Trans-Ancestry Genetic Risk Score Boosts Heart Disease Prediction in Chinese Adults

Coronary artery disease remains the leading cause of death in China, yet the genetic tools built to flag people at elevated risk have long been borrowed from studies of European ancestry populations. A new study published in Genome Medicine reports that a carefully engineered trans-ancestry polygenic risk score, constructed by fusing genome-wide association evidence from East Asian and European cohorts, substantially outperforms ancestry-specific alternatives when applied to Chinese individuals. The work, led by researchers at Fuwai Hospital and Peking University together with collaborators at the University of Oxford, offers a technical blueprint for closing a persistent equity gap in genomic risk prediction.

Polygenic risk scores compress the small effects of hundreds of thousands of common genetic variants into a single number that stratifies people by inherited susceptibility. Their predictive power depends on how well the variant effects estimated in a discovery genome-wide association study transfer to the person being scored. Because allele frequencies, linkage disequilibrium patterns, and effect sizes differ across ancestries, scores trained almost exclusively on European data typically lose a large fraction of their accuracy in East Asian populations, a problem that has limited clinical deployment of genetic risk prediction outside Europe.

The research team tackled this transferability problem using PRS-CSx, a continuous shrinkage framework that jointly models summary statistics from multiple ancestry-specific genome-wide association studies. Rather than forcing a choice between East Asian and European effect estimates, the method borrows information across ancestries through a shared prior, allowing variant effects to be estimated with greater precision while remaining anchored to the population being scored. The authors constructed two configurations. The first, termed PRS-meta, was derived purely from the genome-wide association results and linkage disequilibrium reference panels, requiring no individual-level training data. The second, PRS-combine, was additionally optimized in a Chinese training set of 2,800 coronary artery disease cases and 2,055 controls.

For comparison, the investigators generated East Asian-specific scores using two classical approaches, LDpred and pruning-and-thresholding, and also evaluated previously published coronary artery disease scores, including European-specific ones. The top-performing score for each method in the training set was then carried forward to an external validation of remarkable scale: 72,782 participants with genetic data from the China Kadoorie Biobank, a population-based cohort followed for a mean of 12.1 years for incident coronary events.

The training results were striking. PRS-meta and PRS-combine performed comparably, with odds ratios per standard deviation of 2.21 and 2.23 respectively, meaning each standard deviation increase in score roughly doubled the odds of disease. Both trans-ancestry scores delivered approximately 60 percent increases in pseudo-R squared relative to the best East Asian-specific scores and roughly 90 percent increases relative to the best European-specific scores. In practical terms, the fused scores captured far more of the heritable component of coronary risk in Chinese individuals than any single-ancestry alternative.

Validation in the biobank cohort confirmed that the gains survived outside the training data. Both scores were similarly associated with incident coronary artery disease, with hazard ratios per standard deviation of 1.33 for PRS-meta and 1.31 for PRS-combine. When participants were stratified into quintiles, those in the top quintile faced roughly double the risk of those in the bottom quintile, with hazard ratios of 2.06 for PRS-meta and 1.84 for PRS-combine. The consistency of these associations across more than twelve years of follow-up indicates that the scores measure stable, lifelong genetic susceptibility rather than transient risk factors.

A notable technical finding is that PRS-meta, which requires no individual-level training data at all, matched the performance of PRS-combine, which was tuned on Chinese cases and controls. This matters for global health equity because many populations lack the large, well-phenotyped biobanks needed to train and optimize scores locally. A method that fuses ancestry-specific summary statistics and still achieves top performance without local training data offers a path to equitable genetic risk prediction for underrepresented groups, provided that ancestry-specific genome-wide association studies of sufficient size exist.

The study also situates genetic risk within a broader clinical context. The China Kadoorie Biobank validation allowed the authors to examine how the scores relate to conventional cardiovascular risk factors and to established risk prediction models such as the Prediction for Atherosclerotic cardiovascular disease Risk in China framework. Supplementary analyses covered model calibration, improvements in discrimination and reclassification, and subgroup and sensitivity analyses, all of which support the robustness of the trans-ancestry approach. The scores are intended to complement, not replace, conventional risk assessment, adding an inherited-risk dimension that is present from birth and independent of lifestyle factors measured in adulthood.

Coronary artery disease is shaped by the interplay of hundreds of common variants, each contributing a tiny increment of risk, together with diet, smoking, blood pressure, diabetes, and environment. The trans-ancestry scores developed here do not predict destiny; they stratify inherited susceptibility so that individuals in the upper tail of the distribution can be identified earlier for intensified prevention, from lipid management to lifestyle counseling. Because the scores are computed from standard genotyping arrays and summary statistics, they could in principle be integrated into population screening programs without exotic infrastructure.

The broader significance of the work lies in its generalizable strategy. As genome-wide association studies accumulate for diverse populations, continuous shrinkage methods that share information across ancestries promise risk scores that work everywhere rather than only where the data were collected. The authors highlight PRS-meta as particularly promising for this purpose, and the validation in one of the world’s largest Chinese cohorts provides strong evidence that the approach is ready for wider testing in other East Asian and admixed populations. For a field long criticized for concentrating its benefits in European ancestry populations, the study marks a concrete step toward genomic medicine that serves everyone.

Subject of Research: Development and validation of a trans-ancestry polygenic risk score for coronary artery disease in the Chinese population

Article Title: Development and validation of a trans‑ancestry polygenic risk score for coronary artery disease in the chinese population

Article References: He, J., Yang, S., Cui, Q., Sun, D., Lin, Z., Li, J., Liu, F., Yu, C., Sun, D., Pang, Y., Huang, K., Chen, S., Cao, J., Pei, P., Shen, C., Hu, D., Yang, L., Millwood, I. Y., Liu, X., … Lu, X. (2026). Development and validation of a trans‑ancestry polygenic risk score for coronary artery disease in the chinese population. Genome Medicine. https://doi.org/10.1186/s13073-026-01800-0

Image Credits: AI Generated

DOI: 10.1186/s13073-026-01800-0

Keywords: polygenic risk score, coronary artery disease, trans-ancestry, genomic risk prediction, China Kadoorie Biobank, PRS-CSx, genome-wide association studies, East Asian population, cardiovascular genetics, health equity, risk stratification, Genome Medicine