Analyzing alternative phenotypes as a complementary approach to studying clinically-defined AUD, and psychiatric disorders in general, has generated considerable interest in recent years (46). Collectively, our work demonstrates how AUDIT can inexpensively facilitate such efforts. Here, we have shown that, after correcting for some potential biases, item- or symptom-level analyses can help unpack the genetic etiology of AUD by breaking down genetic influences into specific and shared components; notably, this is only possible because we can contrast our results against gold standard, clinically-ascertained, AUD GWAS datasets. While composite scores have shown some utility in previous genetic association studies, such studies often rely on strong assumptions that the scale is unidimensional, and that each item is equally informative of the construct being measured. In the present paper, we have shown that the latter assumption is false for the AUDIT. In particular, a large proportion of the genetic variance of item 1 appears to be uninformative of a broader consumption construct, as it covaries with. Moreover, although we found a conspicuous degree of unidimensionality among the AUDIT items, our results demonstrate that Consumption and Problems remain distinct in their associations with human health.
