Multiple biomarkers for diagnosis of depression and uses thereof

Abstract

The present invention relates to multiple biomarkers for the diagnosis of depression and uses thereof, and specifically, to: a combination of biomarkers for the diagnosis of depression, the combination of biomarkers comprising three or more proteins selected from the group consisting of TNF-alpha, IFN-gamma, BDNF, and leptin; a composition or kit for diagnosing depression, the composition comprising an agent capable of measuring the level of the biomarker protein or a gene encoding same; and a method for diagnosing depression or a method for screening a drug for preventing or treating depression, the methods using the combination of biomarkers. A combination of multiple biomarkers according to the present invention exhibits an excellent AUC value for depression compared to the case of using a single biomarker.

Description

Multiple biomarkers for the diagnosis of depression and their uses

[0001] The present invention relates to multiple biomarkers for diagnosing depression and their uses, and to a combination of biomarkers for diagnosing depression comprising three or more proteins selected from the group consisting of TNF-alpha, IFN-gamma, BDNF, and leptin, a composition or kit for diagnosing depression comprising a preparation capable of measuring the level of said biomarker protein or the gene encoding it, and a method for diagnosing depression using said biomarker combination or a method for screening drugs for the prevention or treatment of depression.

[0002]

[0003] According to 2022 data from the Ministry of Health and Welfare, it is estimated that a significant number of suicide victims (88.6%) had been diagnosed with or suffered from psychiatric disorders (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 at 82.1% across all age groups. Furthermore, the number of patients with depression officially exceeded 1 million in 2023 according to statistics compiled by the National Health Insurance Service, and the prevalence of depressive disorders among adults aged 19 and older was reported to be approximately 3.9% for men and 6.1% for women in 2022 (2022 National Health Statistics, https: / knhanes.kdca.go.kr / ). Globally, the economic cost of mental illness is projected to reach approximately $16 trillion by 2030, with anxiety disorders and depression expected to cause an annual global economic loss of about $1 trillion (2021 Lundbeck Korea Mental Health Infographic). However, despite the prevalence rate, the rate of counseling experience is low, with only one in ten people receiving a diagnosis from either a professional or a non-professional. Currently, 30–50% of patients with depression remain undetected in the primary care setting, resulting in a lack of access to appropriate treatment. Therefore, efforts are needed to identify and treat patients through screening to reduce prevalence and duration by alleviating symptoms and accelerating recovery through early diagnosis and treatment of depression (Korean J Fam Pract. 2012;2:15-23). Accordingly, in order to promote the mental health of the public, it is important to recognize mental health issues as diseases requiring treatment, and the importance of early detection of depressive disorders and the need to establish a screening system are emerging for a preemptive response to depressive disorders, which account for a high proportion of suicide rates and diagnoses of mental disorders (Ministry of Health and Welfare press release, 'Announcement of the 2024 National Mental Health Knowledge and Knowledge Survey', July 4, 2024).

[0004] As suicide rates emerged as a national issue, the governments of Japan and Australia established national policies for suicide prevention, and it has been reported that they reduced suicide risk factors by expanding mental health services and providing psychological support (Developing a roadmap for the translation of e-mental health services for depression. Sage Journals Vol.49, Issue 9. 2015; The Development, Progress, and Impact of National Suicide Prevention Strategies Worldwide, Practice and Policy Insights, Vol.45, Issue 4, July 2024). In particular, overall psychological health improvement was achieved through timely professional assistance and support by identifying early symptoms of depressive disorder and high-risk groups; however, there is a need for a diagnostic method that is both accurate and convenient to enhance these positive effects.

[0005] Furthermore, the current diagnosis of depressive disorders is primarily based on psychological questionnaires and interviews; however, since this method is based on self-reporting, it has the disadvantage of being susceptible to bias and errors. Therefore, to address this, it is necessary to enhance the objectivity of the diagnosis by including biological indicators, similar to other physical illnesses. It has been revealed that the causes of depressive disorders are related not only to genetic predisposition, endocrine abnormalities, stress, and personality traits, but also to imbalances in neurotransmitters within the body. By utilizing neurotransmitters secreted into the bloodstream, it is possible to detect depressive disorders early simply by analyzing the blood.

[0006] Diagnostic methods utilizing quantitative biomarkers present in the blood, rather than relying solely on the clinician's experience, can enhance reliability for patients. Furthermore, depression requires regular psychological evaluations and monitoring of treatment progress even after an initial diagnosis; this is crucial for assessing treatment effectiveness and adjusting the treatment plan according to the patient's condition. Additionally, since depression is a disease with a high likelihood of recurrence, continuous management is necessary; regular psychological evaluations are an essential process for preventing relapse and maintaining the patient's overall psychological health. In this regard, tracking methods using biomarkers can be both simple and effective.

[0007] Biomarkers are substances measured to serve as objective indicators of normal biological processes, pathogenesis, or pharmacological responses to treatment, and are closely related to the causes or progression of specific diseases. The levels of these biomarkers continuously change depending on an individual's genetic factors and living environment. Although hundreds of presumed biomarkers for depression have been reported in numerous studies, their roles in depressive disorders have not been fully elucidated, nor have methods been established to identify which patients exhibit abnormalities or to use biological information to improve diagnosis, treatment, and prognosis. This lack of progress is partly attributed to the nature and heterogeneity of depression, methodological heterogeneity within the research literature, the existence of various potential biomarkers, and the fact that their expression often varies depending on multiple factors (Neuropsychiatric Disease and Treatment 2017:13 1245-1262). In this regard, there are limitations to the accuracy of diagnosis using a single biomarker, and the development of in vitro diagnostic multivariate index assays (IVDMIA) utilizing reproducible analytical methods is essential for the discovery of biomarkers for the early diagnosis of depressive disorders. In particular, research on protein biomarkers can provide information on potency changes caused by alternative splicing, post-translational modification, and protein interactions, and can effectively represent the diverse and dynamic changes in disease states. Based on this, the protein biomarker industry for personalized medicine is a field predicted to achieve continuous growth.

[0008] Based on this background knowledge, the inventors made diligent efforts to develop a combination of multiple biomarkers capable of diagnosing depression with high accuracy and simplicity. As a result, they confirmed that by measuring the levels of various biomarkers such as BDNF (Brain-Derived Neurotropic Factor), IFN-gamma (Interferon Gamma), leptin, and TNF-alpha (Tumor Necrosis Factor-alpha) and analyzing them using an algorithm, it is possible to improve diagnostic reliability and make accurate predictions compared to a single biomarker, and thus completed the present invention.

[0009]

[0010] The information described above in the background section is intended solely to enhance understanding of the background of the present invention and may not include information that constitutes prior art already known to those skilled in the art to which the present invention belongs.

[0011]

[0012] Summary of the Invention

[0013] The objective of the present invention is to provide a biomarker capable of diagnosing depression with high specificity and sensitivity, and a combination thereof.

[0014] Another objective of the present invention is to provide the use of the biomarker and combinations thereof for diagnosing depression.

[0015] Another objective of the present invention is to provide a composition for diagnosing depression capable of diagnosing depression with high specificity and sensitivity.

