Genome-wide analyses of early-onset acute myocardial infarction identify 29 novel loci by whole genome sequencing

Epigenetic Modulation of Vascular Smooth Muscle Cell Phenotype Switching in Early-Onset Acute Myocardial Infarction

BACKGROUND

The epigenetic mechanisms underlying early-onset acute myocardial infarction (AMI) remain insufficiently characterized. The present study aims to elucidate the pathophysiology of early-onset AMI by investigating its epigenetic features as molecular indicators.

METHODS

A comparative differential methylation analysis was performed on whole blood samples from 298 patients with early-onset AMI with clinical follow-up and 247 controls using targeted bisulfite sequencing. Clusters of differentially methylated sites (CDMSs) were defined to highlight regions of concentrated methylation changes in patients with early-onset AMI. Cox proportional hazards regression was conducted to evaluate the prognostic significance of the methylation biomarkers.

RESULTS

A total of 692 differentially methylated sites (DMSs) were identified as biomarkers associated with early-onset AMI. Among these, 396 DMSs were grouped into 147 CDMSs. Notably, the UHRF1 and STIMATE genes, which regulate synthetic and osteoblast-like vascular smooth muscle cell phenotypes, respectively, contained CDMSs with the highest number of significant DMSs. UHRF1 demonstrated a CDMS with 10 significant DMSs within a 117-bp region, while STIMATE included a 264-bp CDMS with 10 significant DMSs. Both regions also exhibited consistent methylation patterns in coronary tissues, comparing human coronary plaque to normal coronary artery samples. Additionally, the HIPK3 gene, which modulates STAT3 expression, thereby promoting osteoblast-like transformation in vascular smooth muscle cells, showed a CDMS with 5 significant DMSs within a 123-bp region, with further validation in the corresponding tissues. Furthermore, over 66% biomarkers demonstrated significant associations with mortality in patients with early-onset AMI, providing evidence of the impact of these biomarkers on the pathophysiology of the disease.

CONCLUSIONS

This innovative epigenomic study into early-onset AMI not only identifies biomarkers associated with the disease and its mortality but also highlights the critical role of vascular smooth muscle cell phenotype regulation in early-onset AMI pathogenesis. Our findings suggest that changes in vascular smooth muscle cell phenotypes toward synthetic and osteoblast-like states play a crucial role in early-onset AMI.

ACE Gene Mutations (rs577350502) in Early-Onset and Recurrent Myocardial Infarction: A Case Report and Review

Background

Acute myocardial infarction (AMI) is a severe acute coronary syndrome, demonstrating a trend toward affecting younger individuals in recent years. The association between early-onset myocardial infarction and single nucleotide polymorphism necessitates further exploration and evaluation.

Case description

We present a case of a patient experiencing early-onset and recurrent myocardial infarction. The patient underwent stent implantation for myocardial infarction at the age of 53 and subsequently encountered two more myocardial infarctions within a span of 16 years. Following interventional therapy, genetic testing was conducted to assess the efficacy of subsequent anti-heart failure medications, with the aim to preemptively address heart failure risks. Genetic testing revealed a mutation in the angiotensin-converting enzyme (ACE) gene (rs577350502, g.63488533C>A), characterized by an intron-deletion single nucleotide variant.

Conclusion

While this variant has not been previously reported to be associated with any specific disease, we hypothesize that it may contribute to the susceptibility and risk of myocardial infarction and coronary heart disease in the patient under consideration. This observation underscores the significance of investigating the insertion/deletion polymorphisms of the ACE gene in the context of AMI and emphasizes the necessity for further validation of this variant and other genetic markers associated with AMI in related diseases.

Korea4K: whole genome sequences of 4,157 Koreans with 107 phenotypes derived from extensive health check-ups

BACKGROUND

Phenome-wide association studies (PheWASs) have been conducted on Asian populations, including Koreans, but many were based on chip or exome genotyping data. Such studies have limitations regarding whole genome-wide association analysis, making it crucial to have genome-to-phenome association information with the largest possible whole genome and matched phenome data to conduct further population-genome studies and develop health care services based on population genomics.

RESULTS

Here, we present 4,157 whole genome sequences (Korea4K) coupled with 107 health check-up parameters as the largest genomic resource of the Korean Genome Project. It encompasses most of the variants with allele frequency >0.001 in Koreans, indicating that it sufficiently covered most of the common and rare genetic variants with commonly measured phenotypes for Koreans. Korea4K provides 45,537,252 variants, and half of them were not present in Korea1K (1,094 samples). We also identified 1,356 new genotype-phenotype associations that were not found by the Korea1K dataset. Phenomics analyses further revealed 24 significant genetic correlations, 14 pleiotropic associations, and 127 causal relationships based on Mendelian randomization among 37 traits. In addition, the Korea4K imputation reference panel, the largest Korean variants reference to date, showed a superior imputation performance to Korea1K across all allele frequency categories.

CONCLUSIONS

Collectively, Korea4K provides not only the largest Korean genome data but also corresponding health check-up parameters and novel genome-phenome associations. The large-scale pathological whole genome-wide omics data will become a powerful set for genome-phenome level association studies to discover causal markers for the prediction and diagnosis of health conditions in future studies.

Identification and validation of six acute myocardial infarction-associated variants, including a novel prognostic marker for cardiac mortality

Background

Acute myocardial infarction (AMI) is one of the leading causes of death worldwide, and approximately half of AMI-related deaths occur before the affected individual reaches the hospital. The present study aimed to identify and validate genetic variants associated with AMI and their role as prognostic markers.

Materials and methods

We conducted a replication study of 29 previously identified novel loci containing 85 genetic variants associated with early-onset AMI using a new independent set of 2,920 Koreans [88 patients with early- and 1,085 patients with late-onset AMI, who underwent percutaneous coronary intervention (PCI), and 1,747 healthy controls].

Results

Of the 85 previously reported early-onset variants, six were confirmed in our genome-wide association study with a false discovery rate of less than 0.05. Notably, rs12639023, a cis-eQTL located in the intergenic region between LINC02005 and CNTN3, significantly increased longitudinal cardiac mortality and recurrent AMI. CNTN3 is known to play a role in altering vascular permeability. Another variant, rs78631167, located upstream of PLAUR and known to function in fibrinolysis, was moderately replicated in this study. By surveying the nearby genomic region around rs78631167, we identified a significant novel locus (rs8109584) located 13 bp downstream of rs78631167. The present study showed that six of the early-onset variants of AMI are applicable to both early- and late-onset cases.

Conclusion

Our results confirm markers that can potentially be utilized to predict, screen, prevent, and treat candidate patients with AMI and highlight the potential of rs12639023 as a prognostic marker for cardiac mortality in AMI.