Application of peripheral blood TLR4 and S100A8 / S100A9 in combined diagnosis of depression

Abstract

The invention discloses an application of peripheral blood TLR4 and S100A8 / S100A9 in combined diagnosis of depression. Belongs to the field of biological science, discloses a new application of Toll-like receptor 4 (TLR4) and interacting S100calcium-binding protein A8 / A9 (S100A8 / S100A9) in a peripheral blood NF-kappa B signal channel in combined diagnosis of depression, provides a new application of TLR4 and S100A8 / S100A9 in peripheral blood in diagnosis of depression, and provides a new application of TLR4 and S100A8 / S100A9 in diagnosis of depression by performing whole transcriptome sequencing on peripheral blood of natural depression monkeys and control monkeys. Differential expression TLR4, S100A8 / S100A9 of the natural depression monkeys and the control monkeys is analyzed; the relevance between the expression level of the TLR4 and the S100A8 / S100A9 in the depression monkey and the disease state is determined for the first time, and the TLR4 and the S100A8 / S100A9 are used as a novel molecular marker for depression diagnosis.

Description

Technical Field

[0001] The present invention belongs to the field of biological sciences and relates to a method for diagnosing depression based on the detection of peripheral blood inflammatory markers; specifically, it relates to a new use of peripheral whole blood TLR4 and S100A8 / S100A9 as a combined diagnosis of depression. Background Art

[0002] Depression is a type of emotional disorder characterized by a depressed mood. Currently, the diagnosis of depression and other mental illnesses in clinical practice mainly refers to the standards of the Chinese Classification and Diagnostic Criteria for Mental Disorders (Third Edition) (CCMD-3), the International Classification of Diseases (10th Edition) (ICD-10) of the United States, the Diagnostic and Statistical Manual of Mental Disorders (Fourth Edition) (DSM-IV) and the Diagnostic and Statistical Manual of Mental Disorders (Fifth Edition) (DSM-V). However, this method itself has serious shortcomings: strong subjectivity, poor diagnostic consistency and high misdiagnosis rate. Therefore, in order to achieve early diagnosis, early detection and early intervention, it is of great significance to develop effective objective biomarker detection.

[0003] TLR4 is a pattern recognition receptor that mediates innate immune responses and is expressed in peripheral immune cells as well as glial cells within the central nervous system, such as microglia and astrocytes. In patients with major depressive disorder, the TLR4rs1927911-GG genotype is associated with depressive symptoms, including anxiety and suicidal ideation. The S100A family of proteins is associated with inflammation. The S100A8 / S100A9 complex, known as calprotectin, mediates TLR4-NF-κB signaling activation. S100A12, as an endogenous ligand for TLR4, acts as damage-associated molecular patterns (DAMPs). Summary of the invention

[0004] In view of the above problems, the present invention aims to propose the use of peripheral blood TLR4 and S100A8 / S100A9 as a combined diagnosis of depression.

[0005] The technical solution of the present invention is: the peripheral blood TLR4 and S100A8 / S100A9 described in the present invention are used for the combined diagnosis of depression.

[0006] Furthermore, whole transcriptome sequencing was performed on peripheral blood of depressed monkeys and control monkeys to analyze the differentially expressed mRNAs in depressed monkeys and control monkeys, and then key gene network analysis, machine learning and ROC curve analysis were used to determine that the key mRNAs were TLR4 and S100A8 / S100A9.

