WO2023284245A1 - Biomarker and detection reagent for diagnosing depression and predicting therapeutic efficacy of visual cortex targeted repeated transcranial magnetic stimulation - Google Patents
Biomarker and detection reagent for diagnosing depression and predicting therapeutic efficacy of visual cortex targeted repeated transcranial magnetic stimulation Download PDFInfo
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- WO2023284245A1 WO2023284245A1 PCT/CN2021/138036 CN2021138036W WO2023284245A1 WO 2023284245 A1 WO2023284245 A1 WO 2023284245A1 CN 2021138036 W CN2021138036 W CN 2021138036W WO 2023284245 A1 WO2023284245 A1 WO 2023284245A1
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Definitions
- the invention belongs to the field of biotechnology detection, and in particular relates to a biomarker and a detection reagent for the diagnosis of depression and the curative effect of repeated transcranial magnetic stimulation on the targeted visual cortex.
- Repetitive transcranial magnetic stimulation is a form of physical therapy.
- the target of repetitive transcranial magnetic stimulation therapy is the left or (and) right dorsolateral prefrontal cortex, and the visual cortex (occipital lobe) is a new stimulation target.
- studies have shown that not all patients are sensitive to TMS, and there is no technical means to determine whether a patient is sensitive to repetitive TMS before treatment.
- the present invention provides a biomarker that can be used to assess the prevalence of depression and evaluate the therapeutic efficacy to solve the problem that depression has no objective biomarkers for diagnosis and evaluation of therapeutic efficacy.
- One aspect of the present invention provides a detection reagent for evaluating the prevalence of depression in a subject or predicting the therapeutic effect of repetitive transcranial magnetic stimulation targeting the visual cortex on depression.
- the depression biomarker composition is selected from circular RNA DYM (circDYM), antithrombin III (antithrombin III, AT III), C-reactive protein (C-reactive protein, CRP), fibroblast growth factor 9 (fibroblast growth factor 9, FGF9), vitamin D binding protein (VDBP) and inter-alpha-trypsin inhibitor heavy chain H4 (inter-alpha-trypsin inhibitor heavy chain H4, ITIH4) combination, or circular RNA DYM and anticoagulant Combination of blood enzyme III;
- the depression biomarker composition is selected from circular RNA DYM, antithrombin III, C-reactive protein, fibroblast growth factor 9, vitamin D binding protein or inter-alpha-trypsin inhibitor heavy chain H4.
- the reagents for detecting circular RNA DYM are primers and or probes for PCR detection.
- the reagent for detecting anti-thrombin III is an anti-thrombin III antibody or an ELISA quantitative detection kit for anti-thrombin III.
- the antibodies are preferably monoclonal antibodies.
- the reagent for detecting C-reactive protein is an antibody for C-reactive protein or an ELISA quantitative detection kit for C-reactive protein.
- the antibodies are preferably monoclonal antibodies.
- the reagent for detecting fibroblast growth factor 9 is a fibroblast growth factor 9 ELISA quantitative detection kit.
- the antibodies are preferably monoclonal antibodies.
- the reagent for detecting the vitamin D-binding protein is an antibody to the vitamin D-binding protein or an ELISA quantitative detection kit for the vitamin D-binding protein.
- the antibodies are preferably monoclonal antibodies.
- the reagents for detecting the heavy chain H4 of the inter-alpha-trypsin inhibitor are the antibody of the inter-alpha-trypsin inhibitor and the ELISA quantitative detection kit for the heavy chain H4 of the inter-alpha-trypsin inhibitor.
- the antibodies are preferably monoclonal antibodies.
- the detection reagent can be used for the detection of plasma samples.
- One aspect of the present invention provides a kit for evaluating the prevalence of depression in a subject or predicting the therapeutic effect of repetitive transcranial magnetic stimulation targeting the visual cortex on depression, the kit comprising at least one of the above-mentioned detection reagents.
- One aspect of the present invention provides the application of the above detection reagent in the preparation of a kit for evaluating the prevalence of depression; or the application in the preparation of a kit for predicting the curative effect of repetitive transcranial magnetic stimulation targeting the visual cortex on depression.
- the repetitive transcranial magnetic stimulation targeting the visual cortex is a standardized treatment plan or an individualized treatment plan.
- the detection reagent is a combination of reagents for detecting the following markers: circular RNA DYM, antithrombin III, C-reactive protein, fibroblast growth factor 9, vitamin D binding protein and inter-alpha-trypsin inhibitor
- the application is in the preparation of a kit for evaluating the prevalence of depression.
- the detection reagent is a combination of reagents for detecting the following markers: circular RNA DYM and antithrombin III, and the application is to prepare a kit for predicting the curative effect of repetitive transcranial magnetic stimulation targeting the visual cortex on depression in the application.
- the detection device includes a sample detection module and a prediction module;
- the sample detection module is a reagent for obtaining the expression level of at least one depression biomarker in the subject's plasma sample;
- the depression biomarker is selected from circular RNA DYM, antithrombin III, C-reactive protein, At least one of fibroblast growth factor 9, vitamin D binding protein, or inter-alpha-trypsin inhibitor heavy chain H4; or circular RNA DYM, antithrombin III, C-reactive protein, fibroblast growth A combination of factor 9, vitamin D binding protein, and inter-alpha-trypsin inhibitor heavy chain H4; or a combination of circular RNA DYM and antithrombin III;
- the prediction module can obtain the depression prevalence of the subject according to the data of the expression level of depression biomarkers obtained by the sample detection module, and the calculation model in the prediction module, and or obtain the target visual cortex Prediction of the efficacy of repetitive transcranial magnetic stimulation for depression;
- the calculation model is selected from support vector machine learning model, linear discriminant analysis model, recursive feature removal model, predictive analysis of microarray model, logistic regression model, CART algorithm, flextree algorithm, LART algorithm, random forest algorithm, MART algorithm, machine Learning algorithms, penalized regression methods, and their combinations.
- the method for establishing the calculation model is to use the expression level of depression biomarkers in plasma and the condition of the disease or the response to repeated transcranial magnetic stimulation targeting the visual cortex as parameter sample data, through machine learning method to perform calculations to obtain calculation models.
- the establishment method of the calculation model is to use the expression level of depression biomarkers in plasma and the condition of the disease or the response to repeated transcranial magnetic stimulation therapy targeting the visual cortex as parameter sample data, and the support vector The machine was trained to obtain a support vector machine model for predicting depression based on the expression level data of depression biomarkers in plasma or for predicting the response to repetitive transcranial magnetic stimulation therapy targeting the visual cortex.
- sample detection module includes the above-mentioned detection reagent or the above-mentioned kit.
- the depression biomarker is preferably a combination of circular RNA DYM, antithrombin III, C-reactive protein, fibroblast growth factor 9, vitamin D binding protein and inter-alpha-trypsin inhibitor heavy chain H4 .
- the depression biomarker is preferably a combination of circular RNA DYM and antithrombin III.
- the plasma samples come from subjects who have not undergone treatment for depression, or subjects who have undergone repeated transcranial magnetic stimulation targeting the visual cortex.
- the response to the repetitive transcranial magnetic stimulation targeting the visual cortex refers to the subject's response to the repetitive transcranial magnetic stimulation targeting the visual cortex for the treatment of depression within 1-60 days after treatment, for example, whether the depression symptoms Reduced, alleviated or disappeared. It is further preferred that the subject treats depression with repetitive transcranial magnetic stimulation targeting the visual cortex within 5-28 days after treatment.
- the repetitive transcranial magnetic stimulation targeting the visual cortex is a standardized treatment plan or an individualized treatment plan.
- Yet another aspect of the present invention provides a depression biomarker selected from circular RNA DYM, antithrombin III, C-reactive protein, fibroblast growth factor 9, vitamin D binding protein , at least one of the meta-alpha-trypsin inhibitor heavy chain H4.
- compositions of depression biomarkers are circular RNA DYM, antithrombin III, C-reactive protein, fibroblast growth factor 9, vitamin D binding protein and Combination of inter-alpha-trypsin inhibitor heavy chain H4, or combination of circular RNA DYM and antithrombin III.
- Another aspect of the present invention provides the application of a depression biomarker or a combination of depression biomarkers as a biomarker for assessing the prevalence of depression;
- the depression biomarker is selected from circular RNA DYM, antithrombin III, C-reactive protein, fibroblast growth factor 9, vitamin D binding protein or inter-alpha-trypsin inhibitor heavy chain H4;
- the composition of the depression biomarker is circular RNA DYM, antithrombin III, C reactive protein, fibroblast growth factor 9, vitamin D binding protein and inter-alpha-trypsin inhibitor heavy chain H4 combination, or a combination of circular RNA DYM and antithrombin III.
- Another aspect of the present invention provides the application of a depression biomarker or a combination of depression biomarkers as a biomarker for predicting the therapeutic effect of repetitive transcranial magnetic stimulation targeting the visual cortex on depression;
- the depression biomarker is selected from circular RNA DYM, antithrombin III, C-reactive protein, fibroblast growth factor 9, vitamin D binding protein or inter-alpha-trypsin inhibitor heavy chain H4;
- the composition of the depression biomarker is circular RNA DYM, antithrombin III, C reactive protein, fibroblast growth factor 9, vitamin D binding protein and inter-alpha-trypsin inhibitor heavy chain H4 combination, or a combination of circular RNA DYM and antithrombin III.
- the repetitive transcranial magnetic stimulation targeting the visual cortex is a standardized treatment plan or an individualized treatment plan.
- Another aspect of the present invention provides a method for assessing depression, said method comprising the steps of:
- step 2) According to the data set obtained in step 1) and the predictive calculation model, the depression prevalence of the subject is obtained;
- the predictive calculation model is selected from a support vector machine learning model, a linear discriminant analysis model, a recursive feature removal model, a predictive analysis of a microarray model, a logistic regression model, a CART algorithm, a flextree algorithm, a LART algorithm, a random forest algorithm, a MART algorithm, Machine learning algorithms, penalized regression methods and their combinations;
- the depression biomarker is selected from circular RNA DYM, antithrombin III, C-reactive protein, fibroblast growth factor 9, vitamin D binding protein, inter-alpha-trypsin inhibitor heavy chain H4;
- composition of the depression biomarker is selected from circular RNA DYM, antithrombin III, C-reactive protein, fibroblast growth factor 9, vitamin D binding protein, inter-alpha-trypsin inhibitor heavy chain H4 A combination of at least one of them.
- the establishment method of the predictive calculation model is to use the expression level of depression biomarkers in plasma and the condition of the disease as parameter sample data, and perform calculations by machine learning methods to obtain the calculation model.
- the establishment method of the predictive calculation model is to use the expression level of the depression biomarkers in plasma and the condition of the disease as parameter sample data, train the support vector machine, and obtain the Support vector machine models for prediction of depression or response to repetitive transcranial magnetic stimulation therapy targeting the visual cortex based on expression level data in plasma.
- composition of the depression biomarkers is preferably circular RNA DYM, antithrombin III, C-reactive protein, fibroblast growth factor 9, vitamin D binding protein and inter-alpha-trypsin inhibitor Combination of heavy chain H4.
- the subject's blood sample is the plasma sample of the subject before treatment.
- Another aspect of the present invention provides a method for predicting the therapeutic effect of depression through repetitive transcranial magnetic stimulation of the visual cortex, the method comprising the following steps:
- step 2) According to the data set obtained in step 1) and the predictive calculation model, the depression prevalence of the subject is obtained;
- the predictive calculation model is selected from a support vector machine learning model, a linear discriminant analysis model, a recursive feature removal model, a predictive analysis of a microarray model, a logistic regression model, a CART algorithm, a flextree algorithm, a LART algorithm, a random forest algorithm, a MART algorithm, Machine learning algorithms, penalized regression methods and their combinations;
- the depression biomarker is selected from circular RNA DYM, antithrombin III, C-reactive protein, fibroblast growth factor 9, vitamin D binding protein, inter-alpha-trypsin inhibitor heavy chain H4;
- composition of the depression biomarker is selected from circular RNA DYM, antithrombin III, C-reactive protein, fibroblast growth factor 9, vitamin D binding protein, inter-alpha-trypsin inhibitor heavy chain H4 A combination of at least one of them.
- the establishment method of the predictive calculation model is to use the expression level of depression biomarkers in plasma and the condition of the disease or the response to repeated transcranial magnetic stimulation targeting the visual cortex as parameter sample data, through the machine
- the learning method performs calculations to obtain a calculation model.
- the establishment method of the predictive calculation model is to use the expression level of depression biomarkers in plasma and the condition of the disease or the response to repeated transcranial magnetic stimulation targeting the visual cortex as parameter sample data, to support
- the vector machine was trained to obtain a support vector machine model for predicting depression based on the expression level data of depression biomarkers in plasma or for predicting the response to repetitive transcranial magnetic stimulation therapy targeting the visual cortex.
- composition of the depression biomarkers is preferably circular RNA DYM, antithrombin III, C-reactive protein, fibroblast growth factor 9, vitamin D binding protein and inter-alpha-trypsin inhibitor Combination of heavy chain H4.
- the blood sample of the subject is the plasma sample of the subject before no treatment or the plasma sample of the subject after repeated transcranial magnetic stimulation treatment targeting the visual cortex.
- the repetitive transcranial magnetic stimulation targeting the visual cortex is a standardized treatment plan or an individualized treatment plan.
- the present invention provides a variety of biomarkers for diagnosing depression and predicting therapeutic effects, providing an objective standard for the diagnosis and treatment of depression, a mental disease.
- the biomarker of the present invention can be detected through plasma, and the detection method is simple.
- the present invention achieves higher accuracy through the combination of multiple biomarkers.
- the combination of biomarkers of the present invention can not only realize the diagnosis of depression, but also realize the prediction of the treatment effect, which can greatly improve the treatment efficiency and reduce the suffering of patients.
- Figure 1 is a flowchart of neuronavigation VC-rTMS antidepressant treatment trial.
- MDD stands for depression
- MRI magnetic resonance imaging
- VC stands for sensory cortex
- rTMS stands for repetitive transcranial magnetic stimulation
- HAMD-24 stands for 24-item Hamilton Depression Rating Scale.
- Figure 2 is a comparison of plasma circDYM expression levels in the normal control group, the MDD patient group, and the three subgroups of MDD at baseline. From left to right are NC group, MDD group, individualized treatment group, standardized treatment group and sham treatment group. Among them, circDYM stands for circular RNA DYM; FC stands for fold change; NC stands for normal control; MDD stands for depression.
- Figure 3 is a comparison of plasma circDYM expression between normal controls and MDD patients after individualized, standardized and sham treatments.
- Figure 4 shows the relationship between circDYM expression level and neuropsychological assessment in MDD patients at baseline. 1) circDYM expression level was positively correlated with HAMD-24 score; 2) circDYM expression level was positively correlated with HAMD-24 cognitive impairment factor score; 3) circDYM expression level was positively correlated with BSI-CV-C score.
- BSI-CV-C represents the Chinese version of the Beck Suicide Ideation Inventory—the last week.
- Figure 5 is the ROC curve for identifying MDD and predicting the antidepressant efficacy of VC-rTMS by plasma circDYM expression level at baseline.
- ROC curve represents the receiver operating characteristic curve; AUC represents the area under the curve; 95% CI represents the 95% confidence interval.
- Figure 6 shows the comparison results of the expression levels of the four proteins in the NC group and the MDD group at baseline. Among them, 1) comparison of CRP expression level (mg/L); 2) comparison of ATIII expression level (mg/L); 3) comparison of ITIH4 expression level (ng/mL); 4) comparison of VDB expression level ( ⁇ g/mL).
- CRP stands for C-reactive protein
- ATIII stands for antithrombin III
- ITIH4 stands for inter-alpha-trypsin inhibitor heavy chain H4
- VDB stands for vitamin D-binding protein
- NC stands for normal control
- MDD stands for depression.
- Figure 7 is a comparison of the expression levels of four candidate proteins before and after individualized/standardized VC-rTMS and sham treatment. 1) Comparison of CRP expression level (mg/L); 2) Comparison of ATIII expression level (mg/L); 3) Comparison of ITIH4 expression level (ng/mL); 4) Comparison of VDB expression level ( ⁇ g/mL).
- CRP stands for C-reactive protein
- ATIII stands for antithrombin III
- ITIH4 stands for inter-alpha-trypsin inhibitor heavy chain H4
- VDB stands for vitamin D connexin.
- Figure 8 shows the relationship between the change in ATIII expression level (mg/L) and the neuropsychological assessment score before and after individualized VC-rTMS treatment.
- 1) ATIII change value (mg/L) was positively correlated with HAMD-24 deduction value
- 2) ATIII change value (mg/L) was positively correlated with SDS deduction value
- 3) ATIII change value (mg/L) was positively correlated with SDS deduction value
- SAS scores were positively correlated
- ATIII changes (mg/L) were positively correlated with BHS scores
- AMD-24 stands for 24-item Hamilton Depression Rating Scale
- SDS stands for Self-Rating Depression Scale
- SAS stands for Self-Rating Anxiety Scale
- BHS stands for Baker Hopelessness Scale
- ATIII stands for Antithrombin III.
- Figure 9 shows the interaction between the ATIII change value (mg/L) before and after individualized VC-rTMS treatment and the family APGAR score on the SAS score reduction value.
- family APGAR stands for Family Functioning Questionnaire
- ATIII stands for Antithrombin III
- SAS stands for Self-Rating Anxiety Scale.
- Figure 10 is the ROC curve for evaluating the expression level of ATIII and predicting the antidepressant efficacy in the individualized VC-rTMS treatment group.
- AUC stands for area under the curve; 95% CI stands for 95% confidence interval.
