Depression diagnosis marker combination and application thereof

Abstract

The invention discloses a diagnosis marker combination for depression and application thereof, and relates to the technical field of biological medicine. The diagnostic marker combination comprises the following diagnostic markers: CD63, F11R, ATP1A1, SLC6A2, SRC, LRP4 and PLXNB1 (Partial Leucine Xylaniline 1). Through proteomics screening and SPR (Surface Plasmon Resonance) technical verification, seven exosome membrane proteins, namely CD63, F11R, ATP1A1, SLC6A2, SRC, LRP4 and PLXNB1, are successfully identified as the depression core diagnosis markers, the AUC (Amplified Units Content) of the constructed combined diagnosis model reaches 1.000, and the depression can be effectively and accurately distinguished. The marker combination covers a plurality of pathological dimensions such as inflammatory response, blood brain barrier function and energy metabolism, comprehensively reflects depression multi-mechanism abnormal characteristics, breaks through the limitation of strong subjectivity of traditional scale evaluation, and provides an objective diagnosis standard.

Description

Technical Field

[0001] This invention relates to the field of biomedical technology, and in particular to a combination of diagnostic biomarkers for depression and their applications. Background Technology

[0002] Depression is a common mental disorder characterized by depressed mood, lack of interest, and slowed thinking and cognitive function. Depression reduces patients' quality of life and severely impacts their social and psychological functioning.

[0003] The pathological mechanisms of depression are highly complex and not yet fully understood; it is currently generally accepted as a multisystem disorder. Diagnosis of depression primarily relies on scale assessments, which are highly subjective and lack objective diagnostic criteria, hindering accurate diagnosis and treatment.

[0004] Peripheral blood, as a clinical sample, has the advantages of being readily available and having high diagnostic performance, and is widely used in the diagnosis and treatment of clinical diseases. The core advantage of peripheral blood exosomes as biomarkers lies in their ability to trace tissue cells through specific proteins on their membrane surface, thus providing highly specific evidence of origin for disease diagnosis. Simultaneously, their lipid bilayer structure stably protects the contents and enriches functional biological information, ultimately enabling non-invasive liquid biopsy for early disease detection, dynamic monitoring, and precise subtyping. The exosome membrane proteins exposed on the exosome surface allow for extraction-free, direct, and highly sensitive detection of target proteins using novel biosensing technologies such as surface plasmon resonance (SPR). Based on this, this invention aims to develop new diagnostic biomarkers for depression to improve the accuracy of its diagnosis. Summary of the Invention

[0005] The purpose of this invention is to provide a diagnostic biomarker combination for depression and its application, thereby addressing the problems existing in the prior art. This diagnostic biomarker combination covers multiple pathological dimensions such as inflammatory response, blood-brain barrier function, and energy metabolism, enabling effective and accurate differentiation of depression.

[0006] To achieve the above objectives, the present invention provides the following solution: The present invention provides a diagnostic biomarker for depression, wherein the diagnostic biomarker is any one of CD63, F11R, ATP1A1, SLC6A2, SRC, LRP4 and PLXNB1.

[0007] The present invention also provides a combination of diagnostic biomarkers for depression, including the following diagnostic biomarkers: CD63, F11R, ATP1A1, SLC6A2, SRC, LRP4 and PLXNB1.

[0008] The present invention also provides the application of reagents for detecting the expression levels of the above-mentioned diagnostic markers in serum in the preparation of diagnostic products for depression.

[0009] The present invention also provides the use of reagents for detecting the expression levels of the above-mentioned combination of diagnostic markers in serum in the preparation of diagnostic products for depression.

[0010] Furthermore, the diagnostic product is a diagnostic kit.

[0011] Furthermore, the diagnostic product is a chip.

[0012] The present invention also provides a diagnostic product for depression, comprising a reagent for detecting the expression level of the above-mentioned diagnostic markers or combinations of diagnostic markers in serum.

[0013] Furthermore, the diagnostic product is a diagnostic kit.

