When drug treatments bias genetic studies: Mediation and interaction.

ABSTRACT:

Background

Increasingly, genetic analyses are conducted using information from subjects with established disease, who often receive concomitant treatment. We determined when treatment may bias genetic associations with a quantitative trait.

Methods

Graph theory and simulated data were used to explore the impact of drug prescriptions on (longitudinal) genetic effect estimates. Analytic derivations of longitudinal genetic effects are presented, accounting for the following scenarios: 1) treatment allocated independently of a genetic variant, 2) treatment that mediates the genetic effect, 3) treatment that modifies the genetic effect. We additionally evaluate treatment modelling strategies on bias, the root mean squared error (RMSE), coverage, and rejection rate.

Results

SUBMITTER: Schmidt AF 

PROVIDER: S-EPMC6713387 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature