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Memory problems are common among older adults with a history of alcohol use disorder (AUD). Employing a machine learning framework, the current study investigates the use of multi-domain features to classify individuals with and without alcohol-induced memory problems. A group of 94 individuals (ages 50-81 years) with alcohol-induced memory problems (Memorygroup) were compared with a matchedControlgroup who did not have memory problems. The Random Forests model identified specific features from each domain that contributed to the classification of Memory vs. Control group (AUC=88.29%). Specifically, individuals from the Memory group manifested a predominant pattern of hyperconnectivity across the default mode network regions except some connections involving anterior cingulate cortex which were predominantly hypoconnected. Other significant contributing features were (i) polygenic risk scores for AUD, (ii) alcohol consumption and related health consequences during the past 5 years, such as health problems, past negative experiences, withdrawal symptoms, and the largest number of drinks in a day during the past 12 months, and (iii) elevated neuroticism and increased harm avoidance, and fewer positive “uplift” life events. At the neural systems level, hyperconnectivity across the default mode network regions, including the connections across the hippocampal hub regions, in individuals with memory problems may indicate dysregulation in neural information processing. Overall, the study outlines the importance of utilizing multidomain features, consisting of resting-state brain connectivity collected ∼18 years ago, together with personality, life experiences, polygenic risk, and alcohol consumption and related consequences, to predict alcohol-related memory problems that arise in later life.

ImportanceCharacterizing whether genetic variants for psychiatric outcomes operate via specific versus general pathways provides more informative measures of genetic risk, and, potentially, allows us to design more targeted prevention and interventions.ObjectiveEmploy multivariate methods to tease apart variants associated with problematic alcohol use through either general or specific pathways and compare results to standard univariate genetic analysis of problematic alcohol use.DesignWe compared results from a univariate genome wide association study (GWAS) of problematic alcohol use to those from a previous multivariate GWAS of externalizing phenotypes. We identified genetic variants associated with problematic alcohol use through a broad liability to externalizing, and those that remain after removing shared variance with externalizing. We compared these results across SNP overlap, bioannotations, genetic correlations, and polygenic scores.SettingWe included GWAS summary statistics from existing GWAS, and two US based hold out samples: The National Longitudinal Study of Adolescent to Adult Health (Add Health) and the Collaborative Study on the Genetics of Alcoholism (COGA).ParticipantsPublicly available GWAS of externalizing behaviors and participants in Add Health (N=5,107) and COGA (N=7,483), limited to individuals of European ancestries.Exposure(s)N/AMain Outcome(s) and Measure(s)Outcomes included problematic alcohol use (ALCP-O), shared risk for externalizing (EXT), and problematic alcohol use-specific risk (ALCP-S) for the GWASs; a preregistered list of 99 available phenotypes for genetic correlations; and substance use, substance use disorder criteria, and alcohol misuse in the polygenic score analyses.ResultsThe analysis differentiated SNPs operating through common versus specific risk pathways. While ALCP-O was associated with multiple phenotypes, ALCP-S was predominantly associated with alcohol use and other forms of psychopathology. Polygenic scores for ALCP-O were associated with a variety of other forms of substance use and substance use disorders, polygenic scores for ALCP-S were only associated with alcohol phenotypes. Polygenic scores for both ALCP-S and EXT show differential patterns of associations with alcohol misuse across development.Conclusions and RelevanceFocusing on the differential impacts of shared and specific risk can better characterize pathways of risk for alcohol use disorders. Multivariate methods can be a useful tool for studying many psychiatric conditions. Parsing risk pathways will become increasingly relevant as genetic information is incorporated into clinical practice for psychiatric outcomes.

