WO2010039526A1 - Gènes et polymorphismes de nucléotide unique pour un essai génétique de trouble bipolaire - Google Patents

Gènes et polymorphismes de nucléotide unique pour un essai génétique de trouble bipolaire Download PDF

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WO2010039526A1
WO2010039526A1 PCT/US2009/058003 US2009058003W WO2010039526A1 WO 2010039526 A1 WO2010039526 A1 WO 2010039526A1 US 2009058003 W US2009058003 W US 2009058003W WO 2010039526 A1 WO2010039526 A1 WO 2010039526A1
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snps
bipolar
snp
genes
disorder
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Alexander B. Niculescu
Helen Le-Niculescu
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Indiana University Research And Technology Corporation
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    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C12Q1/6876—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes
    • C12Q1/6883—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/156—Polymorphic or mutational markers
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/172—Haplotypes

Definitions

  • This disclosure relates to analysis and identification of markers including SNPs and blood biomarkers for genetic testing and risk prediction of bipolar mood disorder.
  • One strategy is to include in the next generation of GWAS, larger number of subjects, and/or pool independent studies into meta-analyses.
  • An alternate Bayesian approach, convergent functional genomics (CFG) is disclosed herein to mine the GWAS datasets for existing signals that did not reach significance using a genetics-only approach.
  • CFG convergent functional genomics
  • the integration of genetics with genomics, of human and animal model data, and of multiple independent lines of evidence converging on the same genes offers a way of extracting signal from noise, and prioritizing candidates for focused validatory studies- individual candidate gene association studies with more SNPs tested per gene, deep re-sequencing, and/or biological validation such as transgenic animal work.
  • a population of organisms will contain several variants (alleles) of a given gene.
  • Alleles can differ from one another at single base pair. These single base pair differences are called single nucleotide polymorphisms (SNPs), and several can be present in a single gene.
  • SNPs single nucleotide polymorphisms
  • High-throughput genotyping methods using high-density nucleic acid arrays and other methods can accurately genotype (i.e., determine the nucleotide(s) present) hundreds or thousands of SNPs in a genetic sample in parallel to provide an unequivocal molecular fingerprint of the genetic sample.
  • somatic cells of diploid organisms have two copies of each autosomal gene and many high throughput genotyping techniques are sensitive enough to analyze a SNP to determine if an individual is homozygous for a first allele, homozygous for a second allele, or heterozygous (i.e., possesses one copy of each allele).
  • the results of this analysis can be used for research and for making diagnostic and therapeutic decisions.
  • GRPS Genetic Risk Prediction Score
  • the analysis herein is the most comprehensive integration of genetics and functional genomics to date in the field of bipolar disorder, identifying a series of the very best candidate genes for bipolar disorder. Moreover, a comprehensive list of highly probative Single Nucleotide Polymorphisms (SNPs) was generated. Panels of such SNPs are used for genetic testing for bipolar disorder before the illness manifests itself. A Genetic Risk Prediction Score (GRPS) was developed based on such panels and it is demonstrated how in a test cohort the GRPS differentiates between patients with bipolar disorder and normal controls, as well as shows a trend towards predicting earlier age of onset for bipolar disorder. Such testing is used for diagnostics and personalized medicine approaches in general, and specifically for early detection and prevention efforts in high-risk individuals.
  • GRPS Genetic Risk Prediction Score
  • a method of diagnosing a mood disorder includes:
  • the level of the marker is determined in a tissue biopsy sample of the individual by a method selected from the group consisting of analyzing the expression level of RNA transcripts, analyzing the level of protein or peptides or fragments thereof and by an analytical technique selected from the group consisting of microarray gene expression analysis, polymerase chain reaction (PCR), real-time PCR, quantitative PCR, immunohistochemistry, enzyme-linked immunosorbent assays (ELISA), and antibody arrays.
  • the determination of the level of the plurality of biomarkers may also be performed by an analysis of the presence or absence of the biomarkers. In an embodiment, the presence or absence of the biomarkers is performed through an SNP analysis.
  • a method of diagnosing mood disorder includes:
  • a method of predicting the probable course and outcome (prognosis) of a mood disorder comprising: [00020] (a) obtaining a test sample from a subject, wherein the subject is suspected of having a mood disorder; [00021] (b) analyzing the test sample for the presence or level of a plurality of markers of the mood disorder, the markers selected from the group consisting of markers listed in Table 1; and [00022] (c) determining the prognosis of the subject based on the presence or level of the markers and one or more clinicopathological data to implement a particular treatment plan for the subject.
  • the clinicopathological data is selected from the group consisting of patient age, previous personal and/or familial history of the mood disorder, previous personal and/or familial history of response to medications, and any genetic or biochemical predisposition to psychiatric illness.