[0016] Another objective of the present invention is to provide a depression diagnostic kit capable of diagnosing depression with high specificity and sensitivity.

[0017] Another objective of the present invention is to provide a method for diagnosing depression capable of diagnosing depression with high specificity and sensitivity.

[0018]

[0019] To achieve the above objective, the present invention provides a biomarker for diagnosing depression or a combination thereof comprising three or more proteins selected from the group consisting of TNF-alpha, IFN-gamma, BDNF, and leptin.

[0020] The present invention also provides a composition for diagnosing depression comprising a preparation capable of measuring the levels of three or more proteins selected from the group consisting of TNF-alpha, IFN-gamma, BDNF, and leptin, or the expression levels of genes encoding them.

[0021] The present invention also provides a kit for diagnosing depression comprising a preparation capable of measuring the levels of three or more proteins selected from the group consisting of TNF-alpha, IFN-gamma, BDNF, and leptin, or the expression levels of genes encoding them.

[0022] The present invention also provides a method for providing information for diagnosing depression, comprising: (a) measuring the level of three or more proteins selected from a group consisting of TNF-alpha, IFN-gamma, BDNF, and leptin isolated from a target, or the expression level of a gene encoding them; and (b) comparing the level of the protein or the expression level of the gene encoding them with a control group.

[0023] The present invention also provides a method for screening drugs for the prevention or treatment of depression, comprising: (a) treating a sample isolated from a subject or an animal model of depression with a candidate drug; and (b) measuring the levels of two or more proteins selected from the group consisting of TNF-alpha, IFN-gamma, BDNF, and leptin, or the expression levels of genes encoding them, in the sample or animal model of depression treated with the candidate drug.

[0024]

[0025] Figure 1 is a box plot comparing the levels of TNF-alpha, IFN-gamma, BDNF, and leptin in normal individuals and patients with major depressive disorder.

[0026] Figure 2 is a graph showing the diagnostic ability of each single biomarker of TNF-alpha, IFN-gamma, BDNF, and leptin in normal people and patients with major depressive disorder.

[0027] Figure 3 shows the diagnostic efficacy of a combination of two biomarkers using TNF-alpha, IFN-gamma, BDNF, and leptin in normal individuals and patients with major depressive disorder (from left: TNF-alpha & leptin, : TNF-alpha & IFN-gamma, : TNF-alpha & BDNF, leptin & IFN-gamma, leptin & BDNF, : IFN-gamma & BDNF).

[0028] Figure 4 shows the diagnostic ability of a combination of three markers using TNF-alpha, IFN-gamma, BDNF, and leptin in normal individuals and patients with major depressive disorder (from left: TNF-alpha & leptin & IFN-gamma, TNF-alpha & leptin & BDNF, TNF-alpha & IFN-gamma & BDNF, and leptin & IFN-gamma & BDNF).

[0029] Figure 5 shows the box plot and diagnostic ability of the risk values ​​of normal individuals and patients with major depressive disorder for four types of multiple biomarkers.

[0030]

[0031] Detailed Description of the Invention and Preferred Embodiments

[0032] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by a skilled expert in the art to which this invention pertains. In general, the nomenclature used herein is well known and commonly used in the art.

[0033]

[0034] In one embodiment of the present invention, through protein analysis of serum samples, the serum proteins of a normal control group and patients with depression were quantitatively analyzed, and biomarkers capable of effectively diagnosing patients with depression were derived. In addition, through statistical analysis of combinations of the derived biomarker candidates, it was confirmed that depression can be diagnosed with high sensitivity and specificity when using combinations of two or more biomarkers selected from a group consisting particularly of TNF-alpha, IFN-gamma, BDNF, and leptin.

[0035] Biomarkers for diagnosing depression

[0036] Accordingly, in one aspect, the present invention relates to a combination of biomarkers for diagnosing depression comprising three or more proteins selected from the group consisting of TNF-alpha, IFN-gamma, BDNF, and leptin.

[0037] The present invention may be characterized by including three or more proteins among TNF-alpha, IFN-gamma, BDNF, and leptin; more preferably including TNF-alpha, IFN-gamma, and BDNF proteins, or including TNF-alpha, IFN-gamma, and leptin proteins; most preferably including TNF-alpha, IFN-gamma, BDNF, and leptin proteins.

[0038] In the present invention, in addition to three or more proteins among the disclosed TNF-alpha, IFN-gamma, BDNF, and leptin, it may be characterized by being composed in combination with various biomarkers known as conventional depression markers.

[0039] In another aspect, the present invention relates to a combination of two or more proteins selected from the group consisting of TNF-alpha, IFN-gamma, BDNF, and leptin for the diagnosis of depression.

[0040]

[0041] Composition for diagnosing depression

[0042] In another aspect, the present invention relates to a composition for diagnosing depression comprising a preparation capable of measuring the levels of three or more proteins selected from the group consisting of TNF-alpha, IFN-gamma, BDNF, and leptin, or the expression levels of genes encoding them.

[0043] In the present invention, the composition for diagnosing depression may be characterized by comprising a preparation capable of measuring protein levels of TNF-alpha, IFN-gamma, and BDNF or expression levels of genes encoding them; comprising a preparation capable of measuring protein levels of TNF-alpha, IFN-gamma, and leptin or expression levels of genes encoding them; most preferably, comprising a preparation capable of measuring protein levels of TNF-alpha, IFN-gamma, BDNF, and leptin or expression levels of genes encoding them.

[0044] In the present invention, the composition for diagnosing depression may be characterized by additionally comprising, in addition to the biomarker protein for diagnosing depression of the present invention disclosed above, a preparation capable of measuring the level of various biomarker proteins known as conventional depression markers or the expression level of genes encoding such proteins.

[0045] The term “TNF-alpha (Tumor Necrosis Factor-alpha)” of the present invention is a cytokine that induces an inflammatory response, particularly an acute response, and is a protein primarily secreted by activated macrophages. The gene encoding human TNF-alpha is located in class III of the major histocompatibility complex (MHC) on chromosome 6, and a representative sequence of human TNF-alpha can be represented as an amino acid sequence corresponding to UniProt Entry: P01375, but is not limited thereto, and may include a sequence having about 80% or more homology, preferably 85% or more homology, more preferably 90% or more homology, even more preferably 95% or more homology, even more preferably 97% or more homology, and most preferably 99% or more homology.

[0046] The term “BDNF (Brain Derived Neurotrophic Factor)” of the present invention may be used interchangeably with the terms brain-derived neurotrophic factor, brain neuronal growth factor, or brain-derived neurotrophic factor. BDNF appears to be essential for the molecular mechanisms of synaptic transmission and synapse plasticity, as well as neuronal survival and differentiation in the central nervous system, and all functions of BDNF are known to act as triggers for various intercellular signaling pathways by binding to its receptor TrkB and activating tyrosine kinases. A representative sequence of human BDNF may be represented as an amino acid sequence corresponding to UniProt Entry: P23560, but is not limited thereto, and may include a sequence having about 80% or more homology, preferably 85% or more homology, more preferably 90% or more homology, even more preferably 95% or more homology, even more preferably 97% or more homology, and most preferably 99% or more homology.

