PURPOSE:The review surveys the type of machine learning approaches currently used in the alcohol literature, reviews challenges in applying machine learning tools to alcohol data, and explores how overcoming these challenges could advance personalized medicine for alcohol use disorder (AUD). SEARCH METHODS:The authors conducted a search of publications on PubMed, ScienceDirect, and EBSCO Academic Search Premier published from 2015 to April 15, 2025, for articles that used machine learning to analyze alcohol-related outcomes. Search terms were ("drinking" OR "alcohol") AND ("machine learning" OR "deep learning" OR "predict" OR "classify") in the title or abstract. SEARCH RESULTS:The search returned 2,618 manuscripts. Keeping those that predicted alcohol-related outcomes and excluding those that merely used alcohol as a predictor for other outcomes reduced the selection to 567 manuscripts. A final manual selection resulted in 110 original peer-reviewed human research studies that primarily analyzed alcohol consumption behaviors and tested their models on data that they were not trained on. DISCUSSION AND CONCLUSIONS:Predictions focused on alcohol consumption or AUD diagnosis in cohorts with a mean age of 50 years or younger (i.e., when long-term drinking behaviors are being or have been established). Most studies confined the data-driven searches to a single modality and relied on conventional machine learning approaches, which tended to produce accurate and transparent predictions on the relatively small datasets typically collected by AUD studies. The small number of available samples was the most common limitation mentioned by the reviewed articles. Investigators also wished for machine learning models to provide insights about causality. Gaining these insights will be essential to improve diagnosis and treatment of AUD, for which the field must foster multidisciplinary research teams to build rigorous and trustworthy machine learning models and quantitative benchmarks that can capture the multifaceted nature of alcohol use and its comorbidities.
PURPOSE:Resilience is crucial in mitigating the risk of stress-related health issues. Although many people can adapt to adverse stress or trauma, stress exposure can increase the risk of health issues, including obesity, cardiovascular disease, and digestive illnesses. Some individuals may even develop debilitating conditions, such as post-traumatic stress disorder (PTSD). People with PTSD often struggle to adapt, sometimes turning to alcohol to cope, which can lead to alcohol use disorder (AUD), characterized by excessive alcohol-seeking and dependence. Understanding the biological underpinnings of resilience, therefore, is a key to preventing both PTSD and AUD. Recent research has uncovered the neurobiological traits that protect against the development of stress-induced alcohol dependence. Studies have shown that proactive coping and a lack of stress-related symptoms are associated with resilience. Preclinical studies, especially in rodents, have provided deeper insights into how stress impacts alcohol-seeking behaviors. Research has shown that resilience involves adaptive changes at the molecular, cellular, neural circuit, and systems levels. This review aims to integrate this research to better understand what makes people vulnerable to stress and alcohol consumption, highlighting aspects frequently overlooked in clinical models. SEARCH METHODS:This review employed systematic search strategies to achieve a comprehensive and structured assessment of the existing body of literature using the academic databases PubMed, Google Scholar, and Web of Science. Targeted keywords included "stress," "PTSD," "trauma," "alcohol," "AUD," "resilience," "vulnerability," "susceptibility," "sex difference," and "animal models"; Boolean operators (AND, OR, NOT) were used to refine the results. Exclusion criteria included research published before 1990, research that was not peer reviewed, and publications in languages other than English. Additional studies were identified by reviewing the references cited in key articles as well as by identifying subsequent studies that referenced these pivotal works. The search was carried out from April to June 2025 focusing on, but not limited to, experiments involving rodent models. SEARCH RESULTS:The search yielded a total of 347 articles. After screening, 283 articles were removed, either because they met the predefined exclusion criteria or because they were duplicates. This process resulted in 64 articles, forming the core of this comprehensive review. DISCUSSION AND CONCLUSIONS:This review summarizes an overview of recent progress in studies of PTSD and AUD, primarily focusing on the effect of resilience on post-stress alcohol intake in animal models. The findings highlight several biomarkers that may help identify individuals at risk for PTSD, AUD, or their co-occurrence, acknowledging that no single identifier can predict post-trauma outcomes. The identification of these markers is an ongoing process, yet it will be crucial for early diagnosis and risk assessment moving forward.
PURPOSE:There is an urgent need for novel and innovative advancements in alcohol research and treatment. Artificial intelligence (AI) is one such advancement that demonstrates promise, though not without important ethical concerns. This Perspective article examines current applications, ethical considerations, and future implications of integrating AI in alcohol research and treatment. SEARCH METHODS AND RESULTS:A nonsystematic narrative review of peer-reviewed, English-language studies of contemporary applications of AI (specifically, large language models and machine learning) in alcohol research and treatment was conducted in December 2024 through January 2025, using searches of the PubMed, Google Scholar, Web of Science, and PsycInfo databases. Search terms included the following: "alcohol," "alcohol use," "alcohol use disorder," "drinking," "treatment," "screening," "artificial intelligence," "chatbot," "large language models," "research subject recruitment," "research subject enrollment," "electronic health records," "support vector machine," "neural network," "black-box," "random forest," and "machine learning." The article highlights studies that discussed the role of AI in bolstering recruitment and retention for human subjects research and in the application of advanced data analytic techniques for alcohol research. Further, the article examines studies that described current and prospective uses of AI in alcohol use disorder treatment, including assessment and identification of individuals who may benefit from treatment, and as an adjunct to evidence-based treatments for alcohol use disorder. Potential ethical concerns are highlighted alongside potential considerations for the safe and ethical use of AI across these domains. CONCLUSIONS:Based on the identified primary and secondary sources, this review highlights the promises of AI in advancing both alcohol research and treatment, and how its successful implementation is supported by careful and ongoing attention to potential risks. The reviewed studies provide evidence that robust data security protocols, comprehensive informed consent, and ongoing monitoring for potential biases and harms can allow for these tools to advance scientific understanding while improving access to effective and equitable care. However, the current literature and the potential solutions suggested in this Perspective have limitations due to the pace of AI advancements that continue to accelerate at an unprecedent rate. FUTURE DIRECTIONS:Future research can advance the field by explicitly testing and evaluating the utility of these tools in real-world contexts, their risks for bias and privacy violations, and their ethical integration into alcohol research and treatment.
