Non-linear development of EEG coherence in adolescents and young adults shown by the analysis of neurophysiological trajectories and their covariance.

To contribute to the understanding of changes in the factors governing the development of neural connectivity, the developmental structure of EEG coherence in adolescents and young adults was analyzed using the means, variances, and covariances of high alpha frequency band coherence measures from a set of 27 coherence pairs obtained from a sample of 1426 participants from the COGA study with 5006 observations over ages 12 through 31. Means and covariances were calculated at 96 age centers by a LOESS method. In the current study, trajectories of covariance matrices considered as individual units were determined by tensorial analysis: calculation of Riemannian geodesic (non-Euclidean) distances between matrices and application of both linear and non-linear dimension reduction techniques to these distances. Results were evaluated by bootstrap methods. Mean coherence trajectories for males and females were very similar, showing a steady upward trend from ages 12 to 20 which diminishes gradually from 20 to 25 and reaches stability from 25 to 31. In contrast, the individual covariance trajectories of males and female differed, with the male covariance levels becoming greater than that of females during the developmental process. Tensorial determination of the distances from the initial covariance matrix of subsequent covariance matrices to age 20 had the same trajectory as the mean coherence values. Tensorial determination of the trajectories of the covariance matrices of males and females based on their all pairs geodesic distances revealed a non-linear pattern in the multi-dimensional space of each of the trajectories: A steady increase in one dimension is accompanied by deviations from it peaking at age 20 which have both transient and lasting effects. There is a precise temporal parallelism of this pattern of covariance in males and females, while there is a consistent distance between the male and female covariance structures throughout the developmental process. Between region differences (anterior-posterior) within each sex are greater than between sex differences within regions. Examining development using multiple methods provides unique insight into the developmental process.

Prediction of brain age in individuals with and at risk for alcohol use disorder using brain morphological features.

Brain age measures predicted from structural and functional brain features are increasingly being used to understand brain integrity, disorders, and health. While there is a vast literature showing aberrations in both structural and functional brain measures in individuals with and at risk for alcohol use disorder (AUD), few studies have investigated brain age in these groups. The current study examines brain age measures predicted using brain morphological features, such as cortical thickness and brain volume, in individuals with a lifetime diagnosis of AUD as well as in those at higher risk to develop AUD from families with multiple members affected with AUD (i.e., higher family history density (FHD) scores). The AUD dataset included a group of 30 adult males (mean age = 41.25 years) with a lifetime diagnosis of AUD and currently abstinent and a group of 30 male controls (mean age = 27.24 years) without any history of AUD. A second dataset of young adults who were categorized based on their FHD scores comprised a group of 40 individuals (20 males) with high FHD of AUD (mean age = 25.33 years) and a group of 31 individuals (18 males) with low FHD (mean age = 25.47 years). Brain age was predicted using 187 brain morphological features of cortical thickness and brain volume in an XGBoost regression model; a bias-correction procedure was applied to the predicted brain age. Results showed that both AUD and high FHD individuals showed an increase of 1.70 and 0.09 years (1.08 months), respectively, in their brain age relative to their chronological age, suggesting accelerated brain aging in AUD and risk for AUD. Increased brain age was associated with poor performance on neurocognitive tests of executive functioning in both AUD and high FHD individuals, indicating that brain age can also serve as a proxy for cognitive functioning and brain health. These findings on brain aging in these groups may have important implications for the prevention and treatment of AUD and ensuing cognitive decline.

Examining associations between genetic and neural risk for externalizing behaviors in adolescence and early adulthood.

