Potential Role of a Three-Gene Signature for Predicting Diagnosis in Patients With Myocardial Infarction

Abstract

\n ObjectiveIncreasing evidence underscored that the expression of genes was associated with the development and progression of myocardial infarction (MI). In this study, We evaluated the diagnostic value of the feature genes in MI based on data from the Gene Expression Omnibus (GEO) database.MethodsWe used the data from the GEO database (GSE66360) to identify a set of significant differentially expressed genes (DEGs) between MI and healthy control. Univariable logistic regression, the least absolute shrinkage and selection operator (LASSO), SignalP 3.0 server and multivariable logistic regression were used to find the potential role of genes for predicting diagnosis in patients with MI. Receiver operating characteristic (ROC) curve analyses, area under the curve (AUC) and C-index were used to estimate the diagnostic value of genes in patients with MI. The validation for the association was conduct in another six independent data sets (GSE141512, GSE24519, GSE34198, GSE48060, GSE60993, and GSE109048). Then, a meta-analysis was performed to evaluate the diagnostic value of genes in MI.ResultsA total of 44 DEGs were selected from GSE66360. Functional enrichment and KEGG analysis were performed to reveal the DEGs in some inflammation-related biological processes and pathways. A three-gene signature consisted of CCL20, IL1R2 and ITLN1, which could effectively distinguish patients in MI (AUC and C-index were the same value of 0.975). The three-gene signature was effectively validated in 7 independent cohorts, and diagnostic meta-analysis results of the three-gene signature showed that the pooled sensitivity, specificity and ROC curve AUC for MI were0.82 (95% CI: 0.68-0.90), 0.91 (95% CI: 0.81-0.96) and 0.94(95%CI, 0.91-0.96), respectively. ConclusionIt was magnificently suggest that the three-gene signature might potentially serve as novel candidate biomarkers for distinguishing MI from healthy control. Besides, more well-designed cohort studies need to be implemented to warrant the diagnostic value of three-gene signature in clinical purpose.