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bioRxivGenomicsPreprint

Using genotype data to distinguish pleiotropy from heterogeneity: deciphering coheritability in autoimmune and neuropsychiatric diseases

Buhm HaniD, Jennie G Pouget, Kamil SlowikowskiiD, Eli StahliD, Cue Hyunkyu LeeiD, Dorothee Diogo, Xinli HuiD, Yu Rang ParkiD, Eunji Kim, Peter K GregerseniD, Solbritt Rantapaa Dahqvist, Jane WorthingtoniD, Steve Eyre, Lars KlareskogiD, Tom HuizingaiD, Wei-Min Chen, Suna Onengut-Gumuscu, Stephen S RichiD, Major Depressive Disorder Working Group of the PGC, Naomi WrayiD, Soumya RaychaudhuriiD

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Abstract

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, p0.2 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).

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