Multiple biomarkers for the diagnosis of depression and uses thereof

Abstract

Disclosed are multiple biomarkers for diagnosing depression and uses thereof. The combination of multiple biomarkers exhibits high AUC values for depression compared to the use of biomarkers alone.

Description

Background of the Invention Technical Field

[0001] This invention relates to a variety of biomarkers for diagnosing depression and their uses, and more specifically, to a combination of biomarkers for diagnosing depression, said combination of biomarkers comprising at least three proteins selected from the group consisting of TNF-α, IFN-γ, BDNF, and leptin; a composition or kit for diagnosing depression, said composition or kit comprising reagents capable of measuring the level of said biomarker protein or the gene encoding said protein; a method for diagnosing depression using said combination of biomarkers; and a method for screening drugs for the prevention or treatment of depression using said combination of biomarkers.

[0002] Description of related technologies

[0003] According to data released by the Ministry of Health and Welfare in 2022, a significant number of suicide victims (88.6%) were diagnosed with or presumed to have mental illness (Ministry of Health and Welfare press release, “Psychological Autopsy of Suicide, Telling the Story of Life through Death,” July 19, 2022). In particular, depressive disorders accounted for the highest proportion across all age groups, at 82.1%. Furthermore, according to official statistics released by the National Health Insurance Service in 2023, the number of people suffering from depression reportedly exceeded one million in 2022, and the prevalence of depressive disorders among adults aged 19 and above was approximately 3.9% for men and 6.1% for women (2022 National Health Statistics, https: / / knhanes.kdca.go.kr / ). The global economic cost of mental illness is projected to reach approximately $16 trillion by 2030, with anxiety disorders and depression estimated to cause approximately $1 trillion in global economic losses annually (Mental Health Infographic, Korea, 2021). However, compared to the prevalence, the proportion of people diagnosed by both professionals and non-professionals who have received counseling is very low, with only one in ten receiving a diagnosis. Between 30% and 50% of people with depression go undetected in primary care settings and therefore do not receive appropriate treatment. Therefore, efforts are needed to identify and treat patients through screening tests so that early diagnosis and treatment of depression can alleviate symptoms, accelerate recovery, and reduce the prevalence and duration of the illness (Korea J Fam Pract. 2012; 2:15-23). Therefore, it is important to recognize that mental health issues are diseases that require treatment in order to promote mental health, and the importance of early detection of depressive disorders and the necessity of establishing screening systems are becoming apparent in order to proactively address depressive disorders, which account for a high proportion of suicide and mental disorder diagnoses (Ministry of Health and Welfare Press Release, “2024 National Mental Health Knowledge and Attitude Survey”, July 4, 2024).

[0004] According to reports, as suicide has become a national problem, the governments of Japan and Australia have reduced suicide risk factors by developing national policies for suicide prevention, expanding mental health services, and providing psychological support ("Developing aroadmap for the translation of e-mental health services for depression," Sage Journal, Vol. 49, No. 9, 2015; "The Development, Progress, and Impact of National Suicide Prevention Strategies Worldwide," Practice and Policy Insights, Vol. 45, No. 4, July 2024).

[0005] In particular, identifying early symptoms of depressive disorders and high-risk groups, and providing timely professional support, can improve overall mental health. To enhance these positive effects, highly accurate and convenient diagnostic methods are needed.

[0006] Furthermore, current diagnoses of depressive disorders primarily rely on psychological questionnaires and interviews, which are based on self-reporting and prone to bias and error. Therefore, to overcome this limitation, it is necessary to improve the objectivity of diagnosis by incorporating biomarkers, similar to methods used for other physical illnesses.

[0007] It has been revealed that the causes of depressive disorders are related to factors such as genetic predisposition, endocrine disorders, stress, personality traits, and imbalances in neurotransmitters in the body. Only by using neurotransmitters secreted in the bloodstream during diagnosis can depressive disorders be detected in their early stages through blood analysis.

[0008] Compared to diagnoses relying solely on clinician experience, diagnostic methods using quantitative biomarkers in the blood can increase patient reliability. Furthermore, even after early diagnosis, depression requires regular psychological evaluation and monitoring of treatment progress, which is crucial for assessing treatment effectiveness and adjusting treatment plans according to the patient's condition. In addition, depression is an illness with a high risk of relapse, thus requiring continuous management, and regular psychological assessments are essential for preventing relapse and maintaining the patient's overall mental health. In this regard, using biomarkers for tracking can be simple and effective.

[0009] Biomarkers are measurable substances that serve as objective indicators of normal biological processes, disease course, or pharmacological responses to treatment, and are closely related to the etiology or progression of specific diseases. The levels of these biomarkers vary continuously depending on an individual's genetic factors and living environment. Although numerous studies have reported hundreds of putative biomarkers for depression, the roles of these biomarkers in depressive disorders are not fully elucidated, nor are the patients in which these biomarkers are abnormal. Furthermore, no methods have been established to use bioinformatics to improve the diagnosis, treatment, and prognosis of depressive disorders. This lack of progress is partly due to the nature and heterogeneity of depression, methodological heterogeneity in the research literature, and the fact that the expression of various potential biomarkers often depends on multiple factors (Neuropsychiatric Disease and Treatment 2017:13 1245-1262). In this regard, the accuracy of diagnosis using a single biomarker is limited, and the development of in vitro diagnostic multivariate index assays (IVDMIA) using reproducible analytical methods is necessary for discovering biomarkers for the early diagnosis of depressive disorders. In particular, research on protein biomarkers can provide information on titer changes caused by alternative splicing, post-translational modifications, and protein-protein interactions, and can effectively represent the diversity and dynamic changes in disease states. Based on this, the protein biomarker industry in personalized medicine is a promising area for continued growth.

[0010] Based on this background knowledge, the inventors have made extensive efforts to develop a combination of multiple biomarkers that can diagnose depression with high accuracy in a simple manner. As a result, it was found that when the levels of various biomarkers, including brain-derived neurotrophic factor (BDNF), interferon-γ (IFN-γ), leptin, and tumor necrosis factor-α (TNF-α), are measured and then analyzed using an algorithm, the reliability of the diagnosis can be improved and accurate predictions can be achieved compared with using a single biomarker, thus completing the present invention.

[0011] The information disclosed in this background section is only intended to enhance the understanding of the background technology of this invention. Therefore, it may not contain information constituting conventional technology known in the art to which this invention pertains. Summary of the Invention

[0012] The purpose of this invention is to provide biomarkers and combinations thereof that can diagnose depression with high specificity and sensitivity.

[0013] Another object of the present invention is to provide the use of the said biomarkers and combinations thereof for the diagnosis of depression.

[0014] Another object of the present invention is to provide a composition for diagnosing depression, comprising reagents capable of measuring the levels of biomarkers, which are capable of diagnosing depression with high specificity and sensitivity.

[0015] Another object of the present invention is to provide a kit for diagnosing depression, comprising reagents capable of measuring the levels of biomarkers, which can diagnose depression with high specificity and sensitivity.

[0016] Another object of the present invention is to provide a method for diagnosing depression using reagents capable of measuring the levels of biomarkers, which can diagnose depression with high specificity and sensitivity.

