Transcriptome-wide association study and eQTL colocalization identify potentially causal genes responsible for human bone mineral density GWAS associations.
basic_science · Level V
Where this comes from
- Record sourced from PubMed, PMID 36416764.
- Also identified by DOI 10.7554/eLife.77285 and PMC identifier 9683789.
- Licence recorded as CC BY.
- The licence permits redistribution, so the abstract is shown in full and the full text is available from the publisher.
Abstract
Genome-wide association studies (GWASs) for bone mineral density (BMD) in humans have identified over 1100 associations to date. However, identifying causal genes implicated by such studies has been challenging. Recent advances in the development of transcriptome reference datasets and computational approaches such as transcriptome-wide association studies (TWASs) and expression quantitative trait loci (eQTL) colocalization have proven to be informative in identifying putatively causal genes underlying GWAS associations. Here, we used TWAS/eQTL colocalization in conjunction with transcriptomic data from the Genotype-Tissue Expression (GTEx) project to identify potentially causal genes for the largest BMD GWAS performed to date. Using this approach, we identified 512 genes as significant using both TWAS and eQTL colocalization. This set of genes was enriched for regulators of BMD and members of bone relevant biological processes. To investigate the significance of our findings, we selected <i>PPP6R3</i>, the gene with the strongest support from our analysis which was not previously implicated in the regulation of BMD, for further investigation. We observed that <i>Ppp6r3</i> deletion in mice decreased BMD. In this work, we provide an updated resource of putatively causal BMD genes and demonstrate that <i>PPP6R3</i> is a putatively causal BMD GWAS gene. These data increase our understanding of the genetics of BMD and provide further evidence for the utility of combined TWAS/colocalization approaches in untangling the genetics of complex traits.
Medical subject headings
- Genome-Wide Association Study
- Quantitative Trait Loci