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Early adolescent drinking onset is linked to myriad negative consequences. Using the National Consortium on Alcohol and NeuroDevelopment in Adolescence (NCANDA) baseline to year 8 data, this study (1) leveraged best subsets selection and Cox Proportional Hazards regressions to identify the most robust predictors of adolescent first and regular drinking onset, and (2) examined the clinical utility of drinking onset in forecasting later binge drinking and withdrawal effects. Baseline predictors included youth psychodevelopmental characteristics, cognition, brain structure, family, peer, and neighborhood domains. Participants (N=538) were alcohol-naïve at baseline. The strongest predictors of first and regular drinking onset were positive alcohol expectancies (Hazard Ratios [HRs]=1.67-1.87), easy home alcohol access (HRs=1.62-1.67), more parental solicitation (e.g., inquiring about activities; HRs=1.72-1.76), and less parental control and knowledge (HRs=.72-.73). Robust linear regressions showed earlier first and regular drinking onset predicted earlier transition into binge and regular binge drinking (βs=0.57-0.95). Zero-inflated Poisson regressions revealed that delayed first and regular drinking increased the likelihood (Incidence Rate Ratios [IRR]=1.62 and IRR=1.29, respectively) of never experiencing withdrawal. Findings identified behavioral and environmental factors predicting temporal paths to youthful drinking, dissociated first from regular drinking initiation, and revealed adverse sequelae of younger drinking initiation, supporting efforts to delay drinking onset.

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.

Background and aimsRecently, 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 settingCross-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).CasesCases 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.MeasurementsGraph theory metrics of segregation and integration were used to summarize SCN.FindingsMirroring 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.ConclusionStructural 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.

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.

Striatal development is crucial for later motor, cognitive, and reward behavior, but age-related change in striatal physiology during the neonatal period remains understudied. An MRI-based measure of tissue iron deposition, T2*, is a non-invasive way to probe striatal physiology neonatally, linked to dopaminergic processing and cognition in children and adults. Striatal subregions have distinct functions that may come online at different time periods in early life. To identify if there are critical periods before or after birth, we measured if striatal iron accrued with gestational age at birth [range= 34.57-41.85 weeks] or postnatal age at scan [range= 5-64 days], using MRI to probe the T2* signal in N = 83 neonates in three striatal subregions. We found iron increased with postnatal age in the pallidum and putamen but not the caudate. No significant relationship between iron and gestational age was observed. Using a subset of infants scanned at preschool age (N = 26), we show distributions of iron shift between time points. In infants, the pallidum had the least iron of the three regions but had the most by preschool age. Together, this provides evidence of distinct change for striatal subregions, a possible differentiation between motor and cognitive systems, identifying a mechanism that may impact future trajectories.

OBJECTIVE: Dissociation, a disruption or discontinuity in psychological functioning, is often linked with worse psychiatric symptoms; however, the prognostic value of dissociation after trauma is inconsistent. Determining whether trauma-related dissociation is uniquely predictive of later outcomes would enable early identification of at-risk trauma populations. The authors conducted the largest prospective longitudinal biomarker study of persistent dissociation to date to determine its predictive capacity for adverse psychiatric outcomes following acute trauma. METHODS: All data were part of the Freeze 2 data release from the Advancing Understanding of Recovery After Trauma (AURORA) study. Study participants provided self-report data about persistent derealization (N=1,464), a severe type of dissociation, and completed a functional MRI emotion reactivity task and resting-state scan 2 weeks posttrauma (N=145). Three-month follow-up reports were collected of posttraumatic stress, depression, pain, anxiety symptoms, and functional impairment. RESULTS: Derealization was associated with increased ventromedial prefrontal cortex (vmPFC) activation in the emotion reactivity task and decreased resting-state vmPFC connectivity with the cerebellum and orbitofrontal cortex. In separate analyses, brain-based and self-report measures of persistent derealization at 2 weeks predicted worse 3-month posttraumatic stress symptoms, distinct from the effects of childhood maltreatment history and current posttraumatic stress symptoms. CONCLUSIONS: The findings suggest that persistent derealization is both an early psychological and biological marker of worse later psychiatric outcomes. The neural correlates of trauma-related dissociation may serve as potential targets for treatment engagement to prevent posttraumatic stress disorder. These results underscore dissociation assessment as crucial following trauma exposure to identify at-risk individuals, and they highlight an unmet clinical need for tailored early interventions.

