An Atlas of Genetic Correlations across Human Diseases and Traits
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Bulik-Sullivan, Brendan
Finucane, Hilary K
Anttila, Verneri
Day, Felix R.
Duncan, Laramie
Perry, John R.B.
Patterson, Nick
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https://doi.org/10.1038/ng.3406Metadata
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Bulik-Sullivan, B., H. K. Finucane, V. Anttila, A. Gusev, F. R. Day, P. Loh, L. Duncan, et al. 2015. “An Atlas of Genetic Correlations across Human Diseases and Traits.” Nature genetics 47 (11): 1236-1241. doi:10.1038/ng.3406. http://dx.doi.org/10.1038/ng.3406.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 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.Other Sources
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4797329/pdf/Terms of Use
This article is made available under the terms and conditions applicable to Other Posted Material, as set forth at http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-use#LAACitable link to this page
http://nrs.harvard.edu/urn-3:HUL.InstRepos:27320469
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