- Figure 11 is the ROC curve for evaluating ATIII expression levels and predicting antidepressant efficacy in the standardized VC-rTMS treatment group.
- AUC stands for area under the curve; 95% CI stands for 95% confidence interval.
- Figure 12 is a comparison of serum FGF9 expression levels in the normal control group, the MDD patient group and the three subgroups of MDD at baseline.
- FGF9 stands for fibroblast growth factor 9
- NC stands for normal control
- MDD stands for depression.
- Figure 13 is a comparison of serum FGF9 expression levels before and after individualized/standardized VC-rTMS and sham treatment. Wherein, FGF9 stands for fibroblast growth factor 9.
- Figure 14 is a comparison of serum FGF9 expression levels in the response group and non-response group before and after VC-rTMS treatment.
- FGF9 stands for fibroblast growth factor 9.
- Figure 15 shows the relationship between serum FGF9 expression level and neuropsychological assessment in MDD patients at baseline. Among them, 1) FGF9 expression level (pg/mL) was negatively correlated with HAMA score; 2) FGF9 expression level (pg/mL) was negatively correlated with SDS score.
- HAMA stands for Hamilton Anxiety Scale; SDS stands for Self-Rating Depression Scale; FGF9 stands for Fibroblast Growth Factor 9.
- Figure 16 shows the relationship between the change of serum FGF9 expression and the HAMA score after individualized VC-rTMS treatment.
- HAMA stands for Hamilton Anxiety Scale
- FGF9 stands for Fibroblast Growth Factor 9.
- FIG. 17 is the ROC curve for identifying MDD by the serum FGF9 expression level in the baseline period.
- the ROC curve represents the receiver operating characteristic curve
- AUC represents the area under the curve
- 95% CI represents the 95% confidence interval.
- Example 1 Predictive value of plasma circular RNA DYM on antidepressant efficacy of repetitive transcranial magnetic stimulation (VC-rTMS) targeting visual cortex
- NC group unaffected normal people
- 73 MDD patients were included in the study.
- the 73 MDD patients were divided into 3 groups, individualized group, standardized group and sham treatment group, with 24 people and 28 people respectively. people and 21 people.
- the individualized group received individualized repetitive transcranial magnetic stimulation for visual cortex
- the standardized group received standardized repetitive transcranial magnetic stimulation for visual cortex
- the sham treatment group received no repetitive transcranial magnetic stimulation for visual cortex.
- Clinical information collection and multidimensional neuropsychological assessment were performed immediately after the subjects were enrolled.
- the subjects were then arranged for venous blood collection and brain MRI scans, and the MDD patients were randomly assigned to individualized, standardized and sham treatment groups after the MRI scans were completed.
- the researchers Based on the T1-weighted images, the researchers used Brainsight (Brainbox, UK) software to reconstruct the three-dimensional brain structure of the patients, and extracted the peak point coordinates of the significant activation of fast and slow stimuli in the occipital lobe during the task-state fMRI scanning of patients in the individualized group as individualized data.
- the near-infrared navigation system (Rogue Research Inc., the United States and Canada) was used to precisely locate the above coordinate points, and then rTMS treatment was started twice a day for 5 consecutive days.
- the blood sample was mixed with K 2 EDTA, and the plasma separation was completed within 2 hours.
- the specific operation steps were as follows: (1) Anticoagulant tube 2000g, refrigerated and centrifuged at 4°C for 10 minutes, and the obtained supernatant was transferred to a new centrifuge tube, Be careful not to absorb the blood cells in the lower layer, so as not to contaminate the plasma; (2) Centrifuge tubes at 12000g, 4°C for 10 minutes to remove platelets and cell debris, extract the supernatant to obtain plasma samples, store in -80°C in 500 ⁇ L/tube Refrigerator for spare.
- RNA in plasma was extracted using miRNeasy Serum/Plasma Kit (Qiagen, Germany). The specific operation steps are as follows:
- step (6) Repeat step (6) until the remaining sample mixture is completely centrifuged;
- RNA molecules were reverse transcribed into complementary DNA (complementary DNA, cDNA) molecules using HiScript Q RT SuperMix for qPCR Kit (Vazyme, China). The specific operation steps are as follows:
- cDNA was amplified using AceQ qPCR SYBR Green Master Mix (Vazyme, China).
- the primer sequences are shown in Table 1, and the specific operation steps are as follows:
- PCR polymerase chain reaction
- GAPDH glyceraldehyde-3-phosphate dehydrogenase
- circDYM circular RNA DYM.
- NC received fasting venous blood collection after enrollment, and MDD patients received two blood sample collections at baseline and after treatment, and real-time polymerase chain reaction was used to detect the expression level of plasma circDYM.
- the Hamilton Depression Scale (HAMD-24 items) can be used for the evaluation of depressive symptoms of depression, bipolar disorder, neurosis and other diseases, especially for depression. degree of depression. Since the present invention proves that there is a significant correlation between the expression level of circDYM in the baseline period and the HAMD-24 score and between the HAMD-24 cognitive impairment factor scores, it is possible to predict the HAMD- 24 score and its cognitive impairment factor score, which are then used to objectively evaluate whether you have depression, the severity of depression, symptoms related to depression, and the treatment effect on cognitive impairment.
- the present invention also proves that there is a significant correlation between the Beck Suicidal Ideation Scale and the expression level of circDYM in the baseline period, and the suicide tendency of patients can be predicted by detecting the expression level of circDYM in the baseline period.
- the study further analyzed the predictive power of circDYM expression levels at baseline in MDD patients on the response to 5-day individualized or standardized VC-rTMS treatment and the recovery during the 4-week follow-up period after the end of treatment.
- this study confirmed that circDYM was significantly lower expressed in the plasma of MDD patients, and its sensitivity to MDD recognition was higher; circDYM levels in the baseline period had higher efficacy in predicting the short-term and long-term curative effects of standardized VC-rTMS, and Significantly increased after VC-rTMS treatment, supporting the value of circDYM as a biomarker in the identification of MDD and the prediction of VC-rTMS antidepressant efficacy.
- the discovery cohort included 7 MDD patients with extreme traits who had a suicide attempt history and 7 perfectly matched healthy controls in terms of age, gender, years of education, and handedness. A total of 14 people; the validation cohort consisted of 74 MDD patients (including 24 individualized groups, 27 standardized groups and 23 sham treatment groups) and 60 healthy controls, a total of 134 people.
- bioinformatics and machine learning methods were used to screen candidate proteins in the discovery cohort, and then to verify them in the verification cohort, to screen for proteins whose expression levels in the plasma of MDD patients at the baseline period were significantly higher than those of NC.
- the present invention proves that there is a significant correlation between the change value of plasma ATIII expression level before and after antidepressant treatment and the change value of neuropsychological assessment, it is possible to predict HAMD-24 by detecting the change value of patient plasma ATIII expression level before and after antidepressant treatment. , SDS, SAS, BHS, Stroop C, and then used to objectively evaluate the effect of antidepressant treatment and the relief of related symptoms.
- the accuracy and sensitivity of the following predictions were evaluated separately: 1) predicting the 5-day treatment response through the baseline ATIII expression level; 2) predicting the recovery during the 4-week follow-up period through the baseline ATIII expression level; 3) through individualized The expression level of ATIII after VC-rTMS treatment was used to identify the treatment response of patients; 4) The expression level of ATIII after individualized VC-rTMS treatment was used to predict the recovery during the 4-week follow-up period.
- the accuracy and sensitivity of the following predictions were evaluated separately: 1) predicting the 5-day treatment response through the baseline ATIII expression level; 2) predicting the recovery during the 4-week follow-up period through the baseline ATIII expression level; 3) through individualized The expression level of ATIII after VC-rTMS treatment was used to identify the treatment response of patients; 4) The expression level of ATIII after individualized VC-rTMS treatment was used to predict the recovery during the 4-week follow-up period.
- ATIII showed a significant decrease in protein level after VC-rTMS treatment, and its expression changes were related to the improvement of clinical symptoms of patients after individualized treatment, which also provided an objective evaluation standard for the therapeutic effect.
- ATIII has higher performance in evaluating and predicting short-term and long-term antidepressant efficacy, suggesting that this protein may be used as a biomarker reflecting the therapeutic effect of MDD.
- Fibroblast growth factor 9 (fibroblast growth factor 9, FGF9) as a biomarker for the diagnosis of depression and the antidepressant efficacy of repetitive transcranial magnetic stimulation (VC-rTMS) targeting the visual cortex
- NC group includes healthy control (NC group) and MDD patient group: the number of NC group is 30 people, MDD patient group is 73 people (individualized group, standardization group, sham treatment group, the number of three groups is 24, 26 and 23 people respectively ). Quantitative detection of FGF9 protein was done with R&D Systems ELISA commercial kit.
- the expression level of serum FGF9 is mainly based on the change of the disease degree of the patients. Since there are more patients who do not respond to the treatment effect in the standardized group than in the individualized treatment group, it is important to focus on the treatment after treatment. There was no statistically significant change in the expression of FGF9 in the standardized treatment group compared with before treatment. Therefore, it also shows that the expression level of FGF9 is related to the disease and the degree of remission after treatment, and can be used to evaluate the degree of disease and the effect of treatment. The specific results are shown in Figure 14.
- the high expression level of serum FGF9 in MDD patients at baseline can reflect the severity of their negative emotions, and it has high accuracy and specificity for MDD recognition.
- the level of FGF9 was significantly downregulated after individualized VC-rTMS treatment and was associated with the improvement of anxiety symptoms in patients.
- the support vector machine machine learning method was used to analyze the MDD joint recognition performance of the candidate markers screened in Examples 1-3 and 6 indicators including FGF9 and the joint estimation performance of VC-rTMS antidepressant efficacy.
- Support vector machine support vector machine, SVM learning model analysis shows that the combination of the above six markers can classify diseases with an accuracy as high as 91.92%.
- protein, CRP protein, antithrombin III (antithrombin III, ATIII), inter-alpha-trypsin inhibitor heavy chain H4 (inter-alpha-trypsin inhibitor heavy chain H4, ITIH4), vitamin D linking protein (vitamin D binding protein, VDB) and fibroblast growth factor 9 (fibroblast growth factor 9, FGF9) expression levels, the accuracy of predicting whether suffering from depression reached 91.92%.
- circDYM and ATIII were finally selected as the combined indicators for predicting the efficacy of MDD patients, and they were incorporated into the SVM machine learning model for analysis.
- the results showed that the accuracy of the combination of circDYM and ATIII in predicting the response to individualized VC-rTMS 5-day treatment and the recovery during the 4-week follow-up period at the baseline period was 82.61% and 86.96%, respectively; And the accuracy of predicting the short-term and long-term efficacy of rTMS is as high as 95.24% and 90.48%, respectively.
- Accuracy is the proportion of whether the machine learning calculation of depression or not is consistent with the doctor's diagnosis. For example, 100 people are diagnosed with depression by a doctor, thinking that these diagnoses are 100% correct, and there is no misdiagnosis or misdiagnosis. Then use the formula or algorithm combined by the above 6 indicators to diagnose these 100 people, and find that 91.92 people using this formula or algorithm are diagnosed as the same as the doctor's diagnosis, and the other 8 people are slightly different from the doctor's diagnosis, so it is considered The accuracy of the machine learning method is 91.92%.
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Abstract
A biomarker and a detection reagent for diagnosing depression and predicting therapeutic efficacy of visual cortex targeted repeated transcranial magnetic stimulation. The detection reagent for depression biomarkers comprises a reagent for detecting the expression level of at least one depression biomarker or a composition thereof, wherein the depression biomarker is selected from cyclic RNA DYM, anti-thrombin III, C reactive protein, fibroblast growth factor 9, vitamin D binding protein and inter-α-trypsin inhibitor heavy chain H4. The depression biomarker can effectively predict the risk of depression and can accurately predict the therapeutic efficacy of visual cortex targeted repeated transcranial magnetic stimulation on depression, thereby providing an objective basis for the diagnosis and treatment of depression.
Description
本发明属于生物技术检测领域，具体涉及用于抑郁症诊断以及对靶向视觉皮层重复经颅磁刺激治疗疗效的生物标志物及检测试剂。The invention belongs to the field of biotechnology detection, and in particular relates to a biomarker and a detection reagent for the diagnosis of depression and the curative effect of repeated transcranial magnetic stimulation on the targeted visual cortex.
抑郁症目前的治疗策略有心理治疗、药物疗法和物理治疗。重复经颅磁刺激属于物理治疗中的一种。目前重复经颅磁刺激治疗的靶点为左或(和)右侧背外侧前额叶皮质，视觉皮层(枕叶)是一个新的刺激靶点。然而，研究显示，并不是所有患者都对经颅磁刺激敏感，也没有技术手段能在治疗前判断出某患者是否对重复经颅磁刺激敏感。Current treatment strategies for depression include psychotherapy, drug therapy, and physical therapy. Repetitive transcranial magnetic stimulation is a form of physical therapy. At present, the target of repetitive transcranial magnetic stimulation therapy is the left or (and) right dorsolateral prefrontal cortex, and the visual cortex (occipital lobe) is a new stimulation target. However, studies have shown that not all patients are sensitive to TMS, and there is no technical means to determine whether a patient is sensitive to repetitive TMS before treatment.
目前，抑郁症无诊断用和评估治疗疗效用的客观生物标记物，这就导致了患者不信自己罹患抑郁症，进而不积极治疗。虽然有的患者愿意接受某种治疗，但由于该患者并不适合该种疗法，导致疗效差甚或不起效。而治疗的延迟导致了精神残障和***增多。At present, there are no objective biomarkers for diagnosis and evaluation of treatment efficacy for depression, which leads patients to not believe that they are suffering from depression, and thus do not actively treat it. Although some patients are willing to accept a certain treatment, because the patient is not suitable for this kind of treatment, the curative effect is poor or even ineffective. Delays in treatment lead to increased mental disability and suicide.
综上所述，随着抑郁症患病人数的增加，亟需针对抑郁症的客观诊断方法以及对于治疗疗效的预测方法。In summary, with the increase in the number of patients with depression, there is an urgent need for objective diagnostic methods for depression and predictive methods for treatment efficacy.
发明内容Contents of the invention
基于现有技术中存在的上述问题，本发明为解决抑郁症无诊断用和评估治疗疗效用的客观生物标记物的问题，提供了一种能够用于评估抑郁症患病情况以及评估治疗疗效的生物标记物及其基于该生物标记物的检测方法和试剂盒。Based on the above-mentioned problems in the prior art, the present invention provides a biomarker that can be used to assess the prevalence of depression and evaluate the therapeutic efficacy to solve the problem that depression has no objective biomarkers for diagnosis and evaluation of therapeutic efficacy. Biomarker and detection method and kit based on the biomarker.
本发明一个方面提供了一种用于评估受试者抑郁症患病情况或预测靶向视觉皮层的重复经颅磁刺激对抑郁症治疗效果的检测试剂，所述检测试剂中包含用于检测多种抑郁症生物标志物组合物表达水平的试剂或者检测至少一种抑郁症生物标志物表达水平的试剂；One aspect of the present invention provides a detection reagent for evaluating the prevalence of depression in a subject or predicting the therapeutic effect of repetitive transcranial magnetic stimulation targeting the visual cortex on depression. A reagent for the expression level of a depression biomarker composition or a reagent for detecting the expression level of at least one depression biomarker;
所述抑郁症生物标志物组合物选自环状RNA DYM(circDYM)、抗凝血酶Ⅲ(antithrombinⅢ，ATⅢ)、C反应蛋白(C-reactive protein，CRP)、成纤维细胞生长因子9(fibroblast growth factor 9，FGF9)、维生素D结合蛋白(VDBP)和间-alpha-胰蛋白酶抑制剂重链H4(inter-alpha-trypsin inhibitor heavy chain H4，ITIH4)的组合，或者环状RNA DYM和抗凝血酶Ⅲ的组合；The depression biomarker composition is selected from circular RNA DYM (circDYM), antithrombin III (antithrombin III, AT III), C-reactive protein (C-reactive protein, CRP), fibroblast growth factor 9 (fibroblast growth factor 9, FGF9), vitamin D binding protein (VDBP) and inter-alpha-trypsin inhibitor heavy chain H4 (inter-alpha-trypsin inhibitor heavy chain H4, ITIH4) combination, or circular RNA DYM and anticoagulant Combination of blood enzyme III;
所述抑郁症生物标志物组合物选自环状RNA DYM、抗凝血酶Ⅲ、C反应蛋白、成纤维细胞生长因子9、维生素D结合蛋白或间-alpha-胰蛋白酶抑制剂重链H4。The depression biomarker composition is selected from circular RNA DYM, antithrombin III, C-reactive protein, fibroblast growth factor 9, vitamin D binding protein or inter-alpha-trypsin inhibitor heavy chain H4.
进一步地，检测环状RNA DYM的试剂为用于PCR检测的引物和或探针。Further, the reagents for detecting circular RNA DYM are primers and or probes for PCR detection.
进一步地，检测抗凝血酶Ⅲ的试剂为抗凝血酶Ⅲ的抗体或抗凝血酶Ⅲ的ELISA定量检测试剂盒。所述抗体优选为单克隆抗体。Further, the reagent for detecting anti-thrombin III is an anti-thrombin III antibody or an ELISA quantitative detection kit for anti-thrombin III. The antibodies are preferably monoclonal antibodies.
进一步地，检测C反应蛋白的试剂为C反应蛋白的抗体或C反应蛋白的ELISA定量检测试剂盒。所述抗体优选为单克隆抗体。Further, the reagent for detecting C-reactive protein is an antibody for C-reactive protein or an ELISA quantitative detection kit for C-reactive protein. The antibodies are preferably monoclonal antibodies.
