Identifying high school risk factors that forecast heavy drinking onset in understudied young adults.

Heavy alcohol drinking is a major, preventable problem that adversely impacts the physical and mental health of US young adults. Studies seeking drinking risk factors typically focus on young adults who enrolled in 4-year residential college programs (4YCP) even though most high school graduates join the workforce, military, or community colleges. We examined 106 of these understudied young adults (USYA) and 453 4YCPs from the National Consortium on Alcohol and NeuroDevelopment in Adolescence (NCANDA) by longitudinally following their drinking patterns for 8 years from adolescence to young adulthood. All participants were no-to-low drinkers during high school. Whereas 4YCP individuals were more likely to initiate heavy drinking during college years, USYA participants did so later. Using mental health metrics recorded during high school, machine learning forecasted individual-level risk for initiating heavy drinking after leaving high school. The risk factors differed between demographically matched USYA and 4YCP individuals and between sexes. Predictors for USYA drinkers were sexual abuse, physical abuse for girls, and extraversion for boys, whereas 4YCP drinkers were predicted by the ability to recognize facial emotion and, for boys, greater openness. Thus, alcohol prevention programs need to give special consideration to those joining the workforce, military, or community colleges, who make up the majority of this age group.

Transparency and Reproducibility in the Adolescent Brain Cognitive Development (ABCD) Study.

Background: Transparency can build trust in the scientific process, but scientific findings can be undermined by poor and obscure data use and reporting practices. The purpose of this work is to report how data from the Adolescent Brain Cognitive Development (ABCD) Study has been used to date, and to provide practical recommendations on how to improve the transparency and reproducibility of findings. Methods: Articles published from 2017 to 2023 that used ABCD Study data were reviewed using more than 30 data extraction items to gather information on data use practices. Total frequencies were reported for each extraction item, along with computation of a Level of Completeness (LOC) score that represented overall endorsement of extraction items. Univariate linear regression models were used to examine the correlation between LOC scores and individual extraction items. Post hoc analysis included examination of whether LOC scores were correlated with the logged 2-year journal impact factor. Results: There were 549 full-length articles included in the main analysis. Analytic scripts were shared in 30% of full-length articles. The number of participants excluded due to missing data was reported in 60% of articles, and information on missing data for individual variables (e.g., household income) was provided in 38% of articles. A table describing the analytic sample was included in 83% of articles. A race and/or ethnicity variable was included in 78% of reviewed articles, while its inclusion was justified in only 41% of these articles. LOC scores were highly correlated with extraction items related to examination of missing data. A bottom 10% of LOC score was significantly correlated with a lower logged journal impact factor when compared to the top 10% of LOC scores (ß=-0.77, 95% -1.02, -0.51; p-value < 0.0001). Conclusion: These findings highlight opportunities for improvement in future papers using ABCD Study data to readily adapt analytic practices for better transparency and reproducibility efforts. A list of recommendations is provided to facilitate adherence in future research.

Transparency and reproducibility in the Adolescent Brain Cognitive Development (ABCD) study.

BACKGROUND: Transparency can build trust in the scientific process, but scientific findings can be undermined by poor and obscure data use and reporting practices. The purpose of this work is to report how data from the Adolescent Brain Cognitive Development (ABCD) Study has been used to date, and to provide practical recommendations on how to improve the transparency and reproducibility of findings. METHODS: Articles published from 2017 to 2023 that used ABCD Study data were reviewed using more than 30 data extraction items to gather information on data use practices. Total frequencies were reported for each extraction item, along with computation of a Level of Completeness (LOC) score that represented overall endorsement of extraction items. Univariate linear regression models were used to examine the correlation between LOC scores and individual extraction items. Post hoc analysis included examination of whether LOC scores were correlated with the logged 2-year journal impact factor. RESULTS: There were 549 full-length articles included in the main analysis. Analytic scripts were shared in 30 % of full-length articles. The number of participants excluded due to missing data was reported in 60 % of articles, and information on missing data for individual variables (e.g., household income) was provided in 38 % of articles. A table describing the analytic sample was included in 83 % of articles. A race and/or ethnicity variable was included in 78 % of reviewed articles, while its inclusion was justified in only 41 % of these articles. LOC scores were highly correlated with extraction items related to examination of missing data. A bottom 10 % of LOC score was significantly correlated with a lower logged journal impact factor when compared to the top 10 % of LOC scores (ß=-0.77, 95 % -1.02, -0.51; p-value < 0.0001). CONCLUSION: These findings highlight opportunities for improvement in future papers using ABCD Study data to readily adapt analytic practices for better transparency and reproducibility efforts. A list of recommendations is provided to facilitate adherence in future research.

