Application of detection reagents in the preparation of diagnostic tools for type 2 diabetes mellitus with atherosclerosis

Abstract

The present invention belongs to the field of biomedicine, and specifically relates to the use of a detection reagent in the preparation of a diagnostic tool for type 2 diabetes with atherosclerosis. The detection reagent is a detection reagent for detecting the expression of the CD4 gene and the PLEK gene, or detecting the expression of the CD4 protein and the PLEK protein. The test detection agent is selected from oligonucleotide probes that specifically recognize the CD4 gene and the PLEK gene, primers that specifically amplify the CD4 gene and the PLEK gene, or a binding agent that specifically binds to the CD4 protein and the PLEK protein in the sample. The present invention's research confirms that the expression of CD4 and PLEK is significantly upregulated in the disease group. At the same time, we analyzed the diagnostic ability of CD4 and PLEK. The ROC curve results showed that the AUC values ​​of CD4 and PLEK were 0.733 and 0.790, respectively. The results showed that CD4 and PLEK can be used as diagnostic biomarkers and intervention targets for atherosclerosis and type 2 diabetes.

Description

Technical Field

[0001] The present invention belongs to the field of biomedicine, and in particular relates to the application of a detection reagent in the preparation of a diagnostic tool for type 2 diabetes mellitus associated with atherosclerosis. Background Art

[0002] Atherosclerosis (AS) is a chronic inflammatory disease caused by lipid accumulation in the arteries, leading to stenosis and thrombosis. It can affect the heart, brain, and peripheral blood vessels and is a leading cause of death and disability worldwide. Studies have shown a close relationship between diabetes and cardiovascular disease. Patients with diabetes, particularly those with type 2 diabetes, have larger necrotic cores in arterial plaques and more calcification in the arterial media. Compared to healthy individuals, patients with diabetes have a two- to four-fold increased risk of cardiovascular disease. Studies have found that low-density lipoprotein cholesterol (LDL-C) and inflammatory factors are considered to be risk factors for cardiovascular disease in diabetic patients. Furthermore, the insulin signaling pathway plays a role in atherosclerosis, with loss of insulin receptors in smooth muscle cells leading to reduced intimal hyperplasia. However, there has been no systematic study linking atherosclerosis and type 2 diabetes at the genetic level. Therefore, identifying new diagnostic markers and therapeutic targets is crucial for early diagnosis and targeted intervention for both atherosclerosis and type 2 diabetes.

[0003] RNA-seq and microarray technologies are effective tools for exploring genes involved in disease pathogenesis, identifying diagnostic biomarkers, or exploring therapeutic targets. Researchers have found elevated levels of CCL4, CCL18, MMP9, and SPP1 in ruptured plaques, suggesting potential interventional targets. ACLY, SERPING1, and 57ANPEP have been linked to the development of type 2 diabetes. However, research on the association between atherosclerosis and type 2 diabetes is still in its infancy. Summary of the Invention

[0004] To solve the above technical problems, the present invention provides a detection reagent for use in preparing a diagnostic tool for type 2 diabetes with atherosclerosis, wherein the detection reagent is a detection reagent for detecting the expression levels of the CD4 gene and the PLEK gene, or detecting the expression levels of the CD4 protein and the PLEK protein.

[0005] Furthermore, the test agent is selected from oligonucleotide probes that specifically recognize CD4 gene and PLEK gene, primers that specifically amplify CD4 gene and PLEK gene, or binding agents that specifically bind to CD4 protein and PLEK protein in the sample.

[0006] Furthermore, the primer sequences for specifically amplifying the CD4 gene are shown in SEQ ID NOs. 1-2, and the primer sequences for specifically amplifying the PLEK gene are shown in SEQ ID NOs. 3-4.

[0007] Based on the same inventive concept, the present invention also provides a kit for diagnosing type 2 diabetes with atherosclerosis, which contains detection reagents for detecting the expression levels of CD4 gene and PLEK gene, or detecting the expression levels of CD4 protein and PLEK protein; the detection reagents are selected from oligonucleotide probes that specifically recognize CD4 gene and PLEK gene, primers that specifically amplify CD4 gene and PLEK gene, or binding agents that specifically bind to CD4 protein and PLEK protein in a sample.

[0008] Based on the same inventive concept, the present invention also provides the use of the CD4 protein and PLEK protein expression inhibitor in the preparation of a drug for treating type 2 diabetes with atherosclerosis.

[0009] Based on the same inventive concept, the present invention also provides a drug for treating type 2 diabetes with atherosclerosis, the active ingredient of which is the expression inhibitor of the CD4 protein and PLEK protein.

