Document Detail


Improved heritability estimation from genome-wide SNPs.
MedLine Citation:
PMID:  23217325     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
Estimation of narrow-sense heritability, h(2), 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 h(2) 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 h(2) 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 h(2) 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.
Authors:
Doug Speed; Gibran Hemani; Michael R Johnson; David J Balding
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Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't    
Journal Detail:
Title:  American journal of human genetics     Volume:  91     ISSN:  1537-6605     ISO Abbreviation:  Am. J. Hum. Genet.     Publication Date:  2012 Dec 
Date Detail:
Created Date:  2012-12-10     Completed Date:  2013-02-14     Revised Date:  2014-01-23    
Medline Journal Info:
Nlm Unique ID:  0370475     Medline TA:  Am J Hum Genet     Country:  United States    
Other Details:
Languages:  eng     Pagination:  1011-21     Citation Subset:  IM    
Copyright Information:
Copyright © 2012 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.
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MeSH Terms
Descriptor/Qualifier:
Algorithms
Computer Simulation
Genome, Human
Genome-Wide Association Study*
Genotype
Humans
Linkage Disequilibrium
Models, Genetic*
Multifactorial Inheritance / genetics*
Pedigree
Polymorphism, Single Nucleotide*
Grant Support
ID/Acronym/Agency:
G0901388//Medical Research Council
Comments/Corrections
Comment In:
Am J Hum Genet. 2013 Dec 5;93(6):1155-7   [PMID:  24314551 ]
Am J Hum Genet. 2013 Dec 5;93(6):1151-5   [PMID:  24314550 ]

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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