Progress in establishing the etiology of psychiatric illness is limited by the absence of objective biological measures able to detect and discriminate between disorders. This problem is particularly important in developmental disorders, where early identification could eventually assist in prevention of lifelong impairments. The two earlies onsets, most common and costly developmental disorders in child psychiatry are attention deficit hyperactivity disorder (ADHD) and Autism spectrum disorders (ASD). A recent 2011 study, surveying the years 1997-2008, has now verified that 1 in 6 children have a developmental disability, a 17% increase over the past decade driven largely by increases in ASD and ADHD. These developments highlight the need for innovative approaches to address the underlying cause of these disorders. It is likely that the clinical heterogeneity and the imprecise nature of their nosological distinctions represent fundamentally confounding factors limiting a better understanding of their etiology, prevention, and treatment. Interestingly, an emerging observation regarding brain imaging in ASD and ADHD is that they often have the same atypical functional brain signatures. However, because these two syndromes are almost exclusively studied separately, it is difficult to determine atypical brain function that is common compared to what is distinct for each disorder. If we are to improve our understanding regarding the underlying etiology of these disorders, it will be necessary to study these populations simultaneously. With that said, simply comparing groups of children based on their DSM diagnosis is unlikely to suffice. The behavioral and biological heterogeneity within each syndrome further complicates the meaning of any given group difference found in brain imaging. Thus, progress in our understanding requires not only examining these disorders in the same studies, but also identifying how brain signatures relate to distinct behavioral components (i.e., endophenotypes) that span the syndromes. Under this context, and consistent with NIMH's new strategic plan, Strategy 1.4 (also see RDoC), the current proposal aims to use resting state functional connectivity MRI (rs-fcMRI) and structural connectivity (DTI) to identify brain signatures that correspond to fundamental behavioral components (executive, facial recognition, and affect recognition) found in ADHD and/or ASD. We also aim to develop integrated, multimodal sub-classifications (i.e. neurotypes) or """"""""biosignatures"""""""" of these disorders with computational tools that include Graph Theory and support vector machine (SVM) based pattern classification. The potential impact of the proposed mechanistic categorization on future functional, genetic, treatment, and other translational studies of ADHD and ASD are substantial.

Public Health Relevance

The proposed study uses relatively new and advanced imaging techniques (i.e. resting-state functional connectivity MRI, and diffusion tensor imaging), along with computational tools (i.e. Graph theory and pattern classification) to identify atypical brain physiology that is unique and shared across ADHD and Autism. The work will also advance new approaches and methods to classify these disorders based on specific behavioral and neurobiological measures. The result from this study will advance our knowledge regarding the neurobiological underpinnings of ADHD and Autism, and assist in the improved characterization of homogeneous subtypes of future genetic, functional, and therapeutic investigations.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Research Project (R01)
Project #
5R01MH096773-03
Application #
8663311
Study Section
Child Psychopathology and Developmental Disabilities Study Section (CPDD)
Program Officer
Friedman-Hill, Stacia
Project Start
2012-08-06
Project End
2018-05-31
Budget Start
2014-06-01
Budget End
2015-05-31
Support Year
3
Fiscal Year
2014
Total Cost
$561,952
Indirect Cost
$197,048
Name
Oregon Health and Science University
Department
Psychiatry
Type
Schools of Medicine
DUNS #
096997515
City
Portland
State
OR
Country
United States
Zip Code
97239
Dickie, Erin W; Ameis, Stephanie H; Shahab, Saba et al. (2018) Personalized Intrinsic Network Topography Mapping and Functional Connectivity Deficits in Autism Spectrum Disorder. Biol Psychiatry 84:278-286
Mills, Brian D; Grayson, David S; Shunmugavel, Anandakumar et al. (2018) Correlated Gene Expression and Anatomical Communication Support Synchronized Brain Activity in the Mouse Functional Connectome. J Neurosci 38:5774-5787
Rudolph, Marc D; Graham, Alice M; Feczko, Eric et al. (2018) Maternal IL-6 during pregnancy can be estimated from newborn brain connectivity and predicts future working memory in offspring. Nat Neurosci 21:765-772
Anandakumar, Jeya; Mills, Kathryn L; Earl, Eric A et al. (2018) Individual differences in functional brain connectivity predict temporal discounting preference in the transition to adolescence. Dev Cogn Neurosci 34:101-113
Xu, Ting; Falchier, Arnaud; Sullivan, Elinor L et al. (2018) Delineating the Macroscale Areal Organization of the Macaque Cortex In Vivo. Cell Rep 23:429-441
Greene, Deanna J; Koller, Jonathan M; Hampton, Jacqueline M et al. (2018) Behavioral interventions for reducing head motion during MRI scans in children. Neuroimage 171:234-245
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
Feczko, E; Balba, N M; Miranda-Dominguez, O et al. (2018) Subtyping cognitive profiles in Autism Spectrum Disorder using a Functional Random Forest algorithm. Neuroimage 172:674-688
Karalunas, Sarah L; Hawkey, Elizabeth; Gustafsson, Hanna et al. (2018) Overlapping and Distinct Cognitive Impairments in Attention-Deficit/Hyperactivity and Autism Spectrum Disorder without Intellectual Disability. J Abnorm Child Psychol 46:1705-1716
Graham, Alice M; Rasmussen, Jerod M; Rudolph, Marc D et al. (2018) Maternal Systemic Interleukin-6 During Pregnancy Is Associated With Newborn Amygdala Phenotypes and Subsequent Behavior at 2 Years of Age. Biol Psychiatry 83:109-119

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