Carriers of the low activity variant of MAOA–LPR display hyperactivation of the hippocampus and amygdala during the retrieval of negatively valenced emotional material but not during the retrieval of neutral material 82. Therefore, the increased sensitivity to adverse experiences of carriers of the low activity MAOA genotype might be due to their impaired ability to extinguish adverse memories and conditioned fears. Other important mechanisms that are likely to underlie G × E interactions include hormonal effects. Steroid hormones including estrogens, progesterones, androgens and glucocorticoids modulate MAOA expression 83,84. Both glucorticoids and androgens increase MAOA expression through response elements that are located within the MAOA promoter 83.
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In their study, the Yale team discovered that the risk genes were correlated to changes in certain brain regions. This finding suggested to researchers that the risk variants promoted certain brain pathways that contribute to the development of behavior patterns and disorders. The team was able to identify twenty-nine genes linked to increased risk of problematic alcohol use—nineteen of them novel—in the human genome, extending the known genetic architecture of the disorder and giving other scientists a wider breadth of targets for follow-up studies. Researchers found that six to eleven percent of the phenotypic variation—referring to differences in what physical and behavioral traits are expressed—could be explained by genetic information.
- The two earliest Iowa adoption studies (i.e., the LSS and CFS) show significantly elevated risk to adopted-away sons from alcoholic biological backgrounds compared with control adoptees (i.e., risk ratios of 3.5 and 3.6, respectively), consistent with a genetic influence on alcoholism risk in men.
- Indeed, a positive correlation between testosterone level and antisocial behavior was found only among carriers of the low-activity allele, suggesting that this VNTR might influence the effect of testosterone on the MAOA promoter.
- Analysis of such electrophysiological data may reveal a subset of genes that affect these quantitative, biological phenotypes related to alcoholism (Porjesz et al. 1998, 2002).
- The class I ADH enzymes encoded by the ADH1A, ADH1B and ADH1C genes contribute about 70% of the total ethanol oxidizing capacity, and the class II enzyme encoded by ADH4 contributes about 30% 19.
With the exception of the two outlier studies, in the remaining studies, nonshared environmental influences account for at least 30 percent of the variation in alcoholism risk. The liability model provides a natural framework for combining data from different studies using widely different definitions of alcoholism. It also allows us to compare the importance of genetic and/or shared environmental influences on alcoholism risk in men and women, despite the significant gender differences in the prevalence of alcoholism. In genetic studies, these liability correlations are usually expressed in terms of the causes of variation in alcoholism liability.
Thus, the replication sample again provided evidence that genes increasing the risk of alcoholism were located in the same regions of chromosomes 1 and 7, albeit with less statistical support. When the initial and replication samples were combined, these chromosomal regions remained the strongest candidates for containing genes influencing the risk of alcoholism. Evidence for the region on chromosome 2 increased with the additional markers in the initial sample, but the replication sample provided no additional evidence for alcoholism susceptibility genes in this chromosomal region.
Table 1. Criteria for alcohol use disorders.
The oral cavity and esophagus aredirectly exposed to those levels, and the liver is exposed to high levels from theportal circulation. Thus it is not surprising that diseases of the GI system,including cirrhosis, pancreatitis, and cancers of the upper GI tract are affected byalcohol consumption80-86. The researchers believe that even larger studies may help to differentiate the genetics behind alcohol addiction. Your genetics can influence how likely you are to develop AUD, but there’s currently no evidence of a specific gene that directly causes AUD once you start drinking. The risks of smoking were first widely publicized by the Surgeon General’s Report of 1964, and the combination of that medical information and social pressure has reduced the prevalence of smoking over the subsequent decades. An individual’s awareness of personal genetic medical risks may similarly change his or her choices.
Nonetheless, this simplified model provides a good starting point for comparing results from different studies. One approach for comparing studies of disorders having a complex mode of inheritance has been a liability, or “threshold,” model. In this model, a person’s liability to develop alcoholism is assumed to be determined by the combined effects of many separate risk factors—genetic, environmental, or both. The distribution of liability to alcoholism in the general population is assumed to be continuous and to follow a bell curve. The majority of people exhibit an intermediate risk; some, a very low risk; and some, a very high risk. The model assumes that those whose liability exceeds some critical value (i.e., threshold) will become alcoholic.
Beyond replication, the exploration of which specific aspects of the alcoholism phenotype each involved gene affects and which other diseases or traits may be influenced by it is essential. Moreover, it will be equally important to determine the potential underlying mechanisms through functional studies, including the use of animal models, particularly those in which candidate genes or alleles are introduced into the organism (i.e., knocked-in). New technological developments that allow for faster and more complete genotyping and sequencing will accelerate progress, as will technical developments allowing targeted overproduction or inactivation of genes in animal models. The Collaborative Study on the Genetics of Alcoholism (COGA) is a large-scale family study designed to identify genes that affect the risk for alcoholism (i.e., alcohol dependence) and alcohol-related characteristics and behaviors (i.e., phenotypes1).
Are Children of Alcoholics More Likely to Become Alcoholics?
In addition, because heavy drinking can exacerbate age‐related physical and neurocognitive problems, interact with medications, and cause falls and accidents, especially in older adults, a longitudinal follow‐up of COGA participants aged 50 and older is in progress. Of note, assessments, interviewer training and data cleaning are standardized across all sites, with some variations in assessment driven by individual institutional IRB criteria. Taken together, these waves of longitudinal follow‐up provide a perspective of AUD risk and resilience across the lifespan. The increasing availability of the DNA sequence of the entire human genome and knowledge of variations in that sequence among people are greatly aiding the current phase of the research. Particularly important to the current work is the use of the sequence data to identify which genes are located within the regions that have shown linkage with alcoholism and the other phenotypes examined in the COGA analyses and to identify variations (i.e., polymorphisms) within those genes.
Genes contributing to the risk of alcohol dependence
These approacheshave been quite fruitful for some studies and need to be employed in analyses ofalcohol-related traits and phenotypes. Over the next few years, we anticipate theidentification of additional common and rare variants contributing to the risk ofalcohol dependence. Within both the U.S. and Scandinavian studies, no significant gender differences were found in the genetic contribution to alcoholism risk. In the Scandinavian data, genetic factors appear to be more important in women than in men (a pattern that is seen in both the Swedish adoption and Swedish twin studies), but no statistically significant difference exists. Based on the U.S. data, genetic effects account for approximately 60 percent of the variance in alcoholism risk in both men and women, and the twin data suggest that there is no significant effect of family environment. The U.S. adoption data suggest that the adoptees’ family environments may account for one-third of the variance.
Researchers hope to use this knowledge to develop new, more effective, and more targeted treatment and prevention strategies. Instead, variations in many, and perhaps hundreds, of genes likely have a small but measurable influence on disease risk that ultimately adds up to a substantial impact. Moreover, Want to Quit Drinking Use These 8 Strategies to Make It a Reality the impact of any one gene variation depends both on the individual’s genetic background (i.e., other genetic variations the person carries) and on the environment.
