A serum protein expression profile-based auxiliary diagnosis and curative effect evaluation system for adolescent depression

Abstract

The application provides a serum protein expression profile-based auxiliary diagnosis and curative effect evaluation system for adolescent depression, and belongs to the technical field of biological detection. The auxiliary diagnosis and curative effect evaluation system selects a combination of MANF, NDUFA13 and HYOU1 protein markers to construct an auxiliary diagnosis system for adolescent depression, has better identification efficiency than single detection index, effectively improves the diagnostic sensitivity and specificity, reduces the misdiagnosis and missed diagnosis, establishes quantitative input characteristics relying on objective protein expression data, discards the subjective judgment mode of a traditional scale, reduces human factor interference, has high stability and accuracy after sample training and blind verification of the diagnosis system, has a standard and normative overall method process, can realize non-invasive, objective and accurate early screening and disease risk prediction for adolescent depression, is convenient for clinical popularization and application, and helps early diagnosis and treatment of adolescent psychological diseases.

Description

Technical Field

[0001] This invention belongs to the field of biological detection technology, specifically relating to an auxiliary diagnostic and efficacy evaluation system for adolescent depression based on serum protein expression profiles. Background Technology

[0002] Adolescence is a critical stage for both physical and psychological development. Influenced by multiple factors such as academic pressure, family environment, social relationships, and endocrine fluctuations, the incidence of mental health disorders among adolescents is rising year by year. Among these, adolescent depression has become a prevalent mental illness that seriously threatens the physical and mental health of adolescents. This disease has an insidious onset, and early clinical symptoms are often atypical, making it easy to miss or misdiagnose. If timely and accurate screening and early intervention are not implemented, it can lead to persistent low mood, decreased attention span, and social withdrawal in adolescents, and may even trigger school aversion, self-harm, or extreme behaviors, seriously affecting their academic development and mental and emotional health, and placing a heavy burden on families and society.

[0003] Currently, the mainstream screening and diagnosis methods for adolescent depression in clinical practice mostly rely on psychiatrists to make comprehensive subjective judgments by combining consultations and interviews with scores from various psychological and emotional scales. This diagnostic model is highly dependent on the physician's clinical experience and the degree of subjective cooperation of the subject. It is highly subjective and lacks objective quantitative evidence. The completion of scales is easily affected by emotional state, cognitive level, and external environment, which can lead to biased results. At the same time, traditional diagnostic methods are difficult to accurately identify early and insidious lesions of the disease, and there are obvious shortcomings in the timeliness and objectivity of diagnosis.

[0004] With the continuous development of proteomics, mass spectrometry quantitative detection technology, and artificial intelligence modeling and analysis technology, non-invasive and objective diagnosis of mental illnesses based on specific differentially expressed protein biomarkers in human serum has become an emerging research direction. Existing research has confirmed that the abnormal expression of multiple functional proteins in the human body is closely related to the pathogenesis and progression of adolescent depression. However, at present, a mature, stable, standardized, and practically applicable serum protein biomarker joint detection system has not yet been established, and there is also a lack of a dedicated intelligent diagnostic prediction model for adolescent depression based on the joint characteristics of multiple proteins. This makes it impossible to complete an integrated and automated diagnostic process from sample preprocessing, accurate quantification of target proteins, comparison of population differences, to intelligent classification and determination of disease risk.

[0005] Existing diagnostic and analytical equipment and systems generally suffer from problems such as single biomarkers, non-standardized testing procedures, weak model generalization ability, and inconsistent risk grading standards. These limitations make it difficult to balance diagnostic sensitivity, specificity, and clinical applicability, failing to meet the practical application needs of rapid screening in primary healthcare institutions, precise clinical diagnosis in hospitals, and large-scale health screening for adolescents. Therefore, developing a diagnostic and predictive model for adolescent depression based on a combination of specific protein biomarkers, combined with standardized mass spectrometry quantitative detection and logistic regression intelligent modeling, and constructing a supporting integrated intelligent prediction system, will enable non-invasive, rapid, objective, and accurate screening and risk assessment of adolescent depression. This has significant clinical application value and social significance for promoting early screening and diagnosis of adolescent depression and protecting the mental health of adolescents. Summary of the Invention

[0006] In view of the deficiencies in the existing technology, the purpose of this invention is to provide an auxiliary diagnostic and efficacy evaluation system for adolescent depression based on serum protein expression profiles, which can realize the auxiliary diagnosis, condition assessment and objective evaluation of treatment efficacy for adolescent depression.

