One such successful study performed exon-focused sequencing of impulsive individuals derived from a Finnish population isolate and identified a stop codon in HTR2B (1% frequency) that was unique to Finns. The stop codon carriers performed violently impulsive acts, but only whilst intoxicated with alcohol [85]. Despite the evidence supporting the prominence of genetic factors in AUD’s etiology, the identification of genetic risk variants has been difficult and labor intensive. With recent advances in technology, the most promising results stem from recent GWAS, which have helped to identify new variants in the genetics of AUD. Among the variants identified, the most significant SNPs remain in the alcohol metabolism enzyme genes, ADH and ALDH. Importantly, the prevalence of the various isoforms of ADH and ALDH differs among ethnicities and populations.
Supplementary Tables
- The manuscript was written by H.R.K., H. Zhou, R.L.K., R.V.S. and J.G., with comments provided by all other authors.
- COGA’s family-based structure, multimodal assessment with gold-standard clinical and neurophysiological data, and the availability of prospective longitudinal phenotyping continues to provide insights into the etiology of AUD and related disorders.
- As larger samples areassembled and more variants analyzed, a much fuller picture of the many genesand pathways that impact risk will be discovered.
- For example, Hess et al.140 created a “polygenic resilience score” for schizophrenia by matching unaffected individuals at high genetic risk with risk‐matched cases, and then identifying genetic variants that contribute to resilience to schizophrenia and do not overlap with risk loci.
- The data from the second part of the split sample—the replication sample, which comprised 1,295 people from 157 families—generally supported the initial findings (Foroud et al. 2000).
- 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.
Many approaches to creating polygenic scores, from linkage disequilibrium (LD) clumping or pruning and thresholding approaches, to modern Bayesian methods, and even functional polygenic signatures, are available. COGA is one of the few family‐based genetic projects with a significant number of African Americans, who are greatly underrepresented in such studies, particularly those with family‐based designs. Analyses of 987 people from 105 families in the initial sample provided evidence that regions on 3 chromosomes contained genes that increase the risk for alcoholism (Reich et al. 1998). The strongest evidence was for regions on chromosomes 1 and 7, with more modest evidence for a region on chromosome 2. The DNA regions identified through these analyses were broad, as is typical for studies of complex genetic diseases, and therefore are likely to contain numerous genes.
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Abundant evidence indicates thatalcoholism is a complex genetic disease, with variations in a large number ofgenes affecting risk. Some of these genes have been identified, including twogenes of alcohol metabolism, ADH1B and ALDH2,that have the strongest known affects on risk for alcoholism. Studies arerevealing other genes in which variants impact risk for alcoholism or relatedtraits, including GABRA2, CHRM2,KCNJ6, and AUTS2. As larger samples areassembled and more variants analyzed, a much fuller picture of the many genesand pathways that impact risk will be discovered. Given such findings, molecular genetics studies have attempted to identify specific variation within the genome related to increased risk for AUD. Early work in the field focused on genome-wide linkage and candidate gene association studies.
- Their studies have shown that genes like ADH1B and ALDH2 are crucial in alcohol metabolism, with specific variants more prevalent in the Asian population.
- Linkage studies are limited in terms of their spatial resolution, and thus, association studies that measure differences in allele frequencies between ‘case’ and ‘control’ populations were also pursued.
- The purpose of the Collaborative Study on the Genetics of Alcoholism (COGA) is to advance knowledge about the complex influences of gene and environment on development and progression of alcohol use disorder (AUD).
- Those immersed in high-stress occupations or environments often tend to heavy alcohol consumption, more so than those in less stressful situations.
- Significant genetic correlations for AUD-adjusted for BMI did not differ substantially from those for AUD alone.
Supplementary Data 24
The AUDIT, a 10-item, self-reported test developed by the World Health Organization as a screen for hazardous and harmful drinking4,5 has been used for genome-wide association studies (GWASs) both as a total score6,7,8 and as the AUDIT-Consumption (AUDIT-C) and AUDIT-Problems (AUDIT-P) sub-scores8. The three-item AUDIT-C measures the frequency and quantity of usual drinking and the frequency of binge drinking, while the 7-item AUDIT-P measures alcohol-related problems. While the recent use of GWAS to identify the underlying genetic components of AUD has been promising, there are several limitations of GWAS that must be considered. GWAS use a ‘hypothesis-free’ design by genotyping hundreds of thousands to 2 million markers simultaneously in cases and controls.
Genes contributing to the risk of alcohol dependence
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). One component of an ERP is a brain wave called P300, which typically occurs 300 milliseconds after a stimulus. Previous studies had found that a reduced amplitude https://ecosoberhouse.com/ of the P300 wave is a heritable phenotype that correlates with alcohol dependence and other psychiatric disorders (Porjesz et al. 1998). The genetic analyses of the COGA participants identified four regions, on chromosomes 2, 5, 6, and 13, that appear to contain genes affecting the amplitude of the P300 (Begleiter et al. 1998).
The Neuroscience Behind Alcohol Dependence
Over the past decade there have been tremendous advances in large scale SNP genotyping technologies and next generation sequencing and these technologies, including GWAS arrays and whole genome sequencing, are now widely available. Results of GWAS suggest that numerous common variants with very small effect and potentially rare variants with large effects are likely to encode proteins within, or regulate, numerous biological pathways. The current hope is that with very large sample sizes, GWAS will provide novel information about genetic underpinnings of alcoholism, including gene pathways that are altered in disease. The strongest and most consistent findings for GWAS for AUD are for alcohol metabolizing genes, as in a recent study in an East Asian (Korean) sample of alcoholics in which ALDH2 and ADH1B showed up as GWAS signals with genome-wide significance [68].
The region on chromosome 1 provided the strongest evidence for a susceptibility gene in the combined sample. In addition, this new evaluation detected a region on chromosome 8 that was linked with the risk for alcoholism. Despite the significant genetic overlap between the AUDIT-C and AUD diagnosis, downstream analyses revealed biologically meaningful points of divergence. The AUDIT-C yielded some GWS findings that did not overlap with those for AUD, which reflects genetic independence of the traits. This broadens our previous observations using SNPs in ADH1B, in which we validated the AUDIT-C score as an alcohol-related phenotype33. In that study, after accounting for the effects of AUDIT-C score, AUD diagnoses accounted for unique variance in the frequency of ADH1B minor alleles.
Association with chromatin interactions in brain
The rate at which acetaldehyde is produced and converted to the waste product acetate is influenced by genetic variations encoding the isoenzymes of ADH and ALDH. Individuals with isoforms of ADH that oxidize ethanol at a faster rate and/or isoforms of ALDH genetics of alcoholism that oxidize acetaldehyde at a slower rate are protected against AUD due to the unpleasant effects that result from acetaldehyde accumulation. Research using family, adoption, and twin studies was the first to demonstrate the role of genetics in AUD.
- Although information such as family history can currently be used to identify at-risk individuals, understanding the genetic architecture of AUD could enable us to pinpoint these individuals with greater certainty.
- Over the past few years numerous whole genome linkage studies have been performed in which the inheritance of phenotypes and genetic markers is followed in families [12,40].
- In addition, this new evaluation detected a region on chromosome 8 that was linked with the risk for alcoholism.
- A review of studies from 2020, which looked at a genome-wide analysis of more than 435,000 people, found 29 different genetic variants that increased the risk of problematic drinking.
- Over the past decade there have been tremendous advances in large scale SNP genotyping technologies and next generation sequencing and these technologies, including GWAS arrays and whole genome sequencing, are now widely available.
