Genome-Wide Association Studies (GWAS) of Sudden Cardiac Death in Diverse Populations

Background: Sudden cardiac death (SCD) accounts for a significant proportion of cardiovascular mortality, often occurring without prior symptoms or structural heart disease. Despite progress in identifying clinical risk factors, current predictive models lack precision and fail to capture underlying genetic susceptibility. Genome-wide association studies (GWAS) have uncovered numerous loci linked to cardiac electrophysiology, arrhythmias, and structural abnormalities, yet their applicability across diverse populations remains limited. Incorporating ancestry-informed genomic data is critical to improve risk stratification and ensure equitable translation of genetic insights. Methods and Results: This review summarizes findings from major GWAS on SCD conducted between 2008 and 2024, with a focus on population diversity, study design, and biological relevance. Meta-analyses of multi-ethnic cohorts comprising over 200,000 individuals identified both shared and ancestry-specific risk loci associated with SCD, including variants in genes related to ion channel regulation (SCN5A, KCNQ1), cardiac conduction (NOS1AP, CAV1), and myocardial structure (TTN, BAG3). Polygenic risk scores (PRS) derived from European-ancestry datasets showed reduced predictive power in African, Hispanic, and Asian populations, underscoring the need for diverse genomic reference panels. Integrative approaches combining GWAS with expression quantitative trait loci (eQTL), methylation data, and electrophysiological phenotyping have highlighted novel pathways in calcium handling, autonomic modulation, and myocardial fibrosis. Functional validation using CRISPR and induced pluripotent stem cell–derived cardiomyocytes supports the pathogenicity of several lead variants. Conclusion: GWAS have advanced our understanding of the genetic architecture of sudden cardiac death, but greater inclusion of underrepresented populations is essential to realize the full potential of genomic risk prediction. Expanding multi-ethnic cohorts, refining PRS models, and integrating functional genomics will enable more accurate, personalized prevention strategies and foster equitable advances in cardiovascular genetics.