A method to decipher pleiotropy by detecting underlying heterogeneity driven by hidden subgroups applied to autoimmune and neuropsychiatric diseases
Pouget, Jennie G.
Lee, Cue Hyunkyu
Park, Yu Rang
Gregersen, Peter K.
Dahlqvist, Solbritt Rantapää
Rich, Stephen S.
Wray, Naomi R.
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CitationHan, B., J. G. Pouget, K. Slowikowski, E. Stahl, C. H. Lee, D. Diogo, X. Hu, et al. 2016. “A method to decipher pleiotropy by detecting underlying heterogeneity driven by hidden subgroups applied to autoimmune and neuropsychiatric diseases.” Nature genetics 48 (7): 803-810. doi:10.1038/ng.3572. http://dx.doi.org/10.1038/ng.3572.
AbstractThere is growing evidence of shared risk alleles between complex traits (pleiotropy), including autoimmune and neuropsychiatric diseases. This might be due to sharing between all individuals (whole-group pleiotropy), or a subset of individuals within a genetically heterogeneous cohort (subgroup heterogeneity). BUHMBOX is a well-powered statistic distinguishing between these two situations using genotype data. We observed a shared genetic basis between 11 autoimmune diseases and type 1 diabetes (T1D, p<10−4), and 11 autoimmune diseases and rheumatoid arthritis (RA, p<10−3). This sharing was not explained by subgroup heterogeneity (corrected pBUHMBOX>0.2, 6,670 T1D cases and 7,279 RA cases). Genetic sharing between seronegative and seropostive RA (p<10−9) had significant evidence of subgroup heterogeneity, suggesting a subgroup of seropositive-like cases within seronegative cases (pBUHMBOX=0.008, 2,406 seronegative RA cases). We also observed a shared genetic basis between major depressive disorder (MDD) and schizophrenia (p<10−4) that was not explained by subgroup heterogeneity (pBUHMBOX=0.28 in 9,238 MDD cases).
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