TPM2 As A Potential Predictive Biomarker For Atherosclerosis

With the rapid development of China’s economy leading to changes in lifestyle and the aging of the population,the problem of atherosclerosis is becoming more and more serious.Cardiac-cerebral vascular disease(CCVD),is primarily induced by atherosclerosis,and is a leading cause of mortality.Atherosclerotic cardiovascular diseases(ASCVD)accounts for most of CCVD,morbidity and mortality is increasing in our country.Therefore,this problem has attracted the attention of most researchers all over the world.Numerous studies have investigated and attempted to clarify the molecular mechanisms of atherosclerosis;however,its pathogenesis has yet to be completely elucidated.Two expression profiling datasets,GSE43292 and GSE57691,were obtained from the Gene Expression Omnibus(GEO)database.The present study then identified the differentially expressed genes(DEGs),and functional annotation of the DEGs,enrichment analysis,protein-protein interaction analysis,the hub gene mining and identification were performed.Finally,an atherosclerosis animal model and neural network prediction model was constructed to verify the relationship between hub gene and atherosclerosis.The results identified a total of 234 DEGs between the normal and atherosclerosis samples.The DEGs were mainly enriched in actin filament,actin binding,smooth muscle cells,and cytokine-cytokine receptor interactions.A total of 13 genes were identified as hub genes.Following verification of animal model,the common DEG,Tropomyosin 2(TPM2),was found,which were displayed at lower levels in the atherosclerosis models and samples.The neural network model predicts that TPM2 is closely correlated with the development of atherosclerosis and has predictive value.In summary,DEGs identified in the present study may assist clinicians in understanding the pathogenesis governing the occurrence and development of atherosclerosis,and TPM2 exhibits potential as a promising diagnostic and therapeutic biomarker for atherosclerosis.