@article{fed3cef1afb340ac9defcd6091dc9d6c,
title = "Genetic variance estimation with imputed variants finds negligible missing heritability for human height and body mass index",
abstract = "We propose a method (GREML-LDMS) to estimate heritability for human complex traits in unrelated individuals using whole-genome sequencing data. We demonstrate using simulations based on whole-genome sequencing data that ∼97% and ∼68% of variation at common and rare variants, respectively, can be captured by imputation. Using the GREML-LDMS method, we estimate from 44,126 unrelated individuals that all ∼17 million imputed variants explain 56% (standard error (s.e.) = 2.3%) of variance for height and 27% (s.e. = 2.5%) of variance for body mass index (BMI), and we find evidence that height- and BMI-associated variants have been under natural selection. Considering the imperfect tagging of imputation and potential overestimation of heritability from previous family-based studies, heritability is likely to be 60-70% for height and 30-40% for BMI. Therefore, the missing heritability is small for both traits. For further discovery of genes associated with complex traits, a study design with SNP arrays followed by imputation is more cost-effective than whole-genome sequencing at current prices.",
author = "Jian Yang and Andrew Bakshi and Zhihong Zhu and Gibran Hemani and Vinkhuyzen, {Anna A.E.} and Lee, {Sang Hong} and Robinson, {Matthew R.} and Perry, {John R.B.} and Nolte, {Ilja M.} and {Van Vliet-Ostaptchouk}, {Jana V.} and Harold Snieder and Tonu Esko and Lili Milani and Reedik M{\"a}gi and Andres Metspalu and Anders Hamsten and Magnusson, {Patrik K.E.} and Pedersen, {Nancy L.} and Erik Ingelsson and Nicole Soranzo and Keller, {Matthew C.} and Wray, {Naomi R.} and Goddard, {Michael E.} and Visscher, {Peter M.}",
note = "Funding Information: This research was supported by the Australian National Health and Medical Research Council (grants 1052684, 1078037 and 1050218), the Australian Research Council (grant 130102666), the US National Institutes of Health (R01MH100141), the Sylvia and Charles Viertel Charitable Foundation and the University of Queensland Foundation. This study makes use of data from the database of Genotypes and Phenotypes (dbGaP) available under accessions phs000090, phs000091 and phs000428 and the EGCUT, LifeLines, TwinGene and UK10K studies (see the Supplementary Note for the full set of acknowledgments for these data). Publisher Copyright: {\textcopyright} 2015 Nature America, Inc.",
year = "2015",
month = oct,
doi = "10.1038/ng.3390",
language = "English",
volume = "47",
pages = "1114--1120",
journal = "Nature Genetics",
issn = "1061-4036",
publisher = "Nature Publishing Group",
number = "10",
}