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

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.

We aim to develop and validate a metaPRS tool for osteoporosis risk prediction in East Asians.

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.

Per 1-standard deviation increase in metaPRS was associated with a 63% increased risk of osteoporosis (OR = 1.63, 95%CI = 1.27-2.11, P = 1.61 × 10^-4) in the internal validation, corroborated by results of external validation (OR = 1.64, 95%CI = 1.42-1.91, P = 6.17 × 10^-11). 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.

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.