hours, about 4 hours to about 80 hours, about 5 hours to about 70 hours, about 10 hours to about 60 hours, about 20 hours to about 50 hours, or about 30 hours to about 40 hours). For example, in some embodiments, contacting the test cell with a glucocorticoid is performed for a duration of from about 2 hours to about 95 hours. In some embodiments, contacting the test cell with a glucocorticoid is performed for a duration of from about 3 hours to about 90 hours. In some embodiments, contacting the test cell with a glucocorticoid is performed for a duration of from about 4 hours to about 80 hours. In some embodiments, contacting the test cell with a glucocorticoid is performed for a duration of from about 5 hours to about 70 hours. In some embodiments, contacting the test cell with a glucocorticoid is performed for a duration of from about 10 hours to about 60 hours. In some embodiments, contacting the test cell with a glucocorticoid is performed for a duration of from about 20 hours to about 50 hours. In some embodiments, contacting the test cell with a glucocorticoid is performed for a duration of from about 30 hours to about 40 hours. [00156] In some embodiments, the glucocorticoid has a concentration of from about 1 nM to about 10 µM (e.g., about 10 nM to about 9 µM, about 50 nM to about 8 µM, about 100 nM to about 7 µM, about 1 µM to about 6 µM, about 2 µM to about 5 µM, about 3 µM to about 4 µM). For example, in some embodiments, the glucocorticoid has a concentration of from about 10 nM to about 9 µM. In some embodiments, the glucocorticoid has a concentration of from about 50 nM to about 8 µM. In some embodiments, the glucocorticoid has a concentration of from about 100 nM to about 7 µM. In some embodiments, the glucocorticoid has a concentration of from about 1 µM to about 6 µM. In some embodiments, the glucocorticoid has a concentration of from about 2 µM to about 5 µM. In some embodiments, the glucocorticoid has a concentration of from about 3 µM to about 4 µM. Modifiers of the Glucocorticoid Response [00157] As used herein, “modifying the glucocorticoid response,” refers to modifying the formation or function of one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) gene products in the glucocorticoid response pathway. A gene product is functional if it fulfills its normal (wild-type) functions. Disruption of the gene product prevents expression or function. The gene product in the glucocorticoid response pathway may be inhibited by, e.g., removal of at least a portion of the gene from a genome of the individual, alternation of the gene to prevent expression of a gene product encoded by the gene, an interfering RNA, antagonism, or expression of a dominant negative factor by an exogenous gene. This inhibition can be achieved, for example by using nucleic acid molecules, siRNA, shRNA, miRNA, antisense oligonucleotides, nucleases, meganucleases, transcription activator-like effector nucleases, zinc-finger nucleases, a CRISPR associated protein, or an antagonist. Exemplary materials and methods for genetically modifying cells so as to disrupt the expression of one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) gene (e.g., a gene in the glucocorticoid response pathway) are detailed in US 8,518,701; US 9,499,808; and US 2021/0222143, the disclosures of which are incorporated herein by reference in their entirety. In certain embodiments, the modifier of the glucocorticoid response is an agent that modifies the activity and/or expression of the glucocorticoid receptor, such as, but not limited to a glucocorticoid receptor antagonist. In some embodiments, the glucocorticoid response is inhibited by a glucocorticoid receptor antagonist. Exemplary, non-limiting, antagonists for inhibiting the glucocorticoid response are known in the art. [00158] In some embodiments, provided methods include contacting a test cell with one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) agents that modify the glucocorticoid response (e.g., a glucocorticoid receptor antagonist). In some embodiments, contacting a test cell with one or more test agents may be performed for a duration of from about 1 hour to about 96 hours (e.g., about 2 hours to about 95 hours, about 3 hours to about 90 hours, about 4 hours to about 80 hours, about 5 hours to about 70 hours, about 10 hours to about 60 hours, about 20 hours to about 50 hours, or about 30 hours to about 40 hours). For example, in some embodiments, contacting the test cell with one or more agents that modify the glucocorticoid response is performed for a duration of from about 2 hours to about 95 hours. In some embodiments, contacting the test cell with one or more agents that modify the glucocorticoid response is performed for a duration of from about 3 hours to about 90 hours. In some embodiments, contacting the test cell with one or more agents that modify the glucocorticoid response is performed for a duration of from about 4 hours to about 80 hours. In some embodiments, contacting the test cell with one or more agents that modify the glucocorticoid response is performed for a duration of from about 5 hours to about 70 hours. In some embodiments, contacting the test cell with one or more agents that modify the glucocorticoid response is performed for a duration of from about 10 hours to about 60 hours. In some embodiments, contacting the test cell with one or more agents that modify the glucocorticoid response is performed for a duration of from about 20 hours to about 50 hours. In some embodiments, contacting the test cell with one or more agents that modify the glucocorticoid response is performed for a duration of from about 30 hours to about 40 hours. [00159] In some embodiments, the agent that modifies the glucocorticoid response has a concentration of from about 1 nM to about 10 µM (e.g., about 10 nM to about 9 µM, about 50 nM to about 8 µM, about 100 nM to about 7 µM, about 1 µM to about 6 µM, about 2 µM to about 5 µM, about 3 µM to about 4 µM). For example, in some embodiments, the agent that modifies the glucocorticoid response has a concentration of from about 10 nM to about 9 µM. In some embodiments, the agent that modifies the glucocorticoid response has a concentration of from about 50 nM to about 8 µM. In some embodiments, the agent that modifies the glucocorticoid response has a concentration of from about 100 nM to about 7 µM. In some embodiments, the agent that modifies the glucocorticoid response has a concentration of from about 1 µM to about 6 µM. In some embodiments, the agent that modifies the glucocorticoid response has a concentration of from about 2 µM to about 5 µM. In some embodiments, the agent that modifies the glucocorticoid response has a concentration of from about 3 µM to about 4 µM. [00160] In some embodiments, an agent that modifies the glucocorticoid response is administered via a parenteral or a non-parenteral route. For example, in some embodiments, an agent that modifies the glucocorticoid response is administered via a parenteral route. In some embodiments, an agent that modifies the glucocorticoid response is administered via a non-parenteral route. Agents Glucocorticoid Receptor Antagonists [00161] The compositions and methods of the present disclosure may make use of glucocorticoid receptor antagonists. Glucocorticoid receptor (GR) antagonists bind to the receptor and prevent glucocorticoid receptor agonists from binding and eliciting GR mediated events, including transcription. [00162] In some embodiments, the glucocorticoid receptor antagonist is a steroidal glucocorticoid receptor antagonist, such as, for example, mifepristone, monodemethylated mifepristone, didemethylated mifepristone, 17-α-[3'-hydroxy-propynyl] mifepristone, ulipristal, CDB-3877, CDB-3963, CDB-3236, CDB-4183, cortexolone, dexamethasone- oxetanone, 19-nordeoxycorticosterone, 19-norprogesterone, cortisol-21-mesylate; dexamethasone-21-mesylate, 11(-(4-dimethylaminoethoxyphenyl)-17(-propynyl-17(- hydroxy-4,9-estradien-3one, and 17(-hydroxy-17(-19-(4-methylphenyl)androsta-4,9(11)- dien-3-one. For example, in some embodiments, the glucocorticoid receptor antagonist is mifepristone. In some embodiments, the glucocorticoid receptor antagonist is monodemethylated mifepristone. In some embodiments, the glucocorticoid receptor antagonist is didemethylated mifepristone. In some embodiments, the glucocorticoid receptor antagonist is 17-α-[3'-hydroxy-propynyl] mifepristone. In some embodiments, the glucocorticoid receptor antagonist is ulipristal. In some embodiments, the glucocorticoid receptor antagonist is CDB-3877. In some embodiments, the glucocorticoid receptor antagonist is CDB-3963. In some embodiments, the glucocorticoid receptor antagonist is CDB-3236. In some embodiments, the glucocorticoid receptor antagonist is CDB-4183. In some embodiments, the glucocorticoid receptor antagonist is cortexolone. In some embodiments, the glucocorticoid receptor antagonist is dexamethasone-oxetanone. In some embodiments, the glucocorticoid receptor antagonist is 19-nordeoxycorticosterone. In some embodiments, the glucocorticoid receptor antagonist is 19-norprogesterone. In some embodiments, the glucocorticoid receptor antagonist is cortisol-21-mesylate. In some embodiments, the glucocorticoid receptor antagonist is dexamethasone-21-mesylate. In some embodiments, the glucocorticoid receptor antagonist is 11(-(4-dimethylaminoethoxyphenyl)- 17(-propynyl-17(-hydroxy-4,9-estradien-3one. In some embodiments, the glucocorticoid receptor antagonist is 17(-hydroxy-17(-19-(4-methylphenyl)androsta-4,9(11)-dien-3-one. [00163] In some embodiments, the glucocorticoid receptor antagonist is a non-steroidal glucocorticoid receptor antagonist, such as, for example, N-(2-[4,4',441 - trichlorotrityl]oxyethyl)morpholine; 1-(2[4,4',4"-trichlorotrityl]oxyethyl)-4-(2- hydroxyethyl)piperazine dimaleate; N-([4,4',4"]-trichlorotrityl)imidazole; 9-(3-mercapto- 1,2,4-triazolyl)-9-phenyl-2,7-difluorofluorenone; 1-(2-chlorotrityl)-3,5-dimethylpyrazole; 4- (morpholinomethyl)-A-(2-pyridyl)benzhydrol; 5-(5-methoxy-2-(N-methylcarbamoyl)- phenyl)dibenzosuberol; N-(2-chlorotrityl)-L-prolinol acetate; 1-(2-chlorotrityl)-1,2,4-triazole; 1,S-bis(4,4', 4"-trichlorotrityl)-1,2,4-triazole-3-thiol; 4.alpha.(S)-Benzyl-2(R)-chloroethynyl- 1,2,3,4,4.alpha.,9,10,10.alpha; (R)-octahydro-phenanthrene-2,7-diol (CP 394531); 4.alpha. (S)-Benzyl-2(R)-prop-1-ynyl-1,2,3,4,4.alpha.,9,10,10.alpha; (R)-octahydro-phenanthrene- 2,7-diol (CP-409069); trans-(1 R,2R)-3,4-dichloro-N-methyl-N-[2-1 pyrrolidinyl)cyclohexyl]; benzeneacetamide; bremazocine; ethylketocyclazocine; and naloxone. For example, in some embodiments, the glucocorticoid receptor antagonist is N-(2- [4,4',441 - trichlorotrityl]oxyethyl)morpholine. In some embodiments, the glucocorticoid receptor antagonist is 1-(2[4,4',4"-trichlorotrityl]oxyethyl)-4-(2-hydroxyethyl)piperazine dimaleate. In some embodiments, the glucocorticoid receptor antagonist is N-([4,4',4"]- trichlorotrityl)imidazole. In some embodiments, the glucocorticoid receptor antagonist is 9- (3-mercapto- 1,2,4-triazolyl)-9-phenyl-2,7-difluorofluorenone. In some embodiments, the glucocorticoid receptor antagonist is 1-(2-chlorotrityl)-3,5-dimethylpyrazole. In some embodiments, the glucocorticoid receptor antagonist is 4-(morpholinomethyl)-A-(2- pyridyl)benzhydrol. In some embodiments, the glucocorticoid receptor antagonist is 5-(5- methoxy-2-(N-methylcarbamoyl)-phenyl)dibenzosuberol. In some embodiments, the glucocorticoid receptor antagonist is N-(2-chlorotrityl)-L-prolinol acetate. In some embodiments, the glucocorticoid receptor antagonist is 1-(2-chlorotrityl)-1,2,4-triazole. In some embodiments, the glucocorticoid receptor antagonist is 1,S-bis(4,4', 4"-trichlorotrityl)- 1,2,4-triazole-3-thiol. In some embodiments, the glucocorticoid receptor antagonist is 4.alpha.