Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Xi'an Jiaotong University, Xi'an, 710061, China.
Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Xi'an Jiaotong University, Xi'an, China.
Osteoporos Int. 2023 Nov;34(11):1907-1916. doi: 10.1007/s00198-023-06852-1. Epub 2023 Jul 27.
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.
This study aimed to identify the genetic architecture and potential biomarkers of BMD.
Our 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.
A total of 52 genes associated with BMD trajectory mean were identified, of which the top three significant genes were WNT16 (P = 1.31 × 10), FAM3C (P = 4.18 × 10), and CPED1 (P = 8.48 × 10). In addition, 114 genes associated with BMD within-subject variability were also identified, such as AC092079.1 (P = 2.72 × 10) and RGS7 (P = 4.72 × 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 (P = 2.45 × 10) and REGULATION OF OSSIFICATION (P = 2.45 × 10). KEGG enrichment analysis showed that these genes were mainly enriched in WNT SIGNALING PATHWAY.
Our 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.
骨密度(BMD)是骨质疏松症和骨折的重要预测指标。我们进行了 BMD 的全基因组轨迹分析,并分析了 BMD 的变化。
本研究旨在确定 BMD 的遗传结构和潜在生物标志物。
我们的分析包括来自英国生物库的 141261 名白种人参与者,他们有足跟 BMD 表型数据。我们使用全基因组轨迹分析工具 TrajGWAS 对 BMD 进行全基因组关联研究(GWAS)。然后,我们在以前报道的 BMD 遗传关联中验证了我们的发现,并在亚洲参与者中进行了复制分析。最后,使用 FUMA 平台对鉴定出的候选基因进行基因集富集分析(GSEA)。
共鉴定出 52 个与 BMD 轨迹均值相关的基因,其中三个最显著的基因是 WNT16(P=1.31×10)、FAM3C(P=4.18×10)和 CPED1(P=8.48×10)。此外,还鉴定出 114 个与 BMD 个体内变异性相关的基因,如 AC092079.1(P=2.72×10)和 RGS7(P=4.72×10)。这些候选基因的关联在以前的 GWAS 中得到了证实,并在亚洲参与者中成功复制。BMD 变化的 GSEA 结果确定了多个与骨骼发育相关的 GO 术语,如 SKELETAL SYSTEM DEVELOPMENT(P=2.45×10)和 REGULATION OF OSSIFICATION(P=2.45×10)。KEGG 富集分析表明,这些基因主要富集在 WNT 信号通路中。
我们的研究结果表明,CPED1-WNT16-FAM3C 基因座在 BMD 均值轨迹中起重要作用,并确定了几个新的候选基因,这些基因对 BMD 个体内变异性有贡献,有助于理解 BMD 的遗传结构。