Failure to account for such heterogeneity, when it exists, decreases power to detect clear genetic associations in samples where such groups are combined. Differential genetic effects have already been identified as a function of certain sample characteristics such as age of AUD onset and patterns of associated personality traits and comorbid disorders (Ali et al., 2015; Cloninger et al., 1988; Dick et al., 2007; Kuo et al., 2008). There are many additional lines along which such etiological differences may split, given the complex biological, psychological, and social influences impacting alcohol problems. One such possibility is the source of the population, which in research studies is usually either clinical samples of treatment-seeking patients or unselected population-based cohorts. Ascertained samples have, by definition, a higher prevalence of alcohol problems than the general population and a different distribution of AUDs and alcohol-associated traits. The burden of comorbid illness (beyond AUDs) is known to be higher in clinical samples (Kaufmann et al., 2014) and they differ on a number of demographic and disease-related characteristics (Blanco et al., 2015). It is also plausible that the