[0017] Another object of the present invention is to provide the use of reagent preparations for diagnosing depression that can measure biomarker levels, and which can diagnose depression with high specificity and sensitivity.

[0018] To achieve the above objectives, the present invention also provides a composition for diagnosing depression, comprising a reagent capable of measuring the levels of at least three proteins selected from the group consisting of TNF-α, IFN-γ, BDNF and leptin, or the expression level of a gene encoding said proteins.

[0019] The present invention also provides a kit for diagnosing depression, comprising reagents capable of measuring the levels of at least three proteins selected from the group consisting of TNF-α, IFN-γ, BDNF and leptin, or the expression levels of genes encoding said proteins.

[0020] The present invention also provides a reagent capable of measuring the levels of at least three proteins selected from the group consisting of TNF-α, IFN-γ, BDNF and leptin, or the expression levels of genes encoding said proteins, for the purpose of diagnosing depression.

[0021] The present invention provides the use of reagents capable of measuring the levels of at least three proteins selected from the group consisting of TNF-α, IFN-γ, BDNF and leptin, or the expression levels of genes encoding said proteins, for the preparation of compositions or kits for the diagnosis of depression.

[0022] This invention provides a combination of biomarkers for diagnosing depression, comprising at least three selected from the group consisting of TNF-α, IFN-γ, BDNF, and leptin.

[0023] This invention provides the use of a combination of at least three biomarkers selected from the group consisting of TNF-α, IFN-γ, BDNF and leptin for the diagnosis of depression.

[0024] The present invention provides the use of a combination of at least three biomarkers selected from the group consisting of TNF-α, IFN-γ, BDNF and leptin for the preparation of a composition or kit for the diagnosis of depression.

[0025] The present invention also provides a method for providing information for the diagnosis of depression, the method comprising the steps of: (a) measuring the levels of at least three proteins selected from the group consisting of TNF-α, IFN-γ, BDNF and leptin, or the expression levels of genes encoding said proteins, in a sample isolated from a subject; and (b) comparing the levels of said proteins or the expression levels of genes encoding said proteins with corresponding levels in a control group.

[0026] The present invention also provides a method for screening drugs for the prevention or treatment of depression, comprising the steps of: (a) treating a sample isolated from a depressed subject or an animal model of depression with a candidate drug; and (b) in the depressed sample or animal model treated with said candidate drug, measuring the levels of at least two proteins selected from the group consisting of TNF-α, IFN-γ, BDNF and leptin, or the expression level of a gene encoding said protein. Attached Figure Description

[0027] Figure 1 Box plots comparing the levels of TNF-α, IFN-γ, BDNF, and leptin in patients with major depressive disorder and healthy controls are shown.

[0028] Figure 2 The diagnostic capability of each of the single biomarkers (TNF-α, IFN-γ, BDNF, and leptin) in healthy control subjects and patients with major depressive disorder is illustrated.

[0029] Figure 3 The diagnostic capability of combinations of two biomarkers selected from TNF-α, IFN-γ, BDNF and leptin in healthy control subjects and patients with major depressive disorder is shown (from left: TNF-α and leptin; TNF-α and IFN-γ; TNF-α and BDNF; leptin and IFN-γ; leptin and BDNF; and IFN-γ and BDNF).

[0030] Figure 4 The diagnostic capability of combinations of three biomarkers selected from TNF-α, IFN-γ, BDNF and leptin in healthy control subjects and patients with major depressive disorder is shown (from left: TNF-α and leptin and IFN-γ, TNF-α and leptin and BDNF, TNF-α and IFN-γ and BDNF, and leptin and IFN-γ and BDNF).

[0031] Figure 5Box plots show the comparison of risk values ​​calculated using combinations of four different biomarkers in healthy control subjects and patients with major depressive disorder, as well as the diagnostic power of the combinations of biomarkers. Detailed Implementation

[0032] Unless otherwise defined, all technical and scientific terms used in this specification have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure pertains. Generally, the terms used in this specification are those well-known and commonly used in the art.

[0033] In one embodiment of the invention, serum proteins in serum samples from healthy control subjects and patients with depression were quantitatively analyzed, and biomarkers capable of effectively diagnosing patients with depression were identified. Furthermore, statistical analysis of combinations of identified biomarker candidates confirmed that, in particular, the use of combinations of at least two biomarkers selected from the group consisting of TNF-α, IFN-γ, BDNF, and leptin could diagnose depression with high sensitivity and specificity.

[0034] Biomarkers for diagnosing depression

[0035] Therefore, in one aspect, the present invention relates to biomarkers or combinations thereof for the diagnosis of depression, comprising at least three selected from the group consisting of TNF-α, IFN-γ, BDNF and leptin.

[0036] In this invention, the biomarker or combination thereof may include at least three selected from TNF-α, IFN-γ, BDNF and leptin; more preferably, it may include TNF-α, IFN-γ and BDNF, or include TNF-α, IFN-γ and leptin; most preferably, it may include TNF-α, IFN-γ, BDNF and leptin.

[0037] In this invention, in addition to at least three of the above-mentioned TNF-α, IFN-γ, BDNF and leptin, the biomarkers or combinations thereof may also include various biomarkers known in the art as markers of depression.

[0038] On the other hand, the present invention relates to the use of a combination of at least three of the group consisting of TNF-α, IFN-γ, BDNF and leptin for the diagnosis of depression.

[0039] In this invention, the biomarker can be a protein biomarker or a genetic biomarker.

[0040] Composition for diagnosing depression

[0041] In another aspect, the present invention relates to compositions for diagnosing depression, comprising reagents capable of measuring the levels of at least three proteins selected from the group consisting of TNF-α, IFN-γ, BDNF and leptin, or the expression levels of genes encoding said proteins.

[0042] In this invention, the composition for diagnosing depression may include reagents capable of measuring the levels of proteins of TNF-α, IFN-γ, and BDNF or the expression levels of genes encoding said proteins; or may include reagents capable of measuring the levels of proteins of TNF-α, IFN-γ, and leptin or the expression levels of genes encoding these proteins; and most preferably, may include reagents capable of measuring the levels of proteins of TNF-α, IFN-γ, BDNF, and leptin or the expression levels of genes encoding these proteins.

[0043] In this invention, the composition for diagnosing depression may include, in addition to the biomarker proteins for diagnosing depression described above according to the invention, reagents capable of measuring the levels of various biomarker proteins known in the art as markers of depression or the expression levels of genes encoding said biomarker proteins.

[0044] In this invention, the reagent is capable of measuring the protein level of any one of TNF-α, IFN-γ, BDNF, and leptin, or the expression level of the gene encoding it. In this invention, the reagent is capable of measuring the protein level of any two or more of TNF-α, IFN-γ, BDNF, and leptin, or the expression level of the gene encoding it (e.g., a multispecific antibody).

[0045] In this invention, the composition for diagnosing depression may be characterized by comprising a combination of reagents each capable of measuring the protein level of any one of TNF-α, IFN-γ, BDNF and leptin or the expression level of the gene encoding it; or a combination of reagents capable of measuring the protein level of any two or more of TNF-α, IFN-γ, BDNF and leptin or the expression level of the gene encoding it.

