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An Atlas of Genetic Correlations across Human Diseases and Traits

Identifying genetic correlations between complex traits and diseases can provide useful etiological insights and help prioritize likely causal relationships. The major challenges preventing estimation of genetic correlation from genome-wide association study (GWAS) data with current methods are the...

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Autores principales: Bulik-Sullivan, Brendan, Finucane, Hilary K, Anttila, Verneri, Gusev, Alexander, Day, Felix R., Loh, Po-Ru, Duncan, Laramie, Perry, John R.B., Patterson, Nick, Robinson, Elise B., Daly, Mark J., Price, Alkes L., Neale, Benjamin M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4797329/
https://www.ncbi.nlm.nih.gov/pubmed/26414676
http://dx.doi.org/10.1038/ng.3406
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author Bulik-Sullivan, Brendan
Finucane, Hilary K
Anttila, Verneri
Gusev, Alexander
Day, Felix R.
Loh, Po-Ru
Duncan, Laramie
Perry, John R.B.
Patterson, Nick
Robinson, Elise B.
Daly, Mark J.
Price, Alkes L.
Neale, Benjamin M.
author_facet Bulik-Sullivan, Brendan
Finucane, Hilary K
Anttila, Verneri
Gusev, Alexander
Day, Felix R.
Loh, Po-Ru
Duncan, Laramie
Perry, John R.B.
Patterson, Nick
Robinson, Elise B.
Daly, Mark J.
Price, Alkes L.
Neale, Benjamin M.
author_sort Bulik-Sullivan, Brendan
collection PubMed
description Identifying genetic correlations between complex traits and diseases can provide useful etiological insights and help prioritize likely causal relationships. The major challenges preventing estimation of genetic correlation from genome-wide association study (GWAS) data with current methods are the lack of availability of individual genotype data and widespread sample overlap among meta-analyses. We circumvent these difficulties by introducing a technique – cross-trait LD Score regression – for estimating genetic correlation that requires only GWAS summary statistics and is not biased by sample overlap. We use this method to estimate 276 genetic correlations among 24 traits. The results include genetic correlations between anorexia nervosa and schizophrenia, anorexia and obesity and associations between educational attainment and several diseases. These results highlight the power of genome-wide analyses, since there currently are no significantly associated SNPs for anorexia nervosa and only three for educational attainment.
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spelling pubmed-47973292016-05-01 An Atlas of Genetic Correlations across Human Diseases and Traits Bulik-Sullivan, Brendan Finucane, Hilary K Anttila, Verneri Gusev, Alexander Day, Felix R. Loh, Po-Ru Duncan, Laramie Perry, John R.B. Patterson, Nick Robinson, Elise B. Daly, Mark J. Price, Alkes L. Neale, Benjamin M. Nat Genet Article Identifying genetic correlations between complex traits and diseases can provide useful etiological insights and help prioritize likely causal relationships. The major challenges preventing estimation of genetic correlation from genome-wide association study (GWAS) data with current methods are the lack of availability of individual genotype data and widespread sample overlap among meta-analyses. We circumvent these difficulties by introducing a technique – cross-trait LD Score regression – for estimating genetic correlation that requires only GWAS summary statistics and is not biased by sample overlap. We use this method to estimate 276 genetic correlations among 24 traits. The results include genetic correlations between anorexia nervosa and schizophrenia, anorexia and obesity and associations between educational attainment and several diseases. These results highlight the power of genome-wide analyses, since there currently are no significantly associated SNPs for anorexia nervosa and only three for educational attainment. 2015-09-28 2015-11 /pmc/articles/PMC4797329/ /pubmed/26414676 http://dx.doi.org/10.1038/ng.3406 Text en http://www.nature.com/authors/editorial_policies/license.html#terms Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use:http://www.nature.com/authors/editorial_policies/license.html#terms
spellingShingle Article
Bulik-Sullivan, Brendan
Finucane, Hilary K
Anttila, Verneri
Gusev, Alexander
Day, Felix R.
Loh, Po-Ru
Duncan, Laramie
Perry, John R.B.
Patterson, Nick
Robinson, Elise B.
Daly, Mark J.
Price, Alkes L.
Neale, Benjamin M.
An Atlas of Genetic Correlations across Human Diseases and Traits
title An Atlas of Genetic Correlations across Human Diseases and Traits
title_full An Atlas of Genetic Correlations across Human Diseases and Traits
title_fullStr An Atlas of Genetic Correlations across Human Diseases and Traits
title_full_unstemmed An Atlas of Genetic Correlations across Human Diseases and Traits
title_short An Atlas of Genetic Correlations across Human Diseases and Traits
title_sort atlas of genetic correlations across human diseases and traits
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4797329/
https://www.ncbi.nlm.nih.gov/pubmed/26414676
http://dx.doi.org/10.1038/ng.3406
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