(S)-Benzyl-2(R)-chloroethynyl-1,2,3,4,4.alpha.,9,10,10.alpha. In some embodiments, the glucocorticoid receptor antagonist is (R)-octahydro-phenanthrene-2,7-diol (CP 394531) , 4.alpha. In some embodiments, the glucocorticoid receptor antagonist is (S)-Benzyl-2(R)- prop-1-ynyl-1,2,3,4,4.alpha.,9,10,10.alpha. In some embodiments, the glucocorticoid receptor antagonist is (R)-octahydro-phenanthrene-2,7-diol (CP-409069). In some embodiments, the glucocorticoid receptor antagonist is trans-(1 R,2R)-3,4-dichloro-N-methyl-N-[2-1 pyrrolidinyl)cyclohexyl]benzeneacetamide. In some embodiments, the glucocorticoid receptor antagonist is bremazocine. In some embodiments, the glucocorticoid receptor antagonist is ethylketocyclazocine. In some embodiments, the glucocorticoid receptor antagonist is naloxone. Psychedelic Agents [00164] The compositions and methods of the present disclosure may make use of psychedelic agents. Psychedelics are a subclass of hallucinogenic drugs that trigger non- ordinary mental states (known as psychedelic experiences) and/or an apparent expansion of consciousness. Sometimes, psychedelic agents are called classic hallucinogens, serotonergic hallucinogens, or serotonergic psychedelics. Many psychedelic drugs fall into one of the three families of chemical compounds: tryptamines, phenethylamines, and lysergamides. [00165] In some embodiments, psychedelic agents of the disclosure include indoles (e.g., tryptamines (e.g., psilocin, psilocybin, bufotenin, baeocystin, aeruginascin, 5-MeO-DMT, N,N-dimethyltryptamine,5-bromo-DMT, N-methyl-N-ethyltryptamine, N-methyl-N- isopropyltryptamine, N-methyl-N-propyltryptamine, N,N-diethyltryptamine, N-ethyl-N- isopropyltryptamine, N-methyl-N-butyltryptamine, N-propyl-N-isopropyltryptamine, N,N- dipropyltryptamine, N,N-diisopropyltryptamine, N,N-diallyltryptamine, N,N- dibutyltryptamine, N-ethyltryptamine, N-methyltryptamine trimethyltryptamine, α- methyltryptamine, α-ethyltryptamine, α,N-DMT, α,N,N-trimethyltryptamine, ethocybin, 4- HO-MET, 4-HO-DET, 4-HO-MPT, 4-HO-MiPT, 4-HO-MALT4-HO-DPT, 4-HO-DiPT, 4- HO-DALT, 4-HO-DBT, 4-HO-DSBT, 4-HO-αMT, 4-HO-MPMI, 4-HO-TMT, 4-HO-1,N,N- TMT, 4-HO-5-MeO-DMT, 4-AcO-DMT, 4-AcO-MET, 4-AcO-MiPT, 4-AcO-MALT, 4- AcO-DET, 4-AcO-EiPT, 4-AcO-DPT, 4-AcO-DiPT, 4-AcO-DALT, 4-MeO-DMT, 4-MeO- MiPT, 5-MeO-NMT, 5-MeO-MET, 5-MeO-MPT, 5-MeO-MiPT, 5-MeO-MALT, 5-MeO- DET, 5-MeO-EiPT, 5-MeO-EPT, 5-MeO-PiPT, 5-MeO-DPT, 5-MeO-DiPT, 5-MeO-DALT, 5-MeO-αMT, 5-MeO-αET, 5-MeO-MPMI, 5-MeO-2,N,N-TMT, 5-MeO-7,N,N-TMT, 5- MeO-a,N-DMT, 4-F-5-MeO-DMT, 5-MeS-DMT, 5-Me-MiPT, 5-HO-DiPT, 2-α-DMT, 2- Me-DET, 4-Me-αMT, 4-Me-αET, 7-Me-αET, 4,5-DHP-AMT, 4,5-DHP-DMT, 4,5-MDO- DMT, 4,5-MDO-DiPT, 5,6-MDO-DiPT, 5,6-MDO-MiPT, 5-Fluoro-αMT, 6-Fluoro-αMT, 6- Fluoro-DMT, N,N-Tetramethylenetryptamine, 4-HO-pyr-T, 5-MeO-pyr-T, RU-28306, O- 4310, and CP-132,484)), benzofuran derivatives (e.g., dimemebfe and 5-MeO-DiBF), ibogoids (e.g., ibogaine and boacangine), ergolines (e.g., lysergic acid diethylamide, lysergic acid amide, N1-methyl-lysergic acid diethylamide, N-Acetyl-lysergic acid diethylamide, 1- Propionyl-lysergic acid diethylamide, 1‐cyclopropanoyl‐d‐lysergic acid diethylamide, 1- valeryl-D-lysergic acid diethylamide, 6-allyl-6-nor-lysergic acid diethylamide, 6-butyl-6-nor- lysergic acid diethylamide, 6-ethyl-6-nor-lysergic acid diethylamide, 1-propionyl-6-ethyl-6- nor-lysergic acid diethylamide, 6-propyl-6-nor-lysergic acid diethylamide, 6-cyclopropyl-6- nor-lysergic acid diethylamide, 6-nor-lysergic acid diethylamide, lysergic acid ethylamide, lysergic acid α-hydroxyethylamide, lysergic acid 2-butyl amide, lysergic acid 3-pentyl amide, lysergic acid methyl ester, lysergic acid 2,4-dimethylazetidide, lysergic acid piperidine, N,N- dimethyl-lysergamide, methylisopropyllysergamide, N,N-diallyllysergamide, N- pyrrolidyllysergamide, N-morpholinyllysergamide, 1-methyl-lysergic acid butanolamide, lysergic acid β-propanolamide, and lysergic acid 1-butanolamide)), phenethylamines (e.g., mescaline, lophophine, isomescaline, cyclopropylmescaline, thioisomescaline, 4- desoxymescaline, jimscaline, escaline, metaescaline, thiometaescaline, trisescaline, thiotrisescaline, symbescaline, asymbescaline, thiosymbescaline, phenescaline, allylescaline, methallylescaline, proscaline, isoproscaline, metaproscaline, thioproscaline, buscaline, thiobuscaline, α-ethylmescaline, ariadne, macromerine, MEPEA, TOM, Bis-TOM, TOMSO, TOET, BOH, BOM, β-D, 4-D, DME, F-2, F-22, FLEA, MDPH, MDMP, propynyl, and 2,5- dimethoxy, 4-substituted phenethylamines e.g., βk-2C-B, 2C-B, 2CB-2EtO, 2CB-5EtO, 2CB- diEtO, 2C-B-FLY, 2C-B-BUTTERFLY, 2C-C, 2C-D, 2CD-2EtO, 2CD-diEtO, 2CD-5EtO, 2C-E, 2C-EF, 2C-F, 2C-G, 2C-H, 2C-I, 2CI-2EtO, 2C-iP, 2C-N, 2C-O, 2C-O-4, 2C-P, 2C- SE, 2C-T, 2CT-5EtO, 2C-T-2, 2CT-2-2EtO, 2CT-2-5EtO, 2CT-2-diEtO, 2C-T-4, 2CT-4- 2EtO, 2C-T-7, 2CT-7-2EtO, 2C-T-8, 2C-T-9, 2C-T-13, 2C-T-15, 2C-T-16, 2C-T-17, 2C-T- 19,, 2C-T-21, 2C-TFM, 2C-YN, BOB, BOD, BOHD, HOT-2, HOT-7, HOT-17, indane derivatives (e.g., 2CB-Ind), benzocyclobutene derivatives (e.g., 2C-BCB), NBOME derivates (e.g., NBOMe-mescaline, 2C-H-NBOMe, 2C-C-NBOMe, 2CBCB-NBOMe, 2CBFly- NBOMe, 2C-B-NBOMe, 2C-I-NBOMe, 2C-TFM-NBOMe, 2C-D-NBOMe, 2C-G-NBOMe, 2C-E-NBOMe, 2C-P-NBOMe, 2C-iP-NBOMe, 2C-CN-NBOMe, 2C-N-NBOMe, 2C-T- NBOMe, 2C-T-4-NBOMe, 2C-T-7-NBOMe, and DMBMPP), NBOH derivatives (e.g., 2C- C-NBOH, 2C-B-NBOH, 2C-I-NBOH, and 2C-CN-NBOH), NBMD derivatives (e.g., 2C-I- NBMD), NBF derivatives (e.g., 2C-C-NBF, 2C-B-NBF, and 2C-I-NBF), substituted amphetamines (e.g., 3C-E, 3C-P, 3C-DFE, 3C-BZ, DOx, DOAM, DOB, Meta-DOB, Methyl- DOB, DOBU, DOC, DOEF, DOET, DOI, DOM, Ψ-DOM, DON, DOPR, DOiPR, DOT, Meta-DOT, Ortho-DOT, DOTFM, DMCPA, DMMDA, DMMDA-2, 2,5-dimethoxy-3,4- dimethylamphetamine, 4-methyl-2,5-dimethoxymethamphetamine, 2,N-dimethyl-4,5- methylenedioxyamphetamine, dimethoxyamphetamine, trimethoxyamphetamine, tetramethoxyamphetamine, Br-DragonFLY, TFMFly, 2-bromo-4,5- methylenedioxyamphetamine, 4-bromo-3,5-dimethoxyamphetamine, EEE, EEM, EME, EMM, EDMA, EIDA, ethyl-J, methyl-J, ethyl-K, methyl-K, IDNNA, iris, MDAI, MDMAI, MDAT, MDMAT, MDAL, MDBU, MDBZ, MDDM, MDIP, MDMEOET, MDMEO, MDOH, MDHOET, MDPL, MDCPM, MDPR, MEDA, MEM, methyl-DMA, MMDA, MMDA-2, 5-Methyl-MDA, MEE, MME, MPM, DiFMDA, 5-APB, 6-APB, 5-APDB, 6- APDB, 5-MAPB, 5-MAPDB, 6-MAPDB, 6-MAPB, 6-EAPB, 5-EAPB, para- methoxyamphetamine, paramethoxymethamphetamine, 4-ethylamphetamine, 3-methoxy-4- methylamphetamine, 4-methylmethamphetamine, 4-methylthioamphetamine, 4- fluoroamphetamine, norfenfluramine, para-iodoamphetamine, and para-chloroamphetamine) benzoxazines (e.g., efavirenz)), empathogens/entactogens e.g., substituted methylenedioxy- phenethylamines (e.g., MDMA, MDA, 2,3-MDA, 5-Methyl-MDA, MMDA, MDEA, MBDB, MDAL, MDBU, MDBZ, MDDM, MDIP, MDMEOET, MDMEO, MDOH, MDHOET, MDPL, MDCPM, MDPR, BDB, MMDA-2, DiFMDA, EIDA, ethyl-K, lophophine), substittued amphetamines (e.g., EDMA, para-methoxyamphetamine, paramethoxymethamphetamine, 4-ethylamphetamine, 3-methoxy-4-methylamphetamine, 4- methylmethamphetamine, 4-methylthioamphetamine, 4-fluoroamphetamine, norfenfluramine, para-iodoamphetamine, and para-chloroamphetamine), substituted cathinones (e.g., methylone, ethylone, eutylone, butylone, pentylone, 4-ethylmethcathinone, and 3-methylmethcathinone), substituted benzofurans (e.g., 5-APB, 6-APB, 5-APDB, 6- APDB, 5-MAPB, 5-MAPDB, 6-MAPDB,, 6-MAPB, 5-EAPB, 6-EAPB, and 5-MBPB), substituted tetralins (e.g., MDAT, MDMAT, 6-CAT, and tetralinylaminopropane), substituted indanes (e.g., trifluoromethylaminoindane, ethyltrifluoromethylaminoindane, 5- iodo-2-aminoindane, MMAI, MDAI, MDMAI, and indanylaminopropane), substituted naphthalenes (e.g., naphthylaminopropane), substituted phenylisobutylamines (e.g., 4- chlorophenylisobutylamine, 4-methylphenylisobutylamine, and ariadne), alpha-substituted (- alkylated) tryptamines (e.g., α-methyltryptamine, 5-MeO-αMT, α-ethyltryptamine, 4-Me- αET, 7-Me-αET, 5-MeO-αET, and 5-MeO-MiPT)), cannabinoids (e.g., phytocannabinoids (e.g., Δ9-THC, 11-hydroxy-Δ9-THC, CBD, CBN, and THCV)) and synthetic cannabinoids (e.g., (C6)-CP 47,497, (C9)-CP 47,497, 1-butyl-3-(2-methoxybenzoyl)indole, 1-butyl-3-(4- methoxybenzoyl)indole, 1-pentyl-3-(2-methoxybenzoyl)indole, 2-isopropyl-5-methyl-1-, (2,6-dihydroxy-4-nonylphenyl)cyclohex-1-ene, 4-HTMPIPO, 4-nonylphenylboronic acid, 5Br-UR-144, 5Cl-APINACA, 5Cl-UR-144, 5F-3-pyridinoylindole, 5F-AB-FUPPYCA, 5F- ADB-PINACA, 5F-ADBICA, 5F-ADB, 5F-AMB, 5F-APINACA, 5F-CUMYL-PINACA, 5F-EMB-PINACA, 5F-NNE1, 5F-PB-22, 5F-PCN, 5F-PY-PICA, 5F-PY-PINACA, 5F-SDB- 006, HHC, A-796,260, A-834,735, A-836,339, A-955,840, A-40174, A-41988, A-42574, AB-001, AB-CHFUPYCA, AB-CHMFUPPYCA, AB-CHMINACA, AB-FUBICA, AB- FUBINACA 2-fluorobenzyl isomer, AB-FUBINACA, AB-PICA, AB-PINACA, abnormal cannabidiol, ADAMANTYL-THPINACA, ADB-CHMINACA, ADB-FUBICA, ADB- FUBINACA, ADB-PINACA, ADBICA, ADSB-FUB-187, ajulemic acid, AM-087, AM-411, AM-630, AM-630, AM-679, AM-694, AM-855, AM-883, AM-905, AM-906, AM-919, AM- 926, AM-938, AM-1220, AM-1221, AM-1235, AM-1241, AM-1248, AM-1346, AM-1387, AM-1714, AM-2201, AM-2232, AM-2233, AM-2389, AM-4030, AM-4113, AM-6527, AM- 6545, AM-251, AM-281, AM-404, AMB-CHMINACA, AMB-FUBINACA, AMG-1, AMG- 3, AMG-36, AMG-41, APICA, APINACA, APP-FUBINACA, arachidonoyl serotonin, ACEA, ACPA, arvanil, AZ-11713908, BAY 38-7271, BAY 59-3074, BIM-018, biochanin A, BML-190, nabidrox, cannabicyclohexanol, cannabipiperidiethanone, CAY-10401, CAY- 10429, CAY-10508, CB-13, CB-25, CB-52, CB-86, CB-86, CBS-0550, CP 47,497, CP 55,244, CP 55,940, CUMYL-5F-PICA, CUMYL-BICA, CUMYL-PICA, CUMYL-PINACA, CUMYL-THPINACA, dexanabinol, dimethylheptylpyran, drinabant, dronabinol, EAM- 2201, EMB-FUBINACA, FAB-144, FDU-NNE1, FDU-PB-22, FUB-144, FUB-APINACA, FUB-JWH-018, FUB-PB-22, FUBIMINA, genistein, GW-405,833, GW-842,166X, hemopressin, HU-210, HU-243, HU-308, HU-320, HU-331, HU-336, HU-345, HU-910, ibipinabant, IDFP, JNJ 1661010, JTE-907, JTE 7-31, JWH-007, JWH-015, JWH-018, JWH- 019, JWH-030, JWH-051, JWH-073, JWH-081, JWH-098, JWH-116, JWH-122, JWH-133, JWH-139, JWH-147, JWH-149, JWH-161, JWH-164, JWH-167, JWH-175, JWH-176, JWH- 182, JWH-184, JWH-185, JWH-192, JWH-193, JWH-194, JWH-195, JWH-196, JWH-197, JWH-198, JWH-199, JWH-200, JWH-203, JWH-210, JWH-229, JWH-249, JWH-250, JWH- 251, JWH-302, JWH-307, JWH-359, JWH-369, JWH-370, JWH-398, JWH-424, JZL184, JZL195, kaempferol, KM-233, L-759,633, L-759,656, LASSBio-881, LBP-1, leelamine, levonantradol, LH-21, LY-320,135, LY-2183240, MAM-2201, MDA-7, MDA-19, MDA-77, MDMB-CHMICA, MDMB-CHMINACA, MDMB-FUBINACA, menabitan, MEPIRAPIM, methanandamide, MJ-15, MK-9470, MMB-2201, MN-18, MN-25, nabazenil, nabilone, nabitan, naboctate, NESS-0327, NESS-040C5, NIDA-41020, NM-2201, NMP-7, NNE1, nonabine, O-224, O-581, O-585, O-606, O-689, O-774, O-806, O-823, O-889, O-1057, O- 1125, O-1184, O-1191, O-1238, O-1248, O-1269, O-1270, O-1376, O-1399, O-1422, O- 1601, O-1602, O-1624, O-1656, O-1657, O-1660, O-1812, O-1860, O-1861, O-1871, O- 1918, O-2048, O-2050, O-2093, O-2113, O-2220, O-2365, O-2372, O-2373, O-2383, O- 2426, O-2484, O-2545, O-2654, O-2694, O-2715, O-2716, O-3223, O-3226, oleoylethanolamide, olvanil, Org 27569, Org 27759, Org 28312, Org 28611, Org 29647, otenabant, palmitoylethanolamide, parahexyl, PF-03550096, PF-04457845, PF-622, PF-750, PF-3845, PF-514273, PHOP, PipISB, pirnabine, pravadoline, pregnenolone, PSB-SB-487, PSB-SB-1202, PTI-1, PTI-2, PX-1, PX-2, PX-3, QUCHIC, QUPIC, RCS-4, RCS-8, rimonabant, rosonabant, RTI-371, S-444,823, SDB-006, SER-601, SPA-229, SR-144,528, STS-135, surinabant, taranabant, tedalinab, THC-O-acetate, THC-O-phosphate, THJ-018, THJ-2201, tinabinol, TM-38837, UR-144, URB-447, URB-447, URB-597, URB-602, URB- 754, VCHSR, VDM-11, VSN-16, WIN 54,461, WIN 55,212-2, WIN 56,098, XLR-11, and yangonin). EXAMPLES [00166] The disclosure is further illustrated by the following examples. The examples are provided for illustrative purposes only, and are not to be construed as limiting the scope or content of the disclosure in any way. Example 1: Modeling gene x environment interactions: PTSD-specific glucocorticoid- induced transcriptomics in human neurons [00167] Transcriptional response to stress mediators in human induced pluripotent stem cell (hiPSC)-derived glutamatergic neurons and peripheral blood mononuclear cells (PBMCs) were compared for combat veterans with post-traumatic stress disorder (PTSD) (n = 19 hiPSC donors and n = 20 PBMC donors) and controls (n = 20 hiPSC donors and n = 20 PBMC donors). Here, we present evidence that a glucocorticoid hypersensitivity is demonstrated for PTSD neurons, and specific genes are identified that contribute to the PTSD-dependent glucocorticoid response. We provide evidence of a co-regulated network of transcription factors with shared effector regulation that mediates glucocorticoid hyper- responsiveness in PTSD. The findings show that induced neurons represent a new platform in which glucocorticoid response signatures can be used to test the molecular mechanisms underlying PTSD, identify biomarkers of stress response in PTSD, and conduct drug- screening to identify novel therapeutics to prevent or ameliorate PTSD-related clinical phenotypes. Materials and methods Participants [00168] A total of 49 individuals were recruited to yield well-matched and largely over- lapping (30 shared individuals) hiPSC and PBMC cohorts, including combat veterans with (n = 19 hiPSC donors and n = 20 PBMC donors) and without (n = 20 hiPSC donors and n = 20 PBMC donors)) PTSD. Participants in this cross-sectional study were combat-exposed Operation Enduring Freedom, Operation Iraqi Freedom, and Operation New Dawn (OEF/OIF/OND) veterans with and without PTSD who provided written, informed consent (VA HS# YEH-16-03 and ISMMS HS#15-00886) and from whom a viable blood and/or fibroblast sample was provided and sufficient RNA for genome-wide expression analyses was extracted. Eligibility for participation was determined. Participants were included serially in the order in which they consented until the enrollment targets were attained. All participants reported a DSM-IV criterion A combat trauma; all experienced deployment to active military combat zones and experienced one or more significant combat-related traumas. Individuals with and without PTSD did not have significant differences in childhood or pre-deployment trauma, deployment number or cumulative duration. Participants underwent psychological evaluation using the Structured Clinical Interview for DSM-5 (SCID) and the Clinician Administered PTSD Scale (CAPS) for determination of PTSD diagnosis and severity. Eligibility criteria and thresholds were based on CAPS for DSM-IV; PTSD-positive had a current CAPS-IV total score above 40 (frequency + intensity), whereas PTSD-negative participants were combat-exposed veterans had a total score below 40. Although DSM-IV criteria for PTSD were used for inclusion, note that PTSD+ participants also met criteria for PTSD based on DSM-5. Diagnostic and clinical exclusions included: i) presence of moderate or severe substance use disorder within the past 6 months, ii) lifetime history of primary psychotic or Bipolar I disorders, iii) self-reported history of moderate or severe traumatic brain injury, iv) neurological disorder or major systemic illness, v) treatment with systemic steroids, and for PTSD-negative only, vi) current or recurrent major depressive disorder. Psychotropic medication was permitted, but dosage stabilization for at least two weeks was required. ~20% of individuals across both groups are currently treated with psychiatric medications. Current oral steroid treatment was an exclusion based on the impact of systemic steroids on the hypothalamic-pituitary-adrenal axis (HPA) axis. Given the small sample size, there was no additional matching performed for clinical characteristics such as index trauma types, duration of the disorder, comorbidities, and psychiatric medications at time of recruitment. Available clinical information is summarized in Table 3, below. Table 3. Comparison of clinical characteristics of veterans with and without PTSD