[0007] The objective of this invention is achieved through the following technical solution: This invention provides an auxiliary diagnostic system for adolescent depression based on serum protein expression profiles, comprising: The data acquisition unit is used to acquire the expression levels of MANDF, NDUFA13, and HYOU1 protein markers in the serum of the subjects. A data processing unit is used to calculate the expression differences of the protein biomarkers relative to healthy controls; The results output unit is used to compare the expression levels of the protein markers with preset reference ranges; the preset range for MANF is 0.0021325~1563.89; the preset range for NDUFA13 is 0.00102~0.5533; and the preset range for HYOU1 is 139.34~1325.5. Compared to the preset reference range, subjects were considered to be at risk of adolescent depression when at least two protein biomarkers were abnormally expressed.

[0008] This invention provides an application of a combination of protein biomarkers in constructing an auxiliary diagnostic system for adolescent depression; the combination of protein biomarkers includes at least two of MANF, NDUFA13, and HYOU1.

[0009] This invention provides an efficacy evaluation system for treatment methods of adolescent depression, comprising: Upstream data receiving module: After treatment, the expression levels of MANAF, NDUFA13 and HYOU1 protein markers in the patient's serum are obtained; Downstream results generation module: Compares the expression levels of the three obtained protein biomarkers with the expression levels of the corresponding proteins before treatment and the normal reference range; If the expression levels of two or three of the protein markers fall back to the normal reference range and / or show a significant downward trend compared to the expression levels of the corresponding proteins before treatment, the computer determines that the treatment method is effective. If the number of protein biomarkers that return to the normal reference range and show statistically significant differences compared to pre-treatment levels is less than two, the computer determines that the treatment method is ineffective.

[0010] Preferably, the normal reference range for MANF is 0.0021325~1563.89; the normal reference range for NDUFA13 is 0.00102~0.5533; and the normal reference range for HYOU1 is 139.34~1325.5.

[0011] The present invention provides a computer device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor performs unit functions of the auxiliary diagnostic system for adolescent depression described in the above technical solution, or the processor performs unit functions of the efficacy evaluation system described in the above technical solution.

[0012] The present invention provides a computer-readable medium having a computer program stored thereon. When the computer program is executed by a processor, it uses the auxiliary diagnostic system for adolescent depression described in the above technical solution to assess or predict adolescent depression, or uses the efficacy evaluation system described in the above technical solution to evaluate the efficacy of treatment methods for adolescent depression.

[0013] This invention provides a computer program product, including a computer program that, when executed by a processor, uses the adolescent depression auxiliary diagnostic system described above to assess or predict adolescent depression; or uses the efficacy evaluation system described above to evaluate the efficacy of adolescent depression treatment methods.

[0014] This invention provides an application of a combination of protein biomarkers in constructing an efficacy evaluation system for treatment methods for adolescent depression; the combination of protein biomarkers includes at least two of MANF, NDUFA13, and HYOU1.

[0015] The beneficial effects of this invention are: This invention provides an auxiliary diagnostic system for adolescent depression based on serum protein expression profiles, comprising: a data acquisition unit for acquiring the expression levels of MANF, NDUFA13, and HYOU1 protein markers in the serum of a subject; a data processing unit for calculating the expression differences of the protein markers relative to healthy controls; and a result output unit for comparing the expression levels of the protein markers with preset reference ranges; wherein the preset range for MANF is 0.0021325~1563.89; the preset range for NDUFA13 is 0.00102~0.5533; and the preset range for HYOU1 is 139.34~1325.5; and when at least two protein markers are abnormally expressed compared to the preset reference ranges, the subject is determined to have a risk of adolescent depression. This invention utilizes a combination of MANF, NDUFA13, and HYOU1 protein biomarkers to construct an auxiliary diagnostic system for adolescent depression. Compared to single-indicator detection, this system offers superior identification efficiency, effectively improving diagnostic sensitivity and specificity, and reducing misdiagnosis and missed diagnosis. Furthermore, it establishes quantitative input features based on objective protein expression data, abandoning the subjective judgment methods of traditional scales and reducing human interference. After sample training and blinded validation, the diagnostic system demonstrates high stability and accuracy. The overall methodology is standardized and compliant, enabling non-invasive, objective, and accurate early screening and risk prediction for adolescent depression. This facilitates widespread clinical application and supports early diagnosis and treatment of adolescent mental illnesses. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the accompanying drawings used in the embodiments will be briefly described below.

