This application is submitted by a group of investigators at 9 sites distributed throughout the U.S. where there are active developmental research programs involving substantial numbers of typically developing children, and neuroimaging investigators with experience in multi-site imaging initiatives. We propose to join forces to leverage these ongoing pediatric studies to assemble, over a period of 2 years, a large, cross- sectional imaging-genomics dataset to be used as a shared resource. The major aim of our proposal is to create a database that will include genome-wide association results for a large number of neural architectural phenotypes obtained using multimodal structural imaging. We propose to offer this database - essentially a map depicting the genomic landscape of the developing human brain - as a resource to the scientific community. Across the sites, investigators will administer the brief NIH Neuroscience Blueprint Toolbox Cognitive assessment;acquire standardized structural and diffusion images, and collect DNA samples in 1575 children and adolescents who are participants in their ongoing studies. The DNA samples will be shipped to a central Genetics Core for analysis, the imaging data will be uploaded for quality control and computational morphometry by the Imaging Core, and other data will be uploaded to the Coordinating Core, where an aggregate database of demographic, behavioral, imaging, and genomics deliverables will be compiled from 1400 individuals and maintained for shared access. A large, cross-sectional pediatric dataset would fill a significant gap that currently prevents description of gene and gene-by-age effects on neural architecture in children (i.e., main effects of genetic variation and gene effects on developmental trajectories) that are likely to be relevant to variability in behavioral and neuropsychiatric outcomes. Preliminary results of analyses of large adult cohorts suggest that common genetic variation accounts for substantial variability in brain morphology. The age-span of participants in these studies has made it possible to detect gene-by-age interactions relevant to variability in brain aging. Unfortunately because there are no well-powered studies with data from individuals spanning the childhood and adolescent age range, it is not known whether these neural phenotypes are present in children;and if they are, whether they can be observed early in development or evolve as ongoing remodeling of neural structures proceeds during childhood. This project would address the discrepancy between currently available imaging-genetics data in children of different ages and those available in adults. In addition to providing an informative data resource, the project would create a collaborative hub of investigators prepared to participate in an imaging- genomics adjunct study of the National Children's Study, which is in the early planning stages at this time.

Public Health Relevance

The aim of this project is to assemble, over a period of 2 years, a large, cross-sectional imaging-genomics dataset to be used as a shared resource for investigations of genetic bases of neural phenotypes and age-by- genotype interactions that may represent genetically-mediated differences in developmental trajectories.

Agency
National Institute of Health (NIH)
Institute
National Institute on Drug Abuse (NIDA)
Type
High Impact Research and Research Infrastructure Programs (RC2)
Project #
1RC2DA029475-01
Application #
7855514
Study Section
Special Emphasis Panel (ZRG1-BDCN-W (99))
Program Officer
Boyce, Cheryl A
Project Start
2009-09-30
Project End
2011-08-31
Budget Start
2009-09-30
Budget End
2010-08-31
Support Year
1
Fiscal Year
2009
Total Cost
$4,497,885
Indirect Cost
Name
University of California San Diego
Department
Pediatrics
Type
Schools of Arts and Sciences
DUNS #
804355790
City
La Jolla
State
CA
Country
United States
Zip Code
92093
Merz, Emily C; He, Xiaofu; Noble, Kimberly G et al. (2018) Anxiety, depression, impulsivity, and brain structure in children and adolescents. Neuroimage Clin 20:243-251
Brito, Natalie H; Noble, Kimberly G; Pediatric Imaging, Neurocognition, Genetics Study (2018) The independent and interacting effects of socioeconomic status and dual-language use on brain structure and cognition. Dev Sci 21:e12688
Faghiri, Ashkan; Stephen, Julia M; Wang, Yu-Ping et al. (2018) Changing brain connectivity dynamics: From early childhood to adulthood. Hum Brain Mapp 39:1108-1117
Nemmi, Federico; Schel, Margot A; Klingberg, Torkel (2018) Connectivity of the Human Number Form Area Reveals Development of a Cortical Network for Mathematics. Front Hum Neurosci 12:465
Pan, Jessica; Sawyer, Kayle; McDonough, EmilyKate et al. (2018) Cognitive, Neuroanatomical, and Genetic Predictors of Executive Function in Healthy Children and Adolescents. Dev Neuropsychol 43:535-550
Merz, Emily C; Tottenham, Nim; Noble, Kimberly G (2018) Socioeconomic Status, Amygdala Volume, and Internalizing Symptoms in Children and Adolescents. J Clin Child Adolesc Psychol 47:312-323
Wierenga, Lara M; van den Heuvel, Martijn P; Oranje, Bob et al. (2018) A multisample study of longitudinal changes in brain network architecture in 4-13-year-old children. Hum Brain Mapp 39:157-170
Curley, Lauren B; Newman, Erik; Thompson, Wesley K et al. (2018) Cortical morphology of the pars opercularis and its relationship to motor-inhibitory performance in a longitudinal, developing cohort. Brain Struct Funct 223:211-220
Sepehrband, Farshid; Lynch, Kirsten M; Cabeen, Ryan P et al. (2018) Neuroanatomical morphometric characterization of sex differences in youth using statistical learning. Neuroimage 172:217-227
Cheema, Kulpreet; Cummine, Jacqueline; for the Pediatric Imaging, Neurocognition, and Genetics Study (2018) The Relationship between White Matter and Reading Acquisition, Refinement and Maintenance. Dev Neurosci 40:209-222

Showing the most recent 10 out of 100 publications