BACKGROUND: Researchers have identified genetic and neural risk factors for externalizing behaviors. However, it has not yet been determined if genetic liability is conferred in part through associations with more proximal neurophysiological risk markers. METHODS: Participants from the Collaborative Study on the Genetics of Alcoholism, a large, family-based study of alcohol use disorders were genotyped and polygenic scores for externalizing (EXT PGS) were calculated. Associations with target P3 amplitude from a visual oddball task (P3) and broad endorsement of externalizing behaviors (indexed via self-report of alcohol and cannabis use, and antisocial behavior) were assessed in participants of European (EA; N = 2851) and African ancestry (AA; N = 1402). Analyses were also stratified by age (adolescents, age 12-17 and young adults, age 18-32). RESULTS: The EXT PGS was significantly associated with higher levels of externalizing behaviors among EA adolescents and young adults as well as AA young adults. P3 was inversely associated with externalizing behaviors among EA young adults. EXT PGS was not significantly associated with P3 amplitude and therefore, there was no evidence that P3 amplitude indirectly accounted for the association between EXT PGS and externalizing behaviors. CONCLUSIONS: Both the EXT PGS and P3 amplitude were significantly associated with externalizing behaviors among EA young adults. However, these associations with externalizing behaviors appear to be independent of each other, suggesting that they may index different facets of externalizing.

Genomic risk for post-traumatic stress disorder in families densely affected with alcohol use disorders.

Recent genome-wide association studies (GWAS) have identified genetic markers of post-traumatic stress disorder (PTSD) in civilian and military populations. However, studies have yet to examine the genetics of PTSD while factoring in risk for alcohol dependence, which commonly co-occur. We examined genome-wide associations for DSM-IV PTSD among 4,978 trauma-exposed participants (31% with alcohol dependence, 50% female, 30% African ancestry) from the Collaborative Study on the Genetics of Alcoholism (COGA). We also examined associations of polygenic risk scores (PRS) derived from the Psychiatric Genomics Consortium (PGC)-PTSD Freeze 2 (N = 3533) and Million Veterans Program GWAS of PTSD (N = 5200) with PTSD and substance dependence in COGA, and moderating effects of sex and alcohol dependence. 7.3% of COGA participants met criteria for PTSD, with higher rates in females (10.1%) and those with alcohol dependence (12.3%). No independent loci met genome-wide significance in the PTSD meta-analysis of European (EA) and African ancestry (AA) participants. The PGC-PTSD PRS was associated with increased risk for PTSD (B = 0.126, p < 0.001), alcohol dependence (B = 0.231, p < 0.001), and cocaine dependence (B = 0.086, p < 0.01) in EA individuals. A significant interaction was observed, such that EA individuals with alcohol dependence and higher polygenic risk for PTSD were more likely to have PTSD (B = 0.090, p < 0.01) than those without alcohol dependence. These results further support the importance of examining substance dependence, specifically alcohol dependence, and PTSD together when investigating genetic influence on these disorders.

Clinical, genomic, and neurophysiological correlates of lifetime suicide attempts among individuals with alcohol dependence.

Research has identified clinical, genomic, and neurophysiological markers associated with suicide attempts (SA) among individuals with psychiatric illness. However, there is limited research among those with an alcohol use disorder, despite their disproportionately higher rates of SA. We examined lifetime SA in 4,068 individuals with DSM-IV alcohol dependence from the Collaborative Study on the Genetics of Alcoholism (23% lifetime suicide attempt; 53% female; 17% Admixed African American ancestries; mean age: 38). We 1) explored clinical risk factors associated with SA, 2) conducted a genome-wide association study of SA, 3) examined whether individuals with a SA had elevated polygenic scores for comorbid psychiatric conditions (e.g., alcohol use disorders, lifetime suicide attempt, and depression), and 4) explored differences in electroencephalogram neural functional connectivity between those with and without a SA. One gene-based finding emerged, RFX3 (Regulatory Factor X, located on 9p24.2) which had supporting evidence in prior research of SA among individuals with major depression. Only the polygenic score for suicide attempts was associated with reporting a suicide attempt (OR = 1.20, 95% CI = 1.06, 1.37). Lastly, we observed decreased right hemispheric frontal-parietal theta and decreased interhemispheric temporal-parietal alpha electroencephalogram resting-state coherences among those participants who reported a SA relative to those who did not, but differences were small. Overall, individuals with alcohol dependence who report SA appear to experience a variety of severe comorbidities and elevated polygenic risk for SA. Our results demonstrate the need to further investigate suicide attempts in the presence of substance use disorders.

Predicting Alcohol-Related Memory Problems in Older Adults: A Machine Learning Study with Multi-Domain Features.

