WO2015082927A1 - Panel de nouveaux biomarqueurs pour dépressions majeures - Google Patents

Panel de nouveaux biomarqueurs pour dépressions majeures Download PDF

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Publication number
WO2015082927A1
WO2015082927A1 PCT/GB2014/053603 GB2014053603W WO2015082927A1 WO 2015082927 A1 WO2015082927 A1 WO 2015082927A1 GB 2014053603 W GB2014053603 W GB 2014053603W WO 2015082927 A1 WO2015082927 A1 WO 2015082927A1
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mdd
interleukin
alpha
protein
therapy
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PCT/GB2014/053603
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English (en)
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Sabine Bahn
Man Kuan CHAN
Jason Cooper
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Cambridge Enterprise Limited
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    • 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
    • G01N2800/00—Detection or diagnosis of diseases
    • G01N2800/30—Psychoses; Psychiatry
    • G01N2800/304—Mood disorders, e.g. bipolar, depression
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2800/00—Detection or diagnosis of diseases
    • G01N2800/52—Predicting or monitoring the response to treatment, e.g. for selection of therapy based on assay results in personalised medicine; Prognosis
    • 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

  • the invention relates to biomarkers and methods of diagnosing or monitoring major depressive disorder, or a predisposition thereto.
  • Major depressive disorder is a prevalent disabling and costly psychiatric disorder, with a lifetime prevalence of up to 20%.
  • recognition and diagnosis of patients with depression is sub-optimal. Approximately two thirds of patients present with somatic symptoms such as lack of energy and general aches and pains. Therefore, depression is often not recognized initially. In most cases, the depressive symptoms are overlooked and are seen as being part of a non-psychiatric condition. In other cases, the physical symptoms are dealt with as having higher priority over assessing depressive symptoms.
  • the limited time general practitioners have for assessment of each patient is also a limiting factor for recognition and diagnosis of depression in patients who present with chiefly somatic complaints or patients who have difficulties in verbalizing their psychiatric complaints. These patients are substantially harder to treat as most are only recognized at subsequent consultations, often several years after their initial visit. This lag in diagnosis, leads to delays in appropriate pharmacological intervention and increases the subsequent risk of developing chronic, recurrent or even treatment resistance depression in the longer term.
  • IL-lra Interleukin-1 receptor antagonist
  • FRTN Ferritin
  • EN-RAGE EN-RAGE
  • TPC Tenascin-C
  • Interleukin-1 receptor antagonist IL-lra
  • Ferritin FRTN
  • EN-RAGE Tenascin-C
  • MIF Macrophage Migration Inhibitory Factor
  • ACE Angiotensin Converting Enzyme
  • EGF Epidermal Growth Factor
  • GH Growth Hormone
  • IL-13 Interleukin-13
  • vWF von Willebrand Factor
  • MIP-1 alpha Macrophage Inflammatory Protein-1 alpha
  • Interleukin-16 IL-16
  • SOD-1 Superoxide Dismutase 1 soluble
  • SOD-1 Apolipoprotein A-I
  • MIP-1 beta Macrophage Inflammatory Protein-1 beta
  • MPO Myeloperoxidase
  • a method of monitoring efficacy of a therapy in a subject having, suspected of having, or of being predisposed to major depressive disorder comprising detecting and/or quantifying, in a sample from said subject, the analyte biomarkers as defined herein.
  • a further aspect of the invention provides ligands, such as naturally occurring or chemically synthesised compounds, capable of specific binding to the peptide biomarker.
  • a ligand according to the invention may comprise a peptide, an antibody or a fragment thereof, or an aptamer or oligonucleotide, capable of specific binding to the peptide biomarker.
  • the antibody can be a monoclonal antibody or a fragment thereof capable of specific binding to the peptide biomarker.
  • a ligand according to the invention may be labelled with a detectable marker, such as a luminescent, fluorescent or radioactive marker; alternatively or additionally a ligand according to the invention may be labelled with an affinity tag, e.g. a biotin, avidin, streptavidin or His ⁇ e.g. hexa-His) tag.
  • a biosensor according to the invention may comprise the peptide biomarker or a structural/shape mimic thereof capable of specific binding to an antibody against the peptide biomarker. Also provided is an array comprising a ligand or mimic as described herein. Also provided by the invention is the use of one or more ligands as described herein, which may be naturally occurring or chemically synthesised, and is suitably a peptide, antibody or fragment thereof, aptamer or oligonucleotide, or the use of a biosensor of the invention, or an array of the invention, or a kit of the invention to detect and/or quantify the peptide.
  • the detection and/or quantification can be performed on a biological sample such as from the group consisting of whole blood, blood serum, plasma, CSF, urine, saliva, or other bodily fluid, breath, e.g. as condensed breath, or an extract or purification therefrom, or dilution thereof.
  • a biological sample such as from the group consisting of whole blood, blood serum, plasma, CSF, urine, saliva, or other bodily fluid, breath, e.g. as condensed breath, or an extract or purification therefrom, or dilution thereof.
  • kits for performing methods of the invention.
  • Such kits will suitably comprise a ligand according to the invention, for detection and/or quantification of the peptide biomarker, and/or a biosensor, and/or an array as described herein, optionally together with instructions for use of the kit.
  • kits comprising a biosensor capable of detecting and/or quantifying the analyte biomarkers as defined herein for monitoring or diagnosing major depressive disorder.
  • Biomarkers for major depressive disorder or other psychotic disorder are essential targets for discovery of novel targets and drug molecules that retard or halt progression of the disorder.
  • the biomarker is useful for identification of novel therapeutic compounds in in vitro and/or in vivo assays.
  • Biomarkers of the invention can be employed in methods for screening for compounds that modulate the activity of the peptide.
  • a ligand as described, which can be a peptide, antibody or fragment thereof or aptamer or oligonucleotide according to the invention; or the use of a biosensor according to the invention, or an array according to the invention; or a kit according to the invention, to identify a substance capable of promoting and/or of suppressing the generation of the biomarker.
  • a method of identifying a substance capable of promoting or suppressing the generation of the peptide in a subject comprising administering a test substance to a subject animal and detecting and/or quantifying the level of the peptide biomarker present in a test sample from the subject.
  • a doctor or other medical practitioner is apprised that a patient is suffering from major depressive disorder, the practitioner will treat the individual to alleviate the causes or symptoms of the disorder.
  • a method for treating major depressive disorder may comprise treating a patient with anxiolytic or antidepressant drugs and/or non-drug therapies.
  • Treatment may be based upon a diagnosis or suspicion of major depressive disorder derived from the methods, analyte biomarkers and specific panels of analyte biomarkers as described herein.
  • the results of any analyses according to the invention will often be communicated to physicians and/or patients (or other interested parties such as researchers) in a transmittable form that can be communicated or transmitted to any of the above parties. Therefore, according to a further aspect of the invention, there is provided systems for diagnosing and treating major depressive disorder. These systems may comprise sample analyzers, computers and software as described herein.
  • FIGURE 1 ROC curves illustrating test performance achieved in discriminating MDD patients from healthy controls using the top 4 analytes (IL-lra, FRTN, EN-RAGE and TNC) identified in MDD cohorts 1-4 and DN MDD cohorts 1-2.
  • IL-lra IL-lra
  • FRTN FRTN
  • EN-RAGE and TNC analytes identified in MDD cohorts 1-4 and DN MDD cohorts 1-2.
  • FIGURE 3 ROC curves illustrating test performance achieved in discriminating MDD patients from healthy controls using the top most reproducible serum analytes identified in MDD cohorts 1-4 and Drug Na ' ive (DN) MDD cohorts 1-2.
  • the top 6 analytes: IL-lra, FRTN, EN-RAGE, TNC, MIF and ACE;
  • the top 7 analytes: IL-lra, FRTN, EN-RAGE, TNC, MIF, ACE and EGF.
  • FIGURE 4 ROC curves illustrating assay performance achieved in discriminating MDD patients from healthy controls using the top most reproducible serum analytes identified in the medicated or un- medicated NESDA MDD cohorts.
  • the top 4 analytes for these particular cohorts: IL-lra, FRTN, MIF, EN-RAGE;
  • the top 7 analytes for these particular cohorts: IL-lra, FRTN, MIF, EN-RAGE, ACE, TNC and EGF.
  • the top 19 analytes for these particular cohorts IL-lra, FRTN, MIF, EN-RAGE, ACE, TNC, EGF, Testosterone, GH, vWF, IL-16, TBG, RANTES, SOD-1, Apo A-I, MIP-1 beta, MPO, IGFBP-2, and Haptoglobin.
  • the test performance achieved using the top 7 or 19 analytes was on average fair.
  • the data described herein shows the development of a reproducible blood-based biomarker test, resulting from analysis of eight independent MDD cohorts of recurrent previously-medicated patients as well as drug naive first onset MDD patients.
  • the latter group of patients is particularly important for the identification of MDD diagnostic biomarkers to aid early diagnosis of depression within primary care facilities since the majority of patients with somatic or ambiguous symptoms remain undiagnosed for months or years.
  • the invention described herein identifies a panel of biomarkers for diagnosing major depressive disorder (MDD), in particular recurrent and/or drug naive first onset major depressive disorder (MDD) patients.
  • MDD major depressive disorder
  • MDD drug naive first onset major depressive disorder
  • biomarker means a distinctive biological or biologically derived indicator of a process, event, or condition.
  • Peptide biomarkers can be used in methods of diagnosis, e.g. clinical screening, and prognosis assessment and in monitoring the results of therapy, identifying patients most likely to respond to a particular therapeutic treatment, drug screening and development. Biomarkers and uses thereof are valuable for identification of new drug treatments and for discovery of new targets for drug treatment.
  • IL-lra Interleukin-1 receptor antagonist
  • FRTN Ferritin
  • EN-RAGE EN-RAGE
  • Tenascin-C TMC
  • Tables 21-22 and Figures 1 and 2 this combination of 4 analytes can be used to discriminate between MDD patients and healthy controls.
  • this combination was shown to provide a good to excellent performance in discriminating MDD patients from controls in MDD cohorts 1, 3 and 4, and DN MDD cohorts 1 and 2.
  • the panel additionally comprises one or more analyte biomarkers selected from : Angiotensin Converting Enzyme (ACE), Macrophage Migration Inhibitory Factor (MIF) and Epidermal Growth Factor (EGF).
  • ACE Angiotensin Converting Enzyme
  • MIF Macrophage Migration Inhibitory Factor
  • EGF Epidermal Growth Factor
  • Interleukin-1 receptor antagonist IL-lra
  • Ferritin FRTN
  • Macrophage Migration Inhibitory Factor MIF
  • EN-RAGE Angiotensin Converting Enzyme
  • ACE Angiotensin Converting Enzyme
  • TMC Tenascin-C
  • EGF Epidermal Growth Factor
  • IL-lra IL-lra
  • FRTN FRTN
  • MIF FRTN
  • EN-RAGE a specific panel of analyte biomarkers for the diagnosis of MDD, or predisposition thereto.
  • this combination (referred to as "combl” in the Results section herein) provides a good to excellent performance in discriminating MDD patients from controls in MDD cohorts 1, 3 and 4 and DN MDD cohorts 1 and 2.
  • IL-lra FRTN, MIF, EN-RAGE and TNC as a specific panel of analyte biomarkers for the diagnosis of MDD, or predisposition thereto.
  • this combination (referred to as "comb2" in the Results section herein) provides a good to excellent performance in discriminating MDD patients from controls in MDD cohorts 1, 3 and 4 and DN MDD cohorts 1 and 2.
  • this combination was found to be one of the best performing combinations, as shown in Table 22.
  • IL-lra, FRTN, MIF, ACE and TNC as a specific panel of analyte biomarkers for the diagnosis of MDD, or predisposition thereto.
  • this combination (referred to as "comb3" in the Results section herein) provides a good to excellent performance in discriminating MDD patients from controls in MDD cohorts 1, 3 and 4 and DN MDD cohorts 1 and 2.
  • IL-lra, FRTN, EN-RAGE, ACE and TNC as a specific panel of analyte biomarkers for the diagnosis of MDD, or predisposition thereto.
  • this combination (referred to as "comb4" in the Results section herein) provides a good to excellent performance in discriminating MDD patients from controls in MDD cohorts 1, 3 and 4 and DN MDD cohorts 1 and 2.
  • this combination was found to be one of the best performing combinations, as shown in Table 22.
  • IL-lra, MIF, ENRAGE, ACE and TNC as a specific panel of analyte biomarkers for the diagnosis of MDD, or predisposition thereto.
  • this combination (referred to as "comb5" in the Results section herein) provides a good to excellent performance in discriminating MDD patients from controls in MDD cohorts 1 and 4 and DN MDD cohorts 1 and 2.