Figure imgf000161_0001
Figure imgf000162_0001
Biopsy Collection and Generation/Validation ofhiPSCs
[00169] Biological samples (blood and fibroblast) were collected from eligible participants at the James J. Peters VAMC. Blood processing occurred at the JJP VAMC and fibroblasts were transferred to New York Stem Cell Foundation (NYSCF). All human induced pluripotent stem cells (hiPSCs) were reprogrammed together in randomized batches as fibroblast biopsies were obtained over time. Skin fibroblasts of PTSD and non-PTSD participants were collected via skin punch biopsy taken from the upper buttocks. Upon collection, biopsies were immediately placed in Biopsy Collection Media (Cascade Biologics Medium 106 (Life Technologies, M-106-500), 1X Antibiotic-Antimycotic (Life Technologies, 15240-062), LSGS (Life Technologies, S-003- 10)) and stored at 4 °C for a maximum of 24 hours. Biopsies were dissected into ~1 mm3 pieces and plated in Biopsy Plating Media (Knockout-DMEM (Life Technologies, 10829- 018), 10% FBS (Life Technologies, 100821-147), 2 mM GlutaMAX (Life Technologies, 35050-061), 0.1 mM MEM Non-Essential Amino Acids (Life Technologies, 11140-050), 1X Antibiotic-Antimycotic (Life Technologies, 15240-062), 0.1 mM 2-Mercaptoethanol (Life Technologies, 21985-023)). Upon the outgrowth of fibroblasts, samples were entered into an automated pipeline producing vials of cells for both hiPSC reprogramming and backup stock. A cell pellet was collected, with DNA isolated using an EPMotion and the ReliaPrepTM 96 gDNA Miniprep HT System (A2671, Promega). This DNA was used to confirm sample identity throughout the reprogramming process. Fibroblasts were reprogrammed using modified mRNA (Reprocell, 000076) and enriched using anti-fibroblast meads (Miltentyi Biotec, 130-050-601) in automated procedures. Reprogrammed hiPSCs were then expanded using PSC Feeder Free Media (Thermo Fisher Scientific: A14577SA) and grown on Cultrex coated plates (R&D Systems, 3434-010-02). Cells were routinely passaged using an automated platform in the presence of Accutase (ThermoFisher, A11105-01). Following passage, cells were maintained in pluripotent stem cell (PSC) media supplements with 1 µM thiazovivin (Sigma-Aldrich, SML1045-25MG). All cells were frozen in Synthafreeze (ThermoFisher, A12542-01) into master stocks. [00170] As part of the hiPSC validation process, all samples were tested for the absence of Mycoplasma (Lonza, LT07-710) and confirmed to be sterile (Hardy Diagnostics, K82). Samples were confirmed to key karyotypically normal using the Illumina Core Exome Genotyping Chip (Illumina, 20030770) and cnvPartition 3.2.0 (Illumina, Genome Studio). No cell lines displayed karyotypic abnormalities (no reported copy number variations (CNVs) ≥ 2.5 MB in size). All reported CNVs are shown in each certificate of analysis. hiPSC lines were confirmed to be viable post-thaw, achieving a minimum of 50% confluency within 10 days). Sample identity testing was performed using the SNPTrace assay, confirming correct sample association between parental fibroblast and hiPSC line. Gene expression analysis was using a custom Nanostring panel to confirm expression of pluripotency markers such as POU5F1, NANOG, and SOX2, and lack of expression of early differentiation markers such as AFP (Mesoderm), SOX17 (Endoderm), and NR2F2 (Ectoderm). A scorecard panel was used to confirm propensity to differentiate. All hiPSC lines used in this study passed the above QC and have a certificate of analysis. PBMC isolation and culture [00171] Isolation of peripheral blood mononuclear cells (PBMCs), cell culture, and incubation with dexamethasone (DEX) were performed (FIG.1A). PBMC data from n = 10 combat veterans with PTSD and n = 10 without PTSD is first reported here (batch A) and n = 10 combat veterans with PTSD and n = 10 without PTSD was previously reported (see Breen, M. S. et al. Translational psychiatry 9, 201, doi:10.1038/s41398-019-0539-x (2019)) (batch B). In brief, blood was collected in ethylenediaminetetraacetic acid (EDTA)- containing vacutainer tubes (VWR, West Chester, Pennsylvania) and PBMCs were isolated by density gradient centrifugation using Ficoll-Paque (GE Healthcare) and washed twice in HBSS. Mononuclear cells were then counted manually using a Cellometer Disposable Counting Chambers (Nexcelom Bioscience LLC. Lawrence, MA). The cells were re- suspended in complete RPMI, containing RPMI-1640 (Gibco), 10% fetal bovine serum, 50 U/mL penicillin-streptomycin mixture (Gibco) at a density of 1.75-2.00 x 106 cells/mL of the medium. PBMCs were prepared at 2.5 x 106 cells/mL in complete RPMI for DEX treatment experiments. Following incubation at 37 °C, 5%(vol/vol) CO2 for 72 hours, the plates were centrifuged at 900 × g for 15 min at 4 °C and supernatant was collected and pooled from each DEX concentration well. The cell pellet on the bottom of each well was re-suspended in TRIzol reagent. Cell lysates for each DEX dose were pooled, aliquoted and stored at -80 °C until RNA isolation. Automated generation of hiPSC-derived NGN2-neurons [00172] Glutamatergic neurogenin 2 (NGN2)-neurons were generated from iPSCs, using high-throughput automated differentiations, in two batches (batch 1 n = 15 vs 15; batch 2 n = 4 vs 5). hiPSCs were single cell passaged after a 20-minute dissociation with Accutase (STEMCELL Technologies) at 37 °C and 5% CO2.1 million cells per well were plated in 12- well Cultrex coated (R&D Systems, 3434-010-02) tissue culture plates (Corning Costar) in PSC Feeder Free Media (Thermo Fisher Scientific: A14577SA) with 1 µM thiazovivin (Sigma-Aldrich: SML1045). Lentivirus (generated by ALSTEM) carrying pLV-TetO- hNGN2-eGFP-Puro (Addgene#79823) and FUdeltaGW-rtTA (Addgene#19780) was diluted to an MOI=1 each (1 million genome counts of each vector per transduction) in 100 µL DPBS, no calcium, no magnesium (Thermo Fisher Scientific) and added directly after cell seeding. After 24 hours, the medium was exchanged with Neural Induction Medium (NIM) including a 50:50 mix of DMEM/F12 and Neurobasal, with 1X B27+Vit.A, 1X N2, 1X Glutamax (Thermo Fisher Scientific), and 1 µM doxycycline hyclate (Sigma-Aldrich).24 hours later the medium was removed and NIM was added with doxycycline plus 5 µg/mL puromycin. A full medium exchange was performed the next day with NIM plus doxycycline and puromycin.24 hours later cells were passaged by incubating with Accutase for 30 minutes at 37 °C and 5% CO2.96-well plates (PerkinElmer CellCarrier Ultra) were coated with 0.1% Polyethylenimine (PEI) (Sigma-Aldrich: 408727) in 0.1 M Borate buffer pH 8.4 for 30 minutes at room temperature, washed 5 times with water and prefilled with 100 µL per well of Neural Coating Medium (NCM) including Brainphys medium (STEMCELL Technologies) with 1X B27+Vit.A, 1 µM thiazovivin, 5 µg/mL puromycin, 250 µM dbcAMP (Sigma-Aldrich), 40 ng/mL BDNF (R&D Systems), 40 ng/mL GDNF (R&D Systems), 200 µM ascorbic acid (Sigma-Aldrich) and 10 µg/mL natural mouse laminin (Sigma-Aldrich). A sample of cells were stained with 10 µg/mL Hoechst plus 1:500 acridine orange/propidium iodide solution and counted on a Celigo imager (Nexcelom Bioscience).50,000 cells per well were seeded into NCM filled 96-well plates in 100 µL per well of Neural Medium (NM) including Brainphys medium with 1X B27+Vit.A, 1 µM thiazovivin, 5 µg/mL puromycin, 250 µM dbcAMP, 40 ng/mL BDNF, 40 ng/mL GDNF, 200 µM ascorbic acid and 1 µg/mL natural mouse laminin.24 hours after seeding medium was exchanged to Neural Selection Medium (NSM) including Brainphys medium with 1X B27+Vit.A, 250 µM dbcAMP, 40 ng/mL BDNF, 40 ng/mL GDNF, 200 µM ascorbic acid, 1 µg/mL natural mouse laminin, and 2 µM Arabinosylcytosine (Ara-C) (Sigma-Aldrich).48 hours later NSM medium was fully exchanged.48 hours after the medium was fully exchanged with Neural Maintenance Medium (NMM) including Brainphys medium with 1X B27+Vit.A, 250 µM dbcAMP, 40 ng/mL BDNF, 40 ng/mL GDNF, 200 µM ascorbic acid and 1 µg/mL natural mouse laminin. Thereafter every 48 hours, half the medium was exchanged with NMM until day 21 post transduction passage. In Batch 1: All medium exchanges were performed using a Hamilton Star liquid handler set to 5 µL/second for aspirate and dispense as part of the NYSCF Global Stem Cell Array®. Passages were fully automated and performed on a robotic cluster including a Thermo Fisher Scientific C24 Cytomat incubator, a Hamilton Star liquid handler, an Agilent microplate centrifuge, a Precise Automation PreciseFlex 400 Sample Handler and a Perkin Elmer Opera Phenix. Batch 2: Although medium exchanges were fully automated, passages were manually performed. [00173] At harvest, medium was removed using the Bluewasher (BlueCatBio) and cells were lysed for 5 minutes using RLT plus buffer (Qiagen), snap frozen on dry-ice and stored at -80 °C. A replicate plate was fixed for immunofluorescence analysis by adding 32% Paraformaldehyde (Electron Microscopy Sciences) directly to medium to a final concentration of 4% and incubated at room temp for 15 minutes. Cells were washed three times with HBSS (Thermo Fisher Scientific), stained overnight with mouse anti-Nestin 1:3000 (Millipore: 09-0024), chicken anti-MAP21:3000 (Abcam: 09-0006) in 5% Normal Goat Serum (Jackson ImmunoResearch) in 0.1% Triton x-100 (Thermo Fisher Scientific) in HBSS. Primary antibodies were counterstained with Goat anti-Mouse Alexa Fluor 555 and Goat anti-chicken Alexa Fluor 647 and 10 µg/mL Hoechst for 1 hour at room temp. Cells were washed three times with HBSS. Batch 1: Nine fields (40x magnification) were imaged per well (one well per condition per line) using the Perkin Elmer Opera Phenix microscope. Batch 2: Nine fields (20x magnification) were imaged per well (two wells per hiPSC line) using the ArrayScan automated microscope (Thermo Fisher Scientific). Inter-well variability in neuronal identity and maturity was assessed using automated image analyses: NESTIN- positive neural progenitor cells (NPCs) were demarcated from microtubule associated protein 2 (MAP2)-positive post-mitotic neurons (FIG.6). Variation between batches may reflect discrepancies in imaging methods, rather than biological differences in neuronal morphology or maturity. Glucocorticoid treatment [00174] Preliminary studies were conducted to identify optimal culture and glucocorticoid stimulation conditions. These pilot studies sought to evaluate the transcriptional effects of hydrocortisone (HCort) and DEX on NGN2 neurons, and optimize the length of glucocorticoid treatment and concentrations. Neither qPCR for six glucocorticoid regulatory genes (covering ten concentrations of DEX) nor RNAseq (covering three concentrations of DEX) revealed significant gene expression differences following 72 hours of exposure, consistent with minimal upregulation of FKBP5 mRNA expression following DEX treatment of hiPSC neurons. This is consistent DEX treatment of primary cultures being significantly less responsive than astrocytes. Together, this preliminary data supports that astrocyte or endothelial response, rather than neuronal response, mediates brain-level effects of DEX treatment. As the preliminary experiments found a strong genome-wide effect of HCort treatment, we used HCort treatment for neuronal glucocorticoid exposure. Serum measurements of cortisol in patients with and without PTSD have been found to average around 492.52 nM, intermediate between the 100 and 1000 nM doses. HCort treatment medium was prepared by first dissolving HCort (Sigma-Aldrich: H0888) in ethanol to make a 2.8 mM stock. HCort ethanol stock was then diluted to 0.2 mM in HBSS. Ethanol was equalized to 15 µM in control and all treatment media. DEX treatment medium was prepared by dissolving DEX (Sigma-Aldrich, D1156) in HBSS Solution (ThermoFisher, 14175). The final treatment medium was prepared by diluting HCort or DEX stocks into NMM/RPMI, prior to applying to cells by fully exchanging medium. Neurons were treated with HCort for 24 hours (baseline, 100 nM, 1000 nM, 2500 nM), PBMCs with DEX for 72 hours (baseline, 2.5 nM, 5 nM, 50 nM). Baseline media conditions are estimated to contain 58 nM of corticosterone from neuronal supplement B27 (Thermo Fisher), which may predispose neurons to a higher effective concentration for glucocorticoid stimulation, and may bias