[0014] Furthermore, the diagnostic product is a chip.

[0015] The present invention also provides a method for constructing a diagnostic model for depression, wherein the diagnostic model for depression is constructed by using the spectral response values ​​of CD63, F11R, ATP1A1, SLC6A2, SRC, LRP4 and PLXNB1 in serum samples detected by SPR optical chip as input variables; The diagnostic model for depression is: P = 1 / [1 + exp / (12.130 - SPR)] PLXNB1 ×1.010-SPR LRP4 ×6.821-SPR SRC ×0.297-SPR SLC6A2 ×0.672-SPR ATP1A1 ×3.5+SPR F11R ×5.041+SPR CD63 ×8.090)]; In the aforementioned diagnostic model for depression, exp represents an exponential function with the natural constant e as its base; SPR CD63 SPR F11R SPR ATP1A1 SPR SLC6A2 SPR SRC SPR LRP4 and SPR PLXNB1 These represent the spectral response values ​​corresponding to each diagnostic marker; P represents the probability of not having depression, and the lower the P value, the higher the risk of having depression.

[0016] The present invention discloses the following technical effects: This invention, through proteomics screening and SPR technology validation, successfully identified seven exosomal membrane proteins—CD63, F11R, ATP1A1, SLC6A2, SRC, LRP4, and PLXNB1—as core diagnostic biomarkers for depression. The constructed combined diagnostic model achieved an AUC of 1.000, effectively enabling precise differentiation of depression. This biomarker combination covers multiple pathological dimensions, including inflammatory responses, blood-brain barrier function, and energy metabolism, comprehensively reflecting the multi-mechanistic abnormalities of depression. It overcomes the limitations of traditional scale assessments, which are highly subjective, and provides objective diagnostic criteria. Leveraging the structural stability of exosomal membrane proteins and the extraction-free detection advantages of SPR technology, the detection process is simplified, improving result repeatability and sample storage adaptability, and aligning with the needs of clinical reagent kits and chip development. The technical solution of this invention facilitates low-invasive liquid biopsy for depression, providing support for early disease screening, dynamic monitoring, and precise subtyping, and promoting the transformation of depression diagnosis from symptom assessment to molecular biomarker-guided precision medicine, possessing significant clinical translational value. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 A bar chart showing the number of proteins identified in different samples; Figure 2 Volcano plot for differentially expressed proteins; Figure 3 Bubble plot of KEGG enrichment for differentially expressed proteins; Figure 4 Bubble plot for GO enrichment of differentially expressed proteins; Figure 5 A comparison of the levels of 14 exosomal membrane proteins between the MDD group and the HC group; Figure 6 Receiver operating characteristic curves for 7 exosomal membrane proteins; Figure 7 Receiver operating characteristic curves for the combined diagnosis of 7 exosomal membrane proteins. Detailed Implementation

[0019] Various exemplary embodiments of the present invention will now be described in detail. This detailed description should not be considered as a limitation of the present invention, but rather as a more detailed description of certain aspects, features, and embodiments of the present invention.

[0020] It should be understood that the terminology used in this invention is merely for describing particular embodiments and is not intended to limit the invention. Furthermore, with respect to numerical ranges in this invention, it should be understood that each intermediate value between the upper and lower limits of the range is also specifically disclosed. Any stated value or intermediate value within a stated range, as well as each smaller range between any other stated value or intermediate value within said range, is also included in this invention. The upper and lower limits of these smaller ranges may be independently included or excluded from the range.

[0021] Unless otherwise stated, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art. While only preferred methods and materials have been described herein, any methods and materials similar or equivalent to those described herein may be used in the implementation or testing of this invention. All references to this specification are incorporated by way of citation to disclose and describe methods and / or materials associated with those references. In the event of any conflict with any incorporated reference, the content of this specification shall prevail.

