Genetic Architecture of Cardiometabolic Disease

Summary

Cardiometabolic diseases are highly polygenic and heterogeneous, with risk variants acting through distinct tissues and biological processes. Large multi-ancestry GWAS combined with fine-mapping and functional genomics improve locus discovery, causal-gene prioritization and mechanistic subclassification.

Disease Maps

A type 2 diabetes meta-analysis of 2,535,601 people, including 428,452 cases, identified 1,289 independent signals at 611 loci and grouped signals into eight cardiometabolic clusters. Cell-type enrichment and cluster-specific polygenic scores linked obesity-related processes to vascular complications.[1]

A coronary artery disease study of more than 1.1 million participants detected more than 250 loci across European and Japanese analyses. Functionally informed fine-mapping, eight gene-prioritization approaches and CRISPR validation of a MYO9B enhancer connected association signals with vascular-cell migration.[2]

A multi-ancestry stroke study of 521,612 participants expanded the set of established loci to 32 and found shared genetic contributions with blood pressure, cardiac traits and venous thromboembolism, alongside subtype-specific effects.[3]

Network Context and Penetrance

Risk loci do not operate independently of the biochemical state in which their effects occur. A gene-by-flux study found 30 CAD risk-locus-by-reaction relationships in which predicted metabolic activity amplified or buffered allele-associated hazard. The metabolic flux modulation of genetic risk framework therefore adds a network-context layer after locus discovery and fine-mapping.[4]

Citations

[1] Suzuki et al. (2024), "Genetic drivers of heterogeneity in type 2 diabetes pathophysiology" [2] Aragam et al. (2022), "Discovery and systematic characterization of risk variants and genes for coronary artery disease in over a million participants" [3] Malik et al. (2018), "Multiancestry genome-wide association study of 520,000 subjects identifies 32 loci associated with stroke and stroke subtypes" [4] Foguet et al. (2025), "Metabolic reaction fluxes as amplifiers and buffers of risk alleles for coronary artery disease"