[0017] Figure 1 Hierarchical clustering heatmap of differentially expressed proteins between adolescent patients with depression and healthy controls; Figure 2 Heatmap of differential protein hierarchical clustering in the healthy group and before and after acupuncture treatment; Figure 3 Figure showing the changes in the abundance of HYOU1, MANF, and NDUFA13 proteins before and after acupuncture treatment; express P <0.05, express P <0.01, express P <0.001, ns indicates P >0.05; Figure 4 This is a graph showing the changes in HAMD-24 before and after treatment; express P <0.001; Figure 5 This is a ROC curve. Detailed Implementation

[0018] This invention provides an auxiliary diagnostic system for adolescent depression based on serum protein expression profiles, comprising: The data acquisition unit is used to acquire the expression levels of MANDF, NDUFA13, and HYOU1 protein markers in the serum of the subjects. A data processing unit is used to calculate the expression differences of the protein biomarkers relative to healthy controls; The results output unit is used to compare the expression levels of the protein markers with preset reference ranges; the preset range for MANF is 0.0021325~1563.89; the preset range for NDUFA13 is 0.00102~0.5533; and the preset range for HYOU1 is 139.34~1325.5. Compared to the preset reference range, subjects were considered to be at risk of adolescent depression when at least two protein biomarkers were abnormally expressed.

[0019] The gene IDs for MANF, NDUFA13, and HYOU1 in NCBI are 7873, 51079, and 10525, respectively. As an optional embodiment of this invention, when the protein biomarker combination includes two or more of MANF, NDUFA13, and HYOU1, the protein biomarker combination can be MANF and HYOU1, MANF and NDUFA13, NDUFA13 and HYOU1, or MANF, NDUFA13, and HYOU1.

[0020] This invention provides an application of a combination of protein biomarkers in constructing an auxiliary diagnostic system for adolescent depression; the combination of protein biomarkers includes at least two of MANF, NDUFA13, and HYOU1.

[0021] This invention utilizes a combination of MANF, NDUFA13, and HYOU1 protein biomarkers to construct an auxiliary diagnostic system for adolescent depression. Compared to single-indicator detection, this system offers superior identification efficiency, effectively improving diagnostic sensitivity and specificity, and reducing misdiagnosis and missed diagnosis. Furthermore, it establishes quantitative input features based on objective protein expression data, abandoning the subjective judgment methods of traditional scales and reducing human interference. After sample training and blinded validation, the auxiliary diagnostic system demonstrates high stability and accuracy. The overall methodology is standardized and compliant, enabling non-invasive, objective, and accurate early screening and risk prediction for adolescent depression. This facilitates widespread clinical application and supports early diagnosis and treatment of adolescent mental illnesses.

[0022] The present invention provides a computer device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor performs the unit functions of the adolescent depression auxiliary diagnostic system described above.

[0023] The present invention provides a computer-readable medium having a computer program stored thereon. When the computer program is executed by a processor, it uses the adolescent depression auxiliary diagnostic system described above to assess or predict adolescent depression.

[0024] The present invention provides a computer program product, including a computer program that, when executed by a processor, uses the adolescent depression auxiliary diagnostic system described above to assess or predict adolescent depression.

[0025] This invention provides an efficacy evaluation system for treatment methods of adolescent depression, comprising: Upstream data receiving module: After treatment, the expression levels of MANAF, NDUFA13 and HYOU1 protein markers in the patient's serum are obtained; Downstream results generation module: Compares the expression levels of the three obtained protein biomarkers with the expression levels of the corresponding proteins before treatment and the normal reference range; If the expression levels of two or three of the protein markers fall back to the normal reference range or show a significant downward trend compared to the expression levels of the corresponding proteins before treatment, the computer determines that the treatment method is effective. If the number of protein biomarkers that return to the normal reference range and show statistically significant differences compared to pre-treatment levels is less than two, the computer determines that the treatment method is ineffective.

[0026] As an optional embodiment of the present invention, the normal reference range for MANF is 0.0021325~1563.89; the normal reference range for NDUFA13 is 0.00102~0.5533; and the normal reference range for HYOU1 is 139.34~1325.5.

[0027] The present invention provides a computer device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that the processor performs the unit functions of the efficacy evaluation system described above.

[0028] The present invention provides a computer-readable medium having a computer program stored thereon. When the computer program is executed by a processor, it uses the efficacy evaluation system described in the above technical solution to evaluate the efficacy of treatment methods for adolescent depression.

[0029] The present invention provides a computer program product, including a computer program that, when executed by a processor, uses the efficacy evaluation system described above to evaluate the efficacy of treatment methods for adolescent depression.

[0030] This invention provides an application of a combination of protein biomarkers in constructing an efficacy evaluation system for treatment methods for adolescent depression; the protein biomarkers include at least two of MANF, NDUFA13, and HYOU1. As an optional embodiment of this invention, the combination of protein biomarkers can be MANF and NDUFA13, MANF and HYOU1, HYOU1 and NDUFA13, or MANF, NDUFA13, and HYOU1.