  • a method of predicting the likelihood of a successful treatment for a mood disorder in a patient includes: [00025] (a) determining the expression level or the presence of one or more polymorphisms for at least 10 genes (markers) from Table 1; and [00026] (b) predicting the likelihood of successful treatment for the mood disorder by determining whether the sample from the patient expresses biomarkers or has a polymorphism associated with a high mood disorder (mania) or a low mood disorder
  • a method of treating a patient suspected of suffering a mood disorder includes: [00028] (a) diagnosing whether the patient suffers from a high mood or a low mood disorder by determining the expression level or a polymorphism for one or more of the biomarkers listed in Table 1 in a sample obtained from the patient; [00029] (b) selecting a treatment for the mood disorder based on the determination whether the patient suffers from a high mood or a low mood disorder; and
  • the treatment plan is a personalized plan for the patient.
  • kits for diagnosing a mood disorder comprising a component selected from the group consisting of (i) oligonucleotides for amplification of one or more markers listed in
  • a diagnostic microarray comprising a panel of about 10 biomarkers that are predictive of a mood disorder, wherein the microarray comprises one or more nucleic acid fragments representing biomarkers listed in Table 1.
  • a diagnostic microarray consisting essentially of nucleic acid sequences to determine the expression levels or sequence polymorphisms of a plurality of markers/genes listed in Table 1.
  • a method of predicting increased or decreased risk for bipolar mood disorder in a psychiatric patient or a person suspected of having a bipolar disorder or a person to be screened for an increased risk for bipolar disorder includes: [00036] (a) determining the presence of a plurality of SNPs for the bipolar disorder in an isolated sample from a subject, the plurality of SNPs selected from the group listed in
  • a method for assessing the likelihood of having an increased risk of bipolar disorder in an individual or a patient or a subject includes: [00039] (a) analyzing a sample from a subject for the occurrence of one or more single nucleotide polymorphism (SNPs) selected from the SNPs listed in Tables 1-3 or one or more blood biomarkers listed in Tables 1-3, wherein the occurrence of a plurality of the SNPs listed in Tables 1-3.
  • SNPs single nucleotide polymorphism
  • the plurality of SNPs are present in one or more of the genes or fragments thereof selected from the group consisting of about 30 genes designated as Arntl, Bdnf, Grial, Mbp, Adhlal, Cugbp2, Disci, Grm3, KIf 12, Nosl, Rorb, A2bpl, Ank2, Cacnala, Drd2, Dscam, Gsk3b, Htr2a, Nav2, Nr3cl, Nrcam, Nrgl, Oprml, Pcdh9, Prkce, Ptn, Ryr3, Tnik, Ank3 and Cd44.
  • the plurality of SNPs are present in one or more of the genes or fragments thereof selected from the group consisting of about 10 genes designated as Arntl, Bdnf, Glial, Mbp, Adhlal, Cugbp2, Disci, Grm3, KIf 12, and Nosl.
  • the blood biomarkers are selected from the group consisting of genes designated as Bdnf, Mbp, Cugbp2, Disci, KIf 12, Nrgl, Tnik, Cd44, Diaphl, Pde4b, And Qki or fragments thereof.
  • the bipolar disorder is depression (major depressive disorder).
  • Suitable samples include for example, a bodily fluid, such as blood or a tissue biopsy sample of the individual.
  • Suitable samples also include for example, a test sample selected from the group consisting of fresh blood, stored blood, fixed, paraffin-embedded tissue, tissue biopsy, tissue microarray, fine needle aspirates, peritoneal fluid, ductal lavage and pleural fluid or a derivative thereof.
  • the expression of biomarkers may be determined by direct imaging of a suitable tissue such as a brain tissue in vivo.
  • Suitable techniques for determining SNP is by PCR or by direct sequencing or by a hybridization technique or by a microarray analysis.
  • a method of predicting the probable course and outcome (prognosis) of a bipolar mood disorder includes:
  • a method of providing a personalized treatment plan for a bipolar mood disorder includes: [00052] (a) determining the presence of one or more polymorphisms for at least 10 genes from Table 1 ; [00053] (b) determining whether the sample from the patient has polymorphisms associated with an increased risk for high mood disorder (mania) or a low mood disorder
  • a method for diagnosing bipolar disorder in a human subject includes: obtaining a sample from the subject; identifying the occurrence of a single nucleotide polymorphism
  • SNP in linkage disequilibrium with one or more SNPs or genes selected from the SNPs or genes listed in Tables 1-3, wherein the occurrence of one or more SNPs in linkage disequilibrium with an SNP or gene of Tables 1-3 is associated with an increased likelihood that the patient is suffering from bipolar disorder; and reporting or recording said diagnosis based on said occurrence.
  • a method for diagnosing the presence of a polymorphism in a marker gene selected from the list of markers in Tables 1-3, wherein the polymorphism predisposes a human to bipolar disease includes: [00057] (a) obtaining a sample from a human subject; contacting said sample with a reagent, wherein said reagent provides a detectable signal indicative of the presence of a polymorphism in said gene; and
  • a method for distinguishing between bipolar illness and schizophrenia in a subject includes: identifying the presence of one or more single nucleotide polymorphisms (SNPs) selected from the SNPs listed in Table 2 and Table 3, wherein the presence of one or more of said SNPs is associated with an increased likelihood of bipolar disorder.
