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

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2016

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Han, 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.

Abstract

There 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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