  • FRTN, MIF, ENRAGE, ACE and TNC as a specific panel of analyte biomarkers for the diagnosis of MDD, or predisposition thereto.
  • this combination (referred to as "comb6" in the Results section herein) provides a good to excellent performance in discriminating MDD patients from controls in MDD cohorts 1, 3 and 4 and DN MDD cohorts 1 and 2.
  • IL-lra IL-lra, FRTN, MIF, EN-RAGE and EGF as a specific panel of analyte biomarkers for the diagnosis of MDD, or predisposition thereto.
  • this combination (referred to as "comb7" in the Results section herein) provides a good to excellent performance in discriminating MDD patients from controls in MDD cohorts 1, 3 and 4 and DN MDD cohorts 1 and 2.
  • IL-lra, FRTN, EN-RAGE, ACE and EGF as a specific panel of analyte biomarkers for the diagnosis of MDD, or predisposition thereto.
  • this combination (referred to as “comb9" in the Results section herein) provides a good to excellent performance in discriminating MDD patients from controls in MDD cohorts 1, 3 and 4 and DN MDD cohorts 1 and 2.
  • IL-lra, MIF, ENRAGE, ACE and EGF as a specific panel of analyte biomarkers for the diagnosis of MDD, or predisposition thereto.
  • this combination (referred to as “comblO” in the Results section herein) provides a good to excellent performance in discriminating MDD patients from controls in MDD cohorts 1 and 4 and DN MDD cohorts 1 and 2.
  • FRTN FRTN, MIF, EN- RAGE, ACE and EGF
  • combl l a specific panel of analyte biomarkers for the diagnosis of MDD, or predisposition thereto.
  • this combination (referred to as "combl l" in the Results section herein) provides a good to excellent performance in discriminating MDD patients from controls in MDD cohorts 1, 3 and 4 and DN MDD cohorts 1 and 2.
  • IL-lra IL-lra, FRTN, MIF, TNC and EGF
  • combl2 this combination provides a good to excellent performance in discriminating MDD patients from controls in MDD cohorts 1, 3 and 4 and DN MDD cohorts 1 and 2.
  • this combination was found to be one of the best performing combinations, as shown in Table 22.
  • IL-lra IL-lra
  • FRTN FRTN
  • EN-RAGE FRTN
  • TNC vascular endothelial growth factor
  • EGF vascular endothelial growth factor
  • IL-lra, MIF, ENRAGE, TNC and EGF as a specific panel of analyte biomarkers for the diagnosis of MDD, or predisposition thereto.
  • this combination (referred to as "combl4" in the Results section herein) provides a good to excellent performance in discriminating MDD patients from controls in MDD cohorts 1 and 4 and DN MDD cohorts 1 and 2.
  • FRTN, MIF, ENRAGE, TNC and EGF as a specific panel of analyte biomarkers for the diagnosis of MDD, or predisposition thereto.
  • this combination (referred to as "combl5" in the Results section herein) provides a good to excellent performance in discriminating MDD patients from controls in MDD cohorts 1, 3 and 4 and DN MDD cohorts 1 and 2.
  • IL-lra IL-lra
  • FRTN FRTN
  • ACE ACE
  • TNC EGF
  • EGF EGF
  • IL-lra IL-lra, MIF, ACE, TNC and EGF
  • combl7 a good to excellent performance in discriminating MDD patients from controls in MDD cohorts 1 and 4 and DN MDD cohorts 1 and 2.
  • FRTN, MIF, ACE, TNC and EGF as a specific panel of analyte biomarkers for the diagnosis of MDD, or predisposition thereto.
  • this combination (referred to as “combl8" in the Results section herein) provides a good to excellent performance in discriminating MDD patients from controls in MDD cohorts 1, 3 and 4 and DN MDD cohorts 1 and 2.
  • IL-lra, ENRAGE, ACE, TNC and EGF as a specific panel of analyte biomarkers for the diagnosis of MDD, or predisposition thereto.
  • this combination (referred to as “combl9” in the Results section herein) provides a good to excellent performance in discriminating MDD patients from controls in MDD cohorts 1 and 4 and DN MDD cohorts 1 and 2.
  • FRTN, EN-RAGE, ACE, TNC and EGF as a specific panel of analyte biomarkers for the diagnosis of MDD, or predisposition thereto.
  • this combination (referred to as "comb20" in the Results section herein) provides a good to excellent performance in discriminating MDD patients from controls in MDD cohorts 1, 3 and 4 and DN MDD cohorts 1 and 2.
  • IL-lra IL-lra, FRTN, MIF and EN-RAGE as a specific panel of analyte biomarkers for the diagnosis of MDD, or predisposition thereto.
  • this combination can be used to discriminate MDD patients from healthy controls in the tested cohorts.
  • IL-lra FRTN, MIF, EN-RAGE, ACE, TNC, Testosterone, EGF, GH, IL-13, vWF, MIP-1 alpha, IL- 16, TBG, RANTES, SOD-1, Apo A-I, MIP-1 beta, MPO, CA-19-9, IGFBP-2, IL-7, BLC and Haptoglobin as a specific panel of analyte biomarkers for the diagnosis of MDD, or predisposition thereto.
  • this combination is successful at discriminating MDD patients from healthy controls in MDD cohorts 1-4 and DN MDD cohorts 1-2.
  • these twenty four most reproducible markers resulted in an average assay sensitivity and specificity of 91% and 82%, respectively, with a ROC-AUC of 0.93.
  • IL-lra FRTN, MIF, EN-RAGE, ACE, TNC, EGF, Testosterone, GH, vWF, IL-16, TBG, RANTES, SOD-1, Apo A-I, MIP-1 beta, MPO, IGFBP-2, and Haptoglobin as a specific panel of analyte biomarkers for the diagnosis of MDD, or predisposition thereto.
  • this combination is successful at discriminating MDD patients from healthy controls in the medicated or un-medicated NESDA MDD cohorts.
  • the panel additionally comprises one or more analyte biomarkers selected from : Testosterone Total, Growth Hormone (GH), Interleukin-13 (IL-13), von Willebrand Factor (vWF), Macrophage Inflammatory Protein-1 alpha (MIP-1 alpha), Interleukin-16 (IL-16), Thyroxine-Binding Globulin (TBG), T-Cell-Specific Protein RANTES (RANTES), Superoxide Dismutase 1 soluble (SOD-1), Apolipoprotein A-I (Apo A-I), Macrophage Inflammatory Protein-1 beta (MIP-1 beta), Myeloperoxidase (MPO), Cancer Antigen 19-9 (CA- 19-9), Insulin-like Growth Factor-Binding Protein 2 (IGFBP-2), Interleukin-7 (IL- 7), B Lymphocyte Chemoattractant (BLC), Haptoglobin, Chemokine CC-4 (HCC- 4), Cortisol, Hepat
  • Interleukin-1 receptor antagonist IL-lra
  • Ferritin FRTN
  • Macrophage Migration Inhibitory Factor MIF
  • EN-RAGE Angiotensin Converting Enzyme
  • ACE Angiotensin Converting Enzyme
  • TGF Epidermal Growth Factor
  • GH Growth Hormone
  • IL-13 Interleukin-13
  • vWF von Willebrand Factor
  • MIP-1 alpha Macrophage Inflammatory Protein-1 alpha
  • IL-16 Interleukin-16
  • TBG Thyroxine-Binding Globulin
  • T-Cell-Specific Protein RANTES RANTES
  • SOD-1 Superoxide Dismutase 1 soluble
  • SOD-1 Apolipoprotein A-I
  • MIP-1 beta Macrophage Inflammatory Protein-1 beta
  • MPO Myeloperoxidase
  • Cancer Antigen 19-9 CA-19-9
  • Insulin-lra Interleukin-1 receptor antagonist
  • FRTN
  • the use additionally comprises one or more analyte biomarkers selected from : Apolipoprotein C-III (Apo C-III), FASLG Receptor (FAS), Prolactin (PRL), Leptin, Immunoglobulin A (IgA), Macrophage-Derived Chemokine (MDC), Resistin, Interleukin-3 (IL-3), Interleukin-15 (IL-15), Progesterone, Interleukin-5 (IL-5), Interleukin-8 (IL-8), Follicle-Stimulating Hormone (FSH), Creatine Kinase-MB (CK-MB), Vascular Endothelial Growth Factor (VEGF), Interferon gamma (IFN-gamma), Tumor necrosis factor receptor 2 (TNFR2), Thyroid-Stimulating Hormone (TSH), Serotransferrin (Transferrin), Tamm-Horsfall Urinary Glycoprotein (THP), Myoglobin, CD
  • major depressive disorder also include patients with “depression” and "dysthymia”.
  • major depressive disorder which is also known as clinical depression, major depression, unipolar depression, or unipolar disorder
  • DSM-IV Diagnostic and Statistical Manual of Mental Disorders
  • Major depressive disorder is a disabling condition which adversely affects a person's family, work or school life, sleeping and eating habits, and general health. In the United States, approximately 3.4% of people with major depression commit suicide, and up to 60% of all people who commit suicide have depression or another mood disorder.
  • ECT electroconvulsive therapy
  • the course of the disorder varies widely, from one episode lasting months to a lifelong disorder with recurrent major depressive episodes.
  • Depressed individuals have shorter life expectancies than those without depression, in part because of greater susceptibility to medical illnesses.
  • Current and former patients may be stigmatized.
  • Major depressive disorder is based on the patient's self- reported experiences, behaviour reported by relatives or friends, and a mental status exam . There is no laboratory test for major depression, although physicians generally request tests for physical conditions that may cause similar symptoms. The most common time of onset is between the ages of 30 and 40 years, with a later peak between 50 and 60 years. Major depression is reported about twice as frequently in women as in men, although men are at higher risk for suicide.
  • the patient is diagnosed with major depressive disorder (MDD).
  • MDD major depressive disorder
  • the patient is a recurrent major depressive disorder patient.
  • the patient is a drug naive major depressive disorder patient ⁇ e.g. a first onset drug patient).
  • the patient is a chronic major depressive disorder patient.
  • the patient is an un- medicated major depressive disorder patient.
  • drug naive patients includes patients which have not previously been diagnosed or medicated for major depressive disorder.
  • un-medicated refers to patients which have not been taking medication for major depressive disorder for at least 1 year, for example for at least 2, 3, 4, 5, 6, 7, 8, 9 or 10 years, in particular for at least 3 years.
  • the patient is a severe, moderate or mild major depressive disorder patient. In a further embodiment, the patient is a severe or moderate major depressive patient, in particular a severe major disorder patient.
  • references herein to "other psychotic disorder” relate to any appropriate psychotic disorder according to DSM-IV Diagnostic and Statistical Manual of Mental Disorders, 4th edition, American Psychiatric Assoc., Washington, D.C., 2000.
  • the other psychotic disorder is a psychotic disorder related to major depressive disorder.
  • a method of diagnosing major depressive disorder or predisposition in an individual thereto comprising:
  • references to biomarker amounts or levels also include references to a biomarker range. It will be appreciated that references herein to "difference in the level" refer to either a higher or lower level of the biomarker(s) in the test biological sample compared with the reference sample(s).
  • the higher or lower level is a ⁇ 1 fold difference relative to the reference sample, such as a fold difference of 0.9, 0.8, 0.7, 0.6, 0.5, 0.4, 0.3, 0.2, 0.1, 0.05, 0.01 or any ranges therebetween.
  • the lower level is between a 0.1 and 0.85 fold difference relative to the reference sample, such as between a 0.2 and 0.7 fold difference relative to the reference sample.
  • the lower level is between a 0.25 and 0.75 fold difference relative to the reference sample.
  • the higher or lower level is a > 1 fold difference relative to the reference sample, such as a fold difference of 1.5, 2.0, 2.5, 3.0, 3.5, 4.0, 4.5, 5.0, 5.5, 6.0, 6.5, 7.0, 7.5, 8.0, 8.5, 9.0, 9.5, 10, 10.5, 11, 11.5, 12, 12.5, 15 or 20 or any ranges therebetween.
  • the higher level is between a 1 and 15 fold difference relative to the reference sample, such as between a 1.5 and 12 fold difference relative to the reference sample.
  • the higher level is between a 1 and 7 fold difference relative to the reference sample.
  • a method of monitoring efficacy of a therapy in a subject having, suspected of having, or of being predisposed to major depressive disorder comprising detecting and/or quantifying, in a sample from said subject, the analyte biomarkers as defined herein.
  • Monitoring methods of the invention can be used to monitor onset, progression, stabilisation, amelioration and/or remission.