[0046] As used in this article, the term "TNF-α (tumor necrosis factor-α)" refers to a cytokine that induces inflammatory responses, particularly acute responses, and is a protein primarily secreted by activated macrophages.

[0047] The gene encoding human TNF-α is located in class III of the major histocompatibility complex (MHC) on chromosome 6, and the representative sequence of human TNF-α can be represented by the amino acid sequence corresponding to UniProt accession number P01375, but is not limited thereto, and may include sequences having at least about 80% homology, preferably at least 85% homology, more preferably at least 90% homology, more preferably at least 95% homology, more preferably at least 97% homology, and most preferably at least 99% homology with said amino acid sequence.

[0048] As used herein, the term "BDNF (brain-derived neurotrophic factor)" is used interchangeably with the term "brain nerve growth factor." BDNF appears to be essential for the molecular mechanisms of synaptic transmission and synaptic plasticity, as well as for the survival and differentiation of neurons in the central nervous system. BDNF is known to bind to its receptor TrkB and activate tyrosine kinases, which are triggers in various intercellular signaling pathways. A representative sequence of human BDNF can be represented by, but is not limited to, the amino acid sequence corresponding to UniProt accession number P23560, and may include sequences having at least about 80% homology, preferably at least 85% homology, more preferably at least 90% homology, more preferably at least 95% homology, more preferably at least 97% homology, and most preferably at least 99% homology with said amino acid sequence.

[0049] As used herein, the term "leptin" is also known as the obesity protein. Leptin plays an important role in energy balance and weight regulation. It has been reported that when released into circulation, leptin binds to LEPR, which is found in many tissues, and exhibits central and peripheral effects, thereby activating several major signaling pathways. The sequence of human leptin can be represented by an amino acid sequence corresponding to UniProt accession number P41159, but is not limited thereto, and may include sequences having at least about 80% homology, preferably at least 85% homology, more preferably at least 90% homology, more preferably at least 95% homology, more preferably at least 97% homology, and most preferably at least 99% homology with said amino acid sequence.

[0050] As used herein, the term "IFN-γ" is used interchangeably with the terms "IFNG," "IFG," "IFI," and "IMD69." IFN-γ is a type II interferon produced by immune cells such as T cells and NK cells. It has been reported to play important roles in antibacterial, antiviral, and antitumor responses, activating effector immune cells and enhancing antigen presentation.

[0051] The sequence of human IFN-γ can be represented by an amino acid sequence corresponding to UniProt accession number P01579, but is not limited thereto, and may include a sequence having at least about 80% homology, preferably at least 85% homology, more preferably at least 90% homology, more preferably at least 95% homology, more preferably at least 97% homology, and most preferably at least 99% homology with said amino acid sequence.

[0052] In this invention, the term "diagnosis" or "in the process of diagnosis" refers to accurately identifying a subject's symptoms in relation to a specific disease or ailment. For example, "identifying a subject's symptoms in relation to a specific disease or ailment" is used broadly to include not only determining susceptibility to a specific disease or ailment and identifying the subject's current illness, but also determining the characteristics of the disease, such as determining the subject's prognosis, identifying a depressive state, determining the stage of depression, or predicting the disease's susceptibility and responsiveness to treatment, and establishing a basis for appropriate treatment based on the patient's disease and symptoms, such as confirming the subject's symptoms to confirm the therapeutic effect of a specific drug, and further, predicting and confirming the relapse of a subject who has been cured of a specific disease or ailment. Preferably, in this invention, the term "diagnosis" refers to confirming whether a disease has progressed or whether there is a possibility of developing the disease.

[0053] As used herein, the term “prognosis” refers to a predicted medical outcome (e.g., long-term survival, disease-free survival, etc.) and includes positive or negative prognoses, wherein negative prognoses include disease progression or mortality, such as relapse, drug resistance, etc., and wherein positive prognoses include disease remission, such as disease-free status, and improvement or stabilization of the disease.

[0054] As used herein, the term “prediction” refers to predicting medical outcomes; for the purposes of this invention, the term refers to predicting the course of a patient diagnosed with depression (progression, improvement or relapse of the disease, or drug resistance).

[0055] In this invention, depression can be major depressive disorder (MDD) or dysthymia disorder. The diagnosis and classification of depression are typically based on clinical judgment and can be performed according to the American Psychiatric Association's Diagnostic and Statistical Manual of Mental Disorders (DSM).

[0056] The composition for diagnosing depression according to the present invention can be used to diagnose depression, major depressive disorder (MDD), and dysthymia disorder, and is preferably used to diagnose major depressive disorder, but is not limited thereto.

[0057] In this invention, the reagents capable of measuring the level of each of the proteins may be selected from any one or more of the following groups: antibodies, oligopeptides, ligands, peptide nucleic acids (PNAs), and aptamers that specifically bind to each of the proteins, but are not limited thereto.

[0058] In this invention, antibodies include all polyclonal antibodies, monoclonal antibodies, and recombinant antibodies, and the term "antibody" refers to a specific protein molecule targeting an antigenic site. Polyclonal antibodies can be prepared by methods well known in the art, which involve injecting a biomarker protein for diagnosing depression as an antigen into an animal, collecting blood from the animal, and separating serum containing the antibody. The polyclonal antibody can be produced by any animal species host, such as goats, rabbits, sheep, monkeys, horses, pigs, cattle, or dogs. Monoclonal antibodies can be prepared using hybridoma methods well known in the art (see Kohler and Milstein (1976) European Journal of Immunology 6:511-519) or phage antibody library techniques (see Clackson et al., Nature, 352:624-628, 1991; Marks et al., J. Mol. Biol., 222:58, 1-597, 1991). Antibodies produced by the above methods can be separated and purified using methods such as gel electrophoresis, dialysis, salt precipitation, ion exchange chromatography, or affinity chromatography. Furthermore, examples of antibodies of the present invention include not only the complete form having two full-length light chains and two full-length heavy chains, but also functional fragments of the antibody molecule. "Functional fragment of the antibody molecule" refers to a fragment having at least antigen-binding function, examples of which include Fab, F(ab'), F(ab')2, and Fv.

[0059] The antibody can be quantitatively analyzed by colorimetric reaction of a secondary antibody conjugated with an enzyme such as alkaline phosphatase (AP) or horseradish peroxidase (HRP) with its substrate, or by using a monoclonal antibody conjugated with an AP or HRP enzyme targeting the protein.

[0060] In this invention, "peptide nucleic acid (PNA)" refers to a synthetically produced DNA or RNA-like polymer having an N-(2-aminoethyl)-glycine backbone linked by peptide bonds. PNA has enhanced binding affinity and increased stability to DNA or RNA, and is therefore used for diagnostic assays.

[0061] In this invention, an "aptamer" can be an oligonucleotide or peptide molecule that specifically binds to a target. In this invention, the aptamer can specifically bind to at least one biomarker protein for diagnosing depression according to this invention.

[0062] In this invention, the reagents capable of measuring the expression level of each gene can be selected from the group consisting of primers, probes, and antisense oligonucleotides that specifically bind to the gene encoding each protein, but are not limited thereto.

[0063] As used herein, the term "primer" refers to a short nucleic acid sequence having a short, free 3' hydroxyl group that can form a base pair with a complementary template and serve as the starting point for replication of the template.