A precision functional atlas of personalized network topography and probabilities.

Although the general location of functional neural networks is similar across individuals, there is vast person-to-person topographic variability. To capture this, we implemented precision brain mapping functional magnetic resonance imaging methods to establish an open-source, method-flexible set of precision functional network atlases-the Masonic Institute for the Developing Brain (MIDB) Precision Brain Atlas. This atlas is an evolving resource comprising 53,273 individual-specific network maps, from more than 9,900 individuals, across ages and cohorts, including the Adolescent Brain Cognitive Development study, the Developmental Human Connectome Project and others. We also generated probabilistic network maps across multiple ages and integration zones (using a new overlapping mapping technique, Overlapping MultiNetwork Imaging). Using regions of high network invariance improved the reproducibility of executive function statistical maps in brain-wide associations compared to group average-based parcellations. Finally, we provide a potential use case for probabilistic maps for targeted neuromodulation. The atlas is expandable to alternative datasets with an online interface encouraging the scientific community to explore and contribute to understanding the human brain function more precisely.

Cumulative Effects of Resting-State Connectivity Across All Brain Networks Significantly Correlate with Attention-Deficit Hyperactivity Disorder Symptoms.

Identification of replicable neuroimaging correlates of attention-deficit hyperactivity disorder (ADHD) has been hindered by small sample sizes, small effects, and heterogeneity of methods. Given evidence that ADHD is associated with alterations in widely distributed brain networks and the small effects of individual brain features, a whole-brain perspective focusing on cumulative effects is warranted. The use of large, multisite samples is crucial for improving reproducibility and clinical utility of brain-wide MRI association studies. To address this, a polyneuro risk score (PNRS) representing cumulative, brain-wide, ADHD-associated resting-state functional connectivity was constructed and validated using data from the Adolescent Brain Cognitive Development (ABCD, N = 5,543, 51.5% female) study, and was further tested in the independent Oregon-ADHD-1000 case-control cohort (N = 553, 37.4% female). The ADHD PNRS was significantly associated with ADHD symptoms in both cohorts after accounting for relevant covariates (p < 0.001). The most predictive PNRS involved all brain networks, though the strongest effects were concentrated among the default mode and cingulo-opercular networks. In the longitudinal Oregon-ADHD-1000, non-ADHD youth had significantly lower PNRS (Cohen's d = -0.318, robust p = 5.5 × 10-4) than those with persistent ADHD (age 7-19). The PNRS, however, did not mediate polygenic risk for ADHD. Brain-wide connectivity was robustly associated with ADHD symptoms in two independent cohorts, providing further evidence of widespread dysconnectivity in ADHD. Evaluation in enriched samples demonstrates the promise of the PNRS approach for improving reproducibility in neuroimaging studies and unraveling the complex relationships between brain connectivity and behavioral disorders.

Brain structural covariance network features are robust markers of early heavy alcohol use.

