The Clinical Utility of the BMD-related comprehensive Genome-wide polygenic score in identifying individuals with a high risk of osteoporotic fractures

Purpose This study sought to construct genome-wide polygenic scores for femoral neck and total body BMD and to estimate their potential in identifying individuals with a high risk of osteoporotic fractures. Methods Genome-wide polygenic scores were developed and validated for femoral neck and total body BMD. We externally tested the PGSs, both by themselves and in combination with available clinical risk factors, in 455,663 European ancestry individuals from the UK Biobank. The predictive accuracy of the developed genome-wide PGS was also compared with previously published restricted PGS employed in fracture risk assessment. Results For each unit decrease in PGSs, the genome-wide PGSs were associated with up to a 1.17-fold increased fracture risk. Out of four studied PGSs, PGS_TBBMD 81 (HR: 1.03; 95%CI 1.01-1.05, p=0.001) had the weakest and the PGS_TBBMD ldpred (HR: 1.17; 95%CI 1.15-1.19, p<0.0001) had the strongest association with an incident fracture. In the reclassification analysis, compared to the FRAX base model, the models with, PGS_FNBMD 63 , PGS_TBBMD 81 , PGS_FNBMD ldpred , and PGS_TBBMD ldpred improved the reclassification of fracture by 2% (95% CI, 1.5% to 2.4%), 0.2% (95% CI, 0.1% to 0.3%), 1.4% (95% CI, 1.3% to 1.5%), and 2.2% (95% CI, 2.1% to 2.4%), respectively. Conclusions Our findings suggested that an efficient PGS estimate enables the identification of strata with up to 1.5-fold difference in fracture incidence. Incorporating PGS information into clinical diagnosis is anticipated to increase the benefits of screening programs in the population level.