ADHD is has long been believed to include brain-based pathophysiology, but the newest approaches to describing atypical brain organization in ADHD are just emerging and are thus far limited to cross-sectional studies. The present study has as its principal aims three objectives. First, it aims to characterize ADHD's brain organization longitudinally from childhood through adolescence, during a period of time in which ADHD youth enter very high risk for negative life outcomes, poor health outcomes, and comorbid behavioral, mood, and substance use disorders. In particular, the project aims to determine specified circuits, unique brain networks, and brain wide topological properties that relate to clinical course and outcome. Second, the proposal aims to bridge these developmental brain features with an enriched conception of phenotype, examining symptom domains, comorbidity, and measures of executive, reward, and emotional functioning in relation to specified brain metrics and targets. Third, it seeks to move the field forward in regard to clinica prediction by considering heterogeneity in two ways. One way is to examine novel typologies of ADHD based on differential brain organization across development. The other way is to utilize multiple methods to enhance prediction of clinical course. The significance of this effort lies bot in its unprecedented ability to characterize ADHD neurobiology over time with methods of brain characterization that have not been examined in ADHD longitudinally in this way before, and in its effort to move brain imaging into the realm of clinical prediction using a longitudinal design. The project is innovative in regard to implementing network and topology features of brain analysis in a multi-wave design, and tightly linking these to well defined, multi-level clinical course. The approach entails tracking of an already developed novel cohort of 376 children in a cross-lagged longitudinal design, enabling characterization of development from age 7-19 years. Brain organization will be operationalized with both diffusion tensor imaging and resting state functional connectivity. Youth will be characterized annually in relation to clinical symptoms, comorbidity, impairment, cognitive functioning, reward discounting, and emotion regulation and functioning. Analytic approaches will span brain circuit, network, and topological measurements using novel graph theoretical analyses to characterize brain systems. Clinical prediction will be undertaken using machine learning methodologies. Clinical typologies will be evaluated using both novel community detection procedures and more standard mixture model analysis of brain features. Finally, latent class trajectory models will be used to identify distint developmental types of ADHD if they exist. The prior grant period has been productive and this work builds on those findings to strengthen inference regarding the relation of brain organization to ADHD clinical features, course, and outcome.
The Aims directly match key priorities of the NIMH strategic plan. If successful, the project hopes to break the impasse facing the field with regard to clinical utility of the growing grasp of atypical brain physiology in ADHD.

Public Health Relevance

Much has been learned about brain correlates of ADHD, but this work has not yet affected clinical practice. The present project would characterize individual variation in ADHD brain development and attempt to use those findings to enhance clinical prediction. It thus aims to move the field closer to clinical application of brain imaging information of ADHD.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
High Priority, Short Term Project Award (R56)
Project #
2R56MH086654-06A1
Application #
9208912
Study Section
Special Emphasis Panel (ZRG1-BBBP-X (02))
Program Officer
Friedman-Hill, Stacia
Project Start
2009-07-01
Project End
2017-02-28
Budget Start
2016-03-18
Budget End
2017-02-28
Support Year
6
Fiscal Year
2016
Total Cost
$769,969
Indirect Cost
$269,989
Name
Oregon Health and Science University
Department
Psychiatry
Type
Schools of Medicine
DUNS #
096997515
City
Portland
State
OR
Country
United States
Zip Code
97239
Kong, Xiang-Zhen; Mathias, Samuel R; Guadalupe, Tulio et al. (2018) Mapping cortical brain asymmetry in 17,141 healthy individuals worldwide via the ENIGMA Consortium. Proc Natl Acad Sci U S A 115:E5154-E5163
Rudolph, Marc D; Miranda-Domínguez, Oscar; Cohen, Alexandra O et al. (2017) At risk of being risky: The relationship between ""brain age"" under emotional states and risk preference. Dev Cogn Neurosci 24:93-106
Grayson, David S; Fair, Damien A (2017) Development of large-scale functional networks from birth to adulthood: A guide to the neuroimaging literature. Neuroimage 160:15-31