  • SNPs single nucleotide polymorphisms
  • a kit for predicting associated genetic risk for a bipolar mood disorder includes in separate compartments, oligonucleotides for amplification of one or more markers listed in
  • a diagnostic microarray comprising a panel of about 10 or more biomarkers that are predictive of a bipolar disorder, wherein the microarray comprises one or more nucleic acid fragments representing one or more genes listed in Table 1 containing one or more SNPs associated with an increased or a decreased risk for the bipolar disorder.
  • a diagnostic microarray consisting essentially of nucleic acid sequences to determine the single nucleotide polymorphisms of a plurality of markers/genes listed in
  • a DNA microchip for SNP discrimination the DNA chip having a substrate with plural reaction regions formed as spots for hybridization on a surface of the substrate, comprising: four detection probes, which have at least a flanking sequence around an SNP in a specific gene listed in Tables 2 and 3, are different in base species at a site of said SNP, and are separately held in different ones of said reaction regions.
  • Panels of SNPs and/or blood biomarkers include for example, the top 10, 12, 15, 18,
  • SNPs from the genes listed in Tables 1-3 or blood biomarkers listed in Tables 1-3.
  • FIG. 1 shows Convergent Functional Genomics (CFG) to integrate multiple independent lines of evidence for Bayesian cross-validation of GWAS data.
  • CFG Convergent Functional Genomics
  • FIG. 2 illustrates top candidate genes for bipolar disorder identified by CFG of
  • GWAS data CFG score depicted on the right side of the pyramid.
  • Bold font- the gene has human postmortem evidence.
  • Underlined- the gene has additional human genetic evidence beyond the GWAS data.
  • Red/circled- the gene has blood gene expression evidence making it a possible blood biomarker.
  • FIG. 3 shows a comprehensive model for bipolar disorder pathophysiology.
  • FIGS. 4 and 5 show the Genetic Risk Prediction Score (GRPS) based on a panel of the best SNPs from a set of top genes for bipolar disorder.
  • the GRPS shows statistically significant differences between subjects with bipolar disorder and normal controls, in both males (FIG. 4) and females (FIG. 5), as well as a trend to a higher GRPS in early onset vs. late onset bipolar disorder in males.
  • FIG. 6 shows how people can be staged or classified into categories of risk for bipolar mood disorder based on their GRPS scores.
  • An independent cohort containing normal controls and bipolar were analyzed. Thresholds derived from the analysis described in FIGS. 4B and 5B were used. If the GRPS score of a new subject tested falls above the average GRPS for bipolar in the reference cohort, the individual will be categorized as being at higher risk for bipolar (Category 1- between the average and one standard deviation, Category 2- between 1 and 2 standard deviations, Category 3- between 2 and 3 standard deviations, and Category 4- above 3 standard deviations).
  • the individual will be categorized as being at lower risk for bipolar (Category -1- between the average and one standard deviation, Category -2- between 1 and 2 standard deviations, Category -3- between 2 and 3 standard deviations, and Category -A- above 3 standard deviations). Categories with - in front mean lower risk, positive categories with mean higher risk.
  • the new subjects GRPS score is a Category -1, it can be predicted with about 75% accuracy that they will not develop bipolar, if they are a Category -2, with 80% accuracy they will not develop bipolar, if they are a Category -3, with 85% accuracy they will not develop bipolar, and a category -4 , with 100% accuracy they will not likely develop bipolar.
  • the new subject's GRPS score is a Category 4, it can be predicted with about 50% accuracy they will develop bipolar.
  • SNPs DNA sequences
  • Phenotypic testing may be more reliable precise when the illness has already manifested itself, and may be readily diagnosed using clinical criteria.
  • a complicating factor can be that people who are ill with psychiatric disorders, such as bipolar disorder, may sometimes not report accurately their symptoms to clinicians.
  • Biomarkers e.g., gene expression levels are capable of providing early detection and precision.
  • genes and environment leads to gene expression, which is an endophenotype (internal building block for phenotype), and underlies the subsequent ultimate manifestation of external phenotype (such as symptomatic clinical illness).
  • endophenotype internal building block for phenotype
  • phenotypic testing generally increase the yield in terms of combining earlier detection with better precision.
  • CFG Convergent functional genomics
  • the Bonferroni correction may be optional. Moreover, it could introduce a bias against large-size genes, which by and large have more SNPs tested than smaller genes. The converse is true if a correction is not performed for number of SNPs tested and one would expect some noise due to gene size effects.
  • this evidence is being used for integration across platforms and modalities, along with a series of other lines of evidence that have their own attendant noise, as part of a Bayesian approach to characterize signal from noise and prioritize findings. The convergence of lines of evidence likely factors out the noise of the different individual approaches, and makes the network-like CFG approach relatively resilient to error even when one or another of the nodes (lines of evidence) is less strong.
  • methods disclosed herein rely on a list of genes from the GWAS datasets generated by SNPPER identifying SNPs in genes. SNPs that fall into regulatory regions, such as promoter or enhancer regions may also be accounted for. These genes are then cross-matched with gene expression data from various animal model and human datasets generated earlier, and other data. This approach may be termed Convergent Functional Genomics (CFG) methodology. Genes where the illnesses associated SNPs that do not lead to a change in expression levels are generally not captured by the CFG-GWAS cross-validation approach tested here, since gene expression evidence is used as a criteria to mine and extract data from GWAS.
