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Using NGS-methylation profiling to understand the molecular pathogenesis of young MI patients who have subsequent
Michelle Thunders1, Ana Holley2, Scott Harding3
1a Department of Pathology (UOW) , University of Otago , Wellington , New Zealand.
Insights
Young patients experiencing myocardial infarction (MI) with recurrent cardiac events show distinct DNA methylation profiles. These differences in gene methylation may impact pathways crucial for cardiac health, potentially serving as future biomarkers.
Area of Science:
- Genomics and Epigenetics
- Cardiovascular Disease Pathogenesis
Background:
- Ischaemic heart disease is a leading cause of premature death globally.
- Young myocardial infarction (MI) patients (<55 years) face a significant risk of recurrent cardiac events within a year.
- Understanding the molecular mechanisms underlying recurrent events in young MI patients is critical.
Purpose of the Study:
- To investigate DNA methylation differences in young MI patients with recurrent cardiac events compared to those without.
- To identify specific genes and pathways affected by differential methylation in recurrent MI cases.
- To explore the potential of epigenomic differences as predictive biomarkers for clinical progression.
Main Methods:
- Utilized Next Generation Sequencing (NGS) and Reduced Representation Bisulphite Sequencing (RRBS) for methylation analysis.
- Compared DNA methylation profiles between young MI patients with and without recurrent events, matched for key clinical factors.
- Performed differential methylation analyses and pathway enrichment analysis on identified gene lists.
Main Results:
- Identified significantly different DNA methylation profiles between young MI patients with and without recurrent cardiac events.
- Pathway analysis revealed over-representation in cell adhesion, transcription regulation, and cardiac electrical conduction (calcium channel activity) in patients with recurrent events.
- Consistent differential methylation was observed across 16 matched case-control pairs, highlighting specific affected genes.
Conclusions:
- Epigenomic differences, specifically in DNA methylation, are associated with recurrent cardiac events in young MI patients.
- Key affected pathways suggest a role for altered gene regulation in the pathogenesis of recurrent cardiovascular events.
- Further research into these epigenomic variations may yield valuable predictive biomarkers for cardiovascular disease progression.
Abstract:
Globally, ischaemic heart disease is a major contributor to premature morbidity and mortality. A significant number of young Myocardial Infarction (MI) patients (aged <55 y) have subsequent cardiac events within a year of their index event. This study used Next Generation Sequencing (NGS) methylation to understand the pathogenesis in this subset of young MI patients, comparing them to a cohort of patients without recurrent events. Cases and controls were matched for age, gender, ethnicity, and comorbidities. Differential methylation analyses were performed on Reduced Representation Bisulphite Sequencing (RRBS) data. Across the group and within case-control pairs' variation were analysed. Pairwise comparisons across each matched case-control pair resulted in a list of genes that were consistently significantly differentially methylated between all 16 matched pairs. This gene list was input into pathway analysis databases. Of particular relevance to cardiac pathology the following pathways were identified as over-represented in the patients with recurrent events; cell adhesion, transcription regulation and cardiac electrical conduction, specifically relating to calcium channel activity. This study looked at methylation differences between two populations of young MI patients. There were significantly different methylation profiles between the two groups studied; key pathways were identified as specifically affected in the patients with recurrent cardiac events. Matched pairwise comparisons and detailed interpretations of DNA methylation data may help to elucidate complex pathogeneses within and between clinical subtypes. Further analysis will determine whether these epigenomic differences can be useful as predictive biomarkers of clinical progression.
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