responsive genes towards those that respond to severe stressors, rather than homeostatic or regulatory changes, such as circadian rhythms. RNA extraction and quality control [00175] For NGN2-neurons, RNA was harvested with RNeasy plus micro kit (Qiagen). For PBMCs, RNA was extracted from TRIzol-lysed PBMCs using the miRNAeasy Mini Kit (Qiagen). Following each extraction, RNA quantity was measured on the Nano Drop 2000 Spectrophotometer (Thermo Scientific) and the quality and integrity measured with the Agilent 2100 Bioanalyzer (Agilent, Santa Clara, CA, USA). All RNA integrity numbers (RINs) were high in the current study: NGN2-neurons (8.8 ± 0.53) and PBMCs (7.5 ± 0.95). RNA-sequencing data generation [00176] A low-input RNA-sequencing protocol was applied for the generation of RNA- sequencing data from NGN2-neurons. Specifically, polyA enriched RNAs were subjected to RNA-sequencing library preparation using the SMART-Seq v4 Kit (SSv4; Takara) and sequenced using a paired-end 150 bp configuration with 30 M supporting reads per sample. For RNA-seq data generation from PBMCs, Ribo-zero rRNA deleted RNAs were subjected to RNA-sequencing library preparation using the Illumina TruSeq Stranded Total RNA kit (Illumina) and sequenced using a paired-end 150 bp configuration with 20 M supporting reads per sample. RNA-sequencing data pre-processing [00177] All RNA-sequencing FASTQ files underwent matching analytical procedures, as described previously. In brief, resulting short reads with Illumina adapters were trimmed and low-quality reads were filtered using TrimGalore (see Bolger, A. M., Lohse, M. & Usadel, B. Bioinformatics 30, 2114-2120, doi:10.1093/bioinformatics/btu170 (2014);--illumina option). All high-quality reads were then processed for alignment using the hg38 reference and the ultrafast universal RNA-seq aligner STAR with default parameters (see Dobin, A. et al. Bioinformatics 29, 15-21, doi:10.1093/bioinformatics/bts635 (2013)). Mapped bam files were sorted using Samtools and short read data were quantified using featureCounts (see Liao, Y., Smyth, G. K. & Shi, W. Bioinformatics 30, 923-930, doi:10.1093/bioinformatics/btt656 (2014)) with the following parameters: -T 5, -t exon, and -g gene_id. Subsequently, all read counts were exported and all downstream analyses were performed in the R statistical computing environment. Raw count data was subjected to non-specific filtering to remove low-expressed genes that did not meet the requirement of a minimum of two counts per million (cpm) in at least ~ 40% of samples. This filtering threshold was applied to NGN2- neurons and PBMCs separately. All expression values were converted to log2 RPKM and subjected to unsupervised principal component analysis (PCA) to identify and remove outlier samples that lay outside 95% confidence intervals from the grand averages. This identified two outlier samples in NGN2-neuron batch 1 and one outlier sample in batch 2 that were excluded from the analysis. Developmental specificity analysis [00178] RNA-seq datasets from existing postmortem brain tissue and hiPSC models were integrated to validate the developmental specificity of the samples using a previously described approach (see Hoffman, G. E. et al. Nat Commun 8, 2225, doi:10.1038/s41467- 017-02330-5 (2017)). In brief, a total of 16 independent studies were collected covering 2716 independent samples and 12,140 genes. These samples cover a broad range of hiPSCs, NPCs, mature neurons, prenatal and postnatal brain tissues. All expression values were converted to log2 RPKM and collectively normalized using quantile normalization using the limma R package. Subsequently, for each independent sample present in the hiPSC neuron data set, we performed pair-wise correlation analysis (using Pearson’s correlation coefficients) across all independent samples and subsequently aggregated the correlation coefficients for each external study and/or cell type. Next, and as a complimentary approach, all datasets were jointly analyzed and integrated using principal component analysis (PCA) (FIG.8A-8B). Differential gene expression analyses [00179] Transcriptional signatures were generated using a strategy adapted from Hoffman et al. (see Hoffman, G. E. et al. Nat Commun 8, 2225, doi:10.1038/s41467-017-02330-5 (2017)), using scripts available at www.synapse.org/hiPSC_COS. Gene expression values were normalized using VOOM (see Ritchie, M. E. et al. Nucleic Acids Res 43, e47, doi:10.1093/nar/gkv007 (2015)). Confounders explaining a significant proportion of variance in gene expression were identified using variancePartition (see Hoffman, G. E. & Schadt, E. E. BMC bioinformatics 17, 483, doi:10.1186/s12859-016-1323-z (2016)) (i.e., experimental batch, treatment, individual as a repeated measure (i.e., inter-donor effects), PTSD diagnosis and RIN) (FIG.7 A). A significant batch effect was observed (FIG.7A-7B), which was corrected for by constructing a linear model of batch and extracting the residuals. Next, differential gene expression analyses were conducted using a moderated t test from the R package limma (see Ritchie, M. E. et al. Nucleic Acids Res 43, e47, doi:10.1093/nar/gkv007 (2015)). Models examining the HCort-dependent, PTSD-independent effect (FIG.s 1-3) included adjustment for the possible confounding influence of PSTD diagnosis and RIN, while PTSD-dependent models (FIG.s 4-5) included diagnosis as a main outcome. Due to the repeated measures study design, where individuals are represented by multiple independent technical replicates, the duplicate. Correlation function was applied in the limma analysis and gene level significance values were adjusted for multiple testing using the Benjamini and Hochberg method to control the false discovery rate (FDR). Genes with FDR < 5% were considered significantly differentially expressed. To integrate differential gene expression results between batches, summary statistics from differential gene expression analyses to both glucocorticoid-dependent and PTSD-dependent responses in each batch were meta-analyzed using METAL (see Willer, C. J., Li, Y. & Abecasis, G. R. Bioinformatics 26, 2190-2191, doi:10.1093/bioinformatics/btq340 (2010)). Significant results across both studies were identified using a Benjamini–Hochberg-adjusted p-value threshold (FDR < 0.05). Neurite outgrowth analysis [00180] To determine functional and mechanistic consequences of HCort treatment, NGN2-neurons were seeded as 1.5 x 104 cells/well in a 96-well plate coated with 4x Matrigel at day 5. At day 6, NGN2-neurons were treated with HCort for 24 hours (0 nM (vehicle), 100 nM, 1000 nM, 2500 nM) as in prior experiments. At day 7, cultures were fixed using 4% formaldehyde/sucrose in PBS with Ca2+ and Mg2+ for 10 minutes at room temperature (RT). Fixed cultures were washed twice in PBS and permeabilized and blocked using 0.1% Triton/2% Normal Donkey Serum (NDS) in PBS for two hours. Cultures were then incubated with primary antibody solution (1:1000 MAP2 anti chicken (Abcam, ab5392) in PBS with 2% NDS) overnight at 4 degrees. Cultures were then washed 3 times with PBS and incubated with secondary antibody solution (1:500 donkey anti chicken Alexa 647 (Life technologies, A10042) in PBS with 2% NDS) for 1 hour at RT. Cultures were washed a further 3 times with PBS with the second wash containing 1 μg/mL DAPI. Fixed cultures were then imaged on a CellInsight CX7 HCS Platform with a 20x objective (0.4 NA) and neurite tracing analysis performed using the neurite tracing module in the Thermo Scientific HCS Studio 4.0 Cell Analysis Software.12-24 wells were imaged per condition across a minimum of 2 independent cell lines, with 9 images acquired per well for neurite tracing analysis. A Kruskall Wallis test with a post hoc Dunn's multiple comparisons test was performed on data for neurite length per neuron using Graphpad Prism. This analysis was performed in Day 7 neurons to ensure optimal density to observe neurite outgrowth phenotypes, which are less quantifiable by these methods in more mature neurons. Weighted gene co-expression network analysis and functional annotation [00181] Signed co-expression networks were built for PBMCs and NGN2-neurons using weighted gene co-expression network analysis (WGCNA; see Zhang, B. & Horvath, S. A. Stat Appl Genet Mol Biol 4, Article17 (2005)). To construct a global weighted network for each cell type, a total of 20,101 and 16,146 post quality control (QC) genes were used in PBMCs and NGN2-neurons respectively. The absolute values of Biweight midcorrelation coefficients (optimal for small sample sizes) were calculated for all possible gene pairs within each cell type and resulting values were transformed using a β-power (β=4 for NGN2-neurons and β=7 for PBMCs) so that the final correlation matrices followed an approximate scale-free topology (FIGs.12A-12B). In order to determine which modules, and corresponding biological processes, were most associated with HCort/DEX, singular value decomposition of each module’s expression matrix was used; the resulting module eigengene (ME), equivalent to the first principal component, represented the overall expression profiles for each module. Each module was enriched for Gene Ontology (GO) biological processes, molecular factors, cellular components and molecular pathways using ToppGene. All genes passing non- specific filtering in the current data set were used as a genomic background. Only gene sets that passed a multiple test adjustment using the Benjamini Hochberg procedure (Adj. P < 0.05) were deemed significant. ME values were correlated with dosage by Pearson correlation. Protein-protein association networks were constructed using STRING. For protein-protein association analysis of WGCNA modules, genes with high module membership (MM>0.8) were selected for STRING analysis and computation of PPI enrichment p-values. Networks were visualized by cytoscape. Gene co-expression module preservation analysis [00182] Gene co-expression modules that were disrupted or created in response to glucocorticoids across NGN2-neurons and PBMCs, a permutation-based preservation statistic (Zsummary)2 with 200 random permutations was used to measure the (dis)similarity in correlation patterns for the genes within these gene sets: Zsummary > 10 indicates strong evidence of preservation, 2 < Zsummary < 10 indicates weak-to-moderate evidence of preservation and Zsummary < 2 indicates minimal-to-no evidence of preservation. For this analysis, we specifically focused on dynamically regulated, glucocorticoid responsive functional modules that were identified in either NGN2-neurons or PBMCs, respectively. Integration of disease-associated genes and gene sets [00183] Concordance of observed PBMC and neuron transcriptomic signatures to glucocorticoid stimulation (FIGs.1E and 2E), or between PTSD cases and controls (FIG. 4D) and previously reported psychiatric disorder and neurodevelopmental expression patterns was determined. Psychiatric disorder enrichment was determined using genetic and genomic disease-related gene lists for PTSD, major depressive disorder, schizophrenia, bipolar disorder, autism spectrum disorder, alcohol use disorder, and inflammatory bowel disease. Glucocorticoid dysregulation of neurodevelopmental genes was examined using risk genes associated with epilepsy, developmental delay, autism spectrum disorder, intellectual disability, schizophrenia, and FMRP target genes. All gene sets were assessed by Over- Representation Analysis (ORA; see Boyle, E. I. et al. GO: Bioinformatics 20, 3710-3715, doi:10.1093/bioinformatics/bth456 (2004)) using WebGestaltR (see Wang, J. & Liao, Y. WebGestaltR: Gene Set Analysis Toolkit WebGestaltR. R package version 0.4.3., <https://CRAN.R-project.org/package=WebGestaltR> (2020)), with significant enrichment calculated using hypergeometric distribution. All p-values from all gene sets were adjusted for multiple testing using the Benjamini–Hochberg procedure, using a p-value < 0.05 threshold to determine significance. This gene list is available in Table 2. Clustering of PTSD expression patterns [00184] To assess whether significant gene expression patterns could predict PTSD, the differential log2CPM of 1,016 and 402 PTSD-specific DRGs in NGN2-neurons following 100 nM and 1000 nM of HCort, respectively, were plotted using pheatmap (see Kolde, R. pheatmap: Pretty Heatmaps. R package version 1.0.12. , <https://CRAN.R- project.org/package=pheatmap> (2019). K-means clustering was applied with Euclidian distance using average linkage clustering and tested for observed clustering of PTSD-positive and PTSD-negative gene signatures (FIG.4B). Interaction analysis [00185] To test the interaction of HCort concentration with PTSD diagnosis, the linear effect of the HCort x PTSD interaction term was modeled using limma, adjusting for RIN and donor as a repeated measure. Of the 740 genes with significant Benjamini-Hochberg-adjusted p-values <0.05, genes were identified that responded significantly to HCort in either cases or controls by performing one-way ANOVA on log2CPM normalized expression to increasing HCort exposure separately in PTSD cases and controls. Genes with a significant ANOVA p- value in controls but not in PTSD cases as “PTSD hypo-responsive,” genes with a significant ANOVA p-value in both PTSD cases and controls, but with opposite directions of effect as “interactive,” and genes with a