Behavioral therapies can help people develop skills to avoid and overcome triggers, such as stress, that might lead to drinking. Medications also can help deter drinking during times when individuals may be at greater risk of a return to drinking (e.g., divorce, death of a family member). In 2021, more than 46 million people in the United States aged 12 or older had at least one substance use disorder, and only 6.3% had received treatment. Moreover, people who use drugs are facing an increasingly dangerous drug supply, now often tainted with fentanyl. Approximately 107,000 people died of drug overdoses in 2021, and 37% of these deaths involved simultaneous exposure to both opioids and stimulant drugs. Drug use and addiction represent a public health crisis, characterized by high social, emotional, and financial costs to families, communities, and society.

• First and perhaps foremost, most studies ofalcohol-related phenotypes have been small – hundreds or a few thousandsamples.
• GWAS arebeginning to yield robust findings, although the experience in many diseases isthat very large numbers of subjects will be needed.
• Of note, assessments, interviewer training and data cleaning are standardized across all sites, with some variations in assessment driven by individual institutional IRB criteria.

What Increases the Risk for Alcohol Use Disorder?

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). 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, 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).

What Are the Types of Treatment for Alcohol Use Disorder?

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.

Family studies have consistently demonstrated that there is a substantialgenetic contribution to alcohol dependence. Additionalgenes have been identified that have expanded our understanding of the genes andpathways involved; however, the number of findings to date is modest. First and perhaps foremost, most studies ofalcohol-related phenotypes have been small – hundreds or a few thousandsamples.

Associated Data

• Our functional genomics efforts continue to accelerate the pace at which genetic discoveries can be placed in a biological context.
• At the core of COGA’s scientific mission is our expectation that through the systematic characterization of the clinical, genetic, environmental and brain‐related factors that contribute to alcohol use and misuse, we can begin to identify mechanisms that will eventually truncate the course of AUD, if not substantially deter its onset altogether.
• 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.
• 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 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.

Alcohol levels in common drinks rangefrom approximately 5% (1.1 M) for beer, 11-15% for wine (∼3M) and 40% for spirits (∼9 M). The oral cavity and esophagus aredirectly exposed to those levels, and the liver is exposed to high levels from theportal circulation. Thus it is not surprising that diseases of the GI system,including cirrhosis, pancreatitis, and cancers of the upper GI tract are affected byalcohol consumption80-86. Overview of genetically informed designs that have been used or are proposed for use in the COGA sample. Of these 12,145 samples with genotype data, 136 only have C‐SSAGA data, so there are 12,009 COGA participants with full SSAGA and genotype data.

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.

Adolescent Brain Cognitive Development (ABCD) Study

Recent linkage analyses in humans and rodents have pointed to genomic regions harboring genes that influence alcoholism. Refinement of clinical phenotypes and use of intermediate phenotypes will improve chances of gene identification. All these advances in the understanding of the genetics of alcoholism should facilitate the development of more accurately targeted therapies using molecular diagnostic approaches. 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.

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. A particularly attractive feature of studying rare variation in COGA is its family design, which aids the identification of both private and disorder‐generalized mutations. Similarly, our ability to measure the brain’s activity during resting state and during various cognitive tasks with exquisite temporal accuracy, allows us to develop and implement EEG protocols that uniquely address questions regarding the course of AUD. While COGA has maintained its focus on EEG, a subset of COGA genetics of alcohol use disorder national institute on alcohol abuse and alcoholism niaaa participants have been imaged using brain Magnetic Resonance Imaging (MRI) allowing for comparisons between these data.82 Moreover, genetic differences in COGA participants are now being translated into changes in neuronal function using advanced molecular and cellular tools, potentially leading to novel therapeutic strategies for treating AUD.

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 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).

Blood samples were obtained for genomic data generation and were also immortalized as cell lines in the NIAAA/COGA Sharing repository (see 4. Genetics for details). This rich database has grown over the past three decades via the phased recruitment of additional families or family members and longitudinal follow‐up of participants. For example, the COGA prospective study gathered longitudinal assessments of adolescent and young adult offspring from the families. More recently, recognizing the numerous changes including marriage, divorce, childbirth and career transitions that can significantly impact the course of alcohol use, AUD and remission, COGA has focused on longitudinal data collection of those in mid‐life (30–40s). 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.

Behavioral Treatments

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. COGA is a family‐based study8 and members of large families (Figure 1), a subset of which are densely affected with AUD, have been longitudinally characterized9 in clinical, behavioral, neuropsychological, neurophysiological and socio‐environmental domains, yielding a rich multi‐modal phenotypic dataset paired with a large repository of biospecimens and genetic data (Table 1 provides sample sizes). Accompanying this overview are individual reviews (2. Sample and Clinical Data, 3. Brain Function, 4. Genetics and 5. Functional Genomics) that provide in‐depth characterization of our clinical, behavioral, genomic, functional genetic and brain function (electro‐encephalograms EEGs and event‐related potentials ERPs and oscillations EROs) data and the research that these data have supported to date. However, the fundamental strength of COGA has been our ability to integrate across these domains in a cohort of families with whom we have established a robust research relationship for over three decades. While the polygenic nature of complex traits has made individual risk variant and gene identification efforts challenging, this polygenicity can be leveraged with tools such as genome‐wide polygenic scoring115 (PGS or PRS, Figure 1).

Thus, thegenes and SNPs found through GWAS have had little overlap with previous findingsbased on candidate genes/pathways and linkage analyses. Twin studies have established that there are substantial genetic influences on alcoholism (0.5-0.6) in both men and women. Our knowledge of behaviors predisposing to alcoholism, including anxiety and impulsivity, is advancing rapidly through animal and human studies. Although alcoholism is often comorbid with other substance abuse and psychiatric disorders, recent studies have shown that, with the exception of nicotine, the heritability of alcoholism is largely substance-specific. Increasing understanding of the neurobiology of addiction has identified neural pathways in which genetic variation at candidate genes could influence vulnerability.

Further, most clinical trials and behavioral studies have focused on individual substances, rather than addiction more broadly. Behavioral treatments—also known as alcohol counseling, or talk therapy, and provided by licensed therapists—are aimed at changing drinking behavior. Examples of behavioral treatments are brief interventions and reinforcement approaches, treatments that build motivation and teach skills for coping and preventing a return to drinking, and mindfulness-based therapies. This GWAS primarily consisted of AA families based on self‐reported familial ancestry; principal components analysis of genetic data was subsequently used to compute genetic similarities across all participants. 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. Recent successes in genetic studies of AUDs will definetely motivate researchers and lead to better therapeutic interventions for this complex disorder.

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. There are several other genes that have been shown to contribute to the riskof alcohol dependence as well as key endophenotypes. In most cases, studiesrecruited families having multiple members with alcohol dependence; such familiesare likely to segregate variants that affect the risk of alcohol dependence. Themost common initial approach was linkage analysis, in which markers throughout thegenome were measured to identify chromosomal regions that appeared to segregate withdisease across many families.