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. By monitoring the inheritance patterns of such marker alleles within families with alcoholic members, the investigators could identify chromosomal regions that influence (i.e., show genetic linkage with) certain alcohol-related traits. 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. Researchers hope to use this knowledge to develop new, more effective, and more targeted treatment and prevention strategies.
Supplementary Data 23
As in EUR, AUD in AFR was genetically correlated with substance use traits including OUD, smoking trajectory (that identifies groups of individuals that follow a similar progression of smoking behavior), and maximum habitual alcohol intake. PheWAS of PRS in AFR from PsycheMERGE and Yale–Penn confirmed that AUD is genetically correlated with substance use traits. The lack of a wider set of phenotypes for comparison by ancestry is a continuing limitation.
The genetic basis of alcoholism: multiple phenotypes, many genes, complex networks
Together, these endeavors will continue to shed light on the genetic contribution to alcoholism. Second, two studies appear to be outliers, producing results at variance with the general trend. The estimate of the shared environmental contribution to alcoholism risk from the Kaij (1960) study is much greater than in all other studies. The reasons for this are unknown, although it is possible that in the work by Kaij some registrations were accidentally overlooked. However, once one twin from a pair was identified with a registration, the records were searched more thoroughly to determine whether the co-twin also had been registered. Cadoret’s study of four adoption agencies (Cadoret 1994; Cadoret et al. 1995) has yielded a high estimate of the genetic contribution to variability in alcoholism risk, which does not differ significantly from a probability of 100 percent (i.e., complete heritability).
- As more variants are analysed and studies are combined for meta-analysis to achieve increased sample sizes, an improved picture of the many genes and pathways that affect the risk of alcoholism will be possible.
- The lack of a wider set of phenotypes for comparison by ancestry is a continuing limitation.
- The AUDIT-C yielded some GWS findings that did not overlap with those for AUD, which reflects genetic independence of the traits.
- 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).
- Another QTL on chromosome 1 was mapped to a 0.44 Mb interval containing 15 candidate genes, including Kcnj9.
- Red dots are the regions fine mapped across EUR, AFR and LA; blue dots are the regions fine mapped across EUR and AFR; green dots are the regions fine mapped across EUR and LA; and black dots are the regions only fine mapped in EUR.
- One NIAAA-supported study, the Collaborative Study on the Genetics of Alcoholism Project (COGA), explores how genes affect vulnerability to AUD, and has an easy-to-understand web resource about alcohol and genetics.
New NIH study reveals shared genetic markers underlying substance use disorders
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 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 https://ecosoberhouse.com/article/alcohol-poisoning-signs-and-symptoms/ Data for details).
- However, the specific causes are still unknown, and identifying the biological basis for this risk is a vital step in controlling the disease.1 Explore whether alcoholism is passed down through biological families and how you can avoid an AUD if alcohol misuse runs in your family.
- The methods used in these genetic analyses and other aspects of the COGA study are described in more detail in the article by Bierut and colleagues, pp. 208–213, in this issue.
From its inception, COGA has generated and utilized extensive arrays of genotypic and phenotypic data from families densely affected by AUD and from comparison families to identify genes and understand their role in susceptibility to (or protection from) developing AUD and related phenotypes. New genetic variants have been identified, refined endophenotypes have been characterized, and functional information has begun to emerge on known genetic variants that influence risk for and protection from AUD. These longitudinal data have been instrumental in COGA’s ability to chart the etiology and course of alcohol use and AUD across the lifecourse. For instance, our early family data documented the increased co‐aggregation of multiple SUDs in AUD probands and their first degree relatives, relative to comparison families, providing initial support for familial clustering of and potential genetic influences on the comorbidity across AUD and SUDs (e.g., References 21, 22).
The researchers speculated that if the genetic contribution to alcoholism were important, the rates of alcoholism should be higher in the adopted-away offspring of the alcoholic biological parents than in the adopted-away offspring of the control parents. The goals of this renewal concept are to continue to integrate and share COGA data and to continue to add data across the lifecycle, specifically in the adolescent and young adult (Prospective Study) and older adult (Lifespan Study) cohorts. Despite the significant genetic overlap between the AUDIT-C and AUD diagnosis, downstream analyses revealed biologically meaningful points of divergence.
Body mass index-adjusted GWAS
COGA was designed during the linkage era to identify genes affecting the risk for alcohol use disorder (AUD) and related problems, and was among the first AUD-focused studies to subsequently adopt a genome-wide association (GWAS) approach. 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.
We have since conducted several studies that have disentangled family history into elements of genetic liability, nurture and density of risk (e.g., References 23, genetics of alcoholism 24, 25). Our data on adolescent offspring of individuals with AUD documented the role of behavioral precursors, such as externalizing problems, and social environments, such as peers and parents, in trajectories that separated persisting drinking problems from developmentally‐delimited heavy alcohol use (e.g., References 26, 27, 28). We were also able to examine the risk posed by early initiation of alcohol use on later drinking milestones using several analytic paradigms (e.g., References 29, 30). More recently, our longitudinal design has facilitated characterizations of remission and recovery in AUD (e.g., References 31, 32, 33). A detailed description of these findings is outlined in the accompanying review (2. Sample and Clinical Data).
Study Design
C, Comparison for the highest PIPs from cross-ancestry and EUR-only fine mapping in the 92 regions. Red dots are the regions fine mapped across EUR, AFR and LA; blue dots are the regions fine mapped across EUR and AFR; green dots are the regions fine mapped across EUR and LA; and black dots are the regions only fine mapped in EUR. The causes of AUD are complex and can involve a variety of factors, including early exposure to alcohol use, peer group pressure, and living with other mental health conditions. While genetics can account for up to 60% of AUD risk, not everyone with a family history of AUD will develop the condition. AUD isn’t directly caused by genetics, but genetics may predispose you to developing AUD later in life. This risk is considered hereditary and may be passed down to you if you have a family history of AUD.
Recent Findings
In vertebrates, neuropeptide Y (NPY) signaling plays a role in alcohol intake and dependence 61, 62. Invertebrates have an ortholog to NPY, neuropeptide F (NPF), and signaling via NPF also influences ethanol-related behaviors 44, 63. This survey was designed to study the co-occurrence of alcohol and other drug use disorders with psychiatric disorders in the United States. Here, the control adoptees have been assigned a risk of 1 because they are the group against which the other groups in the study are measured. A risk ratio of 3.6 for adopted-away sons of alcoholics thus means that that group is 3.6 times as likely as the control adoptees to become alcoholic.
