Jan 22, 2016

A genetic test for differential causative pathology in disease subgroups

BioRxiv : the Preprint Server for Biology
James LileyChris Wallace

Abstract

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.

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Mentioned in this Paper

Autoantibodies
Genome
Genetic Screening Method
Thyroperoxidase Antibody Assay
Diabetes Mellitus, Insulin-Dependent
Thyroid microsomal antibodies
Simulation
Statistical Technique
Subgroup A Nepoviruses
Subgroup

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