进一步地，检测成纤维细胞生长因子9的试剂为成纤维细胞生长因子的9ELISA定量检测试剂盒。所述抗体优选为单克隆抗体。Further, the reagent for detecting fibroblast growth factor 9 is a fibroblast growth factor 9 ELISA quantitative detection kit. The antibodies are preferably monoclonal antibodies.
进一步地，检测维生素D结合蛋白的试剂为维生素D结合蛋白的抗体或维生素D结合蛋白的ELISA定量检测试剂盒。所述抗体优选为单克隆抗体。Further, the reagent for detecting the vitamin D-binding protein is an antibody to the vitamin D-binding protein or an ELISA quantitative detection kit for the vitamin D-binding protein. The antibodies are preferably monoclonal antibodies.
进一步地，检测间-alpha-胰蛋白酶抑制剂重链H4的试剂为间-alpha-胰蛋白酶抑制剂的抗体、间-alpha-胰蛋白酶抑制剂重链H4的ELISA定量检测试剂盒。所述抗体优选为单克隆抗体。Further, the reagents for detecting the heavy chain H4 of the inter-alpha-trypsin inhibitor are the antibody of the inter-alpha-trypsin inhibitor and the ELISA quantitative detection kit for the heavy chain H4 of the inter-alpha-trypsin inhibitor. The antibodies are preferably monoclonal antibodies.
进一步地，所述检测试剂能够用于血浆样品的检测。Further, the detection reagent can be used for the detection of plasma samples.
本发明一个方面提供了一种用于评估受试者抑郁症患病情况或预测靶向视觉皮层的重复经颅磁刺激对抑郁症治疗效果的试剂盒，所述试剂盒中包含至少一种上述检测试剂。One aspect of the present invention provides a kit for evaluating the prevalence of depression in a subject or predicting the therapeutic effect of repetitive transcranial magnetic stimulation targeting the visual cortex on depression, the kit comprising at least one of the above-mentioned detection reagents.
本发明一个方面提供了上述检测试剂在制备评估抑郁症患病情况的试剂盒中的应用；或者在制备预测靶向视觉皮层的重复经颅磁刺激对于抑郁症疗效的试剂盒中的应用。One aspect of the present invention provides the application of the above detection reagent in the preparation of a kit for evaluating the prevalence of depression; or the application in the preparation of a kit for predicting the curative effect of repetitive transcranial magnetic stimulation targeting the visual cortex on depression.
进一步地，靶向视觉皮层的重复经颅磁刺激为标准化治疗方案或个体化治疗方案。Further, the repetitive transcranial magnetic stimulation targeting the visual cortex is a standardized treatment plan or an individualized treatment plan.
进一步地，检测试剂为检测以下标志物的试剂的组合：环状RNA DYM、抗凝血酶Ⅲ、C反应蛋白、成纤维细胞生长因子9、维生素D结合蛋白和间-alpha-胰蛋白酶抑制剂重链H4，所述应用为在制备评估抑郁症患病情况的试剂盒中的应用。Further, the detection reagent is a combination of reagents for detecting the following markers: circular RNA DYM, antithrombin III, C-reactive protein, fibroblast growth factor 9, vitamin D binding protein and inter-alpha-trypsin inhibitor As for the heavy chain H4, the application is in the preparation of a kit for evaluating the prevalence of depression.
进一步地，检测试剂为检测以下标志物的试剂的组合：环状RNA DYM和抗凝血酶Ⅲ，所述应用为在制备预测靶向视觉皮层的重复经颅磁刺激对于抑郁症疗效的试剂盒中的应用。Further, the detection reagent is a combination of reagents for detecting the following markers: circular RNA DYM and antithrombin III, and the application is to prepare a kit for predicting the curative effect of repetitive transcranial magnetic stimulation targeting the visual cortex on depression in the application.
本发明另一个方面提供了一种用于评估受试者抑郁症患病或预测靶向视觉皮层的重复经颅磁刺激对于抑郁症疗效的检测设备，所述检测设备中包含样品检测模块和预测模块；Another aspect of the present invention provides a detection device for assessing the prevalence of depression in a subject or predicting the curative effect of repetitive transcranial magnetic stimulation targeting the visual cortex on depression. The detection device includes a sample detection module and a prediction module;
所述样品检测模块为获得受试者血浆样品中至少一种抑郁症生物标志物表达水平的试剂；所述抑郁症生物标志物选自环状RNA DYM、抗凝血酶Ⅲ、C反应蛋白、成纤维细胞生长因子9、维生素D结合蛋白或间-alpha-胰蛋白酶抑制剂重链H4中的至少一种；或者为环状RNA DYM、抗凝血酶Ⅲ、C反应蛋白、成纤维细胞生长因子9、维生素D结合蛋白和间-alpha-胰蛋白酶抑制剂重链H4的组合；或者为环状RNA DYM和抗凝血酶Ⅲ的组合；The sample detection module is a reagent for obtaining the expression level of at least one depression biomarker in the subject's plasma sample; the depression biomarker is selected from circular RNA DYM, antithrombin III, C-reactive protein, At least one of fibroblast growth factor 9, vitamin D binding protein, or inter-alpha-trypsin inhibitor heavy chain H4; or circular RNA DYM, antithrombin III, C-reactive protein, fibroblast growth A combination of factor 9, vitamin D binding protein, and inter-alpha-trypsin inhibitor heavy chain H4; or a combination of circular RNA DYM and antithrombin III;
所述预测模块为能够根据所述样品检测模块获得的抑郁症生物标志物表达水平的数据，以及预测模块内的计算模型，获得受试者抑郁症患病情况，和或获得靶向视觉皮层的重复经颅磁刺激对于抑郁症疗效的预测情况；The prediction module can obtain the depression prevalence of the subject according to the data of the expression level of depression biomarkers obtained by the sample detection module, and the calculation model in the prediction module, and or obtain the target visual cortex Prediction of the efficacy of repetitive transcranial magnetic stimulation for depression;
所述计算模型选自支持向量机器学习模型、线性判别分析模型、递归特征去除模型、微阵列模型的预测分析、逻辑回归模型、CART算法、flextree算法、LART算法、随机森林算法、MART算法、机器学习算法、惩罚回归方法及其组合。The calculation model is selected from support vector machine learning model, linear discriminant analysis model, recursive feature removal model, predictive analysis of microarray model, logistic regression model, CART algorithm, flextree algorithm, LART algorithm, random forest algorithm, MART algorithm, machine Learning algorithms, penalized regression methods, and their combinations.
进一步地，所述计算模型的建立方法为以抑郁症生物标志物在血浆中的表达水平以及患病情况或对于靶向视觉皮层的重复经颅磁刺激治疗反应情况作为参数样本数据，通过机器学习方法进行计算获得计算模型。Further, the method for establishing the calculation model is to use the expression level of depression biomarkers in plasma and the condition of the disease or the response to repeated transcranial magnetic stimulation targeting the visual cortex as parameter sample data, through machine learning method to perform calculations to obtain calculation models.
进一步地，所述计算模型的建立方法为以抑郁症生物标志物在血浆中的表达水平以及患病情况或对于靶向视觉皮层的重复经颅磁刺激治疗反应情况作为参数样本数据，对支持向量机进行训练，获得用于根据抑郁症生物标志物在血浆中的表达水平数据进行抑郁症预测或对于靶向视觉皮层的重复经颅磁刺激治疗反应情况预测的支持向量机模型。Further, the establishment method of the calculation model is to use the expression level of depression biomarkers in plasma and the condition of the disease or the response to repeated transcranial magnetic stimulation therapy targeting the visual cortex as parameter sample data, and the support vector The machine was trained to obtain a support vector machine model for predicting depression based on the expression level data of depression biomarkers in plasma or for predicting the response to repetitive transcranial magnetic stimulation therapy targeting the visual cortex.
进一步地，所述样品检测模块包括上述检测试剂或上述试剂盒。Further, the sample detection module includes the above-mentioned detection reagent or the above-mentioned kit.
进一步地，抑郁症生物标志物优选为环状RNA DYM、抗凝血酶Ⅲ、C反应蛋白、成纤维细胞生长因子9、维生素D结合蛋白和间-alpha-胰蛋白酶抑制剂重链H4的组合。Further, the depression biomarker is preferably a combination of circular RNA DYM, antithrombin III, C-reactive protein, fibroblast growth factor 9, vitamin D binding protein and inter-alpha-trypsin inhibitor heavy chain H4 .
进一步地，抑郁症生物标志物优选为环状RNA DYM和抗凝血酶Ⅲ的组合。Further, the depression biomarker is preferably a combination of circular RNA DYM and antithrombin III.
进一步地，所述血浆样品来自于未进行抑郁症治疗前的受试者，或者在进行靶向视觉皮层的重复经颅磁刺激治疗后的受试者。Further, the plasma samples come from subjects who have not undergone treatment for depression, or subjects who have undergone repeated transcranial magnetic stimulation targeting the visual cortex.
进一步地，所述靶向视觉皮层的重复经颅磁刺激治疗反应情况为治疗后1-60天内受试者对于靶向视觉皮层的重复经颅磁刺激治疗抑郁症的情况，例如抑郁症症状是否减轻、缓解或消失。进一步优选为治疗后5-28天内受试者对于靶向视觉皮层的重复经颅磁刺激治疗抑郁症的情况。Further, the response to the repetitive transcranial magnetic stimulation targeting the visual cortex refers to the subject's response to the repetitive transcranial magnetic stimulation targeting the visual cortex for the treatment of depression within 1-60 days after treatment, for example, whether the depression symptoms Reduced, alleviated or disappeared. It is further preferred that the subject treats depression with repetitive transcranial magnetic stimulation targeting the visual cortex within 5-28 days after treatment.
进一步地，靶向视觉皮层的重复经颅磁刺激为标准化治疗方案或个体化治疗方案。Further, the repetitive transcranial magnetic stimulation targeting the visual cortex is a standardized treatment plan or an individualized treatment plan.
本发明又一个方面提供了一种抑郁症生物标志物，所述抑郁症生物标志物选自环状RNA DYM、抗凝血酶Ⅲ、C反应蛋白、成纤维细胞生长因子9、维生素D结合蛋白、间-alpha-胰蛋白酶抑制剂重链H4中的至少一种。Yet another aspect of the present invention provides a depression biomarker selected from circular RNA DYM, antithrombin III, C-reactive protein, fibroblast growth factor 9, vitamin D binding protein , at least one of the meta-alpha-trypsin inhibitor heavy chain H4.
本发明又一个方面提供了一种抑郁症生物标志物的组合物，所述组合物为环状RNA DYM、抗凝血酶Ⅲ、C反应蛋白、成纤维细胞生长因子9、维生素D结合蛋白和间-alpha-胰蛋白酶抑制剂重链H4的组合，或者为环状RNA DYM和抗凝血酶Ⅲ的组合。Another aspect of the present invention provides a composition of depression biomarkers, the composition is circular RNA DYM, antithrombin III, C-reactive protein, fibroblast growth factor 9, vitamin D binding protein and Combination of inter-alpha-trypsin inhibitor heavy chain H4, or combination of circular RNA DYM and antithrombin III.
本发明又一个方面提供了抑郁症生物标志物或抑郁症生物标志物的组合物作为评估抑郁症患病情况的生物标志物的应用；Another aspect of the present invention provides the application of a depression biomarker or a combination of depression biomarkers as a biomarker for assessing the prevalence of depression;
所述抑郁症生物标志物选自环状RNA DYM、抗凝血酶Ⅲ、C反应蛋白、成纤维细胞生长因子9、维生素D结合蛋白或间-alpha-胰蛋白酶抑制剂重链H4；The depression biomarker is selected from circular RNA DYM, antithrombin III, C-reactive protein, fibroblast growth factor 9, vitamin D binding protein or inter-alpha-trypsin inhibitor heavy chain H4;
所述抑郁症生物标志物的组合物为环状RNA DYM、抗凝血酶Ⅲ、C反应蛋白、成纤维细胞生长因子9、维生素D结合蛋白和间-alpha-胰蛋白酶抑制剂重链H4的组合，或者为环状RNA DYM和抗凝血酶Ⅲ的组合。The composition of the depression biomarker is circular RNA DYM, antithrombin III, C reactive protein, fibroblast growth factor 9, vitamin D binding protein and inter-alpha-trypsin inhibitor heavy chain H4 combination, or a combination of circular RNA DYM and antithrombin III.
本发明又一个方面提供了抑郁症生物标志物或抑郁症生物标志物的组合物作为预测靶向视觉皮层的重复经颅磁刺激对于抑郁症疗效的生物标志物的应用；Another aspect of the present invention provides the application of a depression biomarker or a combination of depression biomarkers as a biomarker for predicting the therapeutic effect of repetitive transcranial magnetic stimulation targeting the visual cortex on depression;
所述抑郁症生物标志物选自环状RNA DYM、抗凝血酶Ⅲ、C反应蛋白、成纤维细胞生长因子9、维生素D结合蛋白或间-alpha-胰蛋白酶抑制剂重链H4；The depression biomarker is selected from circular RNA DYM, antithrombin III, C-reactive protein, fibroblast growth factor 9, vitamin D binding protein or inter-alpha-trypsin inhibitor heavy chain H4;
所述抑郁症生物标志物的组合物为环状RNA DYM、抗凝血酶Ⅲ、C反应蛋白、成纤维细胞生长因子9、维生素D结合蛋白和间-alpha-胰蛋白酶抑制剂重链H4的组合，或者为环状RNA DYM和抗凝血酶Ⅲ的组合。The composition of the depression biomarker is circular RNA DYM, antithrombin III, C reactive protein, fibroblast growth factor 9, vitamin D binding protein and inter-alpha-trypsin inhibitor heavy chain H4 combination, or a combination of circular RNA DYM and antithrombin III.
进一步地，靶向视觉皮层的重复经颅磁刺激为标准化治疗方案或个体化治疗方案。Further, the repetitive transcranial magnetic stimulation targeting the visual cortex is a standardized treatment plan or an individualized treatment plan.
本发明再一个方面提供了评估抑郁症的方法，所述方法包括以下步骤：Another aspect of the present invention provides a method for assessing depression, said method comprising the steps of:
1)获得受试者血液样品，并检测样品中抑郁症生物标志物或抑郁症生物标志物的组合物表达水平，获得表达水平的数据集；1) Obtain a blood sample from the subject, and detect the expression level of the depression biomarker or the composition of the depression biomarker in the sample, and obtain a data set of the expression level;
2)根据步骤1)获得的数据集以及预测计算模型，获得受试者抑郁症患病情况；2) According to the data set obtained in step 1) and the predictive calculation model, the depression prevalence of the subject is obtained;
所述预测计算模型选自支持向量机器学习模型、线性判别分析模型、递归特征去除模型、微阵列模型的预测分析、逻辑回归模型、CART算法、flextree算法、LART算法、随机森林算法、MART算法、机器学习算法、惩罚回归方法及其组合；The predictive calculation model is selected from a support vector machine learning model, a linear discriminant analysis model, a recursive feature removal model, a predictive analysis of a microarray model, a logistic regression model, a CART algorithm, a flextree algorithm, a LART algorithm, a random forest algorithm, a MART algorithm, Machine learning algorithms, penalized regression methods and their combinations;
所述抑郁症生物标志物选自环状RNA DYM、抗凝血酶Ⅲ、C反应蛋白、成纤维细胞生长因子9、维生素D结合蛋白、间-alpha-胰蛋白酶抑制剂重链H4；The depression biomarker is selected from circular RNA DYM, antithrombin III, C-reactive protein, fibroblast growth factor 9, vitamin D binding protein, inter-alpha-trypsin inhibitor heavy chain H4;
所述抑郁症生物标志物的组合物选自环状RNA DYM、抗凝血酶Ⅲ、C反应蛋白、成纤维细胞生长因子9、维生素D结合蛋白、间-alpha-胰蛋白酶抑制剂重链H4中至少一种的组合。The composition of the depression biomarker is selected from circular RNA DYM, antithrombin III, C-reactive protein, fibroblast growth factor 9, vitamin D binding protein, inter-alpha-trypsin inhibitor heavy chain H4 A combination of at least one of them.
进一步地，所述预测计算模型的建立方法为以抑郁症生物标志物在血浆中的表达水平以及患病情况作为参数样本数据，通过机器学习方法进行计算获得计算模型。Further, the establishment method of the predictive calculation model is to use the expression level of depression biomarkers in plasma and the condition of the disease as parameter sample data, and perform calculations by machine learning methods to obtain the calculation model.
进一步地，所述预测计算模型的建立方法为以抑郁症生物标志物在血浆中的表达水平以及患病情况作为参数样本数据，对支持向量机进行训练，获得用于根据抑郁症生物标志物在 血浆中的表达水平数据进行抑郁症预测或对于靶向视觉皮层的重复经颅磁刺激治疗反应情况预测的支持向量机模型。Further, the establishment method of the predictive calculation model is to use the expression level of the depression biomarkers in plasma and the condition of the disease as parameter sample data, train the support vector machine, and obtain the Support vector machine models for prediction of depression or response to repetitive transcranial magnetic stimulation therapy targeting the visual cortex based on expression level data in plasma.
进一步地，所述抑郁症生物标志物的组合物优选为环状RNA DYM、抗凝血酶Ⅲ、C反应蛋白、成纤维细胞生长因子9、维生素D结合蛋白和间-alpha-胰蛋白酶抑制剂重链H4的组合。Further, the composition of the depression biomarkers is preferably circular RNA DYM, antithrombin III, C-reactive protein, fibroblast growth factor 9, vitamin D binding protein and inter-alpha-trypsin inhibitor Combination of heavy chain H4.