[0022] Various modifications and variations can be made to the specific embodiments described in this specification without departing from the scope or spirit of the invention, as will be apparent to those skilled in the art. Other embodiments derived from this specification will also be apparent to those skilled in the art. This specification and embodiments are merely exemplary.

[0023] The terms “include,” “including,” “have,” “contain,” etc., used in this article are all open-ended terms, meaning that they include but are not limited to.

[0024] Terminology Explanation: FCER1G: High-affinity IgE receptor γ chain; S100A8: Calcium-binding protein A8, also known as myeloid-associated protein 8; CD63: Differentiation cluster 63, also known as lysosome-associated membrane protein 3; CD31: Differentiation cluster 31, also known as platelet endothelial cell adhesion molecule 1; PIGR: Polyimmunoglobulin receptor; S100A9: Calcium-binding protein A9, also known as myeloid-associated protein 14; TFRC: Transferrin receptor 1; ATP1A1: Na + / K + -ATPase α1 subunit; LRP4: Lipoprotein receptor-associated protein 4; PLXNB1: Cluster protein B1; SEMA4C; Signal 4C; SRC: Sarcoma tyrosine kinase; SLC6A2; sodium-dependent norepinephrine transporter, also known as norepinephrine transporter protein; F11R: F11 receptor, also known as platelet endothelial cell adhesion molecule-like protein 1.

[0025] Example 1: Screening and Construction of a Diagnostic Index Set for Peripheral Blood Exosomes in Depression 1. Materials and Methods (1) Research subjects The subjects of this invention were patients with depression who voluntarily participated in the study at Dongfang Hospital of Beijing University of Chinese Medicine from June 2022 to December 2023. During the same period, healthy subjects of age and gender were recruited through hospital posters, university recruitment platforms and other means. After meeting the diagnostic criteria and inclusion / exclusion criteria and signing informed consent, they were enrolled in the study.

[0026] (2) Diagnostic criteria Meets the diagnostic criteria for depression in the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5): A. Having five (or more) of the following symptoms within two consecutive weeks, and having altered pre-existing function, including at least one symptom of depressed mood or loss of interest in or pleasure in activities.

[0027] Note: This excludes symptoms caused by physical conditions, or delusions or hallucinations that are inconsistent with mood.

[0028] ① Depressed mood for most of the day, a subjective experience (e.g., feeling sad or empty), or observed by others (e.g., crying). Note: Children and adolescents may be irritable.

[0029] ②A significant decrease in interest or pleasure in all or almost all activities for most of the day (subjective experience or observation by others).

[0030] ③ Significant weight loss or gain without dieting (e.g., weight change exceeding 5% within a month), or almost daily loss or gain of appetite. Note: For children, consider that their weight gain may not be as expected.

[0031] ④ I experience either insomnia or excessive sleep almost every day.

[0032] ⑤ Almost every day there is psychomotor agitation or sluggishness (not only do I feel subjectively restless or sluggish, but others can also observe it).

[0033] ⑥ Feeling tired or lacking energy almost every day.

[0034] ⑦ Feeling useless almost every day, or having inappropriate and excessive guilt (to the point of delusional guilt: not just feeling guilty or remorseful for the illness).

[0035] ⑧ Almost every day there is a decline in thinking ability or concentration, or indecisiveness (subjective experience or observation by others).

[0036] ⑨ Repeated thoughts of death (not just fear of death), repeated suicidal ideation without a specific plan, or suicide attempt, or a specific suicide plan.

[0037] B. The symptoms do not meet the criteria for mixed seizures.

[0038] C. Symptoms cause clinically significant distress or impairment in social, occupational, or other important functions.

[0039] D. The symptoms are not caused by the direct physiological effects of substances (such as addictive drugs or prescription drugs) or physical conditions (such as hypothyroidism).

[0040] E. Symptoms cannot be explained by a grief reaction (i.e., the reaction to the loss of a loved one), symptoms last for more than 2 months, or symptoms are characterized by significant functional impairment, pathological immersion in feelings of worthlessness, suicidal ideation, psychotic symptoms, or psychomotor retardation.

