Translational Studies of Alcoholism: Bridging the Gap
Zahr, Natalie M., Sullivan, Edith V., Alcohol Research
What currently is known about alcohol's effects on the brain has benefited from translational research-the parallel study of humans with alcohol dependence and of animal models that mimic targeted aspects of this complex disease. Human studies provide a full depiction of the consequences of chronic alcohol exposure, but they are limited by ethical considerations for experimentation of rigorous controls of relevant variables. Animal models, on the other hand, can distinguish components of the addiction processes but cannot fully represent the human condition.
In humans, 40 to 60 percent of the risk for alcoholism can be attributed to genetic factors. These genetic factors interact with environmental factors (e.g., early-life stress, family structure, peer pressure, or the social environment; McKenzie et al. 2005) to influence an individual's vulnerability to alcohol problems (Prescott and Kendler 1999). The genetic component has been modeled by breeding animal strains (predominantly rats and mice) with a high preference for alcohol (e.g., the alcohol preferring [P] and nonpreferring [NP] rats, high-alcohol-drinking [HAD] and low-alcohol-drinking [LAD] rats, the high-alcohol-preferring [HAP] mouse, and C57 black mice). The environment also has been modeled, for example, by separating young monkeys from their mothers, which reproduces early-life stress (Barr et al. 2004).
The last quarter century has seen a plethora of technologies capable of exploring the human animal in vivo, and many have been applied to alcohol-related research. Currently available noninvasive human technologies (reviewed elsewhere in this two-part series) include electroencephalogram (EEG) (Rangaswamy and Porjesz, pp. 238-242), functional magnetic resonance imaging (WRI) (Nagel and Kroenke, pp. 243-246; Rosenbloom and Pfefferbaum, Part 2), magnetic resonance spectroscopy (MR spectroscopy) (Nagel and Kroenke, pp. 243-246), single- photon emission computed tomography (SPECT) (e.g., Abi-Dargham et al. 1998), and positron emission tomography (PET) (Thanos et al., pp. 233-237). Further investigation of alcohol's effects at the cellular (e.g., He and Crews 2008; Tupala and Tiihonen 2004), molecular (e.g., Alexander-Kaufinan et al. 2007), and genetic (e.g., Dodd et al. 2006; Saba et al., pp. 272-274) levels is made possible by carefully screened human postmortem brain tissue (Harper et al. 2003x).
Even with these new technologies, animal models continue to have a vital role, enabling researchers to better interpret the implications of new findings. Moreover, the wide variation (or heterogeneity) of alcoholic populations examined with respect to genetic predisposition, age of onset, pattern of drinking, frequency of withdrawals, length of sobriety, nutritional, and hepatic status has hampered researchers' attempts to isolate only those specific brain regions affected by alcohol per se. This heterogeneity, and the complexity that it introduces, makes it difficult to thoroughly characterize the disorder (see Oscar-Berman 2000). Animal models, in contrast to the indefinite natural course of alcohol use in humans, allow researchers to determine alcohol toxicity in a way that allows them to control for multiple genetic, environmental, and alcohol consumption factors.
Alcohol dependence is defined in the Diagnostic and Statistical Manual, Fourth Edition (DSM-IV) as the pres ence of three of a total of seven possible criteria within a 12-month period (figure IA; American Psychiatric Association 1994). The diagnosis of alcohol abuse with DSM-IV criteria has helped standardize the classification of alcoholics, both across national and international research facilities and time (Harper et al. 2003b).
In modeling alcoholism, a series of conditions that attempt to parallel DSM-IV criteria have been estab lished (figure 113; Cicero et al. 1971). Of the currently available animal models, the monkey (e.g., Macaca fascicularis) and the P rat best fulfill these criteria. …