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Evaluating the contribution of rare variants to type 2 diabetes and related traits using pedigrees.

Citation
Jun, G., et al. “Evaluating The Contribution Of Rare Variants To Type 2 Diabetes And Related Traits Using Pedigrees.”. Proceedings Of The National Academy Of Sciences Of The United States Of America, pp. 379-384.
Center University of Michigan Albert Einstein College of Medicine University of Chicago
Multicenter
Multicenter
Author Goo Jun, Alisa Manning, Marcio Almeida, Matthew Zawistowski, Andrew R Wood, Tanya M Teslovich, Christian Fuchsberger, Shuang Feng, Pablo Cingolani, Kyle J Gaulton, Thomas Dyer, Thomas W Blackwell, Han Chen, Peter S Chines, Sungkyoung Choi, Claire Churchhouse, Pierre Fontanillas, Ryan King, SungYoung Lee, Stephen E Lincoln, Vasily Trubetskoy, Mark DePristo, Tasha Fingerlin, Robert Grossman, Jason Grundstad, Alison Heath, Jayoun Kim, Young Jin Kim, Jason Laramie, Jaehoon Lee, Heng Li, Xuanyao Liu, Oren Livne, Adam E Locke, Julian Maller, Alexander Mazur, Andrew P Morris, Toni I Pollin, Derek Ragona, David Reich, Manuel A Rivas, Laura J Scott, Xueling Sim, Rick G Tearle, Yik Ying Teo, Amy L Williams, Sebastian Zöllner, Joanne E Curran, Juan Peralta, Beena Akolkar, Graeme I Bell, Noël P Burtt, Nancy J Cox, Jose C Florez, Craig L Hanis, Catherine McKeon, Karen L Mohlke, Mark Seielstad, James G Wilson, Gil Atzmon, Jennifer E Below, Josée Dupuis, Dan L Nicolae, Donna Lehman, Taesung Park, Sungho Won, Robert Sladek, David Altshuler, Mark I McCarthy, Ravindranath Duggirala, Michael Boehnke, Timothy M Frayling, Goncalo R Abecasis, John Blangero
Keywords eQTL, Genetics, rare variants, sequencing, type 2 diabetes
Abstract

A major challenge in evaluating the contribution of rare variants to complex disease is identifying enough copies of the rare alleles to permit informative statistical analysis. To investigate the contribution of rare variants to the risk of type 2 diabetes (T2D) and related traits, we performed deep whole-genome analysis of 1,034 members of 20 large Mexican-American families with high prevalence of T2D. If rare variants of large effect accounted for much of the diabetes risk in these families, our experiment was powered to detect association. Using gene expression data on 21,677 transcripts for 643 pedigree members, we identified evidence for large-effect rare-variant -expression quantitative trait loci that could not be detected in population studies, validating our approach. However, we did not identify any rare variants of large effect associated with T2D, or the related traits of fasting glucose and insulin, suggesting that large-effect rare variants account for only a modest fraction of the genetic risk of these traits in this sample of families. Reliable identification of large-effect rare variants will require larger samples of extended pedigrees or different study designs that further enrich for such variants.

Year of Publication
2018
Journal
Proceedings of the National Academy of Sciences of the United States of America
Volume
115
Issue
2
Number of Pages
379-384
Date Published
12/2018
ISSN Number
1091-6490
DOI
10.1073/pnas.1705859115
Alternate Journal
Proc. Natl. Acad. Sci. U.S.A.
PMID
29279374
PMCID
PMC5777025
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