Research Article: Identifying Genetic Variation for Alcohol Dependence

Date Published: , 2012

Publisher: National Institute on Alcohol Abuse and Alcoholism

Author(s): Arpana Agrawal, Laura J. Bierut.



Researchers are using various strategies to identify the genes that may be associated with alcoholism. The initial efforts primarily relied on candidate gene and linkage studies; more recently, however, modern advances in genotyping have resulted in widespread use of genome-wide association studies for alcohol dependence. The key findings of the earlier studies were that variations (i.e., polymorphisms) in the DNA sequences of the genes encoding alcohol dehydrogenase 1B (i.e., the ADH1B gene), aldehyde dehydrogenase 2 (i.e., the ALDH2 gene), and other alcohol-metabolizing enzymes mediate the risk for alcoholism; moreover, these polymorphisms also have an impact on the risk of alcohol-related cancers, such as esophageal cancer. In addition, a gene encoding one of the receptors for the neurotransmitter γ-aminobutyric acid (GABA) known as GABRA2 seems to have a role in the development of alcohol dependence. Genome-wide association studies now offer a host of emerging opportunities, as well as challenges, for discovering the genetic etiology of alcohol dependence and for unveiling new treatment strategies.

Partial Text

Alcohol dependence was one of the first disorders to be associated with a genetic contribution. In 1972, facial flushing and decreased tolerance after alcohol exposure was observed in subjects of Asian ancestry (Wolff 1972)—a response that is associated with characteristic alterations in alcohol metabolism. Upon ingestion and absorption into the blood stream, alcohol first is converted to acetaldehyde in the liver in a process catalyzed by the enzyme alcohol dehydrogenase (ADH). Acetaldehyde is a highly toxic cancer-inducing substance (i.e., carcinogen) that normally is converted rapidly to acetate, a less toxic form. This reaction is mediated by the mitochondrial enzyme aldehyde dehydrogenase (ALDH). In this metabolic chain of events, two basic mechanisms can result in the accumulation of acetaldehyde in the body—faster metabolism of alcohol to acetaldehyde, which is related to increased ADH activity, and/or slower metabolism of acetaldehyde to acetate, which is caused by decreased ALDH activity. The excessive production and accumulation of acetaldehyde then results in the flushing response, which may be accompanied by lightheadedness, nausea, accelerated heart rate, and headaches. Because of the unpleasantness of this reaction, people experiencing flushing typically drink little or no alcohol.

Other early genetic studies of alcohol dependence relied on candidate gene association studies and genome-wide linkage studies. Candidate gene studies leveraged the earliest identified genetic variations in specific genes by examining one gene, and often one variant, at a time to determine whether the variant was associated with alcoholism. These experiments identified hundreds of genes as potentially contributing to alcoholism. For example, in addition to the genes encoding alcohol-metabolizing enzymes, genes involved in brain signaling (i.e., neurotransmitter) systems, such as the dopaminergic, cholinergic, and serotonergic systems, have been nominated for their association with alcohol dependence. In contrast to the alcohol-metabolizing genes, however, these other candidate gene associations have not yet been validated in the modern large-scale genetic studies. This lack of convergence of candidate gene studies and GWASs potentially reflects a large number of false-positive findings from the previous candidate gene findings. Another potential explanation is that extensive genetic heterogeneity exists, meaning that multiple genes each modestly contribute to the development of alcohol dependence and that the samples collected to date, although they were obtained from thousands of subjects, are not yet sufficient in size to detect variation in these regions.

Genome-wide linkage studies, which examine whether large genetic regions distributed across the entire genome are cotransmitted along with a disease within families, were the first genetic studies to query the entire genome with hundreds or thousands of genetic markers. These studies had two main characteristics: they were family based, and the marker coverage across the genome was modest. Although these linkage studies implicated multiple regions of the genome as being involved in the development of alcoholism, the most consistent findings have pointed to two regions on chromosome 4, with peaks at chromosome locations 4p13–4p12 and on 4q21–4q23.2 The 4q21–4q23 region covers the cluster of alcohol dehydrogenase genes that includes, among others, ADH1B, supporting the candidate gene findings that alcohol-metabolizing genes are associated with alcohol dependence. The chromosome 4p13 region also contains a cluster of genes encoding the α-subunit of the receptor for the inhibitory neurotransmitter γ-aminobutyric acid (GABA), suggesting that polymorphisms in this receptor also may be involved in the development of alcohol dependence. This cluster of GABA receptor genes is of particular interest because of their putative biological relevance to alcohol-related behaviors, as discussed in the following section.

GWASs represent the most recent paradigm change for gene discovery. The allure of GWASs is that they allow for interrogation of hundreds of thousands to over 1 million SNPs across the human genome at relatively modest cost. Thus, GWASs can potentially lead to the identification of variants of modest effect size that may not be recognized in candidate gene studies for their biological significance in alcoholism. The principal disadvantage is the fairly severe multiple-testing burden (i.e., the need to account for the possibility that when 1 million tests are conducted, some positive results will be obtained due to chance alone) imposed by GWASs, which results in the requirement for statistical significance to be denoted by P values of 5 × 10−8 and lower. This represents a very high significance level for validation; consequently, many SNPs that truly are associated with alcoholism risk may not yet have been recognized because they have not yet surpassed this threshold.

Alcohol is consumed by an overwhelming majority of the U.S. population, and 55 percent of the world’s population has consumed alcohol (World Health Organization [WHO] 2011). Per capita consumption varies greatly by country. For example, the most recent figures from the WHO (2011) indicate that among people ages 15 and older, per capita annual alcohol consumption was 11 liters in Russia and 8.5 liters in the United States, with much lower consumption levels reported in parts of Asia and northern Africa. Although modest alcohol consumption is associated with health (e.g., cardiovascular) benefits, according to the WHO, 2.5 million people die each year from the harmful effects of alcohol ( In the United States, nearly 80,000 people die annually from the short- and long-term consequences of alcohol use (Mokdad et al. 2004). Excessive alcohol consumption can lead to alcohol dependence, which affects 12.5 percent of people in the United States across their lifetime (Hasin et al. 2007). Thus, the health effects of alcohol consumption remain a public health priority that needs to be studied from all angles, including improving prevention and treatment, while also examining basic biological underpinnings.

Genetic association studies only are a first step in understanding the biology underlying alcohol dependence. An association represents a correlation with a tested variant (and all the untested correlated variants). These groups of associated SNPs often span many genes on a chromosome, and once a genetic association is confirmed the task is to investigate how these variants and the genes they are located in contribute to the biological mechanisms underlying disease development. The ultimate goal of understanding these biological mechanisms is to gain new insights into potential treatment approaches.

Researchers long have known that alcohol dependence clusters in families. During the past 50 years, adoption and twin studies definitively have demonstrated that this clustering is related to genetic influences. Twin studies have estimated that 30 to 60 percent of the variance in alcohol dependence is attributable to the effects of genetic variants segregating in families (Dick and Bierut 2006). Researchers now are entering a new phase in genetic studies where they are beginning to unlock the genetic code that leads to disease.





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