[0064] In this invention, PCR amplification can be performed using the positive and negative primers of the biomarker polynucleotide of this invention, and the prognosis can be predicted based on whether the desired product is produced. The PCR conditions and the lengths of the positive and negative primers can be modified according to conditions known in the art.

[0065] As used herein, the term "probe" refers to a nucleic acid fragment such as RNA or DNA, ranging in length from a few to several hundred nucleotides, that can specifically bind to mRNA. Probes can be labeled to detect the presence or absence of specific mRNAs. Probes can be prepared in the form of oligonucleotide probes, single-stranded DNA probes, double-stranded DNA probes, RNA probes, etc.

[0066] As used in this article, "antisense oligonucleotide (ASO)" refers to a single-stranded oligonucleotide with a nucleotide sequence complementary to the target RNA and capable of inhibiting the expression of the target gene. Antisense nucleotides can be prepared by phosphodiester synthesis and purification.

[0067] In this invention, "measuring protein levels" refers to determining the presence and expression levels of proteins selected from the group consisting of TNF-α, IFN-γ, BDNF, and leptin in biological samples to diagnose diseases according to the invention. These proteins are biomarkers for diagnosing depression according to the invention.

[0068] In this invention, methods for measuring or comparing protein levels include, but are not limited to: Western blotting, enzyme-linked immunosorbent assay (ELISA), lateral flow immunoassay, chemiluminescent immunoassay, immunoturbidimetric assay, radioimmunoassay, radioimmunodiffusion, fluorescent immunoassay, Ouchterlony immunodiffusion, rocket immunoelectrophoresis, tissue immunostaining, immunoprecipitation assay, complete fixation assay, bead-based immunoassay, Luminex xMAP, FACS, protein chip assay, and mass spectrometry.

[0069] In this invention, "measuring the expression level of genes encoding proteins" refers to determining the expression level of genes encoding proteins selected from the group consisting of TNF-α, IFN-γ, BDNF, and leptin in biological samples to diagnose the diseases according to the invention. These proteins are biomarkers for diagnosing depression according to the invention. Gene expression levels can be determined by measuring the mRNA produced during gene expression.

[0070] In this invention, methods for measuring or comparing the expression levels of genes encoding proteins include, but are not limited to: reverse transcription polymerase chain reaction (RT-PCR), RNA blotting, microarray analysis, RNA sequencing (RNA-Seq), RNA in situ hybridization (RNA-ISH), fluorescence in situ hybridization (FISH), NanoString nCounter analysis, droplet digital PCR (ddPCR), etc.

[0071] Kits for diagnosing depression

[0072] In another aspect, the present invention relates to a kit for diagnosing depression, comprising reagents capable of measuring the levels of at least two proteins selected from the group consisting of TNF-α, IFN-γ, BDNF and leptin, or the expression levels of genes encoding said proteins.

[0073] In this invention, a kit for diagnosing depression may include reagents capable of measuring the levels of proteins of TNF-α, IFN-γ, and BDNF or the expression levels of genes encoding said proteins; or reagents capable of measuring the levels of proteins of TNF-α, IFN-γ, and leptin or the expression levels of genes encoding these proteins.

[0074] In this invention, a kit for diagnosing depression may include reagents capable of measuring the levels of proteins of TNF-α, IFN-γ, BDNF, and leptin, or the expression levels of genes encoding said proteins.

[0075] In this invention, the kit for diagnosing depression may include the composition for diagnosing depression according to the invention.

[0076] In this invention, the contents of the reagents capable of measuring protein levels and the reagents capable of measuring gene expression levels described in the composition for diagnosing depression, as well as the contents of the measurement methods, are equally applicable to the kit for diagnosing depression according to the present invention.

[0077] In this invention, the kit for diagnosing depression may include one or more other component compositions, solutions, or devices suitable for the assay method. For example, the kit may be an RT-PCR kit, a DNA microarray kit, a protein microarray kit, a rapid kit, or an SRM (selective reaction monitoring) / MRM (multiple reaction monitoring) kit.

[0078] In addition to specific primers for each marker gene, an RT-PCR kit may also include test tubes or other suitable containers, reaction buffer, deoxynucleotides (dNTPs), enzymes such as Taq polymerase and reverse transcriptase, DNase, RNase inhibitors, DEPC-water, sterile water, etc. Furthermore, it may include gene-specific primer pairs for use as quantitative controls. DNA microarray kits may include substrates with cDNA corresponding to a gene or fragment attached as a probe, and said substrate may include cDNA corresponding to a quantitative structural gene or fragment.

[0079] Furthermore, the kit according to the invention can be a diagnostic kit comprising reagents for measuring protein levels, wherein the reagents for measuring protein levels are preferably proteins-specific antibodies. Therefore, a diagnostic kit comprising reagents for measuring protein levels can be, for example, a kit for detecting diagnostic biomarkers, comprising the essential components necessary for performing an ELISA, and such a kit may also include reagents capable of detecting antibodies that have formed antigen-antibody complexes, such as labeled secondary antibodies, chromophores, enzymes (e.g., antibody-conjugated enzymes) and their substrates. The kit may also include antibodies specific to quantitative control proteins.

[0080] Furthermore, the amount of antigen-antibody complex formed can be quantitatively measured by detecting the signal intensity of the marker. The marker can be selected from, but is not limited to, a group consisting of enzymes, fluorophores, ligands, luminescent materials, microparticles, redox molecules, and radioactive isotopes.

[0081] Selective reaction monitoring (SRM), also known as multiple reaction monitoring (MRM), is a method used in tandem mass spectrometry. It is used for targeted quantitative proteomics analysis. A detailed description of SRM for targeted quantitative proteomics analysis is found in Nature Methods.9(6):555-566.

[0082] Methods used to inform the diagnosis of depression

[0083] In another aspect, the present invention relates to a method for providing information for diagnosing depression, the method comprising the following steps:

[0084] (a) In a sample isolated from a subject, the levels of at least two proteins selected from the group consisting of TNF-α, IFN-γ, BDNF and leptin, or the expression levels of genes encoding said proteins, are measured.

[0085] (b) Compare the level of the protein or the expression level of the gene encoding the protein with the corresponding level in the control group.

[0086] In this invention, the subject can be an animal including a human, preferably a mammal, and more preferably a human.

[0087] In this invention, the sample may be a solid or non-solid sample isolated from a subject to be diagnosed with depression, such as organs, tissues or cells isolated from the subject, or whole blood, white blood cells, peripheral blood mononuclear cells, erythrocyte sedimentation rate (ESR), plasma, serum, sputum, tears, mucus, nasal wash, nasal aspirate, exhaled breath, urine, semen, saliva, peritoneal lavage, ascites, cyst fluid, meningeal fluid, amniotic fluid, glandular fluid, pancreatic juice, lymphatic fluid, pleural fluid, nipple aspirate, bronchial aspirate, synovial fluid, joint aspirate, organ secretions, cells, cell extracts or cerebrospinal fluid, preferably blood, serum or plasma, but not limited thereto.

[0088] In this invention, step (a) may include measuring the level of protein.