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 (the memory group) were compared with a matched control group who did not have memory problems. The random forests model identified specific features from each domain that contributed to the classification of the memory group vs. the control group (AUC = 88.29%). Specifically, individuals from the memory group manifested a predominant pattern of hyperconnectivity across the default mode network regions except for some connections involving the 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 five years, such as health problems, past negative experiences, withdrawal symptoms, and the largest number of drinks in a day during the past twelve 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 data collected ~18 years ago, together with personality, life experiences, polygenic risk, and alcohol consumption and related consequences, to predict the alcohol-related memory problems that arise in later life.

Associations of parent-adolescent closeness with P3 amplitude, frontal theta, and binge drinking among offspring with high risk for alcohol use disorder.

BACKGROUND: Parents impact their offspring's brain development, neurocognitive function, risk, and resilience for alcohol use disorder (AUD) via both genetic and socio-environmental factors. Individuals with AUD and their unaffected children manifest low parietal P3 amplitude and low frontal theta (FT) power, reflecting heritable neurocognitive deficits associated with AUD. Likewise, children who experience poor parenting tend to have atypical brain development and greater rates of alcohol problems. Conversely, positive parenting can be protective and critical for normative development of self-regulation, neurocognitive functioning and the neurobiological systems subserving them. Yet, the role of positive parenting in resiliency toward AUD is understudied and its association with neurocognitive functioning and behavioral vulnerability to AUD among high-risk offspring is less known. Using data from the Collaborative Study on the Genetics of Alcoholism prospective cohort (N = 1256, mean age [SD] = 19.25 [1.88]), we investigated the associations of closeness with mother and father during adolescence with offspring P3 amplitude, FT power, and binge drinking among high-risk offspring. METHODS: Self-reported closeness with mother and father between ages 12 and 17 and binge drinking were assessed using the Semi-Structured Assessment for the Genetics of Alcoholism. P3 amplitude and FT power were assessed in response to target stimuli using a Visual Oddball Task. RESULTS: Multivariate multiple regression analyses showed that closeness with father was associated with larger P3 amplitude (p = 0.002) and higher FT power (p = 0.01). Closeness with mother was associated with less binge drinking (p = 0.003). Among male offspring, closeness with father was associated with larger P3 amplitude, but among female offspring, closeness with mother was associated with less binge drinking. These associations remained statistically significant with father's and mothers' AUD symptoms, socioeconomic status, and offspring impulsivity in the model. CONCLUSIONS: Among high-risk offspring, closeness with parents during adolescence may promote resilience for developing AUD and related neurocognitive deficits albeit with important sex differences.

Differentiating Individuals with and without Alcohol Use Disorder Using Resting-State fMRI Functional Connectivity of Reward Network, Neuropsychological Performance, and Impulsivity Measures.

Individuals with alcohol use disorder (AUD) may manifest an array of neural and behavioral abnormalities, including altered brain networks, impaired neurocognitive functioning, and heightened impulsivity. Using multidomain measures, the current study aimed to identify specific features that can differentiate individuals with AUD from healthy controls (CTL), utilizing a random forests (RF) classification model. Features included fMRI-based resting-state functional connectivity (rsFC) across the reward network, neuropsychological task performance, and behavioral impulsivity scores, collected from thirty abstinent adult males with prior history of AUD and thirty CTL individuals without a history of AUD. It was found that the RF model achieved a classification accuracy of 86.67% (AUC = 93%) and identified key features of FC and impulsivity that significantly contributed to classifying AUD from CTL individuals. Impulsivity scores were the topmost predictors, followed by twelve rsFC features involving seventeen key reward regions in the brain, such as the ventral tegmental area, nucleus accumbens, anterior insula, anterior cingulate cortex, and other cortical and subcortical structures. Individuals with AUD manifested significant differences in impulsivity and alterations in functional connectivity relative to controls. Specifically, AUD showed heightened impulsivity and hypoconnectivity in nine connections across 13 regions and hyperconnectivity in three connections involving six regions. Relative to controls, visuo-spatial short-term working memory was also found to be impaired in AUD. In conclusion, specific multidomain features of brain connectivity, impulsivity, and neuropsychological performance can be used in a machine learning framework to effectively classify AUD individuals from healthy controls.

