As mentioned earlier, sales of FDA-approved alcohol treatment medications have historically been modest, though to date no substantial marketing efforts have been made for these medications. Therefore, future research needs to focus on collecting more data on the effectiveness and safety of GLP-1 receptor agonists in treating alcohol dependency through clinical trials. This includes evaluating their impact on reducing alcohol intake, controlling alcohol cravings, improving alcohol dependency-related behavioral and physiological indicators, and monitoring potential adverse reactions. Through these studies, the scientific community can gain a more comprehensive understanding of the potential of GLP-1 receptor agonists in treating alcohol dependency, offering more treatment options for patients. There have been several SNPs that show some potential in predicting pharmacotherapy treatment response.
Figure 1. Flow-chart of sample collection and processing pipeline.
The latest GWAS on more than one million participants identified more than 100 genetic variants, and the largest epigenome-wide association studies (EWAS) in blood and brain samples have revealed tissue-specific epigenetic changes. Downstream analyses revealed enriched pathways, genetic correlations with other traits, transcriptome-wide association in brain tissues, and drug-gene interactions for AUD. We also discuss limitations and future directions, including increasing the power of GWAS and EWAS studies as well as expanding the diversity of populations included in these analyses. Larger samples, novel technologies, and analytic approaches are essential; these include whole-genome sequencing, multiomics, single-cell sequencing, spatial transcriptomics, deep-learning prediction of variant function, and integrated methods for disease risk prediction. Numerous other medications have been used off label in the treatment of alcohol use disorder, and many of these have been shown to be modestly effective in meta-analyses and systematic reviews (23, 24, 26, 35).
Themes that Cut Across the Different Phases of Medications Development
A significant advantage of hiPSC models is the expanding availability of various CNS cell types that can be derived from patients. Alternatively, directed differentiation of hiPSCs involves long-term cultures with differentiation-specific growth factors and is generally thought to more closely resemble in vivo conditions but also to produce heterogeneous cell types (Maroof et al., 2013). This approach is suitable for exploring developmental components of AUDs in a mixed excitatory and inhibitory neuronal population.
Promising pharmacogenetic targets for treating alcohol use disorder: evidence from preclinical models
Studies of a wide range of alcohol-related responses in rodents indicate that they often reflect independent genetic influences. A recent large-scale twin study found three distinct dimensions of genetic risk underlying the criteria set forth in the Diagnostic and Statistical Manual of Mental Disorders IV (ref. 1) (DSM-IV) for alcohol dependence. These reflect (i) liability to heavy drinking and tolerance, (ii) self-recognition of alcohol-related problems, loss of control, desire to quit, preoccupation and activities given up, and (iii) withdrawal and continued use despite problems.
Advances in the science and treatment of alcohol use disorder
When these neurons were activated in a closed-loop manner during spontaneous slow waves, it enhanced cortical delta oscillations, an effect that was more pronounced in saline-treated mice compared to ethanol-exposed mice. These findings indicate that SST cortical neurons may play a role in the impaired slow-wave activity observed after PAE. PAE leads to persistent neuroinflammation, suggesting this could be a potential target for future therapies. Mooney et al. demonstrated that specialized pro-resolving lipid mediator (SPM) receptors, specifically FPR2 and ChemR23 receptors involved in anti-inflammatory processes, play a significant role in anxiety and memory formation. Knockout mice with alterations in these receptors exhibit impairments, exacerbated when they are exposed to ethanol in utero.
Choline has been identified as a potential supplement to ameliorate behavioral, neurological, and cognitive deficits from PAE (see Akison et al., 2018 for a review of preclinical and Ernst et al., 2022 for a review of clinical studies). Xu et al. investigated the potential therapeutic benefits of choline in mitigating ethanol-induced cell death in the developing neural tube using BXD strains of mice, known to vary in their sensitivity to ethanol’s teratogenic effects (Downing et al., 2012). Choline administration effectively reduced cell death in all strains, without causing harm in un-exposed mice. However, there were some dose-dependent differences across strains and brain regions, indicating that there is genetic variability in the response to choline treatment as well as ethanol sensitivity. These examples highlight the importance of examining the genotypic variation among individuals with AUD, but even with all this potential, we are still met with limited treatment efficacy and only minor progress over the course of decades of study.
- The environmental effects of exposure to various substances play a critical role in determining how an individual’s genetic risk to become addicted G plays out; and legality plays a large role in exposure.
- Important findings and limitations regarding the effects of these medications on alcohol-related outcomes are discussed.
- For less-prevelent or stigmatized traits, even large biobank samples may not provide sufficient information to investigate SUD polygenic architecture adequately.
- For example, initial sensitivity to alcohol is strongly and inversely related to risk for alcohol dependence64.
- The purpose of this review was to evaluate the current GxI literature focused on alcohol and other substance use behaviors, and discuss implications for future genetically-informed prevention and intervention research.
