RT Journal Article SR Electronic T1 A genetic test for differential causative pathology in disease subgroups JF bioRxiv FD Cold Spring Harbor Laboratory SP 037713 DO 10.1101/037713 A1 James Liley A1 John A Todd A1 Chris Wallace YR 2016 UL http://biorxiv.org/content/early/2016/07/13/037713.abstract AB 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.