Deriving a Measure of Social Recovery Capital From the Important People and Activities Instrument: Construction and Psychometric Properties.

AIM: This study presents a measure of Social Recovery Capital (SRC) derived from the Important People and Activities instrument (IPA). METHODS: The sample comprised young adults who participated in the Collaborative Study on the Genetics of Alcoholism, a high-risk family study of alcohol use disorder (N = 2472). Exploratory and confirmatory factor analysis identified influential items and factor structure, adjusting for family relatedness. The final scale was tested for reliability and validity. RESULTS: Factor analysis retained 10 items loading on three factors (Network Abstinence Behaviors, Basic Network Structure and Network Importance) that together explained 42% of the variance in SRC. The total model showed adequate fit (Comparative Fit Index = 0.95; Tucker Lewis Index = 0.93; Root Mean Square Error of Approximation = 0.06; Standardized Root Mean Squared Residual = 0.05) and acceptable reliability (α = 0.60; McDonald's ω = 0.73) and correlated with validation measures mostly in the weak to moderate range. Due to variable factor scores for reliability and validity, we only recommend using the total score. CONCLUSION: The SRC-IPA is a novel measure of SRC derived from the IPA that captures social network data and has applications in research and clinical work. Secondary data analyses using the SRC-IPA in studies that collected the IPA can further demonstrate the interaction of SRC with a wide variety of clinical indicators and demographic characteristics, making it a valuable addition to other measures of SRC.

Item-Level Genome-Wide Association Study of the Alcohol Use Disorders Identification Test in Three Population-Based Cohorts.

OBJECTIVE: Genome-wide association studies (GWASs) of the Alcohol Use Disorders Identification Test (AUDIT), a 10-item screen for alcohol use disorder (AUD), have elucidated novel loci for alcohol consumption and misuse. However, these studies also revealed that GWASs can be influenced by numerous biases (e.g., measurement error, selection bias), which may have led to inconsistent genetic correlations between alcohol involvement and AUD, as well as paradoxically negative genetic correlations between alcohol involvement and psychiatric disorders and/or medical conditions. The authors used genomic structural equation modeling to elucidate the genetics of alcohol consumption and problematic consequences of alcohol use as measured by AUDIT. METHODS: To explore these unexpected differences in genetic correlations, the authors conducted the first item-level and the largest GWAS of AUDIT items (N=160,824) and applied a multivariate framework to mitigate previous biases. RESULTS: The authors identified novel patterns of similarity (and dissimilarity) among the AUDIT items and found evidence of a correlated two-factor structure at the genetic level ("consumption" and "problems," rg=0.80). Moreover, by applying empirically derived weights to each of the AUDIT items, the authors constructed an aggregate measure of alcohol consumption that was strongly associated with alcohol dependence (rg=0.67), moderately associated with several other psychiatric disorders, and no longer positively associated with health and positive socioeconomic outcomes. Lastly, by conducting polygenic analyses in three independent cohorts that differed in their ascertainment and prevalence of AUD, the authors identified novel genetic associations between alcohol consumption, alcohol misuse, and health. CONCLUSIONS: This work further emphasizes the value of AUDIT for both clinical and genetic studies of AUD and the importance of using multivariate methods to study genetic associations that are more closely related to AUD.

Predicting alcohol use disorder remission: a longitudinal multimodal multi-featured machine learning approach.

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.

Predicting risk for Alcohol Use Disorder using longitudinal data with multimodal biomarkers and family history: a machine learning study.

