Affiliations 

  • 1 Department of Genetics, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia
  • 2 Section of Clinical and Metabolic Genetics, Department of Pediatrics, Hamad Medical Corporation, Doha, Qatar
  • 3 Clinical Genetics Department, Human Genetics and Genome Research Division, National Research Centre, Cairo, Egypt
  • 4 Department of Obstetrics and Gynecology, College of Medicine, King Saud University, Riyadh, Saudi Arabia
  • 5 Department of Pediatrics, College of Medicine & King Khalid University Hospital, King Saud University, Riyadh, Saudi Arabia
  • 6 Genetics and Metabolism Unit, Department of Paediatrics, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
Genet Med, 2018 01;20(1):64-68.
PMID: 28640246 DOI: 10.1038/gim.2017.78

Abstract

PurposeGenome-wide association studies (GWAS) have been instrumental to our understanding of the genetic risk determinants of complex traits. A common challenge in GWAS is the interpretation of signals, which are usually attributed to the genes closest to the polymorphic markers that display the strongest statistical association. Naturally occurring complete loss of function (knockout) of these genes in humans can inform GWAS interpretation by unmasking their deficiency state in a clinical context.MethodsWe exploited the unique population structure of Saudi Arabia to identify novel knockout events in genes previously highlighted in GWAS using combined autozygome/exome analysis.ResultsWe report five families with homozygous truncating mutations in genes that had only been linked to human disease through GWAS. The phenotypes observed in the natural knockouts for these genes (TRAF3IP2, FRMD3, RSRC1, BTBD9, and PXDNL) range from consistent with, to unrelated to, the previously reported GWAS phenotype.ConclusionWe expand the role of human knockouts in the medical annotation of the human genome, and show their potential value in informing the interpretation of GWAS of complex traits.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.