A multi-trait genome-wide association study of coronary artery disease and subclinical atherosclerosis traits

Area of Science:

• Genetics
• Cardiovascular Medicine
• Metabolic Disease

Background:

• Subclinical atherosclerosis measures like coronary artery calcification (CAC) and carotid intima-media thickness (CIMT) are key indicators of coronary artery disease (CAD) pathophysiology.
• These measures share genetic correlations with CAD and its risk factors, suggesting common underlying genetic influences.

Purpose of the Study:

• To identify shared genetic susceptibility loci for atherosclerosis by integrating data from multiple related traits.
• To elucidate the pleiotropic genetic architecture underlying atherosclerosis and its associated risk factors.

Main Methods:

• Conducted 15 multi-trait genome-wide association studies (GWAS) using summary statistics for CAD, CIMT, CAC, type 2 diabetes, LDL cholesterol, and systolic blood pressure.
• Applied an experiment-wide Bonferroni threshold (3.3 × 10^-9) to identify significant shared risk loci.
• Utilized multi-trait and trait-eQTL colocalization analyses to confirm shared causal signals in specific tissues and implicating genes.

Main Results:

• Identified 442 shared risk loci across all analyses, with 195 novel loci for atherosclerosis.
• Confirmed shared causal signals in 25 novel loci through multi-trait colocalization.
• Provided evidence for shared causal signals in arterial, adipose, and cardiac tissues via trait-eQTL colocalization, implicating genes like *PRRX2*, *BNC2*, *CLIC4*, *SCAI*, and *PPP6C*.

Conclusions:

• The study reveals a complex pleiotropic genetic architecture underlying atherosclerosis, involving shared risk loci across cardiovascular and metabolic traits.
• Identified novel genes and pathways, including vascular remodeling, inflammation, and metabolic regulation, contributing to atherosclerosis development.
• Highlights the potential for multi-trait GWAS to uncover shared genetic factors influencing complex diseases.