Predictive models have succeeded in distinguishing between individuals with Alcohol use Disorder (AUD) and controls. However, predictive models identifying who is prone to develop AUD and the biomarkers indicating a predisposition to AUD are still unclear. Our sample (n = 656) included offspring and non-offspring of European American (EA) and African American (AA) ancestry from the Collaborative Study of the Genetics of Alcoholism (COGA) who were recruited as early as age 12 and were unaffected at first assessment and reassessed years later as AUD (DSM-5) (n = 328) or unaffected (n = 328). Machine learning analysis was performed for 220 EEG measures, 149 alcohol-related single nucleotide polymorphisms (SNPs) from a recent large Genome-wide Association Study (GWAS) of alcohol use/misuse and two family history (mother DSM-5 AUD and father DSM-5 AUD) features using supervised, Linear Support Vector Machine (SVM) classifier to test which features assessed before developing AUD predict those who go on to develop AUD. Age, gender, and ancestry stratified analyses were performed. Results indicate significant and higher accuracy rates for the AA compared with the EA prediction models and a higher model accuracy trend among females compared with males for both ancestries. Combined EEG and SNP features model outperformed models based on only EEG features or only SNP features for both EA and AA samples. This multidimensional superiority was confirmed in a follow-up analysis in the AA age groups (12-15, 16-19, 20-30) and EA age group (16-19). In both ancestry samples, the youngest age group achieved higher accuracy score than the two other older age groups. Maternal AUD increased the model's accuracy in both ancestries' samples. Several discriminative EEG measures and SNPs features were identified, including lower posterior gamma, higher slow wave connectivity (delta, theta, alpha), higher frontal gamma ratio, higher beta correlation in the parietal area, and 5 SNPs: rs4780836, rs2605140, rs11690265, rs692854, and rs13380649. Results highlight the significance of sampling uniformity followed by stratified (e.g., ancestry, gender, developmental period) analysis, and wider selection of features, to generate better prediction scores allowing a more accurate estimation of AUD development.

A genome-wide association study of interhemispheric theta EEG coherence: implications for neural connectivity and alcohol use behavior.

Aberrant connectivity of large-scale brain networks has been observed among individuals with alcohol use disorders (AUDs) as well as in those at risk, suggesting deficits in neural communication between brain regions in the liability to develop AUD. Electroencephalographical (EEG) coherence, which measures the degree of synchrony between brain regions, may be a useful measure of connectivity patterns in neural networks for studying the genetics of AUD. In 8810 individuals (6644 of European and 2166 of African ancestry) from the Collaborative Study on the Genetics of Alcoholism (COGA), we performed a Multi-Trait Analyses of genome-wide association studies (MTAG) on parietal resting-state theta (3-7 Hz) EEG coherence, which previously have been associated with AUD. We also examined developmental effects of GWAS findings on trajectories of neural connectivity in a longitudinal subsample of 2316 adolescent/young adult offspring from COGA families (ages 12-30) and examined the functional and clinical significance of GWAS variants. Six correlated single nucleotide polymorphisms located in a brain-expressed lincRNA (ENSG00000266213) on chromosome 18q23 were associated with posterior interhemispheric low theta EEG coherence (3-5 Hz). These same variants were also associated with alcohol use behavior and posterior corpus callosum volume, both in a subset of COGA and in the UK Biobank. Analyses in the subsample of COGA offspring indicated that the association of rs12954372 with low theta EEG coherence occurred only in females, most prominently between ages 25 and 30 (p < 2 × 10-9). Converging data provide support for the role of genetic variants on chromosome 18q23 in regulating neural connectivity and alcohol use behavior, potentially via dysregulated myelination. While findings were less robust, genome-wide associations were also observed with rs151174000 and parieto-frontal low theta coherence, rs14429078 and parieto-occipital interhemispheric high theta coherence, and rs116445911 with centro-parietal low theta coherence. These novel genetic findings highlight the utility of the endophenotype approach in enhancing our understanding of mechanisms underlying addiction susceptibility.

Alcohol-Related, Drug-Related, and Non-Substance-Related Aggression: 3 Facets of a Single Construct or 3 Distinct Constructs?

