U of Cincinnati Bipolar Disorder Imaging & Treatment Research Center (BITREC)

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Bipolar disorder is a dynamic, progressive illness in which treatment decisions are made empirically. Neuroimaging has helped to define neurophysiological models of bipolar disorder that offer the promise of improving treatment assignment by identifying markers and predictors of treatment response and disease progression. We propose the UC Bipolar Disorder Imaging & Treatment Research Center (BITREC) to meet this promise. The overall hypothesis and organizing theme guiding this center is that bipolar disorder results from dysfunctional brain metabolism within specific brain systems (i.e., the anterior limbic network) that can be monitored in response to treatments using magnetic resonance imaging (MRI) and spectroscopy (MRS). In this center, we will integrate MRI and MRS with outcome measures and treatment trials in order to develop specific neurophysiological models of treatment response early in the course of bipolar disorder. These models will provide the means to identify markers and predictors of treatment response to individualize medication prescription, thereby minimizing affective recurrences, preventing disease progression, and improving long-term course of illness. In order to achieve our goals, we will integrate our extensive prior experience and current resources to create specific research and administrative cores; these cores will be used to establish the BITREC infrastructure. With this infrastructure in place, we will recruit a large sample of bipolar patients early in the course of illness (prior to significant illness progression), as well as a cohort of at-risk subjects (adolescents without bipolar disorder, but with bipolar parents). These subjects will be asked to participate in specific projects integrating MRI, MRS, treatment and clinical outcome in order to refine existing models of the neurophysiology of bipolar disorder. We will use these models in order to identify specific neurophysiological markers of treatment response in order to clarify the effects that different medications have on bipolar neurophysiology. We will then use these markers to develop specific neurophysiological predictors of treatment response and illness progression in bipolar disorder. Finally, we will apply these models to at-risk patients (prior to developing a first manic episode) in order to prevent or delay the onset of bipolar disorder.