| Improved heritability estimation from genome-wide SNPs. | |
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MedLine Citation:
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PMID: 23217325 Owner: NLM Status: MEDLINE |
Abstract/OtherAbstract:
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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. |
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Authors:
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Doug Speed; Gibran Hemani; Michael R Johnson; David J Balding |
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Publication Detail:
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Type: Journal Article; Research Support, Non-U.S. Gov't |
Journal Detail:
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Title: American journal of human genetics Volume: 91 ISSN: 1537-6605 ISO Abbreviation: Am. J. Hum. Genet. Publication Date: 2012 Dec |
Date Detail:
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Created Date: 2012-12-10 Completed Date: 2013-02-14 Revised Date: 2013-04-16 |
Medline Journal Info:
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Nlm Unique ID: 0370475 Medline TA: Am J Hum Genet Country: United States |
Other Details:
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Languages: eng Pagination: 1011-21 Citation Subset: IM |
Copyright Information:
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Copyright © 2012 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved. |
Affiliation:
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University College London Genetics Institute, University College London, London WC1E 6BT, UK. doug.speed@ucl.ac.uk |
Export Citation:
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| MeSH Terms | |
Descriptor/Qualifier:
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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:
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G0901388//Medical Research Council |
From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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