BACKGROUND: Aggression often occurs alongside alcohol and drug misuse. However, it is not clear whether the latent and manifest relations among alcohol-related, drug-related, and non-substance-related aggression are separate manifestations of a single construct or instead are 3 distinct constructs. METHODS: To examine these associations, we conducted a preregistered analysis of 13,490 participants in the Collaborative Study on the Genetics of Alcoholism. In a structured interview, participants reported their lifetime perpetration of these 3 aggression phenotypes. RESULTS: The data were better fit by a model that treated these aggression phenotypes as 3 distinct latent factors, as compared to models in which the items all loaded onto 1 ("general") or 2 ("substance-related" and "non-substance-related") aggression factors. This 3-factor model fit better for men than women. Subsequent exploratory analyses then showed that among these 3 factors, alcohol-related aggression explained the variance of overall aggression better than the other 2 factors. CONCLUSIONS: Our findings suggest that these 3 forms of aggression are distinct phenotypes (especially among men). Yet, people's alcohol-related aggression can accurately characterize their overall aggressive tendencies across these domains. Future research will benefit from articulating the unique and shared pathways and risk factors underlying each of these facets of aggression.

Random Forest Classification of Alcohol Use Disorder Using EEG Source Functional Connectivity, Neuropsychological Functioning, and Impulsivity Measures.

: Individuals with alcohol use disorder (AUD) manifest a variety of impairments that can be attributed to alterations in specific brain networks. The current study aims to identify features of EEG-based functional connectivity, neuropsychological performance, and impulsivity that can classify individuals with AUD (N = 30) from unaffected controls (CTL, N = 30) using random forest classification. The features included were: (i) EEG source functional connectivity (FC) of the default mode network (DMN) derived using eLORETA algorithm, (ii) neuropsychological scores from the Tower of London test (TOLT) and the visual span test (VST), and (iii) impulsivity factors from the Barratt impulsiveness scale (BIS). The random forest model achieved a classification accuracy of 80% and identified 29 FC connections (among 66 connections per frequency band), 3 neuropsychological variables from VST (total number of correctly performed trials in forward and backward sequences and average time for correct trials in forward sequence) and all four impulsivity scores (motor, non-planning, attentional, and total) as significantly contributing to classifying individuals as either AUD or CTL. Although there was a significant age difference between the groups, most of the top variables that contributed to the classification were not significantly correlated with age. The AUD group showed a predominant pattern of hyperconnectivity among 25 of 29 significant connections, indicating aberrant network functioning during resting state suggestive of neural hyperexcitability and impulsivity. Further, parahippocampal hyperconnectivity with other DMN regions was identified as a major hub region dysregulated in AUD (13 connections overall), possibly due to neural damage from chronic drinking, which may give rise to cognitive impairments, including memory deficits and blackouts. Furthermore, hypoconnectivity observed in four connections (prefrontal nodes connecting posterior right-hemispheric regions) may indicate a weaker or fractured prefrontal connectivity with other regions, which may be related to impaired higher cognitive functions. The AUD group also showed poorer memory performance on the VST task and increased impulsivity in all factors compared to controls. Features from all three domains had significant associations with one another. These results indicate that dysregulated neural connectivity across the DMN regions, especially relating to hyperconnected parahippocampal hub as well as hypoconnected prefrontal hub, may potentially represent neurophysiological biomarkers of AUD, while poor visual memory performance and heightened impulsivity may serve as cognitive-behavioral indices of AUD.

Random Forest Classification of Alcohol Use Disorder Using fMRI Functional Connectivity, Neuropsychological Functioning, and Impulsivity Measures.

Individuals with alcohol use disorder (AUD) are known to manifest a variety of neurocognitive impairments that can be attributed to alterations in specific brain networks. The current study aims to identify specific features of brain connectivity, neuropsychological performance, and impulsivity traits that can classify adult males with AUD (n = 30) from healthy controls (CTL, n = 30) using the Random Forest (RF) classification method. The predictor variables were: (i) fMRI-based within-network functional connectivity (FC) of the Default Mode Network (DMN), (ii) neuropsychological scores from the Tower of London Test (TOLT), and the Visual Span Test (VST), and (iii) impulsivity factors from the Barratt Impulsiveness Scale (BIS). The RF model, with a classification accuracy of 76.67%, identified fourteen DMN connections, two neuropsychological variables (memory span and total correct scores of the forward condition of the VST), and all impulsivity factors as significantly important for classifying participants into either the AUD or CTL group. Specifically, the AUD group manifested hyperconnectivity across the bilateral anterior cingulate cortex and the prefrontal cortex as well as between the bilateral posterior cingulate cortex and the left inferior parietal lobule, while showing hypoconnectivity in long-range anterior-posterior and interhemispheric long-range connections. Individuals with AUD also showed poorer memory performance and increased impulsivity compared to CTL individuals. Furthermore, there were significant associations among FC, impulsivity, neuropsychological performance, and AUD status. These results confirm the previous findings that alterations in specific brain networks coupled with poor neuropsychological functioning and heightened impulsivity may characterize individuals with AUD, who can be efficiently identified using classification algorithms such as Random Forest.

