Five-Year Outcomes of a School-Based Personality-Focused Prevention Program on Adolescent Substance Use Disorder: A Cluster Randomized Trial.

Objective: Rates of substance use disorders (SUDs) remain significantly above national targets for health promotion and disease prevention in Canada and the United States. This study investigated the 5-year SUD outcomes following a selective drug and alcohol prevention program targeting personality risk factors for adolescent substance misuse.

Methods: The Co-Venture trial is a cluster randomized trial involving 31 high schools in the greater Montreal area that agreed to conduct annual health behavior surveys for 5 years on the entire 7th grade cohort of assenting students enrolled at the school in 2012 or 2013.

Impulsivity behaviors and white matter mediate the relationship between genetic risk for cannabis use disorder and early cannabis use in adolescents.

Background And Aim: Cannabis use disorder (CUD) is strongly influenced by genetic factors; however the mechanisms underpinning this association are not well understood. This study investigated whether a polygenic risk score (PRS) based on a genome-wide association study for CUD in adults predicts cannabis use in adolescents and whether the association can be explained by inter-individual variation in structural properties of brain white matter or risk-taking behaviors.

Design And Setting: Longitudinal and cross-sectional analyses using data from the IMAGEN cohort, a European longitudinal study integrating genetic, neuroimaging and behavioral measures.

Resting-state alterations in emotion salience and default-mode network connectivity in atypical trajectories of psychotic-like experiences.

Social cognition is commonly altered in people with psychosis. Two main brain networks have been implicated: the default-mode network (DMN), which is associated with socio-cognitive processing, and the salience network (SN) associated with socio-affective processing. Disturbances to the resting-state functional connectivity of these networks have been identified in schizophrenia and high-risk individuals, but there have been no studies in adolescents displaying distinct trajectories of subclinical psychotic-like experiences (PLEs).

Mega-analysis of the brain-age gap in substance use disorder: An ENIGMA Addiction working group study.

Background And Aims: The brain age gap (BAG), calculated as the difference between a machine learning model-based predicted brain age and chronological age, has been increasingly investigated in psychiatric disorders. Tobacco and alcohol use are associated with increased BAG; however, no studies have compared global and regional BAG across substances other than alcohol and tobacco. This study aimed to compare global and regional estimates of brain age in individuals with substance use disorders and healthy controls.

Brain-age prediction: Systematic evaluation of site effects, and sample age range and size.

Structural neuroimaging data have been used to compute an estimate of the biological age of the brain (brain-age) which has been associated with other biologically and behaviorally meaningful measures of brain development and aging. The ongoing research interest in brain-age has highlighted the need for robust and publicly available brain-age models pre-trained on data from large samples of healthy individuals. To address this need we have previously released a developmental brain-age model.