BACKGROUND: This is the first report on the association between trauma exposure and depression from the Advancing Understanding of RecOvery afteR traumA(AURORA) multisite longitudinal study of adverse post-traumatic neuropsychiatric sequelae (APNS) among participants seeking emergency department (ED) treatment in the aftermath of a traumatic life experience. METHODS: We focus on participants presenting at EDs after a motor vehicle collision (MVC), which characterizes most AURORA participants, and examine associations of participant socio-demographics and MVC characteristics with 8-week depression as mediated through peritraumatic symptoms and 2-week depression. RESULTS: Eight-week depression prevalence was relatively high (27.8%) and associated with several MVC characteristics (being passenger v. driver; injuries to other people). Peritraumatic distress was associated with 2-week but not 8-week depression. Most of these associations held when controlling for peritraumatic symptoms and, to a lesser degree, depressive symptoms at 2-weeks post-trauma. CONCLUSIONS: These observations, coupled with substantial variation in the relative strength of the mediating pathways across predictors, raises the possibility of diverse and potentially complex underlying biological and psychological processes that remain to be elucidated in more in-depth analyses of the rich and evolving AURORA database to find new targets for intervention and new tools for risk-based stratification following trauma exposure.

BackgroundThe neurodevelopmental model of psychosis was established over 30 years ago; however, the developmental influence on psychotic symptom expression - how age affects clinical presentation in first-episode psychosis - has not been thoroughly investigated.MethodsUsing generalized additive modeling, which allows for linear and non-linear functional forms of age-related change, we leveraged symptom data from a large sample of antipsychotic-naïve individuals with first-episode psychosis (N = 340, 12-40 years, 1-12 visits), collected at the University of Pittsburgh from 1990 to 2017. We examined relationships between age and severity of perceptual and non-perceptual positive symptoms and negative symptoms. We tested for age-associated effects on change in positive or negative symptom severity following baseline assessment and explored the time-varying relationship between perceptual and non-perceptual positive symptoms across adolescent development.ResultsPerceptual positive symptom severity significantly decreased with increasing age (F = 7.0, p = 0.0007; q = 0.003) while non-perceptual positive symptom severity increased with age (F = 4.1, p = 0.01, q = 0.02). Anhedonia severity increased with increasing age (F = 6.7, p = 0.00035; q = 0.0003), while flat affect decreased in severity with increased age (F = 9.8, p = 0.002; q = 0.006). Findings remained significant when parental SES, IQ, and illness duration were included as covariates. There were no developmental effects on change in positive or negative symptom severity (all p > 0.25). Beginning at age 18, there was a statistically significant association between severity of non-perceptual and perceptual symptoms. This relationship increased in strength throughout adulthood.ConclusionsThese findings suggest that as maturation proceeds, perceptual symptoms attenuate while non-perceptual symptoms are enhanced. Findings underscore how pathological brain-behavior relationships vary as a function of development.