[0041] (3) Inclusion criteria Depression patients: ① Meets the diagnostic criteria for depression; ② Meets the syndrome criteria for liver stagnation and spleen deficiency; ③HAMD (17 items) ≥ 7 points; ④ 18 years old ≤ age ≤ 60 years old; ⑤ Those who comply with the treatment plan, are willing to cooperate with the treatment, and voluntarily participate in the informed consent process for this invention.

[0042] Patients who meet all five of the above criteria are eligible for selection.

[0043] Healthy subjects: ①18 years old ≤ age ≤ 60 years old; ②Currently in good mental condition, with no history of mental disorders; HMAD-17 score < 7; ③ No family history of mental illness; ④According to the Traditional Chinese Medicine body constitution scale, it is a balanced constitution; ⑤ Individuals without drug or alcohol dependence; ⑥ Individuals without congenital or acquired intellectual disability; ⑦ Patients without serious organic diseases such as heart, brain, liver, and kidney; ⑧ Women who are not pregnant or breastfeeding.

[0044] Patients who meet all eight criteria above are eligible for selection.

[0045] (4) Exclusion criteria Exclusion criteria for patients with depression: ①Those who have used antibiotics within the past 6 weeks; ② Continuous use of sedative-hypnotic and antidepressant medications for mental illness within the past month; ③ Individuals with drug or alcohol dependence; ④ Patients with serious organic diseases of the heart, brain, liver, kidneys, or other serious primary diseases, as well as patients with acute illnesses, infectious diseases, or malignant tumors; ⑤ Individuals with intellectual disability due to congenital or acquired factors; ⑥ Patients with depression caused by a clear underlying medical condition; ⑦ Pregnant and lactating women; ⑧ Patients with cognitive impairment or personality disorders; ⑨ Individuals with serious suicidal ideation or suicidal behavior.

[0046] Any participant who meets any of the above criteria will be excluded.

[0047] Exclusion criteria for healthy subjects: ① Allergic constitution; ②Those who do not comply with the plan, are unwilling to cooperate with the inspection, or do not sign informed consent.

[0048] Any participant who meets any of the above criteria will be excluded.

[0049] (5) Equipment and Instruments The main equipment and instruments used in this invention are shown in Table 1.

[0050] Table 1 Main Equipment and Instruments (6) Reagents and materials The main reagents and materials used in this invention are shown in Table 2.

[0051] Table 2 Main Reagents and Materials (7) Grouping and sample size The cohort was divided into two groups: 30 patients with depression (MDD) and 15 age- and sex-matched healthy subjects (HC).

[0052] (8) Observation indicators ① Basic Information Name, age, weight, gender, medical history, condition, etc.

[0053] ② Clinical symptom assessment Hamilton Depression Scale (HAMD-17): Developed by Hamilton in 1960, the Depression Scale is the most widely used clinically for assessing depressive states. This invention uses the 17-item version. Most items use a 5-point rating scale (0-4), with each level defined as follows: 0 for none, 1 for mild, 2 for moderate, 3 for severe, and 4 for very severe. A few items use a 3-point rating scale (0-2), with each level defined as follows: 0 for none, 1 for mild-moderate, and 2 for severe. The higher the total score, the more severe the depression.

[0054] Hamilton Anxiety Scale (HAMA): Developed by Hamilton in 1959, the scale comprises 14 items, all using a 5-point rating scale from 0 to 4. The criteria for each level are: 0 for none, 1 for mild, 2 for moderate, 3 for severe, and 4 for very severe. The total score effectively reflects the severity of anxiety symptoms.

[0055] ③ Exosomal proteomics analysis Peripheral blood samples were collected from 15 HC controls and 30 MDD patients and subjected to exosomal proteomics analysis by LC-MS / MS.

[0056] 2. Research Results (1) Comparison of basic information between MDD group and HC group Among the 45 subjects included in this invention, there were no significant differences in age and sex between the MDD group and the HC group. p> 0.05), see Table 3.