[0007] Furthermore, the steps of the combined diagnosis are as follows:

[0008] S1: Naturally depressed monkeys and control monkeys were selected based on their behavior; male cynomolgus monkeys with potential spontaneous depressive behavior were initially selected from candidates with lower social status in the group;

[0009] Low social status includes: 1) being beaten frequently, not resisting, but constantly running away; 2) often being the last to eat; If all of the following criteria are met, such monkeys will be classified as depressive-like monkeys: 1) low social status; 2) like to hide in corners and not interact with people; 3) less exercise; 4) more alert during sleep; 5) persistent depressive-like state for more than 6 months;

[0010] To quantify the degree of depression, the monkeys were first placed in a cage, their daily behavior was videotaped, and behavioral scores were performed;

[0011] S2: Blood sample collection and whole transcriptome sequencing; All monkey blood samples were obtained at the same time of the day (between 10:30 and 11:30 a.m.) and stored at -80°C;

[0012] RNA was extracted from blood samples of both groups; library construction was performed according to standard protocols;

[0013] The library was sequenced using the Illumina high-throughput sequencing platform and a 2×150bp paired-end sequencing strategy. The sequence quality was then verified using FastQC. The filtered reads were compared with the cynomolgus monkey reference database using STAR software. The expression of known genes and transcripts was quantified using the Stringtie analysis program.

[0014] S3: Based on the whole transcriptome sequencing results, the differentially expressed mRNAs in peripheral blood between the MDD group and the control group were screened; differential expression analysis was performed using DEseq2 in R;

[0015] Differentially expressed genes (DEGs) with log2 (fold change)>1 or log2 (fold change)<-1 and statistically significant (P value < 0.05) were identified in the R package;

[0016] Heatmap method was used to evaluate the differences between groups at a general level; Pheatmap package was used to visualize heatmaps, and ggplot2 was used to visualize volcano plots; based on the whole transcriptome sequencing results, differentially expressed mRNAs in peripheral blood between the MDD group and the control group were screened;

[0017] S4: Analyze key gene networks, machine learning and ROC diagnostic curves to clarify the diagnostic value of key differential mRNAs; download molecular interaction information from the STRING database and perform key gene network analysis in Cytoscape software;

[0018] Machine learning methods including support vector machine (SVM), Lasso regression, and random forest were used to identify key molecules; SVM was implemented using the e1071, kernlab, and caret packages in R software;

[0019] Lasso regression uses the glmnet package, and random forest uses the randomForest package; the intersection of the key molecules identified by the three methods is taken; the ROC diagnostic curve is used to predict the diagnostic value of the key molecules;

[0020] Furthermore, in S1, the naturally depressed monkeys screened met the depressive-like behavior, including the evaluation of curling behavior, environmental exploration behavior, anxiety behavior, stereotypic behavior, grooming behavior and autonomous activity behavior.

[0021] Furthermore, in S2, the blood sample collection requires that whole blood be drawn from the monkey on an empty stomach and stored under frozen conditions.

[0022] Further, in S3, the differentially expressed mRNAs satisfying pvalues ​​< 0.05 and |log2FC| > 1 are differentially expressed genes;

[0023] Among them, log2(fold change)>1 is marked as an up-regulated gene; log2(fold change)<-1 is marked as a down-regulated gene.

[0024] The beneficial effects of the present invention are as follows: the present invention discloses a new use of Toll-like receptor 4 (TLR4) and interacting S100 calcium-binding protein A8 / A9 (S100A8 / S100A9) in peripheral blood as a combined diagnosis of depression, provides a new use of TLR4 and S100A8 / S100A9 in peripheral blood in diagnosing depression, and analyzes the differential expression of TLR4 and S100A8 / S100A9 in natural depressed monkeys and control monkeys by whole transcriptome sequencing of peripheral whole blood of natural depressed monkeys and control monkeys; the present invention clarifies for the first time the correlation between the expression levels of TLR4 and S100A8 / S100A9 in depressed monkeys and the disease state, and proposes to use them as new molecular markers for diagnosing depression. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 This is a network diagram of the key genes TLR4 and S100A8 / S100A9 differentially expressed in the peripheral blood of the depressed monkeys of the present invention and the monkeys in the control group;

[0026] Figure 2 This is a machine learning analysis diagram of the differential expression of TLR4 in the peripheral blood of the depressed monkeys of the present invention and the monkeys in the control group;

