Modeling Mood Instability in Bipolar Disorder

As a first step towards precision medicine approaches in bipolar disorder, this project aims to (1) model longitudinal patterns of mood in bipolar disorder, identifying illness phenotypes based on intraindividual mood dynamics, and (2) discover biopsychosocial predictors of such illness phenotypes. We will do so in a unique cohort of patients with bipolar disorder that have been followed for approximately 10 years, integrating repeated and extensive clinical, biological, neurocognitive, personality, and functional assessments with electronic health records to maximize a data-driven approach to identify clinically relevant phenotypes. Results from this study have the potential to inform individualized treatment planning and better risk prognostication in those with bipolar disorder. For example, if an individual has a set of risk factors that are associated with a more severe and turbulent longitudinal course of mood, those risk factors may be targeted first via psychopharmacology, novel intervention approaches (e.g., neuromodulation), and cognitive and behavioral interventions. This project is led by Dr. Sarah Sperry and was funded through the Brain and Behavior Research Foundation (BBRF) Young Investigator Award.