Historically, latent factor and class approaches have been used independently and for different purposes, when in reality each represents a competing hypothesis regarding why key SUD symptoms correlate with each other. Factor mixture models combine these latent factor and latent class approaches while circumventing the limitations of each31. In principle, this hybrid modeling strategy may fit diagnostic data better and, if so, provide a superior measurement and classification for SUDs. Tests comparing these competing approaches have so far revealed that, for substances like cannabis, a single latent factor remains the optimal means of assessing overall risk when measured by use, abuse, dependence and withdrawal criteria33. Alcohol withdrawal symptoms may include anxiety, tremors, nausea, insomnia, and, in severe cases, seizures and delirium tremens. Although up to 50% of individuals with alcohol use disorder present with some withdrawal symptoms after stopping drinking, only a small percentage requires medical treatment for detoxification, and some individuals may be able to reduce their drinking spontaneously.
Phenotypes/ traits to study AUD
The prospects are not quite so good for illegal SUDs that tend to be less-well-represented in biobanks. For less-prevelent or stigmatized traits, even large biobank samples may not provide sufficient information to investigate SUD polygenic architecture adequately. A further limitation of EHR data and some biobank assessments is that they meaure state rather than trait, whereas we are generally more interested in lifetime diagnoses than the research participant’s characteristics at a specific point in time.
Identifying these risk genes and understanding their action will require large clinical samples, and interaction between these studies and work in model organisms. AUD is a complex, heterogeneous disorder encompassing a variety of behavioral, psychological, and physiological traits with a complex longitudinal structure, thus posing an enormous challenge for genetic analysis. Several recent GWAS have used this approach, and it is now common to study quantitative measures, including alcohol consumption and aspects of disordered drinking, in large population samples. As a result, GWAS of alcohol use, misuse and AUD are now beginning to uncover genetic signals that have the potential to be further analyzed at the molecular, cellular, and circuit level in cellular and animal model systems. Findings from polygenic prediction and genetic correlation analyses, which are major trends in psychiatric genetics, have demonstrated that alcohol use behaviors share a common genetic basis with numerous psychiatric, educational and health outcomes. Unsurprisingly, even though studying alcohol consumption has shown some utility, it is apparent that this phenotype cannot be used as a proxy for AUD.
- For physical health, several novel causal effects were observed such as smoking initiation on stroke risk115 and fracture risk116 or body mass index on being a smoker117.
- Many individuals also have mixed genetic ancestry (referred to as admixture), which can contribute to additional variation in allele frequency.
- Across studies, the weighted mean estimates of SUD heritability—the proportion of variability in risk in a population due to genetic differences between individuals—range from 40% to 70% across different psychoactive substances3–5.
- As we have emphasized throughout this Review, it was only recently demonstrated that substance use and dependence may have important genetic differences; this is best established with respect to alcohol.
- Additional research on targeted (i.e., as needed) dosing of medications, such as nalmefene and naltrexone (32, 38), would be promising from the perspective of increasing adherence to medications and also raising awareness of potentially heavy drinking occasions.
Evidence suggests that treatment of psychiatric conditions is often most successful when a combination of pharmacological and psychosocial treatment is used (Anton et al., 2006; Balldin et al., 2003; Dugosh et al., 2016; Hien et al., 2015). However, the inclusion of a “within the skin” treatment introduces complications in the context of understanding interactions between intervention and genetics on substance use outcomes. Nevertheless, understanding the interplay between genetic influences and pharmacological interventions is an important area of research and efforts to summarize findings of such studies are warranted. Given that perturbations in neuronal excitability are thought to underlie many psychiatric disorders (Anticevic and Murray, 2017), the ability to investigate excitability and network activity of human cells is a crucial step for understanding the disease. Whole-cell patch-clamp electrophysiology provides single-cell measurements of neuronal activity, with recent advances in genetic studies of alcohol use disorders pmc details on excitatory and inhibitory synaptic inputs. This is crucial for determining dysfunctions in particular channels implicated in alcoholism (for example, GABAA (Lobo and Harris, 2008).
First is the traditional ‘inside the skin’ pathway typically considered by molecular biology (whereby gene variants influence how the drug is absorbed and interacts with receptors and second messengers, as well as hedonic and motivational pathways). Second is an ‘outside the skin’ pathway, as we illustrated for peer deviance, whereby genetically mediated personality traits affect the degree to which the individual selects themselves into drug-predisposing or protective social environments. Timeline of major findings in alcohol use behaviors (alcohol use, yellow; alcohol sensitivity and withdrawal, light orange; alcohol misuse, orange; alcohol dependence and AUD, dark orange) using GWAS methods. Besides DSM or ICD diagnosis, AUD can be assessed using the Alcohol Use Disorders Identification Test (AUDIT), a 10-item questionnaire developed by the WHO to measure hazardous or harmful drinking in the past year (66). Questions 1–3 are aimed at assessing alcohol consumption levels (AUDIT-C), and questions 4–10 are focused on evaluating problematic alcohol drinking (AUDIT-P). Thus, such a questionnaire could be implemented as a cost-effective strategy for phenotyping samples in large-scale cohorts or biobanks.
For example, initial sensitivity to alcohol is strongly and inversely related to risk for alcohol dependence64. This problem of contingency is also important, but sometimes ignored, in molecular genetic studies of SUDs. An appropriate control subject for a genetic study of drug dependence should have used the drug but not developed dependence.
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