BACKGROUND AND AIMS: Recently, we demonstrated that a distinct pattern of structural covariance networks (SCN) from magnetic resonance imaging (MRI)-derived measurements of brain cortical thickness characterized young adults with alcohol use disorder (AUD) and predicted current and future problematic drinking in adolescents relative to controls. Here, we establish the robustness and value of SCN for identifying heavy alcohol users in three additional independent studies. DESIGN AND SETTING: Cross-sectional and longitudinal studies using data from the Pediatric Imaging, Neurocognition and Genetics (PING) study (n = 400, age range = 14-22 years), the National Consortium on Alcohol and Neurodevelopment in Adolescence (NCANDA) (n = 272, age range = 17-22 years) and the Human Connectome Project (HCP) (n = 375, age range = 22-37 years). CASES: Cases were defined based on heavy alcohol use patterns or former alcohol use disorder (AUD) diagnoses: 50, 68 and 61 cases were identified. Controls had none or low alcohol use or absence of AUD: 350, 204 and 314 controls were selected. MEASUREMENTS: Graph theory metrics of segregation and integration were used to summarize SCN. FINDINGS: Mirroring our prior findings, and across the three data sets, cases had a lower clustering coefficient [area under the curve (AUC) = -0.029, P = 0.002], lower modularity (AUC = -0.14, P = 0.004), lower average shortest path length (AUC = -0.078, P = 0.017) and higher global efficiency (AUC = 0.007, P = 0.010). Local efficiency differences were marginal (AUC = -0.017, P = 0.052). That is, cases exhibited lower network segregation and higher integration, suggesting that adjacent nodes (i.e. brain regions) were less similar in thickness whereas spatially distant nodes were more similar. CONCLUSION: Structural covariance network (SCN) differences in the brain appear to constitute an early marker of heavy alcohol use in three new data sets and, more generally, demonstrate the utility of SCN-derived metrics to detect brain-related psychopathology.

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.

Heightened adolescent emotional reactivity in the brain is associated with lower future distress tolerance and higher depressive symptoms.

Distress tolerance, the ability to persist while experiencing negative psychological states, is essential for regulating emotions and is a transdiagnostic risk/resiliency trait for multiple psychopathologies. Studying distress tolerance during adolescence, a period when emotion regulation is still developing, may help identify early risk and/or protective factors. This study included 40 participants (mean scan age = 17.5 years) and using an emotional Go-NoGo functional magnetic resonance imaging task and voxel-wise regression analysis, examined the association between brain response during emotional face processing and future distress tolerance (two ± 0.5 years), controlling for sex assigned at birth, age, and time between visits. Post-hoc analyses tested the mediating role of distress tolerance on the emotional reactivity and depressive symptom relationship. Whole-brain analysis showed greater inferior occipital gyrus activation was associated with less distress tolerance at follow-up. The mediating role of distress tolerance demonstrated a trend-level indirect effect. Findings suggest that individuals who allocate greater visual resources to emotionally salient information tend to exhibit greater challenges in tolerating distress. Distress tolerance may help to link emotional reactivity neurobiology to future depressive symptoms. Building distress tolerance through emotion regulation strategies may be an appropriate strategy for decreasing depressive symptoms.

Effects of emerging alcohol use on developmental trajectories of functional sleep measures in adolescents.

STUDY OBJECTIVES: Adolescence is characterized by significant brain development, accompanied by changes in sleep timing and architecture. It also is a period of profound psychosocial changes, including the initiation of alcohol use; however, it is unknown how alcohol use affects sleep architecture in the context of adolescent development. We tracked developmental changes in polysomnographic (PSG) and electroencephalographic (EEG) sleep measures and their relationship with emergent alcohol use in adolescents considering confounding effects (e.g. cannabis use). METHODS: Adolescents (n = 94, 43% female, age: 12-21 years) in the National Consortium on Alcohol and Neurodevelopment in Adolescence (NCANDA) study had annual laboratory PSG recordings across 4-years. Participants were no/low drinkers at baseline. RESULTS: Linear mixed effect models showed developmental changes in sleep macrostructure and EEG, including a decrease in slow wave sleep and slow wave (delta) EEG activity with advancing age. Emergent moderate/heavy alcohol use across three follow-up years was associated with a decline in percentage rapid eye movement (REM) sleep over time, a longer sleep onset latency (SOL) and shorter total sleep time (TST) in older adolescents, and lower non-REM delta and theta power in males. CONCLUSIONS: These longitudinal data show substantial developmental changes in sleep architecture. Emergent alcohol use during this period was associated with altered sleep continuity, architecture, and EEG measures, with some effects dependent on age and sex. These effects, in part, could be attributed to the effects of alcohol on underlying brain maturation processes involved in sleep-wake regulation.

