Variability in performance of genetic-enhanced DXA-BMD prediction models across diverse ethnic and geographic populations: A risk prediction study
In this study, we observed that combining genetic and clinical factors improves BMD prediction compared to clinical factors alone. Adjusting inclusion thresholds for genetic variants (e.g., 5×10-6 or 5×10-7) rather than solely considering genome-wide association study (GWAS)-significant variants can enhance the model's explanatory power. The study highlights the need for training models on diverse populations to improve predictive performance across various ethnic and geographical groups.
Authors
- Chong Wu (ORCID: https://orcid.org/0000-0002-8400-1785)
- Hong‐Wen Deng (ORCID: https://orcid.org/0000-0002-0387-8818)
- Chuan Qiu (ORCID: https://orcid.org/0000-0001-6202-9229)
- Hong‐Mei Xiao (ORCID: https://orcid.org/0000-0002-8121-9498)
- Zhe Luo (ORCID: https://orcid.org/0000-0001-6495-408X)
- Y.X. Liu (ORCID: https://orcid.org/0000-0001-9360-1304)
- Xiang‐He Meng (ORCID: https://orcid.org/0000-0001-8731-2899)
- Qing Tian (ORCID: https://orcid.org/0000-0003-3830-6606)
- Lan‐Juan Zhao (ORCID: https://orcid.org/0000-0001-6342-2495)
- Kuan‐Jui Su
- Anqi Liu (ORCID: https://orcid.org/0000-0001-9033-6701)
- Hui Shen (ORCID: https://orcid.org/0009-0006-2913-4629)
- Martha Isabel González-Ramírez
Institutions
- Tulane University (US)
- The University of Texas MD Anderson Cancer Center (US)
- Central South University (CN)
- Hunan Normal University (CN)
- Changsha Hospital for Maternal and Child Health Care (CN)
- Xiangya Hospital Central South University (CN)
Publication Details
- Journal
- PLoS Medicine
- Published
- 2024-08-30
- DOI
- https://doi.org/10.1371/journal.pmed.1004451
- Citations
- 10
- Primary Topic
- Genetic Associations and Epidemiology
- Type
- article
- Field-Weighted Citation Impact
- 5.50
Funders
- National Natural Science Foundation of China
- Central South University