BackgroundThe role of epigenetics in cardiovascular diseases has paved the way for innovative therapeutic approaches. Investigating epigenetic changes using cell-free DNA (cfDNA) holds substantial promise beyond mere diagnostics, especially for heart-related conditions like acute myocardial infarction (AMI), where obtaining tissue samples is a challenge. This study explores the methylation patterns of cfDNA in AMI patients and compares them with genomic DNA (gDNA) from the same individuals, aiming to evaluate the effectiveness of cfDNA as a valuable resource for studying heart-related diseases.MethodologyWe generated global methylome profiles of cfDNA and gDNA from 25 AMI patients using EM-Seq. Tissue deconvolution analysis was performed to estimate tissue specificity based on the methylation patterns. Differentially methylated loci were identified and explored to understand AMI pathophysiology.ResultsComparative analysis of cfDNA and gDNA methylation patterns in AMI patients reveals cfDNA holds more significance than gDNA. Principal component analysis revealed distinct clusters for cfDNA and gDNA, indicating distinct methylome profiles. cfDNA originated from multiple sources, predominantly from neutrophils (~ 75%) and about 10% from the left atrium, highlighting cardiac-specific changes. In contrast, immune cells are the major source of gDNA, indicative of inflammatory responses. Gene set enrichment analysis (GSEA) associates cfDNA methylation patterns with pathways related to cardiac muscle contraction, inflammation, hypoxia, and lipid metabolism. The affected genes include G protein-coupled receptors (GHSR, FFAR2, HTR1A, and VIPR2) that are part of the cAMP signaling pathway.ConclusionEpigenetic changes in cfDNA are more specific to cardiac tissue compared to those in gDNA, providing better insights into the molecular mechanisms involved in AMI. Genes that are differentially methylated in cfDNA and regulate core pathways, such as cAMP signaling, could be targeted for clinical applications, including the development of effective biomarkers and therapeutic targets.
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