OBJECTIVE: Whether short-term, low-potency opioid prescriptions for acute pain lead to future at-risk opioid use remains controversial and inadequately characterized. Our objective was to measure the association between emergency department (ED) opioid analgesic exposure after a physical, trauma-related event and subsequent opioid use. We hypothesized ED opioid analgesic exposure is associated with subsequent at-risk opioid use. METHODS: Participants were enrolled in AURORA, a prospective cohort study of adult patients in 29 U.S., urban EDs receiving care for a traumatic event. Exclusion criteria were hospital admission, persons reporting any non-medical opioid use (e.g., opioids without prescription or taking more than prescribed for euphoria) in the 30 days before enrollment, and missing or incomplete data regarding opioid exposure or pain. We used multivariable logistic regression to assess the relationship between ED opioid exposure and at-risk opioid use, defined as any self-reported non-medical opioid use after initial ED encounter or prescription opioid use at 3-months. RESULTS: Of 1441 subjects completing 3-month follow-up, 872 participants were included for analysis. At-risk opioid use occurred within 3 months in 33/620 (5.3%, CI: 3.7,7.4) participants without ED opioid analgesic exposure; 4/16 (25.0%, CI: 8.3, 52.6) with ED opioid prescription only; 17/146 (11.6%, CI: 7.1, 18.3) with ED opioid administration only; 12/90 (13.3%, CI: 7.4, 22.5) with both. Controlling for clinical factors, adjusted odds ratios (aORs) for at-risk opioid use after ED opioid exposure were: ED prescription only: 4.9 (95% CI 1.4, 17.4); ED administration for analgesia only: 2.0 (CI 1.0, 3.8); both: 2.8 (CI 1.2, 6.5). CONCLUSIONS: ED opioids were associated with subsequent at-risk opioid use within three months in a geographically diverse cohort of adult trauma patients. This supports need for prospective studies focused on the long-term consequences of ED opioid analgesic exposure to estimate individual risk and guide therapeutic decision-making.

BACKGROUND: Cross-sectional studies have found that individuals with posttraumatic stress disorder (PTSD) exhibit deficits in autonomic functioning. While PTSD rates are twice as high in women compared to men, sex differences in autonomic functioning are relatively unknown among trauma-exposed populations. The current study used a prospective design to examine sex differences in posttraumatic autonomic functioning. METHODS: 192 participants were recruited from emergency departments following trauma exposure (Mean age = 35.88, 68.2% female). Skin conductance was measured in the emergency department; fear conditioning was completed two weeks later and included measures of blood pressure (BP), heart rate (HR), and high frequency heart rate variability (HF-HRV). PTSD symptoms were assessed 8 weeks after trauma. RESULTS: 2-week systolic BP was significantly higher in men, while 2-week HR was significantly higher in women, and a sex by PTSD interaction suggested that women who developed PTSD demonstrated the highest HR levels. Two-week HF-HRV was significantly lower in women, and a sex by PTSD interaction suggested that women with PTSD demonstrated the lowest HF-HRV levels. Skin conductance response in the emergency department was associated with 2-week HR and HF-HRV only among women who developed PTSD. CONCLUSIONS: Our results indicate that there are notable sex differences in autonomic functioning among trauma-exposed individuals. Differences in sympathetic biomarkers (BP and HR) may have implications for cardiovascular disease risk given that sympathetic arousal is a mechanism implicated in this risk among PTSD populations. Future research examining differential pathways between PTSD and cardiovascular risk among men versus women is warranted.

OBJECTIVE: Major negative life events, such as trauma exposure, can play a key role in igniting or exacerbating psychopathology. However, few disorders are diagnosed with respect to precipitating events, and the role of these events in the unfolding of new psychopathology is not well understood. The authors conducted a multisite transdiagnostic longitudinal study of trauma exposure and related mental health outcomes to identify neurobiological predictors of risk, resilience, and different symptom presentations. METHODS: A total of 146 participants (discovery cohort: N=69; internal replication cohort: N=77) were recruited from emergency departments within 72 hours of a trauma and followed for the next 6 months with a survey, MRI, and physiological assessments. RESULTS: Task-based functional MRI 2 weeks after a motor vehicle collision identified four clusters of individuals based on profiles of neural activity reflecting threat reactivity, reward reactivity, and inhibitory engagement. Three clusters were replicated in an independent sample with a variety of trauma types. The clusters showed different longitudinal patterns of posttrauma symptoms. CONCLUSIONS: These findings provide a novel characterization of heterogeneous stress responses shortly after trauma exposure, identifying potential neuroimaging-based biotypes of trauma resilience and psychopathology.