[0010] The present invention has the following beneficial effects:

[0011] The present study obtained four datasets from the GEO database containing expression profiles associated with atherosclerotic plaques and type 2 diabetes. After identifying differentially expressed genes shared between the two diseases, we performed a functional enrichment analysis. We then screened core genes based on a protein-protein interaction network and validated them in two other validation datasets and clinical samples. This study demonstrated that CD4 and PLEK could serve as diagnostic biomarkers and intervention targets for atherosclerosis and type 2 diabetes. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Figure 1 It is a shared gene between atherosclerosis and type 2 diabetes. A is a volcano plot of all differentially expressed genes in the GSE28829 dataset, and B is a volcano plot of all differentially expressed genes in the GSE20966 dataset. Genes with p-values ​​< 0.05 and |logFC| > 0.5 are significantly differentially expressed. Dots indicate upregulated genes, squares indicate downregulated genes, and triangles indicate non-significant genes. C is a Venn diagram of upregulated genes in the two datasets, and D is a Venn diagram of downregulated genes in the two datasets.

[0013] Figure 2 Results of GO analysis of biological processes (A), cellular components (B), and molecular functions (C), as well as KEGG functional enrichment analysis (D).

[0014] Figure 3 This is a protein interaction network (PPI) constructed using the STRING website and Cytoscape software. Five-pointed stars indicate upregulated genes, and four-pointed stars indicate downregulated genes.

[0015] Figure 4 Expression of key validation genes CD4 (A), CXCL8 (B), DOCK8 (C), ITGB2 (D), NCF4 (E), PLEK (F), THY1 (G), and TYROBP (H) in the atherosclerosis validation set GSE43292. *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001.

[0016] Figure 5 Expression of the key genes CD4 (A), CXCL8 (B), ITGB2 (C), NCF4 (D), PLEK (E), THY1 (F), and TYROBP (G) in the type 2 diabetes validation set GSE25724. *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001.

[0017] Figure 6 The blood expression of CD4 and PLEK and their diagnostic capabilities are examined. A and B show qRT-PCR detection of CD4 and PLEK expression in healthy individuals and patients with atherosclerosis and type 2 diabetes. C shows the diagnostic sensitivity of CD4 and PLEK using receiver operating characteristic (ROC) analysis. **p<0.01, ***p<0.001. DETAILED DESCRIPTION

[0018] The present invention will be described in detail below with reference to the accompanying drawings and specific examples, but they should not be construed as limiting the present invention. Unless otherwise specified, the technical means used in the following examples are conventional means well known to those skilled in the art, and the materials, reagents, etc. used in the following examples, unless otherwise specified, can be obtained from commercial sources.

[0019] Example 1

[0020] 1 Method

[0021] 1.1 GEO Datasets and Data Processing

[0022] Atherosclerosis and type 2 diabetes gene expression profiles were downloaded from the GEO database. GSE28829 (carotid plaque sequencing data) and GSE20966 (type 2 diabetes sequencing data) were used as training sets, and GSE43292 (carotid plaque sequencing data) and GSE25724 (type 2 diabetes sequencing data) were used as two independent validation sets. The raw sequencing counts were normalized using R software, and probes and gene names were converted. The expression matrix was log2 transformed, and differentially expressed genes were identified using the Limma package (filtering criteria: p < 0.05 and |logFC| > 0.5). A Venn diagram was used to display the shared genes between the two datasets. GO and KEGG enrichment analysis was performed on the differentially expressed genes using online software.

[0023] 1.2 Protein interaction analysis and core target screening

[0024] Protein interaction networks (PPIs) can be used to describe the physical connections between proteins, further understanding disease mechanisms and drug discovery. PPI networks were generated using the STRING online database with an interaction score > 0.4 and visualized using Cytoscape software. The top 10 core genes were calculated using eight algorithms (betweenness, bottle neck, EPC, degree, MCC, MNC, radiality, and stress) within the cytoHubba plug-in. Venn diagrams were used to analyze these core genes.

[0025] 1.3 Verification of shared core genes

[0026] The core genes obtained from the intersection were validated against the expression levels in the GSE43292 and GSE25724 datasets. After normalization and standardization of the data from the two datasets, boxplots were plotted to examine the expression levels of the core genes, with P < 0.05 considered significant.

