The ABCD study: understanding the development of risk for mental and physical health outcomes

Abstract

Following in the footsteps of other large "population neuroscience" studies, the Adolescent Brain Cognitive Development℠ (ABCD) study is the largest in the U.S. assessing brain development. The study is examining approximately 11,875 youth from 21 sites from age 9 to 10 for approximately ten years into young adulthood. The ABCD Study® has completed recruitment for the baseline sample generally using a multi-stage probability sample including a stratified random sample of schools. The dataset has a wealth of measured attributes of youths and their environment, including neuroimaging, cognitive, biospecimen, behavioral, youth selfreport and parent self-report metrics, and environmental measures. The initial goal of the ABCD Study was to examine risk and resiliency factors associated with the development of substance use, but the project has expanded far beyond this initial set of questions and will also greatly inform our understanding of the contributions of biospecimens (e.g., pubertal hormones), neural alterations, and environmental factors to the development of both healthy behavior and brain function as well as risk for poor mental and physical outcomes. This review outlines how the ABCD Study was designed to elucidate factors associated with the development of negative mental and physical health outcomes and will provide a selective overview of results emerging from the ABCD Study. Such emerging data includes initial validation of new instruments, important new information about the prevalence and correlates of mental health challenges in middle childhood, and promising data regarding neural correlates of both healthy and disordered behavior. In addition, we will discuss the challenges and opportunities to understanding both healthy development and the emergence of risk from ABCD Study data. Finally, we will overview the future directions of this large undertaking and the ways in which it will shape our understanding of the development of risk for poor mental and physical health outcomes.

<p>The Impact of Childhood Trauma on Developing Bipolar Disorder: Current Understanding and Ensuring Continued Progress</p>

“…This process involves disruption of the psychological and biological systems mediating responses to stressful events and may remain difficult to describe in precise mechanistic terms until the culmination of large-scale longitudinal studies, such as the UK Biobank, the Avon Longitudinal Study of Parents and Children (ALSPAC), the Adolescent Brain Cognitive Development (ABCD) study and the IMAGEN project. [173][174][175][176] These are well placed to address the interactions of CT with biological markers (eg, genetic, brainderived, hormonal or inflammatory-based) to determine the contributions to the development of BD, its course and severity. Understanding the nature of and key players in this protracted course of causal events and the ensuing altered trajectories of individuals' mental wellbeing and resilience will be vital to the potential progress of effective monitoring, management and intervention standards.…”

Meaningful Associations in the Adolescent Brain Cognitive Development Study

“…Measures collected in the ABCD Study include a neurocognitive battery [15][16][17] , mental and physical health assessments 18 , measures of culture and environment 19 , biospecimens 20 , structural and functional brain imaging 21,22 , geolocation-based environmental exposure data, wearables and mobile technology 23 , and whole genome genotyping 24 . Many of these measures are collected at in-person annual visits, with brain imaging collected at baseline and at every other year going forward.…”

Brain Connectivity Patterns in Children Linked to Neurocognitive Abilities

“…Our study leverages imaging and behavioral data from 11,875 9 and 10-year olds in the Adolescent Brain and Cognitive Development (ABCD) national consortium study, Release 2.1 31,32 . We applied bifactor modeling to the comprehensive ABCD 11-task neurocognitive battery 33 to quantify individual differences in a dominant general factor of neurocognitive ability, which captured 75% of the variation in task scores (coefficient w hierarchical 34 ), as well as three domain-specific factors that together accounted for 13% of the variation in task scores ( Figure 1).…”