[0047] The term “Leptin” of the present invention is also known as an obesity protein and plays an important role in regulating energy balance and weight control. It has been reported that when released into the circulatory system, it binds to LEPR found in many tissues to exert central and peripheral effects, thereby activating several major signaling pathways. A representative sequence of human leptin may be represented by an amino acid sequence corresponding to UniProt Entry: P41159, 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, even more preferably at least 95% homology, even more preferably at least 97% homology, and most preferably at least 99% homology.

[0048] The term “IFN-gamma (Interferon gamma)” of the present invention may be used interchangeably with the terms IFNG, IFG, IFI, and IMD69 in the same sense. IFN-gamma is a type II interferon produced by immune cells such as T cells and NK cells, which plays an important role in antibacterial, antiviral, and antitumor responses, and has been reported to activate effector immune cells and enhance antigen presentation. Representative sequences of human IFN-gamma may be represented by amino acid sequences corresponding to UniProt Entry: P01579, but are not limited thereto, and may include sequences having at least about 80% homology, preferably at least 85% homology, more preferably at least 90% homology, even more preferably at least 95% homology, even more preferably at least 97% homology, and most preferably at least 99% homology.

[0049] In the present invention, the term “diagnosis” refers to accurately identifying the state of a subject regarding a specific disease or condition. For example, the state of a subject regarding a specific disease or condition is used in a broad sense to include not only the susceptibility to the specific disease or condition and the determination of the disease currently suffered by the subject, but also the identification of disease characteristics such as the subject’s prognosis, identification of a depressive state, determination of the stage of depression, or prediction of the disease’s susceptibility and responsiveness to treatment; obtaining grounds for appropriate treatment based on the patient’s disease and condition, such as verifying the subject’s state to confirm the therapeutic effect of a specific drug; and furthermore, predicting and confirming whether there will be a recurrence in a subject who has been cured of the specific disease or condition. In the present invention, preferably, the diagnosis is to confirm whether a disease has occurred or the possibility of its occurrence.

[0050] In the present invention, the term "prognosis" refers to an expectation regarding medical outcomes (e.g., long-term survival probability, disease-free survival rate, etc.), and includes a positive prognosis or a negative prognosis; the negative prognosis includes disease progression or mortality, such as recurrence or drug resistance, and the positive prognosis includes disease improvement or stabilization, such as a disease-free state.

[0051] In the present invention, the term "prediction" means to estimate or guess in advance regarding medical outcomes, and for the purposes of the present invention, it means to estimate in advance the course of a disease (disease progression, improvement, recurrence, drug resistance) of a patient diagnosed with depression.

[0052] In the present invention, the depression may be characterized as Major Depressive Disorder (MDD) or Dysthymic Disorder. The diagnosis and classification of depression are generally performed based on clinical judgment and may be diagnosed and classified based on the Diagnostic and Statistical Manual of Mental Disorders (DSM) of the American Psychiatric Association.

[0053] The composition for diagnosing depression according to the present invention may be characterized as being used to diagnose depression, major depressive disorder (MDD), and dysthymic disorder, and preferably may be used to diagnose major depressive disorder, but is not limited thereto.

[0054] In claim 1, the preparation capable of measuring the protein level may be one or more selected from the group consisting of antibodies, oligopeptides, ligands, PNA (peptide nucleic acid), and aptamers that specifically bind to each protein, but is not limited thereto.

[0055] In the present invention, the antibody includes all "antibodies," such as polyclonal antibodies, monoclonal antibodies, and recombinant antibodies, and an antibody refers to a specific protein molecule directed toward an antigenic site. Polyclonal antibodies can be produced by a method widely known in the art, which involves injecting the biomarker protein for diagnosing depression according to the present invention as an antigen into an animal and collecting blood from the animal to obtain serum containing antibodies. Such polyclonal antibodies can be produced from any animal species host, such as goats, rabbits, sheep, monkeys, horses, pigs, mice, rats, cattle, and dogs. Monoclonal antibodies can be prepared using hybridoma methods widely known in the art (see Kohler and Milstein (1976) European Journal of Immunology 6:511-519) or phage antibody libraries (Clackson et al, Nature, 352:624-628, 1991; Marks et al, J. Mol. Biol., 222:58, 1-597, 1991). Antibodies prepared by the above methods can be separated and purified using methods such as gel electrophoresis, dialysis, salt precipitation, ion exchange chromatography, and affinity chromatography. In addition, the antibodies of the present invention include not only a complete form having two full-length light chains and two full-length heavy chains, but also functional fragments of the antibody molecule. A functional fragment of the antibody molecule refers to a fragment that possesses at least an antigen-binding function, such as Fab, F(ab'), F(ab') 2, and Fv.

[0056] Quantitative analysis can be performed by using a secondary antibody conjugated with an enzyme such as alkaline phosphatase (AP) or horseradish peroxidase (HRP) and its substrate to produce a color reaction, or by directly using a protein monoclonal antibody conjugated with the AP or HRP enzyme.

[0057] In the present invention, the “PNA (Peptide Nucleic Acid)” is an artificially synthesized polymer similar to DNA or RNA, having an N-(2-aminoethyl)-glycine backbone connected by peptide bonds. PNA has improved binding strength and stability to DNA or RNA and is used in diagnostic analysis.

[0058] In the present invention, the “aptamer” may be an oligonucleotide or peptide molecule and may be characterized by specifically binding to a target. In the present invention, the aptamer may be characterized by specifically binding to one or more of the biomarker proteins for diagnosing depression according to the present invention.

[0059] In the present invention, the preparation capable of measuring the expression level of the gene may be characterized by being selected from the group consisting of primers, probes, and antisense nucleotides that specifically bind to the gene encoding each protein, but is not limited thereto.

[0060] In the present invention, the term "primer" refers to a short nucleic acid sequence having a short free 3' hydroxyl group, capable of forming base pairs with a complementary template, and functioning as a starting point for template replication. In the present invention, a prognosis can be predicted by determining whether a desired product is produced by performing PCR amplification using the sense and antisense primers of the marker polynucleotide of the present invention. The PCR conditions and the lengths of the sense and antisense primers can be modified based on those known in the art.

[0061] In the present invention, the term "probe" refers to a nucleic acid fragment, such as RNA or DNA, ranging from a few bases to hundreds of bases in length, capable of forming a specific binding with mRNA, and is labeled to confirm the presence or absence of a specific mRNA. The probe may be produced in the form of an oligonucleotide probe, a single-stranded DNA probe, a double-stranded DNA probe, an RNA probe, etc.

[0062] In the present invention, the term "antisense oligonucleotide (ASO)" refers to a single-stranded oligonucleotide that has a base sequence complementary to target RNA and performs the function of inhibiting target gene expression. Antisense nucleotides can be produced by synthesizing them through a phosphodiester chemical synthesis method and then purifying them.

[0063] In the present invention, the measurement of the protein level means confirming the presence and expression level of a protein selected from the group consisting of TNF-alpha, IFN-gamma, BDNF, and leptin, which are markers for diagnosing depression in a biological sample in order to diagnose the disease of the present invention.

