A multi-trait polygenic risk score enhances osteoporosis risk prediction in East Asian population

INTRODUCTION: A meta-scoring approach of polygenic risk scores (PRSs), metaPRS, has made significant advances in chronic disease prediction, but its application to osteoporosis and in the East Asian populations remain limited. OBJECTIVES: We aim to develop and validate a metaPRS tool for osteoporosis risk prediction in East Asians. METHODS: We utilized two independent cohorts, the West China Health and Ageing Cohort as training (N = 1,878, 80%) and internal validation (N = 470, 20%) sets and the West China Bone Health Cohort as external validation (N = 962). We generated individual PRSs of 18 osteoporosis-related traits spanning anthropometric, lifestyle, endocrine, and comorbidity domains. Using 10-fold cross-validation elastic net logistic regression, we developed and evaluated the performance of metaPRS. RESULTS: ). Participants in the highest metaPRS decile had a 5.8-fold (internal) and a 7.2-fold (external) increased risk of osteoporosis compared to the lowest decile. The performance of metaPRS was comparable to several established screening tools but superior to single-trait PRSs and conventional risk factors. Incorporating metaPRS into each screening tool enhanced model performance, with the combined metaPRS-OSIRIS model achieving the highest area under receiving-operating characteristic curve of 0.754. CONCLUSION: The metaPRS effectively identifies high-risk individuals for osteoporosis in East Asian populations and enhances existing screening approaches, offering valuable potential for early diagnosis, intervention and personalized management.