[0031] To further illustrate the present invention, the technical solutions provided by the present invention will be described in detail below with reference to the accompanying drawings and embodiments, but these should not be construed as limiting the scope of protection of the present invention.

[0032] Example 1 (1) Subject selection: Nineteen adolescent patients with depression and 20 healthy controls were selected. The patients with depression were aged 10-24 years, met the diagnostic criteria of ICD-10 and DSM-5, and had a HAMD-24 score >20. Serious physical illnesses and other mental disorders were excluded. The basic information of the subjects is shown in Table 1.

[0033] Table 1. Statistical Table of Basic Information of Subjects

[0034] (2) Serum sample collection and processing: 3 mL of fasting venous blood was collected from the subjects. After centrifugation to separate the serum, it was stored at -80℃. SiO2 nanoparticles were added to the serum sample for protein enrichment. After centrifugation and washing, the sample was resuspended in buffer for later use.

[0035] (3) Protein detection: Using proteomics, 2 mg of SiO2 NPs with a particle size of 1 μm (concentration of 20 mg / mL) was added to 100 μL of serum and incubated with shaking at 25 °C and 1000 rpm for 1 h. After incubation, the supernatant was removed by centrifugation at 4 °C and 10000 rpm for 10 min, and the NPs were washed and resuspended by 300 μL of 0.9% NaCl aqueous solution by pipetting 100 times. This process was repeated three times to remove the soft crown on the surface of the NPs. 25 μL of Tris-HCl (pH=8) was added to the precipitate, followed by 3.5 μL of DTT (dithiothreitol, 100 mM), and the mixture was reacted at 95 °C for 10 min. 30 μL of a mixed solution of 100 mM DTT and 12 M urea (1:9) was added, and the mixture was reacted at 37 °C for 30 min. Subsequently, 3.2 μL of IAA (iodoacetamide, 400 mM) was added, and the mixture was reacted in the dark at room temperature for 30 min. Add Tris-HCl (pH=8) to adjust the urea concentration to below 1M. Add 5 μL of trypsin (200 μg / mL) digestion solution and incubate at 37°C for 14 hours. Terminate the enzymatic digestion with 10% trifluoroacetic acid (TFA) solution, then centrifuge at 10,000 rpm for 10 min and collect the supernatant. Concentrate the solution to 90–100 μL using a vacuum desiccator at 40°C. Activate the peptide desalting tip (PierceC18) with 50% ACN aqueous solution and wash with 0.1% TFA. Slowly aspirate the peptide solution using a pipette to adsorb the peptide onto the tip. Rinse twice rapidly with washing buffer, then vigorously elute the peptide with 100 μL of elution buffer. Dry completely at 40°C using a vacuum concentrator to obtain peptide powder. 100 μL of formic acid aqueous solution (0.1%) was added to the peptide powder to dissolve it. The solution was then centrifuged at 10,000 rpm for 10 minutes at 4 °C. The supernatant was extracted for subsequent LC-MS / MS detection and analysis. Data collection for the DIA method was performed using a Thermo Scientific Orbitrap Exploris 480. For liquid chromatography, a C18 high-performance liquid chromatography column (75 μm × 2 cm, 3 μm, nanoViper C18, Thermo Scientific) was used. The peptide was separated at a flow rate of 300 nL / min. A separation gradient of 65 minutes was used, as shown below: the concentration of buffer B (buffer A was water, buffer B was acetonitrile solution) was increased from 3% to 8% in 1 minute, then gradually increased from 8% to 35% over the next 51 minutes, then increased from 35% to 95% over 4 minutes, and finally held at the maximum concentration for 9 minutes. The DIA strategy was used for tandem mass spectrometry detection, with a scan range of 350 to 1500 m / z. The primary resolution was set to 60,000, and the maximum injection time was set to 50 ms. The secondary resolution was set to the primary-secondary resolution, and the maximum injection time was set to 54 ms.tMS2 was selected for precursor ion fragmentation, and mass spectrometry data were collected using Xcalibur software (Thermo Scientific, USA). For raw proteomic spectral data analysis, protein spectra were analyzed using Spectronaut 18 software to obtain qualitative and quantitative data for each protein.

[0036] Serum samples were analyzed to obtain protein expression profiles.

[0037] (4) Differential protein screening: Data screening, intergroup comparisons, and differential analysis were performed using R (R version 4.5.1) via the ggplot2, rstatix, tidyverse, circlize, ComplexHeatmap, and ggrepel software packages. The screening criterion was set as |log2FC| > 0.58, and differentially expressed proteins were obtained. A heatmap comparing differentially expressed proteins between the adolescent depression group and healthy volunteers is shown below. Figures 1-3 As shown in Tables 2-3, the expression abundance of MANF, NDUFA13, and HYOU1 proteins is detailed in these tables.

