| Literature DB >> 25439097 |
Elaine T Lim1, Yangfan P Liu2, Yingleong Chan3, Tuomi Tiinamaija4, AnnMari Käräjämäki5, Erik Madsen2, David M Altshuler6, Soumya Raychaudhuri7, Leif Groop8, Jason Flannick9, Joel N Hirschhorn3, Nicholas Katsanis2, Mark J Daly10.
Abstract
Rare-variant association studies in common, complex diseases are customarily conducted under an additive risk model in both single-variant and burden testing. Here, we describe a method to improve detection of rare recessive variants in complex diseases termed RAFT (recessive-allele-frequency-based test). We found that RAFT outperforms existing approaches when the variant influences disease risk in a recessive manner on simulated data. We then applied our method to 1,791 Finnish individuals with type 2 diabetes (T2D) and 2,657 matched control subjects. In BBS10, we discovered a rare variant (c.1189A>G [p.Ile397Val]; rs202042386) that confers risk of T2D in a recessive state (p = 1.38 × 10(-6)) and would be missed by conventional methods. Testing of this variant in an established in vivo zebrafish model confirmed the variant to be pathogenic. Taken together, these data suggest that RAFT can effectively reveal rare recessive contributions to complex diseases overlooked by conventional association tests.Entities:
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Year: 2014 PMID: 25439097 PMCID: PMC4225638 DOI: 10.1016/j.ajhg.2014.09.015
Source DB: PubMed Journal: Am J Hum Genet ISSN: 0002-9297 Impact factor: 11.025