Coronary risk scores get split into eight biological pathways, and abdominal fat turns out to matter most in one of them

Genetic risk for coronary artery disease no longer collapses into a single number; it is split into eight pathways, each corresponding to a biological process and each scored separately for an individual. Conventional polygenic risk scores say who is at elevated risk but not which biological process drives it; comparable decompositions existed for type 2 diabetes, steatotic liver disease and obesity, but not for coronary artery disease. In UK Biobank, SCAPIS and the Mass General Brigham Biobank, all eight pathway scores were associated with clinical coronary events with directionally consistent effects, strongest for cardiac remodeling, lipoprotein(a) and metabolically unhealthy normal weight.

Each pathway score carries its own signature across biomarkers, imaging and disease endpoints rather than being a diluted copy of the total score. Correlations between each pathway score and the total score were modest, and correlations among the pathway scores were low, indicating distinct dimensions of genetic liability. Across 83 clinical, biochemical and imaging markers, 2,923 plasma proteins and 30 comorbidities in UK Biobank, the pathway scores showed different patterns, with the coagulation score standing out for venous thromboembolism.

The fat-distribution pathway changes how waist circumference relates to myocardial infarction. The total coronary polygenic risk score showed no such interaction; only the metabolically unhealthy normal weight score kept a significant interaction with waist circumference after comprehensive adjustment. Among UK Biobank participants free of atherosclerotic cardiovascular disease at baseline, the waist-circumference association with myocardial infarction strengthened at higher pathway scores in both men and women, and the interaction replicated for subclinical plaque burden in SCAPIS.

The framework applies to predominantly European-ancestry populations and was validated in UK Biobank, SCAPIS and the Mass General Brigham Biobank, covering clinical coronary events, imaging-defined subclinical atherosclerosis, biochemical and proteomic markers, and comorbidity endpoints. It is aimed at researchers who want genetic coronary risk resolved by biological process rather than a single aggregate score, and at clinical epidemiology readers interested in the interaction between fat distribution and metabolic risk. The source proposes that intervention studies targeting specific mechanisms of lipoprotein metabolism can test the resulting treatment-response hypotheses.

The genetic components were derived in participants of predominantly European ancestry; seven of the eight pathway scores reproduced in participants of Asian ethnicity, but other groups may require ancestry-specific trait matrix curation and factor decomposition. The decomposition considered only variants reaching genome-wide significance for coronary risk, and a larger variant set might resolve additional mechanisms. The interactions between modifiable risk factors and the pathway scores are observational, and the source states that confirmation will require repeated measurement of risk factors over time or evidence from intervention trials. This report is based on the full text of a preprint that has not been certified by peer review.