[0038] Table 2. Protein expression abundance of MANF, NDUFA13, and HYOU1 in 19 adolescent patients with depression.

[0039] Table 3. Protein expression abundance of MANAF, NDUFA13, and HYOU1 in 20 healthy controls

[0040] The results showed that MANAF, NDUFA13, and HYOU1 were abnormally expressed in patients with depression, such as Figures 2-3 The results show the results of the healthy control group and before acupuncture, where the results before acupuncture are the relevant indicators of adolescent patients with depression before treatment.

[0041] (5) Evaluation of therapeutic effect: Interventional treatment was conducted on 19 adolescent patients with depression. The intervention method was as follows: After routine disinfection of the acupoints, the physician used 0.25×40 mm disposable sterile acupuncture needles to achieve the desired sensation (deqi), and retained the needles for 30 minutes. Treatment was administered 2-3 times per week for a total of 8 sessions. After the intervention, the HAMD-24 scores of the 19 adolescent patients with depression were assessed, and the results were as follows: Figure 4 As shown.

[0042] After intervention, the protein expression levels of 19 adolescent patients with depression were detected again using steps (2) and (3). The results are as follows: Figures 2-3 As stated above. Figures 2-3 The study included the detection results of relevant protein levels in 19 adolescent patients with depression after acupuncture. The results showed that the expression levels of these proteins reverted to those of healthy controls and were significantly correlated with HAMD, indicating consistency with clinical symptom improvement.

[0043] The above analysis reveals that the expression levels of MANF, NDUFA13, and HYOU1 proteins in the serum of adolescents with depression exhibit significant abnormalities, showing clear differences compared to healthy individuals. These proteins could serve as potential specific serum protein markers for auxiliary diagnosis of adolescent depression. After acupuncture intervention, the expression levels of these differentially expressed proteins significantly reverted to those of the healthy control group. Furthermore, the protein expression trend was highly synchronized with the clinical efficacy of improved HAMD-24 depression scale scores in patients, suggesting that these protein expression changes are related to changes in adolescent depression. These proteins can be used for early disease screening, auxiliary clinical diagnosis, and assessment of disease severity. They can also serve as objective molecular indicators to evaluate the therapeutic effect of acupuncture intervention in adolescent depression, providing reliable protein molecular experimental evidence for the clinical diagnosis, disease monitoring, and efficacy assessment of adolescent depression.

[0044] Example 2 To evaluate the auxiliary diagnostic value of MANF, NDUFA13, and HYOU1 for adolescent depression, ROC curve analysis was performed using protein expression data from adolescent depression patients and healthy controls included in Example 1. The results are as follows: Figure 5 A summary table of diagnostic test efficacy is shown in Table 4. The results show that both individual and combined models of each protein have good diagnostic capabilities, with the combined model exhibiting the highest AUC value, indicating that multi-protein combined detection can improve diagnostic sensitivity and specificity.

[0045] Table 4 Summary of Diagnostic Test Efficacy

[0046] Differential diagnosis 1. Sampling A separate external validation population was recruited, and a total of 25 subjects were included as blinded differential diagnosis validation samples, including 12 adolescent patients with depression and 13 healthy controls.

[0047] The enrolled adolescents with depression ranged in age from 10 to 24 years. All patients were diagnosed strictly according to the dual diagnostic criteria of ICD-10 and DSM-5, and had a HAMD-24 score >20. Individuals with serious physical illnesses, other mental illnesses, or endocrine and metabolic disorders were excluded. Healthy controls had no history of mental illness, normal emotional state, and no clinical manifestations related to depression. All validation subjects provided informed consent. Fasting peripheral venous blood was collected in the morning to prepare serum samples. The sample collection time, blood collection procedures, and serum separation and cryopreservation conditions were completely consistent with those of the aforementioned modeling experiment to eliminate interference from differences in sample processing procedures.

[0048] 2. The information of the verification samples is shown in Table 5.

[0049] Table 5 Information on the validation samples

[0050] 3. Differential Diagnostic Test Procedure The relative expression levels of three target proteins, MANF, NDUFA13, and HYOU1, in serum samples were verified using enzyme-linked immunosorbent assay (ELISA). The results are shown in Table 6.

[0051] Table 6. Relative expression levels of target proteins in 25 subjects

[0052] Further analysis of the above data revealed that the combination of three target proteins, MANF, NDUFA13, and HYOU1, as biomarkers for the auxiliary diagnosis of adolescent depression has excellent diagnostic ability.