Adolescent Substance Use Is Associated With Altered Brain Response During Processing of Negative Emotional Stimuli.

OBJECTIVE: Substance misuse is often associated with emotional dysregulation. Understanding the neurobiology of emotional responsivity and regulation as it relates to substance use in adolescence may be beneficial for preventing future use. METHOD: The present study used a community sample, ages 11-21 years old (N = 130, Mage = 17), to investigate the effects of alcohol and marijuana use on emotional reactivity and regulation using an Emotional Go-NoGo task during functional magnetic resonance imaging. The task consisted of three conditions, where target (Go) stimuli were either happy, scared, or calm faces. Self-report lifetime (and past-90-day) drinking and marijuana use days were provided at all visits. RESULTS: Substance use was not differentially related to task performance based on condition. Whole-brain linear mixed-effects analyses (controlling for age and sex) found that more lifetime drinking occasions was associated with greater neural emotional processing (Go trials) in the right middle cingulate cortex during scared versus calm conditions. In addition, more marijuana use occasions were associated with less neural emotional processing during scared versus calm conditions in the right middle cingulate cortex and right middle and inferior frontal gyri. Substance use was not associated with brain activation during inhibition (NoGo trials). CONCLUSIONS: These findings demonstrate that substance use-related alterations in brain circuitry are important for attention allocation and the integration of emotional processing and motor response when viewing negative emotional stimuli.

The Oregon ADHD-1000: A new longitudinal data resource enriched for clinical cases and multiple levels of analysis.

The fields of developmental psychopathology, developmental neuroscience, and behavioral genetics are increasingly moving toward a data sharing model to improve reproducibility, robustness, and generalizability of findings. This approach is particularly critical for understanding attention-deficit/hyperactivity disorder (ADHD), which has unique public health importance given its early onset, high prevalence, individual variability, and causal association with co-occurring and later developing problems. A further priority concerns multi-disciplinary/multi-method datasets that can span different units of analysis. Here, we describe a public dataset using a case-control design for ADHD that includes: multi-method, multi-measure, multi-informant, multi-trait data, and multi-clinician evaluation and phenotyping. It spans > 12 years of annual follow-up with a lag longitudinal design allowing age-based analyses spanning age 7-19 + years with a full age range from 7 to 21. Measures span genetic and epigenetic (DNA methylation) array data; EEG, functional and structural MRI neuroimaging; and psychophysiological, psychosocial, clinical and functional outcomes data. The resource also benefits from an autism spectrum disorder add-on cohort and a cross sectional case-control ADHD cohort from a different geographical region for replication and generalizability. Datasets allowing for integration from genes to nervous system to behavior represent the "next generation" of researchable cohorts for ADHD and developmental psychopathology.

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.

A preliminary study of white matter correlates of a laboratory measure of attention and motor stability in attention-deficit/hyperactivity disorder.