[0089] In this invention, the methods for measuring protein levels include, but are not limited to: Western blotting, enzyme-linked immunosorbent assay (ELISA), lateral flow immunoassay, chemiluminescent immunoassay, immunoturbidimetric assay, radioimmunoassay, radioimmunodiffusion, Ouchterlony immunodiffusion, rocket immunoelectrophoresis, tissue immunostaining, immunoprecipitation assay, complete fixation assay, bead-based immunoassay, Luminex xMAP, FACS, protein chip assay, and mass spectrometry, and any known method capable of measuring said protein levels may be used.

[0090] In this invention, step (a) may include measuring the levels of proteins of TNF-α, IFN-γ, and BDNF, or the expression levels of genes encoding said proteins; or measuring the levels of proteins of TNF-α, IFN-γ, and leptin, or the expression levels of genes encoding said proteins. More preferably, step (a) may include measuring the levels of proteins of TNF-α, IFN-γ, BDNF, and leptin, or the expression levels of genes encoding said proteins.

[0091] In this invention, the composition for diagnosing depression, in addition to the biomarker proteins for diagnosing depression described above according to the invention, can also measure the levels of various biomarker proteins known as conventional markers of depression or the expression levels of genes encoding said biomarker proteins.

[0092] In this invention, the levels in the control group in step (b) can be the levels of TNF-α, IFN-γ, BDNF, and leptin proteins in samples isolated from subjects who have never suffered from depression, or the expression levels of genes encoding said proteins.

[0093] In this invention, the level in the control group in step (b) can be provided by direct measurement or by a threshold value that has been previously measured and provided.

[0094] In one embodiment of the invention, in a quantitative protein analysis comparing patients with depression with healthy controls, four differentially expressed proteins (DEPs) showing significant differences in level were identified, and in particular, it was demonstrated that the combination of four biomarkers increased sensitivity and specificity. It has been shown that the biomarkers for diagnosing depression according to the invention, namely TNF-α, IFN-γ, BDNF, and leptin, are increased in patients with depression.

[0095] Therefore, in this invention, the method further includes step (c): if a change in the level of the protein or the expression level of the gene encoding the protein is detected, corresponding to any three or more of the following i) to iv), then a possibility of depression is determined:

[0096] i) Increased levels of the TNF-α protein and / or increased expression levels of the gene encoding the protein;

[0097] ii) Increased levels of the IFN-γ protein and / or increased expression levels of the gene encoding the protein;

[0098] iii) Increased levels of BDNF protein and / or increased expression levels of the gene encoding the protein; and

[0099] iv) Increased levels of leptin protein and / or increased expression levels of the gene encoding the protein.

[0100] In this invention, i) the increase in the level of TNF-α protein and / or the expression level of the gene encoding the protein may be, for example, an increase of about 1.1 times or more compared to the control group, preferably about 1.2 times or more, more preferably about 1.3 times or more, even more preferably about 1.4 times or more, even more preferably about 1.5 times or more, and most preferably about 1.53 times or more.

[0101] In this invention, ii) the increase in the level of IFN-γ protein and / or the expression level of the gene encoding the protein may be, for example, an increase of about 1.1 times or more compared to the control group, preferably about 1.2 times or more, more preferably about 1.3 times or more, even more preferably about 1.4 times or more, even more preferably about 1.5 times or more, and most preferably about 1.53 times or more.

[0102] In this invention, iii) the increase in the level of BDNF protein and / or the expression level of the gene encoding the protein may be, for example, an increase of about 1.1 times or more compared to the control group, preferably about 1.2 times or more, more preferably about 1.3 times or more, even more preferably about 1.4 times or more, even more preferably about 1.5 times or more, and most preferably about 1.53 times or more.

[0103] In this invention, iv) the increase in the level of leptin protein and / or the expression level of the gene encoding the protein may be, for example, an increase of about 1.1 times or more compared to the control group, preferably about 1.2 times or more, more preferably about 1.3 times or more, even more preferably about 1.4 times or more, even more preferably about 1.5 times or more, and most preferably about 1.53 times or more.

[0104] In this invention, preferably, if step (c) detects a change in the level of the protein or the expression level of the gene encoding the protein, corresponding to i) to iii), then the possibility of depression can be determined:

[0105] i) Increased levels of the TNF-α protein and / or increased expression levels of the gene encoding the protein;

[0106] ii) Increased levels of the IFN-γ protein and / or increased expression levels of the gene encoding the protein; and

[0107] iii) Increased levels of BDNF protein and / or increased expression levels of the gene encoding the protein.

[0108] In this invention, preferably, if step (c) detects a change in the level of the protein or the expression level of the gene encoding the protein, corresponding to i), ii), and iv), then the possibility of depression can be determined:

[0109] i) Increased levels of the TNF-α protein and / or increased expression levels of the gene encoding the protein;

[0110] ii) Increased levels of the IFN-γ protein and / or increased expression levels of the gene encoding the protein; and

[0111] iv) Increased levels of leptin protein and / or increased expression levels of the gene encoding the protein.

[0112] In this invention, most preferably, if step (c) detects a change in the level of the protein or the expression level of the gene encoding the protein, corresponding to i) to iv), then the possibility of depression can be determined:

[0113] i) Increased levels of the TNF-α protein and / or increased expression levels of the gene encoding the protein;

[0114] ii) Increased levels of the IFN-γ protein and / or increased expression levels of the gene encoding the protein;

[0115] iii) Increased levels of BDNF protein and / or increased expression levels of the gene encoding the protein; and

[0116] iv) Increased levels of leptin protein and / or increased expression levels of the gene encoding the protein.

[0117] In this invention, the instances of elevated or decreased levels of each protein and / or expression levels of the gene encoding that protein are based on those values ​​determined and verified in 59 human subjects in embodiments of this invention, and those skilled in the art will clearly understand that the elevation or decrease in levels may be different for each individual subject.

[0118] Therefore, the method of the present invention may further include the step of interpreting changes (increases or decreases) in protein levels and / or the expression levels of genes encoding said proteins in order to accurately diagnose depression or provide information for diagnosing depression.

[0119] In this invention, the step of interpreting changes in protein levels and / or the expression levels of genes encoding proteins may include using a predictive or classification model to interpret the changes. In this invention, the predictive or classification model can be trained using known data analysis methods. For example, the predictive or classification model can be trained using methods selected from: linear regression, logistic regression, ridge regression, Lasso regression, Jackknife regression, decision trees, random forests, K-means clustering, cross-validation, artificial neural networks, ensemble learning, Naive Bayes classifiers, collaborative filtering, principal component analysis (PCA), or support vector machines (SVM), preferably random forests or support vector machines, but not limited thereto. In this invention, in addition to known models, the predictive or classification model can also be trained using supervised or unsupervised algorithms newly designed by those skilled in the art based on embodiments of this invention to diagnose depression.

[0120] In one embodiment of the invention, the results of analyzing the level changes of the biomarkers of the invention using statistical analysis of the Cauchit regression model show that when estimates are obtained using a variety of biomarkers of the invention and at least one of Equations 1 to 3 below, patients with depression can be diagnosed with significantly high sensitivity and specificity.