Genetic predispositions play an important role in alcohol use. Understanding the psychosocial mechanisms through which genetic risk unfolds to influence alcohol use outcomes is critical for identifying modifiable targets and developing prevention and intervention efforts. In this study, we examined the role of sensation seeking and social support from family and friends in linking genetic risk to alcohol use. We also examined the role of social support in moderating the associations between genetic risk and sensation seeking and alcohol use. Data were drawn from a sample of 2,836 European American adults from the Collaborative Study on the Genetics of Alcoholism (46% male, mean age = 35.65, standard deviation [SD] = 10.78). Results from path analysis indicated that genome-wide polygenic scores for alcohol consumption (alc-GPS) were associated with higher sensation seeking, which in turn was associated with higher levels of alcohol use. alc-GPS was also associated with higher alcohol use indirectly via lower levels of family support. In addition, high friend support attenuated the association between alc-GPS and sensation seeking and alcohol use. The pattern of associations was similar for males and females, with some differences in the associations between social support and alcohol use observed across age. Our findings highlight the important role of intermediate phenotypes and gene-environment interplay in the pathways of risk from genetic predispositions to complex alcohol use outcomes. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Predictive models for recovering from alcohol use disorder (AUD) and identifying related predisposition biomarkers can have a tremendous impact on addiction treatment outcomes and cost reduction. Our sample (N = 1376) included individuals of European (EA) and African (AA) ancestry from the Collaborative Study on the Genetics of Alcoholism (COGA) who were initially assessed as having AUD (DSM-5) and reassessed years later as either having AUD or in remission. To predict this difference in AUD recovery status, we analyzed the initial data using multimodal, multi-features machine learning applications including EEG source-level functional brain connectivity, Polygenic Risk Scores (PRS), medications, and demographic information. Sex and ancestry age-matched stratified analyses were performed with supervised linear Support Vector Machine application and were calculated twice, once when the ancestry was defined by self-report and once defined by genetic data. Multifeatured prediction models achieved higher accuracy scores than models based on a single domain and higher scores in male models when the ancestry was based on genetic data. The AA male group model with PRS, EEG functional connectivity, marital and employment status features achieved the highest accuracy of 86.04%. Several discriminative features were identified, including collections of PRS related to neuroticism, depression, aggression, years of education, and alcohol consumption phenotypes. Other discriminated features included being married, employed, medication, lower default mode network and fusiform connectivity, and higher insula connectivity. Results highlight the importance of increasing genetic homogeneity of analyzed groups, identifying sex, and ancestry-specific features to increase prediction scores revealing biomarkers related to AUD remission.

Genome-wide, polygenic risk scores (PRS) have emerged as a useful way to characterize genetic liability. There is growing evidence that PRS may prove useful for early identification of those at increased risk for certain diseases. The current potential of PRS for alcohol use disorders (AUD) remains an open question. Using data from both a population-based sample [the FinnTwin12 (FT12) study] and a high-risk sample [the Collaborative Study on the Genetics of Alcoholism (COGA)], we examined the association between PRSs derived from genome-wide association studies (GWASs) of (1) alcohol dependence/alcohol problems, (2) alcohol consumption, and (3) risky behaviors with AUD and other substance use disorder (SUD) criteria. These PRSs explain ~2.5–3.5% of the variance in AUD (across FT12 and COGA) when all PRSs are included in the same model. Calculations of area under the curve (AUC) show PRS provide only a slight improvement over a model with age, sex, and ancestral principal components as covariates. While individuals in the top 20, 10, and 5% of the PRS distribution had greater odds of having an AUD compared to the lower end of the continuum in both COGA and FT12, the point estimates at each threshold were statistically indistinguishable. Those in the top 5% reported greater levels of licit (alcohol and nicotine) and illicit (cannabis and opioid) SUD criteria. PRSs are associated with risk for SUD in independent samples. However, usefulness for identifying those at increased risk in their current form is modest, at best. Improvement in predictive ability will likely be dependent on increasing the size of well-phenotyped discovery samples.

Genome-wide association studies (GWAS) of alcohol dependence (AD) have reliably identified variation within alcohol metabolizing genes (eg, ADH1B) but have inconsistently located other signals, which may be partially attributable to symptom heterogeneity underlying the disorder. We conducted GWAS of DSM-IV AD (primary analysis), DSM-IV AD criterion count (secondary analysis), and individual dependence criteria (tertiary analysis) among 7418 (1121 families) European American (EA) individuals from the Collaborative Study on the Genetics of Alcoholism (COGA). Trans-ancestral meta-analyses combined these results with data from 3175 (585 families) African-American (AA) individuals from COGA. In the EA GWAS, three loci were genome-wide significant: rs1229984 in ADH1B for AD criterion count (P = 4.16E-11) and Desire to cut drinking (P = 1.21E-11); rs188227250 (chromosome 8, Drinking more than intended, P = 6.72E-09); rs1912461 (chromosome 15, Time spent drinking, P = 1.77E-08). In the trans-ancestral meta-analysis, rs1229984 was associated with multiple phenotypes and two additional loci were genome-wide significant: rs61826952 (chromosome 1, DSM-IV AD, P = 8.42E-11); rs7597960 (chromosome 2, Time spent drinking, P = 1.22E-08). Associations with rs1229984 and rs18822750 were replicated in independent datasets. Polygenic risk scores derived from the EA GWAS of AD predicted AD in two EA datasets (P

