Multiple gene polymorphisms can improve prediction of nonvertebral fracture in postmenopausal women

Lee, Seung Hun; Lee, Seon-Woo; Ahn, Seong Hee; Kim, Taehyeung; Lim, Kyoung Hoon; Kim, Beom-Jun; Cho, Eunhee; Kim, Sang–Wook; Kim, Sang Woo; Kim, Ghi Su; Kim, Shin‐Yoon; Koh, Jung‐Min; Kang, Changwon

doi:10.1002/jbmr.1955

Cited by 25 publications

(17 citation statements)

References 45 publications

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“…Although the set of SNPs used in the study was different from the present study's, the observed magnitude of association between GRS and fracture is consistent with the present study. Two empirical studies in postmenopausal women of Korean background also found that a genetic profiling of 39 SNPs in 30 human genomic loci could increase the precision of nonvertebral fracture prediction and help to define the risk threshold, whereas 35 risk alleles were significantly associated with the risk of vertebral fracture in patients on bisphosphonate. Taken together, these results and the present finding suggest that genetic profiling is useful in the identification of high‐risk individuals.…”

Section: Discussionmentioning

confidence: 99%

Prediction of Bone Mineral Density and Fragility Fracture by Genetic Profiling

Ho-Le

Center

Eisman

et al. 2016

Journal of Bone and Mineral Research

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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.

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Section: Discussionmentioning

confidence: 99%

Prediction of Bone Mineral Density and Fragility Fracture by Genetic Profiling

Ho-Le

Center

Eisman

et al. 2016

Journal of Bone and Mineral Research

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“…Several studies suggested that including GRS as a predictor may help improve the accuracy of various fracture prediction models. For example, GRS of 39 SNPs increased the precision of non-vertebral fracture prediction in postmenopausal Korean women [31]. Additionally, GRS based on 63 SNPs improved the accuracy of non-trauma fracture prediction [26].…”

Section: Discussionmentioning

confidence: 99%

Performance of FRAX in Predicting Fractures in US Postmenopausal Women with Varied Race and Genetic Profiles

Xiao

2020

JCM

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Background: Whether the Fracture Risk Assessment Tool (FRAX) performed differently in estimating the 10-year fracture probability in women of different genetic profiling and race remained unclear. Methods: The genomic data in the Women’s Health Initiative (WHI) study was analyzed (n = 23,981). The genetic risk score (GRS) was calculated from 14 fracture-associated single nucleotide polymorphisms (SNPs) for each participant. FRAX without bone mineral density (BMD) was used to estimate fracture probability. Results: FRAX significantly overestimated the risk of major osteoporotic fracture (MOF) in the WHI study. The most significant overestimation was observed in women with low GRS (predicted/observed ratio (POR): 1.61, 95% CI: 1.45–1.79) specifically Asian women (POR: 3.5, 95% CI 2.48–4.81) and in African American women (POR: 2.59, 95% CI: 2.33–2.87). Compared to the low GRS group, the 10-year probability of MOF adjusted for the FRAX score was 21% and 30% higher in the median GRS group and high GRS group, respectively. Asian, African American, and Hispanic women respectively had a 78%, 76%, and 56% lower hazard than Caucasian women after the FRAX score was adjusted. The results were similar for hip fractures. Conclusions: Our study suggested the FRAX performance varies significantly by both genetic profile and race in postmenopausal women.

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“…However, after BMD adjustment, the effect sizes for these associations were substantially reduced, and they concluded that, when BMD is known, the clinical utility of the two GRSs for fracture prediction is limited in elderly subjects. Lee et al (2013) developed a GRS including 21 SNPs in 19 osteoporosis-susceptibility genes, and demonstrated that adding the GRS to the prediction model consisting of clinical risk factors and BMD could improve its predictive ability for non-vertebral fracture in 1229 unrelated Korean postmenopausal women. Lee et al (2016) also calculated the Korean-specific GRS from 35 SNPs associated with osteoporosis-related traits (GRS35), and found that integration of the GRS35 into the current model further improved its predictability for future osteoporotic fracture occurrence in a 6-year follow-up observational study.…”

Section: Discussionmentioning

confidence: 99%

Genetic risk score based on the prevalence of vertebral fracture in Japanese women with osteoporosis

et al. 2016

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A genetic risk score (GRS) was developed for predicting fracture risk based on the prevalence of vertebral fractures in 441 Japanese females with osteoporosis. A total of 979 (858 nonsynonymous and 121 silent) single-nucleotide polymorphisms (SNPs) located in 74 osteoporosis-susceptibility genes were genotyped and evaluated for their association with fracture prevalence. Four SNPs (protein kinase domain containing, cytoplasmic [PKDCC; rs4952590], CDK5-regulatory subunit-associated protein 1-like 1 [CDKAL1; rs4712556], wingless-type MMTV-integration site family member 16 [WNT16; rs2707466], and G-patch domain-containing gene 1 [GPATCH1; rs10416265]) showed a significant association (p < 0.05) with the fracture, in which the minor allele of the former two SNPs was the protective allele and that of the latter two SNPs was the risk allele. Applying a dominant-genetic model, we allotted − 1 point each to the protective-allele carriers and 1 point each to the risk-allele carriers, and GRS values were calculated as the sum of the points. The receiver-operating characteristic curves showed that GRS adequately predicted vertebral fracture. For the model predicted by the GRS with and without the effect of age, areas under the curves were 0.788 (95% confidence interval [CI]: 0.736–0.840) and 0.667 (95% CI: 0.599–0.735), respectively. Multiple logistic regression analysis revealed that the odds ratio for the association between fracture prevalence and GRS was 3.27 (95% CI: 1.36–7.87, p = 0.008) for scores of − 1 to 0 (n = 303) and 12.12 (95% CI: 4.19–35.07, p < 0.001) for scores of 1 to 2 (n = 35) relative to a score of − 2 (n = 103). The GRS based on the four SNPs could help identify at-risk individuals and enable implementation of preventive measures for vertebral fracture.

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Multiple gene polymorphisms can improve prediction of nonvertebral fracture in postmenopausal women

Cited by 25 publications

References 45 publications

Prediction of Bone Mineral Density and Fragility Fracture by Genetic Profiling

Prediction of Bone Mineral Density and Fragility Fracture by Genetic Profiling

Performance of FRAX in Predicting Fractures in US Postmenopausal Women with Varied Race and Genetic Profiles

Genetic risk score based on the prevalence of vertebral fracture in Japanese women with osteoporosis

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