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

Cited 46 time in Web of Science Cited 45 time in Scopus
Authors

Han, Buhm; Pouget, Jennie G.; Slowikowski, Kamil; Stahl, Eli; Lee, Cue Hyunkyu; Diogo, Dorothee; Hu, Xinli; Park, Yu Rang; Kim, Eunji; Gregersen, Peter K.; Dahlqvist, Solbritt Rantapaa; Worthington, Jane; Martin, Javier; Eyre, Steve; Klareskog, Lars; Huizinga, Tom; Chen, Wei-Min; Onengut-Gumuscu, Suna; Rich, Stephen S.; Wray, Naomi R.; Raychaudhuri, Soumya

Issue Date
2016-07
Publisher
Nature Publishing Group
Citation
Nature Genetics, Vol.48 No.7, pp.803-810
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 < 1 x 10(-4)) and for 11 autoimmune diseases and rheumatoid arthritis (RA; P < 1 x 10(-3)). This sharing was not explained by subgroup heterogeneity (corrected P-BUHMBOX > 0.2; 6,670 T1D cases and 7,279 RA cases). Genetic sharing between seronegative and seropostive RA (P < 1 x 10(-9)) had significant evidence of subgroup heterogeneity, suggesting a subgroup of seropositive-like cases within seronegative cases (P-BUHMBOX = 0.008; 2,406 seronegative RA cases). We also observed a shared genetic basis for major depressive disorder (MDD) and schizophrenia (P < 1 x 10(-4)) that was not explained by subgroup heterogeneity (P-BUHMBOX = 0.28; 9,238 MDD cases).
ISSN
1061-4036
URI
https://hdl.handle.net/10371/191578
DOI
https://doi.org/10.1038/ng.3572
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  • College of Medicine
  • Department of Medicine
Research Area Bioinformatics, Computational Biology, Genomics, Human Leukocyte Antigen, Statistical Genetics

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