  • detecting and/or quantifying the peptide biomarker in a biological sample from a test subject may be performed on two or more occasions. Comparisons may be made between the level of biomarker in samples taken on two or more occasions. Assessment of any change in the level of the peptide biomarker in samples taken on two or more occasions may be performed. Modulation of the peptide biomarker level is useful as an indicator of the state of major depressive disorder or other psychotic disorder or predisposition thereto. An increase in the level of the biomarker, over time is indicative of onset or progression, i.e. worsening of this disorder, whereas a decrease in the level of the peptide biomarker indicates amelioration or remission of the disorder, or vice versa.
  • a method of diagnosis of or monitoring according to the invention may comprise quantifying the peptide biomarker in a test biological sample from a test subject and comparing the level of the peptide present in said test sample with one or more controls.
  • the control used in a method of the invention can be one or more control(s) selected from the group consisting of: the level of biomarker peptide found in a normal control sample from a normal subject, a normal biomarker peptide level; a normal biomarker peptide range, the level in a sample from a subject with major depressive disorder or other psychotic disorder, or a diagnosed predisposition thereto; major depressive disorder or other psychotic disorder biomarker peptide level, or major depressive disorder or other psychotic disorder biomarker peptide range.
  • test samples may be taken on two or more occasions.
  • the method may further comprise comparing the level of the biomarker present in the test sample with one or more reference(s) and/or with one or more previous test sample(s) taken earlier from the same test subject, e.g. prior to commencement of therapy, and/or from the same test subject at an earlier stage of therapy.
  • the method may comprise detecting a change in the level of the biomarker in test samples taken on different occasions.
  • the method comprises comparing the amount of biomarker(s) in said test biological sample with the amount present in one or more samples taken from said patient prior to commencement of treatment, and/or one or more samples taken from said patient during treatment.
  • a higher level of the peptide biomarker in the test sample relative to the level in the normal control is indicative of the presence of major depressive disorder or other psychotic disorder, or predisposition thereto; an equivalent or lower level of the peptide in the test sample relative to the normal control is indicative of absence of major depressive disorder and/or absence of a predisposition thereto.
  • a lower level of the peptide biomarker in the test sample relative to the level in the normal control is indicative of the presence of major depressive disorder or other psychotic disorder, or predisposition thereto; an equivalent or lower level of the peptide in the test sample relative to the normal control is indicative of absence of major depressive disorder and/or absence of a predisposition thereto.
  • diagnosis encompasses identification, confirmation, and/or characterisation of major depressive disorder or other psychotic disorder, or predisposition thereto.
  • predisposition it is meant that a subject does not currently present with the disorder, but is liable to be affected by the disorder in time.
  • Methods of monitoring and of diagnosis according to the invention are useful to confirm the existence of a disorder, or predisposition thereto; to monitor development of the disorder by assessing onset and progression, or to assess amelioration or regression of the disorder.
  • Methods of monitoring and of diagnosis are also useful in methods for assessment of clinical screening, prognosis, choice of therapy, evaluation of therapeutic benefit, i.e. for drug screening and drug development.
  • Efficient diagnosis and monitoring methods provide very powerful "patient solutions” with the potential for improved prognosis, by establishing the correct diagnosis, allowing rapid identification of the most appropriate treatment (thus lessening unnecessary exposure to harmful drug side effects), reducing "downtime” and relapse rates.
  • Methods for monitoring efficacy of a therapy can be used to monitor the therapeutic effectiveness of existing therapies and new therapies in human subjects and in non-human animals ⁇ e.g. in animal models). These monitoring methods can be incorporated into screens for new drug substances and combinations of substances.
  • the time elapsed between taking samples from a subject undergoing diagnosis or monitoring will be 3 days, 5 days, a week, two weeks, a month, 2 months, 3 months, 6 or 12 months.
  • Samples may be taken prior to and/or during and/or following therapy for major depressive disorder, such as an antidepressant therapy. Samples can be taken at intervals over the remaining life, or a part thereof, of a subject.
  • detecting means confirming the presence of the peptide biomarker present in the sample.
  • Quantifying the amount of the biomarker present in a sample may include determining the concentration of the peptide biomarker present in the sample. Detecting and/or quantifying may be performed directly on the sample, or indirectly on an extract therefrom, or on a dilution thereof.
  • the presence of the peptide biomarker is assessed by detecting and/or quantifying antibody or fragments thereof capable of specific binding to the biomarker that are generated by the subject's body in response to the peptide and thus are present in a biological sample from a subject having major depressive disorder or a predisposition thereto.
  • Detecting and/or quantifying can be performed by any method suitable to identify the presence and/or amount of a specific protein in a biological sample from a patient or a purification or extract of a biological sample or a dilution thereof.
  • quantifying may be performed by measuring the concentration of the peptide biomarker in the sample or samples.
  • Biological samples that may be tested in a method of the invention include whole blood, blood serum, plasma, cerebrospinal fluid (CSF), urine, saliva, or other bodily fluid (stool, tear fluid, synovial fluid, sputum), breath, e.g. as condensed breath, or an extract or purification therefrom, or dilution thereof.
  • Biological samples also include tissue homogenates, tissue sections and biopsy specimens from a live subject, or taken post-mortem. The samples can be prepared, for example where appropriate diluted or concentrated, and stored in the usual manner.
  • the biological sample is whole blood, blood serum or plasma, such as blood serum .
  • Detection and/or quantification of peptide biomarkers may be performed by detection of the peptide biomarker or of a fragment thereof, e.g. a fragment with C-terminal truncation, or with N-terminal truncation. Fragments are suitably greater than 4 amino acids in length, for example 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 20 amino acids in length.
  • the biomarker defined herein may be replaced by a molecule, or a measurable fragment of the molecule, found upstream or downstream of the biomarker in a biological pathway.
  • biosensor means anything capable of detecting the presence of the biomarker. Examples of biosensors are described herein.
  • Biosensors according to the invention may comprise a ligand or ligands, as described herein, capable of specific binding to the peptide biomarker. Such biosensors are useful in detecting and/or quantifying a peptide of the invention.
  • the biomarker may be directly detected, e.g. by SELDI or MALDI-TOF.
  • the biomarker may be detected directly or indirectly via interaction with a ligand or ligands such as an antibody or a biomarker-binding fragment thereof, or other peptide, or ligand, e.g. aptamer, or oligonucleotide, capable of specifically binding the biomarker.
  • the ligand may possess a detectable label, such as a luminescent, fluorescent or radioactive label, and/or an affinity tag.
  • detecting and/or quantifying can be performed by one or more method(s) selected from the group consisting of: SELDI (-TOF), MALDI (-TOF), a 1-D gel-based analysis, a 2-D gel-based analysis, Mass spec (MS), reverse phase (RP) LC, size permeation (gel filtration), ion exchange, affinity, HPLC, UPLC and other LC or LC MS-based techniques.
  • Appropriate LC MS techniques include ICAT® (Applied Biosystems, CA, USA), or iTRAQ® (Applied Biosystems, CA, USA).
  • Liquid chromatography ⁇ e.g. high pressure liquid chromatography (HPLC) or low pressure liquid chromatography (LPLC)), thin-layer chromatography, NMR (nuclear magnetic resonance) spectroscopy could also be used.
  • Methods according to the invention may comprise analysing a sample of blood serum by SELDI-TOF or MALDI-TOF to detect the presence or level of the peptide biomarker. These methods are also suitable for clinical screening, prognosis, monitoring the results of therapy, identifying patients most likely to respond to a particular therapeutic treatment, for drug screening and development, and identification of new targets for drug treatment.
  • Detecting and/or quantifying the peptide biomarkers may be performed using an immunological method, involving an antibody, or a fragment thereof capable of specific binding to the peptide biomarker.
  • Suitable immunological methods include sandwich immunoassays, such as sandwich ELISA, in which the detection of the peptide biomarkers is performed using two antibodies which recognize different epitopes on a peptide biomarker; radioimmunoassays (RIA), direct, indirect or competitive enzyme linked immunosorbent assays (ELISA), enzyme immunoassays (EIA), Fluorescence immunoassays (FIA), western blotting, immunoprecipitation and any particle-based immunoassay ⁇ e.g.
  • Immunological methods may be performed, for example, in microtitre plate or strip format. Immunological methods in accordance with the invention may be based, for example, on any of the following methods.
  • Immunoprecipitation is the simplest immunoassay method; this measures the quantity of precipitate, which forms after the reagent antibody has incubated with the sample and reacted with the target antigen present therein to form an insoluble aggregate. Immunoprecipitation reactions may be qualitative or quantitative. In particle immunoassays, several antibodies are linked to the particle, and the particle is able to bind many antigen molecules simultaneously. This greatly accelerates the speed of the visible reaction. This allows rapid and sensitive detection of the biomarker. In immunonephelometry, the interaction of an antibody and target antigen on the biomarker results in the formation of immune complexes that are too small to precipitate. However, these complexes will scatter incident light and this can be measured using a nephelometer. The antigen, i.e. biomarker, concentration can be determined within minutes of the reaction.
  • Radioimmunoassay (RIA) methods employ radioactive isotopes such as I 125 to label either the antigen or antibody.
  • the isotope used emits gamma rays, which are usually measured following removal of unbound (free) radiolabel.
  • the major advantages of RIA compared with other immunoassays, are higher sensitivity, easy signal detection, and well-established, rapid assays.
  • the major disadvantages are the health and safety risks posed by the use of radiation and the time and expense associated with maintaining a licensed radiation safety and disposal program. For this reason, RIA has been largely replaced in routine clinical laboratory practice by enzyme immunoassays.
  • EIA Enzyme immunoassays were developed as an alternative to radioimmunoassays (RIA). These methods use an enzyme to label either the antibody or target antigen. The sensitivity of EIA approaches that of RIA, without the danger posed by radioactive isotopes.
  • One of the most widely used EIA methods for detection is the enzyme-linked immunosorbent assay (ELISA). ELISA methods may use two antibodies one of which is specific for the target antigen and the other of which is coupled to an enzyme, addition of the substrate for the enzyme results in production of a chemiluminescent or fluorescent signal.
  • Fluorescent immunoassay refers to immunoassays which utilize a fluorescent label or an enzyme label which acts on the substrate to form a fluorescent product. Fluorescent measurements are inherently more sensitive than colorimetric (spectrophotometric) measurements. Therefore, FIA methods have greater analytical sensitivity than EIA methods, which employ absorbance (optical density) measurement.
  • Chemiluminescent immunoassays utilize a chemiluminescent label, which produces light when excited by chemical energy; the emissions are measured using a light detector.
  • Immunological methods according to the invention can thus be performed using well-known methods. Any direct ⁇ e.g., using a sensor chip) or indirect procedure may be used in the detection of the peptide biomarker of the invention.
  • Biotin-Avidin or Biotin-Streptavidin systems are generic labelling systems that can be adapted for use in immunological methods of the invention.
  • One binding partner hapten, antigen, ligand, aptamer, antibody, enzyme etc
  • biotin is labelled with avidin or streptavidin.
  • surface e.g. well, bead, sensor etc
  • avidin or streptavidin is labelled with avidin or streptavidin.
  • This is conventional technology for immunoassays, gene probe assays and (bio)sensors, but is an indirect immobilisation route rather than a direct one.
  • a biotinylated ligand ⁇ e.g.
  • antibody or aptamer) specific for a peptide biomarker of the invention may be immobilised on an avidin or streptavidin surface, the immobilised ligand may then be exposed to a sample containing or suspected of containing the peptide biomarker in order to detect and/or quantify a peptide biomarker of the invention. Detection and/or quantification of the immobilised antigen may then be performed by an immunological method as described herein.
  • antibody as used herein includes, but is not limited to: polyclonal, monoclonal, bispecific, humanised or chimeric antibodies, single chain antibodies, Fab fragments and F(ab') 2 fragments, fragments produced by a Fab expression library, anti-idiotypic (anti-Id) antibodies and epitope-binding fragments of any of the above.
  • antibody as used herein also refers to immunoglobulin molecules and immunologically-active portions of immunoglobulin molecules, i.e., molecules that contain an antigen binding site that specifically binds an antigen.
  • the immunoglobulin molecules of the invention can be of any class ⁇ e.g., IgG, IgE, IgM, IgD and IgA) or subclass of immunoglobulin molecule.
  • the identification of key biomarkers specific to a disease is central to integration of diagnostic procedures and therapeutic regimes.
  • appropriate diagnostic tools such as biosensors can be developed, accordingly, in methods and uses of the invention, detecting and quantifying can be performed using a biosensor, microanalytical system, microengineered system, microseparation system, immunochromatography system or other suitable analytical devices.