Background: The Semi-Structured Assessment for the Genetics of Alcoholism (SSAGA) is an interview that assesses psychiatric symptoms and diagnoses, including substance use disorders and anxiety and mood (i.e., internalizing) disorders. Although the SSAGA is widely used, there exists no overall internalizing characteristics scale based on items drawn from SSAGA’s mood and anxiety disorder sections. Objectives: To design and assess a SSAGA-based measurement instrument capturing the overall internalizing dimension that underlies more specific internalizing conditions. Methods: We developed, assessed, and characterized a new scale for measuring internalizing problematic characteristics derived from the SSAGA interview. All samples were drawn from the Collaborative Studies on the Genetics of Alcoholism, a prospective multi-site genetic study of families at high risk for alcohol use disorders. All participants taking part in the study between September 2005 and September 2017 were eligible (n = 904, 52.2% female). Results: The scale had adequate internal consistency (ordinal α = 0.85, 95% CI = [0.81, 0.89]). Construct validity was supported by its association with other measures of internalizing characteristics (Internalizing Scale from Achenbach Self Reports; Neuroticism Scale from the Neuroticism-Extraversion-Openness Five-Factor Personality Inventory). Several indices of alcohol, marijuana, and nicotine misuse were also positively associated with Internalizing Scale scores. Conclusions: The Internalizing Scale has very good psychometric properties and can be used in studies that incorporate the SSAGA interview to study the association between internalizing characteristics and problematic alcohol and other substance use. These associations can potentially be utilized to identify individuals at risk for substance problems and to design treatments targeting such individuals.

Author(s): Schuckit, Marc A; Smith, Tom L; Danko, George; Anthenelli, Robert; Schoen, Lara; Kawamura, Mari; Kramer, John; Dick, Danielle M; Neale, Zoe; Kuperman, Samuel; McCutcheon, Vivia; Anokhin, Andrey P; Hesselbrock, Victor; Hesselbrock, Michie; Bucholz, Kathleen | Abstract: BackgroundAlcohol problems reflect both environmental and genetic characteristics that often operate through endophenotypes like low levels of response (low LRs) to alcohol and higher impulsivity. Relationships of these preexisting characteristics to alcohol problems have been studied, but few analyses have included both low LR and impulsivity in the same model.MethodsWe extracted prospective data from 1,028 participants in the Prospective Youth Sample of the Collaborative Study on the Genetics of Alcoholism (COGA). At Time 1 (age 18), these drinking but non-alcohol-dependent males and females completed the Barratt Impulsivity Scale and the Self-Report of the Effects of Alcohol questionnaire regarding drinks required for effects the first 5 times of drinking (SRE5-LR). Two years later, they reported perceived drinking patterns of peers (PEER), their own alcohol expectancies (EXPECT), and their drinking to cope with stress (COPE). Subsequently, at Time 3, participants reported numbers of up to 11 DSM-IV alcohol criterion items experienced in the 2nyears since Time 2 (ALC PROBS). Data were analyzed using structural equationnmodeling (SEM).ResultsIn the SEM, Baseline SRE5-LR and impulsivity were weakly related and did not interact in predicting later ALC PROBS. LR was directly linked to Time 3 ALC PROBS and to PEER, but had no direct path to EXPECT, with partial mediation to ALC PROBS through PEER to EXPECT and via COPE. Impulsivity did not relate directly to ALC PROBS or PEER, but was directly related to EXPECT and COPE, with effects on ALC PROBS also operating through EXPECT and COPE.ConclusionsLow LRs and impulsivity related to Time 3 ALC PROBS through somewhat different paths. Education- and counseling-based approaches to mitigate future alcohol problems may benefit from emphasizing different potential mediators of adverse alcohol outcomes for youth with low LRs versus those with high impulsivity or both characteristics.

