In the 4th edition of the DSM (DSM-IV), alcohol dependence (AD) and abuse were considered as mutually exclusive diagnoses that together made up AUDs. By considering AD and abuse under single umbrella increased the number of diagnosed subjects, but this number was still not large enough to design powerful GWAS studies. Therefore, many genetic studies of alcoholism also concentrated on nonclinical phenotypes, such as alcohol consumption and Alcohol Use Disorders Identification Test (AUDIT)17–19, from large population based cohorts. The AUDIT, a 10-item, self-reported test was developed by the World Health Organization as a screen for hazardous and harmful drinking and can be used as a total (AUDIT-T), AUDIT-Consumption (AUDIT-C) and AUDIT-Problems (AUDIT-P) sub-scores. This review describes the genetic approaches and results from the family‐based Collaborative Study on the Genetics of Alcoholism (COGA).
For studies of rare variants, families are quite valuable for sortingout true positives from the background of individual variations that we allharbor. From its inception, COGA has focused on the importance of brain function and on developing novel brain intermediary phenotypes of risk for and consequences of alcohol use and AUD. This has been done through the examination of neuropsychological tests and noninvasively recorded brain electrical activity during resting state and cognitive tasks, and more recently, by deriving measures of neural synchrony and connectivity (3. Brain Function). About 80% of those with brain function data have more than one assessment, yielding a relatively large longitudinal cohort with these data.
The genetics of alcohol dependence
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.
What Increases the Risk for Alcohol Use Disorder?
The design of COGA as a large, multi‐modal, family‐based study that was enriched for AUD liability also brings forth certain caveats. Large families that are densely affected may not be representative of the constellation of genetic and socio‐environmental risk and resilience factors influencing AUD in the general population. COGA has contributed to large, collaborative studies (e.g., References 5, 55, 69) that bring together data from many different studies with different ascertainments, and thereby enriched those studies. However, it is worth noting that effect sizes of loci and of polygenic scores may be influenced by our ascertainment strategy. Reassuringly, many COGA findings have been replicated in other samples (e.g., References 76, 77, 78, 79). 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.
- As whole exome and whole genome sequencingtechnologies come down in cost, they are being applied to identifying rarevariants.
- 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.
- Note that the official names of several ADH genes have been changed, and theliterature has been confused by some groups using non-standard names for some ofthe genes29.
- 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.
- The possibility of identifying such genetic “resilience” variants that may help protect against the development of an alcohol use disorder could provide insight into novel treatments or prevention efforts.
Note that the official names of several ADH genes have been changed, and theliterature has been confused by some groups using non-standard names for some ofthe genes29. Health care professionals use criteria from the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5), to assess whether a person has AUD and to determine the severity, if the disorder is present. Severity is based on the number of criteria a person meets based on their symptoms—mild (two to three criteria), moderate (four to five criteria), or severe (six or more criteria).
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.
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).
RECRUITMENT: A FOCUS ON FAMILIES
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).
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.
Genes contributing to the risk of alcohol dependence
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.
“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. To do this accurately, it’s critical that the genetic evidence we gather includes globally representative populations and that we have members of communities historically underrepresented in biomedical research leading and contributing to these kinds of studies,” said Alexander Hatoum, Ph.D., a research assistant professor at Washington University in St. Louis and lead author of the study. It is now appreciated that a whole spectrum of allele frequencies andeffect sizes may play roles, from common variations with small effects throughrare variants of large effect. As whole exome and whole genome sequencingtechnologies come down in cost, they are being applied to identifying rarevariants.
Can People With Alcohol Use Disorder Recover?
- The strong effects of binge drinking suggest that merelycalculating an average number of drinks per week is likely to obscure many effectsof alcohol, since it treats 2 standard drinks per day (14 per week) the same as 7drinks on each of two days per week.
- To provide a community‐facing forum for sharing our own research findings and also provide summaries of the state of scientific knowledge in the field of alcohol research, COGA has developed a series of resources for the public to understand how genetic and environmental factors contribute to the development of alcohol use problems.
- Group meetings are available in most communities at low or no cost, and at convenient times and locations—including an increasing presence online.
- It is likely that, as for most complex diseases, alcohol dependence and AUDsare due to variations in hundreds of genes, interacting with different socialenvironments.
- In a recent application of these “nature of nurture” models in COGA,124 parental polygenic scores were partitioned into alleles that were transmitted and nontransmitted to the child.
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.
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 genetics of alcohol use disorder national institute on alcohol abuse and alcoholism niaaa 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.
Table 1. Criteria for alcohol 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 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).