  • the biosensor may incorporate an immunological method for detection of the biomarker, electrical, thermal, magnetic, optical ⁇ e.g. hologram) or acoustic technologies. Using such biosensors, it is possible to detect the target biomarker at the anticipated concentrations found in biological samples.
  • an apparatus for monitoring major depressive disorder which comprises a biosensor, microanalytical, microengineered, microseparation and/or immunochromatography system configured to detect and/or quantify the biomarker defined herein.
  • the biomarker of the invention can be detected using a biosensor incorporating technologies based on "smart" holograms, or high frequency acoustic systems, such systems are particularly amenable to "bar code” or array configurations.
  • a biosensor incorporating technologies based on "smart" holograms, or high frequency acoustic systems, such systems are particularly amenable to "bar code” or array configurations.
  • smart hologram sensors Smart Holograms Ltd, Cambridge, UK
  • a holographic image is stored in a thin polymer film that is sensitised to react specifically with the biomarker.
  • the biomarker reacts with the polymer leading to an alteration in the image displayed by the hologram.
  • the test result read-out can be a change in the optical brightness, image, colour and/or position of the image.
  • a sensor hologram can be read by eye, thus removing the need for detection equipment.
  • a simple colour sensor can be used to read the signal when quantitative measurements are required. Opacity or colour of the sample does not interfere with operation of the sensor.
  • the format of the sensor allows multiplexing for simultaneous detection of several substances. Reversible and irreversible sensors can be designed to meet different requirements, and continuous monitoring of a particular biomarker of interest is feasible.
  • biosensors for detection of the biomarker of the invention combine biomolecular recognition with appropriate means to convert detection of the presence, or quantitation, of the biomarker in the sample into a signal.
  • Biosensors can be adapted for "alternate site” diagnostic testing, e.g. in the ward, outpatients' department, surgery, home, field and workplace.
  • Biosensors to detect the biomarker of the invention include acoustic, plasmon resonance, holographic and microengineered sensors. Imprinted recognition elements, thin film transistor technology, magnetic acoustic resonator devices and other novel acousto-electrical systems may be employed in biosensors for detection of the biomarker of the invention.
  • Methods involving detection and/or quantification of the peptide biomarker of the invention can be performed on bench-top instruments, or can be incorporated onto disposable, diagnostic or monitoring platforms that can be used in a non-laboratory environment, e.g. in the physician's office or at the patient's bedside.
  • Suitable biosensors for performing methods of the invention include "credit" cards with optical or acoustic readers. Biosensors can be configured to allow the data collected to be electronically transmitted to the physician for interpretation and thus can form the basis for e-neuromedicine.
  • Any suitable animal may be used as a subject non-human animal, for example a non-human primate, horse, cow, pig, goat, sheep, dog, cat, fish, rodent, e.g. guinea pig, rat or mouse; insect ⁇ e.g. Drosophila), amphibian ⁇ e.g. Xenopus) or C. elegans.
  • a method of identifying a substance capable of promoting or suppressing the generation of the peptide biomarker in a subject comprising exposing a test cell to a test substance and monitoring the level of the peptide biomarker within said test cell, or secreted by said test cell .
  • the test cell could be prokaryotic, however a eukaryotic cell will suitably be employed in cell-based testing methods.
  • the eukaryotic cell is a yeast cell, insect cell, Drosophila cell, amphibian cell ⁇ e.g. from Xenopus), C. elegans cell or is a cell of human, non-human primate, equine, bovine, porcine, caprine, ovine, canine, feline, piscine, rodent or murine origin.
  • the test substance can be a known chemical or pharmaceutical substance, such as, but not limited to, an anti-depressive disorder therapeutic; or the test substance can be novel synthetic or natural chemical entity, or a combination of two or more of the aforesaid substances.
  • non-human animals or cells can be used that are capable of expressing the peptide.
  • Screening methods also encompass a method of identifying a ligand capable of binding to the peptide biomarker according to the invention, comprising incubating a test substance in the presence of the peptide biomarker in conditions appropriate for binding, and detecting and/or quantifying binding of the peptide to said test substance.
  • High-throughput screening technologies based on the biomarker, uses and methods of the invention, e.g. configured in an array format, are suitable to monitor biomarker signatures for the identification of potentially useful therapeutic compounds, e.g. ligands such as natural compounds, synthetic chemical compounds ⁇ e.g. from combinatorial libraries), peptides, monoclonal or polyclonal antibodies or fragments thereof, which may be capable of binding the biomarker.
  • Methods of the invention can be performed in array format, e.g. on a chip, or as a multiwell array. Methods can be adapted into platforms for single tests, or multiple identical or multiple non-identical tests, and can be performed in high throughput format. Methods of the invention may comprise performing one or more additional, different tests to confirm or exclude diagnosis, and/or to further characterise a condition.
  • the invention further provides a substance, e.g. a ligand, identified or identifiable by an identification or screening method or use of the invention.
  • a substance e.g. a ligand, identified or identifiable by an identification or screening method or use of the invention.
  • Such substances may be capable of inhibiting, directly or indirectly, the activity of the peptide biomarker, or of suppressing generation of the peptide biomarker.
  • the term "substances" includes substances that do not directly bind the peptide biomarker and directly modulate a function, but instead indirectly modulate a function of the peptide biomarker.
  • Ligands are also included in the term substances; ligands of the invention ⁇ e.g. a natural or synthetic chemical compound, peptide, aptamer, oligonucleotide, antibody or antibody fragment) are capable of binding, suitably specific binding, to the peptide.
  • the invention further provides a substance according to the invention for use in the treatment of major depressive disorder, or predisposition thereto.
  • the method additionally comprises administering an antidepressant to a patient who is diagnosed with or predicted to have MDD.
  • an MDD patient such as a recurrent and/or drug naive first onset MDD patient
  • a method of treating an MDD patient which comprises the step of administering an antidepressant to a patient identified as having differing levels of the analyte biomarkers as defined herein when compared to the levels of said analyte biomarkers from a normal subject.
  • an MDD patient such as a recurrent and/or drug naive first onset MDD patient, which comprises the following steps:
  • step (c) administering an antidepressant to a patient diagnosed in step (b) as a patient with MDD.
  • kits for diagnosing and/or monitoring major depressive disorder comprising reagents and/or a biosensor capable of detecting and/or quantifying the biomarkers described herein.
  • a kit according to the invention may contain one or more components selected from the group: a ligand specific for the peptide biomarker or a structural/shape mimic of the peptide biomarker, one or more controls, one or more reagents and one or more consumables; optionally together with instructions for use of the kit in accordance with any of the methods defined herein.
  • the kit additionally comprises a questionnaire for use in diagnosing a patient with MDD.
  • the questionnaire may be used to support the results obtained from use of the kit and/or to help determine the severity of major depressive disorder ⁇ i.e. severe, moderate or mild).
  • the questionnaire is the Hamilton Rating scale for depression (HAM-D, 17, 21 or 29 items) questionnaire.
  • suitable questionnaires include: the Montgomery-Asberg Depression Rating Scale (MADRS), the Beck Depression Inventory (BDI), the Zung Self- Rating Depression Scale, the Wechsler Depression Rating Scale, the Raskin Depression Rating Scale, the Inventory of Depressive Symptomatology (IDS) or the Quick Inventory of Depressive Symptomatology (QIDS).
  • kits for the diagnosis and monitoring of major depressive disorder or other psychotic disorder are described herein.
  • the kits additionally contain a biosensor capable of detecting and/or quantifying a peptide biomarker.
  • biomarkers for major depressive disorder or other psychotic disorder permits integration of diagnostic procedures and therapeutic regimes.
  • many anti-depressive or anti-psychotic therapies have required treatment trials lasting weeks to months for a given therapeutic approach.
  • Detection of a peptide biomarker of the invention can be used to screen subjects prior to their participation in clinical trials.
  • the biomarkers provide the means to indicate therapeutic response, failure to respond, unfavourable side-effect profile, degree of medication compliance and achievement of adequate serum drug levels.
  • the biomarkers may be used to provide warning of adverse drug response.
  • Biomarkers are useful in development of personalized brain therapies, as assessment of response can be used to fine-tune dosage, minimise the number of prescribed medications, reduce the delay in attaining effective therapy and avoid adverse drug reactions.
  • patient care can be tailored precisely to match the needs determined by the disorder and the pharmacogenomic profile of the patient, the biomarker can thus be used to titrate the optimal dose, predict a positive therapeutic response and identify those patients at high risk of severe side effects.
  • Biomarker-based tests provide a first line assessment of 'new' patients, and provide objective measures for accurate and rapid diagnosis, in a time frame and with precision, not achievable using the current subjective measures.
  • biomarker tests are useful to identify family members or patients at high risk of developing major depressive disorder or other psychotic disorder. This permits initiation of appropriate therapy, or preventive measures, e.g. managing risk factors. These approaches are recognised to improve outcome and may prevent overt onset of the disorder.
  • Biomarker monitoring methods, biosensors and kits are also vital as patient monitoring tools, to enable the physician to determine whether relapse is due to worsening of the disorder, poor patient compliance or substance abuse. If pharmacological treatment is assessed to be inadequate, then therapy can be reinstated or increased; a change in therapy can be given if appropriate.
  • the biomarker is sensitive to the state of the disorder, it provides an indication of the impact of drug therapy or of substance abuse.
  • the levels of one or more analyte biomarkers or the levels of a specific panel of analyte biomarkers in a sample are compared to a reference standard ("reference standard” or “reference level”) in order to direct treatment decisions.
  • the reference standard used for any embodiment disclosed herein may comprise average, mean, or median levels of the one or more analyte biomarkers or the levels of the specific panel of analyte biomarkers in a control population.
  • the reference standard may additionally comprise cutoff values or any other statistical attribute of the control population, such as a standard deviation from the mean levels of the one or more analyte biomarkers or the levels of the specific panel of analyte biomarkers.
  • comparing the level of the one or more analyte biomarkers is performed using a cutoff value. In related embodiments, if the level of the one or more analyte biomarkers is greater than the cutoff value, the individual may be diagnosed as having, or being at risk of developing major depressive disorder. In other distinct embodiments, if the level of the one or more analyte biomarkers is less than the cutoff value, the individual may be diagnosed as having, or being at risk of developing major depressive disorder. Cutoff values may be determined by statistical analysis of the control population to determine which levels represent a high likelihood that an individual does or does not belong to the control population. In some embodiments, comparing the level of the one or more analyte biomarkers is performed using other statistical methods. In related embodiments, comparing comprises logistic or linear regression. In other embodiments, comparing comprises computing an odds ratio.
  • control population may comprise healthy individuals or individuals with major depressive disorder.
  • individuals with levels of one or more analyte biomarkers or levels of a specific panel of analyte biomarkers greater than the reference levels would be more likely to have major depressive disorder. Therefore, an individual presenting with levels of the one or more analyte biomarkers or levels of the specific panel of analyte biomarkers greater than the reference standard would be a candidate for treatment with antidepressant or anxiolytic therapy, or with more aggressive therapy.
  • an individual presenting with levels of the one or more analyte biomarkers or levels of the specific panel of analyte biomarkers less than or equal to the reference standard would be less likely to have major depressive disorder and therefore be a candidate for no antidepressant or anxiolytic therapy, delayed antidepressant or anxiolytic therapy or less aggressive antidepressant or anxiolytic therapy.
  • individuals with levels of one or more analyte biomarkers or levels of a specific panel of analyte biomarkers less than the reference levels would be more likely to have major depressive disorder. Therefore, an individual presenting with levels of the one or more analyte biomarkers or levels of the specific panel of analyte biomarkers less than the reference standard would be a candidate for treatment with antidepressant or anxiolytic therapy, or with more aggressive therapy.
  • an individual presenting with levels of the one or more analyte biomarkers or levels of the specific panel of analyte biomarkers greater than or equal to the reference standard would be less likely to have major depressive disorder and therefore be a candidate for no antidepressant or anxiolytic therapy, delayed antidepressant or anxiolytic therapy or less aggressive antidepressant or anxiolytic therapy.
  • a patient is treated more or less aggressively than a reference therapy.
  • a reference therapy is any therapy that is the standard of care for major depressive disorder.
  • the standard of care can vary temporally and geographically, and a skilled person can easily determine the appropriate standard of care by consulting the relevant medical literature.
  • treatment will be either 1) more aggressive, or 2) less aggressive than a standard therapy.
  • a more aggressive therapy than the standard therapy comprises beginning treatment earlier than in the standard therapy. In some embodiments, a more aggressive therapy than the standard therapy comprises administering additional treatments than in the standard therapy. In some embodiments, a more aggressive therapy than the standard therapy comprises treating on an accelerated schedule compared to the standard therapy. In some embodiments, a more aggressive therapy than the standard therapy comprises administering additional treatments not called for in the standard therapy.