Attention-deficit/hyperactivity disorder (ADHD) is a complex behavioral disorder, often difficult and time consuming to diagnose. Laboratory assessment of ADHD-related constructs of attention and motor activity may be helpful in elucidating neurobiology; however, neuroimaging studies evaluating laboratory measures of ADHD are lacking. In this preliminary study, we assessed the association between fractional anisotropy (FA), a measure of white matter microstructure, and laboratory measures of attention and motor behavior using the QbTest, a widely used measure thought to improve clinician diagnostic confidence. This is the first look at neural correlates of this widely used measure. The sample included adolescents and young adults (ages 12-20, 35% female) with ADHD (n = 31) and without (n = 52). As expected, ADHD status was associated with motor activity, and cognitive inattention and impulsivity in the laboratory. With regard to MRI findings, laboratory observed motor activity and inattention were associated with greater FA in white matter regions of the primary motor cortex. All three laboratory observations were associated with lower FA in regions subserving fronto-striatal-thalamic and frontoparietal (i.e. superior longitudinal fasciculus) circuitry. Further, FA in white matter regions of the prefrontal cortex appeared to mediate the relationship between ADHD status and motor activity on the QbTest. These findings, while preliminary, suggest that performance on certain laboratory tasks is informative with regard to neurobiological correlates of subdomains of the complex ADHD phenotype. In particular, we provide novel evidence for a relationship between an objective measure of motor hyperactivity and white matter microstructure in motor and attentional networks.

Risk for depression tripled during the COVID-19 pandemic in emerging adults followed for the last 8 years.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic has significantly increased depression rates, particularly in emerging adults. The aim of this study was to examine longitudinal changes in depression risk before and during COVID-19 in a cohort of emerging adults in the U.S. and to determine whether prior drinking or sleep habits could predict the severity of depressive symptoms during the pandemic. METHODS: Participants were 525 emerging adults from the National Consortium on Alcohol and NeuroDevelopment in Adolescence (NCANDA), a five-site community sample including moderate-to-heavy drinkers. Poisson mixed-effect models evaluated changes in the Center for Epidemiological Studies Depression Scale (CES-D-10) from before to during COVID-19, also testing for sex and age interactions. Additional analyses examined whether alcohol use frequency or sleep duration measured in the last pre-COVID assessment predicted pandemic-related increase in depressive symptoms. RESULTS: The prevalence of risk for clinical depression tripled due to a substantial and sustained increase in depressive symptoms during COVID-19 relative to pre-COVID years. Effects were strongest for younger women. Frequent alcohol use and short sleep duration during the closest pre-COVID visit predicted a greater increase in COVID-19 depressive symptoms. CONCLUSIONS: The sharp increase in depression risk among emerging adults heralds a public health crisis with alarming implications for their social and emotional functioning as this generation matures. In addition to the heightened risk for younger women, the role of alcohol use and sleep behavior should be tracked through preventive care aiming to mitigate this looming mental health crisis.

Adolescent alcohol use is linked to disruptions in age-appropriate cortical thinning: an unsupervised machine learning approach.

Cortical thickness changes dramatically during development and is associated with adolescent drinking. However, previous findings have been inconsistent and limited by region-of-interest approaches that are underpowered because they do not conform to the underlying spatially heterogeneous effects of alcohol. In this study, adolescents (n = 657; 12-22 years at baseline) from the National Consortium on Alcohol and Neurodevelopment in Adolescence (NCANDA) study who endorsed little to no alcohol use at baseline were assessed with structural magnetic resonance imaging and followed longitudinally at four yearly intervals. Seven unique spatial patterns of covarying cortical thickness were obtained from the baseline scans by applying an unsupervised machine learning method called non-negative matrix factorization (NMF). The cortical thickness maps of all participants' longitudinal scans were projected onto vertex-level cortical patterns to obtain participant-specific coefficients for each pattern. Linear mixed-effects models were fit to each pattern to investigate longitudinal effects of alcohol consumption on cortical thickness. We found in six NMF-derived cortical thickness patterns, the longitudinal rate of decline in no/low drinkers was similar for all age cohorts. Among moderate drinkers the decline was faster in the younger adolescent cohort and slower in the older cohort. Among heavy drinkers the decline was fastest in the younger cohort and slowest in the older cohort. The findings suggested that unsupervised machine learning successfully delineated spatially coordinated patterns of vertex-level cortical thickness variation that are unconstrained by neuroanatomical features. Age-appropriate cortical thinning is more rapid in younger adolescent drinkers and slower in older adolescent drinkers, an effect that is strongest among heavy drinkers.

Earlier Bedtime and Effective Coping Skills Predict a Return to Low-Risk of Depression in Young Adults during the COVID-19 Pandemic.

