Subjective Response to Alcohol Challenge: A Quantitative Review

The study of twins has estimated that approximately 50% of the variance in alcohol use disorder (AUD) status is explained by genetic influences (Liu et al., 2004; Prescott and Kendler, 1999). The substantial heritability of AUDs has led to efforts to identify the genetic contributions to this major public health concern. Because AUD diagnosis reflects a clinical syndrome likely resulting from multiple distinct sets of risk factors (Hines et al., 2005), the specific factors, referred to as intermediate phenotypes, that reflect genetic influences on AUDs have been a major focus of research in recent years (Schuckit, 2009). One potential intermediate phenotype is subjective response to alcohol. Schuckit (1980) first demonstrated that men with a positive family history of AUDs (FH+) responded less to the effects of alcohol relative to men with a negative family history (FH−) three decades ago. The etiological role of subjective response to alcohol continues, however, to be a source of both research and disagreement (for recent reviews and critiques, see Morean and Corbin, 2010 and Newlin and Renton, 2010). The Low Level of Response Model (LLRM), arguably the most widely accepted model of subjective response as a phenotypic risk factor, proposes that FH+ individuals experience lower subjective response to alcohol relative to FH− individuals (Schuckit, 2009). The model further suggests that “if individuals drink for effects and more alcohol is required to achieve the feelings they want, [low responders] are more likely to drink more heavily,” which leads to a greater likelihood of developing tolerance, withdrawal, and dependence (Schuckit, 2009, p. S7). Evidence for the LLRM first came from alcohol-challenge studies, which compared responses to set doses of alcohol administered in controlled laboratory settings among FH+ and FH− men matched for typical alcohol consumption. The level of response has been measured with self-report questionnaires, notably including the Subjective High Assessment Scale (SHAS; Judd et al., 1977; Schuckit and Gold, 1988), but studies have also demonstrated a similar effect on physiological responses, including static ataxia (Schuckit, 1985), cortisol, prolactin, and adrenocorticotrophic hormone release (Schuckit et al., 1987a; Schuckit et al, 1987b; Shuckit et al., 1988b), and electroencephalographic background activity (Ehlers and Schuckit, 1991) and P300 event-related potential latency (Schuckit et al., 1988a). Recent research has also begun identifying neural correlates of level of response to alcohol (Trim et al., 2010). Additional support for the role of subjective response to alcohol as an intermediate phenotype comes from a study of twins, which estimated the heritability of level of response at approximately 60% (Heath et al., 1999), and from studies demonstrating specific molecular genetic associations with level of response (e.g., Corbin et al., 2006; Hinkers et al., 2006; Hu et al., 2005; Lind et al., 2008; Schuckit et al., 1999). Moreover, low response to alcohol predicts the development of AUDs in longitudinal studies (Schuckit, 1994; Schuckit and Smith, 1996; Schuckit and Smith, 2000; Schuckit and Smith, 2001; Schuckit et al., 2007; Trim et al., 2009). Consistent with its development as a model of risk among sons of alcoholics, the LLRM appears to apply more to men than to women. An early meta-analysis estimated that FH+ men responded approximately one third of a standard deviation less than did FH− men (Pollock, 1992), but several studies have failed to replicate the effect among women (e.g., Evans and Levin, 2003). If the LLRM accurately explains the accumulated data derived from alcohol-challenge studies, it would be reasonable to conclude that a low level of response to alcohol is an inherited intermediate phenotype for the development of AUDs. Complicating this account, however, is the non-trivial number of studies failing to replicate the effect. In fact, in a number of alcohol challenges, those at risk have demonstrated greater response to alcohol (e.g., Earleywine, 1995; Lex et al., 1994; Moss et al., 1989). Whereas some authors have argued that these contradictory findings result from small sample sizes and differing alcohol-administration protocols (e.g., Hines et al., 2005; Schuckit et al., 2010), others have noted that much of the early evidence for the LLRM derived from comparisons made as BACs decline—the period during which alcohol tends to produce more aversive, sedative effects (e.g., Schuckit et al., 2005). As an alternative to the LLRM, Newlin and Thomson (1990) proposed that a Newtonian Differentiator Model (DM) might more accurately explain differences between FH+ and FH− groups. The DM states that those at risk for AUDs “may be more sensitive to the drug during the rising blood alcohol curve, when euphoria is greatest, and less sensitive during the falling curve, when anxiety and depression are greatest” (Newlin and Thomson, 1990, p. 399). That is, the DM proposes that a greater response to the positive, stimulant effects of alcohol, which are most prominent on the ascending limb of the BAC curve, and a lower response to the aversive, sedative effects of alcohol, which are most prominent on the descending limb of the BAC curve, may serve as a risk factor for AUD. The DM therefore makes some similar predictions to those of the LLRM. It critically differs, however, in predicting greater response among those at risk under three conditions: on the ascending limb of the BAC curve, on measures of the positively reinforcing stimulant effects of alcohol, and, most specifically, on stimulant measures during the ascending limb. An early meta-analysis of alcohol-challenge studies failed to find support for the DM (Pollock, 1992). That meta-analysis, however, preceded the development of self-report measures that explicitly capture the euphoric, stimulant effects of alcohol. Included studies used single-item measures of intoxication and the SHAS, which largely assesses the negative, sedative effects of alcohol (Ray et al., 2009). The DM account has benefitted from the validation and use of the Biphasic Alcohol Effects Scale (BAES; Martin et al., 1993), an alcohol response questionnaire designed to assess both stimulant and sedative effects. More recent comparisons of FH+ and FH− participants using the BAES have found some support for the DM (e.g., Erblich et al., 2003). Additionally, although the DM was originally developed to explain FH differences, comparisons of heavier versus lighter drinkers have also produced results consistent with the DM (e.g., King et al., 2002; Marczinski et al., 2007). These studies of typical consumption are qualitatively distinct from FH comparisons, and they have differing and important limitations. Notably, they cannot establish that differences in subjective response precede patterns of alcohol use. Nonetheless, they can potentially provide evidence that greater response to the positively rewarding effects of alcohol is associated with risk for the development of AUDs.