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

2015

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.

Nature Genetics, 47(10), p. 1114-1120

1546-1718

1061-4036

https://hdl.handle.net/1959.11/18856

en

Nature Publishing Group

Genetic variance estimation with imputed variants finds negligible missing heritability for human height and body mass index

Journal Article

Publication