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

作者：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^*

来源：Nature Genetics, 2016, 48(7): 803-+.

DOI：10.1038/ng.3572

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).

• 出版日期2016-7
• 单位河北医科大学