eLife (Nov 2022)

Transcriptome-wide association study and eQTL colocalization identify potentially causal genes responsible for human bone mineral density GWAS associations

  • Basel Maher Al-Barghouthi,
  • Will T Rosenow,
  • Kang-Ping Du,
  • Jinho Heo,
  • Robert Maynard,
  • Larry Mesner,
  • Gina Calabrese,
  • Aaron Nakasone,
  • Bhavya Senwar,
  • Louis Gerstenfeld,
  • James Larner,
  • Virginia Ferguson,
  • Cheryl Ackert-Bicknell,
  • Elise Morgan,
  • David Brautigan,
  • Charles R Farber

DOI
https://doi.org/10.7554/eLife.77285
Journal volume & issue
Vol. 11

Abstract

Read online

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 PPP6R3, 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 Ppp6r3 deletion in mice decreased BMD. In this work, we provide an updated resource of putatively causal BMD genes and demonstrate that PPP6R3 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.

Keywords