This revised application builds upon promising pilot data and several recent papers4-9 to request support to more thoroughly evaluate if functional magnetic resonance imaging (fMRI) data add significantly to alcohol challenge-based measures of a low level of response (LR) to alcohol in predicting heavy drinking, alcohol problems and alcohol use disorders. The subjects will be 120 healthy men and women who as non-alcoholic drinkers completed their fMRI evaluations at about age 19, and who would be followed up at about age 25. A low LR (or low sensitivity) to alcohol is a genetically influenced characteristics that can be observed early in life and that predicts later heavy drinking and alcohol-related problems.1-3 Several physiologic correlates of LR have been documented, and the >40% heritability of this low response has been well established. However, each gene explains only a small proportion of the LR risk, and the less intense alcohol-related changes in motor performance, blood hormone levels, and electrophysiologic measures associated with the low LR are so broad in scope that they raise the possibility that the underlying mechanisms of the low LR may involve some overarching cognitive CNS processes, not just the response to alcohol. This conclusion is supported by several prior small-scale fMRI studies of 15-to-25-yr-old healthy, drinking, but non-alcoholic subjects that reported differences between individuals with low and high LRs in neural activity during a cognitive task, even with placebo or with no beverage challenge.4-6 Reflecting these data, in this R21 proposal we hypothesize that the low LR might reflect a relatively general physiological brain characteristic that is present even in th absence of alcohol and that makes it more difficult for a person to recognize the effects of modest alcohol doses. Thus, the fMRI pattern associated with the low LR established in our recent papers may be closer to the general mechanisms that underlie the low LR than the currently available measures of LR itself. Therefore, consistent with our pilot data, the fMRI results may add significantly to the direct measures of LR in predicting adverse alcohol outcomes. To further test this hypothesis, we need to follow up and evaluate the outcomes for the 19-yr-old subjects studied ~5 yrs ago in our prior protocol. If our hypotheses are correct, our findings could lead to the search for more simple and less expensive cognitive or physiological measures of the brain processes related to the low LR. Future studies could also evaluate if measures of the processes that underlie LR can identify the related risk for heavy drinking even before the first drink, which, in turn, might facilitate the early life use of prevention efforts t decrease the risk for alcohol problems.47

Public Health Relevance

This proposed research's central relevance to public health is its focus on evaluating a potential predictor of heavy drinking. The question is whether functional magnetic resonance imaging (fMRI) data previously collected during both placebo and alcohol sessions for subjects grouped on the basis of their level of response (LR) to alcohol can predict future heavy drinking and alcohol problems. The 2 currently available measures of LR (an evaluation of a person's responding to alcohol at a given blood alcohol concentration and a retrospective Self-Report of the number of drinks required for a range of Effects [SRE]) do not directly measure the physiological underpinnings that contribute to LR, and thus, might not be optimally precise as well as providing little direct information regarding possible mechanisms of action.

National Institute of Health (NIH)
National Institute on Alcohol Abuse and Alcoholism (NIAAA)
Exploratory/Developmental Grants (R21)
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Biomedical Research Review Subcommittee (AA)
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Matochik, John A
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University of California San Diego
Schools of Medicine
La Jolla
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Schuckit, Marc A; Smith, Tom L; Paulus, Martin P et al. (2016) The Ability of Functional Magnetic Resonance Imaging to Predict Heavy Drinking and Alcohol Problems 5 Years Later. Alcohol Clin Exp Res 40:206-13
Schuckit, Marc A; Smith, Tom L; Heron, Jon et al. (2015) Latent trajectory classes for alcohol-related blackouts from age 15 to 19 in ALSPAC. Alcohol Clin Exp Res 39:108-16