Parallel to the emphasis on increasing sample sizes to drive gene discovery is the growing recognition of the value of a sample like COGA with its family‐based design, deep phenotyping, longitudinal framework, multi‐modal data, wide age range, and ancestral diversity (see, Figure 2 for summary of key contributions enabled by COGA). Simply put, the family‐based COGA data are well‐suited to answer scientific questions that are not possible even in very large samples of unrelated individuals. These include questions such as parsing direct versus indirect genetic effects, testing whether identified loci and polygenic signals are robust to careful control for confounding via within‐family comparisons, and fine‐grained examination of how genetic predispositions for AUD manifest across development and their pleiotropic effects on other traits and disorders. Advances in our understanding of the genetic etiology of AUD will continue to depend on more detailed, family‐based designs in data‐rich samples like COGA, as well as large‐scale, collaborative meta‐analyses that incorporate summary data from COGA alongside many other cohorts.
