| Title: | A longitudinal genome-wide association study of bone mineral density mean and variability in the UK Biobank |
| Journal: | Osteoporosis International |
| Published: | 27 Jul 2023 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/37500982/ |
| DOI: | https://doi.org/10.1007/s00198-023-06852-1 |
| Citations: | 2 (2 in last 2 years) as of 8 Aug 2024 |
Publication 11653
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Abstract
Bone mineral density (BMD) is an essential predictor of osteoporosis and fracture. We conducted a genome-wide trajectory analysis of BMD and analyzed the BMD change.PurposeThis study aimed to identify the genetic architecture and potential biomarkers of BMD.MethodsOur analysis included 141,261 white participants from the UK Biobank with heel BMD phenotype data. We used a genome-wide trajectory analysis tool, TrajGWAS, to conduct a genome-wide association study (GWAS) of BMD. Then, we validated our findings in previously reported BMD genetic associations and performed replication analysis in the Asian participants. Finally, gene-set enrichment analysis (GSEA) of the identified candidate genes was conducted using the FUMA platform.ResultsA total of 52 genes associated with BMD trajectory mean were identified, of which the top three significant genes were WNT16 (P = 1.31 × 10−126), FAM3C (P = 4.18 × 10−108), and CPED1 (P = 8.48 × 10−106). In addition, 114 genes associated with BMD within-subject variability were also identified, such as AC092079.1 (P = 2.72 × 10−13) and RGS7 (P = 4.72 × 10−10). The associations for these candidate genes were confirmed in the previous GWASs and replicated successfully in the Asian participants. GSEA results of BMD change identified multiple GO terms related to skeletal development, such as SKELETAL SYSTEM DEVELOPMENT (Padjusted = 2.45 × 10−3) and REGULATION OF OSSIFICATION (Padjusted = 2.45 × 10−3). KEGG enrichment analysis showed that these genes were mainly enriched in WNT SIGNALING PATHWAY.ConclusionsOur findings indicated that the CPED1-WNT16-FAM3C locus plays a significant role in BMD mean trajectories and identified several novel candidate genes contributing to BMD within-subject variability, facilitating the understanding of the genetic architecture of BMD.</p>
11 Authors
- Dan He
- Huan Liu
- Wenming Wei
- Yijing Zhao
- Qingqing Cai
- Sirong Shi
- Xiaoge Chu
- Xiaoyue Qin
- Na Zhang
- Peng Xu
- Feng Zhang
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