[0064] In the present invention, methods for measuring or comparing protein levels include, but are not limited to, western blotting, ELISA (enzyme-linked immunosorbent assay), lateral flow immunoassay, chemiluminescent immunoassay, immunoturbidimetric test, radioimmunoassay, radioimmunodiffusion, fluorescence-based immunodetection, Ouchterlony immunodiffusion, Rocket immunoelectrophoresis, tissue immunostaining, immunoprecipitation assay, complete fixation assay, bead-based immunoassay, Luminex xMAP, FACS, protein chip, and mass spectrometry.

[0065] In the present invention, measuring the expression level of the gene encoding the protein means confirming the degree of expression of DNA encoding a protein selected from the group consisting of TNF-alpha, IFN-gamma, BDNF, and leptin, which are markers for diagnosing depression according to the present invention, in order to diagnose the disease of the present invention. The degree of expression of the DNA can be confirmed through the measurement of mRNA generated during DNA expression, etc.

[0066] In the present invention, methods for measuring or comparing the expression level of a protein-coding gene include RT-PCR (Reverse Transcription Polymerase Chain Reaction), Northern Blotting, microarray analysis, RNA-Seq (RNA Sequencing), RNA-ISH (RNA in situ Hybridization), FISH (Fluorescence In Situ Hybridization), NanoString nCounter Analysis, ddPCR (Droplet Digital PCR), but are not limited thereto.

[0067]

[0068] Depression diagnostic kit

[0069] In another aspect, the present invention relates to a kit for diagnosing depression comprising a preparation capable of measuring the levels of two or more proteins selected from the group consisting of TNF-alpha, IFN-gamma, BDNF, and leptin, or the expression levels of genes encoding them.

[0070] In the present invention, the depression diagnostic kit may be characterized by comprising a preparation capable of measuring protein levels of TNF-alpha, IFN-gamma, and BDNF or expression levels of genes encoding them; or comprising a preparation capable of measuring protein levels of TNF-alpha, IFN-gamma, and leptin or expression levels of genes encoding them.

[0071] In the present invention, the depression diagnostic kit may be characterized by comprising a preparation capable of measuring the protein levels of TNF-alpha, IFN-gamma, BDNF, and leptin, or the expression levels of genes encoding them.

[0072] In the present invention, the depression diagnostic kit may be characterized by including the depression diagnostic composition of the present invention.

[0073] In the present invention, the details regarding the preparation capable of measuring the protein level and the preparation capable of measuring the gene expression level described in the composition for diagnosing depression, as well as the details regarding the measurement method, can be equally applied to the kit for diagnosing depression of the present invention.

[0074] In the present invention, the depression diagnostic kit may include one or more other component compositions, solutions, or devices suitable for an analysis method. For example, it may be an RT-PCR kit, a DNA chip kit, a protein chip kit, a rapid kit, or an SRM (selected reaction monitoring) / MRM (multiple reaction monitoring) kit.

[0075] In addition to each primer pair specific to the marker gene, the RT-PCR kit may include a test tube or other suitable container, reaction buffer, deoxynucleotides (dNTPs), enzymes such as Taq-polymerase and reverse transcriptase, DNase, RNase inhibitors, DEPC-water, sterile water, etc. Additionally, it may include a primer pair specific to the gene used as a quantitative control. The DNA chip kit includes a substrate to which cDNA corresponding to a gene or a fragment thereof is attached as a probe, and the substrate may include cDNA corresponding to the gene or a fragment thereof.

[0076] In addition, the kit according to the present invention may be a diagnostic kit comprising a preparation for measuring the protein level, wherein the preparation for measuring the protein level may preferably be an antibody specific to the protein. Accordingly, the diagnostic kit comprising the preparation for measuring the protein level may be, for example, a kit for detecting diagnostic markers that includes essential elements necessary for performing ELISA, and such a kit may include a reagent capable of detecting an antibody that has formed an "antigen-antibody complex," such as a labeled secondary antibody, chromophores, an enzyme (e.g., conjugated with an antibody), and a substrate thereof. In addition, it may include an antibody specific to a quantitative control protein.

[0077] In addition, the amount of the antigen-antibody complex formed can be quantitatively measured through the magnitude of the signal of the detection label. Such a detection label may be selected from the group consisting of enzymes, fluorescent dyes, ligands, luminescent materials, microparticles, redox molecules, and radioisotopes, but is not limited thereto.

[0078] The above-mentioned SRM (selected reaction monitoring) is also referred to as MRM (multiple reaction monitoring) and is a method used in tandem mass spectrometry, and is used for targeted quantitative proteomic analysis. The SRM used for targeted quantitative proteomic analysis is described in detail in Nature Methods. 9 (6): 555-566.

[0079]

[0080] Method of providing information for the diagnosis of depression

[0081] In another aspect, the present invention comprises: (a) measuring the level of two or more proteins selected from the group consisting of TNF-alpha, IFN-gamma, BDNF, and leptin, or the expression level of a gene encoding the same from a sample isolated from a target; and

[0082] (b) A method for providing information for the diagnosis of depression, comprising the step of comparing the protein level or the expression level of the gene encoding it with a control group.

[0083] In the present invention, the subject may be characterized as an animal including a human, preferably a mammal, and more preferably a human.

[0084] In the present invention, the sample may be a solid or non-solid sample separated from a subject to be diagnosed with depression, for example, an organ, tissue, or cell separated from the subject, or whole blood, leukocytes, peripheral blood mononuclear cells, buffy coat, plasma, serum, sputum, tears, mucus, nasal washes, nasal aspirate, breath, urine, semen, saliva, peritoneal washings, ascites, cystic fluid, meningeal fluid, amniotic fluid, glandular fluid, pancreatic fluid, lymph fluid, pleural fluid, nipple aspirate It may be aspirate), bronchial aspirate, synovial fluid, joint aspirate, organ secretions, cell, cell extract, or cerebrospinal fluid, and preferably may be blood, serum, or plasma, but is not limited thereto.

[0085] In the present invention, the above step (a) may be characterized by measuring the protein level.

[0086] In the present invention, methods for measuring the level of the protein include, but are not limited to, western blotting, ELISA (enzyme-linked immunosorbent assay), lateral flow immunoassay, chemiluminescent immunoassay, immunoturbidimetric test, radioimmunoassay, radioimmunodiffusion, Ouchterlony immunodiffusion, Rocket immunoelectrophoresis, tissue immunostaining, immunoprecipitation assay, complete fixation assay, bead-based immunoassay, Luminex xMAP, FACS, protein chip, and mass spectrometry, and any known method capable of measuring the level of the protein.

[0087] In the present invention, the step (a) may preferably be characterized by measuring the protein levels of TNF-alpha, IFN-gamma, and BDNF or the expression levels of genes encoding them; or measuring the protein levels of TNF-alpha, IFN-gamma, and leptin or the expression levels of genes encoding them. More preferably, the step (a) may be characterized by measuring the protein levels of TNF-alpha, IFN-gamma, BDNF, and leptin or the expression levels of genes encoding them.

[0088] In the present invention, the composition for diagnosing depression may be characterized by measuring, in addition to the biomarker protein for diagnosing depression disclosed in the present invention, the level of various biomarker proteins known as conventional depression markers or the expression level of genes encoding them.

[0089] In the present invention, the control group in step (b) may be characterized as having levels of TNF-alpha, IFN-gamma, BDNF, and leptin proteins or expression levels of genes encoding them in a sample isolated from a subject who does not suffer from depression.

[0090] In the present invention, the control group in step (b) may be provided by direct measurement or may be characterized as a reference value that has been previously measured and provided.

[0091] In one embodiment of the present invention, in a quantitative protein analysis comparing patients with depression and a normal control group, four differentially expressed proteins (DEPs) showing a significant difference were identified, and in particular, an increase in sensitivity and specificity through the combination of the four biomarkers was confirmed. It was confirmed that the biomarkers for diagnosing depression according to the present invention—TNF-alpha, IFN-gamma, BDNF, and leptin—were increased in patients with depression.

[0092] Accordingly, in the present invention, the method may further comprise the step of confirming that there is a possibility of developing depression when a change in the expression level of any three or more of the following proteins or the gene encoding them is detected:

[0093] i) Increase in TNF-alpha protein levels and / or expression levels of the gene encoding it;

[0094] ii) Increase in IFN-gamma protein levels and / or the expression levels of genes encoding it;

[0095] iii) an increase in BDNF protein levels and / or the expression levels of the gene encoding it; and

[0096] iv) Increase in leptin protein levels and / or expression levels of the gene encoding it.

[0097] In the present invention, the increase in i) the level of TNF-alpha protein and / or the expression level of the gene encoding it may be characterized by, for example, being increased by 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, more preferably about 1.4 times or more, more preferably about 1.5 times or more, and most preferably about 1.53 times or more.

[0098] In the present invention, the increase in the level of IFN-gamma protein and / or the expression level of the gene encoding it ii) may be characterized by, for example, being increased by 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, more preferably about 1.4 times or more, more preferably about 1.5 times or more, and most preferably about 1.53 times or more.

[0099] In the present invention, the increase in the iii) level of BDNF protein and / or the expression level of the gene encoding it may be characterized by, for example, being increased by 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, more preferably about 1.4 times or more, more preferably about 1.5 times or more, and most preferably about 1.53 times or more.

[0100] In the present invention, the increase in the level of leptin protein and / or the expression level of the gene encoding it iv) may be characterized by, for example, being increased by 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, more preferably about 1.4 times or more, more preferably about 1.5 times or more, and most preferably about 1.53 times or more.

[0101] In the present invention, the step (c) may preferably be characterized by confirming that there is a possibility of developing depression when a change in the expression level of any three or more of the following proteins or the gene encoding them is detected:

[0102] i) Increase in TNF-alpha protein levels and / or expression levels of the gene encoding it;

[0103] ii) an increase in IFN-gamma protein levels and / or the expression levels of genes encoding it; and

[0104] iii) Increase in BDNF protein levels and / or expression levels of the gene encoding it.

[0105] In the present invention, the above step (c) may preferably be characterized by confirming that there is a possibility of developing depression when a change in the expression level of the following protein or the gene encoding it is detected:

[0106] i) Increase in TNF-alpha protein levels and / or expression levels of the gene encoding it;

[0107] ii) an increase in IFN-gamma protein levels and / or the expression levels of genes encoding it; and

[0108] iv) Increase in leptin protein levels and / or expression levels of the gene encoding it.

[0109] In the present invention, the above step (c) is most preferably characterized by confirming that there is a possibility of developing depression when a change in the following protein level or the expression level of the gene encoding it is detected:

[0110] i) Increase in TNF-alpha protein levels and / or expression levels of the gene encoding it;

[0111] ii) Increase in IFN-gamma protein levels and / or the expression levels of genes encoding it;

[0112] iii) an increase in BDNF protein levels and / or the expression levels of the gene encoding it; and

[0113] iv) Increase in leptin protein levels and / or expression levels of the gene encoding it.

[0114] In the present invention, examples of increases or decreases in the expression levels of each protein level and / or the gene encoding it are derived based on values ​​confirmed and verified in 59 human subjects in the embodiments of the present invention, and it will be obvious to a person skilled in the art that the decrease or increase in levels may differ for each individual subject.

[0115] Accordingly, in order to provide accurate diagnosis of depression or information for diagnosis, the present invention may further include a step of interpreting changes (increase or decrease) in the expression level of the protein and / or the gene encoding it.

[0116]

[0117] In the present invention, the step of interpreting changes in the expression level of the protein level and / or the gene encoding it may be characterized by being interpreted by a prediction or classification model. In the present invention, the prediction or classification model may be characterized by being trained by a known data analysis method. For example, the prediction or classification model may be trained using methods such as linear regression, logistic regression, ridge regression, Lasso regression, jackknife regression, decision tree, random forest, K-means clustering, cross-validation, artificial neural network, ensemble learning, naive Bayesian classifier, collaborative filtering, principal component analysis (PCA), and support vector machine (SVM), preferably trained using random forest or support vector machine, but is not limited thereto. In the present invention, the prediction or classification model may be trained by a supervised or unsupervised algorithm newly designed by a person skilled in the art for the diagnosis of depression based on embodiments of the present invention, in addition to known models.

[0118] In one embodiment of the present invention, the change in the level of the biomarker of the present invention was analyzed using a Cauchit regression model statistical analysis, and it was demonstrated that patients with depression can be diagnosed with significantly high sensitivity and specificity when using the multiple biomarker of the present invention and an estimate derived through one or more of Equations 1 to 3.

[0119] In the present invention, the method may include the step of (d) calculating an estimate (x) of the probability of being diagnosed with depression by substituting the protein level or the expression level of the gene encoding it measured through step (a) into the following mathematical formula 1:

[0120] [Mathematical Formula 1]

[0121] x = α + {β1 × (concentration of TNF-alpha in sample)} + {β2 × (concentration of IFN-gamma in sample)} + {β3 × (concentration of BDNF in sample)}

[0122] In the above mathematical formula 1, x is an estimate of the probability of being diagnosed with depression, α is the intercept value when the estimate (x) is 0 (-50 ≤ α ≤ 10), β1 is a regression coefficient representing the weight for the concentration value of TNF-alpha in the sample (-5 ≤ β1 ≤ 20), β2 is a regression coefficient representing the weight for the concentration value of IFN-gamma in the sample (-5 ≤ β2 ≤ 5), and β3 is a regression coefficient representing the weight for the concentration value of BDNF in the sample (-5 ≤ β3 ≤ 10).