[0121] In this invention, the method may include step (d): calculating an estimate (x) of the probability of being diagnosed with depression by substituting the level of the protein or the expression level of the gene encoding the protein, measured in step (a), into Equation 1 below:

[0122] [Equation 1]

[0123] x = α + {β1 × (TNF-α concentration in the sample)} + {β2 × (IFN-γ concentration in the sample)} + {β3 × (BDNF concentration in the sample)}

[0124] In Equation 1 above, x is the estimated probability of being diagnosed with depression, α is the intercept when the estimated value (x) is 0 (-50≤α≤10), β1 is the regression coefficient representing the weight of TNF-α concentration in the sample (-5≤β1≤20), β2 is the regression coefficient representing the weight of IFN-γ concentration in the sample (-5≤β2≤5), and β3 is the regression coefficient representing the weight of BDNF concentration in the sample (-5≤β3≤10).

[0125] Furthermore, in this invention, the method may include step (d): calculating an estimate (x) of the probability of being diagnosed with depression by substituting the level of the protein measured in step (a) or the expression level of the gene encoding the protein into Equation 2 below:

[0126] [Equation 2]

[0127] x = α + {β1 × (TNF-α concentration in the sample)} + {β2 × (IFN-γ concentration in the sample)} + {β4 × (leptin concentration in the sample)}

[0128] In Equation 2 above, x is the estimated probability of being diagnosed with depression, α is the intercept when the estimated value (x) is 0 (-50≤α≤10), β1 is the regression coefficient representing the weight of TNF-α concentration in the sample (-5≤β1≤20), β2 is the regression coefficient representing the weight of IFN-γ concentration in the sample (-5≤β2≤5), and β4 is the regression coefficient representing the weight of leptin concentration in the sample (-10≤β4≤5).

[0129] Furthermore, in this invention, the method for providing information for diagnosing depression may include step (d): calculating an estimate (x) of the probability of being diagnosed with depression by substituting the level of the protein or the expression level of the gene encoding the protein, measured in step (a), into Equation 3 below:

[0130] [Equation 3]

[0131] x = α + {β1 × (TNF-α concentration in the sample)} + {β2 × (IFN-γ concentration in the sample)} + {β3 × (BDNF concentration in the sample) + {β4 × (leptin concentration in the sample)}

[0132] In Equation 3 above, x is the estimated probability of being diagnosed with depression, α is the intercept when the estimated value (x) is 0 (-50≤α≤10), β1 is the regression coefficient representing the weight of TNF-α concentration in the sample (-5≤β1≤20), β2 is the regression coefficient representing the weight of IFN-γ concentration in the sample (-5≤β2≤5), β3 is the regression coefficient representing the weight of BDNF concentration in the sample (-5≤β3≤10), and β4 is the regression coefficient representing the weight of leptin concentration in the sample (-10≤β4≤5).

[0133] In this invention, the method may further include the following steps: determining an estimated value x of the probability of being diagnosed with depression calculated by step (d), wherein the closer x is to -∞, the higher the probability of being diagnosed with depression, and the closer the estimated value x is to ∞, the higher the probability of being diagnosed with bipolar disorder.

[0134] The results showed that by using the depression biomarker protein of the present invention to perform the above series of processes, an indicator of whether a particular individual will be diagnosed with depression can be provided.

[0135] It will be apparent to those skilled in the art that the biomarker protein for diagnosing depression according to the present invention can be used to diagnose whether a subject has depression, and based on this, the biomarker protein can also be used to determine whether the depression of a patient who has been diagnosed with depression has been improved or treated, and based on this, the biomarker protein can be used to screen for drugs for the prevention or treatment of depression.

[0136] Therefore, in another aspect, the present invention relates to a method for screening drugs for the prevention or treatment of depression, comprising the steps of: (a) treating a sample isolated from a depressed subject or an animal model of depression with a candidate drug; and (b) in the depressed sample or animal model treated with said candidate drug, measuring the levels of at least three proteins selected from the group consisting of TNF-α, IFN-γ, BDNF and leptin, or the expression levels of genes encoding said proteins.

[0137] The above description of methods for diagnosing depression and / or methods for providing information for diagnosing depression in this specification can also be applied to methods for screening drugs for the prevention or treatment of depression according to the present invention.

[0138] The present invention will be described in detail below by way of embodiments to aid in understanding it. However, embodiments of the present invention can be modified in various different forms, and the scope of the invention should not be construed as limited to the following embodiments.

[0139] Example

[0140] Example 1: Material Preparation and Experimental Methods

[0141] Example 1-1 Blood Sample Collection

[0142] Serum samples were used from patients with major depressive disorder (N=19) and from healthy controls (N=40). The age distribution of the healthy controls ranged from 21 to 61 years (median: 31 years), and the age distribution of the patients with major depressive disorder ranged from 20 to 56 years (median: 40 years). Among the patients with major depressive disorder, 3 had moderate depression. Serum was obtained by collecting peripheral blood from either healthy controls or patients with major depressive disorder, incubating it at room temperature for one hour, centrifuging to collect the supernatant, and storing it at -80°C until use. Serum samples used were provided by Seoul National University Hospital.

[0143] Example 1-2 Measurement of Proteins in Serum

[0144] Among the protein biomarkers in the serum of patients with major depressive disorder (n=19) and healthy controls (n=40), the concentration of tumor necrosis factor-α (TNF-α) was measured using the Luminex xMAP technique, and the concentrations of other protein biomarkers, leptin, interferon-γ (IFN-γ), and brain-derived neurotrophic factor (BDNF), were measured using enzyme-linked immunosorbent assay (ELISA). TNF-α protein was measured using a human cytokine plate A magnetic bead plate (Millipore). Leptin and IFN-γ proteins were measured using a DuoSet ELISA kit (R&D Systems). BDNF protein was measured using a human BDNF ELISA kit (Abcam). All protein biomarker measurements were performed in 96-well plates according to their respective manufacturers' protocols. For TNF-α measurements, standard material or serum was mixed with the mixing beads in each well of the 96-well plate, incubated on a plate shaker for 2 hours, then treated with the detection antibody, followed by incubation for 1 hour. After treating each well with streptavidin-phycoerythrin and incubating for 30 minutes, the assay was performed using… 200 TMMFI was measured, and the results were analyzed using a 5-parameter curve fitting method. For the measurement of leptin and IFN-γ, each well of a 96-well plate was coated with capture antibody and incubated overnight at 25°C. Standard material or serum was added to each well, followed by incubation for 2 hours. Subsequently, each well was treated with biotin-labeled detection antibody and incubated for 2 hours. Then, streptavidin-horseradish peroxidase was added to each well, followed by incubation at room temperature for 20 minutes. TMB was added to each well to initiate the colorimetric reaction. After 20 minutes, the reaction was terminated with sulfuric acid, and the absorbance was measured at 450 nm using a microplate reader. The results were analyzed using a 4-parameter curve fitting method. For the measurement of BDNF, each well of a 96-well plate was treated with a mixture of antibody containing capture and detection antibodies, followed by incubation at room temperature for 1 hour. TMB was added to each well to initiate the colorimetric reaction. After 10 minutes, the reaction was terminated with sulfuric acid, and the absorbance was measured at 450 nm using a microplate reader. The results were analyzed using a 4-parameter curve fitting method. Information about the kit is shown in Table 1 below.