  • a less aggressive therapy than the standard therapy comprises delaying treatment relative to the standard therapy. In some embodiments, a less aggressive therapy than the standard therapy comprises administering less treatment than in the standard therapy. In some embodiments, a less aggressive therapy than the standard therapy comprises administering treatment on a decelerated schedule compared to the standard therapy. In some embodiments, a less aggressive therapy than the standard therapy comprises administering no treatment.
  • Health practitioners treat depression by taking actions to ameliorate the causes or symptoms of the disorder in a patient.
  • Treatment may comprise drug-based or non-drug-based therapies.
  • Drug-based therapies may include: selecting and administering one or more antidepressant drugs to the patient, adjusting the dosage of an antidepressant drug, adjusting the dosing schedule of an antidepressant drug, and adjusting the length of the therapy with an antidepressant drug.
  • Antidepressant drugs are selected by practitioners based on the nature of the symptoms and the patient's response to any previous treatments.
  • the dosage of an antidepressant drug can be adjusted as well by the practitioner based on the nature of the drug, the nature of the patient's symptoms, the patient's response to previous treatment, and the patient's response to the drug.
  • the dosing schedule can also be adjusted by the practitioner based on the nature of the drug, the nature of the patient's symptoms, the patient's response to previous treatment, and the patient's response to the drug.
  • the length of the therapy can be adjusted by the practitioner based on the nature of the drug, the nature of the patient's symptoms, the patient's response to previous treatment, and the patient's response to the drug.
  • the practitioner can select between a single drug therapy, a dual drug therapy, or a triple drug therapy.
  • a practitioner may optionally treat the patient with a combination of one or more antidepressant drugs and one or more non-drug-based therapies.
  • the practitioner begins antidepressant therapy based on a comparison between a reference level and the levels of one or more analyte biomarkers or the levels of a specific panel of analyte biomarkers in a sample from a patient.
  • therapy comprises the selection and administration of an antidepressant drug to the patient by the practitioner.
  • therapy comprises the selection and administration of two antidepressant drugs to the patient by the practitioner as part of dual therapy.
  • therapy comprises the selection and administration of three antidepressant drugs to the patient by the practitioner as part of triple therapy.
  • Antidepressant drugs are commonly used by medical practitioners, and a skilled person may identify the appropriate antidepressant drug to administer based on the medical literature.
  • treatment comprises administering to an individual a selective serotonin reuptake inhibitor ("SSRI").
  • SSRI selective serotonin reuptake inhibitor
  • the SSRI is citalopram .
  • the SSRI is escitalopram .
  • the SSRI is fluoxetine.
  • the SSRI is paroxetine.
  • the SSRI is sertraline.
  • treatment comprises administering to an individual a serotonin-norepinephrine reuptake inhibitors ("SNRI").
  • SNRI serotonin-norepinephrine reuptake inhibitors
  • the SNRI is venlafaxine.
  • the SNRI is duloxetine.
  • treatment comprises administering to an individual a norepinephrine and dopamine reuptake inhibitor ("NDRI").
  • NDRI norepinephrine and dopamine reuptake inhibitor
  • the NDRI is bupropion.
  • treatment comprises administering to an individual a tetracyclic antidepressant ("tetracyclic").
  • tetracyclic is amoxapine.
  • the tetracyclic is maprotiline.
  • the tetracyclic is mazindol.
  • the tetracyclic is mirtazapine.
  • treatment comprises administering to an individual a tricyclic antidepressant ("tricyclic").
  • tricyclic is amitriptyline.
  • the tricyclic is imipramine.
  • the tricyclic is nortriptyline.
  • treatment comprises administering to an individual a monoamine oxidase inhibitor ("MAOI").
  • MAOI monoamine oxidase inhibitor
  • the MAOI is selegiline.
  • the MAOI is isocarboxazid.
  • the MAOI is phenelzine.
  • the MAOI is tranylcypromine.
  • a practitioner may also treat an individual with non-drug-based antidepressant therapies.
  • the non-drug based therapy comprises cognitive-behavioral therapy.
  • the non-drug based therapy comprises psychotherapy.
  • the non-drug based therapy comprises psychodynamic therapy.
  • the non-drug based therapy comprises electroconvulsive therapy.
  • the non-drug based therapy comprises hospitalization and residential treatment programs.
  • the non-drug based therapy comprises vagus nerve stimulation.
  • the non-drug based therapy comprises transcranial magnetic stimulation.
  • the non-drug based therapy comprises regular, vigorous exercise.
  • the practitioner adjusts the antidepressant therapy based on a comparison between a reference level and the levels of one or more analyte biomarkers or the levels of a specific panel of analyte biomarkers in a sample from a patient.
  • the practitioner adjusts the therapy by selecting and administering a different drug.
  • the practitioner adjusts the therapy by selecting and administering a different combination of drugs.
  • the practitioner adjusts the therapy by adjusting drug dosage.
  • the practitioner adjusts the therapy by adjusting dose schedule.
  • the practitioner adjusts the therapy by adjusting length of therapy.
  • the practitioner adjusts the therapy by selecting and administering a different drug combination and adjusting drug dosage.
  • the practitioner adjusts the therapy by selecting and administering a different drug combination and adjusting dose schedule. In one embodiment, the practitioner adjusts the therapy by selecting and administering a different drug combination and adjusting length of therapy. In one embodiment, the practitioner adjusts the therapy by adjusting drug dosage and dose schedule. In one embodiment, the practitioner adjusts the therapy by adjusting drug dosage and adjusting length of therapy. In one embodiment, the practitioner adjusts the therapy by adjusting dose schedule and adjusting length of therapy. In one embodiment, the practitioner adjusts the therapy by selecting and administering a different drug, adjusting drug dosage, and adjusting dose schedule. In one embodiment, the practitioner adjusts the therapy by selecting and administering a different drug, adjusting drug dosage, and adjusting length of therapy.
  • the practitioner adjusts the therapy by selecting and administering a different drug, adjusting dose schedule, and adjusting length of therapy. In one embodiment, the practitioner adjusts the therapy by adjusting drug dosage, adjusting dose schedule, and adjusting length of therapy. In one embodiment, the practitioner adjusts the therapy by selecting and administering a different drug, adjusting drug dosage, adjusting dose schedule, and adjusting length of therapy.
  • treatment comprises a less aggressive therapy than a reference therapy.
  • a less aggressive therapy comprises not administering drugs and taking a "watchful waiting" approach.
  • a less aggressive therapy comprises delaying treatment.
  • a less aggressive therapy comprises selecting and administering less potent drugs.
  • a less aggressive therapy comprises decreasing dosage of antidepressant drugs.
  • a less aggressive therapy comprises decreasing the frequency treatment.
  • a less aggressive therapy comprises shortening length of therapy.
  • less aggressive therapy comprises selecting and administering less potent drugs and decreasing drug dosage.
  • less aggressive therapy comprises selecting and administering less potent drugs and decelerating dose schedule.
  • less aggressive therapy comprises selecting and administering less potent drugs and shortening length of therapy.
  • less aggressive therapy comprises decreasing drug dosage and decelerating dose schedule. In one embodiment, less aggressive therapy comprises decreasing drug dosage and shortening length of therapy. In one embodiment, less aggressive therapy comprises decelerating dose schedule and shortening length of therapy. In one embodiment, less aggressive therapy comprises selecting and administering less potent drugs, decreasing drug dosage, and decelerating dose schedule. In one embodiment, less aggressive therapy comprises selecting and administering less potent drugs, decreasing drug dosage, and shortening length of therapy. In one embodiment, less aggressive therapy comprises selecting and administering less potent drugs, decelerating dose schedule, and shortening length of therapy. In one embodiment, less aggressive therapy comprises decreasing drug dosage, decelerating dose schedule, and shortening length of therapy. In one embodiment, less aggressive therapy comprises selecting and administering less potent drugs, decreasing drug dosage, decelerating dose schedule, and shortening length of therapy. In some embodiments, a less aggressive therapy comprises administering only non-drug-based therapies.
  • treatment comprises a more aggressive therapy than a reference therapy.
  • a more aggressive therapy comprises earlier administration of antidepressant drugs.
  • a more aggressive therapy comprises increased dosage of antidepressant drugs.
  • a more aggressive therapy comprises increased length of therapy.
  • a more aggressive therapy comprises increased frequency of the dose schedule.
  • more aggressive therapy comprises selecting and administering more potent drugs and increasing drug dosage.
  • more aggressive therapy comprises selecting and administering more potent drugs and accelerating dose schedule.
  • more aggressive therapy comprises selecting and administering more potent drugs and increasing length of therapy.
  • more aggressive therapy comprises increasing drug dosage and accelerating dose schedule.
  • more aggressive therapy comprises increasing drug dosage and increasing length of therapy.
  • more aggressive therapy comprises accelerating dose schedule and increasing length of therapy. In one embodiment, more aggressive therapy comprises selecting and administering more potent drugs, increasing drug dosage, and accelerating dose schedule. In one embodiment, more aggressive therapy comprises selecting and administering more potent drugs, increasing drug dosage, and increasing length of therapy. In one embodiment, more aggressive therapy comprises selecting and administering more potent drugs, accelerating dose schedule, and increasing length of therapy. In one embodiment, more aggressive therapy comprises increasing drug dosage, accelerating dose schedule, and increasing length of therapy. In one embodiment, more aggressive therapy comprises selecting and administering more potent drugs, increasing drug dosage, accelerating dose schedule, and increasing length of therapy. In some embodiments, a more aggressive therapy comprises administering a combination of drug-based and non-drug-based therapies.
  • results of any analyses according to the invention will often be communicated to physicians and/or patients (or other interested parties such as researchers) in a transmittable form that can be communicated or transmitted to any of the above parties.
  • a form can vary and can be tangible or intangible.
  • the results can be embodied in descriptive statements, diagrams, photographs, charts, images or any other visual forms.
  • the statements and visual forms can be recorded on a tangible medium such as papers, computer readable media such as hard disks, compact disks, etc., or on an intangible medium, e.g., an electronic medium in the form of email or website on internet or intranet.
  • results can also be recorded in a sound form and transmitted through any suitable medium, e.g., analog or digital cable lines, fiber optic cables, etc., via telephone, facsimile, wireless mobile phone, internet phone and the like.
  • the information and data on a test result can be produced anywhere in the world and transmitted to a different location.
  • the information and data on a test result may be generated, cast in a transmittable form as described above, and then imported into the United States.
  • the present invention also encompasses a method for producing a transmittable form of information on levels of one or more analyte biomarkers or levels of a specific panel of analyte biomarkers for at least one patient sample.
  • the method comprises the steps of (1) determining levels of one or more analyte biomarkers or levels of a specific panel of analyte biomarkers for at least one patient sample according to methods of the present invention; and (2) embodying the result of the determining step in a transmittable form.
  • the transmittable form is the product of such a method.
  • Techniques for analyzing levels of one or more analyte biomarkers or levels of a specific panel of analyte biomarkers for at least one patient sample will often be implemented using hardware, software or a combination thereof in one or more computer systems or other processing systems capable of effectuating such analysis.
  • the present invention further provides a system for determining whether an individual suffers from major depressive disorder, comprising : (1) a sample analyzer for determining the levels of one or more analyte biomarkers or levels of a specific panel of analyte biomarkers for at least one patient sample, wherein the sample analyzer contains the patient sample; (2) a first computer program for (a) receiving data regarding the levels of one or more analyte biomarkers or the levels of a specific panel of analyte biomarkers; and optionally (3) a second computer program for comparing the test value to one or more reference standards each associated with a predetermined degree of risk of major depressive disorder.
  • the sample analyzer can be any instruments useful in determining the levels of biomarkers in a sample, as described herein.
  • the computer-based analysis function can be implemented in any suitable language and/or browsers. For example, it may be implemented with C language and preferably using object-oriented high-level programming languages such as Visual Basic, SmallTalk, C++, and the like.
  • the application can be written to suit environments such as the Microsoft WindowsTM environment including WindowsTM 98, WindowsTM 2000, WindowsTM NT, and the like.
  • the application can also be written for the MacIntoshTM, SUNTM, UNIX or LINUX environment.
  • the functional steps can also be implemented using a universal or platform-independent programming language.
  • multi-platform programming languages include, but are not limited to, hypertext markup language (HTML), JAVATM, JavaScriptTM, Flash programming language, common gateway interface/structured query language (CGI/SQL), practical extraction report language (PERL), AppleScriptTM and other system script languages, programming language/structured query language (PL/SQL), and the like.
  • JavaTM- or JavaScriptTM-enabled browsers such as HotJavaTM, MicrosoftTM ExplorerTM, or NetscapeTM can be used.
