Genetic Variance Estimation with Imputed Variants Finds Negligible Missing Heritability for Human Height and Body Mass Index

Overview

Journal Nat Genet

Specialty Genetics

Date 2015 Sep 1

PMID 26323059

Citations 413

Authors

Jian Yang

Andrew Bakshi

Zhihong Zhu

Gibran Hemani

Anna A E Vinkhuyzen

Sang Hong Lee

Matthew R Robinson

John R B Perry

Ilja M Nolte

Jana V van Vliet-Ostaptchouk

Harold Snieder

Tonu Esko

Lili Milani

Reedik Magi

Andres Metspalu

Anders Hamsten

Patrik K E Magnusson

Nancy L Pedersen

Erik Ingelsson

Nicole Soranzo

Matthew C Keller

Naomi R Wray

Michael E Goddard

Peter M Visscher

Affiliations

Soon will be listed here.

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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