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Genetic variations in the enzymes involved in alcohol and nicotine metabolism can profoundly affect the rates of metabolism of these drugs, which in turn can influence drug-taking behaviors. The frequency of these genetic variants differs substantially among ethnic groups, resulting in differing genetic influences, or degrees of risk, among different populations. For many of these enzymatic pathways, the genetic variations that affect the rates of metabolism are very different in Asians and Caucasians and may contribute to population differences in alcohol- and tobacco-related behaviors and diseases. Understanding how variations in alcohol- and nicotine-metabolizing enzymes alter these drug responses and behaviors, with special focus on genetic variations, is the subject of this review. Each section describes genetic variations in a particular enzymatic pathway and reviews what is known about population variation and the resulting impact on alcohol- and/or nicotine-related disorders. Each section concludes with some thoughts on future research priorities. Sections 1 and 2 review the primary alcohol- and acetaldehyde-metabolizing enzymes and provide a working model for how the genetic variations in these enzymes may affect alcohol consumption and related disorders. Section 1 focuses on the alcohol and acetaldehyde dehydrogenases, while section 2 focuses on CYP2E1 and its possible role in alcohol and tobacco dependence. Sections 3 and 4 describe enzymes involved in nicotine metabolism, with section 3 focusing on the major nicotine-to-cotinine metabolizing enzyme, CYP2A6, and how genetically differing rates of metabolic inactivation of nicotine alter smoking. Section 4 describes data on the many additional enzymes involved in the metabolism of nicotine and its metabolites and summarizes our current understanding of the influence these enzymes may have on metabolism and addiction in this relatively new research area.

The outcome of drug therapy is often unpredictable, ranging from beneficial effects to lack of efficacy to serious adverse effects. Variations in single genes are 1 well-recognized cause of such unpredictability, defining the field of pharmacogenetics (see Glossary). Such variations may involve genes controlling drug metabolism, drug transport, disease susceptibility, or drug targets. The sequencing of the human genome and the cataloguing of variants across human genomes are the enabling resources for the nascent field of pharmacogenomics (see Glossary), which tests the idea that genomic variability underlies variability in drug responses. However, there are many challenges that must be overcome to apply rapidly accumulating genomic information to understand variable drug responses, including defining candidate genes and pathways; relating disease genes to drug response genes; precisely defining drug response phenotypes; and addressing analytic, ethical, and technological issues involved in generation and management of large drug response data sets. Overcoming these challenges holds the promise of improving new drug development and ultimately individualizing the selection of appropriate drugs and dosages for individual patients.

Genetic diversity in the form of single nucleotide DNA polymorphisms (SNPs) contributes to variable disease susceptibility and drug response. The candidate gene approach has been widely used to identify the genetic basis for pharmacogenetic traits and becomes increasingly more powerful with the recent advances in genomic technologies. High-throughput sequencing and SNP genotyping technologies allow the study of thousands of candidate genes and the identification of those involved in drug efficacy and toxicity. Expression-based genomic technologies such as DNA microarrays and proteomics also facilitate the understanding of important biological and pharmacological pathways, thus identifying more candidate genes for SNP studies. Candidate gene-based pharmacogenetic studies will lead to improved drug development, improved clinical trial design and therapeutics tailored to individual genotypes.