TY - JOUR T1 - Disease as collider: a new case-only method to discover environmental factors in complex diseases with genetic risk estimation JF - bioRxiv DO - 10.1101/124560 SP - 124560 AU - Félix Balazard AU - Sophie Le Fur AU - Pierre Bougnères AU - Alain-Jacques Valleron AU - the Isis-Diab collaborative group Y1 - 2017/01/01 UR - http://biorxiv.org/content/early/2017/04/10/124560.abstract N2 - Background Genetic risk scores can quantify part of the predisposition of an individual to a disease. The identification of environmental factors is more challenging. Collider bias appears between two causes (e.g. gene and environment) when conditioning on a shared consequence (the collider, disease).Methods We introduce Disease As Collider (DAC), a new case-only methodology to validate environmental factors using genetic risk. A complex disease is a collider between genetic and environmental factors. Under reasonable assumptions, a negative correlation between genetic risk and environment in cases provides a signature of a genuine environmental risk factor. Simulation of disease occurrence in a source population allows to estimate the statistical power of DAC as a function of prevalence of the disease, predictive accuracy of genetic risk and sample size. We illustrate DAC in 831 type 1 diabetes (T1D) patients.Results The power of DAC increases with sample size, prevalence and accuracy of genetic risk estimation. For a prevalence of 1% and a realistic genetic risk estimation, power of 80% is reached for a sample size under 3000. Power was low in our case study as the prevalence of T1D in children is low (0.2%).Conclusions DAC could provide a new line of evidence for discovering which environmental factors play a role in complex diseases, or validating results obtained in case-control studies. We discuss the circumstances needed for DAC to participate in the triangulation of environmental causes of disease. We highlight the link with the case-only design for gene environment interaction.Key messagesDisease is a collider between genetic risk and environmental factors.This can be used to discover or validate the association between a disease and an environmental factor in a case-only setting.Statistical power of this approach depends strongly on the prevalence of the disease as well as on sample size and genetic risk prediction accuracy. ER -