[0123] In addition, the present invention may include the step of (d) calculating an estimate (x) of the probability of being diagnosed with depression by substituting the protein level or the expression level of the gene encoding it measured through step (a) into the following mathematical formula 2:

[0124] [Mathematical Formula 2]

[0125] x = α + {β1 × (concentration of TNF-alpha in sample)} + {β2 × (concentration of IFN-gamma in sample)} + β4 × (concentration of leptin in sample)}

[0126] In the above mathematical formula 2, x is an estimate of the probability of being diagnosed with depression, α is the intercept value when the estimate (x) is 0 (-50 ≤ α ≤ 10), β1 is a regression coefficient representing the weight for the concentration value of TNF-alpha in the sample (-5 ≤ β1 ≤ 20), β2 is a regression coefficient representing the weight for the concentration value of IFN-gamma in the sample (-5 ≤ β2 ≤ 5), and β4 is a regression coefficient representing the weight for the concentration value of leptin in the sample (-10 ≤ β4 ≤ 5).

[0127] In addition, the present invention comprises a method for providing information for diagnosing depression, wherein the method includes the step of (d) substituting the protein level or the expression level of the gene encoding it measured through step (a) into the following mathematical formula 3 to calculate an estimate (x) of the probability of being diagnosed with depression:

[0128] [Mathematical Formula 3]

[0129] x = α + {β1 × (concentration of TNF-alpha in sample)} + {β2 × (concentration of IFN-gamma in sample)} + {β3 × (concentration of BDNF in sample)} + {β4 × (concentration of leptin in sample)}

[0130] In the above mathematical formula 3, x is an estimate of the probability of being diagnosed with depression, α is the intercept value when the estimate (x) is 0 (-50 ≤ α ≤ 10), β1 is a regression coefficient representing the weight for the concentration value of TNF-alpha in the sample (-5 ≤ β1 ≤ 20), β2 is a regression coefficient representing the weight for the concentration value of IFN-gamma in the sample (-5 ≤ β2 ≤ 5), β3 is a regression coefficient representing the weight for the concentration value of BDNF in the sample (-5 ≤ β3 ≤ 10), and β4 is a regression coefficient representing the weight for the concentration value of leptin in the sample (-10 ≤ β4 ≤ 5).

[0131] In the present invention, the method may additionally include a step of diagnosing that the closer the estimate x of the probability of being diagnosed with depression calculated through step (d) is to -∞, the higher the probability of being diagnosed with depression, and the closer it is to ∞, the higher the probability of being diagnosed with bipolar disorder.

[0132] Consequently, by using the depression biomarker proteins of the present invention and going through the series of processes described above, it is possible to provide an indicator for whether to diagnose a specific individual with depression.

[0133]

[0134] It is obvious to a person skilled in the art that the biomarker protein for diagnosing depression according to the present invention can be used to diagnose whether a subject is suffering from depression, and based on this, can be utilized to confirm whether depression has improved or been treated in patients already confirmed to have depression, and based on this, can be utilized for screening drugs for the prevention or treatment of depression.

[0135] Accordingly, in another aspect, the present invention relates to a method for screening drugs for the prevention or treatment of depression, comprising: (a) treating a sample isolated from a subject or an animal model of depression with a candidate drug; and (b) measuring the levels of three or more proteins selected from the group consisting of TNF-alpha, IFN-gamma, BDNF, and leptin, or the expression levels of genes encoding them, in the sample or animal model of depression treated with the candidate drug.

[0136] The description in this specification regarding the diagnosis of depression and / or the method for providing information for diagnosis may be equally applied to the screening method for drugs for the prevention or treatment of depression according to the present invention.

[0137]

[0138] Hereinafter, the present invention will be described in detail with reference to examples to aid in understanding. However, the embodiments according to the present invention may be modified in various different forms, and the scope of the present invention should not be interpreted as being limited to the following embodiments.

[0139]

[0140] Examples

[0141] Example 1: Material Preparation and Experimental Method

[0142] Example 1-1. Blood Sample Collection

[0143] Serum from patients with major depressive disorder (19 individuals) and normal individuals (40 individuals) was used. Regarding the age distribution, the normal individuals ranged from 21 to 61 years (median: 31 years), while the patients with major depressive disorder ranged from 20 to 56 years (median: 40 years). Among the patients with major depressive disorder, there were 3 individuals with moderate depression. The serum was obtained by collecting peripheral blood from normal individuals or patients with major depressive disorder, leaving it at room temperature for one hour, centrifuging it, and collecting the supernatant; the samples were stored at -80°C until use. The serum samples were provided by Seoul National University Hospital.

[0144] Example 1-2. Measurement of protein in serum

[0145] The concentration of the protein biomarker TNF-alpha (Tumor Necrosis Factor-alpha) in the serum of patients with major depressive disorder (19 subjects) and healthy individuals (40 subjects) was measured using the Luminex xMAP method, while the concentrations of other protein biomarkers, such as leptin, IFN-gamma (Interferon-gamma), and BDNF (Brain Derived Neurotrophic Factor), were measured using the Enzyme-linked Immunosorbent Assay (ELISA) method. The Millipore MILLIPLEX® Human Cytokine Panel A Magnetic Bead Panel was used for TNF-alpha protein measurement. The R&D Systems Duoset ELISA kit was used for leptin and IFN-gamma protein measurement. The Abcam Human BDNF ELISA kit was used for BDNF protein measurement. All protein biomarkers were measured in 96-well plates according to each manufacturer's protocol. For TNF-alpha, standard substances or serum were mixed with mixing beads in each well of a 96-well plate and incubated using a plate shaker for 2 hours, after which the detection antibody was added and incubated for 1 hour. After incubating with Streptavidin-Phycoerythrin for 30 minutes, the MFI was measured using Luminex® 200™, and the results were analyzed by 5-parameter curve fitting. For Leptin and IFN-gamma, capture antibodies were overnight coated in each well of a 96-well plate at 25°C, and standard substances or serum were added to each well and incubated for 2 hours. Subsequently, biotin-labeled detection antibodies were added and incubated for 2 hours, after which streptavidin-horseradise was added and incubated at room temperature for 20 minutes.TMB was added to induce a color reaction, and after 20 minutes, the reaction was stopped with sulfuric acid. Absorbance was then measured at 450 nm using a microplate reader. The results were analyzed by 4-parameter curve fitting. For BDNF, standard substances or serum were added to each well of a 96-way plate, along with an antibody cocktail containing capture and detection antibodies, and incubated at room temperature for 1 hour. TMB was added to induce a color reaction, and after 10 minutes, the reaction was stopped with sulfuric acid. Absorbance was then measured at 450 nm using a microplate reader. The results were analyzed by 4-parameter curve fitting. Kit information is shown in Table 1 below.

[0146]

[0147] Examples 1-3. Statistical Analysis

[0148] The significance of differences in biomarker expression levels between patients with major depressive disorder and healthy individuals was confirmed using a T-test. To verify whether the combination of multiple biomarkers demonstrated appropriate significance between patients with major depressive disorder and healthy individuals, an analysis was conducted using bioinformatics and the R statistical package. A Cauchit regression model was used for the statistical analysis, and the performance of the prediction results for validating the biomarker combinations was assessed using the Area Under an ROC Curve (ARC).