[0057] Table 3 Comparison of baseline basic information between the MDD group and the HC group (2) Comparison of HAMD and HAMA scale scores between the MDD group and the HC group Compared with the HC group, the MDD group showed significantly higher scores on both the HAMD and HAMA scales. p＜ The values ​​were 0.01), and all HC group members were within the healthy range of the scale, as shown in Table 4.

[0058] Table 4 Comparison of HAMD and HAMA scale scores between the MDD group and the HC group (3) Exosomal proteomics results ① Protein identification results A total of 183 proteins were detected in the sample after LC-MS / MS analysis.

[0059] ② Differential protein screening This invention included peripheral blood samples from 15 HC controls and 30 MDD patients. After log-transformation, proteomic data were used to assess the differences in protein expression between groups using two parameters: fold change (FC, calculated from log2FC, log2Foldchange = experimental group mean - control group mean) and the p-value obtained by t-test. In this report, the differential screening criteria were: p-value < 0.05, FC ≥ 2.0, or FC ≤ 1 / 2.0.

[0060] Compared with the healthy group, 183 significantly differentially expressed proteins were identified in the peripheral blood exosomes of patients with depression. Among them, the expression levels of 122 proteins were increased and the expression levels of 61 proteins were decreased. The volcano plot comparison between the two groups is shown in Table 5. Figure 1 and Figure 2 .

[0061] Table 5. Statistical table of differentially expressed proteins ③ KEGG analysis of differentially expressed proteins The Kyoto Encyclopedia of Genes and Genomes (KEGG) is a database that systematically analyzes gene function and links genomic and functional information.

[0062] Compared with the control group, KEGG enrichment analysis ( Figure 3The differentially expressed proteins were found to be mainly involved in gap junctions, focal adhesion, extracellular matrix-receptor interactions, leukocyte transendothelial migration, glutathione metabolism, axon guidance, FcγR-mediated phagocytosis, endocytosis, lysosomes, neurotrophin signaling pathway, tight junctions, chemokine signaling pathway, and MAPK signaling pathway.

[0063] ④ Differential protein GO analysis Compared with the control group, GO enrichment analysis ( Figure 4The differentially expressed proteins were found to be mainly involved in the establishment of localization, immune system processes, immune responses, biological processes involved in interspecies interactions between organisms, vesicle-mediated transport, responses to other organisms, responses to external biotic stimuli, responses to biotic stimuli, regulation of immune system processes, defense responses to other organisms, immune effector processes, endocytosis, regulation of cell activation, phagocytosis, defense responses to bacteria, and leukocyte-mediated immunity.

[0064] In summary, the main findings of this invention are as follows: Exosomal proteomics suggests that, compared with healthy individuals, MDD patients have increased expression levels of 122 proteins and decreased expression levels of 61 proteins in peripheral blood exosomal proteins. Bioinformatics analyses using KEGG and GO revealed that the differentially expressed proteins are mainly enriched in multiple aspects, including immune response, immune cell migration, tight junction pathways, neural axon development and guidance, neurotrophic factor signaling pathways, MAPK signaling pathways, and glutathione metabolism. This reveals that multiple pathological mechanisms of MDD are simultaneously abnormal, such as inflammatory activation, blood-brain barrier damage, energy and metabolic disorders, and impaired neural development and synaptic remodeling.

[0065] Based on this, 14 core exosomal membrane proteins from the aforementioned pathways were selected as biomarkers for depression and will be further validated in clinical trials. Immune inflammation: FCE R1G, CD63, CD31, S100A8, PIGR, S100A9; Energy and metabolism: TFRC, ATP1A1; Neurodevelopment and synaptic remodeling: LRP4, PLXNB1, SEMA4C, SRC, SLC6A2; Blood-brain barrier: F11R.