[0053] Example 3 A serum protein expression profile-based auxiliary diagnostic system for adolescent depression includes a system that uses the expression of three target proteins, MANF, NDUFA13, and HYOU1, in an individual's serum as the core detection and evaluation object. Through an upstream data receiving module and a downstream result generation module, it can accurately determine whether the subject has adolescent depression, providing objective and non-invasive molecular evidence for clinical auxiliary diagnosis, and completing risk assessment without relying on scale scores.

[0054] (a) Upstream data receiving module 1. Sample Acquisition Module Sample collection: Collect 3 mL of fasting venous blood from the subject in the morning, let it stand at room temperature for 30 min, then centrifuge at 4℃ and 3000 rpm for 10 min to separate the serum, and freeze at -80℃ for later use.

[0055] Information Recording: Synchronously record basic individual information, including age, gender, BMI, history of mental illness, history of physical illness, sample collection time, etc. 2. Standardized Sample Processing Module (1) Serum separation: The frozen blood sample was warmed to 4°C, placed in a centrifuge, and centrifuged at 4°C and 3000 rpm for 10 min. The supernatant serum was collected for later use. (2) Protein enrichment and purification: Take 100 μL of serum, add 2 mg of SiO2 nanoparticles with a particle size of 1 μm (concentration 20 mg / mL), and incubate at 25℃ and 1000 rpm for 1 h; centrifuge at 4℃ and 10000 rpm for 10 min to remove the supernatant, wash and resuspend with 300 μL of 0.9% NaCl aqueous solution by blowing 100 times, repeat 3 times to remove the soft crown on the surface of the particles; (3) Protein denaturation and enzymatic digestion: Add 25 μL Tris-HCl (pH=8) and 3.5 μL 100 mM DTT to the precipitate and react at 95 °C for 10 min; add 30 μL of a mixture of 100 mM DTT and 12 M urea (volume ratio 1:9) and incubate at 37 °C for 30 min; add 3.2 μL 400 mM IAA and react at room temperature in the dark for 30 min; adjust the urea concentration to below 1 M with Tris-HCl, add 5 μL 200 μg / mL trypsin, and incubate at 37 °C for 14 h; (4) Peptide treatment: Add 10% TFA solution to terminate enzymatic hydrolysis, centrifuge at 10000rpm for 10min to collect the supernatant, and concentrate under vacuum at 40℃ to 90~100μL; after desalting with Pierce C18 peptide desalting tip, dry under vacuum at 40℃ to obtain peptide powder; add 100μL of 0.1% formic acid aqueous solution to dissolve, centrifuge at 4℃ and 10000rpm for 10min, and take the supernatant for subsequent detection.

[0056] 3. LC-MS / MS standardized testing module Instrument parameters: Thermo Scientific Orbitrap Exploris 480 mass spectrometer was used, equipped with a C18 high performance liquid chromatography column (75μm×2 cm, 3μm, nanoViper C18). Detection parameters: Peptide separation flow rate 300 nL / min, gradient elution for 65 minutes (buffer A is water, buffer B is acetonitrile, the percentage of buffer B is increased from 3% to 8% in 1 minute, then gradually increased from 8% to 35% in the next 51 minutes, then increased from 35% to 95% in 4 minutes, and finally held at the maximum concentration for 9 minutes).

[0057] DIA detection strategy: Level 1 scan range 350~1500 m / z, resolution 60000, maximum injection time 50ms; Level 2 resolution is the primary and secondary resolution, maximum injection time 54ms, tMS2 is selected for precursor ion cleavage. Data acquisition: Xcalibur software collects raw mass spectrometry data to ensure that the detection parameters of individual samples are completely consistent with those in the modeling stage (healthy controls and adolescent patients with depression) to avoid systematic errors.

[0058] 4. Individual target protein quantification module Mass spectrometry data were analyzed using Spectronaut 18 software to target and extract the relative expression levels of three proteins: MANF, NDUFA13, and HYOU1. Output the specific expression values ​​of the three target proteins for each individual, forming an "Individual Target Protein Expression Quantitative Report".

[0059] (ii) Downstream Result Generation Module 1. Construct submodules by referring to the standard library. Built-in standard database: preset reference ranges, specifically: the preset range of MANF is 0.0021325~1563.89; the preset range of NDUFA13 is 0.00102~0.5533; the preset range of HYOU1 is 139.34~1325.5.

[0060] The preset reference range was derived from the detection results of serum samples from healthy control groups. The same proteomics detection platform as in Example 1 was used to detect the samples from the healthy control group, and the expression range of each protein in the healthy population was statistically analyzed. The preset range was determined using the minimum to maximum values ​​from the detection results of the healthy control group.

[0061] Table 7 shows the differences in target protein characteristics between healthy individuals and adolescents with depression.

