Associations between alcohol use and sex-specific maturation of subcortical gray matter morphometry from adolescence to adulthood: Replication across two longitudinal samples.

Subcortical brain morphometry matures across adolescence and young adulthood, a time when many youth engage in escalating levels of alcohol use. Initial cross-sectional studies have shown alcohol use is associated with altered subcortical morphometry. However, longitudinal evidence of sex-specific neuromaturation and associations with alcohol use remains limited. This project used generalized additive mixed models to examine sex-specific development of subcortical volumes and associations with recent alcohol use, using 7 longitudinal waves (n = 804, 51% female, ages 12-21 at baseline) from the National Consortium on Alcohol and Neurodevelopment in Adolescence (NCANDA). A second, independent, longitudinal dataset, with up to four waves of data (n = 467, 43% female, ages 10-18 at baseline), was used to assess replicability. Significant, replicable non-linear normative volumetric changes with age were evident in the caudate, putamen, thalamus, pallidum, amygdala and hippocampus. Significant, replicable negative associations between subcortical volume and alcohol use were found in the hippocampus in all youth, and the caudate and thalamus in female but not male youth, with significant interactions present in the caudate, thalamus and putamen. Findings suggest a structural vulnerability to alcohol use, or a predisposition to drink alcohol based on brain structure, with female youth potentially showing heightened risk, compared to male youth.

Alcohol-induced changes in mesostriatal resting-state functional connectivity are linked to sensation seeking in young adults.

BACKGROUND: Studies in animals and humans suggest that greater levels of sensation seeking and alcohol use are related to individual differences in drug-induced dopamine release. However, it remains unclear whether drug-induced alterations in the functional synchrony between mesostriatal regions are related to sensation seeking and alcohol use. METHODS: In this within-subject masked-design study, 21-year-old participants (n = 34) underwent functional magnetic resonance imaging to measure ventral tegmental area (VTA) resting-state functional connectivity to the striatum after receiving alcohol (target blood alcohol concentration 0.08 g/dL) or placebo. Participants also completed the UPPS-P Impulsive Behavior Scale to assess sensation seeking, the Young Adult Alcohol Consequences Questionnaire, and self-reported patterns of alcohol and drug use. RESULTS: Voxel-wise analyses within the striatum demonstrated that during the alcohol condition (compared with placebo) young adults had less connectivity between the VTA and bilateral caudate (p < 0.05 corrected). However, young adults exhibiting smaller alcohol-induced decreases or increases in VTA-left caudate connectivity reported greater sensation seeking. CONCLUSION: These findings provide novel information about how acute alcohol impacts resting-state connectivity, an effect that may be driven by the complex pre and postsynaptic effects of alcohol on various neurotransmitters including dopamine. Further, alcohol-induced differences in VTA connectivity represent a plausible mechanistic substrate underlying sensation seeking.

Prediction of suicidal ideation and attempt in 9 and 10 year-old children using transdiagnostic risk features.

The objective of the current study was to build predictive models for suicidal ideation in a sample of children aged 9-10 using features previously implicated in risk among older adolescent and adult populations. This case-control analysis utilized baseline data from the Adolescent Brain and Cognitive Development (ABCD) Study, collected from 21 research sites across the United States (N = 11,369). Several regression and ensemble learning models were compared on their ability to classify individuals with suicidal ideation and/or attempt from healthy controls, as assessed by the Kiddie Schedule for Affective Disorders and Schizophrenia-Present and Lifetime Version. When comparing control participants (mean age: 9.92±0.62 years; 4944 girls [49%]) to participants with suicidal ideation (mean age: 9.89±0.63 years; 451 girls [40%]), both logistic regression with feature selection and elastic net without feature selection predicted suicidal ideation with an AUC of 0.70 (CI 95%: 0.70-0.71). The random forest with feature selection trained to predict suicidal ideation predicted a holdout set of children with a history of suicidal ideation and attempt (mean age: 9.96±0.62 years; 79 girls [41%]) from controls with an AUC of 0.77 (CI 95%: 0.76-0.77). Important features from these models included feelings of loneliness and worthlessness, impulsivity, prodromal psychosis symptoms, and behavioral problems. This investigation provided an unprecedented opportunity to identify suicide risk in youth. The use of machine learning to examine a large number of predictors spanning a variety of domains provides novel insight into transdiagnostic factors important for risk classification.