%0 Journal Article %A Buhm Han %A Jennie G Pouget %A Kamil Slowikowski %A Eli Stahl %A Cue Hyunkyu Lee %A Dorothee Diogo %A Xinli Hu %A Yu Rang Park %A Eunji Kim %A Peter K Gregersen %A Solbritt Rantapää Dahlqvist %A Jane Worthington %A Javier Martin %A Steve Eyre %A Lars Klareskog %A Tom Huizinga %A Wei-Min Chen %A Suna Onengut-Gumuscu %A Stephen S Rich %A Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium %A Naomi Wray %A Soumya Raychaudhuri %T Using genotype data to distinguish pleiotropy from heterogeneity: deciphering coheritability in autoimmune and neuropsychiatric diseases %D 2015 %R 10.1101/030783 %J bioRxiv %P 030783 %X Shared genetic architecture between phenotypes may be driven by a common genetic basis (pleiotropy) or a subset of genetically similar individuals (heterogeneity). We developed BUHMBOX, a well-powered statistical method to distinguish pleiotropy from heterogeneity using genotype data. We observed a shared genetic basis between 11 of 17 tested autoimmune diseases and type I diabetes (T1D, p<10−12) and 11 of 17 tested autoimmune diseases and rheumatoid arthritis (RA, p<10−7). This sharing could not be explained by heterogeneity (corrected pBUHMBOX>0.2 using 6,670 T1D cases and 7,279 RA cases), suggesting that shared genetic features in autoimmunity are due to pleiotropy. We observed a shared genetic basis between seronegative and seropostive RA (p<10−22), explained by heterogeneity (pBUHMBOX=0.008 in 2,406 seronegative RA cases). Consistent with previous observations, we observed genetic sharing between major depressive disorder (MDD) and schizophrenia (p<10−9). This sharing is not explained by heterogeneity (pBUHMBOX=0.28 in 9,238 MDD cases). %U https://www.biorxiv.org/content/biorxiv/early/2015/11/06/030783.full.pdf