进一步地，受试者血液样品为未进行治疗前受试者的血浆样品。Further, the subject's blood sample is the plasma sample of the subject before treatment.
本发明再一个方面提供了预测抑郁症通过重复经颅磁刺激视觉皮层治疗的治疗效果的方法，所述方法包括以下步骤：Another aspect of the present invention provides a method for predicting the therapeutic effect of depression through repetitive transcranial magnetic stimulation of the visual cortex, the method comprising the following steps:
1)获得受试者血液样品，并检测样品中抑郁症生物标志物或抑郁症生物标志物的组合物表达水平，获得表达水平的数据集；1) Obtain a blood sample from the subject, and detect the expression level of the depression biomarker or the composition of the depression biomarker in the sample, and obtain a data set of the expression level;
2)根据步骤1)获得的数据集以及预测计算模型，获得受试者抑郁症患病情况；2) According to the data set obtained in step 1) and the predictive calculation model, the depression prevalence of the subject is obtained;
所述预测计算模型选自支持向量机器学习模型、线性判别分析模型、递归特征去除模型、微阵列模型的预测分析、逻辑回归模型、CART算法、flextree算法、LART算法、随机森林算法、MART算法、机器学习算法、惩罚回归方法及其组合；The predictive calculation model is selected from a support vector machine learning model, a linear discriminant analysis model, a recursive feature removal model, a predictive analysis of a microarray model, a logistic regression model, a CART algorithm, a flextree algorithm, a LART algorithm, a random forest algorithm, a MART algorithm, Machine learning algorithms, penalized regression methods and their combinations;
所述抑郁症生物标志物选自环状RNA DYM、抗凝血酶Ⅲ、C反应蛋白、成纤维细胞生长因子9、维生素D结合蛋白、间-alpha-胰蛋白酶抑制剂重链H4；The depression biomarker is selected from circular RNA DYM, antithrombin III, C-reactive protein, fibroblast growth factor 9, vitamin D binding protein, inter-alpha-trypsin inhibitor heavy chain H4;
所述抑郁症生物标志物的组合物选自环状RNA DYM、抗凝血酶Ⅲ、C反应蛋白、成纤维细胞生长因子9、维生素D结合蛋白、间-alpha-胰蛋白酶抑制剂重链H4中至少一种的组合。The composition of the depression biomarker is selected from circular RNA DYM, antithrombin III, C-reactive protein, fibroblast growth factor 9, vitamin D binding protein, inter-alpha-trypsin inhibitor heavy chain H4 A combination of at least one of them.
进一步地，所述预测计算模型的建立方法为以抑郁症生物标志物在血浆中的表达水平以及患病情况或对于靶向视觉皮层的重复经颅磁刺激治疗反应情况作为参数样本数据，通过机器学习方法进行计算获得计算模型。Further, the establishment method of the predictive calculation model is to use the expression level of depression biomarkers in plasma and the condition of the disease or the response to repeated transcranial magnetic stimulation targeting the visual cortex as parameter sample data, through the machine The learning method performs calculations to obtain a calculation model.
进一步地，所述预测计算模型的建立方法为以抑郁症生物标志物在血浆中的表达水平以及患病情况或对于靶向视觉皮层的重复经颅磁刺激治疗反应情况作为参数样本数据，对支持向量机进行训练，获得用于根据抑郁症生物标志物在血浆中的表达水平数据进行抑郁症预测或对于靶向视觉皮层的重复经颅磁刺激治疗反应情况预测的支持向量机模型。Further, the establishment method of the predictive calculation model is to use the expression level of depression biomarkers in plasma and the condition of the disease or the response to repeated transcranial magnetic stimulation targeting the visual cortex as parameter sample data, to support The vector machine was trained to obtain a support vector machine model for predicting depression based on the expression level data of depression biomarkers in plasma or for predicting the response to repetitive transcranial magnetic stimulation therapy targeting the visual cortex.
进一步地，所述抑郁症生物标志物的组合物优选为环状RNA DYM、抗凝血酶Ⅲ、C反应蛋白、成纤维细胞生长因子9、维生素D结合蛋白和间-alpha-胰蛋白酶抑制剂重链H4的组合。Further, the composition of the depression biomarkers is preferably circular RNA DYM, antithrombin III, C-reactive protein, fibroblast growth factor 9, vitamin D binding protein and inter-alpha-trypsin inhibitor Combination of heavy chain H4.
进一步地，受试者血液样品为未进行治疗前受试者的血浆样品或者为进行了靶向视觉皮层的重复经颅磁刺激治疗后受试者的血浆样品。Further, the blood sample of the subject is the plasma sample of the subject before no treatment or the plasma sample of the subject after repeated transcranial magnetic stimulation treatment targeting the visual cortex.
进一步地，靶向视觉皮层的重复经颅磁刺激为标准化治疗方案或个体化治疗方案。Further, the repetitive transcranial magnetic stimulation targeting the visual cortex is a standardized treatment plan or an individualized treatment plan.
1)本发明提供了多种抑郁症诊断用以及治疗效果预测用的生物标记物，为抑郁症这种精神疾病的诊断和治疗提供了客观标准。1) The present invention provides a variety of biomarkers for diagnosing depression and predicting therapeutic effects, providing an objective standard for the diagnosis and treatment of depression, a mental disease.
2)本发明的生物标记物能够通过血浆进行检测，检测方法简单。2) The biomarker of the present invention can be detected through plasma, and the detection method is simple.
3)本发明通过多种生物标记物的组合实现更高的准确度。3) The present invention achieves higher accuracy through the combination of multiple biomarkers.
4)本发明生物标记物的组合不但能够实现对于抑郁症的诊断，还可以实现对于治疗效果的预测，这能极大地提高治疗效率，减少病患的痛苦。4) The combination of biomarkers of the present invention can not only realize the diagnosis of depression, but also realize the prediction of the treatment effect, which can greatly improve the treatment efficiency and reduce the suffering of patients.
图1为神经导航VC-rTMS抗抑郁治疗试验流程图。其中，MDD代表抑郁症；MRI代表磁共振成像；VC代表觉皮层；rTMS代表重复经颅磁刺激；HAMD-24代表24项汉密尔顿抑郁评定量表。Figure 1 is a flowchart of neuronavigation VC-rTMS antidepressant treatment trial. Among them, MDD stands for depression; MRI stands for magnetic resonance imaging; VC stands for sensory cortex; rTMS stands for repetitive transcranial magnetic stimulation; HAMD-24 stands for 24-item Hamilton Depression Rating Scale.
图2为正常对照组、MDD患者组及MDD三个亚组基线期血浆circDYM表达水平比较。从左到右分别为NC组、MDD组、个体化治疗组、标准化治疗组以及假治疗组。其中，circDYM代表环状RNA DYM；FC代表倍数变化；NC代表正常对照；MDD代表抑郁症。Figure 2 is a comparison of plasma circDYM expression levels in the normal control group, the MDD patient group, and the three subgroups of MDD at baseline. From left to right are NC group, MDD group, individualized treatment group, standardized treatment group and sham treatment group. Among them, circDYM stands for circular RNA DYM; FC stands for fold change; NC stands for normal control; MDD stands for depression.
图3为正常对照与MDD患者个体化、标准化及假治疗后血浆circDYM表达情况比较。Figure 3 is a comparison of plasma circDYM expression between normal controls and MDD patients after individualized, standardized and sham treatments.
图4为MDD患者基线期circDYM表达水平与神经心理评估的关系。1)circDYM表达水平与HAMD-24评分呈正相关；2)circDYM表达水平与HAMD-24认知障碍因子分呈正相关；3)circDYM表达水平与BSI-CV-C评分呈正相关。其中，BSI-CV-C代表贝克***意念量表中文版—最近一周。Figure 4 shows the relationship between circDYM expression level and neuropsychological assessment in MDD patients at baseline. 1) circDYM expression level was positively correlated with HAMD-24 score; 2) circDYM expression level was positively correlated with HAMD-24 cognitive impairment factor score; 3) circDYM expression level was positively correlated with BSI-CV-C score. Among them, BSI-CV-C represents the Chinese version of the Beck Suicide Ideation Inventory—the last week.
图5为基线期血浆circDYM表达水平识别MDD及预测VC-rTMS抗抑郁疗效的ROC曲线。其中，1)circDYM识别MDD的ROC曲线；2)circDYM预测5天个体化VC-rTMS治疗反应的ROC曲线；3)circDYM预测个体化治疗后4周随访期内恢复情况的ROC曲线；4)circDYM预测5天标准化VC-rTMS治疗反应的ROC曲线；5)circDYM预测标准化治疗后4周随访期内恢复情况的ROC曲线。ROC曲线代表受试者工作特征曲线；AUC代表曲线下面积；95％CI代表95％置信区间。Figure 5 is the ROC curve for identifying MDD and predicting the antidepressant efficacy of VC-rTMS by plasma circDYM expression level at baseline. Among them, 1) the ROC curve of circDYM identifying MDD; 2) the ROC curve of circDYM predicting the response to 5-day individualized VC-rTMS treatment; 3) the ROC curve of circDYM predicting the recovery during the 4-week follow-up period after individualized treatment; 4) circDYM ROC curve for predicting response to 5-day standardized VC-rTMS treatment; 5) ROC curve for circDYM to predict recovery during 4-week follow-up period after standardized treatment. ROC curve represents the receiver operating characteristic curve; AUC represents the area under the curve; 95% CI represents the 95% confidence interval.
图6为NC组及MDD组基线期4种蛋白表达水平比较结果。其中，1)CRP表达水平比较(mg/L)；2)ATIII表达水平比较(mg/L)；3)ITIH4表达水平比较(ng/mL)；4)VDB表达水平比较(μg/mL)。CRP代表C反应蛋白；ATIII代表抗凝血酶III；ITIH4代表间-alpha-胰 蛋白酶抑制剂重链H4；VDB代表维生素D结合蛋白；NC代表正常对照；MDD代表抑郁症。Figure 6 shows the comparison results of the expression levels of the four proteins in the NC group and the MDD group at baseline. Among them, 1) comparison of CRP expression level (mg/L); 2) comparison of ATIII expression level (mg/L); 3) comparison of ITIH4 expression level (ng/mL); 4) comparison of VDB expression level (μg/mL). CRP stands for C-reactive protein; ATIII stands for antithrombin III; ITIH4 stands for inter-alpha-trypsin inhibitor heavy chain H4; VDB stands for vitamin D-binding protein; NC stands for normal control; MDD stands for depression.
图7为个体化/标准化VC-rTMS及假治疗前后4种候选蛋白表达水平比较。1)CRP表达水平比较(mg/L)；2)ATIII表达水平比较(mg/L)；3)ITIH4表达水平比较(ng/mL)；4)VDB表达水平比较(μg/mL)。其中，CRP代表C反应蛋白；ATIII代表抗凝血酶III；ITIH4代表间-alpha-胰蛋白酶抑制剂重链H4；VDB代表维生素D连接蛋白。Figure 7 is a comparison of the expression levels of four candidate proteins before and after individualized/standardized VC-rTMS and sham treatment. 1) Comparison of CRP expression level (mg/L); 2) Comparison of ATIII expression level (mg/L); 3) Comparison of ITIH4 expression level (ng/mL); 4) Comparison of VDB expression level (μg/mL). Among them, CRP stands for C-reactive protein; ATIII stands for antithrombin III; ITIH4 stands for inter-alpha-trypsin inhibitor heavy chain H4; VDB stands for vitamin D connexin.
图8为个体化VC-rTMS治疗前后ATIII表达水平变化值(mg/L)与神经心理评估减分值的相关关系。其中1)ATIII变化值(mg/L)与HAMD-24减分值呈正相关；2)ATIII变化值(mg/L)与SDS减分值呈正相关；3)ATIII变化值(mg/L)与SAS减分值呈正相关；4)ATIII变化值(mg/L)与BHS减分值呈正相关；5)ATIII变化值(mg/L)与Stroop C减分值呈负相关。AMD-24代表24项汉密尔顿抑郁评定量表；SDS代表抑郁自评量表；SAS代表焦虑自评量表；BHS代表贝克绝望量表；ATIII代表抗凝血酶III。Figure 8 shows the relationship between the change in ATIII expression level (mg/L) and the neuropsychological assessment score before and after individualized VC-rTMS treatment. Among them, 1) ATIII change value (mg/L) was positively correlated with HAMD-24 deduction value; 2) ATIII change value (mg/L) was positively correlated with SDS deduction value; 3) ATIII change value (mg/L) was positively correlated with SDS deduction value; SAS scores were positively correlated; 4) ATIII changes (mg/L) were positively correlated with BHS scores; 5) ATIII changes (mg/L) were negatively correlated with Stroop C scores. AMD-24 stands for 24-item Hamilton Depression Rating Scale; SDS stands for Self-Rating Depression Scale; SAS stands for Self-Rating Anxiety Scale; BHS stands for Baker Hopelessness Scale; ATIII stands for Antithrombin III.
图9为个体化VC-rTMS治疗前后ATIII变化值(mg/L)与家庭APGAR评分在SAS减分值上的交互作用。其中，家庭APGAR代表家庭功能问卷；ATIII代表抗凝血酶III；SAS代表焦虑自评量表。Figure 9 shows the interaction between the ATIII change value (mg/L) before and after individualized VC-rTMS treatment and the family APGAR score on the SAS score reduction value. Among them, family APGAR stands for Family Functioning Questionnaire; ATIII stands for Antithrombin III; SAS stands for Self-Rating Anxiety Scale.
图10为个体化VC-rTMS治疗组ATIII表达水平评估及预测抗抑郁疗效的ROC曲线。其中，1)基线期ATIII表达水平预测5天治疗反应情况的ROC曲线；2)基线期ATIII表达水平预测4周随访期内恢复情况的ROC曲线；3)个体化VC-rTMS治疗后ATIII表达水平识别患者治疗反应的ROC曲线；4)个体化VC-rTMS治疗后ATIII表达水平预测4周随访期内恢复情况的ROC曲线。AUC代表曲线下面积；95％CI代表95％置信区间。Figure 10 is the ROC curve for evaluating the expression level of ATIII and predicting the antidepressant efficacy in the individualized VC-rTMS treatment group. Among them, 1) the ROC curve of the expression level of ATIII in the baseline period predicting the 5-day treatment response; 2) the ROC curve of the expression level of ATIII in the baseline period predicting the recovery in the 4-week follow-up period; 3) the expression level of ATIII after individualized VC-rTMS treatment ROC curve for identifying the treatment response of patients; 4) ROC curve for predicting the recovery of ATIII expression level in the 4-week follow-up period after individualized VC-rTMS treatment. AUC stands for area under the curve; 95% CI stands for 95% confidence interval.
图11为标准化VC-rTMS治疗组ATIII表达水平评估及预测抗抑郁疗效的ROC曲线。其中，1)基线期ATIII表达水平预测5天治疗反应情况的ROC曲线；2)基线期ATIII表达水平预测4周随访期内恢复情况的ROC曲线；3)标准化VC-rTMS治疗后ATIII表达水平识别患者治疗反应的ROC曲线；4)标准化VC-rTMS治疗后ATIII表达水平预测4周随访期内恢复情况的ROC曲线。AUC代表曲线下面积；95％CI代表95％置信区间。Figure 11 is the ROC curve for evaluating ATIII expression levels and predicting antidepressant efficacy in the standardized VC-rTMS treatment group. Among them, 1) the ROC curve of the expression level of ATIII in the baseline period predicting the 5-day treatment response; 2) the ROC curve of the expression level of ATIII in the baseline period predicting the recovery in the 4-week follow-up period; 3) the identification of the expression level of ATIII after standardized VC-rTMS treatment ROC curve of patients' treatment response; 4) ROC curve of ATIII expression level after standardized VC-rTMS treatment to predict recovery during 4-week follow-up period. AUC stands for area under the curve; 95% CI stands for 95% confidence interval.
图12为正常对照组、MDD患者组及MDD三个亚组基线期血清FGF9表达水平比较。其中，FGF9代表成纤维细胞生长因子9；NC代表正常对照；MDD代表抑郁症。Figure 12 is a comparison of serum FGF9 expression levels in the normal control group, the MDD patient group and the three subgroups of MDD at baseline. Among them, FGF9 stands for fibroblast growth factor 9; NC stands for normal control; MDD stands for depression.
图13为个体化/标准化VC-rTMS及假治疗前后血清FGF9表达水平比较。其中，FGF9代表成纤维细胞生长因子9。Figure 13 is a comparison of serum FGF9 expression levels before and after individualized/standardized VC-rTMS and sham treatment. Wherein, FGF9 stands for fibroblast growth factor 9.
图14为VC-rTMS治疗前后应答组及无应答组血清FGF9表达水平比较。其中，FGF9代表成纤维细胞生长因子9。Figure 14 is a comparison of serum FGF9 expression levels in the response group and non-response group before and after VC-rTMS treatment. Wherein, FGF9 stands for fibroblast growth factor 9.
图15为MDD患者基线期血清FGF9表达水平与神经心理评估的关系。其中，1)FGF9表达水平(pg/mL)与HAMA评分呈负相关；2)FGF9表达水平(pg/mL)与SDS评分呈负相关。HAMA代表汉密尔顿焦虑量表；SDS代表抑郁自评量表；FGF9代表成纤维细胞生长因子9。Figure 15 shows the relationship between serum FGF9 expression level and neuropsychological assessment in MDD patients at baseline. Among them, 1) FGF9 expression level (pg/mL) was negatively correlated with HAMA score; 2) FGF9 expression level (pg/mL) was negatively correlated with SDS score. HAMA stands for Hamilton Anxiety Scale; SDS stands for Self-Rating Depression Scale; FGF9 stands for Fibroblast Growth Factor 9.
