Susan F. Tapert

Adolescence involves pronounced changes in sleep timing and duration that have been linked to executive functioning, impulsivity, and risk behaviors, yet evidence for generalizable sleep - self-regulation associations remains limited. We used regularized canonical correlation analysis to examine multivariate relationships between sleep and self-regulation across two independent cohorts. In the Adolescent Brain Cognitive Development study (n = 11,143), later chronotype and shorter sleep duration were associated with higher impulsivity, particularly urgency and deficits in planning and perseverance (r = 0.21, permutation p < 0.001), with minimal contribution from delay discounting. Social jetlag showed weak loadings. In the National Consortium on Alcohol and Neurodevelopment in Adolescence cohort (n = 831), only one canonical function was statistically significant (r = 0.15, p = 0.011), characterized by later chronotype and greater social jetlag, with minimal contribution from sleep duration and primary loadings on impulsivity-related measures. Applying the ABCD-derived sleep - self-regulation pattern to NCANDA produced a small but nonzero association, driven primarily by social jetlag and delayed sleep timing, with minimal influence of sleep duration. These findings provide multivariate evidence linking delayed sleep timing and circadian misalignment to adolescent self-regulation, though effect sizes attenuate across cohorts. Longitudinal work is needed to clarify predictive pathways and inform sleep-focused interventions during this vulnerable developmental period.

Neurodevelopmental models implicate dopaminergic and neurocognitive maturation in adolescent risk-taking, yet their joint contribution to substance use trajectories in humans remains unclear. We examined basal ganglia tissue iron, a marker of dopamine-related neurobiology, alongside impulsivity and inhibitory control in relation to longitudinal substance use patterns in the NCANDA-A cohort (N = 802; ages 12–30; 6,078 visits). Growth Mixture Models identified four trajectories: no/low use (30% of participants), youth peak (26%), adolescent increasing (17%), and adult increasing (26%). Substance use, inhibitory control, and tissue iron increased with age, while impulsivity declined. Greater substance use was associated with heightened impulsivity, low inhibitory control, and low tissue iron, prominently in early adolescence among youth peak patterns. Trajectories were further distinguished by divergent maturation of impulsivity and tissue iron. Results suggest that developmental variation in tissue iron and neurocognition contribute to youth substance use, highlighting adolescence as a sensitive window for risk stratification and prevention.

Adolescents experience extensive neurocognitive development, with cannabis use potentially impacting developmental trajectories. Here, we comprehensively assess the influence of adolescent cannabis use onset on neurocognitive trajectories and consider how recent delta-9-tetrahydrocannabinol (THC) and cannabidiol (CBD) may influence neurocognition. We use the large, diverse longitudinal Adolescent Brain Cognitive Development (ABCD) Study dataset, combining self-reported substance use with objective toxicological tests (hair, urine, breath, oral fluid). Longitudinal mixed methods of the full cohort (n = 11,036, ages 9-17; 47% Female/53% Male) investigate time-varying cannabis onset on neurocognitive performance. Primary model covariates include sociodemographics, family history of substance use disorder, prenatal substance exposure, early psychopathology, other substance use, and nesting for participant ID, study site, and family ID. Secondarily, in participants with repeat toxicological hair testing (n = 645; 38% Female/62% Male) at ages 12-16, we consider the influence of THC v. CBD v. Controls. Primary models included false discovery rate corrections (FDR- p < .05) while secondary models were interpreted at p < .01. Cannabis group interacted with age to show altered neurocognitive trajectories across domains (immediate recall and delayed memory, processing speed, inhibitory control, visuospatial processing, language, and working memory; βs = -0.11- -0.52). Secondary models indicated hair-identified THC exposure*age predicted worse episodic memory than in Controls (β = -0.60, p = .007), with no difference between CBD exposed and Controls. Data suggest those who use cannabis show likely pre-existing better cognitive performance during late childhood, with reduced improvement or flattened trajectories over time. These neurocognitive trajectories in youth (ages 9-17) who initiate cannabis use were demonstrated after accounting for within-person change and numerous known confounds and improving accuracy in identifying cannabis use through incorporating toxicological measures. Continued monitoring of this cohort will clarify cannabinoid-cognition relationships into young adulthood, including the impact of timing of cannabis use initiation.

Methamphetamine (METH) use is highly prevalent among people with HIV (PWH) and those at risk and may contribute to overall worse health outcomes. Poorer health-related problems may be mediated by METH enhancing risky decision-making among PWH. While both METH and HIV are known to have overlapping and deleterious effects on the frontostriatal neural circuitry essential for decision-making, few studies have examined their combined effects. Eighty-eight participants stratified by HIV and a history of METH use disorder completed a risky decision-making paradigm, which involved choosing among safe (20¢) and risky (40¢/80¢ win or loss) choices, during blood-oxygen level-dependent functional magnetic resonance imaging (fMRI). Linear mixed-effects models were used to assess voxelwise differences in group and choice constrained to the anterior cingulate cortex (ACC), insula, and striatum. Despite similar choice behavior across groups, PWH and a history of METH use disorder had greater activation of the ACC and caudate than either condition alone (i.e., HIV+/METH− and HIV−/METH+), which was similar to seronegative, non-using controls. Within the ACC in particular, these differences may have been driven by safe choices. A longer estimated duration of HIV infection was associated with greater ACC activation to risky choices for PWH regardless of METH use history. These findings suggest that PWH and a history of METH use disorder may exhibit compensatory activation of regions associated with decision-making in the context of rewards and that the effects of HIV and past METH use might not be additive.

