Modeling risk factors for nicotine and other drug abuse in the preclinical laboratory

Abstract Risk factors that predict vulnerability for nicotine and other drug abuse have been identified using preclinical models, and there is close agreement with clinical and epidemiological studies. The major risk factors to be discussed are age, sex/hormonal status, impulsivity, sweet-liking, no...

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Bibliographic Details
Published in:Drug and alcohol dependence 2009-10, Vol.104, p.S70-S78
Main Authors: Carroll, Marilyn E, Anker, Justin J, Perry, Jennifer L
Format: Article
Language:English
Subjects:
Adolescence
Age Factors
Animals
Behavior, Addictive - etiology
Behavior, Addictive - psychology
Drug abuse
Drug Evaluation, Preclinical - methods
Environmental enrichment
Exploratory Behavior
Hormonal influences
Humans
Impulsivity
Models, Psychological
Nicotine
Novelty reactivity
Physical activity
Preclinical models
Psychiatry
Risk Factors
Sex
Sex Factors
Substance-Related Disorders - etiology
Substance-Related Disorders - psychology
Sweet preference
Tobacco Use Disorder - etiology
Tobacco Use Disorder - psychology
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Summary:Abstract Risk factors that predict vulnerability for nicotine and other drug abuse have been identified using preclinical models, and there is close agreement with clinical and epidemiological studies. The major risk factors to be discussed are age, sex/hormonal status, impulsivity, sweet-liking, novelty reactivity, proclivity for exercise, and environmental impoverishment (vs. enrichment). This discussion will focus on factors that preclinical research has determined are strong and translatable predictors of nicotine and other drug abuse. An advantage of using preclinical models is that prospective, longitudinal studies and within-subject designs can be used to reveal risk factors that are diverse yet maintain unique characteristics. The many interrelationships among these factors lead to an additive vulnerability that increases the predictability that drug abuse will occur. A feature that these risk factors have in common is that they consistently predict vulnerability to drug abuse over critical transition phases of addiction that are difficult to examine prospectively in humans, such as acquisition, escalation, and reinstatement of drug-seeking after abstinence (relapse). The models offer valuable information that has been transferred to effective prevention and treatment strategies for smoking and other drug abuse in humans.
ISSN:0376-8716
1879-0046
DOI:10.1016/j.drugalcdep.2008.11.011