  • active content web pages may include JavaTM applets or ActiveXTM controls or other active content technologies.
  • the analysis function can also be embodied in computer program products and used in the systems described above or other computer- or internet-based systems. Accordingly, another aspect of the present invention relates to a computer program product comprising a computer-usable medium having computer-readable program codes or instructions embodied thereon for enabling a processor to carry out disease risk analysis.
  • These computer program instructions may be loaded onto a computer or other programmable apparatus to produce a machine, such that the instructions which execute on the computer or other programmable apparatus create means for implementing the functions or steps described above.
  • These computer program instructions may also be stored in a computer-readable memory or medium that can direct a computer or other programmable apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory or medium produce an article of manufacture including instructions which implement the analysis.
  • the computer program instructions may also be loaded onto a computer or other programmable apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions or steps described above.
  • one aspect of the present invention provides a system for determining whether a patient has major depressive disorder.
  • the system comprises (1) computer program for receiving, storing, and/or retrieving data regarding levels of biomarkers in a patient's sample and optionally clinical parameter data ⁇ e.g., disease-related symptoms); (2) computer program for querying this patient data; (3) computer program for concluding whether an individual suffers from major depressive disorder based on this patient data; and optionally (4) computer program for outputting/displaying this conclusion.
  • this computer program for outputting the conclusion may comprise a computer program for informing a health care professional of the conclusion.
  • Computer software products of the invention typically include computer readable media having computer-executable Instructions for performing the logic steps of the method of the invention.
  • Suitable computer readable medium include floppy disk, CD-ROM/DVD/DVD- ROM, hard-disk drive, flash memory, ROM/RAM, magnetic tapes and etc.
  • Basic computational biology methods are described in, for example, Setubal et al., INTRODUCTION TO COMPUTATIONAL BIOLOGY METHODS (PWS Publishing Company, Boston, 1997); Salzberg et al.
  • BIOINFORMATICS BASICS APPLICATION IN BIOLOGICAL SCIENCE AND MEDICINE (CRC Press, London, 2000); and Ouelette & Bzevanis, Attorney Docket No. 3330-01-lP Page 38 of 64 BIOINFORMATICS : A PRACTICAL GUIDE FOR ANALYSIS OF GENE AN D PROTEINS (Wiley & Sons, Inc., 2nd ed., 2001); see also, U.S. Pat. No. 6,420,108.
  • MDD cohorts were analyzed, 6 of which were independent and 2 were a subset of larger cohorts. These 2 cohorts were independent from each other and selected to include only drug naive (DN) first onset MDD patients and healthy controls.
  • MDD cohort 1 was from University of Cologne (Germany)
  • MDD cohort 2 from University of Muenster (Germany)
  • MDD cohorts 3 and 4 were from the University of Magdeburg (Germany)
  • the DN MDD cohorts 1 and 2 were a subset of MDD cohorts 3 and 4
  • NESDA MDD cohorts were from the Netherlands Study of Depression and Anxiety Severity (NESDA), an on-going multi-site naturalistic longitudinal cohort study.
  • the NESDA patients had a current MDD diagnosis based on disease occurrence within 6 months.
  • the study protocols were approved by the institutional ethical committee associated with each of the clinical centres. All diagnoses and clinical tests were performed by trained psychiatrists to minimize variability. Informed written consent was given by all participants and all studies were conducted according to the Declaration of Helsinki. All diagnoses were carried out using the Diagnostic and Statistical Manual DSM-IV-TR for a unipolar major depressive episode. Severity of depressive symptoms was assessed at baseline using the Hamilton Rating scale for depression (HAM-D, 17 or 21 items) questionnaire.
  • the exclusion criteria typically included most or all of the following : chronic illnesses ⁇ e.g.
  • HumanMAP HumanMAP® multiplexed antigen immunoassays
  • DN MDD cohorts 1 and 2 a newer version of the HumanMAP was used which measures greater than 200 analytes.
  • NESDA MDD cohorts the latest version of the HumanMAP was used which measures greater than 250 analytes. All samples were randomized and blinded to analysts using code numbers until all biochemical assays were complete to avoid any sequential bias due to the diagnosis, age and gender.
  • the study described herein aimed to identify a panel of candidate biomarkers in serum which can discriminate MDD patients recruited from both primary and specialized mental health care from healthy controls. This was determined by stepwise logistic regression and the most frequently selected covariates included gender and smoking. Application of this method led to identification of 34 serum molecules in at least 3 cohorts and the directions of change (increased or decreased levels) were mostly consistent (see Table 2 for a brief summary of the MDD diagnostic markers identified in common and Tables 3 - 10 for the full results from each cohort). The biomarkers identified were more similar between MDD cohorts 1, 3, 4 and DN MDD cohorts 1 and 2, compared to those identified in MDD cohort 2 and the NESDA MDD cohorts. This may be explained by disease heterogeneity among MDD patients.
  • ROC-AUC receiver operating characteristic
  • the top 19-24 most reproducible markers could be tested together as a panel ( Figures 3 and 4).
  • analyte panel combinations 2 [IL-lra, FRTN, MIF, EN-RAGE, TNC], 4 [IL-lra, FRTN, EN-RAGE, ACE, TNC], 12 [IL-lra + FRTN + MIF + TNC + EGF], 13 [IL-lra + FRTN + ENRAGE + TNC + EGF] and 16 [IL-lra + FRTN + ACE + TNC + EGF] gave the best performance apart from only poor performance in cohort 2.
  • a star indicates a cohort where an analyte wa found to be altered in patients relative to controls.
  • ) indicates a cohort where an analyt was found to be increased and decreased in patients relative to controls, respectively.
  • Sig. p ⁇ 0.05; Trend: 0.05 ⁇ p ⁇ 0.07; NA: analyte failed QC or not included in the DiscMAP used.
  • MPO Myeloperoxidase
  • VCAM-1 Vascular Cell Adhesion Molecule-1 19.68 0.011
  • Thyroxine-Binding Globulin 19.75 0.012
  • Interleukin-13 (IL-13) -10.24 0.016 von Willebrand Factor (vWF) 7.09 0.021
  • Interleukin-1 receptor antagonist IL-lra
  • Apolipoprotein C-III (Apo C-III) 7.51 0.031
  • Macrophage Inflammatory Protein-1 beta (MIP-1 beta) -7.82 0.031
  • EGF Epidermal Growth Factor
  • HGF Hepatocyte Growth Factor
  • FAS FASLG Receptor
  • Apolipoprotein H (Apo H) 11.29 0.040
  • CD40 Ligand (CD40-L) 9.41 0.044
  • Angiotensin-Converting Enzyme (ACE) -7.17 0.057
  • Interleukin-16 9.48 0.061
  • Interleukin-7 (IL-7) -5.56 0.067
  • Thyroid-Stimulating Hormone (TSH) -5.59 0.058
  • Plasminogen Activator Inhibitor 1 (PAI-1) 6.72 0.081
  • Interleukin-15 (IL-15) -2.25 0.094
  • Glutathione S-Transferase alpha (GST-alpha) -3.02 0.094
  • SCF Stem Cell Factor
  • Apolipoprotein A-I (Apo A-I) 4.96 0.114
  • TNF-Related Apoptosis-Inducing Ligand Receptor 3 (TRAIL- 3.65 0.183 R3)
  • MCP-1 Monocyte Chemotactic Protein 1
  • CD 40 antigen CD40 8.57 0.251
  • Interleukin-5 IL-5 -1.61 0.266
  • FSH Follicle-Stimulating Hormone
  • Cancer Antigen 19-9 (CA-19-9) -1.45 0.292
  • ICM-1 Intercellular Adhesion Molecule 1
  • VEGF Vascular Endothelial Growth Factor
  • Interleukin-18 (IL-18) 2.78 0.348
  • MIP-1 alpha Macrophage Inflammatory Protein-1 alpha
  • Beta-2-Microglobulin (B2M) 5.64 0.388
  • Interferon gamma IFN-gamma
  • Interleukin-8 (IL-8) -1.65 0.433
  • Serum Amyloid P-Component (SAP) 1.62 0.471
  • Chromogranin-A (CgA) 0.6 0.518
  • CRP C-Reactive Protein
  • IGFBP-2 Insulin-like Growth Factor-Binding Protein 2
  • BLC B Lymphocyte Chemoattractant
  • Interleukin-1 alpha 0.86 0.717
  • Interleukin-3 (IL-3) -0.58 0.771
  • TFR2 Tumor necrosis factor receptor 2
  • Interleukin-10 (IL-10) -0.28 0.874
  • SHBG Sex Hormone-Binding Globulin
  • MMP-3 Matrix Metalloproteinase-3
  • IP-10 Interferon gamma Induced Protein 10 (IP-10) NA NA
  • MMP-2 Matrix Metalloproteinase-2 (MMP-2) NA NA
  • EGFR Epidermal Growth Factor Receptor
  • LDL Receptor 1 NA NA Neutrophil Gelatinase-Associated Lipocalin (NGAL) NA NA NA NA
  • CTGF Connective Tissue Growth Factor
  • MCP-4 Monocyte Chemotactic Protein 4 (MCP-4) NA NA
  • Apolipoprotein A-II (Apo A-II) NA NA
  • MMP-2 Matrix Metalloproteinase-2
  • MIP-1 alpha Macrophage Inflammatory Protein-1 alpha 4.41 1.27E-03
  • Interleukin-18 (IL-18) 5.7 0.002
  • MMP-3 Matrix Metalloproteinase-3
  • MIP-1 beta Macrophage Inflammatory Protein-1 beta
  • Apolipoprotein A-I (Apo A-I) -3.38 0.006
  • SHBG Sex Hormone-Binding Globulin
  • Serum Amyloid P-Component (SAP) 3.35 0.014
  • CRP C-Reactive Protein
  • Glutathione S-Transferase alpha (GST-alpha) 1.01 0.024
  • Interleukin-10 (IL-10) 1.9 0.024
  • HGF Hepatocyte Growth Factor
  • Immunoglobulin A (IgA) -2.23 0.039
  • FAS FASLG Receptor
  • TFR2 Tumor necrosis factor receptor 2
