“Substance use disorders and mental disorders often co-occur, and we know that the most effective treatments help people address both issues at the same time. The shared genetic mechanisms between substance use and mental disorders revealed in this study underscore the importance of thinking about these disorders in tandem,” said NIMH Director Joshua A. Gordon, M.D., Ph.D. “Using genomics, we can create a data-driven pipeline to prioritize existing medications for further study and improve chances of discovering new treatments.
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Thus, thegenes and SNPs found through GWAS have had little overlap with previous findingsbased on candidate genes/pathways and linkage analyses. Since then, there have been significant advances in techniques available for mapping genes and as a result considerable changes in outlook have occurred. It is now generally accepted that genetic risk for alcoholism is likely to be due to common variants in numerous genes, each of small effect, however rare variants with large effects might also play a role. After years of family-based linkage studies and case-control candidate gene studies, attention has shifted to large scale genome-wide association studies (GWAS) for the detection of novel common variants (≥ 1%). Exome and whole genome sequencing studies for the detection of rare variants are beginning to emerge. However, it should be borne in mind that no matter how sophisticated genetic techniques might become, further advances in detecting genotype – phenotype associations are hampered by the fact that alcoholism is a heterogeneous phenotype.
The Collaborative Study on the Genetics of Alcoholism: An Update
By focusing on molecular similarities, this research opens avenues for novel therapeutic strategies and highlights the importance of addressing alcohol consumption in Alzheimer’s prevention and treatment. They also underscore the need to understand how subtle differences in physiology can contribute to a disorder as complex as addiction. This ALDH1 gene variant has since been found to be common in Asian populations–seen in 44 percent of Japanese, 53 percent of Vietnamese, 27 percent of Koreans and 30 percent of Chinese (including 45 percent of Han Chinese)–yet it is rare in people of European descent. As might be expected, people with this slow-metabolizing gene variant also have a decreased risk, by up to sixfold, for alcoholism, so it is an example of a genetic variation that can protect against developing the disorder.
Genetics of alcohol-associated diseases
If you is alcoholism a genetic disease live in a situation of poverty, for example, or in an area with limited resources, you may be less likely to have access to quality foods, community services, or adequate healthcare. Just as risk factors increase your chance of experiencing a condition, protective factors lower your risk. Having a close family relative, such as a parent, can account for up to 60% of your risk of developing AUD.
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- Sanchez-Roige and Palmer noted that their group has developed a 10-year partnership with 23andMe that has focused on numerous traits, especially those with relevance for addiction.
- The impact of genes on behavior like alcohol use or even sexual orientation has long been the subject of scientific debate.
- Revealing the biological processes that can build and reinforce alcohol addiction will most certainly help to better target existing treatments and devise new ones to break alcohol’s hold.
- Interestingly, these variations in GABRA2 do not change the protein structure of the GABAA receptor; instead they seem to modify production of the affected protein subunit, perhaps reducing the total number of functioning receptors.
Janowsky’s group proposed that muscarinic supersensitivity–that is, an enhanced effect of acetylcholine on the muscarinic cholinergic receptors–in persons prone to depression and related conditions was an underlying source of imbalance in the brain. Beyond that, Palmer and his team want to develop a better understand of how the genes they’ve identified might influence these traits, but using animal and cellular models. Alcohol use disorder (AUD) is a leading cause of death and disability worldwide and is characterized by frequent and problematic drinking behaviors, such as binge drinking, loss of control, and continued drinking despite harmful consequences. In the 170 years since the term “alcoholism” was first classified as a behavior, problematic drinking has been a widely studied condition to settle the nature versus nurture argument. Overview of COGA participants across data modalitiesa including the Semi‐Structured Assessment for the Genetics of Alcoholism (SSAGA), genome‐wide association study (GWAS) and electroencephalography (EEG) data. If you feel that you sometimes drink too much alcohol, or your drinking is causing problems, or if your family is concerned about your drinking, talk with your health care provider.
- It is no secret that the genes we inherit from our parents determine simple physical traits such as hair color and height.
- Information about the underlying genetic factors that influence risk to AUD can be derived from multiple levels of AUD including amounts of drinks (Alcohol consumption), severity and symptoms of alcohol abuse and dependence.
- The first involves focusing the testing on specific genes that are selected on the basis of their physiological roles or their reported involvement in related traits.
- Undoubtedly, there is value in limiting the use of alcohol, nicotine and other mood-altering drugs in general.
The participation of all COGA investigators at these meetings also ensures that a legacy is in place for onboarding new scientists joining the group. Insight, Not DestinyThe coga project has been structured around families, but this type of research has also strengthened understanding of the relative importance of specific gene variants as risk factors in different ethnic groups. This is not to say that certain ethnicities are more prone to alcoholism; instead, like the ALDH1 gene version that makes many East Asians intolerant of alcohol, certain of the genetic variants that contribute to risk are much more prevalent in some ethnic groups than in others. The knowledge that such genes are likely to be influencing dependence in patients belonging to one of these populations is another tool that can be used to assess the nature of an individual’s problem and to tailor treatment accordingly. As is true of many other human disorders, alcoholism does not have a single cause, nor is its origin entirely genetic. Genes can play an important role, however, by affecting processes in the body and brain that interact with one another and with an individual’s life experiences to produce protection or susceptibility.
A less generalized loss of GABA-induced inhibition, however, is thought to be involved in behavioral undercontrol or impulsivity, which is a feature of a number of psychiatric disorders, including bipolar affective disorder, substance abuse and chronic conduct problems. Studies by COGA consortium members have demonstrated that variants of the GABRA2 gene are linked to alcoholism, a finding that has since been confirmed by at least four groups. Interestingly, these variations in GABRA2 do not change the protein structure of the GABAA receptor; instead they seem to modify production of the affected protein subunit, perhaps reducing the total number of functioning receptors. Our functional genomics efforts continue to accelerate the pace at which genetic discoveries can be placed in a biological context. Furthermore, whole genome sequencing (WGS) methods, especially as their accessibility increases, would substantively improve COGA’s ability to study rarer and structural variants, the role of which continues to emerge for psychiatric disorders.
- There are 35 different ways one could pick 3 criteria from 7 (DSM-IValcohol dependence) and 330 ways to pick 4 from 11 (DSM-5 severe AUD).
- Neurons that respond to acetylcholine–described as cholinergic neurons–also have an important role in modulating the overall balance between excitation and inhibition in the brain.
- Awareness of the need for large sample sizes for GWAS has resulted in the formation of large scale collaborations for sharing data, such as the Psychiatric Genomics Consortium 82.
- Twin studies and other research have shown that genetics accounts for about half of the overall risk for alcoholism.
First and perhaps foremost, most studies ofalcohol-related phenotypes have been small – hundreds or a few thousandsamples. Most robust associations that have been reported in common disease haveemployed tens of thousands of samples and are now beginning to combine severalstudies of these magnitude into even larger meta analyses. The alcohol researchcommunity has begun to form larger consortia for meta-analyses and it is anticipatedthat with the resulting increase in sample size the number of robust associationswill increase. A second approach that will likely benefit the alcohol researchcommunity will be greater examination of pathways or gene sets. 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.
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 COGA investigators also evaluated electrophysiological variables, such as EEGs and ERPs, from study participants. EEGs measure overall brain activity, whereas ERPs are brain waves elicited in response to specific stimuli (e.g., a light or sound). 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).