Diffusion-weighted magnetic resonance imaging (dMRI) is the primary method for noninvasively studying the organization of white matter in the human brain. Here we introduce QSIPrep, an integrative software platform for the processing of diffusion images that is compatible with nearly all dMRI sampling schemes. Drawing on a diverse set of software suites to capitalize on their complementary strengths, QSIPrep facilitates the implementation of best practices for processing of diffusion images.

Exogenous causes, such as alcohol use, and endogenous factors, such as temperament and sex, can modulate developmental trajectories of adolescent neurofunctional maturation. We examined how these factors affect sexual dimorphism in brain functional networks in youth drinking below diagnostic threshold for alcohol use disorder (AUD). Based on the 3-year, annually acquired, longitudinal resting-state functional magnetic resonance imaging (MRI) data of 526 adolescents (12-21 years at baseline) from the National Consortium on Alcohol and Neurodevelopment in Adolescence (NCANDA) cohort, developmental trajectories of 23 intrinsic functional networks (IFNs) were analyzed for (1) sexual dimorphism in 259 participants who were no-to-low drinkers throughout this period; (2) sex-alcohol interactions in two age- and sex-matched NCANDA subgroups (N = 76 each), half no-to-low, and half moderate-to-heavy drinkers; and (3) moderating effects of gender-specific alcohol dose effects and a multifactorial impulsivity measure on IFN connectivity in all NCANDA participants. Results showed that sex differences in no-to-low drinkers diminished with age in the inferior-occipital network, yet girls had weaker within-network connectivity than boys in six other networks. Effects of adolescent alcohol use were more pronounced in girls than boys in three IFNs. In particular, girls showed greater within-network connectivity in two motor networks with more alcohol consumption, and these effects were mediated by sensation-seeking only in girls. Our results implied that drinking might attenuate the naturally diminishing sexual differences by disrupting the maturation of network efficiency more severely in girls. The sex-alcohol-dose effect might explain why women are at higher risk of alcohol-related health and psychosocial consequences than men.

AimTo examine individual variability between perceived physical features and hormones of pubertal maturation in 9-10-year-old children as a function of sociodemographic characteristics.MethodsCross-sectional metrics of puberty were utilized from the baseline assessment of the Adolescent Brain Cognitive Development (ABCD) Study-a multi-site sample of 9-10 year-olds (n = 11,875)-and included perceived physical features via the pubertal development scale (PDS) and child salivary hormone levels (dehydroepiandrosterone and testosterone in all, and estradiol in females). Multi-level models examined the relationships among sociodemographic measures, physical features, and hormone levels. A group factor analysis (GFA) was implemented to extract latent variables of pubertal maturation that integrated both measures of perceived physical features and hormone levels.ResultsPDS summary scores indicated more males (70%) than females (31%) were prepubertal. Perceived physical features and hormone levels were significantly associated with child's weight status and income, such that more mature scores were observed among children that were overweight/obese or from households with low-income. Results from the GFA identified two latent factors that described individual differences in pubertal maturation among both females and males, with factor 1 driven by higher hormone levels, and factor 2 driven by perceived physical maturation. The correspondence between latent factor 1 scores (hormones) and latent factor 2 scores (perceived physical maturation) revealed synchronous and asynchronous relationships between hormones and concomitant physical features in this large young adolescent sample.ConclusionsSociodemographic measures were associated with both objective hormone and self-report physical measures of pubertal maturation in a large, diverse sample of 9-10 year-olds. The latent variables of pubertal maturation described a complex interplay between perceived physical changes and hormone levels that hallmark sexual maturation, which future studies can examine in relation to trajectories of brain maturation, risk/resilience to substance use, and other mental health outcomes.