[0027] 1.4 RT-qPCR detection of core gene mRNA levels in blood

[0028] Blood was collected from healthy individuals and patients with atherosclerosis and type 2 diabetes, and RNA was extracted. After reverse transcription, the DNA was amplified using a fluorescent quantitative PCR instrument. The primers were designed by Sangon Biotechnology Co., Ltd., and the sequences are shown in Table 1. PCR conditions were: 95°C pre-denaturation for 3 min, 95°C denaturation for 10 s, 60°C annealing and extension for 34 s, and 45 cycles of amplification. △△Ct The relative amount of target gene = 2- △△Ct, ΔΔCt=[Ct(test sample)-Ct GAPDH(test sample)]-[Ct(calibration sample)-Ct GAPDH(calibration sample)].

[0029] Table 1 Primers for specific amplification of CD4 and PLEK genes

[0030]

[0031] 2. Statistical processing

[0032] Data are expressed as mean ± standard deviation The two sample means were compared using the two-sample independent t-test, with P < 0.05 considered a significant difference.

[0033] 3. Results

[0034] 3.1 Shared genes between atherosclerosis and type 2 diabetes

[0035] After correcting and normalizing the expression matrix in the GEO dataset, 965 differentially expressed genes (602 upregulated and 363 downregulated) were identified from the GSE28829 dataset, and 644 differentially expressed genes (373 upregulated and 271 downregulated) were identified from the GSE20966 dataset. A Venn diagram was used to extract the differentially expressed genes shared by the two datasets as potential intersection genes. The results showed that 34 genes were differentially expressed in both datasets, of which 28 were upregulated and 6 were downregulated ( Figure 1 ).

[0036] 3.2 Shared gene characteristics and functions

[0037] There were 34 overlapping genes in the datasets related to atherosclerosis and type 2 diabetes. In order to explore the potential functions of shared genes, GO enrichment analysis was performed. The results showed that in the changes of biological processes (BP), most genes were mainly enriched in the regulation of cytokine production, immune response and leukocyte activation; in cellular components (CC), most genes were enriched in secretory granule membranes and cell leading edges; in molecular functions (MF), most gene functions were related to phosphatidylinositol binding and phospholipid binding. The main enriched pathways of KEGG were: lipid and atherosclerosis, cytokine-cytokine receptor interaction ( Figure 2 Taken together, these results suggest that inflammatory pathways and immune activation are involved in the development of atherosclerosis and type 2 diabetes.

[0038] 3.3 Key gene screening and verification

[0039] The STING database was used to analyze all shared genes and construct a PPI network, which included 47 nodes. Based on the Cytohubba plug-in, eight topological analysis methods (betweenness, bottleNeck, EPC, degree, MCC, MNC, radiality, stress) were used to analyze the top 10 genes. Finally, eight core genes were obtained by cross-section, namely CD4, CXCL8, DOCK8, ITGB2, NCF4, PLEK, THY1 and TYROBP ( Figure 3 To verify the reliability of these core gene expression levels, we selected two other datasets of atherosclerosis and type 2 diabetes and analyzed the expression levels of these core genes. The results showed that in the type 2 diabetes dataset GSE20966, only CD4, PLEK and THY1 genes were upregulated ( Figure 4 ); In the atherosclerosis-related dataset GSE43292, the expression of all core genes was significantly upregulated ( Figure 5 )

[0040] 3.4 RNA extraction and RT-qPCR detection

[0041] Blood was collected from healthy individuals and patients with type 2 diabetes and atherosclerosis, RNA was extracted, and the expression of CD4, PLEK, and THY1 was detected by RT-qPCR. Figure 6 As shown in the data, compared with healthy subjects, the expression of CD4 and PLEK was significantly upregulated in the disease group. At the same time, we analyzed the diagnostic ability of CD4 and PLEK. The ROC curve results showed that the AUC values ​​of CD4 and PLEK were 0.733 and 0.790, respectively, indicating that they have high diagnostic value.

[0042] Although the preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0043] Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if such changes and modifications fall within the scope of the claims and their equivalents, the present invention is intended to include such changes and modifications.

Claims

1. Use of a detection reagent in the preparation of a diagnostic tool for type 2 diabetes mellitus associated with atherosclerosis, characterized in that: The detection reagent is a detection reagent for detecting the expression levels of CD4 gene and PLEK gene.

2. The use according to claim 1, characterized in that The detection reagent includes primers for specifically amplifying CD4 gene and PLEK gene.

3. The use according to claim 2, characterized in that The primer sequences for specifically amplifying the CD4 gene are shown in SEQ ID NOs. 1-2, and the primer sequences for specifically amplifying the PLEK gene are shown in SEQ ID NOs. 3-4.

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