[0066] Example 2: Validation of peripheral blood exosome diagnostic indices for depression using plasma resonance (SPR) technology 1. Materials and Methods (1) Research subjects The subjects of this invention were patients with depression who voluntarily participated in the study at Dongfang Hospital of Beijing University of Chinese Medicine from June 2023 to December 2024. During the same period, healthy subjects of age and gender were recruited through hospital posters, university recruitment platforms and other means. After meeting the diagnostic criteria and inclusion / exclusion criteria and signing informed consent, they were enrolled.

[0067] (2) Diagnostic criteria The diagnostic criteria for patients with depression are the same as in Example 1.

[0068] (3) Inclusion criteria The inclusion criteria for patients with depression are the same as in Example 1.

[0069] (4) Exclusion criteria The same exclusion criteria for patients with depression as in Example 1.

[0070] (5) Grouping and sample size The validation cohort consisted of 30 MDD patients recruited separately (different from Example 1) and 15 age- and sex-matched HC patients.

[0071] (6) Instruments and equipment Table 6. Main instruments and equipment used in this invention (7) Reagents and materials Table 7. Main reagents and materials used in this invention (8) Observation indicators ① Basic Information Name, age, weight, gender, medical history, condition, and information from the four diagnostic methods of Traditional Chinese Medicine; ② Clinical efficacy indicators Hamilton Depression Scale (HAMD-17): Developed by Hamilton in 1960, the Depression Scale is the most widely used clinically for assessing depressive states. This invention uses the 17-item version. Most items use a 5-point rating scale (0-4), with each level defined as follows: 0 for none, 1 for mild, 2 for moderate, 3 for severe, and 4 for very severe. A few items use a 3-point rating scale (0-2), with each level defined as follows: 0 for none, 1 for mild-moderate, and 2 for severe. The higher the total score, the more severe the depression.

[0072] Hamilton Anxiety Scale (HAMA): Developed by Hamilton in 1959, the scale comprises 14 items, all using a 5-point rating scale from 0 to 4. The criteria for each level are: 0 for none, 1 for mild, 2 for moderate, 3 for severe, and 4 for very severe. The total score effectively reflects the severity of anxiety symptoms.

[0073] ③Detection indicators 14 candidate exosomal membrane proteins Inflammation: FCER1G, S100A8, CD63, CD31, PIGR, S100A9; Energy and metabolism: TFRC, ATP1A1; Neurodevelopment and synaptic remodeling: LRP4, PLXNB1, SEMA4C, SRC, SLC6A2; Blood-brain barrier: F11R.

[0074] (9) Statistical analysis SPSS 22.6 software was used for statistical analysis, and GraphPad Prism was used for result presentation. Independent samples t-tests were performed on the two groups of subjects.

[0075] Comparison of scale scores and basic information between the healthy group and the MDD patient group; normality test performed on the data; independent samples t-test was used for data that conform to normal distribution and homogeneous variance; chi-square test was used for categorical data. p A value <0.05 is statistically significant.

[0076] Binary logistic regression analysis was performed on statistically significant indicators to calculate their predicted probability values. Then, receiver operating characteristic (ROC) analysis and ROC curve plotting were performed on the predicted probability values ​​of the differential indicators to verify the diagnostic performance of the indicator set.

[0077] (10) Detection methods and processes 1. The 14 core exosomal membrane proteins screened in Example 1 were validated using SPR optical chip technology. Serum exosomal proteins were specifically captured using a metasurface biochip, and their membrane protein indicators were detected.

[0078] Detailed experimental procedure: (1) Samples that melt rapidly on ice.

[0079] (2) Take 100 μL of sample and put it onto the antibody-functionalized metasurface chip, and react at 37 °C for 30 min.

[0080] (3) Rinse three times with deionized water.

[0081] (4) The signal is measured using a spectrometer.

[0082] 2. Research Results (1) Comparison of basic information between MDD group and HC group Among the 45 subjects included in this invention, there were no significant differences in age and sex between the MDD group and the HC group. p> 0.05), see Table 8.