[0062] Table 7. Target protein population differential characteristics

[0063] 2. Submodule for determining individual expression differences Single-protein differential analysis: The expression levels of three target proteins in an individual are compared with the reference range of healthy individuals. Combined with the population expression trend of significant upregulation, the expression status of each protein is determined (Example: If the expression level of MANF in an individual is significantly higher than the upper limit of the 95% confidence interval of healthy individuals, then it is significantly high expression). Expression status classification: clearly define the results: significantly high expression (meeting a significant upregulation trend), normal expression (not reaching the difference threshold or within the reference range of healthy people); Comprehensive difference assessment: Based on the degree of deviation of the above protein expression levels from the normal reference range, it is determined whether the subject is in a depressive state. The number of target proteins with significantly high expression is counted. When at least two of the proteins MANF, NDUFA13 and HYOU1 are detected to be abnormally expressed, the subject is determined to be in a depressive state.

[0064] Example 4 An efficacy evaluation system for a treatment method for adolescent depression includes a system that uses the expression of three target proteins, MANF, NDUFA13, and HYOU1, in an individual's serum as the core detection and evaluation object. Through a data acquisition unit and a result output unit, the system can accurately determine whether the treatment method is effective for adolescents with depression after treatment, and provide an objective and non-invasive molecular evaluation standard for the treatment of adolescent depression.

[0065] (a) Upstream data receiving module 1. Sample Acquisition Module Sample collection: Before treatment, the expression levels of three target proteins, MANF, NDUFA13, and HYOU1, were measured in patients. After treatment, 3 mL of fasting venous blood was collected from each subject in the morning. After standing at room temperature for 30 min, the serum was separated by centrifugation at 3000 rpm for 10 min at 4°C and then frozen at -80°C for later use.

[0066] Information Recording: Synchronously record basic individual information, including age, gender, BMI, history of mental illness, history of physical illness, sample collection time, etc. 2. Standardized Sample Processing Module (1) Serum separation: The frozen blood sample was warmed to 4°C, placed in a centrifuge, and centrifuged at 4°C and 3000 rpm for 10 min. The supernatant serum was collected for later use. (2) Protein enrichment and purification: Take 100 μL of serum, add 2 mg of SiO2 nanoparticles with a particle size of 1 μm (concentration 20 mg / mL), and incubate at 25℃ and 1000 rpm for 1 h; centrifuge at 4℃ and 10000 rpm for 10 min to remove the supernatant, wash and resuspend with 300 μL of 0.9% NaCl aqueous solution by blowing 100 times, repeat 3 times to remove the soft crown on the surface of the particles; (3) Protein denaturation and enzymatic digestion: Add 25 μL Tris-HCl (pH=8) and 3.5 μL 100 mM DTT to the precipitate and react at 95 °C for 10 min; add 30 μL of a mixture of 100 mM DTT and 12 M urea (volume ratio 1:9) and incubate at 37 °C for 30 min; add 3.2 μL 400 mM IAA and react at room temperature in the dark for 30 min; adjust the urea concentration to below 1 M with Tris-HCl, add 5 μL 200 μg / mL trypsin, and incubate at 37 °C for 14 h; (4) Peptide treatment: Add 10% TFA solution to terminate enzymatic hydrolysis, centrifuge at 10000rpm for 10min to collect the supernatant, and concentrate under vacuum at 40℃ to 90~100μL; after desalting with Pierce C18 peptide desalting tip, dry under vacuum at 40℃ to obtain peptide powder; add 100μL of 0.1% formic acid aqueous solution to dissolve, centrifuge at 4℃ and 10000rpm for 10min, and take the supernatant for subsequent detection.

[0067] 3. LC-MS / MS standardized testing module Instrument parameters: Thermo Scientific Orbitrap Exploris 480 mass spectrometer was used, equipped with a C18 high performance liquid chromatography column (75μm×2 cm, 3μm, nanoViper C18). Detection parameters: Peptide separation flow rate 300 nL / min, gradient elution for 65 minutes (buffer A is water, buffer B is acetonitrile, the percentage of buffer B is increased from 3% to 8% in 1 minute, then gradually increased from 8% to 35% in the next 51 minutes, then increased from 35% to 95% in 4 minutes, and finally held at the maximum concentration for 9 minutes).

[0068] DIA detection strategy: Level 1 scan range 350~1500 m / z, resolution 60000, maximum injection time 50ms; Level 2 resolution is the primary and secondary resolution, maximum injection time 54ms, tMS2 is selected for precursor ion cleavage. Data acquisition: Xcalibur software collects raw mass spectrometry data to ensure that the detection parameters of individual samples are completely consistent with those in the modeling stage (healthy controls and adolescent patients with depression) to avoid systematic errors.

