The Covariate's Dilemma

An important step in analyzing genetic association study data is deciding whether to adjust for covariates—those variables ancillary to the variants of interest. In particular, when testing for novel associations, should the statistical model also include known genetic or nongenetic covariates that are predictors of the trait (e.g., body mass index when studying type 2 diabetes)? Yes, if the covariates are also correlated with the primary variants but do not mediate their effects, because they may confound the genetic associations. Including them helps control bias and prevent false discoveries (Figure 1a). But the answer is less clear-cut if the covariates are not confounders.