title: Prediction of Bone Mineral Density and Fragility Fracture by Genetic Profiling.
abstract: Although the susceptibility to fracture is partly determined by genetic factors, the contribution of newly discovered genetic variants to fracture prediction is still unclear. This study sought to define the predictive value of a genetic profiling for fracture prediction. Sixty-two bone mineral density (BMD)-associated single-nucleotide polymorphisms (SNPs) were genotyped in 557 men and 902 women who had participated in the Dubbo Osteoporosis Epidemiology Study. The incidence of fragility fracture was ascertained from X-ray reports between 1990 and 2015. Femoral neck BMD was measured by dual-energy X-ray absorptiometry. A weighted polygenic risk score (genetic risk score [GRS]) was created as a function of the number of risk alleles and their BMD-associated regression coefficients for each SNP. The association between GRS and fracture risk was assessed by the Cox proportional hazards model. Individuals with greater GRS had lower femoral neck BMD (p < 0.01), but the variation in GRS accounted for less than 2% of total variance in BMD. Each unit increase in GRS was associated with a hazard ratio of 1.20 (95% CI, 1.04 to 1.38) for fracture, and this association was independent of age, prior fracture, fall, and in a subset of 33 SNPs, independent of femoral neck BMD. The significant association between GRS and fracture was observed for the vertebral and wrist fractures, but not for hip fracture. The area under the receiver-operating characteristic (ROC) curve (AUC) for the model with GRS and clinical risk factors was 0.71 (95% CI, 0.68 to 0.74). With GRS, the correct reclassification of fracture versus nonfracture ranged from 12% for hip fracture to 23% for wrist fracture. A genetic profiling of BMD- associated genetic variants could improve the accuracy of fracture prediction over and above that of clinical risk factors alone, and help stratify individuals by fracture status. © 2016 American Society for Bone and Mineral Research.
authors.affiliation: Centre for Health Technologies, University of Technology, Sydney, Australia.
authors.forename: Thao P
authors.initials: TP
authors.lastname: Ho-Le
authors.affiliation: Bone Biology Division, Garvan Institute of Medical Research, Darlinghurst, Australia.|St Vincent Clinical School, University of New South Wales, Darlinghurst, Australia.
authors.forename: Jacqueline R
authors.initials: JR
authors.lastname: Center
authors.affiliation: Bone Biology Division, Garvan Institute of Medical Research, Darlinghurst, Australia.|St Vincent Clinical School, University of New South Wales, Darlinghurst, Australia.|School of Medicine, Notre Dame University Australia, Sydney, Australia.
authors.forename: John A
authors.initials: JA
authors.lastname: Eisman
authors.affiliation: Centre for Health Technologies, University of Technology, Sydney, Australia.
authors.forename: Hung T
authors.initials: HT
authors.lastname: Nguyen
authors.affiliation: Centre for Health Technologies, University of Technology, Sydney, Australia.|Bone Biology Division, Garvan Institute of Medical Research, Darlinghurst, Australia.|St Vincent Clinical School, University of New South Wales, Darlinghurst, Australia.|School of Medicine, Notre Dame University Australia, Sydney, Australia.|School of Public Health and Community Medicine, University of New South Wales, Darlinghurst, Australia.
authors.forename: Tuan V
authors.initials: TV
authors.lastname: Nguyen
mesh_terms: D000368:Aged; D015519:Bone Density / Q000235:genetics*; D005260:Female; D050723:Fractures, Bone / Q000235:genetics* / Q000503:physiopathology*; D006801:Humans; D016014:Linear Models; D008297:Male; D016016:Proportional Hazards Models; D012307:Risk Factors
keywords: FRACTURE; FRACTURE PREDICTION; GENETIC PROFILING; GENETIC VARIANT; OSTEOPOROSIS