[0145] [Table 1] Kit information for Luminex xMAP and ELISA for analyzing TNF-α, leptin, IFN-γ and BDNF proteins

[0146]

[0147] Examples 1-3. Statistical Analysis

[0148] The t-test confirmed the significant difference in biomarker expression levels between patients with major depressive disorder and healthy controls. To confirm whether combinations of multiple biomarkers showed significant differences between patients with major depressive disorder and healthy controls, analysis was performed using the R statistical software package (Bioinformatics and Statistical Analysis Methods). Statistical analysis was performed using a Cauchit regression model, and the performance of the biomarker combinations for predicting outcomes was confirmed by the AUC (area under the curve) value of the ROC curve (Receiver Operating Characteristic curve).

[0149] Example 2: Evaluation of diagnostic performance when using a single biomarker

[0150] To identify biomarkers that could aid in the diagnosis of major depressive disorder (MDD) by specifically detecting changes in their levels in the blood of patients with the disorder, serum protein levels were measured in 19 patients with MMD and 40 healthy controls using Luminex xMAP and ELISA techniques. Results showed that patients with MMD had elevated levels of TNF-α, BDNF, leptin, and IFN-γ compared to healthy controls (p<0.000). Box plots of each biomarker are shown below. Figure 1 As shown.

[0151] Single biomarkers showed significant increases in the blood of patients with major depressive disorder, but as a result of evaluating diagnostic capability using single biomarkers, the AUC values ​​shown in the ROC curves for TNF-α, BDNF, leptin, and IFN-γ were 0.7434, 0.6934, 0.5118, and 0.7454, respectively. Figure 2 ).

[0152] Example 3: Evaluation of diagnostic performance when using multiple biomarkers

[0153] Example 3-1 Diagnostic performance evaluation using two biomarkers

[0154] The diagnostic performance of each combination including two of the four selected biomarkers was confirmed using a t-test. The performance of six possible combinations of two biomarkers was evaluated using Cauchit regression analysis (1. TNF-α and leptin, 2. TNF-α and IFN-γ, 3. TNF-α and BDNF, 4. leptin and IFN-γ, 5. leptin and BDNF, and 6. IFN-γ and BDNF). As evaluation results, these combinations showed ROC-AUC values ​​of 0.7408, 0.8184, 0.6711, 0.7776, 0.65, and 0.6961, respectively. Compared to using a single biomarker alone, the inventors identified combinations that showed reduced diagnostic ability and combinations that showed improved diagnostic ability. Figure 3 Among the combinations of two biomarkers, the combination showing the best diagnostic ability was TNF-α and IFN-γ (AUC = 0.8184), while the combinations of leptin and IFN-γ (AUC = 0.7776) and TNF-α and leptin (AUC = 0.7408) also showed high diagnostic ability. The combination of leptin and BDNF (AUC = 0.65) showed the lowest diagnostic ability among the combinations of two biomarkers.

[0155] Example 3-2 Diagnostic performance evaluation using three biomarkers

[0156] The performance of four possible combinations of biomarkers (TNF-α and leptin and IFN-γ, TNF-α and leptin and BDNF, TNF-α and IFN-γ and BDNF, and leptin and IFN-γ and BDNF) was evaluated using Cauchit regression analysis. As a result, these combinations showed ROC-AUC values ​​of 0.8171, 0.6882, 0.8039, and 0.7539, respectively, indicating improved diagnostic ability compared to each individual biomarker. Figure 4(See Table 2). Among the combinations of the three biomarkers, the combination showing the best performance was TNF-α and leptin and IFN-γ (AUC = 0.8171), and the combination of TNF-α and IFN-γ and BDNF (AUC = 0.8039) also showed excellent diagnostic ability. On the other hand, the combination showing the lowest performance was TNF-α and leptin and BDNF (AUC = 0.6882). This confirms that only combinations including either leptin or BDNF exhibit excellent diagnostic ability.

[0157] [Table 2] Specificity and sensitivity of the combination of three biomarkers for major depressive disorder

[0158]

[0159] Example 3-3 Diagnostic performance evaluation using four biomarkers

[0160] The performance of the combination of four biomarkers was evaluated using Cauchit regression analysis. As a result, the combination showed a specificity of 90%, a sensitivity of 74%, and a diagnostic ability AUC of 0.9307. Figure 5 (and Table 3). These results are significantly better than those obtained using each single label.

[0161] [Table 3] Specificity and sensitivity of a combination of four biomarkers for major depressive disorder

[0162] Specificity 95％ 90％ 85％ 80％ 75％ Sensitivity 47％ 74％ 84％ 87％ 90％

[0163] Using quantitative analysis data of four proteins, combinations of multiple biomarkers were screened to identify those with significantly improved diagnostic capabilities compared to individual biomarkers. The regression analysis model of the above equations maximized the effect of the combination of multiple biomarkers by using optimal weights for the variable values ​​of each biomarker. Through the above analysis, it has been clearly demonstrated that combinations of three or more of the biomarkers TNF-α, IFN-γ, BDNF, and leptin according to the present invention can be used as multiple biomarkers with excellent efficiency in diagnosing depression.

[0164] Industrial applicability

[0165] The combination of multiple biomarkers according to the present invention exhibits an AUC value 1.5 times higher for depression than when biomarkers are used alone. By using the combination of multiple biomarkers according to the present invention, depression can be diagnosed simply and effectively, providing useful information for diagnosing depressed patients, adjusting treatment plans, and managing prognosis. Furthermore, by combining the combination of multiple biomarkers with existing techniques for diagnosing and analyzing depression, techniques capable of objectively evaluating depression can be developed, providing objective indicators for depression assessment. Moreover, by combining the combination of multiple biomarkers with existing psychological testing and counseling-based diagnostic methods, more systematic management can be achieved.

[0166] Although the invention has been described in detail with reference to specific features, it will be apparent to those skilled in the art that this description represents only preferred embodiments of the invention and does not limit the scope of the invention. Therefore, the essential scope of the invention will be defined by the appended claims and their equivalents.

Claims

1. A composition or kit for diagnosing depression, comprising reagents capable of measuring the levels of at least three proteins selected from the group consisting of TNF-α, IFN-γ, BDNF, and leptin, or the expression level of a gene encoding said proteins.

2. The composition or kit according to claim 1, comprising reagents capable of measuring the levels of proteins encoding TNF-α, IFN-γ, and BDNF, or the expression levels of genes encoding said proteins; or This includes reagents capable of measuring the levels of proteins of TNF-α, IFN-γ, and leptin, or the expression levels of genes encoding said proteins.

3. The composition or kit according to claim 1, comprising reagents capable of measuring the levels of proteins of TNF-α, IFN-γ, BDNF and leptin or the expression levels of genes encoding said proteins.

4. The composition or kit according to claim 1, wherein, The reagent capable of measuring the level of each of the proteins is selected from any one or more of the following groups: antibodies, oligopeptides, ligands, peptide nucleic acids (PNAs), and aptamers that specifically bind to each of the proteins.

5. The composition or kit according to claim 1, wherein, The reagent capable of measuring the expression level of each of the genes is selected from the group consisting of primers, probes, and antisense oligonucleotides that specifically bind to the genes encoding each of the proteins.