  • VEGF Vascular Endothelial Growth Factor
  • MPO Myeloperoxidase
  • MCP-1 Monocyte Chemotactic Protein 1
  • Interleukin-15 0.74 0.086
  • BLC B Lymphocyte Chemoattractant
  • TNF-Related Apoptosis-Inducing Ligand Receptor 3 (TRAIL- 1.78 0.126 R3)
  • CD40 Ligand (CD40-L) 0.59 0.187
  • Interleukin-7 IL-7 0.9 0.224
  • IGFBP-2 Insulin-like Growth Factor-Binding Protein 2
  • SCF Stem Cell Factor
  • Interleukin-3 1.03 0.287
  • EGF Epidermal Growth Factor
  • Apolipoprotein C-III (Apo C-III) -1.21 0.295
  • CD 40 antigen (CD40) 1.6 0.315
  • Plasminogen Activator Inhibitor 1 (PAI-1) 1.42 0.345
  • Apolipoprotein H (Apo H) 1.32 0.407
  • FSH Follicle-Stimulating Hormone
  • Interleukin-5 0.41 0.484
  • Interleukin-1 receptor antagonist (IL-lra) 0.24 0.617
  • Epithelial-Derived Neutrophil-Activating Protein 78 (ENA-78) -0.36 0.660
  • Interleukin-8 (IL-8) -0.31 0.746 Thyroxine-Binding Globulin (TBG) -0.47 0.783
  • Interleukin-1 alpha (IL-1 alpha) -0.17 0.802
  • Interleukin-16 0.26 0.854
  • Vascular Cell Adhesion Molecule-1 (VCAM-1) -0.14 0.933
  • Thyroid-Stimulating Hormone (TSH) -0.01 0.989
  • Interferon gamma IFN-gamma
  • IP-10 Interferon gamma Induced Protein 10 (IP-10) NA NA
  • EGFR Epidermal Growth Factor Receptor
  • CTGF Connective Tissue Growth Factor
  • MCP-4 Monocyte Chemotactic Protein 4 (MCP-4) NA NA
  • Apolipoprotein A-II (Apo A-II) NA NA
  • Interleukin-1 receptor antagonist (IL-lra) 4.45 7.98E-06
  • Interleukin-16 (IL-16) 5.75 4.04E-05
  • IGFBP-2 Insulin-like Growth Factor-Binding Protein 2
  • Interferon gamma IFN-gamma
  • Interleukin-7 (IL-7) -1.24 0.002
  • Thyroid-Stimulating Hormone Thyroid-Stimulating Hormone (TSH) -1.74 0.002
  • Thrombospondin-1 1.55 0.003
  • Interleukin-5 IL-5 -1.33 0.004
  • Interleukin-3 IL-3
  • IL-3 Interleukin-3
  • MPO Myeloperoxidase
  • Macrophage Inflammatory Protein-1 alpha (MIP-1 alpha) 4.1 0.010
  • TNF-Related Apoptosis-Inducing Ligand Receptor 3 (TRAIL- 2.28 0.013
  • FSH Follicle-Stimulating Hormone
  • Interleukin-13 (IL-13) -1.96 0.019
  • BLC B Lymphocyte Chemoattractant
  • Angiotensin-Converting Enzyme (ACE)-2.62 0.028
  • TNFR2 Tumor necrosis factor receptor 2
  • VEGF Vascular Endothelial Growth Factor
  • Interleukin-8 1.59 0.037
  • Interleukin-15 (IL-15) -0.7 0.043
  • Thyroxine-Binding Globulin (TBG) -2.5 0.056 von Willebrand Factor (vWF) 1.43 0.058
  • MCP-1 Monocyte Chemotactic Protein 1
  • Apolipoprotein C-III (Apo C-III) -1.64 0.127
  • GRO-alpha Growth-Regulated alpha protein
  • EGF Epidermal Growth Factor
  • Vascular Cell Adhesion Molecule-1 VCAM-1 (VCAM-1) -1.98 0.196
  • Immunoglobulin A 1.02 0.238
  • Plasminogen Activator Inhibitor 1 PAI-1.64 0.253 Apolipoprotein H (Apo H) 1.78 0.254
  • HGF Hepatocyte Growth Factor
  • Alpha-2-Macroglobulin (A2Macro) 1.3 0.334
  • SCF Stem Cell Factor
  • Epithelial-Derived Neutrophil-Activating Protein 78 (ENA-78) -0.53 0.393
  • CRP C-Reactive Protein
  • SHBG Sex Hormone-Binding Globulin
  • Glutathione S-Transferase alpha 0.15 0.643
  • Interleukin-10 0.31 0.694
  • MIP-1 beta Macrophage Inflammatory Protein-1 beta 0.35 0.704
  • FAS FASLG Receptor
  • Interleukin-18 0.21 0.865
  • Chromogranin-A (CgA) 0.04 0.883
  • MMP-3 Matrix Metalloproteinase-3
  • Apolipoprotein A-I (Apo A-I) 0.11 0.911
  • Interleukin-1 alpha (IL-1 alpha) -0.05 0.940
  • IP-10 Interferon gamma Induced Protein 10 (IP-10) NA NA
  • MMP-2 Matrix Metalloproteinase-2 (MMP-2) NA NA
  • EGFR Epidermal Growth Factor Receptor
  • CTGF Connective Tissue Growth Factor
  • MCP-4 Monocyte Chemotactic Protein 4 (MCP-4) NA NA
  • Apolipoprotein A-II (Apo A-II) NA NA
  • Fetuin-A NA NA Key Signal : p ⁇ 0.05; Trend : 0.05 ⁇ p ⁇ 0.07; NA: analyte failed QC or not included in the DiscMAP used
  • Interleukin-1 receptor antagonist (IL-lra) 8.86 0.003
  • MIP-1 alpha Macrophage Inflammatory Protein-1 alpha
  • MIF Macrophage Migration Inhibitory Factor
  • EGF Epidermal Growth Factor
  • Angiotensin-Converting Enzyme (ACE) -14.15 0.031
  • IGFBP-2 Insulin-like Growth Factor-Binding Protein 2
  • Apolipoprotein A-I (Apo A-I) -10.93 0.061
  • MIP-1 beta Macrophage Inflammatory Protein-1 beta 7.61 0.072
  • Apolipoprotein C-III (Apo C-III) -6.62 0.084
  • Interleukin-16 6.27 0.088
  • Interleukin-1 alpha (IL-1 alpha) 2.05 0.166
  • Interleukin-10 (IL-10) 3.18 0.167
  • MPO Myeloperoxidase
  • MMP-3 Matrix Metalloproteinase-3
  • Sex Hormone-Binding Globulin (SHBG) -1.93 0.281
  • CRP C-Reactive Protein
  • FAS FASLG Receptor
  • IgA Immunoglobulin A
  • Interleukin-18 (IL-18) 2.94 0.355
  • MCP-1 Monocyte Chemotactic Protein 1
  • B Lymphocyte Chemoattractant (BLC) -0.99 0.371
  • SCF Stem Cell Factor
  • vWF von Willebrand Factor
  • Vascular Cell Adhesion Molecule-1 VCAM-1 -2.75 0.504
  • CD 40 antigen (CD40) 3.85 0.507
  • Serum Amyloid P-Component 1.38 0.576
  • TNF-Related Apoptosis-Inducing Ligand Receptor 3 (TRAIL- 1.2 0.579 R3)
  • Apolipoprotein H (Apo H) 1.78 0.740
  • Interleukin-13 0.61 0.753
  • Interleukin-7 0.36 0.754
  • TFR2 Tumor necrosis factor receptor 2
  • Glutathione S-Transferase alpha (GST-alpha) -0.31 0.807
  • Interleukin-8 (IL-8) -0.43 0.825
  • ICM-1 Intercellular Adhesion Molecule 1
  • VEGF Vascular Endothelial Growth Factor
  • Plasminogen Activator Inhibitor 1 (PAI-1) -0.67 0.856
  • HGF Hepatocyte Growth Factor
  • MMP-2 Matrix Metalloproteinase-2
  • Thyroid-Stimulating Hormone 0.12 0.953
  • Interleukin-3 0.01 0.994
  • Interleukin-5 (IL-5) NA NA N-(Interleukin-5) NA NA
  • Interferon gamma IFN-gamma
  • EGFR Epidermal Growth Factor Receptor
  • CTGF Connective Tissue Growth Factor
  • MCP-4 Monocyte Chemotactic Protein 4 (MCP-4) NA NA
  • Apolipoprotein A-II (Apo A-II) NA NA
  • Interleukin-16 (IL-16) 10.58 1.00E-03
  • Interleukin-3 (IL-3) -3.74 1.00E-03
  • Interleukin-1 receptor antagonist IL-lra
  • MPO Myeloperoxidase
  • Interleukin-15 (IL-15) -1.81 0.005
  • EGFR Epidermal Growth Factor Receptor
  • NGAL Neutrophil Gelatinase-Associated Lipocalin
  • Interleukin-7 (IL-7) -2.59 0.012
  • Alpha-l-Antichymotrypsin (AACT) 2.41 0.015 Interleukin-5 (IL-5) -1.77 0.017
  • IP-10 Interferon gamma Induced Protein 10
  • Interleukin-13 (IL-13) -4.8 0.022
  • Epithelial-Derived Neutrophil-Activating Protein 78 (ENA-78) -2.45 0.025
  • GRO-alpha Growth-Regulated alpha protein
  • SCF Stem Cell Factor
  • Apolipoprotein A-I (Apo A-I) -4.09 0.031
  • Angiotensin-Converting Enzyme -5.29 0.032
  • Apolipoprotein C-III (Apo C-III) -4.55 0.032
  • IGFBP-2 Insulin-like Growth Factor-Binding Protein 2
  • BLC B Lymphocyte Chemoattractant
  • MCP-1 Monocyte Chemotactic Protein 1
  • Interleukin-8 (IL-8) 2.89 0.048
  • Interferon gamma IFN-gamma
  • Apolipoprotein D (Apo D) 4.8 0.071
  • Apolipoprotein H (Apo H) 6.04 0.074
  • FAS FASLG Receptor
  • ICM-1 Intercellular Adhesion Molecule 1
  • TNF-Related Apoptosis-Inducing Ligand Receptor 3 (TRAIL- 2.45 0.095 R3)
  • HGF Hepatocyte Growth Factor
  • Interleukin-18 (IL-18) 3.02 0.130
  • MCP-4 Monocyte Chemotactic Protein 4
  • Immunoglobulin A (IgA) 2.35 0.178
  • VEGF Vascular Endothelial Growth Factor
  • Interleukin-1 alpha (IL-1 alpha) -1.53 0.218
  • MIP-1 alpha Macrophage Inflammatory Protein-1 alpha
  • Apolipoprotein A-II (Apo A-II) -2.37 0.245
  • FSH Follicle-Stimulating Hormone
  • MMP-3 Matrix Metalloproteinase-3
  • Interleukin-10 0.86 0.487
  • MIP-1 beta Macrophage Inflammatory Protein-1 beta 0.78 0.603
  • SHBG Sex Hormone-Binding Globulin
  • Plasminogen Activator Inhibitor 1 (PAI-1) -1.01 0.648
  • CRP C-Reactive Protein
  • Vascular Cell Adhesion Molecule-1 (VCAM-1) -0.78 0.754
  • Glutathione S-Transferase alpha 0.02 0.973
  • EGF Epidermal Growth Factor
  • TFR2 Tumor necrosis factor receptor 2
  • MMP-2 Matrix Metalloproteinase-2 (MMP-2) NA NA
  • CTGF Connective Tissue Growth Factor
  • EGF Epidermal Growth Factor
  • MIF Macrophage Migration Inhibitory Factor
  • MIP-1 alpha Macrophage Inflammatory Protein-1 alpha
  • FSH Follicle-Stimulating Hormone
  • vWF von Willebrand Factor
  • MIP-1 beta Macrophage Inflammatory Protein-1 beta 7.86 0.028
  • CTGF Connective Tissue Growth Factor
  • Luteinizing Hormone (LH) 4.56 0.030
  • Immunoglobulin A (IgA) 3.91 0.038
  • Interleukin-1 alpha (IL-1 alpha) 2.55 0.045
  • Angiotensin-Converting Enzyme (ACE) -7.29 0.046
  • Trefoil Factor 3 (TFF3) -4.28 0.053
  • Interleukin-16 7.09 0.062
  • FAS FASLG Receptor
  • Apolipoprotein A-I (Apo A-I) -7.05 0.089
  • MCP-1 Monocyte Chemotactic Protein 1
  • Apolipoprotein C-III (Apo C-III) -5.44 0.098
  • GRO-alpha Growth-Regulated alpha protein
  • SHBG Sex Hormone-Binding Globulin
  • MMP-3 Matrix Metalloproteinase-3
  • Vascular Cell Adhesion Molecule-1 (VCAM-1) 6.38 0.164
  • EGFR Epidermal Growth Factor Receptor
  • Interleukin-8 (IL-8) -2.76 0.167
  • Apolipoprotein A-II (Apo A-II) -5.59 0.167
  • Interleukin-10 3.00 0.170
  • CRP C-Reactive Protein
  • PAI-1 Plasminogen Activator Inhibitor 1
  • Interleukin-7 1.12 0.222
  • NGAL Neutrophil Gelatinase-Associated Lipocalin
  • SCF Stem Cell Factor
  • Serum Amyloid P-Component (SAP) 2.45 0.282
  • IGFBP-2 Insulin-like Growth Factor-Binding Protein 2
  • ICM-1 Intercellular Adhesion Molecule 1
  • Apolipoprotein H (Apo H) 3.96 0.405
  • TNF-Related Apoptosis-Inducing Ligand Receptor 3 (TRAIL- 1.58 0.408 R3)
  • CD 40 antigen (CD40) 3.85 0.420
  • Interleukin-3 IL-3 -1.51 0.464
  • Apolipoprotein D (Apo D) 2.42 0.490
  • MMP-2 Matrix Metalloproteinase-2 0.78 0.525
