Integrative Analysis of Expression Quantitative Trait Loci and Mendelian Randomization Analyses Identified Candidate Genes and Pathways in Myocardial Infarction

Abstract

Background: Myocardial infarction (MI) is a myocardial necrosis event caused by an unstable ischemic state that might reduce life expectancy primarily through cardiac functional impairment and cardiomyocyte death. This study aimed to investigate the genetic mechanisms underlying MI by integrating expression quantitative trait loci (eQTLs) and Mendelian randomization (MR) analyses. Methods: We comprehensively analyzed independent MI datasets from the GEO database. The relationships between differentially expressed genes (DEGs) and MI were evaluated through differential expression analysis, eQTL, and MR analyses. Additionally, GO and KEGG enrichment analyses were performed to clarify the functional pathways of the candidate genes, whereas GSEA was used to identify MI-associated genes. An in vitro model of MI was established by subjecting AC16 cells to oxygen–glucose deprivation (OGD), and gene expression levels were validated through quantitative reverse transcription–polymerase chain reaction (RT‒qPCR). Results: After the MR analysis and mRNA expression profile results were compared, 13 overlapping genes (MRPL35, SNUPN, ADM, BCL6, BNIP3L, CMTM2, DGAT2, HSPA6, IER3, IFNGR1, PLAUR, SERPINB8, and VNN2) were identified. GO and KEGG enrichment analyses revealed that these genes participate in essential biological processes, including mitochondrial apoptotic and mitochondrial organization regulatory pathways. GSEA demonstrated that the candidate genes were enriched in NOD-like signaling pathways; immunological response; and lysosomal, ribosomal, and metabolic pathways related to MI. Furthermore, the RT‒qPCR results verified the gene expression levels. Conclusion: This study highlights the potential of specific molecular pathways for targeted treatment of MI. More studies are warranted to elucidate the genetic mechanisms of MI.