[0149]

[0150] Example 2: Confirmation of diagnostic performance using a single biomarker

[0151] To select biomarkers that can be usefully employed in the diagnosis of major depressive disorder by showing specific changes in values ​​in the blood of patients with major depressive disorder, protein levels were measured in the serum of 19 patients with major depressive disorder and 40 healthy individuals using Luminex xMAP and ELISA techniques. As a result, TNF-alpha, BDNF, leptin, and IFN-gamma showed an increasing trend in levels in patients with major depressive disorder compared to healthy individuals (p<0.000). The box plots for each biomarker are shown in Figure 1.

[0152] Although single biomarkers show a significant increase in the blood of patients with major depressive disorder, when examining the diagnostic ability using single biomarkers, TNF-alpha, BDNF, leptin, and IFN-gamma showed AUC values ​​of 0.7434, 0.6934, 0.5118, and 0.7454, respectively, on the ROC curve (Fig. 2).

[0153]

[0154] Example 3: Confirmation of diagnostic performance when using multiple biomarkers

[0155] Example 3-1. Confirmation of diagnostic performance when using dual biomarkers

[0156] The diagnostic performance of each of the various combinations containing four biomarkers selected via T-test was verified. The performance of six derivable combinations of two markers (1. TNF-alpha & leptin, 2. TNF-alpha & IFN-gamma, 3. TNF-alpha & BDNF, 4. Leptin & IFN-gamma, 5. Leptin & BDNF, 6. IFN-gamma & BDNF) was evaluated using Cougite regression analysis. The results showed that each combination exhibited ROC AUC values ​​of 0.7408, 0.8184, 0.6711, 0.7776, 0.65, and 0.6961, respectively. Combinations showing reduced diagnostic ability and combinations showing improved diagnostic ability compared to the case using a single biomarker were identified (Fig. 3). Among the combinations of two biomarkers, the combination showing the best diagnostic ability was TNF-alpha & IFN-gamma (AUC=0.8184), and the combinations of leptin & IFN-gamma (AUC=0.7776) and TNF-alpha & leptin (AUC=0.7408) also showed high diagnostic ability. The leptin & BDNF (AUC=0.65) combination showed the lowest diagnostic ability among the two-marker combinations.

[0157]

[0158] Example 3-2. Confirmation of diagnostic performance when using triple biomarkers

[0159] The performance of four derivable combinations of three biomarkers (TNF-alpha & leptin & IFN-gamma, TNF-alpha & leptin & BDNF, TNF-alpha & IFN-gamma & BDNF, and leptin & IFN-gamma & BDNF) was evaluated using Cougite regression analysis. The results showed that each combination exhibited ROC AUC values ​​of 0.8171, 0.6882, 0.8039, and 0.7539, confirming that all combinations demonstrated improved diagnostic efficacy compared to the diagnostic efficacy of each individual biomarker (Fig. 4, Table 2). Among the combinations of three biomarkers, the combination showing the best performance was TNF-alpha & leptin & IFN-gamma (AUC=0.8171), and TNF-alpha & IFN-gamma & BDNF (AUC=0.8039) also demonstrated excellent diagnostic efficacy. On the other hand, the combination with the lowest performance was TNF-alpha & leptin & BDNF (AUC=0.6882). It was confirmed that there was a tendency for superior diagnostic ability when only either leptin or BDNF was utilized.

[0160]

[0161] Example 3-3. Confirmation of diagnostic performance when using quadruple biomarkers

[0162] The performance of the combination of four biomarkers was evaluated using Cougite regression analysis. As a result, it showed a diagnostic ability with a specificity of 90%, a sensitivity of 74%, and an AUC of 0.9307 (Fig. 5, Table 3). This is a significantly superior result compared to using each individual single marker.

[0163]

[0164] The quantitative analysis data of the four proteins mentioned above was used to select a combination of multiple biomarkers that has significantly improved diagnostic ability compared to the performance of a single biomarker, and the regression analysis model of the above mathematical formula maximized the effect of the combination of multiple biomarkers by using optimal weights for the variable values ​​for each biomarker. Through such analysis, it was clearly confirmed that the multiple biomarkers formed by the combination of TNF-alpha, IFN-gamma, BDNF, and leptin of the present invention can be utilized as markers with excellent diagnostic efficiency for depression.

[0165]

[0166] The combination of multiple biomarkers according to the present invention exhibits an AUC value that is at least 1.5 times superior to that of depression compared to the case where a single biomarker is used. When the combination of multiple biomarkers according to the present invention is used, depression can be diagnosed simply and effectively, providing useful information for the diagnosis, adjustment of treatment plans, and prognosis management of patients with depression. Furthermore, by developing a technology that can objectively evaluate depression by incorporating existing depression diagnostic analysis techniques, objective indicators for depression evaluation are presented, and more systematic management is possible through mutual complementarity with existing psychological testing and counseling-based diagnostic methods.

[0167]

[0168] Foregoing, specific parts of the present invention have been described in detail. It will be apparent to those skilled in the art that such specific descriptions are merely preferred embodiments and do not limit the scope of the invention. Accordingly, the actual scope of the invention is defined by the appended claims and their equivalents.

Claims

1. A composition for diagnosing depression comprising a preparation capable of measuring the levels of three or more proteins selected from the group consisting of TNF-alpha, IFN-gamma, BDNF, and leptin, or the expression levels of genes encoding them.

2. In claim 1, comprising a preparation capable of measuring protein levels of TNF-alpha, IFN-gamma, and BDNF or expression levels of genes encoding them; A composition for diagnosing depression comprising a preparation capable of measuring protein levels of TNF-alpha, IFN-gamma, and leptin or expression levels of genes encoding them.

3. A composition for diagnosing depression according to claim 1, comprising a preparation capable of measuring protein levels of TNF-alpha, IFN-gamma, BDNF, and leptin or expression levels of genes encoding them.

4. A composition for diagnosing depression according to claim 1, characterized in that the preparation capable of measuring the protein level is one or more selected from the group consisting of antibodies, oligopeptides, ligands, PNA (peptide nucleic acid), and aptamers that specifically bind to each protein.

5. A composition for diagnosing depression according to claim 1, wherein the preparation capable of measuring the expression level of the gene is selected from the group consisting of primers, probes, and antisense nucleotides that specifically bind to the gene encoding each protein.

6. A kit for diagnosing depression comprising a preparation capable of measuring the levels of three or more proteins selected from the group consisting of TNF-alpha, IFN-gamma, BDNF, and leptin, or the expression levels of genes encoding them.

7. In paragraph 6, comprising a preparation capable of measuring protein levels of TNF-alpha, IFN-gamma, and BDNF or expression levels of genes encoding them; A kit for diagnosing depression comprising a preparation capable of measuring protein levels of TNF-alpha, IFN-gamma, and leptin or expression levels of genes encoding them.

8. A kit for diagnosing depression according to claim 7, comprising a preparation capable of measuring protein levels of TNF-alpha, IFN-gamma, BDNF, and leptin or expression levels of genes encoding them.

9. A kit for diagnosing depression according to claim 6, characterized in that the preparation capable of measuring the protein level is one or more selected from the group consisting of antibodies, oligopeptides, ligands, PNA (peptide nucleic acid), and aptamers that specifically bind to each protein.