  • CFG Convergent Functional Genomics
  • genes that have changes in expression levels but no intragenic SNP in the GWAS datasets are generally not captured. Some of these later genes may be changed in expression as a consequence of distal regulatory SNPs or other genes in a network, which may be accounted for by other approaches/analytical tools known to those of skilled in the art.
  • Animal model data may be used for CFG cross-validation, in addition to the data from the pharmacogenomic (e.g., methamphetamine/valproate) and the genetic (DBP knock-out mouse) models that were generated.
  • pharmacogenomic e.g., methamphetamine/valproate
  • genetic DBP knock-out mouse
  • Comprehensive human brain and blood gene expression datasets published to date can also be used for cross-validation.
  • an extensive public mouse QTL/transgenic database was relied upon for cross-validation of the methods disclosed herein.
  • Prioritization of genes within one or more lists disclosed herein may be refined as new human blood, postmortem brain, and human genetic studies or other evidence become available for some of the genes identified herein.
  • the list of genes organized in the prioritization list/pyramid shown in FIG. 2 may be reorganized such that one or more genes may be ranked higher or lower.
  • One of the models generated herein is consistent with mood being a function of trophicity through energy metabolism and cellular growth (FIG. 3). From an evolutionary standpoint, it may make sense for the organism to react to a favorable environment by activity and expansion, and to an unfavorable environment by inactivity and retraction. In this view, high resources translate into high mood and high libido, as the environment is favorable and can support growth, expansion and progeny. The threshold to pain may be elevated, so activity can occur even in the face of actual injuries. Conversely, low resources translate into a low mood and low libido, as the environment is unfavorable and cannot support more growth, expansion and progeny. The threshold to pain is reduced, so one can react and retract in the face of potential injuries. In clinical illness (bipolar disorder, depression), this congruence between mood and environment may be lost and/or the mood reaction to environmental cues may be disproportionate.
  • GWAS of complex disorders have shown that not necessarily the same SNPs show the strongest signal, but as the analyses show rather there is more consistency at the level of genes, and even more so at the level of gene families and biological pathways.
  • the distance from genotype to phenotype may be a bridge too far for genetic-only approaches, given the intervening complex layers of epigenetics, gene expression regulation and endophenotypes.
  • Using GWAS data in conjunction with gene expression data as part of CFG or integrative genomics approaches, followed by pathway - level analysis of the prioritized candidate genes, may serve as a tool for unraveling the genetic code of complex disorders such as bipolar disorder.
  • Bipolar disorder generally refers to a mood disorder characterized by alternating periods of extreme moods.
  • a person with bipolar disorder experiences cycling of moods that usually swing from being overly elated or irritable (mania) to sad and hopeless (depression) and then back again, with periods of normal mood in between.
  • Diagnosis of bipolar disorder is described in, e.g., Diagnostic and Statistical Manual for Mental Disorders, IV Edition (DSM IV).
  • One who is predisposed for a bipolar disorder generally refers to a person who has an inclination or a higher likelihood of developing a bipolar disorder when compared to an average person in the general population. It is likely that such persons have a family history of mental disorders.
  • Polymorphism generally refers to the presence of two or more alternative sequences or alleles in a population.
  • a polymorphic site refers to the locus at which divergence occurs. Preferred polymorphic sites have at least two alleles, each occurring at a frequency of greater than 1%, and more preferably greater than 10% or 20% or 25% of a selected population.
  • a polymorphic locus can be as small as one base pair (i.e., a single nucleotide polymorphism - SNP).
  • Polymorphic markers include restriction fragment length polymorphisms, variable number of tandem repeats (VNTR's), hypervariable regions, minisatellites, dinucleotide repeats, trinucleotide repeats, tetranucleotide repeats, simple sequence repeats, and insertion elements such as AIu.
  • the first identified allele is arbitrarily designated as the reference allele and other alleles are designated as alternative or "variant alleles.”
  • the allele occurring most frequently in a selected population is sometimes referred to as the "wild-type” allele.
  • Diploid organisms may be homozygous or heterozygous for the variant alleles.
  • the variant allele may or may not produce an observable physical or biochemical characteristic ("phenotype") in an individual carrying the variant allele.
  • phenotype physical or biochemical characteristic
  • a variant allele may alter the enzymatic activity of a protein encoded by a gene of interest.
  • linkage disequilibrium generally refers to a condition where a particular combination of alleles (i.e., a variant form of a given gene) or a combination of polymorphisms at two loci appears more frequently than would be expected by mere chance.
  • significant linkage disequilibrium between an SNP and a particular variant (or variants) indicate that patients possessing such variant (or variants) may be at risk of bipolar disorder.
  • variants in significant LD with an SNP listed in Table 3 are preferred.
  • polymorphisms that are not the actual bipolar-causing (causative) polymorphisms, but are in LD with such causative polymorphisms, are also useful.
