%0 Journal Article %A James Liley %A John A Todd %A Chris Wallace %T A genetic test for differential causative pathology in disease subgroups %D 2016 %R 10.1101/037713 %J bioRxiv %P 037713 %X Many common diseases show wide phenotypic variation. We present a statistical method for determining whether phenotypically defined subgroups of disease cases represent different genetic pathophysiologies, in which disease-associated variants have different effect sizes in the two subgroups. Our method models the genome-wide distributions of genetic association statistics with mixture Gaussians. We apply a global test without requiring explicit identification of disease-associated variants, thus maximising power in comparison to a standard variant by variant subgroup analysis. Where evidence for genetic subgrouping is found, we present methods for post-hoc identification of the contributing genetic variants.We demonstrate the method on a range of simulated and test datasets where expected results are already known. We investigate subgroups of type 1 diabetes (T1D) cases defined by autoantibody positivity, establishing evidence for differential genetic basis with thyroid peroxidase antibody positivity, driven generally by variants in known T1D associated regions. %U https://www.biorxiv.org/content/biorxiv/early/2016/08/02/037713.full.pdf