ArticleScientific reports2019
Genetic risk factors identified in populations of European descent do not improve the prediction of osteoporotic fracture and bone mineral density in Chinese populations.
Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
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9 citing papers in PubMed, 1 synthesis or guideline pooled it, 13 citations in OpenAlex.
- Using a Polygenic Score to Predict the Risk of Developing Primary Osteoporosis.International journal of molecular sciences · 2022Pooled it
- Osteoporosis genetic risk prediction using bone mineral density polygenic scores in Japanese: TMM CommCohort study.Journal of human genetics · 2026Article
- Emerging applications of feature selection in osteoporosis research: from biomarker discovery to clinical decision support.Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research · 2025Review
- A plasma protein-based risk score to predict hip fractures.Nature aging · 2024Article
- Interaction between MARK3 (rs11623869), PLCB4 (rs6086746) and GEMIN2 (rs2277458) variants with bone mineral density and serum 25-hidroxivitamin D levels in Mexican Mestizo women.Frontiers in endocrinology · 2024Article
- The role of genetic and epigenetic factors in determining the risk of spinal fragility fractures: new insights in the management of spinal osteoporosis.Quantitative imaging in medicine and surgery · 2023Review
- Short-term effects of COVID-19 on the risk of traumatic fractures in China cities.Scientific reports · 2022Article
- Improved prediction of fracture risk leveraging a genome-wide polygenic risk score.Genome medicine · 2021Article
- A Comprehensive Analysis of MicroRNAs in Human Osteoporosis.Frontiers in endocrinology · 2020Article
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12 authors at 7 institutions in 2 countries.
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Abstract
Aiming to investigate whether genetic risk factors (GRFs) for fracture and bone mineral density (BMD) identified from people of European descent can help improve the prediction of osteoporotic fracture (OF) risk and BMD in Chinese populations, we built assessment models for femoral neck (FN)-fracture prediction and BMD value prediction using 700 elderly Chinese Han subjects and 1,620 unrelated Chinese Han subjects, respectively. 17 fracture-associated genes and 82 FN-BMD associated genes identified in people of European descent were used to build a logistic regression model with clinical risk factors (CRFs) for FN-fracture prediction in Chinese. Meanwhile 107 BMD-associated genes from people of European descent were used to build a multiple linear regression model with CRFs for BMD prediction in Chinese. A Lasso algorithm was employed for informative SNP selection to construct the genetic risk score (GRS) with ten-fold cross-validation. The results showed that, adding fracture GRF and FN-BMD GRF to the model with CRFs, the area under the receiver operating characteristic curve (AUC) decrease from 0.653 to 0.587 and 0.588, respectively, for FN fracture prediction. 62.3% and 61.8% of the risk variation were explained by the Model with CRFs and fracture GRF and by the Model with CRFs and FN-BMD GRF, respectively, as compared to 65.5% in the Model with CRFs only. The net reclassification improvement (NRI) index in the reclassification analysis is 0.56% (P = 0.57) and 1.13% (P = 0.29), respectively. There is no significant difference either between the performance of the model with CRFs and that of the model with both CRFs and GRF for BMD prediction. We concluded that, in the current study, GRF of fracture identified in people of European descent does not contributes to improve the fracture prediction in Chinese; and GRF of BMD from people of European descent cannot help improve the accuracy of the fracture prediction in Chinese perhaps partially because GRF of BMD from people of European descent may not contribute to BMD prediction in Chinese. This study highlights the limited utility of the current genetics studies largely focused on people of European descent for disease or risk factor prediction in other ethnic groups, and calls for more and larger scale studies focused on other ethnic groups.
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