Please use this identifier to cite or link to this item:
|Title:||Estimation of pleiotropy between complex diseases using single-nucleotide polymorphism-derived genomic relationships and restricted maximum likelihood||Contributor(s):||Lee, Sang Hong (author); Yang, J (author); Goddard, M E (author); Visscher, P M (author); Wray, N R (author)||Publication Date:||2012||Open Access:||Yes||DOI:||10.1093/bioinformatics/bts474||Handle Link:||https://hdl.handle.net/1959.11/22064||Abstract:||Genetic correlations are the genome-wide aggregate effects of causal variants affecting multiple traits. Traditionally, genetic correlations between complex traits are estimated from pedigree studies, but such estimates can be confounded by shared environmental factors. Moreover, for diseases, low prevalence rates imply that even if the true genetic correlation between disorders was high, co-aggregation of disorders in families might not occur or could not be distinguished from chance. We have developed and implemented statistical methods based on linear mixed models to obtain unbiased estimates of the genetic correlation between pairs of quantitative traits or pairs of binary traits of complex diseases using population-based case-control studies with genome-wide single-nucleotide polymorphism data. The method is validated in a simulation study and applied to estimate genetic correlation between various diseases from Wellcome Trust Case Control Consortium data in a series of bivariate analyses. We estimate a significant positive genetic correlation between risk of Type 2 diabetes and hypertension of ~0.31 (SE 0.14, P = 0.024).||Publication Type:||Journal Article||Source of Publication:||Bioinformatics, 28(19), p. 2540-2542||Publisher:||Oxford University Press||Place of Publication:||United Kingdom||ISSN:||1367-4811
|Fields of Research (FoR) 2008:||060405 Gene Expression (incl. Microarray and other genome-wide approaches)||Fields of Research (FoR) 2020:||310505 Gene expression (incl. microarray and other genome-wide approaches)||Socio-Economic Objective (SEO) 2008:||920110 Inherited Diseases (incl. Gene Therapy)||Socio-Economic Objective (SEO) 2020:||200101 Diagnosis of human diseases and conditions||Peer Reviewed:||Yes||HERDC Category Description:||C1 Refereed Article in a Scholarly Journal|
|Appears in Collections:||Journal Article|
Files in This Item:
checked on May 20, 2023
checked on Mar 9, 2023
Items in Research UNE are protected by copyright, with all rights reserved, unless otherwise indicated.