Brain Circuitry Analysis in Bipolar Disorder

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PROJECT SUMMARY/ABSTRACT Bipolar disorder (BD) is a mood disorder in which patients experience mania or hypomania that cycles between episodes of major depression. Even with all currently available therapies, high rates of relapse into manic and/ or depressive states persist throughout the course of the disease. Ultimately, the early onset and chronicity of illness cause BD to be a major chronic disorder of young people and a leading cause of disability worldwide. Emerging data from the investigators of this proposal, which are supported by the literature, suggest that abnormal brain circuitry plays a role in the pathophysiology BD. However, a comprehensive understanding of the specific neural networks associated with BD is still needed. This project aims to characterize brain circuitry in BD subjects to gain insight into the etiology of the disorder, possibly aiding in diagnosis and in the development of new therapies, including surgical interventions such as deep brain stimulation (DBS). The proposed study will investigate white matter (WM) pathways using MR diffusion-weighted imaging based tractography (DWT) in three groups of subjects: Treatment-Refractory BD (REF-BD), Treatment-Responsive BD (RSP-BD), and Healthy Controls (HC). The overall approach will build upon the preliminary data conducted by the investigators, which found that connectivity differences in the brain exist between BD subjects and HCs, as well as between REF-BD and RSP-BD subjects. These findings indicate that specific neural networks may underlie BD, and that phenotypic differences between BD subjects may be identifiable on DWT. Understanding and delineating these pathways more comprehensively will shed light on the anatomical substrate of BD and may facilitate patient diagnosis and guide treatment strategies. The unique, subspecialty expertise of the study team will be employed to carry out three specific aims: 1) Use patient-specific neuroimaging (DWT) to further describe the WM anatomy of brain networks in BD subjects compared to HCs. This will build upon the pilot data using high quality DW datasets, a large sample size, and controlling for psychoactive medications. Findings will improve our understanding of the complex brain circuitry involved in BD; 2) Correlate clinical features of BD (using psychiatric, eye-tracking, and neuropsychological assessments) to DWT data. Results may identify distinct connectivity biomarkers for BD phenotypes, possibly aiding in patient diagnosis and treatment; and 3) Explore the effects of stimulation on implicated WM tracts, using computer modeling and DWT, to investigate DBS as a potential therapy for BD patients in the future.