Adverse posttraumatic neuropsychiatric sequelae (APNS) are common among civilian trauma survivors and military veterans. These APNS, as traditionally classified, include posttraumatic stress, postconcussion syndrome, depression, and regional or widespread pain. Traditional classifications have come to hamper scientific progress because they artificially fragment APNS into siloed, syndromic diagnoses unmoored to discrete components of brain functioning and studied in isolation. These limitations in classification and ontology slow the discovery of pathophysiologic mechanisms, biobehavioral markers, risk prediction tools, and preventive/treatment interventions. Progress in overcoming these limitations has been challenging because such progress would require studies that both evaluate a broad spectrum of posttraumatic sequelae (to overcome fragmentation) and also perform in-depth biobehavioral evaluation (to index sequelae to domains of brain function). This article summarizes the methods of the Advancing Understanding of RecOvery afteR traumA (AURORA) Study. AURORA conducts a large-scale (n = 5000 target sample) in-depth assessment of APNS development using a state-of-the-art battery of self-report, neurocognitive, physiologic, digital phenotyping, psychophysical, neuroimaging, and genomic assessments, beginning in the early aftermath of trauma and continuing for 1 year. The goals of AURORA are to achieve improved phenotypes, prediction tools, and understanding of molecular mechanisms to inform the future development and testing of preventive and treatment interventions.

AimTo examine individual variability between perceived physical features and hormones of pubertal maturation in 9-10-year-old children as a function of sociodemographic characteristics.MethodsCross-sectional metrics of puberty were utilized from the baseline assessment of the Adolescent Brain Cognitive Development (ABCD) Study-a multi-site sample of 9-10 year-olds (n = 11,875)-and included perceived physical features via the pubertal development scale (PDS) and child salivary hormone levels (dehydroepiandrosterone and testosterone in all, and estradiol in females). Multi-level models examined the relationships among sociodemographic measures, physical features, and hormone levels. A group factor analysis (GFA) was implemented to extract latent variables of pubertal maturation that integrated both measures of perceived physical features and hormone levels.ResultsPDS summary scores indicated more males (70%) than females (31%) were prepubertal. Perceived physical features and hormone levels were significantly associated with child's weight status and income, such that more mature scores were observed among children that were overweight/obese or from households with low-income. Results from the GFA identified two latent factors that described individual differences in pubertal maturation among both females and males, with factor 1 driven by higher hormone levels, and factor 2 driven by perceived physical maturation. The correspondence between latent factor 1 scores (hormones) and latent factor 2 scores (perceived physical maturation) revealed synchronous and asynchronous relationships between hormones and concomitant physical features in this large young adolescent sample.ConclusionsSociodemographic measures were associated with both objective hormone and self-report physical measures of pubertal maturation in a large, diverse sample of 9-10 year-olds. The latent variables of pubertal maturation described a complex interplay between perceived physical changes and hormone levels that hallmark sexual maturation, which future studies can examine in relation to trajectories of brain maturation, risk/resilience to substance use, and other mental health outcomes.

The 21-site Adolescent Brain Cognitive Development (ABCD) study provides an unparalleled opportunity to characterize functional brain development via resting-state functional connectivity (RSFC) and to quantify relationships between RSFC and behavior. This multi-site data set includes potentially confounding sources of variance, such as differences between data collection sites and/or scanner manufacturers, in addition to those inherent to RSFC (e.g., head motion). The ABCD project provides a framework for characterizing and reproducing RSFC and RSFC-behavior associations, while quantifying the extent to which sources of variability bias RSFC estimates. We quantified RSFC and functional network architecture in 2,188 9-10-year old children from the ABCD study, segregated into demographically-matched discovery (N = 1,166) and replication datasets (N = 1,022). We found RSFC and network architecture to be highly reproducible across children. We did not observe strong effects of site; however, scanner manufacturer effects were large, reproducible, and followed a "short-to-long" association with distance between regions. Accounting for potential confounding variables, we replicated that RSFC between several higher-order networks was related to general cognition. In sum, we provide a framework for how to characterize RSFC-behavior relationships in a rigorous and reproducible manner using the ABCD dataset and other large multi-site projects.

