Statistics on Alcohol Abuse and Alcoholism in the US

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. These include investigations of genetic risk and trajectories of substance use and use disorders, phenome‐wide association studies of loci of interest, and investigations of pleiotropy, social genomics, genetic nurture, and within‐family comparisons. COGA is one of the few AUD genetics projects that includes a substantial number of participants of African ancestry. The sharing of data and biospecimens has been a cornerstone of the COGA project, and COGA is a key contributor to large‐scale GWAS consortia. COGA’s wealth of publicly available genetic and extensive phenotyping data continues to provide a unique and adaptable resource for our understanding of the genetic etiology of AUD and related traits.

• These efforts ultimately are expected to lead to the identification of genes that affect the risk for alcoholism and related phenotypes.
• 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.
• Some who have inherited genes making them susceptible to alcoholism are responsible drinkers or never take a drink in their life.

DNA Regions with Susceptibility Genes

Subsequent analyses that included the additional markers supported the initial findings (Foroud et al. 2000) but did not narrow the chromosomal regions in which genes influencing alcoholism susceptibility are likely to lie. The strategies for genetic analyses in the COGA study also had to accommodate the anticipated genetic complexity of alcoholism and the multiple phenotypes that would be collected. For participants from families with three or more alcoholic family members, the investigators conducted genetic analyses using microsatellite markers—DNA regions located across all chromosomes, in which short repeated sequences exist in many variants (i.e., alleles). More than 1.2 million genotypes have been generated on 2,310 people from families of alcoholics and 1,238 people from control families.

New NIH study reveals shared genetic markers underlying substance use disorders

Approximately 75% of the families were ascertained via a proband in treatment for alcohol dependence. Initial recruitment prioritized families with at least three first degree relatives meeting criteria for alcohol dependence (i.e., densely affected) although many families include more than three individuals with AUD, hence the higher than population prevalence of alcohol dependence and AUD (Table 1). As shown in Figure 2, the proportion of families where more than half of the members met criteria for AUD ranged from 51% to 57%. Both probands and family members were characterized celebrities with fetal alcohol syndrome with age‐appropriate assessments, including a standardized diagnostic instrument designed by COGA, the Semi‐Structured Assessment for the Genetics of Alcoholism (SSAGA),10, 11 administered by trained interviewers. Additional questionnaires (e.g., personality, family history and home environment) were also administered (see 2. Sample and Clinical Data for details). Given the focus on brain‐related phenotypes, COGA collected neurocognitive and neurophysiological measures using EEG and ERP/EROs (Event‐Related Potentials/Event‐Related Oscillations; see 3. Brain Function for details).

Genetics and alcoholism

Previous studies had found that a reduced amplitude 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). Several study designs—including case–control studies, population studies, and family studies—have been used to test whether a specific gene or gene variant affects risk for a disease (for more information, see the article by Foroud and Phillips, pp. 266–272).

Because the diagnosis of an AUD requires the presence of a set ofsymptoms from a checklist, there are many different ways one could meet thecriteria. 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). Thedifficulties of genetic studies are compounded by environmental heterogeneity inaccess to alcohol and social norms related to drinking. A major goal of genetic research into alcoholism and related traits is to better understand the biology underlying this disease by identifying specific genes in which variations contribute to a person’s risk of developing the disease and then examining the pathways through which these genes and their variants affect the disease.

GCTA estimates could be used for diagnostic purposes and provide further insight as to whether variants in ADH and ALDH, among other genes, in fact contribute to the genetic predisposition for AUD. The more risk factors a person has, the greater the chance of developing an alcohol use disorder or addiction. Among the genes and pathways highlighted in this brief section are genes involved in the immune system, including nuclear factor-κB–related genes (see the article by Crews, pp. 355–361), the circadian system (see the article by Sarkar, pp. 362–366), and genes whose function is not yet clear (see the article by Buck and colleagues, pp. 367–374).

Genetic influences and causal pathways shared between cannabis use disorder and other substance use traits

• Participants with at least one inpatient or two outpatient ICD-9/10 codes for AUD were assigned as AUD cases, while participants with zero ICD codes for AUD were controls.
• These coding regions may have a strong impact on disease etiology and shed new light into possible pathophysiological mechanisms (Cirulli and Goldstein, 2010; Ng and Kirkness, 2010; Kato, 2015).
• With the advent of microarrays that can measure hundreds of thousands tomillions of single nucleotide polymorphisms (SNPs) across the genome,genome-wide association studies (GWAS) have provided a relatively unbiased wayto identify specific genes that contribute to a phenotype.
• We report here the largest multi-ancestry GWAS for PAU so far, comprising over 1 million individuals and including 165,952 AUD/AD cases.
• The inclusion of multiple ancestries both broadened the findings and demonstrated that the genetic architecture of PAU is substantially shared across these populations.
• COGA is an interdisciplinary project with the overarching goal of understanding the contributions and interactions of genetic, neurobiological and environmental factors towards risk and resilience over the developmental course of AUD, including relapse and recovery.
• The inclusion of data from different ancestral groups in this study cannot and should not be used to assign or categorize variable genetic risk for substance use disorder to specific populations.

Are You At Risk Of Becoming An Alcoholic?

Treatment and Medication Options for Alcohol Use Disorder

• A changing definition of the heterogeneous phenotype of AUD may also pose a challenge to identifying genetic variants through GWAS.
• Moreover, people who use drugs are facing an increasingly dangerous drug supply, now often tainted with fentanyl.
• Environmental factors, as well as gene and environment interactions, account for the remainder of the risk.
• Researchers have used both case–control and family studies to identify genes related to alcoholism risk.
• 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.