| Literature DB >> 28651948 |
Cheng Peng1, Jie Shen2, Xu Lin2, Kuan-Jui Su3, Jonathan Greenbaum3, Wei Zhu3, Hui-Ling Lou4, Feng Liu4, Chun-Ping Zeng5, Wei-Feng Deng6, Hong-Wen Deng7.
Abstract
Bone mineral density (BMD) is a complex trait with high missing heritability. Numerous evidences have shown that BMD variation has a relationship with coronary artery disease (CAD). This relationship may come from a common genetic basis called pleiotropy. By leveraging the pleiotropy with CAD, we may be able to improve the detection power of genetic variants associated with BMD. Using a recently developed conditional false discovery rate (cFDR) method, we jointly analyzed summary statistics from two large independent genome wide association studies (GWAS) of lumbar spine (LS) BMD and CAD. Strong pleiotropic enrichment and 7 pleiotropic SNPs were found for the two traits. We identified 41 SNPs for LS BMD (cFDR<0.05), of which 20 were replications of previous GWASs and 21 were potential novel SNPs that were not reported before. Four genes encompassed by 9 cFDR-significant SNPs were partially validated in the gene expression assay. Further functional enrichment analysis showed that genes corresponding to the cFDR-significant LS BMD SNPs were enriched in GO terms and KEGG pathways that played crucial roles in bone metabolism (adjP<0.05). In protein-protein interaction analysis, strong interactions were found between the proteins produced by the corresponding genes. Our study demonstrated the reliability and high-efficiency of the cFDR method on the detection of trait-associated genetic variants, the present findings shed novel insights into the genetic variability of BMD as well as the shared genetic basis underlying osteoporosis and CAD.Entities:
Keywords: Bone mineral density (BMD); Coronary artery disease (CAD); Genome wide association study (GWAS); Pleiotropy
Mesh:
Year: 2017 PMID: 28651948 PMCID: PMC5796548 DOI: 10.1016/j.bone.2017.06.016
Source DB: PubMed Journal: Bone ISSN: 1873-2763 Impact factor: 4.398