Importance: Despite the importance placed on physical activity throughout childhood to adolescence, the extent to which physical activity is associated with trajectories of brain structure development remains unclear.Objective: To investigate the associations between physical activity on volumetric gray matter morphometry throughout adolescence.Design: The Adolescent Brain Cognitive Development (ABCD) Study is a cohort-based longitudinal design of over 11,880 participants from ages 9-10 followed for 10 years.Setting: Multi-site study design including 21 U.S.-based sites within the continental United States.Participants: 9,291 participants (ages 9-17; 49% female; 55% white/non-Hispanic) with usable neuroimaging and sports activity involvement questionnaire data were analyzed across four longitudinal follow-up visits (i.e., year-0 to year-6).Exposures: Past-year amount of physical activity, from sports and activities, converted to a common metric (metabolic equivalent of task; METs) across late childhood to mid-adolescence.Main Outcomes and Measures: Longitudinal linear mixed effect models evaluated brain structure measured across 84 gray matter volumetric regions-of-interest. The interaction between METs and age was the primary effect investigated; non-linear fits of age were evaluated. Covariates included: total intracranial volume, sex, household income, body mass index, pubertal stage, MRI software version, genetic principal components, and random effects of participant identification, family identification, and MRI serial number.Results: Across 24,929 total observations, participants engaged in an average of 13,858 past-year MET-minutes (i.e., 266 MET-minutes/week) from sports/activities with stepwise increases across time. A quadratic effect of age resulted in optimal model fit. Linear mixed-effect regressions identified significant effects of total past-year METs*age-squared across 23 regions-of-interest with more pronounced trajectories of changes in volume observed for youth with higher past-year METs; standardized beta estimates range from -.005 to -.01 (all FDR-correct p<.05). Significant regions were predominantly frontotemporal, but also included: subcortical, parietal, occipital, and cingulate regions.Conclusions and Relevance: Findings suggest that the volume of physical activity engaged in from sports/activities is linked with brain morphological metrics throughout late childhood into adolescence. Physical activity remains an important modifiable health factor that influences neurodevelopmental trajectories.

Objectives. To detail the prevalence of substance use in the Adolescent Brain Cognitive Development (ABCD) Study from ages 9-17.Methods. 11,880 youth across the U.S., recruited at ages 9-10, completed annual study visits from September 2016 to January 2024. ABCD 6.0 data release comprises baseline to year-6 data. Lifetime and annual substance use, sex differences, and polysubstance use were analyzed.Results. Substance use steadily increased with age; 38% lifetime use by age 16. Alcohol, cannabis, and nicotine remain the most reported. Boys reported more use prior to age 12; girls reported more from ages 13 onward. Polysubstance use analyses detail the most shared substance use.Conclusions. Prevalence rates mirror other national surveys showing increases in reported use across early adolescence, with alcohol, cannabis, and nicotine being the most used substances. Unique sex differences and polysubstance use rates are contextualized alongside prior national reports of these behaviors in the U.S.Policy Implications. Adolescent substance use is a continued public health concern. Understanding the latest prevalences, specifically in a well-phenotyped cohort, guides knowledge of rates for continued analysis of antecedents and sequelae of use on health.

Aim: Develop brief, practical risk indexes for identifying children with no/minimal history of substance use who are at risk of high-risk substance use patterns during adolescence.Design: Observational, longitudinal cohort study (ABCD Study).Setting: 21 study sites across the United States.Participants: Community-based sample of 8,055 youth recruited at ages 9-10 years old (49% female, 20% Hispanic; 15% Black).Measurements: To create the risk indexes, we drew items from a comprehensive baseline assessment when youth were 9-10 years old that measured all major risk factors for adolescent substance use. We then measured substance use outcomes at annual follow-up assessments occurring annually through age 15-16 years old. We used a training subsample (n=5,555) to choose which items should be on the risk indexes and fit a risk algorithm, then evaluated the predictive performance of each risk score in holdout data (n=2,500).Findings: The parent- and youth-report risk indexes were 8 items long, each asking questions about multiple risk factors for future substance use. The risk score based on parent report at ages 9-10 predicted several clinically meaningful outcomes during early-to-mid adolescence: being treated for a substance use problem (AUC=0.84), meeting DSM 5 criteria for a substance use disorder (AUC=0.68), experiencing multiple negative consequences of use (AUC=0.64) and establishing monthly use before one’s 15th birthday (AUC=0.68) (ps<.001). Children in the top 10% of the parent-report risk score were 2.1-3.1x times more likely than the base rates to go on to display high-risk substance use outcomes during adolescence. The risk scores significantly predicted alcohol, cannabis, and nicotine use outcomes, in addition to general substance use. Risk scores based on youth report were also significant predictors of substance use outcomes, but their performance was weaker (mean AUC=0.65, vs. 0.68 for parent report).Conclusions: 8-item parent- and youth-reported risk indexes a identify children at markedly elevated risk of clinically concerning substance use outcomes. These risk indexes compare favorably with existing tools and might prove useful for triage, monitoring, or targeted prevention. The next step is to perform external validations in new samples.