[0027] Figure 3 is a ROC diagnostic curve diagram of TLR4 differential expression in peripheral blood of the depressed monkeys of the present invention and the monkeys in the control group;

[0028] Figure 4 is a ROC diagnostic curve diagram of the differential expression of S100A8 in the peripheral blood of the depressed monkeys of the present invention and the monkeys in the control group;

[0029] Figure 5 It is a ROC diagnostic curve diagram of the differential expression of S100A9 in the peripheral blood of the depressed monkeys of the present invention and the monkeys in the control group. DETAILED DESCRIPTION

[0030] The specific technical scheme of the present invention is further described in detail below with reference to specific examples.

[0031] As shown in the figure, the present invention discloses a method for diagnosing depression based on the detection of peripheral blood inflammatory markers. For the first time, a new use of Toll-like receptor 4 and interacting S100A8 / S100A9 as biomarkers for specific diagnosis of depression was found in depressed monkeys. Whole transcriptome sequencing was performed on peripheral blood of depressed monkeys and control monkeys to analyze the differentially expressed mRNAs of depressed monkeys and control monkeys, and then key gene network analysis was performed to determine that the key mRNAs are TLR4 and S100A8 / S100A9. The differential expression of TLR4 and S100A8 / S100A9 in peripheral blood of depressed monkeys found by the present invention is used as a biomolecular marker for the joint diagnosis of depression.

[0032] The purpose of the present invention can be achieved through the following technical solutions:

[0033] S1: Naturally depressed monkeys and control monkeys were selected based on their behavior;

[0034] S2: blood sample collection and whole blood transcriptome sequencing;

[0035] S3: Based on the results of whole transcriptome sequencing, differentially expressed mRNAs in peripheral whole blood between the MDD group and the control group were screened;

[0036] S4: Analyze key gene networks, machine learning and ROC diagnostic curves to clarify the diagnostic value of key differential mRNAs;

[0037] Furthermore, in step S1, the screening of the naturally depressed monkeys needs to comply with depressive-like behavior, including the evaluation of curling-up behavior, environmental exploration behavior, anxiety behavior, stereotypic behavior, grooming behavior, and autonomous activity behavior.

[0038] Furthermore, in step S2, the blood sample collection requires that whole blood be drawn from the monkey on an empty stomach and stored at -80°C.

[0039] Furthermore, in step S3, the differentially expressed mRNAs satisfying pvalues ​​< 0.05 and |log2FC|> 1 are differentially expressed genes, wherein log2 (fold change)> 1 is marked as an up-regulated gene; log2 (fold change) < -1 is marked as a down-regulated gene.

[0040] Example

[0041] Peripheral blood TLR4 and S100A8 / S100A9 are used as a new method for diagnosing depression. The experimental steps are as follows:

[0042] S1. According to the behavioral criteria of depressed monkeys, four naturally depressed monkeys and three control monkeys were selected strictly according to age, sex and weight matching. 2.5 ml of whole blood was drawn from the fasting state using PAXgene tubes. Seven whole blood samples were subjected to whole transcriptome sequencing under frozen conditions. Deseq2 software was used to analyze the differentially expressed mRNA between the control and MDD groups. Genes with pvalues ​​< 0.05 and |log2FC| > 1 were considered differentially expressed genes, where log2 (fold change) > 1 was marked as up-regulated genes; and log2 (foldchange) < -1 was marked as down-regulated genes.