To track iron accumulation and location in the brain across adolescence, we repurposed diffusion tensor imaging (DTI) and functional magnetic resonance imaging (fMRI) data acquired in 513 adolescents and validated iron estimates with quantitative susceptibility mapping (QSM) in 104 of these subjects. DTI and fMRI data were acquired longitudinally over 1 year in 245 male and 268 female, no-to-low alcohol-consuming adolescents (12-21 years at baseline) from the National Consortium on Alcohol and NeuroDevelopment in Adolescence (NCANDA) study. Brain region average signal values were calculated for susceptibility to nonheme iron deposition: pallidum, putamen, dentate nucleus, red nucleus, and substantia nigra. To estimate nonheme iron, the corpus callosum signal (robust to iron effects) was divided by regional signals to generate estimated R2 (edwR2 for DTI) and R2 * (eR2 * for fMRI). Longitudinal iron deposition was measured using the normalized signal change across time for each subject. Validation using baseline QSM, derived from susceptibility-weighted imaging, was performed on 46 male and 58 female participants. Normalized iron deposition estimates from DTI and fMRI correlated with age in most regions; both estimates indicated less iron in boys than girls. QSM results correlated highly with DTI and fMRI results (adjusted R2 = 0.643 for DTI, 0.578 for fMRI). Cross-sectional and longitudinal analyses indicated an initial rapid increase in iron, notably in the putamen and red nucleus, that slowed with age. DTI and fMRI data can be repurposed for identifying regional brain iron deposition in developing adolescents as validated with high correspondence with QSM.

The second iteration of the Autism Brain Imaging Data Exchange (ABIDE II) aims to enhance the scope of brain connectomics research in Autism Spectrum Disorder (ASD). Consistent with the initial ABIDE effort (ABIDE I), that released 1112 datasets in 2012, this new multisite open-data resource is an aggregate of resting state functional magnetic resonance imaging (MRI) and corresponding structural MRI and phenotypic datasets. ABIDE II includes datasets from an additional 487 individuals with ASD and 557 controls previously collected across 16 international institutions. The combination of ABIDE I and ABIDE II provides investigators with 2156 unique cross-sectional datasets allowing selection of samples for discovery and/or replication. This sample size can also facilitate the identification of neurobiological subgroups, as well as preliminary examinations of sex differences in ASD. Additionally, ABIDE II includes a range of psychiatric variables to inform our understanding of the neural correlates of co-occurring psychopathology; 284 diffusion imaging datasets are also included. It is anticipated that these enhancements will contribute to unraveling key sources of ASD heterogeneity.

During adolescence, problems reflecting cognitive, behavioral and affective dysregulation, such as inattention and emotional dyscontrol, have been observed to be associated with substance use disorder (SUD) risks and outcomes. Prior studies have typically been with small samples, and have typically not included comprehensive measurement of executive dysfunction domains. The relationships of executive dysfunction in daily life with performance based testing of cognitive skills and structural brain characteristics, thought to be the basis for executive functioning, have not been definitively determined. The aims of this study were to determine the relationships between executive dysfunction in daily life, measured by the Behavior Rating Inventory of Executive Function (BRIEF), cognitive skills and structural brain characteristics, and SUD risks, including a global SUD risk indicator, sleep quality, and risky alcohol and cannabis use. In addition to bivariate relationships, multivariate models were tested. The subjects (n = 817; ages 12 through 21) were participants in the National Consortium on Alcohol and Neurodevelopment in Adolescence (NCANDA) study. The results indicated that executive dysfunction was significantly related to SUD risks, poor sleep quality, risky alcohol use and cannabis use, and was not significantly related to cognitive skills or structural brain characteristics. In multivariate models, the relationship between poor sleep quality and risky substance use was mediated by executive dysfunction. While these cross-sectional relationships need to be further examined in longitudinal analyses, the results suggest that poor sleep quality and executive dysfunction may be viable preventive intervention targets to reduce adolescent substance use.