[0083] Table 8 Comparison of baseline basic information between the MDD group and the HC group (2) Comparison of HAMD and HAMA scale scores between the MDD group and the HC group Compared with the HC group, the MDD group showed significantly higher scores on the HAMD, HAMA, and AIS scales. p＜ (0.01), and all HC group members were within the healthy range of the scale, as shown in Table 9.

[0084] Table 9 Comparison of HAMD and HAMA scale scores between the MDD group and the HC group (3) Comparison of the levels of 14 exosome membrane proteins in peripheral blood between the MDD group and the HC group like Figure 5 As shown, there were significant differences in 13 peripheral blood exosome membrane proteins compared to healthy individuals in MDD patients. Combined with the proteomics results from Example 1, seven of these proteins showed consistent expression before and after expression, exhibiting good stability: CD63, F11R, ATP1A1, SLC6A2, SRC, LRP4, and PLXNB1. p＜ 0.01, p＜ (0.05), involving inflammation, barrier function, energy metabolism, neurotransmitters, neural development and synaptic remodeling, can relatively comprehensively summarize the characteristics of depression.

[0085] (4) Individual subject operating characteristics analysis of 7 differences between the MDD group and the HC group Receiver operating characteristic analysis was performed on the seven differential indicators between the MDD group and the HC group. Among them, CD63, F11R, ATP1A1, SLC6A2, SRC, LRP4, and PLXNB1 showed good distinguishing effect between healthy individuals and MDD patients and were statistically significant. p <0.05), see Table 10. Receiver operating characteristic curves were plotted for the above seven indicators with significant discrimination, and the results are shown in [Table 10]. Figure 6 .

[0086] Table 10. Analysis of participant operating characteristics of 7 exosomal membrane proteins in the MDD and HC groups. (5) Construction of a diagnostic model for depression The spectral responses of seven exosome membrane proteins were detected using the SPR optical chip method described in the examples. Then, the spectral response values ​​of CD63, F11R, ATP1A1, SLC6A2, SRC, LRP4, and PLXNB1 in serum samples from 30 MDD patients and 15 healthy controls were subjected to binary logistic regression joint analysis to construct a depression prediction model. P (P = MDD negative) = 1 / [1 + exp / (12.130 - SPR)] PLXNB1 ×1.010-SPR LRP4 ×6.821-SPR SRC ×0.297-SPR SLC6A2 ×0.672-SPR ATP1A1 ×3.5+SPR F11R ×5.041+SPR CD63 ×8.090)]; In this predictive model: exp represents an exponential function with the natural constant e as the base, SPR CD63 SPR F11R SPR ATP1A1 SPR SLC6A2 SPR SRC SPR LRP4 SPR PLXNB1 These represent the spectral response values ​​corresponding to their respective indicators, and P represents the probability of not suffering from depression.

[0087] (6) Analysis of 7 differences between the MDD group and the HC group combined with subject operating characteristics Receiver operating characteristic (AUC) analysis of the above seven indicators revealed an AUC of 1.000, a Youden index of 1.000, and a sensitivity and specificity of 1.000 for diagnosing MDD patients. (See [link to relevant documentation]). Figure 7 See Table 11.

[0088] Table 11 Analysis of diagnostic subject-operating characteristics of 7 exosomal membrane proteins In summary, based on the multi-mechanism pathological characteristics of MDD, this invention constructs a combined diagnostic model comprising seven indicators—CD63, F11R, ATP1A1, SLC6A2, SRC, LRP4, and PLXNB1—starting with peripheral blood exosome membrane proteins. This indicator set covers multiple key pathological dimensions, including blood-brain barrier integrity, neurotransmitter reuptake, ion homeostasis, intracellular signal transduction, and synaptic plasticity. It demonstrates extremely high discriminative efficacy (combined diagnostic rate of 1.000%) in distinguishing MDD patients from healthy individuals, showing significant auxiliary diagnostic value.

