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Updated: Mar 28, 2026

Digital PCR for Quantifying Circulating MicroRNAs in Acute Myocardial Infarction and Cardiovascular Disease
Published on: July 3, 2018
Integrated expression quantitative trait loci and Mendelian randomization analyses of the candidate genes and
Peichun He1, Xiangwen Lv2, Chuwen Fu3
1School of Basic Medical Sciences, Guangxi Medical University, Nanning, Guangxi, China.
Background:
Myocardial infarction (MI) is a myocardial necrosis event caused by an unstable ischemic state that reduces life expectancy primarily through cardiac functional impairment and cardiomyocyte death. The present study aims 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 Gene Expression Omnibus database. The relationships between MI and the differentially expressed genes were evaluated through differential expression, eQTL, and MR analyses. Additionally, GO and KEGG enrichment analyses were performed to clarify the functional pathways of the candidate genes, and gene set enrichment analysis (GSEA) was used to identify the genes associated with MI. An in vitro model of MI was established by subjecting AC16 cells to oxygen and glucose deprivation, and the gene expression levels were validated through reverse transcription quantitative polymerase chain reaction (RT-qPCR).
Results:
By comparing the results from the MR analysis and mRNA expression profiles, we identified 13 overlapping genes: MRPL35, SNUPN, ADM, BCL6, BNIP3L, CMTM2, DGAT2, HSPA6, IER3, IFNGR1, PLAUR, SERPINB8, and VNN2. The 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 the NOD-like signaling pathways; immunological responses; and lysosomal, ribosomal, and metabolic pathways related to MI. Furthermore, the gene expression levels were verified through RT-qPCR.
Conclusion:
This study highlights the potential of specific molecular pathways for targeted treatment of MI. Our work also warrants additional research efforts to elucidate the genetic mechanisms of MI.
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