| Literature DB >> 28475861 |
Farhad Hormozdiari1, Anthony Zhu2, Gleb Kichaev3, Chelsea J-T Ju2, Ayellet V Segrè4, Jong Wha J Joo5, Hyejung Won6, Sriram Sankararaman7, Bogdan Pasaniuc8, Sagiv Shifman9, Eleazar Eskin10.
Abstract
Recent successes in genome-wide association studies (GWASs) make it possible to address important questions about the genetic architecture of complex traits, such as allele frequency and effect size. One lesser-known aspect of complex traits is the extent of allelic heterogeneity (AH) arising from multiple causal variants at a locus. We developed a computational method to infer the probability of AH and applied it to three GWASs and four expression quantitative trait loci (eQTL) datasets. We identified a total of 4,152 loci with strong evidence of AH. The proportion of all loci with identified AH is 4%-23% in eQTLs, 35% in GWASs of high-density lipoprotein (HDL), and 23% in GWASs of schizophrenia. For eQTLs, we observed a strong correlation between sample size and the proportion of loci with AH (R2 = 0.85, p = 2.2 × 10-16), indicating that statistical power prevents identification of AH in other loci. Understanding the extent of AH may guide the development of new methods for fine mapping and association mapping of complex traits.Entities:
Keywords: allelic heterogeneity; causal variants; complex traits; eQTL; gene expression
Mesh:
Year: 2017 PMID: 28475861 PMCID: PMC5420356 DOI: 10.1016/j.ajhg.2017.04.005
Source DB: PubMed Journal: Am J Hum Genet ISSN: 0002-9297 Impact factor: 11.025