Density and Dichotomous Family History Measures of Alcohol Use Disorder as Predictors of Behavioral and Neural Phenotypes: A Comparative Study Across Gender and Race/Ethnicity.

BACKGROUND: Family history (FH) is an important risk factor for the development of alcohol use disorder (AUD). A variety of dichotomous and density measures of FH have been used to predict alcohol outcomes; yet, a systematic comparison of these FH measures is lacking. We compared 4 density and 4 commonly used dichotomous FH measures and examined variations by gender and race/ethnicity in their associations with age of onset of regular drinking, parietal P3 amplitude to visual target, and likelihood of developing AUD. METHODS: Data from the Collaborative Study on the Genetics of Alcoholism (COGA) were utilized to compute the density and dichotomous measures. Only subjects and their family members with DSM-5 AUD diagnostic information obtained through direct interviews using the Semi-Structured Assessment for the Genetics of Alcoholism (SSAGA) were included in the study. Area under receiver operating characteristic curves were used to compare the diagnostic accuracy of FH measures at classifying DSM-5 AUD diagnosis. Logistic and linear regression models were used to examine associations of FH measures with alcohol outcomes. RESULTS: Density measures had greater diagnostic accuracy at classifying AUD diagnosis, whereas dichotomous measures presented diagnostic accuracy closer to random chance. Both dichotomous and density measures were significantly associated with likelihood of AUD, early onset of regular drinking, and low parietal P3 amplitude, but density measures presented consistently more robust associations. Further, variations in these associations were observed such that among males (vs. females) and Whites (vs. Blacks), associations of alcohol outcomes with density (vs. dichotomous) measures were greater in magnitude. CONCLUSIONS: Density (vs. dichotomous) measures seem to present more robust associations with alcohol outcomes. However, associations of dichotomous and density FH measures with different alcohol outcomes (behavioral vs. neural) varied across gender and race/ethnicity. These findings have great applicability for alcohol research examining FH of AUD.

Association of Polygenic Liability for Alcohol Dependence and EEG Connectivity in Adolescence and Young Adulthood.

Differences in the connectivity of large-scale functional brain networks among individuals with alcohol use disorders (AUD), as well as those at risk for AUD, point to dysfunctional neural communication and related cognitive impairments. In this study, we examined how polygenic risk scores (PRS), derived from a recent GWAS of DSM-IV Alcohol Dependence (AD) conducted by the Psychiatric Genomics Consortium, relate to longitudinal measures of interhemispheric and intrahemispheric EEG connectivity (alpha, theta, and beta frequencies) in adolescent and young adult offspring from the Collaborative Study on the Genetics of Alcoholism (COGA) assessed between ages 12 and 31. Our findings indicate that AD PRS (p-threshold < 0.001) was associated with increased fronto-central, tempo-parietal, centro-parietal, and parietal-occipital interhemispheric theta and alpha connectivity in males only from ages 18-31 (beta coefficients ranged from 0.02-0.06, p-values ranged from 10-6-10-12), but not in females. Individuals with higher AD PRS also demonstrated more performance deficits on neuropsychological tasks (Tower of London task, visual span test) as well as increased risk for lifetime DSM-5 alcohol and opioid use disorders. We conclude that measures of neural connectivity, together with neurocognitive performance and substance use behavior, can be used to further understanding of how genetic risk variants from large GWAS of AUD may influence brain function. In addition, these data indicate the importance of examining sex and developmental effects, which otherwise may be masked. Understanding of neural mechanisms linking genetic variants emerging from GWAS to risk for AUD throughout development may help to identify specific points when neurocognitive prevention and intervention efforts may be most effective.