  • the genotype of the polymorphism(s) that is/are in LD with the causative polymorphism is predictive of the genotype of the causative polymorphism and, consequently, predictive of the phenotype (e.g., bipolar) that is influenced by the causative SNP(s).
  • polymorphic markers that are in LD with causative polymorphisms are useful as risk predictors, and are particularly useful when the actual causative polymorphism(s) is/are unknown.
  • genotype generally refers to the genetic composition of an organism, including, for example, whether a diploid organism is heterozygous or homozygous for one or more variant alleles of interest.
  • marker and biomarker are synonymous and as used herein, generally refer to the presence or absence or the levels of nucleic acid sequences or proteins or polypeptides or fragments thereof to be used for associating or correlating bipolar disorder.
  • a biomarker includes any indicia of the level of expression of an indicated marker gene. The indicia can be direct or indirect and measure over- or under-expression of the gene in comparison to an internal control, normal tissue or another phenotype. Nucleic acids or proteins or polypeptides or portions thereof used as markers are contemplated to include any fragments thereof, in particular, fragments that can specifically hybridize with their intended targets under stringent conditions and immunologically detectable fragments.
  • proteins/peptides as biomarkers can include any method known in the art including, without limitation, measuring amount, activity, modifications such as glycosylation, phosphorylation, ADP-ribosylation, ubiquitination, etc., imunohistochemistry (1HC).
  • SNP Single nucleotide polymorphism
  • SNPs such as those listed in Table 3 are useful, for instance, for diagnosis of diseases (e.g., bipolar disorder) whose occurrence is linked to the gene sequences of the invention.
  • diseases e.g., bipolar disorder
  • the individual is likely predisposed for bipolar.
  • the individual is particularly predisposed for occurrence of that disease.
  • the SNP associated with the gene sequences identified herein is located within 300,000; 200,000; 100,000; 75,000; 50,000; or 10,000 base pairs from the gene sequence.
  • Various real-time PCR methods can be used to detect the SNPs disclosed herein, including, e.g., Taqman or molecular beacon-based assays (e.g., U.S. Pat. Nos. 5,210,015; 5,487,972). Additional SNP detection methods include, e.g., direct DNA sequencing, sequencing by hybridization, dot blotting, oligonucleotide array (DNA Chip) hybridization analysis, or are described in, e.g., U.S. Pat. No. 6,177,249; Landegren et al., Genome Research, 8:769-776 (1998). PCR methods can also be used to detect deletion/insertion polymorphisms. The Gene ID provided herein for the markers provide adequate sequence description for identifying the listed SNPs.
  • Reagents for detecting SNPs based on the flanking nucleotide sequences are provided. These reagents may include for example, a hybridization probe or an amplification primer that is useful in the specific detection of a SNP of interest.
  • a protein detection reagent is used to detect a variant protein which is encoded by a nucleic acid molecule containing a SNP disclosed herein.
  • a suitable protein detection reagent is an antibody or an antigen-reactive antibody fragment.
  • kits comprising SNP detection reagents, and methods for detecting the SNPs disclosed herein by using the detection reagents.
  • a method for diagnosis includes detecting the presence or absence of a SNP allele disclosed herein is provided.
  • an isolated SNP-containing nucleic acid molecule includes one or more
  • flanking sequence can include nucleotide residues that are naturally associated with the SNP site and/or heterologous nucleotide sequences.
  • the flanking sequence is up to about 2000, 1500, 1000, 500, 300, 100, 60, 50, 30, 25, 20, 15, 10, 8, or 6 nucleotides (or any other length in-between) on either side of a SNP position, or as long as the full-length gene or entire protein-coding sequence (or any portion thereof such as an exon).
  • the flanking sequence may be part of an intron, exon, promoter, untranslated region, coding sequence, non-coding sequence, or any part of the genome.
  • an amplified polynucleotide is at least about 16 or 20 or 30, 40, 45, 50,
  • a SNP may be present anywhere along its sequence.
  • the amplified product is at least about 200 nucleotides in length, that includes one or more SNPs listed in Table 3.
  • the SNP identified in Tables 2-3 is located at the middle of the amplified product (e.g., at position 101 in an amplified product that is 201 nucleotides in length, or at position 51 in an amplified product that is 101 nucleotides in length), or within 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 15, or 20 nucleotides from the middle of the amplified product (however, as indicated above, the SNP of interest may be located anywhere along the length of the amplified product).
  • nucleic acid molecules disclosed in Tables 1-3 such as naturally occurring allelic variants (as well as orthologs and paralogs) and synthetic variants produced by mutagenesis techniques, can be identified and/or produced using methods well known in the art.
  • Such further variants can comprise a nucleotide sequence that shares at least 80-85%, 85-90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, or 99% sequence identity with a nucleic acid sequence disclosed in Table 3 (or a fragment thereof) and that includes a SNP allele disclosed in Table 3.
  • nucleic acid molecules that have a certain degree of sequence variation compared with the sequences shown in Tables 1-3, but that contain a novel SNP allele disclosed herein are included. Such nucleic acid sequences can also be determined by high stringency hybridization.
