Author(s) |
Yang, Jian
Bakshi, Andrew
Zhu, Zhihong
Hemani, Gibran
Vinkhuyzen, Anna A E
Lee, Sang Hong
Robinson, Matthew R
Perry, John R B
Nolte, Ilja M
van Vliet-Ostaptchouk, Jana V
Snieder, Harold
Esko, Tonu
Milani, Lili
Mägi, Reedik
Metspalu, Andres
Hamsten, Anders
Magnusson, Patrik K E
Pedersen, Nancy L
Ingelsson, Erik
Soranzo, Nicole
Keller, Matthew C
Wray, Naomi R
Goddard, Michael E
Visscher, Peter M
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Publication Date |
2015
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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.
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Citation |
Nature Genetics, 47(10), p. 1114-1120
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ISSN |
1546-1718
1061-4036
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Link | |
Publisher |
Nature Publishing Group
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Title |
Genetic variance estimation with imputed variants finds negligible missing heritability for human height and body mass index
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Type of document |
Journal Article
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Entity Type |
Publication
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