Early Sexual Trauma Exposure and Neural Response Inhibition in Adolescence and Young Adults: Trajectories of Frontal Theta Oscillations During a Go/No-Go Task.

OBJECTIVE: Trauma, particularly when experienced early in life, can alter neurophysiologic and behavioral development, thereby increasing risk for substance use disorders and related psychopathology. However, few studies have empirically examined trauma using well-characterized developmental samples that are followed longitudinally. METHOD: The association of assaultive, non-assaultive, and sexual assaultive experiences before 10 years of age with developmental trajectories of brain function during response inhibition was examined by measuring electrophysiologic theta and delta oscillations during no-go and go conditions in an equal probability go/no-go task. Data were drawn from the Collaborative Study of the Genetics of Alcoholism (COGA) prospective cohort, composed of offspring who were aged 12 through 22 years at enrollment from high-risk and comparison families, with follow-ups at 2-year intervals since 2004. In addition, other important predictors of neurophysiologic functioning (eg, substance use, impulsivity, and parental alcohol use disorders) were investigated. Moreover, associations of neurophysiologic functioning with alcohol and cannabis use disorder symptom counts and externalizing and internalizing psychopathology were examined. RESULTS: Individuals exposed to sexual assaultive trauma before 10 years of age had slower rates of change in developmental trajectories of no-go frontal theta during response inhibition. Importantly, effects remained significant after accounting for exposure to other traumatic exposures, such as parental history of alcohol use disorder and participants' substance use, but not measures of impulsivity. Further, slower rates of change in no-go frontal theta adolescent and young adult development were associated with increased risk for alcohol use disorder symptoms and internalizing psychopathology, but not for cannabis use disorder symptoms or externalizing psychopathology. CONCLUSION: Childhood sexual assault is associated with atypical frontal neurophysiologic development during response inhibition. This could reflect alterations in frontal lobe development, synaptic pruning, and/or cortical maturation involving neural circuits for inhibitory control. These same areas could be associated with increased risk for young adult alcohol use disorder symptoms and internalizing psychopathology. These findings support the hypothesis that changes in neurocognitive development related to early sexual trauma exposure could increase the risk for mental health and substance use problems in young adulthood.

A KCNJ6 gene polymorphism modulates theta oscillations during reward processing.

Event related oscillations (EROs) are heritable measures of neurocognitive function that have served as useful phenotype in genetic research. A recent family genome-wide association study (GWAS) by the Collaborative Study on the Genetics of Alcoholism (COGA) found that theta EROs during visual target detection were associated at genome-wide levels with several single nucleotide polymorphisms (SNPs), including a synonymous SNP, rs702859, in the KCNJ6 gene that encodes GIRK2, a G-protein inward rectifying potassium channel that regulates excitability of neuronal networks. The present study examined the effect of the KCNJ6 SNP (rs702859), previously associated with theta ERO to targets in a visual oddball task, on theta EROs during reward processing in a monetary gambling task. The participants were 1601 adolescent and young adult offspring within the age-range of 17-25years (800 males and 801 females) from high-dense alcoholism families as well as control families of the COGA prospective study. Theta ERO power (3.5-7.5Hz, 200-500ms post-stimulus) was compared across genotype groups. ERO theta power at central and parietal regions increased as a function of the minor allele (A) dose in the genotype (AA>AG>GG) in both loss and gain conditions. These findings indicate that variations in the KCNJ6 SNP influence magnitude of theta oscillations at posterior loci during the evaluation of loss and gain, reflecting a genetic influence on neuronal circuits involved in reward-processing. Increased theta power as a function of minor allele dose suggests more efficient cognitive processing in those carrying the minor allele of the KCNJ6 SNPs. Future studies are needed to determine the implications of these genetic effects on posterior theta EROs as possible "protective" factors, or as indices of delays in brain maturation (i.e., lack of frontalization).