As many as 25% of all children have tics (brief, repetitive movements or noises) at some point, yet individuals have greatly varying prognoses. Even within the first year after tic onset, some children improve and experience no significant impairment, while others develop a chronic disorder (Tourette syndrome: TS) that can severely impinge upon their quality of life. Understanding the brain features present early in the course of TS that mediate or predict these different outcomes could revolutionize prognosis and treatment. The purpose of this Mentored Research Scientist Development Award (K01) is to provide the applicant with the training necessary to transition to independence with a research program focused on the brain mechanisms underlying TS and related disorders (e.g., attention-deficit/hyperactivity disorder: ADHD, obsessive-compulsive disorder: OCD). The applicant's long-term goal is to identify predictive biomarkers that can help guide prognosis and treatment. In order to achieve such goals, the applicant will receive unparalleled mentorship by experts in TS and neuroimaging methodologies (Drs. K. Black, B. Schlaggar, E. Sowell, R. Poldrack, and T. Hershey) and will have access to superb clinical and imaging resources at Washington University. The proposed training plan will enable the applicant to achieve several short-term goals necessary to facilitate her long-term goals, including new training in structural MRI methods, advanced analytic strategies, and longitudinal study design, and continued training in resting state functional connectivity MRI and in the clinical aspects of TS and its comorbid conditions. These training goals will be advanced through the proposed research. First, supervised learning methods will be used to identify patterns of brain structure and function that can classify an individual child as having TS or not, providing a principled starting point for exploring predictive biomarkers (Aim 1). Second, unsupervised learning methods will be used to identify brain-based phenotypic subgroups of TS, helping to better account for the heterogeneity of TS (Aim 2). Finally, supervised learning methods will be used to predict symptom progression for children when they first present with tics, using longitudinal follow-up of children during ther first year after tic onset (Aim 3). Thus, the proposed project is a first step toward brain- based individualized predictions for children with tics. Notably, the proposed methods can be extended to other childhood neuropsychiatric disorders (e.g., autism, ADHD), setting the stage for early treatment, as well as discovery of the underlying mechanisms. The longitudinal data collected as part of this award will be foundational for future R01 applications targeting the developmental trajectory of TS. The training and research plan proposed in this application will facilitate the applicant's transition to a unique and independent research career in translational developmental neuroscience. With a research program that employs multiple converging techniques and analysis methods to interrogate biomarkers of TS and related disorders, the applicant will continue to address research questions relevant to the NIMH throughout her independent career.
Up to 25% of all children have tics (i.e., repetitive, purposeless movements or noises) at some point, yet these individuals have tremendously varying prognoses. Within the first year after tic onset, some children experience marked improvement and no significant impairment, while others develop a chronic disorder that can severely impinge upon their quality of life. Therefore, tic disorders, including Tourette syndrome (TS), would benefit highly from individualized predictions. Understanding the brain features present early in the course of TS that mediate or predict different outcomes could revolutionize prognosis and treatment. The proposed project is a first step toward brain-based individualized predictions for children with tics. More generally, the proposed methods may give insights into how to approach other neurodevelopmental disorders such as autism or attention-deficit/hyperactivity disorder (ADHD).
|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|
|Gordon, Evan M; Laumann, Timothy O; Gilmore, Adrian W et al. (2017) Precision Functional Mapping of Individual Human Brains. Neuron 95:791-807.e7|
|Greene, D J; Williams Iii, A C; Koller, J M et al. (2017) Brain structure in pediatric Tourette syndrome. Mol Psychiatry 22:972-980|
|Greene, Deanna J; Church, Jessica A; Dosenbach, Nico U F et al. (2016) Multivariate pattern classification of pediatric Tourette syndrome using functional connectivity MRI. Dev Sci 19:581-98|
|Greene, Deanna J; Black, Kevin J; Schlaggar, Bradley L (2016) Considerations for MRI study design and implementation in pediatric and clinical populations. Dev Cogn Neurosci 18:101-12|
|Greene, Deanna J; Schlaggar, Bradley L; Black, Kevin J (2015) Neuroimaging in Tourette Syndrome: Research Highlights From 2014-2015. Curr Dev Disord Rep 2:300-308|
|Schechter, Jacqueline R; Greene, Deanna J; Koller, Jonathan M et al. (2014) A revised method for measuring distraction by tactile stimulation. F1000Res 3:188|