图16为个体化VC-rTMS治疗后血清FGF9表达变化与HAMA减分值的关系。其中，HAMA代表汉密尔顿焦虑量表；FGF9代表成纤维细胞生长因子9。Figure 16 shows the relationship between the change of serum FGF9 expression and the HAMA score after individualized VC-rTMS treatment. Among them, HAMA stands for Hamilton Anxiety Scale; FGF9 stands for Fibroblast Growth Factor 9.
图17为基线期血清FGF9表达水平识别MDD的ROC曲线。其中，ROC曲线代表受试者工作特征曲线；AUC代表曲线下面积；95％CI代表95％置信区间。FIG. 17 is the ROC curve for identifying MDD by the serum FGF9 expression level in the baseline period. Among them, the ROC curve represents the receiver operating characteristic curve; AUC represents the area under the curve; 95% CI represents the 95% confidence interval.
为了使本发明的上述目的、特征和优点能够更加明显易懂，下面对本发明的具体实施方式做详细的说明，但不能理解为对本发明的可实施范围的限定。In order to make the above objects, features and advantages of the present invention more obvious and understandable, the specific implementation modes of the present invention will be described in detail below, but they should not be construed as limiting the scope of implementation of the present invention.
实施例1 血浆环状RNA DYM对靶向视觉皮层的重复经颅磁刺激(VC-rTMS)抗抑郁疗效的预测价值研究Example 1 Predictive value of plasma circular RNA DYM on antidepressant efficacy of repetitive transcranial magnetic stimulation (VC-rTMS) targeting visual cortex
为了在MDD独立样本中验证血浆circDYM表达水平，探索神经导航VC-rTMS治疗前后circDYM的表达变化，阐明血浆circDYM可否作为VC-rTMS抗抑郁效应生物标记物进行以下实验。In order to verify the expression level of plasma circDYM in independent samples of MDD, explore the expression changes of circDYM before and after neuronavigation VC-rTMS treatment, and clarify whether plasma circDYM can be used as a biomarker of VC-rTMS antidepressant effect for the following experiments.
方法：研究共纳入32名未患病正常人(NC组)及73名MDD患者，73名MDD患者共分为3组，个体化组、标准化组以及假治疗组，人数分别为24人、28人及21人。其中个体化组接受个体化重复经颅磁刺激视觉皮层治疗，标准化组接受标准化重复经颅磁刺激视觉皮层治疗，假治疗组未经重复经颅磁刺激视觉皮层治疗。Methods: A total of 32 unaffected normal people (NC group) and 73 MDD patients were included in the study. The 73 MDD patients were divided into 3 groups, individualized group, standardized group and sham treatment group, with 24 people and 28 people respectively. people and 21 people. The individualized group received individualized repetitive transcranial magnetic stimulation for visual cortex, the standardized group received standardized repetitive transcranial magnetic stimulation for visual cortex, and the sham treatment group received no repetitive transcranial magnetic stimulation for visual cortex.
纳入了73名从未服用抗抑郁药物或至少两周内未用药MDD患者，以及32名年龄、性别、受教育年限等与MDD患者相匹配的正常对照(normal control，NC)。A total of 73 MDD patients who had never taken antidepressant drugs or had not used antidepressants for at least two weeks, and 32 normal controls (normal control, NC) matched with MDD patients in terms of age, gender, and years of education were included.
受试入组后立即对其进行临床信息采集及多维度神经心理学评估。随后安排受试进行静脉血液采集及脑部MRI扫描，其中MDD患者在MRI扫描完成后被随机分配至个体化、标准化及假治疗三组。研究者根据T1加权像利用Brainsight(Brainbox，英国)软件重建患者脑部三维结构，提取个体化组患者任务态fMRI扫描过程中快刺激较慢刺激在枕叶内显著激活的峰值点坐标作为个体化rTMS治疗靶点；而对于标准化组及假治疗组患者，则选择左侧V1区MNI(Montreal Neurological Institute)坐标系坐标(x＝-1.8，y＝-98.14，z＝-6)作为其rTMS刺激靶点。利用近红外导航***(Rogue Research Inc.，美国及加拿大)对上述坐标点进行精准定位，进而开始连续5天，每天2次的rTMS治疗。rTMS治疗仪Magstim Rapid
2(Magstim，英国) 设置参数如下：治疗强度＝90％静息运动阈值(Resting Motor Threshold，RMT)，频率＝10Hz，每次持续时间＝4s，间隔时间＝26s，刺激时间＝20min，总脉冲数＝1600/次，5天总脉冲数＝16000。对于假治疗组患者，操作时将线圈探头弯折90°，使其无法于患者脑部产生磁场及感应电流。每次rTMS治疗结束后详细询问患者是否耐受及有无不良反应，并于rTMS治疗第1、3天结束后对患者重复进行情绪状态评估，在第5天治疗结束后对患者进行情绪状态和认知功能评估，并再次采集静脉血液样本及多模态MRI数据。5天rTMS治疗期间禁止患者合并使用抗抑郁药物治疗或电休克疗法。全部治疗结束后，开始为期4周的随访研究，由同一评定者利用HAMD-24对MDD患者进行每周1次的抑郁症状评估以了解患者恢复情况。试验流程详见图1。
Clinical information collection and multidimensional neuropsychological assessment were performed immediately after the subjects were enrolled. The subjects were then arranged for venous blood collection and brain MRI scans, and the MDD patients were randomly assigned to individualized, standardized and sham treatment groups after the MRI scans were completed. Based on the T1-weighted images, the researchers used Brainsight (Brainbox, UK) software to reconstruct the three-dimensional brain structure of the patients, and extracted the peak point coordinates of the significant activation of fast and slow stimuli in the occipital lobe during the task-state fMRI scanning of patients in the individualized group as individualized data. rTMS treatment target; for patients in the standardization group and the sham treatment group, the left V1 area MNI (Montreal Neurological Institute) coordinate system coordinates (x=-1.8, y=-98.14, z=-6) were selected as the rTMS stimulation target. The near-infrared navigation system (Rogue Research Inc., the United States and Canada) was used to precisely locate the above coordinate points, and then rTMS treatment was started twice a day for 5 consecutive days. rTMS therapeutic instrument Magstim Rapid 2 (Magstim, UK) set parameters as follows: treatment intensity=90% resting motor threshold (Resting Motor Threshold, RMT), frequency=10Hz, each duration=4s, interval time=26s, stimulation time =20min, total pulse number=1600/time, total pulse number=16000 in 5 days. For patients in the sham treatment group, the coil probe was bent 90° during operation so that it could not generate magnetic field and induced current in the brain of the patient. After each rTMS treatment, patients were asked in detail whether they tolerated it and whether there were any adverse reactions, and the emotional state of the patients was evaluated repeatedly after the end of the first and third days of rTMS treatment. Cognitive function was assessed, and venous blood samples and multimodal MRI data were collected again. During the 5-day rTMS treatment, the patients were forbidden to use antidepressant drugs or electroconvulsive therapy. After all the treatment was over, a 4-week follow-up study was started, and the same evaluator used HAMD-24 to assess the depressive symptoms of MDD patients once a week to understand the recovery of the patients. The test process is shown in Figure 1 in detail.
受试者于临床资料收集完成后的当日或次日上午6:00-10:00接受空腹静脉血液样本采集，5mL/人次，以5mL K
2EDTA紫色抗凝管(鑫乐，中国)收集。MDD患者需于5天治疗后再次采血，要求同前。
Subjects received fasting venous blood samples from 6:00-10:00 am on the day after the clinical data collection was completed, 5mL/time, collected in 5mL K 2 EDTA purple anticoagulant tubes (Xinle, China). MDD patients need to collect blood again after 5 days of treatment, and the requirements are the same as before.
采血后立即将血液样本与K
2EDTA混匀，于2h内完成血浆分离，具体操作步骤如下：(1)抗凝管2000g、4℃冷冻离心10min，将所得上清液转移至新离心管内，注意不能吸取到下层血细胞，以免污染血浆；(2)离心管12000g、4℃冷冻离心10min，以去除血小板及细胞碎片，提取上清液即得到血浆样本，500μL/管分装保存于-80℃冰箱备用。
Immediately after blood collection, the blood sample was mixed with K 2 EDTA, and the plasma separation was completed within 2 hours. The specific operation steps were as follows: (1) Anticoagulant tube 2000g, refrigerated and centrifuged at 4°C for 10 minutes, and the obtained supernatant was transferred to a new centrifuge tube, Be careful not to absorb the blood cells in the lower layer, so as not to contaminate the plasma; (2) Centrifuge tubes at 12000g, 4°C for 10 minutes to remove platelets and cell debris, extract the supernatant to obtain plasma samples, store in -80°C in 500μL/tube Refrigerator for spare.
RNA提取RNA extraction
利用miRNeasy Serum/Plasma Kit(Qiagen，德国)对血浆中总RNA进行提取。具体操作步骤如下：Total RNA in plasma was extracted using miRNeasy Serum/Plasma Kit (Qiagen, Germany). The specific operation steps are as follows:
(1)取200μL血浆样本于崭新、干燥、无菌、无DNA/RNA酶的1.5mL eppendorf(EP)管中；(1) Take 200μL plasma sample in a new, dry, sterile, DNA/RNase-free 1.5mL eppendorf (EP) tube;
(2)取1mL QIAzol Lysis Reagent(Qiagen，德国)加入样本中，通过涡流振荡器振荡进行充分混匀，室温(15℃-25℃)孵育5min；(2) Take 1 mL of QIAzol Lysis Reagent (Qiagen, Germany) and add it to the sample, mix thoroughly by vortex shaker, and incubate at room temperature (15°C-25°C) for 5 min;
(3)加入200μL氯仿溶液于上述样本混合物中，盖紧管盖，剧烈振荡15s后室温孵育3min；(3) Add 200 μL of chloroform solution to the above sample mixture, close the cap tightly, shake vigorously for 15 seconds, and incubate at room temperature for 3 minutes;
(4)12000rpm、4℃冷冻离心15min；(4) 12000rpm, 4°C refrigerated centrifugation for 15min;
(5)吸取所得上清液600μL并转移至新EP管内，注意避免吸取下层杂质。再向EP管内加入900μL无水乙醇，通过移液器反复多次吹吸进行充分混匀；(5) Aspirate 600 μL of the obtained supernatant and transfer it to a new EP tube, taking care to avoid absorbing the impurities in the lower layer. Then add 900 μL of absolute ethanol to the EP tube, and repeatedly blow and suck through the pipette to fully mix;
(6)取RNeasy MinElute spin column(Qiagen，德国)置于2mL收集管中，吸取上述样本混合物700μL于柱内，盖紧柱盖后8000rpm室温离心15s，弃废液；(6) Put RNeasy MinElute spin column (Qiagen, Germany) into a 2mL collection tube, draw 700μL of the above sample mixture into the column, close the column cap tightly, centrifuge at 8000rpm room temperature for 15s, and discard the waste liquid;
(7)重复步骤(6)，直至剩余样本混合物全部完成离心；(7) Repeat step (6) until the remaining sample mixture is completely centrifuged;
(8)取700μL RWT缓冲液(Qiagen，德国)于RNeasy MinElute spin column内，盖紧柱盖8000rpm室温离心15s，弃废液；(8) Take 700 μL of RWT buffer solution (Qiagen, Germany) in the RNeasy MinElute spin column, tightly cover the column cap and centrifuge at 8000 rpm for 15 s at room temperature, discard the waste liquid;
(9)取500μL RPE缓冲液(Qiagen，德国)于RNeasy MinElute spin column内，盖紧柱盖8000rpm室温离心15s，弃废液；(9) Take 500 μL of RPE buffer solution (Qiagen, Germany) in the RNeasy MinElute spin column, tightly cover the column cap and centrifuge at 8000 rpm for 15 s at room temperature, and discard the waste liquid;
(10)取500μL 80％乙醇于RNeasy MinElute spin column内，盖紧柱盖8000rpm室温离心2min，弃废液及收集管；(10) Take 500 μL of 80% ethanol in the RNeasy MinElute spin column, tightly cover the column cap and centrifuge at 8000 rpm for 2 minutes at room temperature, discard the waste liquid and the collection tube;
(11)将RNeasy MinElute spin column转移至2mL新收集管内，打开柱盖12000rpm室温离心5min以使柱内薄膜干燥，弃废液及收集管；(11) Transfer the RNeasy MinElute spin column to a new 2mL collection tube, open the column cover and centrifuge at 12000rpm at room temperature for 5min to dry the film in the column, discard the waste liquid and the collection tube;
(12)将RNeasy MinElute spin column转移至1.5mL新收集管内，在薄膜中央加入20μL去RNA酶水，冰上静置3h，轻轻关闭柱盖，12000rpm离心1min以洗脱RNA，收集管内即为提取得到的RNA。(12) Transfer the RNeasy MinElute spin column to a new 1.5mL collection tube, add 20μL of RNase-free water to the center of the film, let it stand on ice for 3 hours, gently close the column cover, and centrifuge at 12000rpm for 1min to elute the RNA. The collection tube is Extract the resulting RNA.
RNA浓度检测RNA concentration detection
(1)将收集管置于冰上，用移液器依次轻轻混匀其内溶液；(1) Place the collection tube on ice, and gently mix the solution in it with a pipette;
(2)以焦碳酸二乙酯(diethypyrocarbonate，DEPC)处理过的无菌超纯水(DEPC水)作为对照，取1μL DEPC水于OD-1000+One Drop分光光度计(五义科技，中国)下样品台中央加样孔内进行调零；(2) Using sterile ultrapure water (DEPC water) treated with diethylpyrocarbonate (DEPC) as a control, take 1 μL of DEPC water in an OD-1000+One Drop spectrophotometer (Wuyi Technology, China) Perform zero adjustment in the sample hole in the center of the lower sample platform;
(3)用吸水纸擦干DEPC水，依次取RNA样本1μL于加样孔内，操作计算机配套程序检测RNA浓度，每次测量前注意擦净前次样本。全部RNA样本均检测两次，取均值作为最终浓度。(3) Dry the DEPC water with absorbent paper, take 1 μL of RNA samples in the sampling hole in turn, operate the computer supporting program to detect the RNA concentration, and pay attention to cleaning the previous sample before each measurement. All RNA samples were tested twice, and the mean value was taken as the final concentration.
RNA逆转录RNA reverse transcription
利用HiScript Q RT SuperMix for qPCR Kit(Vazyme，中国)将RNA分子逆转录为互补DNA(complementary DNA，cDNA)分子。具体操作步骤如下：RNA molecules were reverse transcribed into complementary DNA (complementary DNA, cDNA) molecules using HiScript Q RT SuperMix for qPCR Kit (Vazyme, China). The specific operation steps are as follows:
(1)0.2mL无RNA酶PCR管内加入2μL 4×gDNA wiper Mix试剂(Vazyme，中国)及120ng RNA样本(样本体积根据120ng/样本浓度计算得出)，之后向EP管内加入无RNA酶水至总溶液体积8μL，离心1s混匀，42℃放置2min；(1) Add 2 μL of 4×gDNA wiper Mix reagent (Vazyme, China) and 120ng RNA sample (the sample volume is calculated based on the concentration of 120ng/sample) into a 0.2mL RNase-free PCR tube, and then add RNase-free water to the EP tube to The total solution volume is 8 μL, centrifuge for 1 second to mix well, and place at 42°C for 2 minutes;
(2)向EP管内加2μL 5×qRT SuperMix II试剂(Vazyme，中国)，离心1s混匀；(2) Add 2 μL of 5×qRT SuperMix II reagent (Vazyme, China) to the EP tube, and centrifuge for 1 second to mix;
(3)将EP管转移至TC-5000梯度PCR仪(TECHNE，英国)内进行RNA逆转录，参数设置为25℃/10min，50℃/30min，85℃/5min。(3) Transfer the EP tube to a TC-5000 gradient PCR instrument (TECHNE, UK) for RNA reverse transcription, with parameters set at 25°C/10min, 50°C/30min, and 85°C/5min.
