A method to decipher pleiotropy by detecting underlying heterogeneity driven by hidden subgroups applied to autoimmune and neuropsychiatric diseases.

Nat Genet

Publication type	Journal Article
Authors	Buhm Han Jennie Pouget Kamil Slowikowski Eli Stahl Cue Lee Dorothée Diogo Xinli Hu Yu Park Eunji Kim Peter Gregersen Solbritt Dahlqvist Jane Worthington Javier Martín Steve Eyre Lars Klareskog Tom Huizinga Wei-Min Chen Suna Onengut-Gumuscu Stephen Rich Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium Naomi Wray Soumya Raychaudhuri
Abstract	There is growing evidence of shared risk alleles for complex traits (pleiotropy), including autoimmune and neuropsychiatric diseases. This might be due to sharing among all individuals (whole-group pleiotropy) or a subset of individuals in a genetically heterogeneous cohort (subgroup heterogeneity). Here we describe the use of a well-powered statistic, BUHMBOX, to distinguish between those two situations using genotype data. We observed a shared genetic basis for 11 autoimmune diseases and type 1 diabetes (T1D; P 0.2; 6,670 T1D cases and 7,279 RA cases). Genetic sharing between seronegative and seropostive RA (P
Year of Publication	2016
Journal	Nat Genet
Volume	48
Issue	7
Pages	803-10
Date Published	2016 Jul
ISSN	1546-1718
URL	http://dx.doi.org/10.1038/ng.3572
DOI	10.1038/ng.3572
PubMed ID	27182969
PubMed Central ID	PMC4925284
Links	PubMed Google Scholar DOI
Grant list	U19 AI111224 / AI / NIAID NIH HHS / United States T32 HG002295 / HG / NHGRI NIH HHS / United States T32 GM007753 / GM / NIGMS NIH HHS / United States U01 GM092691 / GM / NIGMS NIH HHS / United States U01 DK062418 / DK / NIDDK NIH HHS / United States R01 AR063759 / AR / NIAMS NIH HHS / United States UH2 AR067677 / AR / NIAMS NIH HHS / United States