© 2015 Research Society on Alcoholism. Background: Heavy alcohol consumption and alcohol problems among college students are widespread and associated with negative outcomes for individuals and communities. Although current methods for prevention and intervention programming have some demonstrated efficacy, heavy drinking remains a problem. A previous pilot study and a recent large-scale evaluation (Schuckit et al., 2012, 2015) found that a tailored prevention program based on a risk factor for heavy drinking, low level of response (low LR) to alcohol, was more effective at reducing heavy drinking than a state-of-the-art (SOTA) standard prevention program for individuals with the low LR risk factor. Methods: This study enrolled 231 first-semester college freshmen with either high or low LR into the same level of response-based (LRB) or SOTA online prevention programs as in the previous reports (consisting of 4 weeks of video modules), as well as a group of matched controls not receiving alcohol prevention, and compared changes in alcohol use between these groups across a 6-month period. Results: Individuals in alcohol prevention programs had a greater reduction in maximum drinks per occasion and alcohol use disorder symptoms than controls. There was limited evidence for interactions between LR and prevention group in predicting change in alcohol use behaviors; only among participants with strict adherence to the program was there an interaction between LR and program in predicting maximum drinks per occasion. However, overall, low LR individuals showed greater decreases in drinking behaviors, especially risky behaviors (e.g., maximum drinks, frequency of heavy drinking) than high LR individuals. Conclusions: These results indicate that prevention programs, including brief and relatively inexpensive web-based programs, may be effective for persons at highest risk for heavier drinking, such as those with a low LR. Tailored programs may provide incremental benefits under some conditions. Long-term follow-ups and further investigations of tailored prevention programs based on other risk factors are needed.

In this project, we aimed to bring large-scale gene-identification findings into a developmental psychopathology framework. Using a family-based sample, we tested whether polygenic scores for externalizing disorders—based on single nucleotide polymorphism weights derived from genome-wide association study results in adults ( n = 1,249)—predicted externalizing disorders, subclinical externalizing behavior, and impulsivity-related traits among adolescents ( n = 248) and young adults ( n = 207) and whether parenting and peer factors in adolescence moderated polygenic risk to predict externalizing disorders. Polygenic scores predicted externalizing disorders in adolescents and young adults, even after we controlled for parental externalizing-disorder history. Polygenic scores also predicted subclinical externalizing behavior and impulsivity traits in the adolescents and young adults. Adolescent parental monitoring and peer substance use moderated polygenic scores to predict externalizing disorders. This illustrates how state-of-the-science genetics can be integrated with psychological science to identify how genetic risk contributes to the development of psychopathology.

BackgroundThe age at onset of alcohol dependence (AD) is a critical moderator of genetic associations for alcohol dependence. The present study evaluated whether single nucleotide polymorphisms (SNPs) can influence the age at onset of AD in large high-risk families from the Collaborative Study on the Genetics of Alcoholism (COGA).MethodsGenomewide SNP genotyping was performed in 1788 regular drinkers from 118 large European American families densely affected with alcoholism. We used a genome-wide Cox proportional hazards regression model to test for association between age at onset of AD and SNPs.ResultsThis family-based analysis identified an intergenic SNP, rs2168784 on chromosome 3 that showed strong evidence of association (P=5×10(-9)) with age at onset of AD among regular drinkers. Carriers of the minor allele of rs2168784 had 1.5 times the hazard of AD onset as compared with those homozygous for the major allele. By the age of 20 years, nearly 30% of subjects homozygous for the minor allele were alcohol dependent while only 19% of those homozygous for the major allele were. We also identified intronic SNPs in the ADP-ribosylation factor like 15 (ARL15) gene on chromosome 5 (P=1.11×10(-8)) and the UTP20 small subunit (UTP20) gene on chromosome 12 (P=4.32×10(-8)) that were associated with age at onset of AD.ConclusionsThis extended family based genome-wide cox-proportional hazards analysis identified several loci that might be associated with age at onset of AD.

ObjectiveA person's pattern of heavier drinking often changes over time, especially during the early drinking years, and reflects complex relationships among a wide range of characteristics. Optimal understanding of the predictors of drinking during times of change might come from studies of trajectories of alcohol intake rather than cross-sectional evaluations.MethodThe patterns of maximum drinks per occasion were evaluated every 2 years between the average ages of 18 and 24 years for 833 subjects from the Collaborative Study on the Genetics of Alcoholism. Latent class growth analysis identified latent classes for the trajectories of maximum drinks, and then logistic regression analyses highlighted variables that best predicted class membership.ResultsFour latent classes were found, including Class 1 (69%), with about 5 maximum drinks per occasion across time; Class 2 (15%), with about 9 drinks at baseline that increased to 18 across time; Class 3 (10%), who began with a maximum of 18 drinks per occasion but decreased to 9 over time; and Class 4 (6%), with a maximum of about 22 drinks across time. The most consistent predictors of higher drinking classes were female sex, a low baseline level of response to alcohol, externalizing characteristics, prior alcohol and tobacco use, and heavier drinking peers.ConclusionsFour trajectory classes were observed and were best predicted by a combination of items that reflected demography, substance use, level of response and externalizing phenotypes, and baseline environment and attitudes.