Real-time PCRReal-time PCR
利用AceQ qPCR SYBR Green Master Mix(Vazyme，中国)对cDNA进行扩增。引物序列如表1所示，具体操作步骤如下：cDNA was amplified using AceQ qPCR SYBR Green Master Mix (Vazyme, China). The primer sequences are shown in Table 1, and the specific operation steps are as follows:
(1)取0.2mL无RNA酶PCR管，加入10μL AceQ qPCR SYBR Green Master Mix试剂、0.4μL circDYM发散引物1、0.4μL circDYM发散引物2、2μL RNA逆转录中获取的cDNA，加入灭菌蒸馏水使溶液总量达到20μL；(1) Take 0.2mL RNase-free PCR tube, add 10μL AceQ qPCR SYBR Green Master Mix reagent, 0.4μL circDYM Divergent Primer 1, 0.4μL circDYM Divergent Primer 2, 2μL cDNA obtained in RNA reverse transcription, add sterilized distilled water to make The total amount of the solution reaches 20 μL;
(2)取相同0.2mL无RNA酶PCR管，加入10μL AceQ qPCR SYBR Green Master Mix试剂、0.4μL甘油醛-3-磷酸脱氢酶(glyceraldehyde-3-phosphate dehydrogenase，GAPDH)引物1、0.4μL GAPDH引物2、2μL RNA逆转录中获取的cDNA，加入灭菌蒸馏水使溶液总量达到20μL；(2) Take the same 0.2mL RNase-free PCR tube, add 10μL AceQ qPCR SYBR Green Master Mix reagent, 0.4μL glyceraldehyde-3-phosphate dehydrogenase (glyceraldehyde-3-phosphate dehydrogenase, GAPDH) primer 1, 0.4μL GAPDH Primer 2, cDNA obtained in 2 μL RNA reverse transcription, add sterilized distilled water to make the total solution reach 20 μL;
(3)将(1)、(2)中所得的每种cDNA样本溶液分别加入PCR板两孔内。上样结束后盖好盖膜，3000rpm离心1min以使试剂沉底；(3) Add each cDNA sample solution obtained in (1) and (2) into two wells of the PCR plate respectively. After loading the sample, cover the membrane and centrifuge at 3000rpm for 1min to make the reagent sink to the bottom;
(4)将PCR板放置于StepOne Real-Time PCR System(Applied Biosystems，美国)内进行扩增，参数设置为：95℃/5min、95℃/10s+60℃/30s(40个循环)；(4) Place the PCR plate in the StepOne Real-Time PCR System (Applied Biosystems, USA) for amplification, the parameters are set as: 95°C/5min, 95°C/10s+60°C/30s (40 cycles);
(5)得到样本循环阈值(Cycle threshold，Ct)，以GAPDH作为内参，利用2
-△△Ct法[△Ct
(受试)＝Ct
(受试目的基因)-Ct
(受试内参基因)；-△△Ct
(受试)＝△Ct
(对照)均值-△Ct
(受试)]计算样本的倍数变化(fold change，FC)值[FC
(受试)＝2
-△△Ct
(受试)/2
-△△Ct
(对照)均值]。
(5) Obtain sample cycle threshold (Cycle threshold, Ct), with GAPDH as internal reference, utilize 2 -ΔΔCt method [ΔCt (tested) =Ct (tested target gene) -Ct (tested internal reference gene) ; -△△Ct (test) = △Ct (control) mean-△Ct (test) ] calculate the fold change (fold change, FC) value of the sample [FC (test) = 2 -△△Ct (test ) /2 - △△Ct (control) mean].
表1 PCR引物序列Table 1 PCR primer sequences
缩略词：PCR：聚合酶链反应；GAPDH：甘油醛-3-磷酸脱氢酶；circDYM：环状RNA DYM。Abbreviations: PCR: polymerase chain reaction; GAPDH: glyceraldehyde-3-phosphate dehydrogenase; circDYM: circular RNA DYM.
NC于入组后接受空腹静脉血采集，MDD患者于基线期及治疗结束后接受两次血液样本采集，利用实时聚合酶链反应对血浆circDYM表达水平进行检测。NC received fasting venous blood collection after enrollment, and MDD patients received two blood sample collections at baseline and after treatment, and real-time polymerase chain reaction was used to detect the expression level of plasma circDYM.
实验结果显示：experiment result shows:
(1)参见图2，MDD患者基线期血浆circDYM与NC相比呈显著低表达(z＝-2.785，p＝0.005)。MDD三个亚组间比较结果表明，个体化组、标准化组及假治疗组circDYM表达未见显著统计学差异(H＝1.421，p＝0.491)。(1) Referring to Figure 2, the expression of circDYM in the plasma of MDD patients at baseline was significantly lower than that of NC (z=-2.785, p=0.005). The results of comparison among the three subgroups of MDD showed that there was no significant statistical difference in the expression of circDYM in the individualized group, the standardized group and the sham treatment group (H=1.421, p=0.491).
(2)经分析，5天治疗结束后，MDD三个亚组及NC组间血浆circDYM表达水平存在显著差异(H＝12.673，p＝0.005)。如图3所示，在接受5天个体化或标准化VC-rTMS治疗后，患者血浆circDYM水平均显著升高(个体化组：t＝-2.420，p＝0.025；标准化组：t＝-2.998，p＝0.006)，达到正常状态，与NC组间无统计学差异(个体化组：校正H＝-0.566，p＝1.000；标准化组：校正H＝0.838，p＝1.000)。反之，假治疗5天后患者血浆circDYM表达呈进一步下降趋势(t＝1.423，p＝0.170)，显著低于标准化治疗5天后患者血浆水平(校正H＝3.418，p＝0.004)及NC水平(校正H＝-2.783，p＝0.032)。(2) After analysis, after 5 days of treatment, there were significant differences in plasma circDYM expression levels among the three MDD subgroups and the NC group (H=12.673, p=0.005). As shown in Figure 3, after 5 days of individualized or standardized VC-rTMS treatment, the plasma circDYM levels of patients were significantly increased (individualized group: t=-2.420, p=0.025; standardized group: t=-2.998, p=0.006), reached the normal state, and had no statistical difference with the NC group (individualized group: corrected H=-0.566, p=1.000; standardized group: corrected H=0.838, p=1.000). On the contrary, after 5 days of sham treatment, the expression of plasma circDYM showed a further downward trend (t=1.423, p=0.170), which was significantly lower than the plasma level (corrected H=3.418, p=0.004) and NC level (corrected H =-2.783, p=0.032).
(3)本研究将年龄、性别、受教育年限、利手作为控制变量对MDD患者circDYM基线期水平及神经心理评分进行偏相关分析，进行协变量矫正。结果显示，MDD患者基线期血浆circDYM表达水平与HAMD-24总分、认知障碍因子分及BSI-CV-C评分呈显著正相关(HAMD-24：r＝0.267，p＝0.026；认知障碍因子分：r＝0.239，p＝0.046；BSI-CV-C：r＝0.252，p＝0.036)，详见图4。利用多元线性回归分析对该结果进行进一步验证，结果显示circDYM与上述三项评估间的相关关系均被证实具有统计学意义(HAMD-24：标准化β＝0.249；p＝0.028；认知障碍因子分：标准化β＝0.212，p＝0.045；BSI-CV-C：标准化β＝0.264，p＝0.025)。(3) In this study, age, gender, years of education, and handedness were used as control variables to perform partial correlation analysis on the baseline level of circDYM and neuropsychological scores in MDD patients, and covariate correction was performed. The results showed that the plasma circDYM expression level in MDD patients at baseline was significantly positively correlated with HAMD-24 total score, cognitive impairment factor score and BSI-CV-C score (HAMD-24: r=0.267, p=0.026; cognitive impairment Factor score: r=0.239, p=0.046; BSI-CV-C: r=0.252, p=0.036), see Figure 4 for details. The result was further verified by multiple linear regression analysis, and the results showed that the correlation between circDYM and the above three assessments was confirmed to be statistically significant (HAMD-24: standardized β=0.249; p=0.028; cognitive impairment factor score : normalized β=0.212, p=0.045; BSI-CV-C: normalized β=0.264, p=0.025).
Hamilton汉密尔顿抑郁量表(HAMD-24项)可用于抑郁症、双向情感障碍、神经症等多种疾病的抑郁症状之评定，尤其适用于抑郁症，根据评分可以判断是否患有抑郁症以及患有抑郁症的程度。由于本发明证明了基线期circDYM的表达水平与HAMD-24评分之间以及与HAMD-24认知障碍因子分之间具有显著相关性的关系，可以通过检测患者基线期circDYM的表达水平预测HAMD-24评分及其认知障碍因子分，进而用于客观评价是否患有抑郁症、抑郁症的严重程度、抑郁症相关症状以及对认知障碍的治疗效果。The Hamilton Depression Scale (HAMD-24 items) can be used for the evaluation of depressive symptoms of depression, bipolar disorder, neurosis and other diseases, especially for depression. degree of depression. Since the present invention proves that there is a significant correlation between the expression level of circDYM in the baseline period and the HAMD-24 score and between the HAMD-24 cognitive impairment factor scores, it is possible to predict the HAMD- 24 score and its cognitive impairment factor score, which are then used to objectively evaluate whether you have depression, the severity of depression, symptoms related to depression, and the treatment effect on cognitive impairment.
本发明还证明了贝克***意念量表与基线期circDYM的表达水平之间具有显著相关性的关系，可以通过检测基线期circDYM的表达水平预测患者的***倾向。The present invention also proves that there is a significant correlation between the Beck Suicidal Ideation Scale and the expression level of circDYM in the baseline period, and the suicide tendency of patients can be predicted by detecting the expression level of circDYM in the baseline period.
(4)基线期血浆circDYM水平识别MDD患者的曲线下面积(area under the curve，AUC)为0.671[95％置信区间(confidence interval，CI)：0.565-0.777]，对应敏感度及特异度分别为84.38％及53.42％。(4) The area under the curve (AUC) of the plasma circDYM level in the baseline period to identify MDD patients was 0.671 [95% confidence interval (CI): 0.565-0.777], and the corresponding sensitivity and specificity were respectively 84.38% and 53.42%.
此外，研究进一步分析了MDD患者基线期circDYM表达水平对5天个体化或标准化VC-rTMS治疗反应以及治疗结束后4周随访期内恢复情况的预测效能。如图5所示，circDYM预测个体化治疗反应的AUC仅为0.633(95％CI：0.404-0.861，敏感度＝56.25％，特异度＝87.50％)，而预测随访期恢复情况的AUC更是仅为0.589(95％CI：0.318-0.860，敏感度＝42.86％，特异度＝87.50％)。circDYM预测标准化VC-rTMS治疗反应及随访期恢复情况的效 能较高，对应AUC分别为0.706(95％CI：0.480-0.932，敏感度＝94.12％，特异度＝54.55％)及0.799(95％CI：0.623-0.975，敏感度＝76.92％，特异度＝76.92％)。In addition, the study further analyzed the predictive power of circDYM expression levels at baseline in MDD patients on the response to 5-day individualized or standardized VC-rTMS treatment and the recovery during the 4-week follow-up period after the end of treatment. As shown in Figure 5, the AUC of circDYM for predicting individualized treatment response was only 0.633 (95% CI: 0.404-0.861, sensitivity=56.25%, specificity=87.50%), and the AUC for predicting recovery during the follow-up period was only 0.633. It was 0.589 (95% CI: 0.318-0.860, sensitivity=42.86%, specificity=87.50%). circDYM has high performance in predicting standardized VC-rTMS treatment response and recovery during follow-up, corresponding to AUC of 0.706 (95%CI: 0.480-0.932, sensitivity = 94.12%, specificity = 54.55%) and 0.799 (95%CI : 0.623-0.975, sensitivity=76.92%, specificity=76.92%).
结论：上述结果证实能够通过外周血的血浆中circDYM的定量检测进行MDD的标准化诊断。其中，circDYM在MDD患者血浆中呈显著低表达，其对于MDD识别的敏感度较高；且随着重复经颅磁刺激治疗，circDYM表达水平会随之提高。此外，基线期circDYM表达水平可有效预测标准化VC-rTMS近、远期疗效，且于VC-rTMS治疗后显著升高，支持了circDYM作为生物标记物在MDD识别及VC-rTMS抗抑郁疗效预测中具有较高价值。Conclusions: The above results demonstrate the ability to standardize the diagnosis of MDD by quantitative detection of circDYM in peripheral blood plasma. Among them, circDYM was significantly low-expressed in the plasma of MDD patients, and its sensitivity to MDD recognition was high; and with repeated transcranial magnetic stimulation treatment, the expression level of circDYM would increase accordingly. In addition, the expression level of circDYM in the baseline period can effectively predict the short-term and long-term efficacy of standardized VC-rTMS, and it increases significantly after VC-rTMS treatment, which supports the use of circDYM as a biomarker in the identification of MDD and the prediction of the antidepressant efficacy of VC-rTMS have a higher value.
综上，本研究证实了circDYM在MDD患者血浆中呈显著低表达，其对于MDD识别的敏感度较高；基线期circDYM水平在预测标准化VC-rTMS近、远期疗效中具有较高效能，且于VC-rTMS治疗后显著升高，支持了circDYM作为生物标记物在MDD识别及VC-rTMS抗抑郁疗效预测中的价值。In summary, this study confirmed that circDYM was significantly lower expressed in the plasma of MDD patients, and its sensitivity to MDD recognition was higher; circDYM levels in the baseline period had higher efficacy in predicting the short-term and long-term curative effects of standardized VC-rTMS, and Significantly increased after VC-rTMS treatment, supporting the value of circDYM as a biomarker in the identification of MDD and the prediction of VC-rTMS antidepressant efficacy.
实施例2 基于蛋白组学筛选用于诊断抑郁症和预测治疗效果的候选蛋白Example 2 Screening of candidate proteins for diagnosing depression and predicting treatment effects based on proteomics
研究以7名MDD极端性状患者及7名对照作为发现队列，分别利用生物信息学及机器学***进行验证。随后利用酶联免疫吸附试验，完成对24名个体化组、27名标准化组及23名假治疗组患者相应治疗前后血浆候选蛋白表达变化的检测。In the study, 7 patients with MDD extreme traits and 7 controls were used as the discovery cohort, and bioinformatics and machine learning methods were used to screen the target proteins that meet the requirements, and the expression levels of the screened candidate proteins were evaluated in the discovery cohort and validation cohort. authenticating. Then, the enzyme-linked immunosorbent assay was used to detect the expression changes of plasma candidate proteins before and after corresponding treatment in 24 individualized group, 27 standardized group and 23 sham treatment group patients.
纳入发现队列及验证队列两组受试样本，发现队列包括7名具有***未遂史的极端性状MDD患者及7名在年龄、性别、受教育年限、利手方面与之完全匹配的健康对照，共计14人；验证队列为74名MDD患者(包括24名个体化组、27名标准化组及23名假治疗组)和60名健康对照，共计134人。Two groups of samples were included in the discovery cohort and the verification cohort. The discovery cohort included 7 MDD patients with extreme traits who had a suicide attempt history and 7 perfectly matched healthy controls in terms of age, gender, years of education, and handedness. A total of 14 people; the validation cohort consisted of 74 MDD patients (including 24 individualized groups, 27 standardized groups and 23 sham treatment groups) and 60 healthy controls, a total of 134 people.
本实施例利用生物信息学及机器学***均显著高于NC的蛋白。In this example, bioinformatics and machine learning methods were used to screen candidate proteins in the discovery cohort, and then to verify them in the verification cohort, to screen for proteins whose expression levels in the plasma of MDD patients at the baseline period were significantly higher than those of NC.
结果：result:
(1)参见图6，发现4种候选蛋白在基线期MDD患者血浆中的表达水平均显著高于NC(CRP：t＝7.411，p<0.001；ATIII：t＝7.067，p<0.001；ITIH4：t＝6.655，p<0.001；VDB：t＝5.903，p<0.001)。这四种蛋白分别为：C反应蛋白(C-reactive protein，CRP)、抗凝血酶III(antithrombin III，ATIII)、间-alpha-胰蛋白酶抑制剂重链H4(inter-alpha-trypsin inhibitor heavy chain H4，ITIH4)及维生素D连接蛋白(vitamin D binding protein，VDB)。(1) Referring to Figure 6, it was found that the expression levels of the four candidate proteins in the plasma of MDD patients at baseline were significantly higher than those of NC (CRP: t=7.411, p<0.001; ATIII: t=7.067, p<0.001; ITIH4: t=6.655, p<0.001; VDB: t=5.903, p<0.001). These four proteins are: C-reactive protein (C-reactive protein, CRP), antithrombin III (antithrombin III, ATIII), inter-alpha-trypsin inhibitor heavy chain H4 (inter-alpha-trypsin inhibitor heavy chain chain H4, ITIH4) and vitamin D binding protein (vitamin D binding protein, VDB).
(2)参见图7，个体化治疗后，患者ATIII、ITIH4及VDB血浆表达水平显著降低(ATIII：t＝5.447，p<0.001；ITIH4：t＝2.893，p＝0.008；VDB：t＝2.955，p＝0.007)；标准化治疗后，全 部4种候选蛋白在MDD患者血浆中的表达量均显著降低(CRP：t＝3.298，p＝0.003；ATIII：t＝4.523，p<0.001；ITIH4：t＝4.589，p<0.001；VDB：t＝3.029，p＝0.005)；假治疗后，MDD患者血浆中4种蛋白表达水平无显著改变。(2) See Figure 7, after individualized treatment, the plasma expression levels of ATIII, ITIH4 and VDB were significantly reduced (ATIII: t=5.447, p<0.001; ITIH4: t=2.893, p=0.008; VDB: t=2.955, p=0.007); after standardized treatment, the expression levels of all four candidate proteins in the plasma of MDD patients were significantly reduced (CRP: t=3.298, p=0.003; ATIII: t=4.523, p<0.001; ITIH4: t= 4.589, p<0.001; VDB: t=3.029, p=0.005); after the sham treatment, the expression levels of the four proteins in the plasma of MDD patients had no significant changes.
(3)抗抑郁治疗前后患者血浆ATIII表达水平变化值与神经心理评估变化值(HAMD-24减分值、SDS减分值、SAS减分值、BHS减分值、Stroop C减分值)的关系。结果显示，抗抑郁治疗前后患者血浆ATIII表达水平与HAMD-24减分值、SDS减分值、SAS减分值、BHS减分值呈显著正相关(HAMD-24：r＝0.539，p＝0.010；SDS减分值：r＝0.598，p＝0.003；SAS减分值：r＝0.431，p＝0.045，Stroop C减分值：r＝0.507，p＝0.016)，与Stroop C减分值显著负相关(r＝-0.056，p＝0.007)，详见图8。(3) Changes in plasma ATIII expression levels before and after antidepressant treatment and changes in neuropsychological assessments (HAMD-24, SDS, SAS, BHS, and Stroop C) relation. The results showed that the plasma ATIII expression level before and after antidepressant treatment was significantly positively correlated with HAMD-24, SDS, SAS and BHS scores (HAMD-24: r=0.539, p=0.010 ;SDS deduction value: r=0.598, p=0.003; SAS deduction value: r=0.431, p=0.045, Stroop C deduction value: r=0.507, p=0.016), and Stroop C deduction value significantly negative Correlation (r=-0.056, p=0.007), see Figure 8 for details.