6. The reagents are used to prepare compositions or kits for diagnosing depression. in, The reagent is capable of measuring the levels of at least three proteins selected from the group consisting of TNFα, IFN-γ, BDNF, and leptin, or the expression levels of genes encoding the proteins.

7. A combination of biomarkers for the diagnosis of depression, comprising at least three selected from the group consisting of TNFα, IFN-γ, BDNF and leptin.

8. The biomarker combination according to claim 7, wherein, The biomarker is a protein biomarker or a gene biomarker.

9. Biomarker combinations are used to prepare compositions or kits for diagnosing depression. The combination of biomarkers mentioned herein includes at least three selected from the group consisting of TNFα, IFN-γ, BDNF, and leptin.

10. A method for providing information for diagnosing depression, comprising the following steps: (a) In a sample isolated from a subject, the levels of at least three proteins selected from the group consisting of TNF-α, IFN-γ, BDNF and leptin, or the expression levels of genes encoding said proteins, are measured. (b) Compare the level of the protein or the expression level of the gene encoding the protein with the corresponding level in the control group.

11. The method according to claim 10, wherein, The sample mentioned in step (a) is blood, serum, or plasma.

12. The method according to claim 10, wherein, Step (a) includes measuring the level of the protein by any one or more of the following: Western blotting, enzyme-linked immunosorbent assay (ELISA), lateral flow immunoassay, chemiluminescent immunoassay, immunoturbidimetric assay, radioimmunoassay, radioimmunodiffusion, Ouchterlony immunodiffusion, rocket immunoelectrophoresis, tissue immunostaining, immunoprecipitation assay, complete fixation assay, bead-based immunoassay, Luminex xMAP, FACS, protein chip assay, and mass spectrometry.

13. The method of claim 10, wherein, Step (a) includes measuring the levels of proteins of TNF-α, IFN-γ, and BDNF or the expression levels of genes encoding said proteins; Alternatively, the levels of proteins of TNF-α, IFN-γ, and leptin, or the expression levels of genes encoding these proteins, can be measured.

14. The method of claim 10, wherein, Step (a) includes measuring the protein levels of TNF-α, IFN-γ, BDNF, and leptin, or the expression levels of genes encoding said proteins.

15. The method of claim 10, further comprising step (c): if a change in the level of the protein or the expression level of the gene encoding the protein is detected, corresponding to the following i) to If any three or more of the following are found in iv), then the likelihood of developing depression is determined: i) Increased levels of the TNF-α protein and / or increased expression levels of the gene encoding the protein; ii) Increased levels of the IFN-γ protein and / or increased expression levels of the gene encoding the protein; iii) Increased levels of BDNF proteins and / or increased expression levels of genes encoding said proteins; as well as iv) Increased levels of leptin protein and / or increased expression levels of the gene encoding the protein.

16. The method according to claim 15, wherein, Step (c) includes determining the likelihood of depression if a change in the level of the protein or the expression level of the gene encoding the protein is detected, corresponding to i) through iii) below: i) Increased levels of the TNF-α protein and / or increased expression levels of the gene encoding the protein; ii) Increased levels of the IFN-γ protein and / or increased expression levels of the gene encoding the protein; as well as iii) Increased levels of BDNF protein and / or increased expression levels of the gene encoding the protein.

17. The method according to claim 15, wherein, Step (c) includes detecting a change in the level of the protein or the expression level of the gene encoding the protein, which corresponds to the following i), ii), and iv) then determine the possibility of developing depression: i) Increased levels of the TNF-α protein and / or increased expression levels of the gene encoding the protein; ii) Increased levels of the IFN-γ protein and / or increased expression levels of the gene encoding the protein; and iv) Increased levels of leptin protein and / or increased expression levels of the gene encoding the protein.

18. The method according to claim 15, wherein, Step (c) includes determining the likelihood of depression if a change in the level of the protein or the expression level of the gene encoding the protein is detected, corresponding to i) through iv) below: i) Increased levels of the TNF-α protein and / or increased expression levels of the gene encoding the protein; ii) Increased levels of the IFN-γ protein and / or increased expression levels of the gene encoding the protein; iii) Increased levels of BDNF proteins and / or increased expression levels of genes encoding said proteins; as well as iv) Increased levels of leptin protein and / or increased expression levels of the gene encoding the protein.

19. The method of claim 13, comprising step (d): calculating an estimate (x) of the probability of being diagnosed with depression by substituting the level of the protein measured in step (a) or the expression level of the gene encoding the protein into Equation 1 below: [Equation 1] x = α + {β1 × (TNF-α concentration in the sample)} + {β2 × (IFN-γ concentration in the sample)} + {β3 × (BDNF concentration in the sample)} Where x is the estimated probability of being diagnosed with depression, α is the intercept when the estimated value (x) is 0 (–50≤α≤10), β1 is the regression coefficient representing the weight of TNF-α concentration in the sample (-5≤β1≤20), β2 is the regression coefficient representing the weight of IFN-γ concentration in the sample (-5≤β2≤5), and β3 is the regression coefficient representing the weight of BDNF concentration in the sample (-5≤β3≤10).

20. The method of claim 13, comprising step (d): calculating an estimate (x) of the probability of being diagnosed with depression by substituting the level of the protein measured in step (a) or the expression level of the gene encoding the protein into Equation 2 below: [Equation 2] x = α + {β1 × (TNF-α concentration in the sample)} + {β2 × (IFN-γ concentration in the sample)} + {β4 × (leptin concentration in the sample)} Where x is the estimated probability of being diagnosed with depression, α is the intercept when the estimated value (x) is 0 (–50≤α≤10), β1 is the regression coefficient representing the weight of TNF-α concentration in the sample (-5≤β1≤20), β2 is the regression coefficient representing the weight of IFN-γ concentration in the sample (-5≤β2≤5), and β4 is the regression coefficient representing the weight of leptin concentration in the sample (-10≤β4≤5).

21. The method of claim 14, comprising step (d): calculating an estimate (x) of the probability of being diagnosed with depression by substituting the level of the protein measured in step (a) or the expression level of the gene encoding the protein into Equation 3 below: [Equation 3] x = α + {β1 × (TNF-α concentration in the sample)} + {β2 × (IFN-γ concentration in the sample)} + {β3 × (BDNF concentration in the sample) + {β4 × (leptin concentration in the sample)} Where x is the estimated probability of being diagnosed with depression, α is the intercept when the estimated value (x) is 0 (–50≤α≤10), β1 is the regression coefficient representing the weight of TNF-α concentration in the sample (-5≤β1≤20), β2 is the regression coefficient representing the weight of IFN-γ concentration in the sample (-5≤β2≤5), β3 is the regression coefficient representing the weight of BDNF concentration in the sample (-5≤β3≤10), and β4 is the regression coefficient representing the weight of leptin concentration in the sample (-10≤β4≤5).

22. A method for screening drugs for the prevention or treatment of depression, comprising the following steps: (a) Treating samples isolated from depressed subjects or animal models of depression with a candidate drug; and (b) In the depressed sample or animal model treated with the candidate drug, measure the levels of at least three proteins selected from the group consisting of TNF-α, IFN-γ, BDNF and leptin, or the expression levels of genes encoding the proteins.

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