An atlas of genetic correlations across human diseases and traits

Brendan Bulik-Sullivan; Hilary K Finucane; Verneri Anttila; Alexander Gusev; Felix R Day; Po-Ru Loh; ReproGen Consortium; Psychiatric Genomics Consortium; Genetic Consortium for Anorexia Nervosa (GCAN); Wellcome Trust Case Control Consortium 3 (WTCCC3); Laramie Duncan; John R B Perry; Nick Patterson; Elise B Robinson; Mark J Daly; Alkes L Price; Benjamin M Neale

doi:10.1038/ng.3406

An atlas of genetic correlations across human diseases and traits

Brendan Bulik-Sullivan^*, Hilary K Finucane^*, Verneri Anttila, Alexander Gusev, Felix R Day, Po-Ru Loh, ReproGen Consortium, Psychiatric Genomics Consortium, Genetic Consortium for Anorexia Nervosa (GCAN), Wellcome Trust Case Control Consortium 3 (WTCCC3), Laramie Duncan, John R B Perry, Nick Patterson, Elise B Robinson, Mark J Daly, Alkes L Price^*, Benjamin M Neale^*

^*Corresponding author for this work

Research output: Contribution to journal › Article › Academic › peer-review

2606 Citations (Scopus)

Abstract

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-level 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 educational attainment and several diseases. These results highlight the power of genome-wide analyses, as there currently are no significantly associated SNPs for anorexia nervosa and only three for educational attainment.

Original language	English
Pages (from-to)	1236-1241
Number of pages	6
Journal	Nature Genetics
Volume	47
Issue number	11
DOIs	https://doi.org/10.1038/ng.3406
Publication status	Published - Nov 2015

Bibliographical note

Geen EMC auteur, alleen in Group Authors

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10.1038/ng.3406

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Bulik-Sullivan, B., Finucane, H. K., Anttila, V., Gusev, A., Day, F. R., Loh, P.-R., ReproGen Consortium, Psychiatric Genomics Consortium, Genetic Consortium for Anorexia Nervosa (GCAN), Wellcome Trust Case Control Consortium 3 (WTCCC3), Duncan, L., Perry, J. R. B., Patterson, N., Robinson, E. B., Daly, M. J., Price, A. L., & Neale, B. M. (2015). An atlas of genetic correlations across human diseases and traits. Nature Genetics, 47(11), 1236-1241. https://doi.org/10.1038/ng.3406

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abstract = "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-level 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 educational attainment and several diseases. These results highlight the power of genome-wide analyses, as there currently are no significantly associated SNPs for anorexia nervosa and only three for educational attainment.",

author = "Brendan Bulik-Sullivan and Finucane, {Hilary K} and Verneri Anttila and Alexander Gusev and Day, {Felix R} and Po-Ru Loh and {ReproGen Consortium} and {Psychiatric Genomics Consortium} and {Genetic Consortium for Anorexia Nervosa (GCAN)} and {Wellcome Trust Case Control Consortium 3 (WTCCC3)} and Laramie Duncan and Perry, {John R B} and Nick Patterson and Robinson, {Elise B} and Daly, {Mark J} and Price, {Alkes L} and Neale, {Benjamin M} and Lisette Stolk and Visser, {Jenny A.} and Andr{\'e} Uitterlinden and Fernando Rivadeneira and {van Meurs}, Joyce and Bert Hofman and Joop Laven",

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Bulik-Sullivan, B, Finucane, HK, Anttila, V, Gusev, A, Day, FR, Loh, P-R, ReproGen Consortium, Psychiatric Genomics Consortium, Genetic Consortium for Anorexia Nervosa (GCAN), Wellcome Trust Case Control Consortium 3 (WTCCC3), Duncan, L, Perry, JRB, Patterson, N, Robinson, EB, Daly, MJ, Price, AL & Neale, BM 2015, 'An atlas of genetic correlations across human diseases and traits', Nature Genetics, vol. 47, no. 11, pp. 1236-1241. https://doi.org/10.1038/ng.3406

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AU - Bulik-Sullivan, Brendan

AU - Finucane, Hilary K

AU - Anttila, Verneri

AU - Gusev, Alexander

AU - Day, Felix R

AU - Loh, Po-Ru

AU - ReproGen Consortium

AU - Psychiatric Genomics Consortium

AU - Genetic Consortium for Anorexia Nervosa (GCAN)

AU - Wellcome Trust Case Control Consortium 3 (WTCCC3)

AU - Duncan, Laramie

AU - Perry, John R B

AU - Patterson, Nick

AU - Robinson, Elise B

AU - Daly, Mark J

AU - Price, Alkes L

AU - Neale, Benjamin M

AU - Stolk, Lisette

AU - Visser, Jenny A.

AU - Uitterlinden, André

AU - Rivadeneira, Fernando

AU - van Meurs, Joyce

AU - Hofman, Bert

AU - Laven, Joop

N1 - Geen EMC auteur, alleen in Group Authors

PY - 2015/11

Y1 - 2015/11

N2 - 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-level 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 educational attainment and several diseases. These results highlight the power of genome-wide analyses, as there currently are no significantly associated SNPs for anorexia nervosa and only three for educational attainment.

AB - 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-level 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 educational attainment and several diseases. These results highlight the power of genome-wide analyses, as there currently are no significantly associated SNPs for anorexia nervosa and only three for educational attainment.

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DO - 10.1038/ng.3406

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SP - 1236

EP - 1241

JO - Nature Genetics

JF - Nature Genetics

IS - 11

ER -

An atlas of genetic correlations across human diseases and traits

Abstract

Bibliographical note

UN SDGs

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