ADHD is a major public health problem with severe long term outcomes. Existing treatments do not achieve long term change, which has increased the urgency of discovering biomarkers, biological bases of heterogeneity, and developmental specificity of effects. The proposed project would test focused theories of aberrant developmental organization of brain networks in ADHD in a longitudinal design. It would also seek to identify subtypes of ADHD based on brain networks. Two latest-generation methods will be utilized: Diffusion tensor imaging (DTI) and functional connectivity MRI (fcMRI). Use of these methods is directly in line with the NIH Human Connectome guidelines, so the data set will also serve as a resource in the eventual creation of a child connectome. A total of 490 children age 7-10 would be enrolled prior to data loss to attrition and motion artifact. They will be followed annually in three waves, yielding an age based accelerated longitudinal design spanning ages 7-12 years. 70% of the sample will have ADHD (all subtypes) and 30% will be typically developing comparison youth. Community- based recruitment is emphasized so that some treatment naove scans will be obtained. Clinical change, treatment use, and psychosocial moderators will be tracked. Selected cognitive measures will be used to cross validate clinical findings and determine whether mechanistic suppositions about brain circuits hold at the cognitive level of analysis. The major innovations in this project are: (a) evaluates ADHD as a dynamic entity rather than a static phenomenon, (b) the first longitudinal study of functional connectivity or DTI in ADHD, (c) combines functional and structural connectivity measures in ADHD, (d) introduces sophisticated usage of graph theory in order to determine biological subtypes of ADHD based on brain networks. The major significance is that it will enable new discoveries about brain networks in ADHD that can enable significant advances in describing neurobiological markers of liability (those that persist regardless of symptom change) and markers of course of illness (those that are acutely sensitive to phenotypic change or predict outcome or treatment response). Those data can inform new models of assessment, individualized treatments, and treatment monitoring. If the project is successful it will represent an important step forward in mapping integrative, paradigmatic models of ADHD mechanism using the newest insights about brain development.

Public Health Relevance

ADHD is a costly disorder. Understanding of causes has been hampered by inconsistent findings on brain imaging due to the variability that ADHD exhibits across cases and across time. The present study will identify specific brain networks that are altered in ADHD and track these changes over time. The results are intended to identify clear markers of ADHD in the brain that endure over time, as well as to identify subtypes of ADHD based on brain network involvement.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Research Project (R01)
Project #
5R01MH086654-03
Application #
8288320
Study Section
Child Psychopathology and Developmental Disabilities Study Section (CPDD)
Program Officer
Friedman-Hill, Stacia
Project Start
2010-07-20
Project End
2015-02-28
Budget Start
2012-03-01
Budget End
2013-02-28
Support Year
3
Fiscal Year
2012
Total Cost
$667,856
Indirect Cost
$234,183
Name
Oregon Health and Science University
Department
Psychiatry
Type
Schools of Medicine
DUNS #
096997515
City
Portland
State
OR
Country
United States
Zip Code
97239
Gates, Kathleen M; Molenaar, Peter C M; Iyer, Swathi P et al. (2014) Organizing heterogeneous samples using community detection of GIMME-derived resting state functional networks. PLoS One 9:e91322
Di Martino, A; Yan, C-G; Li, Q et al. (2014) The autism brain imaging data exchange: towards a large-scale evaluation of the intrinsic brain architecture in autism. Mol Psychiatry 19:659-67
Ray, Siddharth; Miller, Meghan; Karalunas, Sarah et al. (2014) Structural and functional connectivity of the human brain in autism spectrum disorders and attention-deficit/hyperactivity disorder: A rich club-organization study. Hum Brain Mapp 35:6032-48
Karalunas, Sarah L; Fair, Damien; Musser, Erica D et al. (2014) Subtyping attention-deficit/hyperactivity disorder using temperament dimensions: toward biologically based nosologic criteria. JAMA Psychiatry 71:1015-24
dos Santos Siqueira, Anderson; Biazoli Junior, Claudinei Eduardo; Comfort, William Edgar et al. (2014) Abnormal functional resting-state networks in ADHD: graph theory and pattern recognition analysis of fMRI data. Biomed Res Int 2014:380531
Grayson, David S; Ray, Siddharth; Carpenter, Samuel et al. (2014) Structural and functional rich club organization of the brain in children and adults. PLoS One 9:e88297
Karalunas, Sarah L; Geurts, Hilde M; Konrad, Kerstin et al. (2014) Annual research review: Reaction time variability in ADHD and autism spectrum disorders: measurement and mechanisms of a proposed trans-diagnostic phenotype. J Child Psychol Psychiatry 55:685-710
Alaerts, Kaat; Woolley, Daniel G; Steyaert, Jean et al. (2014) Underconnectivity of the superior temporal sulcus predicts emotion recognition deficits in autism. Soc Cogn Affect Neurosci 9:1589-600
Iyer, Swathi P; Shafran, Izhak; Grayson, David et al. (2013) Inferring functional connectivity in MRI using Bayesian network structure learning with a modified PC algorithm. Neuroimage 75:165-75
Costa Dias, Taciana G; Wilson, Vanessa B; Bathula, Deepti R et al. (2013) Reward circuit connectivity relates to delay discounting in children with attention-deficit/hyperactivity disorder. Eur Neuropsychopharmacol 23:33-45

Showing the most recent 10 out of 13 publications