significant ANOVA p-value to HCort in PTSD cases but not in controls were labelled as “PTSD hyper-responsive” (FIG.4E). We selected these three categories to maximize biological interpretability, suggesting hyper- and hypo-sensitivity of targets as physiologically relevant to PTSD. To assess spatial association of genes with the most significant interactive effects with known common variant effectors involved in PTSD, expression of PTSD GWAS (see Nievergelt, C. M. et al. Nat Commun 10, 4558, doi:10.1038/s41467-019-12576-w (2019)) variants was imputed using PrediXcan (see Gamazon, E. R. et al. Nat Genet 47, 1091-1098, doi:10.1038/ng.3367 (2015)) and mapped against the significance of the HCort x PTSD interaction term in the study (FIG.5D). [00186] To identify upstream drivers of the PTSD-specific HCort response signature, enrichment for transcription factor targets, defined based on MSigDB C3 gene set groupings (see Xie, X. et al. Nature 434, 338-345, doi:10.1038/nature03441 (2005)), was performed using the FUMA pipeline (see Watanabe, K., Taskesen, E., van Bochoven, A. & Posthuma, D. Nat Commun 8, 1826, doi:10.1038/s41467-017-01261-5 (2017)). Transcription factors were tested for their overlap with genes previously reported in post-mortem brains of individuals with PTSD and genes associated with CAPS scores in whole blood. The significance of the number of transcription factors enriched in PTSD gene sets was tested using a binomial test. Results [00187] To study how glucocorticoids influence gene expression in donor-specific brain and blood cells, skin and blood samples were collected from well-matched and largely over- lapping (30 shared individuals) hiPSC-derived glutamatergic neuron and PBMC cohorts respectively, including combat veterans with (n = 19 hiPSC donors and n = 20 PBMC donors) and without (n = 20 hiPSC donors and n = 20 PBMC donors)) PTSD (Table 1). For technical reasons, glucocorticoid treatment of NGN2-neurons (batch 1 n = 15vs15, batch 2 n = 4vs5) and PBMCs (batch A n = 10vs10, batch B n = 10vs10) were completed independently and then meta-analyzed together to adjust for batch effects. Dexamethasone-stimulated transcriptional responses in PBMCs [00188] Treatment of PBMCs in vitro with the synthetic glucocorticoid DEX is a promising method to explore molecular responses to stress hormones in PTSD. To continue these earlier findings, identical methods were applied to expand this study of combat-exposed veterans to (n = 20) and without (n = 20) PTSD (FIG.1A) (Table 3). [00189] RNA-sequencing was generated from cultured PBMCs treated for 72-hours with three concentrations of DEX (2.5 nM, 5 nM, 50 nM), and analyzed relative to baseline samples. To identify reliable markers of glucocorticoid activation independent of PTSD, diagnosis as well as other confounds were adjusted for (see Methods). Incubation with increasing concentrations of DEX (2.5 nM, 5 nM, 50 nM, respectively) identified 6,153; 8,114; and 15,128 differentially expressed genes (DEGs) in batch A, and 4,880; 13,297; and 18,856 DEGs in batch B, respectively (q-value < 0.05) (FIG.1B). Overall transcriptome- wide concordance of DEX-induced fold changes relative to vehicle between the two batches was exceedingly high (average r = 0.738) (FIG.10A), and was highly concordant with reported responses to DEX in PBMCs (r = 0.7 in the 50nM dose) (FIG.10C-10D). These findings demonstrate strong conservation of transcriptional changes in PBMCs in response to DEX that are independent of PTSD and other potentially confounding factors. [00190] Gene co-expression modules were calculated to probe functional consequences of DEX exposure in PBMCs. Of 36 significant co-expression modules (M), 24 were significantly dynamically regulated in response to increasing concentrations of DEX. Gene ontology analysis found enrichment in neuronal regulation terms such as synapse (ME lightcyan, p = 4.23e-4) and immune regulation terms such as activation of immune response (ME skyblue, p = 1.34e-3) and lymphocyte proliferation (ME purple, p = 2.02e-4), and glucocorticoid signaling terms such as steroid hormone mediated signaling pathway (ME blue, p = 2.64e-3) and Fc receptor signaling pathway (ME skyblue, p = 1.91e-4) (FIG.1D). These enrichments are representative of shared regulation of genes involved in cell migration, cytoskeletal, and cell-adhesion properties, which are broadly shared by immune and neural cells, through common processes such as cell migration, degranulation, and cellular outgrowth, which may explain the neural term represented in this module. Together, these enrichments are consistent with glucocorticoid response impacts on cell signaling, neurogenesis and immunosuppression. (FIG.1D). Gene set enrichment for psychiatric disorder gene sets revealed enrichment of DEX-upregulated PBMC DEGs broadly across neuropsychiatric disorder risk genes, but not across PTSD-specific signatures (FIG.1E). This indicates that after adjusting for diagnosis, glucocorticoid treatment of PBMCs alone is insufficient to recapitulate PTSD signatures. Although glucocorticoid treatment of PBMCs (batch A) was highly correlated to the DEX-induced gene responses previously reported (batch B) (FIG.10A), the larger meta-analysis did not identify PTSD-specific DEX-induced differential response genes (PBMC-DRGs) at an FDR-corrected threshold (FIGs.14A-14B and FIG.15). Hydrocortisone-stimulated transcriptional responses in hiPSC-neurons [00191] We and others have demonstrated that NGN2-neurons are > 95% pure glutamatergic neurons, robustly express glutamatergic genes, release neurotransmitters, produce spontaneous synaptic activity, and recapitulate the impact of psychiatric disease associated genes. Well-matched to the PBMCs described above, 21-day-old NGN2-neurons from combat-exposed veterans with (n = 19) and without (n = 20) PTSD (Table 3) were treated with two to three distinct concentrations of HCort (100 nM, 1000 nM, or 2500 nM) and an untreated baseline condition for 24 hours prior to RNA-sequencing (FIG.2A). [00192] To confirm the neuronal identity and developmental specificity of these data, a large comparative and integrative analysis was performed across sixteen existing transcriptome datasets including 2,716 independent samples from a range of hiPSC-derived neurons and developmentally distinct post-mortem brain tissue . A high degree of transcriptomic convergence was observed for the hiPSC-derived neurons with fetal brain tissue and hiPSC-derived neurons described in previous reports, confirming their early developmental gene expression profiles (FIG.8A-8B). Neuronal fate was further confirmed by demonstrated expression of pan-neuronal and synaptic genes in hiPSC-neurons but not in PBMCs (FIG.9 A) and VGLUT expression in NGN2-neurons (FIG.9B). Glucocorticoid and mineralocorticoid receptor (MR) expression was additionally confirmed for each cell type (FIG.9C), with PBMCs demonstrating higher expression of both receptors, consistent with heightened glucocorticoid transcriptional response in PBMCs. Immunostaining of a parallel well demonstrated consistent cell number (4,307 +/- 1,313) and neuronal marker expression (78.5 +/- 6 % MAP2-positive and 0.4 +/- 0.6 % NESTIN-positive) (FIG.2B, FIG.6) that did not significantly differ by diagnosis or glucocorticoid treatment. [00193] HCort dose-dependent transcriptional responses were resolved relative to those in baseline untreated NGN2-neurons. To identify reliable markers of glucocorticoid activation independent of PTSD, diagnosis as well as other confounds were adjusted for. Incubation with increasing HCort concentrations (batch 1: 0 nM, 100 nM, 1000 nM; batch 2: 0 nM, 100 nM, 1000 nM, 2500 nM) resulted in 1,031 and 4,175 DEGs in batch 1, and 165; 3,785; and 4,025 DEGs in batch 2, respectively (q-value < 0.05) (FIG.2C, FIG.11A). Transcriptome- wide concordance was examined using HCort-associated log2 fold-changes and HCort responses between doses was highly concordant and preserved across increasing concentrations of HCort in both batches (FIG.11A). Meta-analysis of differential expression summary statistics found 1,837 significant response genes in the 100 nM dose and 5,956 in the 1000 nM dose (FIG.2D). To assess whether this large transcriptional response to HCort elicited non-specific cell toxicity, we measured cell density of untreated and HCort-treated neurons by quantifying the number of Hoescht-positive neurons in untreated and treated neurons. We observed no significant differences in cell density between doses (FIG.11B). This suggests that HCort treatment in the neurons did not induce significant cell toxicity. As with PBMCs, gene set enrichment for psychiatric disorder gene sets revealed enrichment of HCort upregulated NGN2-neuron DEGs broadly across neuropsychiatric disorder risk genes, but not across PTSD-specific signatures (FIG.2F), again demonstrating that glucocorticoid treatment of NGN2-neurons, without considering PTSD diagnosis, is insufficient to recapitulate PTSD signatures. [00194] Weighted gene co-expression modules were calculated from the meta-analyzed studies to better understand the functional aspects of the HCort-induced transcriptional changes in NGN2-neurons. Seven significant co-expression modules (M1-M7) were identified that were dynamically regulated in response to increasing concentrations of HCort in the signed analysis (FIG.3A). Module eigengene (ME) values for M1-M3 were downregulated with increasing concentrations of HCort and enriched for biological processes related to acetylcholine signaling, such as acetylcholine receptor signaling pathway (p = 1.60e-04), protein degradation such as ubiquitin protein ligase binding (p = 8.28e-05) and skin regulation such as regulation of keratinocyte differentiation (p = 8.15e-05). These signatures are consistent with known glucocorticoid inhibition of acetylcholine signaling and role in skin atrophy. Glucocorticoid-acetylcholine signaling interactions occur in pathways affecting memory consolidation, and alter glutamatergic synapses and synaptic stability, suggesting that glucocorticoid exposure alters acetylcholine signaling to impact glutamatergic synaptic biology. Remaining ME values for modules M4-7 significantly increased with HCort treatment. Many terms within these modules enriched for immune processes such as positive regulation of isotype switching (p = 1.55e-03), regulation of NK T cell differentiation (p = 5.27e-05), and somatic recombination of immunoglobulin gene segments (p = 1.31e-03), processes that are well-established markers of glucocorticoid activation. Finally enrichments for hallmark glucocorticoid processes of histone acetylation such as H4 histone acetyltransferase activity (p = 3.77e-03) and transcriptional suppression (negative regulation of gene expression (p = 1.43e-03)) were enriched. Unsigned modules significantly associated with neural projection terms, such as neural crest cell differentiation (p = 3.96e- 04) and regulation of neuron projection development (p = 1.04e-03), and immune terms, such as regulation of acute inflammatory response (p = 1.83e-03) (FIGs.13A-13B). To visualize module connectivity, protein-protein interactions of genes within modules were mapped, finding a significant observed number of edges in all modules (p<1.0e-16) (FIG.3B). Overall, HCort treatment of NGN2-neurons, independent of diagnosis, resulted in robust down-regulation of acetylcholine signaling and skin development, and up-regulation of inflammation-modulating and cell-signaling genes. [00195] As transcriptomic responses to HCort exposure enriched in neuronal projection and signaling terms, we sought to validate these functional measures of HCort exposure in NGN2-neurons. To visualize the effects of HCort exposure on neurite outgrowth, we performed neurite tracing analysis on NGN2-neurons treated with HCort, finding a dose- dependent decrease in neurite length per neuron after stimulation with 100 nM, 1000 nM and 2500 nM of HCort (FIG.2E). This finding is concordant with previously described dendritic retraction phenotypes in response to trauma-related glucocorticoid signaling. PTSD diagnosis-dependent differences in human neurons [00196] PTSD-specific transcriptional responses to glucocorticoid exposure were examined in human neurons. Baseline gene expression profiles (vehicle; 0 nM HCort) between PTSD-positive and PTSD-negative groups were compared, with no significant differences in gene expression observed (q-value < 0.05) (FIG.4A). Linear contrast analysis was used to examine the extent to which genes respond differently to HCort, relative to baseline, in PTSD-positive relative to PTSD-negative combat veterans, here termed differential response genes (DRGs).1,016 and 402 PTSD-specific DRGs were identified in NGN2-neurons following 100 nM and 1000 nM of HCort, respectively (FIG.4A). The significant DRGs in NGN2-neurons predicted PTSD; for each individual, unsupervised classification revealed a clear pattern of HCort response dysregulation that correctly classified NGN2-neurons from PTSD-positive and PTSD-negative groups (FIG.4B). Meta- analysis revealed shared DRGs across batches (FIG.4C), demonstrating the validity of this PTSD signature. A gene set enrichment analysis of the DRGs against 17 psychiatric disorder gene sets revealed significant enrichment in post-mortem PTSD dorsolateral prefrontal cortex (dlPFC) (p = 2.30e-7), and orbitofrontal cortex (OFC) (p = 0.016) as well as female and male specific interpersonal traumas (p = 1.03e-6, p = 0.005, respectively) (FIG.4D). Altogether, PTSD-specific neuronal DEGs are not detectable at baseline, most significant in response to low (100 nM) glucocorticoid exposure, and enriched for post-mortem PTSD transcriptomic signatures. [00197] The dose-dependent impact of HCort on PTSD case/control status was tested, revealing 740 genes with a significant diagnosis x HCort exposure interactive effect (FDR < 5%) (FIG.4F). From this, three gene categories of interest were evaluated: (1) PTSD x HCort interaction, where expression effect with increasing HCort exposure was significant and in opposite directions in cases and controls (1 gene at FDR < 5%), (2) PTSD hypo- responsivity, where increasing HCort exposure only caused a significant expression change in controls, but not cases (84 genes at FDR < 5%), and (3) PTSD hyper-responsivity, where increasing HCort exposure caused a significant expression change in cases, but not controls (312 genes at FDR < 5%) (FIG.4E). To assess spatial association of significantly interactive genes with common variants associated in PTSD, we mapped imputed expression of PTSD GWAS variants against the significance of the HCort x PTSD interaction term (FIG.5D). Shared peaks were visible in chromosomes 10, 17, and 19. Transcription factor regulation of PTSD hyper-responsivity. [00198] Given previous reports of glucocorticoid hyper-responsivity in PTSD, putative neuronal driver genes that may mediate this hyper-responsivity were predicted. The FUMA pipeline was used to perform gene set enrichment for transcription factor targets, finding 38 significantly enriched transcription factors for which the hyper-responsive genes were targets. To examine differences in regulatory function of these transcription factors within the study, the relationship between transcription factor expression and target expression was investigated in PTSD cases and controls treated with HCort (FIG.5A). In a subset of putative driver genes, increased transcription factor levels more tightly corresponded to increased expression of target genes in neurons derived from PTSD cases than controls. These different patterns of transcription factor co-regulation in PTSD suggest a significant role for these transcription factors in driving PTSD-specific transcriptional response. The co-regulation network was mapped by visualizing protein-protein interactions (FIG.5B), finding a significant observed number of edges (p < 1.0e-16), showing that linked expression of genes in this network translate to a shared effector regulation. Four of these 38 transcription factors, and two targets of identified transcription factors, were noted to be differentially expressed in previously reported post-mortem and/or blood studies of PTSD (p-value of 0.011, binomial test with an alpha of 0.05) (FIG.5C), demonstrating that the study provided considerably more PTSD-specific transcription factors over the prior art. Altogether, coordinated transcriptional regulation and proteomic interaction of a network of transcription factors with shared effector regulation can mediate glucocorticoid hyper-responsiveness in PTSD. Example 2: A method of treating PTSD [00199] Using the methods of the disclosure, an individual diagnosed with PTSD may be treated with a therapeutically effective amount of a glucocorticoid receptor antagonist. Such treatment may alleviate one or more symptoms of the individual’s symptoms of PTSD. Example 3: A method of preventing PTSD [00200] Using the methods of the disclosure, an individual at risk for PTSD may be administered a therapeutically effective amount of a glucocorticoid receptor antagonist and/or a psychedelic agent. Such administration may serve as a prophylactic treatment for one or more symptoms of PTSD or for the development of PTSD. Example 4: A method of treating PTSD [00201] Using the methods of the disclosure, an individual at risk for PTSD, suffering from one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) symptoms associated with PTSD, or diagnosed with PTSD may be treated with one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) agents that modify the glucocorticoid response (e.g., a glucocorticoid receptor antagonist) and/or psychedelic agents. [00202] For example, in some embodiments, the method includes obtaining a biological sample (e.g., blood cells (e.g., peripheral blood mononuclear cells), neurons (e.g., glutamatergic neurons), fibroblasts, or hiPSCs) from the individual suspected of being at risk for PTSD, suffering from one or more symptoms associated with PTSD, or diagnosed with PTSD; processing a cell obtained from the biological sample to produce a test cell; contacting the test cell with a glucocorticoid to produce a glucocorticoid-induced response; detecting the expression and/or activity of one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) genes of the glucocorticoid response (e.g., one or more genes of Table 1 and/or Table 2); identifying an individual as at risk for PTSD or diagnosing the individual with PTSD when the expression or activity of the one or more (genes of the glucocorticoid response are modified relative to a suitable control (e.g., a control with substantially no test agent); and administering to the individual identified as at risk for PTSD or diagnosed with PTSD one or more psychedelic agents and/or agents that modify the glucocorticoid response. [00203] For instance, the individual may be identified as being at risk for PTSD when the expression of two genes of Table 1 are increased relative to a suitable control (e.g., a control with substantially no test agent). Alternatively, for example, the individual may be identified as having PTSD when the activity of three genes of Table 1 are decreased relative to a suitable control (e.g., a control with substantially no test agent). In such instances, the individual identified as at risk for PTSD or diagnosed with PTSD, respectively, may be administered a glucocorticoid receptor antagonist and/or a psychedelic agent. [00204] In another example, an individual at risk for developing PTSD, diagnosed with PTSD, or experiencing one or more symptoms associated with PTSD, may be administered one more agents that modify the glucocorticoid-induced response (e.g., a glucocorticoid receptor antagonist) or one or pyschedelic agents. Such a method may serve as a method of treatment. Example 5: Identifying individuals at risk for PTSD [00205] Using the methods of the disclosure, an individual at risk for PTSD or diagnosed with PTSD may be identified. For instance, in some embodiments, the method includes obtaining a biological sample (e.g., blood cell (e.g., peripheral blood mononuclear cell), neuron (e.g., glutamatergic neuron), fibroblast, or hiPSC) from the individual suspected of being at risk for PTSD or diagnosed with PTSD, processing a cell obtained from the biological sample to produce a test cell, contacting the test cell with a glucocorticoid to produce a glucocorticoid-induced response, detecting the expression and/or activity of the one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) genes of the glucocorticoid response (e.g., one or more genes of Table 1 and/or Table 2), and identifying an individual as having an elevated risk for PTSD or diagnosing the individual with PTSD if the expression and/or activity of the one or more genes of the glucocorticoid response are elevated relative to a suitable control (e.g., a control with substantially no test agent). Alternatively, for example, an individual may be identified as not having an elevated risk for PTSD or not having PTSD if the expression and/or activity of the one or more genes of the glucocorticoid response are not found to be elevated relative to a suitable control (e.g., a control with substantially no test agent). [00206] For example, fibroblasts from an individual suspected of being at risk for PTSD may be obtained, a cell from the biological sample may be processed to produce a test cell, the test cell may be contacted with a glucocorticoid to produce a glucocorticoid-induced response, expression of the one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) genes of the glucocorticoid response of Table 1 may be detected, and the individual may be identified as having an elevated risk for PTSD if the expression of the one or more genes of the glucocorticoid response are elevated relative to a suitable control (e.g., a control with substantially no test agent). Example 6: A Method of screening compounds for treating PTSD [00207] Using the methods of the disclosure, compounds may be screened for their ability to reduce the risk of an individual developing PTSD, reduce the risk of an individual developing one or more symptoms of PTSD, or alleviate one or more symptoms of PTSD. For example, one may obtain cells (e.g., fibroblasts, neurons, or blood cells) from individuals at risk for PTSD or suffering from PTSD, process a cell obtained from the biological sample to produce a test cell, contact the cells (e.g., fibroblasts, neurons, or blood cells) with one or more test agents, detect the expression and/or activity of one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) genes of the glucocorticoid response (e.g., one or more genes of Table 1 and/or Table 2), and identify a test agent as a compound that reduces the risk of an individual developing PTSD, reduces the risk of an individual developing one or more symptoms of PTSD, and/or alleviates one or more symptoms of PTSD in an individual if the test agent reduces the transcriptional profile of the PTSD-dependent glucocorticoid response gene signature (e.g., one or more genes of Table 1 and/or Table 2). [00208] For instance, hiPSCs (e.g., a hiPSC induced glutamatergic neuron) from an individual at risk for PTSD may be obtained, the cells may be contacted with a test agent, the expression of three genes of the glucocorticoid response of Table 1 may be detected by RNA sequencing, the test agent may be found to reduce the transcriptional profile of the PTSD- dependent glucocorticoid response gene signature, and the test agent may be identified as a compound that does reduce the risk of an individual developing PTSD. Example 7: A method for monitoring PTSD status [00209] One can measure PTSD status (e.g., progression or regression) during therapy using the methods of the disclosure. In order to monitor the status of PTSD in an individual, individual samples may be compared to reference samples taken early in the diagnosis of the disorder. Such monitoring may be useful, for example, in assessing the efficacy of a particular therapeutic agent (e.g., a glucocorticoid receptor antagonist) in an individual, determining dosages, or in assessing disease progression or status. For example, the expression and/or activity of any of the genes described herein (e.g., one or more genes from Table 1 and/or Table 2) can be monitored in an individual, and as the expression levels or activities increase or decrease, relative to control, the dosage or administration of therapeutic agents may be adjusted. For example, modifications (e.g., an increase or a decrease as compared to a prior sample of an individual) can be detected to indicate an improvement or decline in PTSD status. For example, the levels of the glucocorticoid response gene signature may be measured repeatedly as a method of monitoring the treatment, prevention, or management of the disorder. Example 8: A method for optimizing the dosage of a compound for the treatment of PTSD [00210] Using the methods of the disclosure, on can determine the proper dosage (e.g., the therapeutically effective amount) of a therapeutic agent for an individual, the proper duration of dosage of a therapeutic agent for an individual, the proper type of therapeutic agent, or whether a therapy should be administered. For example, one may obtain cells (e.g., fibroblasts, neurons, or blood cells) from individuals at risk for PTSD or suffering from PTSD, process a cell obtained from the biological sample to produce a test cell, contact the cells (e.g., fibroblasts, neurons, or blood cells) with one or more test agents, detect the expression and/or activity of one or more (e.g., two, three, four, five, ten, fifteen, or twenty or more) genes of the glucocorticoid response (e.g., one or more genes of Table 1 and/or Table 2), and identify the proper dosage or dosage duration of a test agent by assessing modifications to the transcriptional profile of the PTSD-dependent glucocorticoid response gene signature (e.g., one or more genes of Table 1 and/or Table 2). [00211] For instance, hiPSCs (e.g., a hiPSC induced glutamatergic neuron) from an individual diagnosed with PTSD may be obtained, the cells may be contacted with a test agent, with a dose of a glucocorticoid receptor antagonist the expression of three genes of the glucocorticoid response of Table 1 may be detected by RNA sequencing, the dose of the test agent may have been found to reduce the transcriptional profile of the PTSD-dependent glucocorticoid response gene signature, and the dose of the test agent may be identified as a dose that is therapeutically effective. INCORPORATION BY REFERENCE [00212] The entire disclosure of each of the patent documents and scientific articles cited herein is incorporated by reference for all purposes.
