Improved heritability estimation from genome-wide SNPs

Speed, Doug, Hemani, Gibran, Johnson, Michael R. and Balding, David J. (2012) Improved heritability estimation from genome-wide SNPs. American Journal of Human Genetics, 91 6: 1011-1021. doi:10.1016/j.ajhg.2012.10.010

Author Speed, Doug
Hemani, Gibran
Johnson, Michael R.
Balding, David J.
Title Improved heritability estimation from genome-wide SNPs
Journal name American Journal of Human Genetics   Check publisher's open access policy
ISSN 0002-9297
Publication date 2012-12
Sub-type Article (original research)
DOI 10.1016/j.ajhg.2012.10.010
Volume 91
Issue 6
Start page 1011
End page 1021
Total pages 11
Place of publication Cambridge, MA, United States
Publisher Cell Press
Collection year 2013
Language eng
Formatted abstract
Estimation of narrow-sense heritability, h2, from genome-wide SNPs genotyped in unrelated individuals has recently attracted interest and offers several advantages over traditional pedigree-based methods. With the use of this approach, it has been estimated that over half the heritability of human height can be attributed to the ∼300,000 SNPs on a genome-wide genotyping array. In comparison, only 5%-10% can be explained by SNPs reaching genome-wide significance. We investigated via simulation the validity of several key assumptions underpinning the mixed-model analysis used in SNP-based h 2 estimation. Although we found that the method is reasonably robust to violations of four key assumptions, it can be highly sensitive to uneven linkage disequilibrium (LD) between SNPs: contributions to h2 are overestimated from causal variants in regions of high LD and are underestimated in regions of low LD. The overall direction of the bias can be up or down depending on the genetic architecture of the trait, but it can be substantial in realistic scenarios. We propose a modified kinship matrix in which SNPs are weighted according to local LD. We show that this correction greatly reduces the bias and increases the precision of h2 estimates. We demonstrate the impact of our method on the first seven diseases studied by the Wellcome Trust Case Control Consortium. Our LD adjustment revises downward the h2 estimate for immune-related diseases, as expected because of high LD in the major-histocompatibility region, but increases it for some nonimmune diseases. To calculate our revised kinship matrix, we developed LDAK, software for computing LD-adjusted kinships.
Keyword SNP
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2013 Collection
UQ Diamantina Institute Publications
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 102 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 110 times in Scopus Article | Citations
Google Scholar Search Google Scholar
Created: Sun, 20 Jan 2013, 00:24:50 EST by System User on behalf of UQ Diamantina Institute