To determine the persistent effects of the pandemic on mental health in young adults, we categorized depressive symptom trajectories and sought factors that promoted a reduction in depressive symptoms in high-risk individuals. Specifically, longitudinal analysis investigated changes in the risk for depression before and during the pandemic until December 2021 in 399 young adults (57% female; age range: 22.8 ± 2.6 years) in the United States (U.S.) participating in the National Consortium on Alcohol and NeuroDevelopment in Adolescence (NCANDA) study. The Center for Epidemiologic Studies Depression Scale (CES-D-10) was administered multiple times before and during the pandemic. A score ≥10 identified individuals at high-risk for depression. Self-reported sleep behavior, substance use, and coping skills at the start of the pandemic were assessed as predictors for returning to low-risk levels while controlling for demographic factors. The analysis identified four trajectory groups regarding depression risk, with 38% being at low-risk pre-pandemic through 2021, 14% showing persistent high-risk pre-pandemic through 2021, and the remainder converting to high-risk either in June 2020 (30%) or later (18%). Of those who became high-risk in June 2020, 51% were no longer at high-risk in 2021. Logistic regression revealed that earlier bedtime and, for the older participants (mid to late twenties), better coping skills were associated with this declining risk. Results indicate divergence in trajectories of depressive symptoms, with a considerable number of young adults developing persistent depressive symptoms. Healthy sleep behavior and specific coping skills have the potential to promote remittance from depressive symptoms in the context of the pandemic.

Prior test experience confounds longitudinal tracking of adolescent cognitive and motor development.

BACKGROUND: Accurate measurement of trajectories in longitudinal studies, considered the gold standard method for tracking functional growth during adolescence, decline in aging, and change after head injury, is subject to confounding by testing experience. METHODS: We measured change in cognitive and motor abilities over four test sessions (baseline and three annual assessments) in 154 male and 165 female participants (baseline age 12-21 years) from the National Consortium on Alcohol and NeuroDevelopment in Adolescence (NCANDA) study. At each of the four test sessions, these participants were given a test battery using computerized administration and traditional pencil and paper tests that yielded accuracy and speed measures for multiple component cognitive (Abstraction, Attention, Emotion, Episodic memory, Working memory, and General Ability) and motor (Ataxia and Speed) functions. The analysis aim was to dissociate neurodevelopment from testing experience by using an adaptation of the twice-minus-once tested method, which calculated the difference between longitudinal change (comprising developmental plus practice effects) and practice-free initial cross-sectional performance for each consecutive pairs of test sessions. Accordingly, the first set of analyses quantified the effects of learning (i.e., prior test experience) on accuracy and after speed domain scores. Then developmental effects were  determined for each domain for accuracy and speed having removed the measured learning effects. RESULTS: The greatest gains in performance occurred between the first and second sessions, especially in younger participants, regardless of sex, but practice gains continued to accrue thereafter for several functions. For all 8 accuracy composite scores, the developmental effect after accounting for learning was significant across age and was adequately described by linear fits. The learning-adjusted developmental effects for speed were adequately described by linear fits for Abstraction, Emotion, Episodic Memory, General Ability, and Motor scores, although a nonlinear fit was better for Attention, Working Memory, and Average Speed scores. CONCLUSION: Thus, what appeared as accelerated cognitive and motor development was, in most cases, attributable to learning. Recognition of the substantial influence of prior testing experience is critical for accurate characterization of normal development and for developing norms for clinical neuropsychological investigations of conditions affecting the brain.

Attention-Deficit/Hyperactivity Disorder: Restricted Phenotypes Prevalence, Comorbidity, and Polygenic Risk Sensitivity in the ABCD Baseline Cohort.