[0089] Compared to conventional serum protein testing, exosome membrane proteins have significant advantages: More specific functional targets: Membrane proteins directly participate in key processes such as cell adhesion and signal transduction, and are more closely linked to MDD-related pathways; More specific source: traceable to neurons or specific cell origins, with lower information noise; Greater stability: The exosome membrane structure effectively protects proteins from degradation, making it easier for clinical sample storage and standardized testing.

[0090] Furthermore, exosomal membrane proteins offer unique advantages in terms of ease of detection compared to intramembrane proteins. The exposure of membrane proteins on the exosome surface allows for extraction-free, direct, and highly sensitive detection of target proteins using novel biosensing technologies such as surface plasmon resonance (SPR). This not only significantly simplifies the detection process and shortens analysis time but also reduces variability introduced during sample processing, substantially improving the stability and reproducibility of the detection, demonstrating enormous potential for clinical translation.

[0091] In summary, the seven exosomal membrane protein biomarkers proposed in this invention not only provide a novel liquid biopsy strategy for the objective diagnosis of MDD from multiple mechanism perspectives, but also demonstrate significant clinical application potential due to their membrane protein properties, which allow for efficient coupling with extraction-free detection technologies such as SPR. With future expanded sample validation, this indicator set is expected to become a practical tool for MDD subtyping diagnosis, efficacy monitoring, and prognostic assessment, propelling psychiatry towards a new stage of precision medicine.

[0092] The embodiments described above are merely preferred embodiments of the present invention and are not intended to limit the scope of the present invention. Various modifications and improvements made by those skilled in the art to the technical solutions of the present invention without departing from the spirit of the present invention should fall within the protection scope defined by the claims of the present invention.

Claims

1. A diagnostic biomarker for depression, characterized in that, The diagnostic biomarkers are any one of CD63, F11R, ATP1A1, SLC6A2, SRC, LRP4, and PLXNB1.

2. A combination of diagnostic biomarkers for depression, characterized in that, The following diagnostic markers are included: CD63, F11R, ATP1A1, SLC6A2, SRC, LRP4, and PLXNB1.

3. The use of a reagent for detecting the expression level of the diagnostic marker of claim 1 in serum in the preparation of diagnostic products for depression.

4. The use of a reagent for detecting the expression level of the diagnostic biomarker combination of claim 2 in serum in the preparation of diagnostic products for depression.

5. The application according to claim 3 or 4, characterized in that, The diagnostic product is a diagnostic kit.

6. The application according to claim 3 or 4, characterized in that, The diagnostic product is a chip.

7. A diagnostic product for depression, characterized in that, The reagent includes a reagent for detecting the expression level of the diagnostic biomarker of claim 1 or the combination of diagnostic biomarkers of claim 2 in serum.

8. The diagnostic product according to claim 7, characterized in that, The diagnostic product is a diagnostic kit.

9. The diagnostic product according to claim 7, characterized in that, The diagnostic product is a chip.

10. A method for constructing a diagnostic model for depression, characterized in that, The depression diagnostic model was constructed using the spectral response values ​​of CD63, F11R, ATP1A1, SLC6A2, SRC, LRP4 and PLXNB1 in serum samples detected by the SPR optical chip as input variables. The diagnostic model for depression is: P = 1 / [1 + exp / (12.130 - SPR)] PLXNB1 ×1.010-SPR LRP4 ×6.821-SPR SRC ×0.297-SPR SLC6A2 ×0.672-SPR ATP1A1 ×3.5+SPR F11R ×5.041+SPR CD63 ×8.090)]; In the aforementioned diagnostic model for depression, exp represents an exponential function with the natural constant e as its base; SPR CD63 SPR F11R SPR ATP1A1 SPR SLC6A2 SPR SRC SPR LRP4 and SPR PLXNB1 These represent the spectral response values ​​corresponding to each diagnostic marker; P represents the probability of not having depression, and the lower the P value, the higher the risk of having depression.

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