  • High stringency hybridization conditions or highly stringent hybridization include at least about 6X SSC and 1% SDS at 65°C, with a first wash for 10 minutes at about 42°C with about 20% (v/v) formamide in 0.1X SSC, and with a subsequent wash with 0.2 X SSC and 0.1% SDS at 65°C. These conditions are used for example, identifying highly similar sequences for probe designs and to identify related homologs. Moderately stringent conditions may be obtained by varying the temperature at which the hybridization reaction occurs and/or the wash conditions as set forth above.
  • Nucleic acid sequences useful for deciphering the mode of action of currently used mood stabilizer medications are provided.
  • the sequences (SNPs) provided are also useful for drug discovery, e.g., discovering new leads to identifying more efficacious therapeutic targets in the form of a central molecule/pathway through which an entire system or network of pathways can be modulated to remedy the perturbed cellular process underlying bipolar, or a principal endophenotype of these disorders.
  • Improved knowledge of target- specificity of drugs could help to minimize side effects associated with numerous mood stabilizers currently in use. It could also facilitate development of a subset of biomarker genes useful in early diagnosis of bipolar, and in monitoring drug efficacy.
  • An example of a detection reagent is a probe that hybridizes to a target nucleic acid containing one or more of the SNPs provided in Table 3.
  • a probe can differentiate between nucleic acids having a particular nucleotide (allele) at a target SNP position from other nucleic acids that have a different nucleotide at the same target SNP position.
  • a detection reagent may hybridize to a specific region 5' and/or 3' to a SNP position, particularly a region corresponding to the context sequences provided in Table 3.
  • a detection reagent is a primer which acts as an initiation point of nucleotide extension along a complementary strand of a target polynucleotide.
  • the SNP sequence information provided herein is also useful for designing primers, e.g. allele- specific primers, to amplify (e.g., using PCR) any SNP of the present invention.
  • a SNP detection reagent is an isolated or synthetic DNA or RNA polynucleotide probe or primer or PNA oligomer, or a combination of DNA, RNA and/or PNA, that hybridizes to a segment of a target nucleic acid molecule containing a SNP identified in Table 3.
  • a detection reagent in the form of a polynucleotide may optionally contain modified base analogs, intercalators or minor groove binders.
  • probes may be, for example, affixed to a solid support (e.g., arrays or beads) or supplied in solution (e.g., probe/primer sets for enzymatic reactions such as PCR, RT-PCR, TaqMan assays, or primer-extension reactions) to form a SNP detection kit.
  • a solid support e.g., arrays or beads
  • solution e.g., probe/primer sets for enzymatic reactions such as PCR, RT-PCR, TaqMan assays, or primer-extension reactions
  • a probe or primer typically is a substantially purified oligonucleotide or PNA oligomer.
  • Such oligonucleotide typically comprises a region of complementary nucleotide sequence that hybridizes under stringent conditions to at least about 8, 10, 12, 16, 18, 20, 22, 25, 30, 40, 50, 60, 100 (or any other number in-between) or more consecutive nucleotides in a target nucleic acid molecule.
  • the consecutive nucleotides can either include the target SNP position, or be a specific region in close enough proximity 5' and/or 3' to the SNP position to carry out the desired assay. It will be apparent to one of skill in the art that such primers and probes are directly useful as reagents for genotyping the SNPs of the present invention, and can be incorporated into any kit/system format.
  • the gene/transcript and/or the sequence surrounding the SNP is typically examined using a computer algorithm.
  • Algorithms generally identify oligos of a defined length that are unique to the gene/SNP surrounding sequence, have a GC content within a range suitable for hybridization, lack predicted secondary structure that may interfere with hybridization, and/or possess other desired characteristics or that lack other undesired characteristics.
  • a primer or probe used herein is generally at least about 12-50 nucleotides in length.
  • a primer or a probe is at least about 10 nucleotides in length. In a preferred embodiment, a primer or a probe is at least about 12 nucleotides in length. In a more preferred embodiment, a primer or probe is at least about 16, 17, 18, 19, 20, 21, 22, 23, 24 or 25 nucleotides in length. While the maximal length of a probe can be as long as the target sequence to be detected, depending on the type of assay in which it is employed, it is typically less than about 50, 60, 65, or 70 nucleotides in length. In the case of a primer, it is typically less than about 30 nucleotides in length.
  • a primer or a probe is within the length of about 18 and about 28 nucleotides.
  • the probes can be longer, such as on the order of 30- 70, 75, 80, 90, 100, or more nucleotides in length (see the section below entitled "SNP Detection Kits and Systems").
  • oligonucleotides specific for alternative SNP alleles may be referred to by such terms as allele- specific oligonucleotides, allele- specific probes, or allele- specific primers.
  • allele-specific probes for analyzing polymorphisms well-known.
  • SNP detection kits and systems including but not limited to, packaged probe and primer sets (e.g., TaqMan probe/primer sets), arrays/microarrays of nucleic acid molecules, and beads that contain one or more probes, primers, or other detection reagents for detecting one or more SNPs of the present invention.
