Prediction of Diagnostic Biomarkers and TCM Targeting Cuprotosis-Related Genes for Myocardial Infarction Based on Bioinformatics
10.19378/j.issn.1003-9783.2024.05.011
- VernacularTitle:基于生物信息学预测冠心病心肌梗死的诊断性生物标志物及靶向铜死亡相关基因的中药
- Author:
Xiang QI
1
;
Shan CAO
;
Kaixuan DUAN
;
Yijia ZHANG
Author Information
1. 河南中医药大学,河南 郑州 450046
- Keywords:
coronary heart disease;
myocardial infarction;
machine learning;
bioinformatics;
cuproptosis;
biomarkers;
blood-activating and stasis-eliminating drugs;
qi-promoting and analgesic drugs
- From:
Traditional Chinese Drug Research & Clinical Pharmacology
2024;35(5):694-705
- CountryChina
- Language:Chinese
-
Abstract:
Objective Coronary heart disease(CHD)is one of the major lethal diseases in the world at present.The detection of biomarkers is an important non-invasive method to evaluate the progression of CHD,which is of great significance for the diagnosis and secondary prevention of CHD.This study aims to screen diagnostic biomarkers in the pathogenesis of myocardial infarction,analyze cuprotosis-related genes in the development of this disease,and further predict the traditional Chinese medicine of regulating cuprotosis-related genes.Methods The GEO database was searched to obtain chip data of myocardial infarction,differentially expressed genes(DEGs)were analyzed.Then,DEGs enrichment analysis was performed,and key genes were screened based on least absolute shrinkage and selection operator(LASSO)and random forest(RF)methods.Diagnostic model was constructed and verified.After immune cell infiltration analysis was performed on differential genes,the results were further combined with weighted gene co-expression network analysis to obtain differentially expressed immune-related genes,which were intersected with cuproptosis genes to obtain cuproptosis immune-related Hub genes.The correlation between cuproptosis-related genes and diagnostic genes were analyzed.Gene set enrichment analysis(GSEA)was performed on cuproptosis-related genes to further predict the traditional Chinese medicines of regulating the genes related to cuproptosis.Results A total of 115 DEGs,which were mainly enriched in the biological processes and pathways related to lymphocyte-mediated immunity,mitochondrial respiratory chain complex Ⅳ,C-type lectin receptor signaling pathway,and chemokine signaling pathway,were obtained by differential analysis.Five diagnostic genes,SNORA20,SNORA19,H4C3,SNORD81,and COX7B,were screened out by machine learning methods.Immune infiltration analysis found dendritic cells,macrophages M2,monocytes,neutrophils,natural killer cells,CD4+T cells,CD8+T cells,and γδ T cells.It was indicated the above eight immune cells play a certain role in the pathogenesis of myocardial infarction in coronary heart disease.Weighted correlation network analysis(WGCNA)and immune infiltration analysis were used to obtain 358 key module genes,which were intersected with cuproptosis genes to obtain three cuproptosis and immune signature genes.The correlation analysis results of five diagnostic genes and Hub genes showed that there was a correlation between the expressions of SLC31A1 and SNORA20,LIAS and SNORA19,SNORD81,MTF1 and H4C3,SNORA20,SNORA19,SNORD81.GSEA analysis results indicated that LIAS and MTF1 had a significant effect on the NF-κB signaling pathway,NOD-like receptor signaling pathway and Toll-like receptor signaling pathway.The potential regulatory Chinese medicines are mainly blood-activating and stasis-eliminating,qi-promoting and analgesic drugs.Conclusion SNORA20,SNORA19,H4C3,SNORD81,COX7B have a certain diagnostic value for myocardial infarction in coronary heart disease.The prediction of genes related to cuproptosis and immune infiltration in the pathogenesis of myocardial infarction provides a certain reference for the study of the mechanism of traditional Chinese medicine intervention in myocardial infarction.
