Chronological relationship between antisocial personality disorder and alcohol dependence

Personality disorders, and particularly antisocial personality disorder (ASPD), frequently co-occur with alcohol dependence. ASPD is considered to be an important cofactor in the pathogenesis and clinical course of alcohol dependence. The chronological relationship between the onset of symptoms of ASPD and alcohol-dependence characteristics has not yet been studied in great detail and the role of ASID in classification schemes of alcohol dependence as suggested by Cloninger and Schuckit has yet to be determined. We studied 55 alcohol-dependent patients to assess the prevalence and age at manifestation of ASPD, conduct disorder characteristics as well as alcohol dependence by employing the Semi-Structured Assessment for the Genetics of Alcoholism and the Structured Clinical Interview for DSM-IIIR. Results indicate that the onset of ASPD characteristics precede that of alcohol dependence by some 4 years. This finding suggests that in patients with ASPD, alcohol dependence might be a secondary syndrome as suggested by previous research. Copyright (C) 2002 S. Karger AG, Basel

Is alcohol dependence best viewed as a chronic relapsing disorder?

This 'For Debate' paper starts by recognizing the growing trend towards considering alcohol dependence as a chronic relapsing disorder. We argue that the adoption of this model results from focusing on those in treatment for alcohol dependence rather than considering the larger number of people in the general population who meet criteria for alcohol dependence at some point in their lives. The majority of the general population who ever experience alcohol dependence do not behave as though they have a chronic relapsing disorder: they do not seek treatment, resolve their dependence themselves and do not relapse repeatedly. We suggest that caution is therefore needed in using the chronic relapsing disorder label. Our primary concerns are that this formulation privileges biological aspects of dependence to the detriment of psychological and social contributions, it inhibits much-needed developments in understanding alcohol dependence and leads to inefficient distributions of public health and clinical care resources for alcohol dependence. We invite debate on this issue

GABRA2 and Alcohol Dependence in College-Aged Students

GABRA2 and Alcohol Dependence in College-aged Students Abaiz Chaudhri, Depts. of Biology and Chemistry, with Dr. Amy Adkins and Dr. Sally Kuo, Dept. of Psychology Problematic alcohol use and associated consequences is a major problem in college-aged students. These outcomes, and alcohol dependence (uncontrolled alcohol consumption despite consequences), are complex and influenced by genetics and environmental factors, and the interplay between both. Variants in the gene GABRA2 have been shown to be associated with alcohol dependence in adolescents and older adults, yet the association is not studied nearly enough in the college-aged population, a high-risk period for the development of alcohol-related problems. The hypothesis of this study is that GABRA2 is associated with alcohol dependence in college-aged students of European and African ancestry. The data was obtained from Spit4Science, where surveys were given to college students and saliva samples were collected and DNA extracted. The results indicate that the 8 genetic variants studied showed no significant association between GABRA2 and alcohol dependence in either ancestry. Our results suggest that further research needs to be conducted, either on the same or different genetic variants to see whether there may still be an association. This study adds a primary look at GABRA2 as it relates to alcohol dependence within a college-aged sample.https://scholarscompass.vcu.edu/uresposters/1341/thumbnail.jp

Co-occurring risk factors for alcohol dependence and habitual smoking.

Smoking and alcohol dependence frequently occur together, and both behaviors are determined in part by genetic influences. The Collaborative Study on the Genetics of Alcoholism (COGA), which is investigating the genetic factors contributing to alcohol dependence, also allows for analyses of the genetic factors determining smoking. Using a sample comprised of alcoholics and their closest (i.e., first-degree) relatives as well as a community-based control sample, COGA investigators found that both alcohol dependence and habitual smoking were transmitted within families. This familial transmission resulted from both common and drug-specific influences, which likely include genetic factors. Further genetic studies (i.e., candidate gene studies and genomic screening approaches) have identified several DNA regions that may contain genes that confer a susceptibility for alcoholism. Some of those genes also may contribute to the risk for habitual smoking

A multimodal neuroimaging classifier for alcohol dependence

With progress in magnetic resonance imaging technology and a broader dissemination of state-of-the-art imaging facilities, the acquisition of multiple neuroimaging modalities is becoming increasingly feasible. One particular hope associated with multimodal neuroimaging is the development of reliable data-driven diagnostic classifiers for psychiatric disorders, yet previous studies have often failed to find a benefit of combining multiple modalities. As a psychiatric disorder with established neurobiological effects at several levels of description, alcohol dependence is particularly well-suited for multimodal classification. To this aim, we developed a multimodal classification scheme and applied it to a rich neuroimaging battery (structural, functional task-based and functional resting-state data) collected in a matched sample of alcohol-dependent patients (N = 119) and controls (N = 97). We found that our classification scheme yielded 79.3% diagnostic accuracy, which outperformed the strongest individual modality - grey-matter density - by 2.7%. We found that this moderate benefit of multimodal classification depended on a number of critical design choices: a procedure to select optimal modality-specific classifiers, a fine-grained ensemble prediction based on cross-modal weight matrices and continuous classifier decision values. We conclude that the combination of multiple neuroimaging modalities is able to moderately improve the accuracy of machine-learning-based diagnostic classification in alcohol dependence