由于本发明证明了抗抑郁治疗前后患者血浆ATIII表达水平变化值与神经心理评估变化值之间具有显著相关性的关系，可以通过检测患者抗抑郁治疗前后患者血浆ATIII表达水平变化值预测HAMD-24、SDS、SAS、BHS、Stroop C，进而用于客观评价抗抑郁治疗效果、以及相关症状的缓解情况。Since the present invention proves that there is a significant correlation between the change value of plasma ATIII expression level before and after antidepressant treatment and the change value of neuropsychological assessment, it is possible to predict HAMD-24 by detecting the change value of patient plasma ATIII expression level before and after antidepressant treatment. , SDS, SAS, BHS, Stroop C, and then used to objectively evaluate the effect of antidepressant treatment and the relief of related symptoms.
此外，个体化治疗前后ATIII水平变化值与家庭APGAR评分在SAS减分值上存在交互作用(标准化β＝0.418，p＝0.042)，详见图9，即个体化治疗后ATIII表达减少越显著且家庭APGAR评分越高的患者，其SAS评估减分越明显。In addition, there is an interaction between the change of ATIII level before and after individualized treatment and the family APGAR score on SAS score reduction (standardized β=0.418, p=0.042), see Figure 9 for details, that is, the more significant the decrease in ATIII expression after individualized treatment and The higher the family APGAR score, the more obvious the reduction in SAS assessment.
(4)通过个体化治疗基线期ATIII表达水平或VC-rTMS治疗后ATIII表达水平评估治疗效果的研究(4) Research on the evaluation of treatment effect by the expression level of ATIII in the baseline period of individualized treatment or the expression level of ATIII after VC-rTMS treatment
分别评估以下几种预测的准确性和敏感度：1)通过基线期ATIII表达水平预测5天治疗反应情况；2)通过基线期ATIII表达水平预测4周随访期内恢复情况；3)通过个体化VC-rTMS治疗后ATIII表达水平识别患者治疗反应；4)通过个体化VC-rTMS治疗后ATIII表达水平预测4周随访期内恢复情况。The accuracy and sensitivity of the following predictions were evaluated separately: 1) predicting the 5-day treatment response through the baseline ATIII expression level; 2) predicting the recovery during the 4-week follow-up period through the baseline ATIII expression level; 3) through individualized The expression level of ATIII after VC-rTMS treatment was used to identify the treatment response of patients; 4) The expression level of ATIII after individualized VC-rTMS treatment was used to predict the recovery during the 4-week follow-up period.
结果见图10，个体化治疗后ATIII水平在评估5天VC-rTMS治疗反应及预测4周随访期间恢复情况的AUC分别为0.875及0.828。基线期ATIII表达水平预测5天VC-rTMS治疗反应及预测4周随访期间恢复情况的AUC分别为0.547和0.688。The results are shown in Figure 10. After individualized treatment, the AUCs of ATIII levels in evaluating the response to 5-day VC-rTMS treatment and predicting recovery during the 4-week follow-up period were 0.875 and 0.828, respectively. The AUCs of ATIII expression level at baseline in predicting response to 5-day VC-rTMS treatment and recovery during 4-week follow-up were 0.547 and 0.688, respectively.
对于个体化组来说，VC-rTMS治疗后的ATIII水平具有更高的疗效预测能力，且其对于识别MDD患者有无治疗反应具有更高的特异度(AUC＝0.875，95％CI：0.714-1.000，敏感度＝0.750，特异度＝0.938)，而对于预测随访期恢复情况则有更高的敏感度(AUC＝0.828，95％CI：0.656-1.000，敏感度＝0.875，特异度＝0.625)。反之，基线期ATIII表达水平无法有效预测患者 对治疗的反应情况及随访期间的恢复情况(AUC＝0.547，95％CI：0.250-0.844，敏感度＝0.375，特异度＝1.000；AUC＝0.688，95％CI：0.456-0.919，敏感度＝0.750，特异度＝0.625)。For the individualized group, the ATIII level after VC-rTMS treatment has a higher efficacy predictive ability, and it has a higher specificity for identifying the treatment response in MDD patients (AUC=0.875, 95% CI: 0.714- 1.000, sensitivity = 0.750, specificity = 0.938), and higher sensitivity for predicting recovery during the follow-up period (AUC = 0.828, 95% CI: 0.656-1.000, sensitivity = 0.875, specificity = 0.625) . On the contrary, the expression level of ATIII in the baseline period could not effectively predict the patient's response to treatment and recovery during follow-up (AUC=0.547, 95%CI: 0.250-0.844, sensitivity=0.375, specificity=1.000; AUC=0.688,95 %CI: 0.456-0.919, sensitivity = 0.750, specificity = 0.625).
(5)通过标准化治疗基线期ATIII表达水平或VC-rTMS治疗后ATIII表达水平评估治疗效果的研究(5) Research on the evaluation of treatment effect by ATIII expression level in the baseline period of standardized treatment or ATIII expression level after VC-rTMS treatment
分别评估以下几种预测的准确性和敏感度：1)通过基线期ATIII表达水平预测5天治疗反应情况；2)通过基线期ATIII表达水平预测4周随访期内恢复情况；3)通过个体化VC-rTMS治疗后ATIII表达水平识别患者治疗反应；4)通过个体化VC-rTMS治疗后ATIII表达水平预测4周随访期内恢复情况。The accuracy and sensitivity of the following predictions were evaluated separately: 1) predicting the 5-day treatment response through the baseline ATIII expression level; 2) predicting the recovery during the 4-week follow-up period through the baseline ATIII expression level; 3) through individualized The expression level of ATIII after VC-rTMS treatment was used to identify the treatment response of patients; 4) The expression level of ATIII after individualized VC-rTMS treatment was used to predict the recovery during the 4-week follow-up period.
结果见图11，标准化治疗组基线期血浆ATIII水平在预测MDD患者治疗反应及4周恢复情况中的AUC分别为0.771及0.736。The results are shown in Figure 11. The AUCs of the baseline plasma ATIII levels in the standardized treatment group in predicting the treatment response and 4-week recovery of MDD patients were 0.771 and 0.736, respectively.
见图11，与个体化组结果相反，标准化治疗组基线期血浆ATIII水平在预测MDD患者5天治疗反应及4周恢复情况中更有价值(治疗反应：AUC＝0.771，95％CI：0.571-0.971，敏感度＝0.588，特异度＝0.900；恢复情况：AUC＝0.736，95％CI：0.529-0.943，敏感度＝0.643，特异度＝0.846)，而标准化VC-rTMS治疗后的ATIII表达水平则未表现出有效的疗效预测效能(治疗反应：AUC＝0.524，95％CI：0.293-0.754，敏感度＝0.500，特异度＝0.706；恢复情况：AUC＝0.533，95％CI：0.309-0.757，敏感度＝0.786，特异度＝0.385)。As shown in Figure 11, contrary to the results of the individualized group, the baseline plasma ATIII level in the standardized treatment group is more valuable in predicting the 5-day treatment response and 4-week recovery of MDD patients (treatment response: AUC=0.771, 95%CI: 0.571- 0.971, sensitivity=0.588, specificity=0.900; recovery: AUC=0.736, 95%CI: 0.529-0.943, sensitivity=0.643, specificity=0.846), while the ATIII expression level after standardized VC-rTMS treatment was Did not show effective predictive efficacy of efficacy (treatment response: AUC=0.524, 95%CI: 0.293-0.754, sensitivity=0.500, specificity=0.706; recovery: AUC=0.533, 95%CI: 0.309-0.757, sensitive degree=0.786, specificity=0.385).
(6)基线期ATIII表达水平可有效预测汉密顿抑郁量表HAMD-24在治疗期间的评分(HAMD-24：t＝2.41，p＝0.020)；基线期ATIII表达水平及其治疗前后变化值可共同预测随访期间HAMD-24评分(基线期ATIII：p＝0.024；ATIII变化值：p＝0.023)。(6) The expression level of ATIII in the baseline period can effectively predict the score of the Hamilton Depression Rating Scale HAMD-24 during treatment (HAMD-24: t=2.41, p=0.020); the expression level of ATIII in the baseline period and its changes before and after treatment They could jointly predict HAMD-24 score during follow-up (ATIII at baseline: p=0.024; change in ATIII: p=0.023).
结论：ATIII在VC-rTMS治疗后表现为蛋白水平的显著下降，且其表达变化与个体化治疗后患者的临床症状改善有关，这也为治疗效果提供了客观评价标准。此外，ATIII在近、远期抗抑郁疗效评估及预测中具有较高效能，提示该蛋白或可作为反映MDD治疗效应的生物标记物。Conclusion: ATIII showed a significant decrease in protein level after VC-rTMS treatment, and its expression changes were related to the improvement of clinical symptoms of patients after individualized treatment, which also provided an objective evaluation standard for the therapeutic effect. In addition, ATIII has higher performance in evaluating and predicting short-term and long-term antidepressant efficacy, suggesting that this protein may be used as a biomarker reflecting the therapeutic effect of MDD.
实施例3、成纤维细胞生长因子9(fibroblast growth factor 9，FGF9)作为抑郁症诊断及靶向视觉皮层的重复经颅磁刺激(VC-rTMS)抗抑郁疗效的生物标记物研究Example 3. Fibroblast growth factor 9 (fibroblast growth factor 9, FGF9) as a biomarker for the diagnosis of depression and the antidepressant efficacy of repetitive transcranial magnetic stimulation (VC-rTMS) targeting the visual cortex
纳入健康对照(NC组)和MDD患者组：NC组人数为30人，MDD患者组为73人(个体化组、标准化组、假治疗组，三组人数分别为24人、26人及23人)。FGF9蛋白定量检测采用R&D Systems ELISA商业试剂盒完成。Include healthy control (NC group) and MDD patient group: the number of NC group is 30 people, MDD patient group is 73 people (individualized group, standardization group, sham treatment group, the number of three groups is 24, 26 and 23 people respectively ). Quantitative detection of FGF9 protein was done with R&D Systems ELISA commercial kit.
结果显示：The results show:
(1)与NC相比，MDD患者基线期血清FGF9呈显著高表达(t＝5.116，p<0.001)。而MDD组划分的3组：个体化治疗组、标准化治疗组和假治疗组，在基线期血清中三组之间没有显著性差异。具体结果见图12。(1) Compared with NC, MDD patients showed significantly higher expression of serum FGF9 at baseline (t=5.116, p<0.001). However, the MDD group was divided into three groups: individualized treatment group, standardized treatment group and sham treatment group, and there was no significant difference between the three groups in baseline serum levels. The specific results are shown in Figure 12.
(2)个体化治疗后MDD患者血清FGF9表达显著减少(t＝3.062，p＝0.006)，而标准化及假治疗后MDD患者血清FGF9表达变化无统计学意义。具体结果见图13。(2) The expression of serum FGF9 in MDD patients was significantly reduced after individualized treatment (t=3.062, p=0.006), while there was no significant change in the expression of serum FGF9 in MDD patients after standardized and sham treatment. The specific results are shown in Figure 13.
(3)VC-rTMS治疗后，应答组患者血清FGF9表达水平显著降低(t＝3.856，p<0.001)，而无应答组FGF9水平则未见明显改变。从第(2)和(3)结果来看，血清FGF9表达水平主要是基于患者的患病程度变化，由于标准化组治疗效果无应答的患者较个体化治疗组更多，所以在针对治疗后的标准化治疗组与治疗前相比FGF9表达变化无统计学意义。由此，也说明FGF9表达水平与患病和治疗后缓解程度相关，能够用于患病程度以及治疗效果的评价。具体结果见图14。(3) After VC-rTMS treatment, the expression level of FGF9 in the response group decreased significantly (t=3.856, p<0.001), while the FGF9 level in the non-response group did not change significantly. Judging from the results of (2) and (3), the expression level of serum FGF9 is mainly based on the change of the disease degree of the patients. Since there are more patients who do not respond to the treatment effect in the standardized group than in the individualized treatment group, it is important to focus on the treatment after treatment. There was no statistically significant change in the expression of FGF9 in the standardized treatment group compared with before treatment. Therefore, it also shows that the expression level of FGF9 is related to the disease and the degree of remission after treatment, and can be used to evaluate the degree of disease and the effect of treatment. The specific results are shown in Figure 14.
根据治疗5天后的抗抑郁疗效，将接受靶向视觉皮层的重复经颅磁刺激治疗的患者分为应答组和无应答组，应答的标准为治疗后HAMD-24评分较基线期下降超过50％，反之则为非应答。结果发现应答组患者血清FGF9表达水平与基线期相比显著降低(t＝3.856，p<0.001)，而非应答组则无统计学差异(t＝1.410，p＝0.168)。According to the antidepressant efficacy after 5 days of treatment, patients receiving repetitive transcranial magnetic stimulation therapy targeting the visual cortex were divided into response group and non-response group. , otherwise it is a non-response. The results showed that the expression level of serum FGF9 in the response group was significantly lower than that in the baseline period (t=3.856, p<0.001), but there was no statistical difference in the non-response group (t=1.410, p=0.168).
(4)见图15，MDD患者基线期血清FGF9表达水平与汉密尔顿焦虑量表(Hamilton Anxiety Scale，HAMA)及抑郁自评量表评分间具有显著相关(HAMA：r＝-0.272，p＝0.023；抑郁自评量表：r＝-0.288，p＝0.016)。上述结果说明MDD患者基线期血清FGF9表达水平可反映其负性情绪严重程度。(4) As shown in Figure 15, there is a significant correlation between the expression level of serum FGF9 in MDD patients at baseline and the scores of Hamilton Anxiety Scale (HAMA) and Depression Self-Rating Scale (HAMA: r=-0.272, p=0.023; Depression self-rating scale: r=-0.288, p=0.016). The above results indicate that the expression level of serum FGF9 in MDD patients at baseline can reflect the severity of their negative emotions.
MDD患者基线期血清FGF9表达水平与HAMA及SDS评分负相关(HAMA：r＝-0.272，p＝0.023；SDS：r＝-0.288，p＝0.016)。The expression level of serum FGF9 in MDD patients at baseline was negatively correlated with HAMA and SDS scores (HAMA: r=-0.272, p=0.023; SDS: r=-0.288, p=0.016).
(5)见图16，个体化VC-rTMS治疗前后FGF9表达变化值与HAMA减分值间呈显著正相关(r＝0.494，p＝0.027)。(5) As shown in Figure 16, there was a significant positive correlation between the change of FGF9 expression before and after individualized VC-rTMS treatment and the HAMA score reduction (r=0.494, p=0.027).
(6)见图17，基线期FGF9表达水平在MDD患者识别中的AUC为0.739，并伴有较高特异性(特异度＝0.767)。(6) As shown in Figure 17, the AUC of FGF9 expression level in the identification of MDD patients in the baseline period was 0.739, with high specificity (specificity=0.767).
综上所述，MDD患者基线期血清FGF9高表达水平可反映其负性情绪严重程度，且对于MDD识别具有较高的准确度及特异性。个体化VC-rTMS治疗后FGF9水平显著下调，并与患者的焦虑症状改善有关。In summary, the high expression level of serum FGF9 in MDD patients at baseline can reflect the severity of their negative emotions, and it has high accuracy and specificity for MDD recognition. The level of FGF9 was significantly downregulated after individualized VC-rTMS treatment and was associated with the improvement of anxiety symptoms in patients.
实施例4 生化指标的联合评估Example 4 Joint Evaluation of Biochemical Indexes
采用支持向量机机器学习方法，对实施例1-3中所筛选出的候选标记物及FGF9在内的6个指标的MDD联合识别效能及VC-rTMS抗抑郁疗效联合估测效能进行了分析。The support vector machine machine learning method was used to analyze the MDD joint recognition performance of the candidate markers screened in Examples 1-3 and 6 indicators including FGF9 and the joint estimation performance of VC-rTMS antidepressant efficacy.
支持向量机器(support vector machine，SVM)学***的检测，预测是否患有抑郁症的准确度达到了91.92％。Support vector machine (support vector machine, SVM) learning model analysis shows that the combination of the above six markers can classify diseases with an accuracy as high as 91.92%. protein, CRP), antithrombin III (antithrombin III, ATIII), inter-alpha-trypsin inhibitor heavy chain H4 (inter-alpha-trypsin inhibitor heavy chain H4, ITIH4), vitamin D linking protein (vitamin D binding protein, VDB) and fibroblast growth factor 9 (fibroblast growth factor 9, FGF9) expression levels, the accuracy of predicting whether suffering from depression reached 91.92%.
此外，本研究基于前文中几种候选标记物所表现出的抗抑郁疗效评估及预测效能，最终选择circDYM及ATIII作为MDD患者疗效预测的联合指标，共同纳入SVM机器学***联合评估及预测rTMS近、远期疗效的准确度则分别高达95.24％及90.48％。另一方面，对于标准化治疗组患者来说，其基线期circDYM及ATIII水平联合预测VC-rTMS治疗反应及恢复情况的准确度分别为92.00％及80.00％，而治疗后二者联合估测MDD患者近、远期治疗效应的准确度则分别达到91.30％及95.65％。In addition, based on the antidepressant efficacy evaluation and prediction performance of several candidate markers in the previous study, circDYM and ATIII were finally selected as the combined indicators for predicting the efficacy of MDD patients, and they were incorporated into the SVM machine learning model for analysis. The results showed that the accuracy of the combination of circDYM and ATIII in predicting the response to individualized VC-rTMS 5-day treatment and the recovery during the 4-week follow-up period at the baseline period was 82.61% and 86.96%, respectively; And the accuracy of predicting the short-term and long-term efficacy of rTMS is as high as 95.24% and 90.48%, respectively. On the other hand, for patients in the standardized treatment group, the accuracy of the combination of circDYM and ATIII levels in the baseline period to predict the response and recovery of VC-rTMS treatment was 92.00% and 80.00%, respectively. The accuracy of short-term and long-term treatment effects reached 91.30% and 95.65%, respectively.
