Comprehensive Polygenic Risk Profiling Across Multiple Health Outcomes (CARDINAL)

University Of Maryland Baltimore, Baltimore MD

Investigators

Linked publications & trials

Abstract

Non-communicable conditions such as type 2 diabetes and hypertension; breast and cervical cancer; and infections like human papillomavirus that elevate malignancy risk comprise a significant share of illness and death in the United States. Traditional risk models rely on family history and clinical measures but often miss the full spectrum of inherited variation. Polygenic risk scores (PRSs) integrate thousands of genetic variants to quantify individual susceptibility, yet many scores lose precision when applied outside their original development cohort. The Comprehensive Polygenic Risk Profiling Across Multiple Health Outcomes (CARDINAL) Study Site will merge high-quality genomic data with health records, laboratory results, and longitudinal follow-up for more than 50,000 adults enrolled through US research initiatives. By harmonizing quality-controlled genotypes with richly annotated phenotype data, CARDINAL will enable a rigorous evaluation of existing PRSs for metabolic traits, infection-associated cancer risk, and hormone-driven malignancies. We will implement advanced statistical and machine-learning pipelines that adjust for genetic substructure, local ancestry, and gene- environment interactions, refining risk models to improve calibration and reclassification in real-world patient cohorts. Innovative tools will map individual and aggregate risk distributions, highlight PRS performance relative to conventional predictors, and facilitate rigorous comparisons of modeling strategies. Through collaborative partnerships with national research consortia and healthcare networks, CARDINAL will create an open system for sharing summary results, analysis code, and reporting guidelines. By developing, validating, and disseminating robust PRS tools within a U.S. healthcare context, CARDINAL aims to accelerate the incorporation of genetic risk assessment into routine clinical workflows, support risk-tailored intervention strategies, and ultimately reduce the burden of common chronic diseases, hormone-related cancers, and infection-associated malignancies.