EQUIVALENTS
[00213] The disclosure can be embodied in other specific forms without departing from the essential characteristics thereof. The foregoing embodiments therefore are to be considered illustrative rather than limiting on the disclosure described herein. The scope of the disclosure is indicated by the appended claims rather than by the foregoing description, and all changes that come within the meaning and range of equivalency of the claims are intended to be embraced therein.

Claims

What is claimed is: 1. A psychedelic agent for use in the treatment of post-traumatic stress disorder (PTSD), wherein the individual has modified expression and/or activity of MYC, PAX6, YY1, LEF1, or NFKB1 relative to a suitable control.
2. The psychedelic agent for use of claim 1, wherein the individual has modified expression and/or activity of MYC, PAX6, YY1, and LEF1 relative to a suitable control.
3. The psychedelic agent for use of claim 1 or 2, wherein the individual has increased expression and/or activity of MYC, increased expression and/or activity of PAX6, increased expression and/or activity of YY1, and/or increased expression and/or activity of LEF1.
4. A method of treating an individual having modified expression and/or activity of MYC, PAX6, YY1, LEF1, or NFKB1 relative to a suitable control for post-traumatic stress disorder (PTSD), the method comprising administering to the individual a therapeutically effective amount of a psychedelic agent.
5. The method of claim 4, wherein the individual has modified expression and/or activity of MYC, PAX6, YY1, and LEF1 relative to a suitable control.
6. The method of claim 4 or 5, wherein the individual has increased expression and/or activity of MYC, increased expression and/or activity of PAX6, increased expression and/or activity of YY1, and/or increased expression and/or activity of LEF1.
7. A method of treating an individual diagnosed with PTSD comprising administering to the individual diagnosed with PTSD a therapeutically effective amount of a psychedelic agent and/or glucocorticoid receptor antagonist.
8. The method of claim 7, wherein the individual diagnosed with PTSD is diagnosed with PTSD by a the method comprising: i) obtaining a biological sample from the individual suspected of being at risk for PTSD; ii) processing a cell obtained from the biological sample to produce a test cell; iii) contacting the test cell with a glucocorticoid to produce a glucocorticoid-induced response; iv) detecting the expression and/or activity of one or more gene(s) of the glucocorticoid-induced response; and v) diagnosing the individual with PTSD if the expression and/or activity of the one or more gene(s) of the glucocorticoid-induced response are modified relative to a suitable control.
9. The method of claim 8, wherein the biological sample comprises blood cells and/or fibroblasts.
10. The method of claim 8, wherein processing the cell obtained from the biological sample comprises dedifferentiating the cell to produce an induced pluripotent stem cell (iPSC).
11. The method of claim 10, wherein the iPSC is differentiated to produce the test cell.
12. The method of claim 11, wherein the differentiated iPSC comprises an induced neuron or an induced peripheral blood mononuclear cell.
13. The method of claim 8, wherein the test cell comprises a neuron or a peripheral blood mononuclear cell.
14. The method of claim 13, wherein the neuron is a glutamatergic neuron.
15. The method of claim 8, wherein the glucocorticoid comprises a glucocorticoid receptor agonist.
16. The method of claim 7 or 8, wherein the glucocorticoid receptor agonist is dexamethasone or hydrocortisone.
17. The method of claim 8, wherein the detecting comprises sequencing RNA derived from the biological sample.
18. The method of claim 8, wherein the detecting comprises detecting a transcriptional profile of a glucocorticoid-induced response.
19. The method of claim 8, wherein the detecting comprises assessing epigenetic changes of the one or more gene(s) of the glucocorticoid-induced response.
20. The method of claim 19, wherein the assessing of epigenetic changes comprises performing a chromatin immunoprecipitation assay.
21. The method of claim 8, wherein the expression and/or activity of the one or more gene(s) of the glucocorticoid-induced response is increased for a first subset of genes and decreased for a second subset of genes to produce a glucocorticoid-induced response signature.
22. The method of claim 8, wherein the processing comprises automated reprogramming of the cell obtained from the biological sample.
23. The method of claim 8, wherein contacting the test cell with a glucocorticoid is performed for a duration of from about 1 hour to about 96 hours.
24. The method of claim 8, wherein the glucocorticoid has a concentration of from about 1 nM to about 10 µM.
25. A method of preventing PTSD in an individual at risk for PTSD comprising administering to the individual a therapeutically effective amount of a glucocorticoid receptor antagonist and/or a psychedelic agent.
26. The method of claim 25, wherein an individual at risk for PTSD is identified as an individual at risk for PTSD by the method comprising: i) obtaining a biological sample from the individual suspected of being at risk for PTSD; ii) processing a cell obtained from the biological sample to produce a test cell; iii) contacting the test cell with a glucocorticoid to produce a glucocorticoid-induced response; iv) detecting the expression and/or activity of one or more gene(s) of the glucocorticoid-induced response; and v) identifying the individual as at risk for PTSD or if the expression and/or activity of the one or more gene(s) of the glucocorticoid-induced response are modified relative to a suitable control.
27. The method of claim 26, wherein the biological sample comprises blood cells and/or fibroblasts.
28. The method of claim 26, wherein processing the cell obtained from the biological sample comprises dedifferentiating the cell to produce an iPSC.
29. The method of claim 28, wherein the iPSC is differentiated to produce the test cell.
30. The method of claim 29, wherein the differentiated iPSC comprises an induced neuron or an induced peripheral blood mononuclear cell.
31. The method of claim 26, wherein the test cell comprises a neuron or a peripheral blood mononuclear cell.
32. The method of claim 31, wherein the neuron is a glutamatergic neuron.
33. The method of claim 26, wherein the glucocorticoid comprises a glucocorticoid receptor agonist.
34. The method of claim 26, wherein the glucocorticoid receptor agonist is dexamethasone or hydrocortisone.
35. The method of claim 26, wherein the detecting comprises sequencing RNA derived from the biological sample.
36. The method of claim 26, wherein the detecting comprises detecting a transcriptional profile of a glucocorticoid-induced response.
37. The method of claim 26, wherein the detecting comprises assessing epigenetic changes of the one or more gene(s) of the glucocorticoid-induced response.
38. The method of claim 37, wherein the assessing of epigenetic changes comprises performing a chromatin immunoprecipitation assay.
39. The method of claim 26, wherein the expression and/or activity of the one or more gene(s) of the glucocorticoid-induced response is increased for a first subset of genes and decreased for a second subset of genes to produce a glucocorticoid-induced response signature.
40. The method of claim 26, wherein the processing comprises automated reprogramming of the cell obtained from the biological sample.
41. The method of claim 26, wherein contacting the test cell with a glucocorticoid is performed for a duration of from about 1 hour to about 96 hours.
42. The method of claim 26, wherein the glucocorticoid has a concentration of from about 1 nM to about 10 µM.
43. A method of treating an individual at risk for PTSD, suffering from one or more symptoms associated with PTSD, and/or diagnosed with PTSD, the method comprising: i) obtaining a biological sample from the individual suspected of being at risk for PTSD, suffering from one or more symptoms associated with PTSD, or diagnosed with PTSD; ii) processing a cell obtained from the biological sample to produce a test cell; iii) contacting the test cell with a glucocorticoid to produce a glucocorticoid-induced response; iv) detecting the expression and/or activity of one or more gene(s) of the glucocorticoid-induced response; v) identifying the individual as at risk for PTSD or diagnosing the individual with PTSD when the expression and/or activity of the one or more gene(s) of the glucocorticoid-induced response are modified relative to a suitable control; and vi) administering to the individual identified as at risk for PTSD or diagnosed with PTSD one or more psychedelic agent(s) and/or agent(s) that modify the glucocorticoid-induced response.
44. The method of claim 43, wherein the one or more gene(s) of the glucocorticoid-induced response comprise one or more genes selected from the group consisting of MAN1A2, CD1D, CEP350, DISP1, USP37, NPHP3, GOLGA4, KIAA1109, DKK4, BMI1, NEDD4, NF1, CEACAM19, ZNF235, KRCC1, KCTD16, RP11-664D7.4, C8orf87, ANO1, PACS1, UBQLNL, LRRC56, DPYSL4, HMBS, SNRNP35, TM2D3, C17orf75, GATA5, ZNF443, ZC3H12B, RSF1, KPNA4, C12orf57, ATP6V0B, ANAPC11, KCNK2, OR7D2, NUDT16, ANKRD17, ERGIC3, KLF7, PEAK1, ASAP1, MIAT, SGPP2, RPS11, A1L2, CSMD1, PEX6, PDE11A, MASP1, IL1RAPL2, MRPL11, RBX1, TMEM98, IFT27, PPIB, DCTN3, TOMM22, CALCB, RNF152, TIMP3, ZNF587, FGD5, NTAN1P2, C9orf169, GJA10, ZNF385C, MAN1A2, BMI1, CTC-448F2.6, CORO6, TTLL6, YY1, XBP1, USF2, USF1, TEF, STAT1, SRF, SREBF1, SP1, SOX5, SMAD3, POU3F2, PAX6, NRF1, NFKB1, MYC, MEIS1, MEF2A, MAF, LEF1, HSF1, HLF, FOXO1, ETS2, ETF1, ELK1, ELF1, EGR1, E4F1, E2F4, E2F3, E2F1, CREB1, CEBPG, CDPF1, ATF4, ATF3, and combinations thereof.
45. The method of claim 43, wherein the one or more gene(s) of the glucocorticoid-induced response are increased relative to a suitable control.
46. The method of claim 45, wherein the one or more gene(s) comprise one or more genes selected from the group consisting of ZC3H12B, RSF1, ANKRD17, KLF7, PEAK1, ASAP1, MIAT, SGPP2, RPS11, A1L2, CSMD1, PEX6, PDE11A, DCTN3, TIMP3, ZNF587, and combinations thereof.
47. The method of claim 43, wherein the one or more gene(s) of the glucocorticoid-induced response are decreased relative to a suitable control.
48. The method of claim 47, wherein the one or more gene(s) comprise one or more genes selected from the group consisting of KPNA4, C12orf57, ATP6V0B, ANAPC11, KCNK2, OR7D2, NUDT16, ERGIC3, MASP1, IL1RAPL2, MRPL11, RBX1, TMEM98, IFT27, PPIB, TOMM22, CALCB, RNF152, and combinations thereof.
49. The method of claim 43, wherein the suitable control comprises a prior biological sample taken from the same individual, a biological sample from a healthy individual not having a risk for PTSD, a biological sample from an individual not having one or more symptoms associated with PTSD, or a biological sample from an individual that is diagnosed with PTSD that has been treated for PTSD.
50. The method of claim 43, wherein the biological sample comprises blood cells and/or fibroblasts.
51. The method of claim 43, wherein processing the cell obtained from the biological sample comprises dedifferentiating the cell to produce an iPSC.
52. The method of claim 51, wherein the iPSC is differentiated to produce the test cell.
53. The method of claim 52, wherein the differentiated iPSC comprises an induced neuron or an induced peripheral blood mononuclear cell.
54. The method of claim 43, wherein the test cell comprises a neuron or a peripheral blood mononuclear cell.
55. The method of claim 54, wherein the neuron is a glutamatergic neuron.
56. The method of claim 43, wherein the glucocorticoid comprises a glucocorticoid receptor agonist.
57. The method of claim 43, wherein the glucocorticoid receptor agonist is dexamethasone or hydrocortisone.
58. The method of claim 43, wherein the one or more agent(s) that modify the glucocorticoid- induced response comprises a glucocorticoid receptor antagonist.