[0069] 4. Individual target protein quantification module Mass spectrometry data were analyzed using Spectronaut 18 software to target and extract the relative expression levels of three proteins: MANF, NDUFA13, and HYOU1. Output the specific expression values ​​of the three target proteins for each individual, forming an "Individual Target Protein Expression Quantitative Report".

[0070] (ii) Downstream Result Generation Module 1. Construct submodules by referring to the standard library. Built-in standard database: preset normal reference ranges, specifically: the normal reference range of MANF is 0.0021325~1563.89; the normal reference range of NDUFA13 is 0.00102~0.5533; the normal reference range of HYOU1 is 139.34~1325.5.

[0071] Meanwhile, the expression levels of each protein before treatment were used as a reference standard.

[0072] The results of the differential expression of target proteins before and after treatment are shown in Table 8.

[0073] Table 8. Target protein population differential characteristics

[0074] 2. Submodule for determining individual expression differences Single protein differential analysis: The expression levels of three target proteins, MANF, NDUFA13 and HYOU1, in individuals were compared with the reference range in healthy individuals and the expression levels of the corresponding proteins before treatment.

[0075] When at least two of the MANAF, NDUFA13 and HYOU1 protein markers meet one of the following conditions: (1) their expression levels revert to the reference range for healthy individuals; and / or (2) their expression levels change statistically significantly compared to pre-treatment levels and revert to the reference range for healthy individuals; The computer then determines that the treatment method is effective.

[0076] If fewer than two protein biomarkers meet the above criteria, the computer determines that the treatment method is ineffective.

[0077] Although the above embodiments have provided a detailed description of the present invention, they are only some embodiments of the present invention, and not all embodiments. People can obtain other embodiments based on these embodiments without creative effort, and these embodiments all fall within the protection scope of the present invention.

Claims

1. A system for auxiliary diagnosis of adolescent depression based on serum protein expression profiles, characterized in that, include: The data acquisition unit is used to acquire the expression levels of MANDF, NDUFA13, and HYOU1 protein markers in the serum of the subjects. A data processing unit is used to calculate the expression differences of the protein biomarkers relative to healthy controls; The results output unit is used to compare the expression levels of the protein markers with preset reference ranges; the preset range for MANF is 0.0021325~1563.89; the preset range for NDUFA13 is 0.00102~0.5533; and the preset range for HYOU1 is 139.34~1325.

5. Compared to the preset reference range, subjects were considered to be at risk of adolescent depression when at least two protein biomarkers were expressed abnormally.

2. The application of a combination of protein biomarkers in constructing an auxiliary diagnostic system for adolescent depression; said combination of protein biomarkers includes at least two of MANF, NDUFA13 and HYOU1.

3. A system for evaluating the efficacy of treatments for adolescent depression, characterized in that, include: Upstream data receiving module: After treatment, the expression levels of MANAF, NDUFA13 and HYOU1 protein markers in the patient's serum are obtained; Downstream results generation module: Compares the expression levels of the three obtained protein biomarkers with the expression levels of the corresponding proteins before treatment and the normal reference range; If the expression levels of two or three of the protein markers fall back to the normal reference range and / or show a significant downward trend compared to the expression levels of the corresponding proteins before treatment, the computer determines that the treatment method is effective. If the number of protein biomarkers that return to the normal reference range and show statistically significant differences compared to pre-treatment levels is less than two, the computer determines that the treatment method is ineffective.

4. The efficacy evaluation system according to claim 3, characterized in that, The normal reference range for MANF is 0.0021325~1563.89; the normal reference range for NDUFA13 is 0.00102~0.5533; and the normal reference range for HYOU1 is 139.34~1325.

5.

5. A computer device, comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that the processor performs the unit functions of the auxiliary diagnostic system for adolescent depression according to claim 1, or the processor performs the unit functions of the efficacy evaluation system according to claim 3 or 4.

6. A computer-readable medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it uses the adolescent depression auxiliary diagnostic system of claim 1 to assess or predict adolescent depression, or uses the efficacy assessment system of claim 3 or 4 to assess the efficacy of adolescent depression treatment methods.

7. A computer program product, comprising a computer program, characterized in that, When executed by a processor, the computer program assesses or predicts adolescent depression using the adolescent depression auxiliary diagnostic system of claim 1; or assesses the efficacy of adolescent depression treatments using the efficacy assessment system of claim 3 or 4.

8. The application of a combination of protein biomarkers in constructing an efficacy evaluation system for treatment methods for adolescent depression; said combination of protein biomarkers includes at least two of MANF, NDUFA13 and HYOU1.

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