[0043] S2. Based on the results of whole transcriptome sequencing, the differentially expressed mRNAs in peripheral blood of the MDD group and the control group were screened, as shown in Table 1;

[0044] Table 1 Differential expression of TLR4 and S100A8 / S100A9 in peripheral blood between MDD group and control group

[0045]

[0046] S3. Analyze key gene networks, machine learning and ROC diagnostic curves to clarify the diagnostic value of key differential mRNAs, namely TLR4 and S100A8 / S100A9;

[0047] like Figure 1 As shown, the data indicated that TLR4 and S100A8 / S100A9 in peripheral whole blood were key molecules in the differential gene network;

[0048] like Figure 2 As shown, the data indicated that TLR4 in peripheral blood was a key molecule in the machine learning analysis;

[0049] like Figure 3-5As shown, the data indicate that peripheral whole blood TLR4 and S100A8 / S100A9 have high discrimination efficiency in differential diagnosis of depressed monkeys and control monkeys, and the area under the ROC curve (AUC) is 1.00; 0.833; 0.750, respectively.

Claims

1. The use of peripheral blood TLR4 and S100A8 / S100A9 as a combined diagnosis of depression.

2. The use of peripheral blood TLR4 and S100A8 / S100A9 as a combined diagnosis of depression according to claim 1, characterized in that: By performing whole transcriptome sequencing on peripheral blood of depressed monkeys and control monkeys, the differentially expressed mRNAs in depressed monkeys and control monkeys were analyzed, and then the key mRNAs were determined to be TLR4 and S100A8 / S100A9 through key gene network, machine learning and ROC curve analysis.

3. The use of peripheral blood TLR4 and S100A8 / S100A9 as a combined diagnosis of depression according to claim 2, characterized in that: The steps of the combined diagnosis are as follows: S1: Naturally depressed monkeys and control monkeys were selected based on their behavior; S2: blood sample collection and whole blood transcriptome sequencing; S3: Based on the results of whole transcriptome sequencing, differentially expressed mRNAs in peripheral whole blood between the MDD group and the control group were screened; S4: Analyze key gene networks, machine learning and ROC diagnostic curves to clarify the diagnostic value of key differential mRNAs.

4. The use of peripheral blood TLR4 and S100A8 / S100A9 as a combined diagnosis of depression according to claim 3, characterized in that: In S1, the naturally depressed monkeys screened were consistent with depressive-like behaviors, including assessment of curling behavior, environmental exploration behavior, anxiety behavior, stereotypic behavior, grooming behavior, and autonomous activity behavior.

5. The use of peripheral blood TLR4 and S100A8 / S100A9 as a combined diagnosis of depression according to claim 3, characterized in that: In S2, the blood sample collection requires that whole blood be drawn from the monkey on an empty stomach and stored under frozen conditions.

6. The use of peripheral blood TLR4 and S100A8 / S100A9 for combined diagnosis of depression according to claim 5, characterized in that: The freezing condition was -80°C, and RNA was extracted from the two groups of blood samples.

7. The use of peripheral blood TLR4 and S100A8 / S100A9 for combined diagnosis of depression according to claim 3, characterized in that: In S3, the differentially expressed mRNAs satisfying pvalues ​​< 0.05 and |log2FC| > 1 are differentially expressed genes.

8. The use of peripheral blood TLR4 and S100A8 / S100A9 for combined diagnosis of depression according to claim 7, characterized in that: in, log2(fold change)>1 was marked as an up-regulated gene; log2(fold change)<-1 was marked as a down-regulated gene.

9. The use of peripheral blood TLR4 and S100A8 / S100A9 for combined diagnosis of depression according to claim 3, characterized in that: The S4 specifically includes: downloading the molecular interaction information from the STRING database, performing key gene network analysis in the Cytoscape software, and identifying key molecules using a machine learning method that supports SVM, Lasso regression, and random forest.

10. The use of peripheral blood TLR4 and S100A8 / S100A9 for combined diagnosis of depression according to claim 9, characterized in that: The SVM was implemented using the e1071, kernlab, and caret packages in R software, the Lasso regression was implemented using the glmnet package, and the random forest was implemented using the randomForest package; The intersection of the key molecules identified by the three methods was taken, and the ROC diagnostic curve was used to predict the diagnostic value of the key molecules.

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