Details

Autor(en) / Beteiligte

• 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

Titel

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

Ist Teil von

• Nature genetics, 2015-10, Vol.47 (10), p.1114-1120

Ort / Verlag

United States: Nature Publishing Group

Erscheinungsjahr

2015

Link zum Volltext

Quelle

MEDLINE

Beschreibungen/Notizen

• 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.