The ABCD-USA Consortium proposes a study designed to permit the scientific community to answer important questions about the effects of substance use (SU) patterns on behavioral and brain development of adolescents. We have assembled a team of investigators with unparalleled research experience with children and adolescents, and specific expertise in adolescent SU, child and adolescent development, developmental psychopathology, longitudinal multi-site imaging, developmental neuroimaging, developmental cognitive neuroscience, genetics and imaging genetics, bioassays, epidemiology, survey research, bioinformatics, and mobile assessment technologies. We propose a comprehensive, nationwide study to be conducted at 21 sites organized into 11 hubs (over 89 million Americans, 29% of the US population, live within 50 miles of our geographically spread sites), that, uniquely, can provide a nationally representative sample and a large twin sample that together can help distinguish environmental, sociocultural, and genetic factors relevant to SU. We ensure cohesion and standardization by employing a recruitment strategy designed by a professional survey company (experience with Monitoring the Future); standardized environmental, neurocognitive and mental health assessments, MRI assessments with all scanners using harmonized Human Connectome Project procedures, and computerized data collection with real-time quality control. Developmentally tailored assessments will have stable sensitivity and construct validity across the childhood and adolescent developmental period. They minimize participant burden, yet capture even subtle changes over time in substance use, mental health, neurocognition, development, and environment, and we employ novel state-of-the-art bioassays and passive data collection from mobile devices. A detailed retention plan builds on the experience and success of our investigators. This application describes the ABCD-USA Data Analysis and Informatics Center (DAIC), which will: establish a harmonized MRI acquisition protocol, compatible with all major scanner platforms, taking advantage of recent technological advances in structural and functional MRI; establish rigorous quality control and quantitative calibration procedures to ensure accuracy and comparability of derived imaging measures across scanners and across time; implement advanced computational analysis workflows for all imaging data; implement reliable data entry, quality control, and monitoring tools for the substance use questionnaire, neurocognitive assessments, bioassay-derived measures, and mobile technologies assessment data; implement the state- of-the-art statistical analysis tools and procedures needed to integrate information across measures and modalities; and implement infrastructure and procedures for public sharing of raw- and derived data and associated tools and computational workflows, and enable interactive data exploration and analytics through a web-based Portal.

Public Health Relevance

The ABCD-USA Consortium will use multimodal brain imaging, cognitive and clinical assessments, bioassays, mobile monitoring, and careful assessment of substance use, environment, psychopathological symptoms, and social functioning in 11,111 adolescents followed over 10 years to determine the effects of substance use on adolescent brain and cognitive development. Our 2/13 ABCD-USA Data Analysis and Informatics Center (DAIC) will establish harmonized MRI protocols across Sites and scanners, perform quality control of raw- and derived data, and implement the informatics and computational infrastructure needed for the overall project.

Agency
National Institute of Health (NIH)
Institute
National Institute on Drug Abuse (NIDA)
Type
Resource-Related Research Projects--Cooperative Agreements (U24)
Project #
3U24DA041123-03S2
Application #
9564268
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Deeds, Bethany
Project Start
2015-09-30
Project End
2020-05-31
Budget Start
2017-06-01
Budget End
2018-05-31
Support Year
3
Fiscal Year
2017
Total Cost
Indirect Cost
Name
University of California, San Diego
Department
Neurosciences
Type
Schools of Medicine
DUNS #
804355790
City
La Jolla
State
CA
Country
United States
Zip Code
92093
Walsh, Jeremy J; Barnes, Joel D; Cameron, Jameason D et al. (2018) Associations between 24 hour movement behaviours and global cognition in US children: a cross-sectional observational study. Lancet Child Adolesc Health 2:783-791
Sundar, V S; Fan, Chun-Chieh; Holland, Dominic et al. (2018) Determining Genetic Causal Variants Through Multivariate Regression Using Mixture Model Penalty. Front Genet 9:77
Zucker, Robert A; Gonzalez, Raul; Feldstein Ewing, Sarah W et al. (2018) Assessment of culture and environment in the Adolescent Brain and Cognitive Development Study: Rationale, description of measures, and early data. Dev Cogn Neurosci 32:107-120
Casey, B J; Cannonier, Tariq; Conley, May I et al. (2018) The Adolescent Brain Cognitive Development (ABCD) study: Imaging acquisition across 21 sites. Dev Cogn Neurosci 32:43-54
Teruel, Jose R; Kuperman, Joshua M; Dale, Anders M et al. (2018) High temporal resolution motion estimation using a self-navigated simultaneous multi-slice echo planar imaging acquisition. J Magn Reson Imaging :
Clark, Duncan B; Fisher, Celia B; Bookheimer, Susan et al. (2018) Biomedical ethics and clinical oversight in multisite observational neuroimaging studies with children and adolescents: The ABCD experience. Dev Cogn Neurosci 32:143-154
Ferrari, Raffaele; Wang, Yunpeng; Vandrovcova, Jana et al. (2017) Genetic architecture of sporadic frontotemporal dementia and overlap with Alzheimer's and Parkinson's diseases. J Neurol Neurosurg Psychiatry 88:152-164
Olney, Nicholas T; Alquezar, Carolina; Ramos, Eliana Marisa et al. (2017) Linking tuberous sclerosis complex, excessive mTOR signaling, and age-related neurodegeneration: a new association between TSC1 mutation and frontotemporal dementia. Acta Neuropathol 134:813-816
Yokoyama, Jennifer S; Karch, Celeste M; Fan, Chun C et al. (2017) Shared genetic risk between corticobasal degeneration, progressive supranuclear palsy, and frontotemporal dementia. Acta Neuropathol 133:825-837
Dosenbach, Nico U F; Koller, Jonathan M; Earl, Eric A et al. (2017) Real-time motion analytics during brain MRI improve data quality and reduce costs. Neuroimage 161:80-93

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