准确度为机器学习计算得到的是否患有抑郁症的结果与医生诊断结果相吻合的比例。例如，100个人被医生诊断为抑郁症，认为这些诊断是100％正确的，不存在任何误诊和错诊。而后通过上面6个指标组合出来的公式或者算法，来诊断这100个人，发现91.92个人用这个公式或算法诊断的是跟医生诊断的一样，另外8个多一点跟医生的诊断不一样，则认为机器学习的方法准确度是91.92％。Accuracy is the proportion of whether the machine learning calculation of depression or not is consistent with the doctor's diagnosis. For example, 100 people are diagnosed with depression by a doctor, thinking that these diagnoses are 100% correct, and there is no misdiagnosis or misdiagnosis. Then use the formula or algorithm combined by the above 6 indicators to diagnose these 100 people, and find that 91.92 people using this formula or algorithm are diagnosed as the same as the doctor's diagnosis, and the other 8 people are slightly different from the doctor's diagnosis, so it is considered The accuracy of the machine learning method is 91.92%.
Claims (10)
- 一种针对用于评估受试者抑郁症患病情况或预测靶向视觉皮层的重复经颅磁刺激对抑郁症治疗效果的检测试剂，其特征在于，所述检测试剂中包含用于检测多种抑郁症生物标志物组合物表达水平的试剂或者检测至少一种抑郁症生物标志物表达水平的试剂；A detection reagent for assessing the prevalence of depression in a subject or predicting the therapeutic effect of repetitive transcranial magnetic stimulation targeting the visual cortex on depression, characterized in that the detection reagent contains a variety of Reagents for expression levels of a depression biomarker composition or reagents for detecting expression levels of at least one depression biomarker;所述抑郁症生物标志物组合物选自环状RNA DYM(circDYM)、抗凝血酶Ⅲ(antithrombinⅢ，ATⅢ)、C反应蛋白(C-reactive protein，CRP)、成纤维细胞生长因子9(fibroblast growth factor 9，FGF9)、维生素D结合蛋白(VDBP)和间-alpha-胰蛋白酶抑制剂重链H4(inter-alpha-trypsin inhibitor heavy chain H4，ITIH4)的组合，或者环状RNA DYM和抗凝血酶Ⅲ的组合；The depression biomarker composition is selected from circular RNA DYM (circDYM), antithrombin III (antithrombin III, AT III), C-reactive protein (C-reactive protein, CRP), fibroblast growth factor 9 (fibroblast growth factor 9, FGF9), vitamin D binding protein (VDBP) and inter-alpha-trypsin inhibitor heavy chain H4 (inter-alpha-trypsin inhibitor heavy chain H4, ITIH4) combination, or circular RNA DYM and anticoagulant Combination of blood enzyme III;所述抑郁症生物标志物组合物选自环状RNA DYM、抗凝血酶Ⅲ、C反应蛋白、成纤维细胞生长因子9、维生素D结合蛋白或间-alpha-胰蛋白酶抑制剂重链H4；The depression biomarker composition is selected from circular RNA DYM, antithrombin III, C-reactive protein, fibroblast growth factor 9, vitamin D binding protein or inter-alpha-trypsin inhibitor heavy chain H4;优选地，检测环状RNA DYM的试剂为用于PCR检测的引物和或探针；Preferably, the reagents for detecting circular RNA DYM are primers and or probes for PCR detection;优选地，检测抗凝血酶Ⅲ的试剂为抗凝血酶Ⅲ的抗体或抗凝血酶Ⅲ的ELISA定量检测试剂盒；Preferably, the reagent for detecting anti-thrombin III is an anti-thrombin III antibody or an ELISA quantitative detection kit for anti-thrombin III;优选地，检测C反应蛋白的试剂为C反应蛋白的抗体或C反应蛋白的ELISA定量检测试剂盒；Preferably, the reagent for detecting C-reactive protein is an antibody for C-reactive protein or an ELISA quantitative detection kit for C-reactive protein;优选地，检测成纤维细胞生长因子9的试剂为成纤维细胞生长因子的9ELISA定量检测试剂盒；Preferably, the reagent for detecting fibroblast growth factor 9 is a fibroblast growth factor 9 ELISA quantitative detection kit;优选地，检测维生素D结合蛋白的试剂为维生素D结合蛋白的抗体或维生素D结合蛋白的ELISA定量检测试剂盒；Preferably, the reagent for detecting vitamin D-binding protein is an antibody to vitamin D-binding protein or an ELISA quantitative detection kit for vitamin D-binding protein;优选地，检测间-alpha-胰蛋白酶抑制剂重链H4的试剂为间-alpha-胰蛋白酶抑制剂的抗体、间-alpha-胰蛋白酶抑制剂重链H4的ELISA定量检测试剂盒。Preferably, the reagent for detecting the heavy chain H4 of the inter-alpha-trypsin inhibitor is an antibody to the inter-alpha-trypsin inhibitor and an ELISA quantitative detection kit for the heavy chain H4 of the inter-alpha-trypsin inhibitor.
- 一种用于评估受试者抑郁症患病情况或预测靶向视觉皮层的重复经颅磁刺激对抑郁症治疗效果的试剂盒，其特征在于，所述试剂盒中包含至少一种权利要求1中的检测试剂。A test kit for assessing the prevalence of depression in a subject or predicting the therapeutic effect of repetitive transcranial magnetic stimulation targeting the visual cortex on depression, characterized in that the test kit comprises at least one of claims 1 detection reagents in.
- 权利要求1所述的检测试剂在制备评估抑郁症患病情况的试剂盒中的应用；或者在制备预测靶向视觉皮层的重复经颅磁刺激对于抑郁症疗效的试剂盒中的应用；The application of the detection reagent described in claim 1 in the preparation of a kit for evaluating the prevalence of depression; or the application in the preparation of a kit for predicting the efficacy of repetitive transcranial magnetic stimulation targeting the visual cortex for depression;优选地，靶向视觉皮层的重复经颅磁刺激为标准化治疗方案或个体化治疗方案。Preferably, the repetitive transcranial magnetic stimulation targeting the visual cortex is a standardized treatment plan or an individualized treatment plan.
- 根据权利要求3所述的应用，其特征在于，检测试剂为检测以下标志物的试剂的组合：环状RNA DYM、抗凝血酶Ⅲ、C反应蛋白、成纤维细胞生长因子9、维生素D结合蛋白和 间-alpha-胰蛋白酶抑制剂重链H4，所述应用为在制备评估抑郁症患病情况的试剂盒中的应用；或者The application according to claim 3, wherein the detection reagent is a combination of reagents for detecting the following markers: circular RNA DYM, antithrombin III, C-reactive protein, fibroblast growth factor 9, vitamin D binding Protein and inter-alpha-trypsin inhibitor heavy chain H4, the application is in the preparation of a kit for evaluating the prevalence of depression; or检测试剂为检测以下标志物的试剂的组合：环状RNA DYM和抗凝血酶Ⅲ，所述应用为在制备预测靶向视觉皮层的重复经颅磁刺激对于抑郁症疗效的试剂盒中的应用。The detection reagent is a combination of reagents for detecting the following markers: circular RNA DYM and antithrombin III, and the application is the application in the preparation of a kit for predicting the curative effect of repetitive transcranial magnetic stimulation targeting the visual cortex on depression .
- 一种用于评估受试者抑郁症患病或预测靶向视觉皮层的重复经颅磁刺激对于抑郁症疗效的检测设备，其特征在于，所述检测设备中包含样品检测模块和预测模块；A detection device for assessing the prevalence of depression in a subject or predicting the curative effect of repetitive transcranial magnetic stimulation targeting the visual cortex on depression, characterized in that the detection device includes a sample detection module and a prediction module;所述样品检测模块为获得受试者血浆样品中至少一种抑郁症生物标志物表达水平的试剂；所述抑郁症生物标志物选自环状RNA DYM、抗凝血酶Ⅲ、C反应蛋白、成纤维细胞生长因子9、维生素D结合蛋白或间-alpha-胰蛋白酶抑制剂重链H4中的至少一种；或者为环状RNA DYM、抗凝血酶Ⅲ、C反应蛋白、成纤维细胞生长因子9、维生素D结合蛋白和间-alpha-胰蛋白酶抑制剂重链H4的组合；或者为环状RNA DYM和抗凝血酶Ⅲ的组合；The sample detection module is a reagent for obtaining the expression level of at least one depression biomarker in the subject's plasma sample; the depression biomarker is selected from circular RNA DYM, antithrombin III, C-reactive protein, At least one of fibroblast growth factor 9, vitamin D binding protein, or inter-alpha-trypsin inhibitor heavy chain H4; or circular RNA DYM, antithrombin III, C-reactive protein, fibroblast growth A combination of factor 9, vitamin D binding protein, and inter-alpha-trypsin inhibitor heavy chain H4; or a combination of circular RNA DYM and antithrombin III;所述预测模块为能够根据所述样品检测模块获得的抑郁症生物标志物表达水平的数据，以及预测模块内的计算模型，获得受试者抑郁症患病情况，和或获得靶向视觉皮层的重复经颅磁刺激对于抑郁症疗效的预测情况；The prediction module can obtain the depression prevalence of the subject according to the data of the expression level of depression biomarkers obtained by the sample detection module, and the calculation model in the prediction module, and or obtain the target visual cortex Prediction of the efficacy of repetitive transcranial magnetic stimulation for depression;所述计算模型选自支持向量机器学习模型、线性判别分析模型、递归特征去除模型、微阵列模型的预测分析、逻辑回归模型、CART算法、flextree算法、LART算法、随机森林算法、MART算法、机器学习算法、惩罚回归方法及其组合。The calculation model is selected from support vector machine learning model, linear discriminant analysis model, recursive feature removal model, predictive analysis of microarray model, logistic regression model, CART algorithm, flextree algorithm, LART algorithm, random forest algorithm, MART algorithm, machine Learning algorithms, penalized regression methods, and their combinations.
- 根据权利要求5所述的检测设备，其特征在于，所述计算模型的建立方法为以抑郁症生物标志物在血浆中的表达水平以及患病情况或对于靶向视觉皮层的重复经颅磁刺激治疗反应情况作为参数样本数据，通过机器学习方法进行计算获得计算模型；The detection device according to claim 5, characterized in that, the method for establishing the calculation model is based on the expression levels of depression biomarkers in plasma and the disease status or repetitive transcranial magnetic stimulation targeting the visual cortex The treatment response is used as parameter sample data, which is calculated by machine learning methods to obtain a calculation model;优选地，所述计算模型的建立方法为以抑郁症生物标志物在血浆中的表达水平以及患病情况或对于靶向视觉皮层的重复经颅磁刺激治疗反应情况作为参数样本数据，对支持向量机进行训练，获得用于根据抑郁症生物标志物在血浆中的表达水平数据进行抑郁症预测或对于靶向视觉皮层的重复经颅磁刺激治疗反应情况预测的支持向量机模型。Preferably, the establishment method of the calculation model is to use the expression level of the depression biomarker in the plasma and the condition of the disease or the response to the repeated transcranial magnetic stimulation treatment targeting the visual cortex as the parameter sample data, and the support vector The machine was trained to obtain a support vector machine model for predicting depression based on the expression level data of depression biomarkers in plasma or for predicting the response to repetitive transcranial magnetic stimulation therapy targeting the visual cortex.
- 根据权利要求5或6所述的检测设备，其特征在于，所述样品检测模块包括权利要求1所述的检测试剂或权利要求2所述的试剂盒。The detection device according to claim 5 or 6, wherein the sample detection module comprises the detection reagent according to claim 1 or the kit according to claim 2.
- 一种抑郁症生物标志物或其组合物，其特征在于，所述抑郁症生物标志物选自环状 RNA DYM、抗凝血酶Ⅲ、C反应蛋白、成纤维细胞生长因子9、维生素D结合蛋白或间-alpha-胰蛋白酶抑制剂重链H4中的至少一种；A depression biomarker or its composition, characterized in that, the depression biomarker is selected from circular RNA DYM, antithrombin III, C-reactive protein, fibroblast growth factor 9, vitamin D binding At least one of protein or inter-alpha-trypsin inhibitor heavy chain H4;所述组合物为环状RNA DYM、抗凝血酶Ⅲ、C反应蛋白、成纤维细胞生长因子9、维生素D结合蛋白和间-alpha-胰蛋白酶抑制剂重链H4的组合，或者为环状RNA DYM和抗凝血酶Ⅲ的组合。The composition is a combination of circular RNA DYM, antithrombin III, C-reactive protein, fibroblast growth factor 9, vitamin D binding protein and inter-alpha-trypsin inhibitor heavy chain H4, or a circular Combination of RNA DYM and antithrombin III.
- 权利要求8所述的抑郁症生物标志物或其组合物作为评估抑郁症患病情况的生物标志物的应用；或者作为预测靶向视觉皮层的重复经颅磁刺激对于抑郁症疗效的生物标志物的应用。The application of the depression biomarker or composition thereof as claimed in claim 8 as a biomarker for evaluating the prevalence of depression; or as a biomarker for predicting the efficacy of repetitive transcranial magnetic stimulation targeting the visual cortex for depression Applications.
- 一种评估抑郁症或预测抑郁症通过重复经颅磁刺激视觉皮层治疗的治疗效果的方法，其特征在于，所述方法包括以下步骤：A method for assessing depression or predicting the therapeutic effect of depression by repeated transcranial magnetic stimulation visual cortex treatment, characterized in that the method comprises the following steps:1)获得受试者血液样品，并检测样品中抑郁症生物标志物或抑郁症生物标志物的组合物表达水平，获得表达水平的数据集；1) Obtain a blood sample from the subject, and detect the expression level of the depression biomarker or the composition of the depression biomarker in the sample, and obtain a data set of the expression level;2)根据步骤1)获得的数据集以及预测计算模型，获得受试者抑郁症患病情况；2) According to the data set obtained in step 1) and the predictive calculation model, the depression prevalence of the subject is obtained;所述预测计算模型选自支持向量机器学习模型、线性判别分析模型、递归特征去除模型、微阵列模型的预测分析、逻辑回归模型、CART算法、flextree算法、LART算法、随机森林算法、MART算法、机器学习算法、惩罚回归方法及其组合；The predictive calculation model is selected from a support vector machine learning model, a linear discriminant analysis model, a recursive feature removal model, a predictive analysis of a microarray model, a logistic regression model, a CART algorithm, a flextree algorithm, a LART algorithm, a random forest algorithm, a MART algorithm, Machine learning algorithms, penalized regression methods and their combinations;所述抑郁症生物标志物选自环状RNA DYM、抗凝血酶Ⅲ、C反应蛋白、成纤维细胞生长因子9、维生素D结合蛋白、间-alpha-胰蛋白酶抑制剂重链H4；The depression biomarker is selected from circular RNA DYM, antithrombin III, C-reactive protein, fibroblast growth factor 9, vitamin D binding protein, inter-alpha-trypsin inhibitor heavy chain H4;所述抑郁症生物标志物的组合物选自环状RNA DYM、抗凝血酶Ⅲ、C反应蛋白、成纤维细胞生长因子9、维生素D结合蛋白、间-alpha-胰蛋白酶抑制剂重链H4中至少一种的组合；The composition of the depression biomarker is selected from circular RNA DYM, antithrombin III, C-reactive protein, fibroblast growth factor 9, vitamin D binding protein, inter-alpha-trypsin inhibitor heavy chain H4 A combination of at least one of;优选地，所述预测计算模型的建立方法为以抑郁症生物标志物在血浆中的表达水平以及患病情况作为参数样本数据，通过机器学习方法进行计算获得计算模型；Preferably, the establishment method of the predictive calculation model is to use the expression level of the depression biomarkers in plasma and the condition of the disease as parameter sample data, and obtain the calculation model through calculation by machine learning method;优选地，所述预测计算模型的建立方法为以抑郁症生物标志物在血浆中的表达水平以及患病情况作为参数样本数据，对支持向量机进行训练，获得用于根据抑郁症生物标志物在血浆中的表达水平数据进行抑郁症预测或对于靶向视觉皮层的重复经颅磁刺激治疗反应情况预测的支持向量机模型；Preferably, the establishment method of the predictive calculation model is to use the expression level of the depression biomarkers in plasma and the condition of the disease as parameter sample data, train the support vector machine, and obtain Support vector machine models for prediction of depression or response to repetitive transcranial magnetic stimulation therapy targeting the visual cortex based on expression level data in plasma;优选地，所述抑郁症生物标志物的组合物优选为环状RNA DYM和抗凝血酶Ⅲ的组合物，环状RNA DYM、抗凝血酶Ⅲ、C反应蛋白、成纤维细胞生长因子9、维生素D结合蛋白和 间-alpha-胰蛋白酶抑制剂重链H4的组合物；Preferably, the composition of the depression biomarker is preferably a composition of circular RNA DYM and antithrombin III, circular RNA DYM, antithrombin III, C-reactive protein, fibroblast growth factor 9 , a composition of vitamin D binding protein and inter-alpha-trypsin inhibitor heavy chain H4;优选地，受试者血液样品为未进行治疗前受试者或进行了重复经颅磁刺激视觉皮层治疗治疗后受试者的血浆样品。Preferably, the blood sample of the subject is the plasma sample of the subject before no treatment or after repeated transcranial magnetic stimulation of the visual cortex.
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