PURPOSE:Alcohol misuse is widely accepted as an independent risk factor for a wide variety of lung diseases, such as pneumonia and acute respiratory distress syndrome. Alcohol induces changes in the regulatory mechanisms of the lung, both at a mechanical and immunological level. Understanding these changes might help discover new targets for drugs and therapeutic approaches for the prevention of respiratory disease following alcohol misuse. SEARCH METHODS:A systematic literature search was conducted on January 25, 2025, in PubMed, Medline, and Embase of manuscripts published between January 2000 and January 2025 using the terms ("alcohol" or "ethanol") AND ("lung," or "respiratory," or "pulmonary") AND ("pneumonia" or "damage" or "leak"). Eligible manuscripts included studies that discussed the effects of ethanol on the lungs. SEARCH RESULTS:A total of 962 publications were identified; after excluding duplicates and research not covering alcohol-related lung effects (e.g., studies investigating liver damage or alcohol-related tissue injury; 814 articles), 148 studies were reviewed. An additional 15 papers from before 2000 were included as historical precedents for the current research cited. Of the 148 studies, 114 were cited in this review; previous review articles and those discussing in utero or prenatal alcohol exposure were excluded (34 articles). DISCUSSION AND CONCLUSIONS:The lungs are particularly susceptible to infections and injury following alcohol misuse. Several key mechanisms by which alcohol misuse drives lung damage have been identified. Alcohol misuse leads to impaired mucus-facilitated clearance of bacterial pathogens, increases the aspiration of microbes from the upper alimentary tract, and suppresses tissue recruitment and function of innate and adaptive immune cells. Alcohol-related reductions in antioxidant levels, trace metals, and metabolites may also contribute to lung disease in people with underlying alcohol misuse. Several regulatory molecules may play crucial roles in alcohol-induced disease processes. Although there are currently no approved therapies to combat the detrimental effects of chronic alcohol consumption on the respiratory system, these molecules may be potential therapeutic targets to guide future investigation. Despite these advancements, limitations and knowledge gaps in the field still exist. For example, few studies have investigated dose- and duration-dependent effects of alcohol on the lung, sex-specific differences in lung responses, and the interaction of alcohol with other coexposures/comorbidities, such as smoking and HIV. In addition, well-defined observational and longitudinal human studies employing robust measures of alcohol use are limited. These gaps represent novel opportunities for more thorough and robust experimental designs of human and animal studies investigating alcohol-associated lung disease.
PURPOSE:Alcohol use disorder (AUD) and mild traumatic brain injury (mTBI) have a bidirectional, synergistic, and complicated relationship. Although it is difficult to definitively say that mTBI causes AUD, certain biological mechanisms that occur after trauma are also associated with hazardous alcohol use. Hazardous drinking is defined as any quantity or pattern of alcohol consumption that places people at risk for physical and/or psychological harm. This review explores how the physiological, emotional, and behavioral consequences of mTBI may lead to worse outcomes after hazardous alcohol use and increase the risk for AUD. AUD is one of the most common comorbid conditions that occurs after mTBI, and thus a clear understanding of the mechanistic changes that influence its onset may help to identify preventative and therapeutic measures for individuals who are at risk. This review provides an overview of recently published studies (from 2021 to 2024) and how these new findings fit into the existing literature. SEARCH METHODS:This review was conducted by searching "alcohol, traumatic brain injury, TBI" in PubMed, Google Scholar, and Medline databases in October and December 2024. Only articles in English were reviewed. Titles, abstracts, and methods of all articles were read to determine relevance, then the full texts of articles that met inclusion criteria were obtained. The search included articles published after March 2021; relevant papers published before 2021 were identified by consulting previously published reviews on this topic. Articles were excluded if they only discussed (1) moderate/severe TBI, (2) adolescent populations or TBI during adolescence, (3) populations with a history of AUD before TBI, (4) acute outcomes after TBI (less than 2 weeks), or (5) prevalence or effects of TBI while intoxicated. Also excluded were papers that did not specify if TBI preceded or followed hazardous alcohol use or did not discuss the relationship between TBI and alcohol use. SEARCH RESULTS:The search resulted in 196 articles for initial examination. Of those, 155 were excluded and 42 were included. Eight review papers about alcohol use after TBI published from 2009 to 2023 were also examined, which provided foundational and additional background information on publications from 1990 to 2021. DISCUSSION AND CONCLUSIONS:This review discusses mechanisms that contribute to negative outcomes after mTBI and hazardous alcohol use and to the development of AUD after mTBI. These include inflammation and immune signaling, neuroendocrine alterations, oxidative stress, neurodegeneration, dopamine signaling, and behavioral impairments. Although current literature on the role of the gut-microbiome axis in this context is limited, this topic is also explored.There has been significant research on the biological changes that occur after mTBI and on which mechanisms may precede development of AUD; however, few studies have directly measured the outcomes of alcohol use after mTBI in the same experiment. Future preclinical and clinical research that concurrently studies alcohol use and mTBI could help establish causality for the complex relationship between trauma and alcohol use. Improved knowledge could help identify preventative measures and treatment options to improve quality of life for individuals who experience mTBI and hazardous alcohol use.