A multimodal neuroimaging classifier for alcohol dependence

With progress in magnetic resonance imaging technology and a broader dissemination of state-of-the-art imaging facilities, the acquisition of multiple neuroimaging modalities is becoming increasingly feasible. One particular hope associated with multimodal neuroimaging is the development of reliable data-driven diagnostic classifiers for psychiatric disorders, yet previous studies have often failed to find a benefit of combining multiple modalities. As a psychiatric disorder with established neurobiological effects at several levels of description, alcohol dependence is particularly well-suited for multimodal classification. To this aim, we developed a multimodal classification scheme and applied it to a rich neuroimaging battery (structural, functional task-based and functional resting-state data) collected in a matched sample of alcohol-dependent patients (N = 119) and controls (N = 97). We found that our classification scheme yielded 79.3% diagnostic accuracy, which outperformed the strongest individual modality - grey-matter density - by 2.7%. We found that this moderate benefit of multimodal classification depended on a number of critical design choices: a procedure to select optimal modality-specific classifiers, a fine-grained ensemble prediction based on cross-modal weight matrices and continuous classifier decision values. We conclude that the combination of multiple neuroimaging modalities is able to moderately improve the accuracy of machine-learning-based diagnostic classification in alcohol dependence

ADH1B is associated with alcohol dependence and alcohol consumption in populations of European and African ancestry.

A coding variant in alcohol dehydrogenase 1B (ADH1B) (rs1229984) that leads to the replacement of Arg48 with His48 is common in Asian populations and reduces their risk for alcoholism, but because of very low allele frequencies the effects in European or African populations have been difficult to detect. We genotyped and analyzed this variant in three large European and African-American case-control studies in which alcohol dependence was defined by the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) criteria, and demonstrated a strong protective effect of the His48 variant (odds ratio (OR) 0.34, 95% confidence interval (CI) 0.24, 0.48) on alcohol dependence, with genome-wide significance (6.6 × 10(-10)). The hypothesized mechanism of action involves an increased aversive reaction to alcohol; in keeping with this hypothesis, the same allele is strongly associated with a lower maximum number of drinks in a 24-hour period (lifetime), with P=3 × 10(-13). We also tested the effects of this allele on the development of alcoholism in adolescents and young adults, and demonstrated a significantly protective effect. This variant has the strongest effect on risk for alcohol dependence compared with any other tested variant in European populations

A Network Model of Alcoholism and Alcohol Policy

The evolution of alcohol dependence in populations of people on different social networks is studied. Two models are studied. One is the evolution of the states of individuals on hypothesized social structures from a rewired connected caveman model. This model spans a range of social structures (networks) from very ordered to effectively random with small world structures in between. The second model is a zip-code-level model which uses data from a recent survey in Delaware. The model is a discrete model using 10 zip codes. The results show that the evolution of alcohol dependence, as governed by the simple rules that we use, depends sensitively on the network structure and a hypothetical treatment regime

DNA methylation age is accelerated in alcohol dependence.

Alcohol dependence (ALC) is a chronic, relapsing disorder that increases the burden of chronic disease and significantly contributes to numerous premature deaths each year. Previous research suggests that chronic, heavy alcohol consumption is associated with differential DNA methylation patterns. In addition, DNA methylation levels at certain CpG sites have been correlated with age. We used an epigenetic clock to investigate the potential role of excessive alcohol consumption in epigenetic aging. We explored this question in five independent cohorts, including DNA methylation data derived from datasets from blood (n = 129, n = 329), liver (n = 92, n = 49), and postmortem prefrontal cortex (n = 46). One blood dataset and one liver tissue dataset of individuals with ALC exhibited positive age acceleration (p < 0.0001 and p = 0.0069, respectively), whereas the other blood and liver tissue datasets both exhibited trends of positive age acceleration that were not significant (p = 0.83 and p = 0.57, respectively). Prefrontal cortex tissue exhibited a trend of negative age acceleration (p = 0.19). These results suggest that excessive alcohol consumption may be associated with epigenetic aging in a tissue-specific manner and warrants further investigation using multiple tissue samples from the same individuals