  • the kits/systems can optionally include various electronic hardware components; for example, arrays ("DNA chips") and microfluidic systems ("lab-on-a-chip” systems) provided by various manufacturers typically comprise hardware components are provided.
  • kits/systems may not include electronic hardware components, but may be comprised of, for example, one or more SNP detection reagents (along with, optionally, other biochemical reagents) packaged in one or more containers.
  • a SNP detection kit typically contains one or more detection reagents and other components (e.g., a buffer, enzymes such as DNA polymerases or ligases, chain extension nucleotides such as deoxynucleotide triphosphates, and in the case of Sanger-type DNA sequencing reactions, chain terminating nucleotides, positive control sequences, negative control sequences, and the like) necessary to carry out an assay or reaction, such as amplification and/or detection of a SNP-containing nucleic acid molecule.
  • detection reagents e.g., a buffer, enzymes such as DNA polymerases or ligases, chain extension nucleotides such as deoxynucleotide triphosphates, and in the case of Sanger-type DNA sequencing reactions, chain terminating nucleotides, positive control sequences, negative control sequences, and the like
  • kits may further contain means for determining the amount of a target nucleic acid, and means for comparing the amount with a standard, and can comprise instructions for using the kit to detect the SNP-containing nucleic acid molecule of interest.
  • kits are provided which contain the necessary reagents to carry out one or more assays to detect one or more SNPs disclosed herein.
  • SNP detection kits/systems are in the form of nucleic acid arrays, or compartmentalized kits, including microfluidic/lab- on-a-chip systems.
  • arrays are generally used to refer to an array of distinct polynucleotides affixed to a substrate, such as glass, plastic, paper, nylon or other type of membrane, filter, chip, or any other suitable solid support.
  • the polynucleotides can be synthesized directly on the substrate, or synthesized separate from the substrate and then affixed to the substrate.
  • the microarray is prepared and used at least according to the methods described in U.S. Pat. No. 5,837,832, Chee et al., PCT application WO95/11995 (Chee et al.), Lockhart, D. J. et al. (1996; Nat. Biotech.
  • Microfluidic devices which may also be referred to as "lab-on-a-chip” systems, biomedical micro-electro-mechanical systems (bioMEMs), or multicomponent integrated systems, are exemplary kits/systems for analyzing SNPs. Such systems miniaturize and compartmentalize processes such as probe/target hybridization, nucleic acid amplification, and capillary electrophoresis reactions in a single functional device. Such microfluidic devices typically utilize detection reagents in at least one aspect of the system, and such detection reagents may be used to detect one or more SNPs of the present invention.
  • a microfluidic system is disclosed in U.S. Pat. No.
  • microfluidic systems comprise a pattern of microchannels designed onto a glass, silicon, quartz, or plastic wafer included on a microchip.
  • the movements of the samples may be controlled by electric, electroosmotic or hydrostatic forces applied across different areas of the microchip to create functional microscopic valves and pumps with no moving parts. Varying the voltage can be used as a means to control the liquid flow at intersections between the micro-machined channels and to change the liquid flow rate for pumping across different sections of the microchip. See, for example, U.S. Pat. No. 6,153,073, Dubrow et al, and U.S. Pat. No. 6,156,181, Parce et al.
  • a method of providing a genetic risk prediction analysis includes receiving a sample, performing a SNP analysis and/or biomarker gene expression analysis for the sample, and providing results to a clinician or a hospital or any health care provider.
  • the clinician or the health care provider uses the results from the SNP or biomarker analysis to for example, assign a risk factor, choose a personalized treatment plan, develop a monitoring method for the patient, or provide counseling with respects to risks associated with developing a bipolar mood disorder or a combination thereof.
  • diagnose, diagnosis, and diagnostics include, but are not limited to any of the following: predisposing bipolar condition or disorder, likelihood of suffering from the bipolar disorder, that an individual may presently have or be at risk for, predisposition screening (i.e., determining the increased risk for an individual in developing bipolar disorder in the future, or determining whether an individual has a decreased risk of developing bipolar disorder in the future), determining a particular type or severity of bipolar disorder in an individual, confirming or reinforcing a previously made diagnosis of bipolar condition, pharmacogenomic evaluation of an individual to determine which therapeutic strategy that individual is most likely to positively respond to or to predict whether a patient is likely to respond to a particular treatment, and evaluating the future prognosis of an individual having bipolar disorder.
  • Such diagnostic uses are based on the SNPs individually or in a unique combination or SNP haplotypes disclosed herein.
  • Haplotypes are particularly useful in that, for example, fewer SNPs can be genotyped to determine if a particular genomic region harbors a locus that influences a particular phenotype, such as in linkage disequilibrium-based SNP association analysis.
  • Genome- Wide Association data for bipolar disorder The GWA data for the bipolar study from the Wellcome Trust Consortium (WTCC) is available at http://www.wtccc.org.uk/info/access_to_data_samples.shtmll. The GWA data from NIMH and German studies is available at http://mapgenetics.nimh. nih.gov/bp_pooling2. The genotypic test p-value (standard analysis) was used. Two nominal p-value thresholds for SNP selection- a lower stringency threshold (p ⁇ 0.05), and a higher stringency threshold (p ⁇ 0.001) were used.