OBJECTIVE: To evaluate the prevalence and major comorbidities of ADHD using different operational definitions in a newly available national dataset and to test the utility of operational definitions against genetic and cognitive correlates. METHOD: The US Adolescent Brain Cognitive Development (ABCD) Study enrolled 11,878 children aged 9-10 years at baseline. ADHD prevalence, comorbidity, and association with polygenic risk score and laboratory-assessed executive functions were calculated at 4 thresholds of ADHD phenotype restrictiveness. Bias from missingness, sampling, and nesting were addressed statistically. RESULTS: Prevalence of current ADHD for 9- to 10-year old children was 3.53% (95% CI 3.14%-3.92%) when Computerized Schedule for Affective Disorders and Schizophrenia for School-Age Children (K-SADS-COMP) score and parent and teacher ratings were required to converge. Of ADHD cases so defined, 70% had a comorbid psychiatric disorder. After control for overlapping comorbidity and ruling out for psychosis or low IQ, 30.9% (95% CI 25.7%-36.7%) had a comorbid disruptive behavior disorder, 27.4% (95% CI 22.3%-33.1%) had an anxiety or fear disorder, and 2.1% (95% CI 1.2%-3.8%) had a mood disorder. Children in the top decile of polygenic load incurred a 63% increased chance of having ADHD vs the bottom half of polygenic load (p < .01)-an effect detected only with a stringent phenotype definition. Dimensional latent variables for irritability, externalizing, and ADHD yielded convergent results for cognitive correlates. CONCLUSION: This fresh estimate of national prevalence of ADHD in the United States suggests that the DSM-5 definition requiring multiple informants yields a prevalence of about 3.5%. Results may inform further ADHD studies in the ABCD sample.

Age-related changes and longitudinal stability of individual differences in ABCD Neurocognition measures.

Temporal stability of individual differences is an important prerequisite for accurate tracking of prospective relationships between neurocognition and real-world behavioral outcomes such as substance abuse and psychopathology. Here we report age-related changes and longitudinal test-retest stability (TRS) for the Neurocognition battery of the Adolescent Brain and Cognitive Development (ABCD) study, which included the NIH Toolbox (TB) Cognitive Domain and additional memory and visuospatial processing tests administered at baseline (ages 9-11) and two-year follow-up. As expected, performance improved significantly with age, but the effect size varied broadly, with Pattern Comparison and the Crystallized Cognition Composite showing the largest age-related gain (Cohen's d:.99 and.97, respectively). TRS ranged from fair (Flanker test: r = 0.44) to excellent (Crystallized Cognition Composite: r = 0.82). A comparison of longitudinal changes and cross-sectional age-related differences within baseline and follow-up assessments suggested that, for some measures, longitudinal changes may be confounded by practice effects and differences in task stimuli or procedure between baseline and follow-up. In conclusion, a subset of measures showed good stability of individual differences despite significant age-related changes, warranting their use as prospective predictors. However, caution is needed in the interpretation of observed longitudinal changes as indicators of neurocognitive development.

Associations between testosterone, estradiol, and androgen receptor genotype with amygdala subregions in adolescents.

Much is known about the development of the whole amygdala, but less is known about its structurally and functionally diverse subregions. One notable distinguishing feature is their wide range of androgen and estrogen receptor densities. Given the rise in pubertal hormones during adolescence, sex steroid levels as well as receptor sensitivity could influence age-related subregion volumes. Therefore, our goal was to evaluate the associations between the total amygdala and its subregion volumes in relation to sex hormones - estradiol and free testosterone (FT) - as a function of age and genetic differences in androgen receptor (AR) sensitivity in a sample of 297 adolescents (46% female). In males, we found small effects of FT-by-age interactions in the total amygdala, portions of the basolateral complex, and the cortical and medial nuclei (CMN), with the CMN effects being moderated by AR sensitivity. For females, small effects were seen with increased genetic AR sensitivity relating to smaller basolateral complexes. However, none of these small effects passed multiple comparisons. Future larger studies are necessary to replicate these small, yet possibly meaningful effects of FT-by-age associations and modulation by AR sensitivity on amygdala development to ultimately determine if they contribute to known sex differences in emotional neurodevelopment.