Despite these advances with the GWASs of alcohol consumption, genetic studies of AUD and AD drew multiple challenges and limited success[45]. In a community based cohort (e.g. UKBiobank), it is relatively easy to derive the measure of alcohol consumption using number of alcoholic drinks consumed by an individual. But these large population based cohorts lack individuals diagnosed with AUD or AD. Substance use disorder working group of PGC (PGCSUD) tried to circumvent this problem by performing genome-wide meta-analysis of well characterized cohorts for DSM-IV diagnosed AD[45]. This meta-analysis identified, genome-wide significant effects of different ADH1B variants in European (rs1229984; P=9.8 ×10–13) and African ancestries (rs2066702; P=2.2 ×10–9). This study also found that the genetic underpinnings of DSM-IV diagnosed AD only partially overlap with those for alcohol consumption, underscoring the genetic distinction between pathological and nonpathological drinking behaviors[45]. Recently, Sanchez and colleagues also reported similar genetic differences among AUD (measured as AUDIT-P) and alcohol consumption (measured as AUDIT-C)[61]. In this meta-analysis (UKBiobank and 23andMe), AUDIT-P score showed a strong genetic correlation with alcohol dependence (PGC-SUD GWAS), while AUDIT-C score showed stronger