59. The method of claim 43, wherein the detecting comprises sequencing RNA derived from the biological sample.
60. The method of claim 43, wherein the detecting comprises detecting a transcriptional profile of a glucocorticoid-induced response.
61. The method of claim 43, wherein the detecting comprises assessing epigenetic changes of the one or more gene(s) of the glucocorticoid-induced response.
62. The method of claim 61, wherein one or more gene(s) of the glucocorticoid-induced response comprise one or more genes selected from the group consisting of MAN1A2, CD1D, CEP350, DISP1, USP37, NPHP3, GOLGA4, KIAA1109, DKK4, BMI1, NEDD4, NF1, CEACAM19, ZNF235, KRCC1, KCTD16, RP11-664D7.4, C8orf87, ANO1, PACS1, UBQLNL, LRRC56, DPYSL4, HMBS, SNRNP35, TM2D3, C17orf75, GATA5, ZNF443, ZC3H12B, RSF1, KPNA4, C12orf57, ATP6V0B, ANAPC11, KCNK2, OR7D2, NUDT16, ANKRD17, ERGIC3, KLF7, PEAK1, ASAP1, MIAT, SGPP2, RPS11, A1L2, CSMD1, PEX6, PDE11A, MASP1, IL1RAPL2, MRPL11, RBX1, TMEM98, IFT27, PPIB, DCTN3, TOMM22, CALCB, RNF152, TIMP3, ZNF587, FGD5, NTAN1P2, C9orf169, GJA10, ZNF385C, MAN1A2, BMI1, CTC-448F2.6, CORO6, TTLL6, YY1, XBP1, USF2, USF1, TEF, STAT1, SRF, SREBF1, SP1, SOX5, SMAD3, POU3F2, PAX6, NRF1, NFKB1, MYC, MEIS1, MEF2A, MAF, LEF1, HSF1, HLF, FOXO1, ETS2, ETF1, ELK1, ELF1, EGR1, E4F1, E2F4, E2F3, E2F1, CREB1, CEBPG, CDPF1, ATF4, ATF3, and combinations thereof.
63. The method of claim 61, wherein the assessing of epigenetic changes comprises performing a chromatin immunoprecipitation assay.
64. The method of claim 43, wherein the expression and/or activity of the one or more gene(s) of the glucocorticoid-induced response is increased for a first subset of genes and decreased for a second subset of genes to produce a glucocorticoid-induced response signature.
65. The method of claim 43, wherein the one or more agent(s) is administered via a parenteral or a non-parenteral route.
66. The method of claim 43, wherein the processing comprises automated reprogramming of the cell obtained from the biological sample.
67. The method of claim 43, wherein contacting the test cell with a glucocorticoid is performed for a duration of from about 1 hour to about 96 hours.
68. The method of claim 43, wherein the glucocorticoid has a concentration of from about 1 nM to about 10 µM.
69. A method for identifying an individual at risk for PTSD or diagnosed with PTSD, the method comprising: i) obtaining a biological sample from the individual suspected of being at risk for PTSD or diagnosed with PTSD; ii) processing a cell obtained from the biological sample to produce a test cell; iii) contacting the test cell with a glucocorticoid to produce a glucocorticoid-induced response; iv) detecting the expression and/or activity of one or more gene(s) of the glucocorticoid-induced response; and v) identifying the individual as at risk for PTSD or diagnosing the individual with PTSD if the expression and/or activity of the one or more gene(s) of the glucocorticoid-induced response are modified relative to a suitable control.
70. The method of claim 69, wherein the biological sample comprises blood cells and/or fibroblasts.
71. The method of claim 69, wherein processing the cell obtained from the biological sample comprises dedifferentiating the cell to produce an iPSC.
72. The method of claim 71, wherein the iPSC is differentiated to produce the test cell.
73. The method of claim 72, wherein the differentiated iPSC comprises an induced neuron or an induced peripheral blood mononuclear cell.
74. The method of claim 69, wherein the test cell comprises a neuron or a peripheral blood mononuclear cell.
75. The method of claim 74, wherein the neuron is a glutamatergic neuron.
76. The method of claim 69, wherein the glucocorticoid comprises a glucocorticoid receptor agonist.
77. The method of claim 69, wherein the glucocorticoid receptor agonist is dexamethasone or hydrocortisone.
78. The method of claim 69, wherein the detecting comprises sequencing RNA derived from the biological sample.
79. The method of claim 69, wherein the detecting comprises detecting a transcriptional profile of a glucocorticoid-induced response.
80. The method of claim 69, wherein the detecting comprises assessing epigenetic changes of the one or more gene(s) of the glucocorticoid-induced response.
81. The method of claim 80, wherein the assessing of epigenetic changes comprises performing a chromatin immunoprecipitation assay.
82. The method of claim 69, wherein the expression and/or activity of the one or more gene(s) of the glucocorticoid-induced response is increased for a first subset of genes and decreased for a second subset of genes to produce a glucocorticoid-induced response signature.
83. The method of claim 69, wherein the processing comprises automated reprogramming of the cell obtained from the biological sample.
84. The method of claim 69, wherein contacting the test cell with a glucocorticoid is performed for a duration of from about 1 hour to about 96 hours.
85. The method of claim 69, wherein the glucocorticoid has a concentration of from about 1 nM to about 10 µM.
86. A method of treating an individual at risk for developing PTSD, diagnosed with PTSD, or experiencing one or more symptoms associated with PTSD, the method comprising administering to the individual one more psychedelic agent(s) and/or agent(s) that modify the glucocorticoid-induced response.
87. The method of claim 86, wherein the one or more agent(s) that modify the glucocorticoid- induced response comprises a glucocorticoid receptor antagonist.
88. The method of claim 86, wherein the one or more agent(s) is administered via a parenteral or a non-parenteral route.
89. A method for screening compounds that reduce the risk of an individual developing PTSD, reduce the risk of an individual developing one or more symptoms of PTSD, and/or alleviate one or more symptoms of PTSD in an individual, the method comprising: i) obtaining a biological sample from the individual at risk for PTSD or suffering from PTSD; ii) processing a cell obtained from the biological sample to produce a test cell; iii) contacting the test cell with a glucocorticoid to produce a glucocorticoid-induced response; iv) contacting the test cell with one or more test agent(s); detecting the expression and/or activity of one or more gene(s) of the glucocorticoid-induced response; and v) if the one or more test agent(s) modifies the expression and/or activity of one or more gene(s) of the glucocorticoid-induced response compared to a suitable control, identifying the test agent as a compound that does reduce the risk of an individual developing PTSD, reduce the risk of an individual developing one or more symptoms of PTSD, and/or alleviate one or more symptoms of PTSD in an individual.
90. The method of claim 89, wherein the one or more gene(s) of the glucocorticoid-induced response comprise one or more genes selected from the group consisting of MAN1A2, CD1D, CEP350, DISP1, USP37, NPHP3, GOLGA4, KIAA1109, DKK4, BMI1, NEDD4, NF1, CEACAM19, ZNF235, KRCC1, KCTD16, RP11-664D7.4, C8orf87, ANO1, PACS1, UBQLNL, LRRC56, DPYSL4, HMBS, SNRNP35, TM2D3, C17orf75, GATA5, ZNF443, ZC3H12B, RSF1, KPNA4, C12orf57, ATP6V0B, ANAPC11, KCNK2, OR7D2, NUDT16, ANKRD17, ERGIC3, KLF7, PEAK1, ASAP1, MIAT, SGPP2, RPS11, A1L2, CSMD1, PEX6, PDE11A, MASP1, IL1RAPL2, MRPL11, RBX1, TMEM98, IFT27, PPIB, DCTN3, TOMM22, CALCB, RNF152, TIMP3, ZNF587, FGD5, NTAN1P2, C9orf169, GJA10, ZNF385C, MAN1A2, BMI1, CTC-448F2.6, CORO6, TTLL6, YY1, XBP1, USF2, USF1, TEF, STAT1, SRF, SREBF1, SP1, SOX5, SMAD3, POU3F2, PAX6, NRF1, NFKB1, MYC, MEIS1, MEF2A, MAF, LEF1, HSF1, HLF, FOXO1, ETS2, ETF1, ELK1, ELF1, EGR1, E4F1, E2F4, E2F3, E2F1, CREB1, CEBPG, CDPF1, ATF4, ATF3, and combinations thereof.
91. The method of claim 89, wherein the one or more test agent(s) increases the expression and/or activity of one or more gene(s) of the glucocorticoid-induced response.
92. The method of claim 91, wherein the one or more gene(s) comprise one or more genes selected from the group consisting of ZC3H12B, RSF1, ANKRD17, KLF7, PEAK1, ASAP1, MIAT, SGPP2, RPS11, A1L2, CSMD1, PEX6, PDE11A, DCTN3, TIMP3, ZNF587, and combinations thereof.
93. The method of claim 89, wherein the one or more test agent(s) decreases the expression and/or activity of one or more gene(s) of the glucocorticoid-induced response.
94. The method of claim 93, wherein the one or more gene(s) comprise one or more genes selected from the group consisting of KPNA4, C12orf57, ATP6V0B, ANAPC11, KCNK2, OR7D2, NUDT16, ERGIC3, MASP1, IL1RAPL2, MRPL11, RBX1, TMEM98, IFT27, PPIB, TOMM22, CALCB, RNF152, and combinations thereof.
95. The method of claim 89, wherein the suitable control comprises a prior biological sample taken from the same individual, a biological sample from a healthy individual not having a risk for PTSD, a biological sample from an individual not having one or more symptoms associated with PTSD, or a biological sample from an individual that is diagnosed with PTSD that has been treated for PTSD.
96. The method of claim 89, wherein the biological sample comprises blood cells and/or fibroblasts.
97. The method of claim 89, wherein processing the cell obtained from the biological sample comprises dedifferentiating the cell to produce an iPSC.
98. The method of claim 93, wherein the iPSC is differentiated to produce the test cell.
99. The method of claim 98, wherein the differentiated iPSC comprises an induced neuron or an induced peripheral blood mononuclear cell.
100. The method of claim 89, wherein the test cell comprises a neuron or a peripheral blood mononuclear cell.
101. The method of claim 100, wherein the neuron is a glutamatergic neuron.
102. The method of claim 89, wherein the glucocorticoid comprises a glucocorticoid receptor agonist.
103. The method of claim 89, wherein the glucocorticoid receptor agonist is dexamethasone or hydrocortisone.
104. The method of claim 89, wherein the detecting comprises sequencing RNA derived from the biological sample.
105. The method of claim 89, wherein the detecting comprises detecting a transcriptional profile of a glucocorticoid-induced response.
106. The method of claim 89, wherein the detecting comprises assessing epigenetic changes of the one or more gene(s) of the glucocorticoid-induced response.
107. The method of claim 106, wherein the assessing of epigenetic changes comprises performing a chromatin immunoprecipitation assay.
108. The method of claim 89, wherein the expression and/or activity of the one or more gene(s) of the glucocorticoid-induced response is increased for a first subset of genes and decreased for a second subset of genes to produce a glucocorticoid-induced response signature.
109. The method of claim 89, wherein the suitable control comprises substantially no test agent.
110. The method of claim 89, wherein the processing comprises automated reprogramming of the cell obtained from the biological sample.
111. The method of claim 89, wherein contacting the test cell with a glucocorticoid is performed for a duration of from about 1 hour to about 96 hours.
112. The method of claim 89, wherein the glucocorticoid has a concentration of from about 1 nM to about 10 µM.
113. The method of claim 89, wherein contacting the test cell with one or more test agent(s) is performed for a duration of from about 1 hour to about 96 hours.
114. The method of claim 89, wherein the test agent has a concentration of from about 1 nM to about 10 µM.
115. A method of identifying a PTSD-dependent glucocorticoid response gene signature, the method comprising: i) obtaining a biological sample from an individual suspected of being at risk for PTSD, suffering from one or more symptoms associated with PTSD, or diagnosed with PTSD; ii) processing a cell obtained from the biological sample to produce a test cell; iii) contacting the test cell with a glucocorticoid to produce a glucocorticoid-induced response; iv) detecting the expression and/or activity of a plurality of genes; and v) comparing the expression and/or activity of the plurality of genes with the expression and/or activity of the plurality of genes from a suitable control sample obtained from a healthy individual.
116. The method of any one of claims 7-115, wherein the individual is a juvenile.
117. A method of treating an individual at risk for PTSD, suffering from one or more symptoms associated with PTSD, or diagnosed with PTSD, the method comprising: administering to the individual one or more psychedelic agent(s) and/or agent(s) that modify the glucocorticoid-induced response, wherein expression and/or activity of one or more gene(s) of the glucocorticoid- induced response in test cells produced from a biological sample obtained from the individual were modified relative to a suitable control when such test cells were contacted with a glucocorticoid.
118. A psychedelic agent for use in a method of treating an individual at risk for PTSD, suffering from one or more symptoms associated with PTSD, or diagnosed with PTSD, wherein expression and/or activity of one or more gene(s) of the glucocorticoid-induced response in test cells produced from a biological sample obtained from the individual were modified relative to a suitable control when such test cells were contacted with a glucocorticoid.
119. An agent that modifies the glucocorticoid response for use in a method of treating an individual at risk for PTSD, suffering from one or more symptoms associated with PTSD, or diagnosed with PTSD, wherein expression and/or activity of one or more gene(s) of the glucocorticoid-induced response in test cells produced from a biological sample obtained from the individual were modified relative to a suitable control when such test cells were contacted with a glucocorticoid.
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