| Literature DB >> 26462479 |
Heying Zhou1, Seijiro Mori2, Tatsuro Ishizaki3, Masashi Tanaka4, Kumpei Tanisawa4,5, Makiko Naka Mieno6, Motoji Sawabe7, Tomio Arai8, Masaaki Muramatsu9, Yoshiji Yamada10, Hideki Ito11.
Abstract
A genetic risk score (GRS) was developed for predicting fracture risk based on lifetime prevalence of femoral fractures in 924 consecutive autopsies of Japanese males. A total of 922 non-synonymous single nucleotide polymorphisms (SNPs) located in 62 osteoporosis susceptibility genes were genotyped and evaluated for their association with the prevalence of femoral fracture in autopsy cases. GRS values were calculated as the sum of risk allele counts (unweighted GRS) or the sum of weighted scores estimated from logistic regression coefficients (weighted GRS). Five SNPs (α-ʟ-iduronidase rs3755955, C7orf58 rs190543052, homeobox C4 rs75256744, G patch domain-containing gene 1 rs2287679, and Werner syndrome rs2230009) showed a significant association (P < 0.05) with the prevalence of femoral fracture in 924 male subjects. Both the unweighted and weighted GRS adequately predicted fracture prevalence; areas under receiver-operating characteristic curves were 0.750 [95 % confidence interval (CI) 0.660-0.840] and 0.770 (95 % CI 0.681-0.859), respectively. Multiple logistic regression analysis revealed that the odds ratio (OR) for the association between fracture prevalence and unweighted GRS ≥3 (n = 124) was 8.39 (95 % CI 4.22-16.69, P < 0.001) relative to a score <3 (n = 797). Likewise, the OR for a weighted GRS of 6-15 (n = 135) was 7.73 (95 % CI 3.89-15.36, P < 0.001) relative to scores of 0-5 (n = 786). The GRS based on risk allele profiles of the five SNPs could help identify at-risk individuals and enable implementation of preventive measures for femoral fracture.Entities:
Keywords: Femoral fracture; Genetic risk score; Osteoporosis; Single nucleotide polymorphism
Mesh:
Year: 2015 PMID: 26462479 DOI: 10.1007/s00774-015-0718-7
Source DB: PubMed Journal: J Bone Miner Metab ISSN: 0914-8779 Impact factor: 2.626