Osteoporosis Genetic Risk Prediction Using Bone Mineral Density Polygenic Scores in Japanese: TMM CommCohort Study

Osteoporosis and fractures are major health concerns. We developed and validated a polygenic score (PGS) for osteoporosis in a Japanese population using heel quantitative ultrasound-derived T-scores. Genome-wide association study data from 12,371 participants in the Tohoku Medical Megabank Community-Based Cohort identified genome-wide significant loci, including MBL2, TMEM135, and WNT16. PGS models were constructed and evaluated using independent datasets for model selection (n = 1,419) and validation (n = 8,711). Adding the PGS to age and sex yielded modest improvements in discrimination but supported genetic risk stratification. Compared with the intermediate group, the lowest PGS quintile (bottom 20%, genetically high-risk) had higher odds of osteoporosis (OR = 1.22, 95% confidence interval (CI): 1.07-1.40), whereas the highest PGS quintile (top 20%, genetically low-risk) had lower odds of osteoporosis (OR = 0.85, 95% CI: 0.71-0.98). Prospective follow-up (mean 3.4 years) showed a similar gradient for incident osteoporosis, with higher incidence rate ratios in the high-risk group (1.42, 95% CI: 1.17-1.73) and lower incidence rate ratios in the low-risk group (0.70, 95% CI: 0.54-0.89). Age-stratified analyses revealed no significant age-PGS interaction and no differences in the slope of age-related T-score declines across genetic risk groups. Observed T-scores in young adults (20-44 years) and extrapolation to age 20 suggested lower bone status around peak bone mass among genetically high-risk individuals. These findings indicate that a Japanese-specific PGS can stratify osteoporosis risk and may help identify individuals at elevated genetic risk earlier in adulthood.