The Collaborative Study on the Genetics of Alcoholism: An Update PMC
Ethanol is metabolized largely in the liver by alcohol dehydrogenases (ADH) to the toxic acetaldehyde which is then converted to acetate by aldehyde dehydrogenases (ALDH), primarily by the mitochondrial enzyme ALDH2. 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. However, results reached significance if the diagnostic criteria were either narrowed (to require withdrawal symptoms) or broadened (to include problem drinking).
Genetics and alcoholism
Although it is clearly known that genetic factors play a role in alcoholism, identification of the specific genes involved has proved challenging. Major determinants of complexity are likely to include genetic heterogeneity (see Glossary at the end of this paper), heterogeneity at the level of neurobiological vulnerability, polygenicity, phenocopies, gene × environment interaction and incomplete penetrance. Consequently, several genetic loci that moderate vulnerability to alcoholism have been identified.
Core Resource information on genetic vulnerability to AUD
As noted above, the functional ADH1B polymorphism isnot represented on GWAS platforms; GABA-receptor genes are often nominallysignificant but well below genome-wide significance in these studies. Thus, thegenes and SNPs found through GWAS have had little overlap with previous findingsbased on candidate genes/pathways and linkage analyses. This finding suggests that variants of a gene or genes within this region reduced the risk of becoming alcoholic. ADH alleles are known to affect the risk for alcoholism; however, the known protective alleles occur at high frequency in Asian populations but are rare in the Caucasian population that makes up most of the COGA sample (Edenberg 2000). Therefore, these analyses may have identified a new protective ADH allele or another protective gene located nearby. The number of unaffected sibling pairs genotyped in the replication sample was too small to analyze.
- For individual studies, Heath and colleagues (in press) estimated the proportions of variability in alcoholism liability explained by genetic and family environmental influences.
- These mechanisms, that include DNA methylation, post-translational covalent modifications of histones, nucleosome sliding and nucleosome and histone substitution, cause modifications of chromatin conformation which, in turn, regulate gene expression (for review see Tsankova et al. 123).
- Individual reviews in this issue provide detailed illustrations of the ways in which COGA data have contributed towards advancing our understanding of the etiology, course and consequences of AUD, and pathways from onset to remission and relapse.
- Postulating a 28-percent prevalence rate for alcohol problems in the general population, the risk of alcoholism in adopted-away sons from alcoholic backgrounds is significantly greater than that for the general population.
- Estimates of the prevalence of alcoholism are highly variable, depending on how alcoholism is defined.
- Therefore, a more refined search for candidate genes within the region of interest is subsequently conducted.
At the phenotype level, major progress has been made through the use of intermediate phenotypes. As mentioned, alcoholism is a multi-factorial disease and several genes, each of small effect, as well as environmental variables, are likely to be involved. As will be discussed, in some instances common functional alleles of small effect have been identified, and in other cases uncommon alleles of strong effect are also known. From what is known, and from the large part of the genetic variance in risk that is still unexplained by genes identified so far, it is clear that methods are needed to identify additional loci whose individual influence is small at the population level.
Alcohol metabolism and the risk for AUD
Many genes contribute to this risk, with most of those genes making only very small contributions to the overall risk. Genes that affect AUD risk are involved in various biological processes and mental states and traits, including physiological responses to alcohol and stress, alcohol metabolism, addiction-related neurobiology, and behavioral eco sober house tendencies such as impulsivity. Scientists have learned through studies of identical and non-identical twins that alcohol use disorder is heritable, with genetic factors accounting for about half of the risk of alcohol dependence. Part of the challenge has been to gather a study that is large enough to detect a genetic signal, said Palmer.
In addition, a fruit fly’s resistance to alcohol appears to be controlled by the same molecular mechanism as humans. Although the genetic bases of alcoholism remain largely unknown, there are reasons to think that more genes will be discovered in the future. Multiple and complementary approaches will be required to piece together the mosaic of causation.
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Many factors are involved in the development of AUD, but having a relative, or relatives, living with AUD may account for almost one-half of your individual risk. Alcohol use disorder (AUD) is a diagnosis once referred to as “alcoholism.” It’s a condition characterized by patterns of excessive alcohol misuse despite negative consequences and major distress in important areas of daily function. The sensitive mice tend to lose their inhibitions and pass out rather quickly, earning them the nickname „long sleepers.“ „Short sleepers“ are mice that are genetically less sensitive to alcohol. A genetic analysis tool containing a large number of features such that many different DNAs, RNAs or proteins can be measured simultaneously. Witnessing parents abusing alcohol and experiencing the linked disruptions can increase the likelihood of developing problematic drinking patterns later in life.
Alcoholism has a substantial heritability yet the detection of specific genetic influences has largely proved elusive. Moreover, it has become apparent that variants in stress-related genes such as CRHR1, may only confer risk in individuals exposed to trauma, particularly in early life. Over the past decade there have been tremendous advances in large scale SNP genotyping technologies allowing for genome-wide associations studies (GWAS).
About 80% of those with brain function data have more than one assessment, yielding a relatively large longitudinal cohort with these data. While the D2 dopamine receptor gene did not have the effect expected on alcoholism, the study contributed to moving forward genetic research. “We know now that it was only a first step of a very long road of complex genetics,” said Renato Polimanti, a colleague of Gelernter at the Yale School of Medicine. In contrast to Angier’s conclusion that AUD is decided by the environment, scientists have since found multiple genetic players. They are essential in influencing the brain’s function and response to addictive substances like alcohol. Certain genetic variations, such as cytochrome enzymes in the liver, can also influence how quickly a person metabolizes drugs.
If genetic influences, in particular, are important, a significantly higher risk ratio should occur in MZ compared with DZ twin pairs. 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. For male adoptees in the remaining two samples, the risk to those from an alcoholic background is not significantly higher than that for control adoptees. In these latter studies, however, the rates of alcoholism are high, even in the control adoptees (from 55 to 58 percent), raising the possibility that the entire sample of adoptees, on average, came from high-risk biological backgrounds. Postulating a 28-percent prevalence rate for alcohol problems in the general population, the risk of alcoholism in adopted-away sons from alcoholic backgrounds is significantly greater than that for the general population. The goal of this series of reviews is to describe the study design, highlight the multi‐modal data available in the Collaborative Study on the Genetics of Alcoholism (COGA), and document the insights that these data have produced in our understanding of the lifecourse of AUD.
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