  • the GWA data from the STEP-BD study is available at http://pngu.mgh.harvard.edu/ ⁇ purcell/bpwgas3.
  • the GWA data for GAIN-BP is available from NIMH4. No Bonferroni correction for number of SNPs tested was performed.
  • Animal model brain and blood gene expression data For animal model brain and blood gene expression evidence, data from two different animal models for bipolar disorder developed, one pharmacogenomic and one transgenic were used (developed previously).
  • CFG Convergent Functional Genomics
  • Data from GWAS were weighted more heavily, bringing the data from this one methodological approach on par with the data from all the other methodological approaches combined. That other ways of weighing the scores of line of evidence may give slightly different results in terms of prioritization, if not in terms of the list of genes per se.
  • Simple scoring system provides a good separation of genes based on the focus on identifying signal in the GWAS.
  • GRP Genetic Risk Prediction
  • GRPS Genetic Risk prediction Score
  • Each SNP has two alleles, Al and A2 (represented by base letters at that position). One of them is associated with the illness, and a score of 1 is assigned, the other is not, and is assigned a score of 0. Then, in each individual subject, the paternal and maternal chromosomes were analyzed, and to which alleles they have. Thus, for a SNP in a particular individual subject, one can have any permutation of 1 and 0 (1 and 1, 0 and 1, 1 and 0, 0 and 0). By adding these numbers, the minimum score for a SNP in an individual subject is 0, and the maximum score is 2.
  • a matrix can be generated, with rows corresponding to individual subjects and columns corresponding to individual SNPs.
  • Each SNP is listed twice, corresponding to a paternal chromosome and a maternal chromosome copy.
  • GRPS Genetic Risk Predictive Score
  • GRPS genetic score
  • a primer also called an extension primer
  • reagent e.g. ddTTP
  • a first allele base e.g. ' A ' allele
  • the target fragment DNA includesthe first allele (e.g. ' A ' allele)
  • a product containing only one base complementary to the first allele (e.g. ' T ' ) added is obtained.
  • the target DNA fragment included a second allele (e.g. ' G ' allele)
  • the length of the product extending from the primer was determined using mass analysis to determine the type of allele in the target DNA.

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Abstract

La présente invention concerne des polymorphismes de nucléotide unique (SNP) multiples dans différents gènes classés par priorité associés à un trouble bipolaire sur la base de l’analyse intégrée d’études d’association au génome total (Genome-Wide Association studies : GWAS) avec des études d’expression génique (génomique fonctionnelle) (modèles humains et animaux). La présente invention concerne en outre des procédés d’évaluation des risques, de diagnostic, de prédiction ou d’identification d’une prédisposition chez des individus à un trouble bipolaire.
PCT/US2009/058003 2008-09-23 2009-09-23 Gènes et polymorphismes de nucléotide unique pour un essai génétique de trouble bipolaire WO2010039526A1 (fr)

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CN109935321A (zh) * 2019-04-11 2019-06-25 东南大学 基于功能核磁共振影像数据的抑郁症患者转为双相情感障碍的风险预测模型
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CN114514329A (zh) * 2019-05-30 2022-05-17 纽卡斯尔大学 治疗或预防方法
CN111430027B (zh) * 2020-03-18 2023-04-28 浙江大学 基于肠道微生物的双相情感障碍生物标志物及其筛选应用

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Cited By (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2013044354A1 (fr) * 2011-09-26 2013-04-04 Trakadis John Procédé et système pour la recherche de caractères génétiques sur la base du phénotype et du génome d'un sujet humain
WO2013139676A1 (fr) * 2012-03-19 2013-09-26 Brainco Biopharma, S.L. Modèle d'animal transgénique pour les troubles de l'humeur
US9398761B2 (en) 2012-03-19 2016-07-26 Brainco Biopharma, S.L. Transgenic animal model of mood disorders
EP3019865A4 (fr) * 2013-07-12 2017-04-05 Immuneering Corporation Systèmes, procédés, et environnement pour l'examen automatisé de données génomiques pour identifier une expression génétique régulée à la baisse et/ou régulée à la hausse indicative d'une maladie ou d'un état
CN109935321A (zh) * 2019-04-11 2019-06-25 东南大学 基于功能核磁共振影像数据的抑郁症患者转为双相情感障碍的风险预测模型
CN109935321B (zh) * 2019-04-11 2023-07-07 东南大学 基于功能核磁共振影像数据的抑郁症患者转为双相情感障碍的风险预测系统
CN114514329A (zh) * 2019-05-30 2022-05-17 纽卡斯尔大学 治疗或预防方法
CN111430027B (zh) * 2020-03-18 2023-04-28 浙江大学 基于肠道微生物的双相情感障碍生物标志物及其筛选应用
CN112048553A (zh) * 2020-09-28 2020-12-08 宜昌市优抚医院 血浆外周血分子标志物hsa-miR-574-5p的应用

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