10. A kit for diagnosing depression according to claim 6, wherein the preparation capable of measuring the expression level of the gene is selected from the group consisting of primers, probes, and antisense nucleotides that specifically bind to the gene encoding each protein. 11.(a) a step of measuring the levels of three or more proteins selected from the group consisting of TNF-alpha, IFN-gamma, BDNF, and leptin, or the expression levels of genes encoding them, from a sample isolated from a subject; and (b) a method for providing information for the diagnosis of depression, comprising the step of comparing a protein level or the expression level of a gene encoding it with a control group.

12. A method for providing information for the diagnosis of depression, characterized in that, in claim 11, the sample of step (a) is blood, serum, or plasma.

13. A method for providing information for the diagnosis of depression, wherein step (a) is characterized by measuring protein levels through one or more selected from the group consisting of western blotting, ELISA (enzyme-linked immunosorbent assay), lateral flow immunoassay, chemiluminescent immunoassay, immunoturbidimetric test, radioimmunoassay, radioimmunodiffusion, Ouchterlony immunodiffusion, Rocket immunoelectrophoresis, tissue immunostaining, immunoprecipitation assay, complete fixation assay, bead-based immunoassay, Luminex xMAP, FACS, protein chip, and mass spectrometry.

14. In paragraph 11, the above step (a) measures the protein levels of TNF-alpha, IFN-gamma, and BDNF or the expression levels of the genes encoding them; A method for providing information for the diagnosis of depression, characterized by measuring protein levels of TNF-alpha, IFN-gamma, and leptin or expression levels of genes encoding them.

15. A method for providing information for the diagnosis of depression, wherein, in claim 11, step (a) measures the protein levels of TNF-alpha, IFN-gamma, BDNF, and leptin or the expression levels of genes encoding them.

16. In Paragraph 11, (c) A method for providing information for the diagnosis of depression, further comprising the step of confirming that there is a possibility of developing depression when a change in the expression level of any three or more of the following proteins or the gene encoding them is detected: i) Increase in TNF-alpha protein levels and / or expression levels of the gene encoding it; ii) Increase in IFN-gamma protein levels and / or the expression levels of genes encoding it; iii) an increase in BDNF protein levels and / or the expression levels of the gene encoding it; and iv) Increase in leptin protein levels and / or expression levels of the gene encoding it.

17. In Paragraph 16, A method for providing information for the diagnosis of depression, characterized in that step (c) above confirms that there is a possibility of developing depression when a change in the expression level of the following protein or the gene encoding it is detected: i) Increase in TNF-alpha protein levels and / or expression levels of the gene encoding it; ii) an increase in IFN-gamma protein levels and / or the expression levels of genes encoding it; and iii) Increase in BDNF protein levels and / or expression levels of the gene encoding it.

18. In Paragraph 16, A method for providing information for the diagnosis of depression, characterized in that step (c) above confirms that there is a possibility of developing depression when a change in the expression level of the following protein or the gene encoding it is detected: i) Increase in TNF-alpha protein levels and / or expression levels of the gene encoding it; ii) an increase in IFN-gamma protein levels and / or the expression levels of genes encoding it; and iv) Increase in leptin protein levels and / or expression levels of the gene encoding it.

19. In Paragraph 16, A method for providing information for the diagnosis of depression, characterized in that step (c) above confirms that there is a possibility of developing depression when a change in the expression level of the following protein or the gene encoding it is detected: i) Increase in TNF-alpha protein levels and / or expression levels of the gene encoding it; ii) Increase in IFN-gamma protein levels and / or the expression levels of genes encoding it; iii) an increase in BDNF protein levels and / or the expression levels of the gene encoding it; and iv) Increase in leptin protein levels and / or expression levels of the gene encoding it.

20. In Paragraph 14, (d) a step of calculating an estimate (x) of the probability of being diagnosed with depression by substituting the protein level or the expression level of the gene encoding it measured through step (a) above into the following mathematical formula 1; a method for providing information for diagnosing depression: [Mathematical Formula 1] x = α+{β1×(concentration of TNF-alpha in sample)}+{β2×(concentration of IFN-gamma in sample)}+{β3×(concentration of BDNF in sample)} In the above mathematical formula 1, x is an estimate of the probability of being diagnosed with depression, α is the intercept value when the estimate (x) is 0 (-50 ≤ α ≤ 10), β1 is a regression coefficient representing the weight for the concentration value of TNF-alpha in the sample (-5 ≤ β1 ≤ 20), β2 is a regression coefficient representing the weight for the concentration value of IFN-gamma in the sample (-5 ≤ β2 ≤ 5), and β3 is a regression coefficient representing the weight for the concentration value of BDNF in the sample (-5 ≤ β3 ≤ 10).

21. In Paragraph 14, (d) a step of calculating an estimate (x) of the probability of being diagnosed with depression by substituting the protein level or the expression level of the gene encoding it measured through step (a) above into the following mathematical formula 2; a method for providing information for diagnosing depression: [Mathematical Formula 2] x = α+{β1×(concentration of TNF-alpha in sample)}+{β2×(concentration of IFN-gamma in sample)}+β4×(concentration of leptin in sample)} In the above mathematical formula 2, x is an estimate of the probability of being diagnosed with depression, α is the intercept value when the estimate (x) is 0 (-50 ≤ α ≤ 10), β1 is a regression coefficient representing the weight for the concentration value of TNF-alpha in the sample (-5 ≤ β1 ≤ 20), β2 is a regression coefficient representing the weight for the concentration value of IFN-gamma in the sample (-5 ≤ β2 ≤ 5), and β4 is a regression coefficient representing the weight for the concentration value of leptin in the sample (-10 ≤ β4 ≤ 5).

22. In Paragraph 15, (d) a step of calculating an estimate (x) of the probability of being diagnosed with depression by substituting the protein level or the expression level of the gene encoding it measured through step (a) above into the following mathematical formula 3; a method for providing information for diagnosing depression: [Mathematical Formula 3] x = α + {β1 × (concentration of TNF-alpha in sample)} + {β2 × (concentration of IFN-gamma in sample)} + {β3 × (concentration of BDNF in sample)} + {β4 × (concentration of leptin in sample)} In the above mathematical formula 3, x is an estimate of the probability of being diagnosed with depression, α is the intercept value when the estimate (x) is 0 (-50 ≤ α ≤ 10), β1 is a regression coefficient representing the weight for the concentration value of TNF-alpha in the sample (-5 ≤ β1 ≤ 20), β2 is a regression coefficient representing the weight for the concentration value of IFN-gamma in the sample (-5 ≤ β2 ≤ 5), β3 is a regression coefficient representing the weight for the concentration value of BDNF in the sample (-5 ≤ β3 ≤ 10), and β4 is a regression coefficient representing the weight for the concentration value of leptin in the sample (-10 ≤ β4 ≤ 5). 23.(a) a step of treating a sample isolated from a subject or an animal model of depression with a candidate drug; and (b) A method for screening drugs for the prevention or treatment of depression, comprising the step of measuring the levels of three or more proteins selected from the group consisting of TNF-alpha, IFN-gamma, BDNF, and leptin, or the expression levels of genes encoding them, in a sample treated with the above candidate drug or in an animal model of depression.

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