  • Thrombospondin-1 1.89 0.548
  • VEGF Vascular Endothelial Growth Factor
  • Alpha-l-Microglobulin (AlMicro) 1.78 0.593
  • MPO Myeloperoxidase
  • Interleukin-13 (IL-13) -0.36 0.769
  • Interleukin-18 0.75 0.805
  • MCP-4 Monocyte Chemotactic Protein 4 0.72 0.809
  • Alpha-2-Macroglobulin (A2Macro) -0.91 0.823
  • Glutathione S-Transferase alpha (GST-alpha) -0.15 0.901
  • IP-10 Interferon gamma Induced Protein 10
  • HGF Hepatocyte Growth Factor
  • Interleukin-5 (IL-5) NA NA N-(Interleukin-5) NA NA
  • Interferon gamma IFN-gamma
  • TNFR2 Tumor necrosis factor receptor 2
  • Fatty Acid-Binding Protein, adipocyte (FABP, adipocyte) 2.68 1.69E-04
  • MMP-10 Matrix Metalloproteinase-10
  • Apolipoprotein A-I (Apo A-I) 4.82 0.002
  • HGF Hepatocyte Growth Factor
  • EGF Epidermal Growth Factor
  • Chromogranin-A (CgA) 1.58 0.006
  • Apolipoprotein H (Apo H) 3.08 0.008
  • Fibulin-lC (Fib-lC) 3.02 0.012
  • Interleukin-6 receptor subunit beta (IL-6R beta) 5.56 0.012
  • Plasminogen Activator Inhibitor 1 (PAI-1) -2.76 0.019
  • TTR Transthyretin
  • MSP Macrophage-Stimulating Protein
  • BAFF B cell-activating factor
  • Apolipoprotein C-I (Apo C-I) 2.98 0.038
  • VKDPS Vitamin K-Dependent Protein S
  • Apolipoprotein A-II (Apo A-II) 2.48 0.059
  • Serum Amyloid P-Component (SAP) 1.90 0.069
  • Tyrosine kinase with Ig and EGF homology domains 2 TIE- -2.24 0.072 2
  • IGFBP6 Insulin-like Growth Factor Binding Protein 6
  • Interleukin-2 receptor alpha (IL-2 receptor alpha) 1.73 0.090
  • Apolipoprotein A-IV (Apo A-IV) 1.55 0.095
  • IGFBP4 Insulin-like Growth Factor Binding Protein 4
  • Apolipoprotein C-III (Apo C-III) 1.54 0.098
  • Urokinase-type plasminogen activator receptor (uPAR) 1.16 0.104
  • IP-10 Interferon gamma Induced Protein 10
  • Interleukin-18 (IL-18) -1.17 0.109
  • Urokinase-type Plasminogen Activator (uPA) 1.44 0.115
  • IGFBP-2 Insulin-like Growth Factor-Binding Protein 2
  • FSH Follicle-Stimulating Hormone
  • Latency-Associated Peptide of Transforming Growth Factor -1.33 0.135 beta 1 (LAP TGF-bl)
  • VEGF Vascular Endothelial Growth Factor
  • N-terminal prohormone of brain natriuretic peptide (NT -0.44 0.175 proBNP)
  • IGFBP-1 Insulin-like Growth Factor-Binding Protein 1
  • Macrophage inflammatory protein 3 beta (MIP-3 beta) 1.05 0.213
  • Interleukin-16 IL-16 -1.04 0.214 Prolactin (PRL) 0.78 0.226 von Willebrand Factor (vWF) 0.88 0.234
  • Osteoprotegerin (OPG) 1.31 0.236
  • VCAM-1 Vascular Cell Adhesion Molecule-1
  • Immunoglobulin M 0.75 0.249
  • TNF RI Tumor Necrosis Factor Receptor I
  • Thyroid-Stimulating Hormone (TSH) -0.50 0.294
  • BDNF Brain-Derived Neurotrophic Factor
  • Interleukin-12 Subunit p40 (IL-12p40) 0.94 0.327
  • TFR2 Tumor necrosis factor receptor 2
  • MMP-7 Matrix Metalloproteinase-7
  • VEGF-C Vascular Endothelial Growth Factor C 1.31 0.363
  • HER-2 Human Epidermal Growth Factor Receptor 2 (HER-2) -0.89 0.381
  • M-CSF Macrophage Colony-Stimulating Factor 1
  • Platelet-Derived Growth Factor BB (PDGF-BB) -0.61 0.415
  • Immunoglobulin A 0.50 0.434
  • MIP-1 beta Macrophage Inflammatory Protein-1 beta
  • Vascular endothelial growth factor receptor 3 (VEGFR-3) -0.49 0.466
  • MPIF-1 Myeloid Progenitor Inhibitory Factor 1
  • MMP-3 Matrix Metalloproteinase-3
  • TNF-Related Apoptosis-Inducing Ligand Receptor 3 (TRAIL- 0.51 0.506 R3)
  • Neuronal Cell Adhesion Molecule (Nr-CAM) -0.43 0.511
  • IGFBP-3 Insulin-like Growth Factor-Binding Protein 3
  • SHBG Sex Hormone-Binding Globulin
  • Alpha-2-Macroglobulin (A2Macro) 0.66 0.560
  • Interleukin-1 receptor antagonist (IL-lra) -0.58 0.573
  • MMP-1 Matrix Metalloproteinase-1
  • Vascular Endothelial Growth Factor Receptor 2 (VEGFR-2) -0.69 0.603
  • Apolipoprotein E (Apo E) -0.36 0.611
  • Chemokine CC-4 HCC-4 0.30 0.619 Neuropilin-1 0.74 0.622
  • Tissue Inhibitor of Metalloproteinases 1 (TIMP-1) -0.71 0.630
  • HGF receptor Hepatocyte Growth Factor receptor 0.57 0.650
  • MCP-2 Monocyte Chemotactic Protein 2
  • CRP C-Reactive Protein
  • SCF Stem Cell Factor
  • IGFBP5 Insulin-like Growth Factor Binding Protein 5
  • NGAL Neutrophil Gelatinase-Associated Lipocalin
  • MCP-4 Monocyte Chemotactic Protein 4
  • Angiotensin-Converting Enzyme (ACE) -0.33 0.738
  • Interleukin-8 0.22 0.748
  • Trefoil Factor 3 (TFF3) -0.12 0.749
  • GRO-alpha Growth-Regulated alpha protein
  • MPO Myeloperoxidase
  • PSAT Phosphoserine Aminotransferase
  • Interleukin-23 (IL-23) -0.20 0.852
  • CEA Carcinoembryonic Antigen
  • EGFR Epidermal Growth Factor Receptor
  • MCP-1 Monocyte Chemotactic Protein 1 0.10 0.888
  • Angiopoietin-2 (ANG-2) -0.04 0.951
  • VDBP Vitamin D-Binding Protein
  • Thrombospondin-1 0.00 0.999
  • EGF Epidermal Growth Factor
  • Apolipoprotein H (Apo H) 3.56 3.10E-04
  • N-terminal prohormone of brain natriuretic peptide (NT -1.01 4.18E-04 proBNP)
  • MCP-4 Monocyte Chemotactic Protein 4
  • Alpha-l-Microglobulin (AlMicro) 4.38 0.001
  • IGFBP4 Insulin-like Growth Factor Binding Protein 4
  • Fatty Acid-Binding Protein, adipocyte (FABP, adipocyte) 1.47 0.008
  • Fibulin-lC (Fib-lC) 2.78 0.009
  • BDNF Brain-Derived Neurotrophic Factor
  • MCP-2 Monocyte Chemotactic Protein 2
  • Plasminogen Activator Inhibitor 1 (PAI-1) -2.38 0.019
  • HGF receptor Hepatocyte Growth Factor receptor

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  • Life Sciences & Earth Sciences (AREA)
  • Health & Medical Sciences (AREA)
  • Engineering & Computer Science (AREA)
  • Molecular Biology (AREA)
  • Chemical & Material Sciences (AREA)
  • Biomedical Technology (AREA)
  • Urology & Nephrology (AREA)
  • Hematology (AREA)
  • Immunology (AREA)
  • Biotechnology (AREA)
  • Analytical Chemistry (AREA)
  • Cell Biology (AREA)
  • Proteomics, Peptides & Aminoacids (AREA)
  • Food Science & Technology (AREA)
  • Medicinal Chemistry (AREA)
  • Physics & Mathematics (AREA)
  • Microbiology (AREA)
  • Biochemistry (AREA)
  • General Health & Medical Sciences (AREA)
  • General Physics & Mathematics (AREA)
  • Pathology (AREA)
  • Investigating Or Analysing Biological Materials (AREA)
  • Measuring Or Testing Involving Enzymes Or Micro-Organisms (AREA)

Abstract

L'invention concerne des biomarqueurs et des méthodes permettant de diagnostiquer ou de surveiller des troubles dépressifs majeurs ou une prédisposition auxdits troubles.
PCT/GB2014/053603 2013-12-05 2014-12-04 Panel de nouveaux biomarqueurs pour dépressions majeures WO2015082927A1 (fr)

Applications Claiming Priority (2)

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GBGB1321474.7A GB201321474D0 (en) 2013-12-05 2013-12-05 Novel biomarkers

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WO2015082927A1 true WO2015082927A1 (fr) 2015-06-11

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Cited By (9)

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BE1026030B1 (nl) * 2018-02-16 2019-09-20 Laboratorium M Nuytinck Bv Bvba Werkwijze voor het detecteren van vermoeidheidssyndromen bij een individu
CN110988351A (zh) * 2019-09-05 2020-04-10 首都医科大学附属北京安定医院 血管细胞黏附分子在制备抑郁症诊断治疗相关产品的用途
CN111551751A (zh) * 2020-04-26 2020-08-18 东南大学 诊断抑郁症的血清蛋白标记物及其应用
CN112649608A (zh) * 2020-12-01 2021-04-13 中国人民解放军军事科学院军事医学研究院 血清中mmp19在焦虑抑郁症中的应用
EP3783362A3 (fr) * 2019-08-22 2021-06-09 Laboratorium M. Nuytinck Biosignatures de stress mental chronique
CN113151506A (zh) * 2021-05-19 2021-07-23 首都医科大学脑重大疾病研究中心(北京脑重大疾病研究院) 动脉粥样硬化相关细胞标记分子及其应用
CN114137214A (zh) * 2021-12-06 2022-03-04 上海市精神卫生中心（上海市心理咨询培训中心） 用于预测应激后精神心理症状发生的免疫检测试剂盒及应用
JP2022133139A (ja) * 2021-03-01 2022-09-13 勝彦 山▲崎▼ 抗うつ薬抵抗性の大うつ病患者を識別するための、データの取得方法およびキット
CN115097143A (zh) * 2022-07-11 2022-09-23 东南大学 外周血血浆总外泌体中维生素d结合蛋白在诊断抑郁症中的应用

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WO2011121362A2 (fr) * 2010-04-01 2011-10-06 Cambridge Enterprise Limited Marqueurs biologiques
WO2012085557A2 (fr) * 2010-12-20 2012-06-28 Cambridge Enterprise Limited Biomarqueurs
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Cited By (15)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
BE1026030B1 (nl) * 2018-02-16 2019-09-20 Laboratorium M Nuytinck Bv Bvba Werkwijze voor het detecteren van vermoeidheidssyndromen bij een individu
EP3783362A3 (fr) * 2019-08-22 2021-06-09 Laboratorium M. Nuytinck Biosignatures de stress mental chronique
CN110988351A (zh) * 2019-09-05 2020-04-10 首都医科大学附属北京安定医院 血管细胞黏附分子在制备抑郁症诊断治疗相关产品的用途
CN110988351B (zh) * 2019-09-05 2023-10-20 首都医科大学附属北京安定医院 血管细胞黏附分子在制备抑郁症诊断治疗相关产品的用途
CN111551751A (zh) * 2020-04-26 2020-08-18 东南大学 诊断抑郁症的血清蛋白标记物及其应用
CN112649608B (zh) * 2020-12-01 2022-05-17 中国人民解放军军事科学院军事医学研究院 血清中mmp19在焦虑抑郁症中的应用
CN112649608A (zh) * 2020-12-01 2021-04-13 中国人民解放军军事科学院军事医学研究院 血清中mmp19在焦虑抑郁症中的应用
JP2022133139A (ja) * 2021-03-01 2022-09-13 勝彦 山▲崎▼ 抗うつ薬抵抗性の大うつ病患者を識別するための、データの取得方法およびキット
JP7432190B2 (ja) 2021-03-01 2024-02-16 勝彦 山▲崎▼ 抗うつ薬抵抗性の大うつ病患者を識別するための、データの取得方法およびキット
CN113151506B (zh) * 2021-05-19 2022-01-14 首都医科大学脑重大疾病研究中心(北京脑重大疾病研究院) 动脉粥样硬化相关细胞标记分子及其应用
CN113151506A (zh) * 2021-05-19 2021-07-23 首都医科大学脑重大疾病研究中心(北京脑重大疾病研究院) 动脉粥样硬化相关细胞标记分子及其应用
CN114137214A (zh) * 2021-12-06 2022-03-04 上海市精神卫生中心（上海市心理咨询培训中心） 用于预测应激后精神心理症状发生的免疫检测试剂盒及应用
CN114137214B (zh) * 2021-12-06 2024-03-01 上海市精神卫生中心（上海市心理咨询培训中心） 用于预测应激后精神心理症状发生的免疫检测试剂盒及应用
CN115097143A (zh) * 2022-07-11 2022-09-23 东南大学 外周血血浆总外泌体中维生素d结合蛋白在诊断抑郁症中的应用
CN115097143B (zh) * 2022-07-11 2023-07-21 东南大学 外周血血浆总外泌体中维生素d结合蛋白在诊断抑郁症中的应用

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