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Category: Project

Description: Objective: We used data-driven approaches to identify subgroups of individuals with bipolar disorders (BDs) based on mood instability, identified biopsychosocial predictors of mood instability, and determined whether mood instability predicted future outcomes. Methods: Data from the Prechter Longitudinal Study of Bipolar Disorder was used. Mood was assessed every two months (PHQ, ASRM) over five years, and clinical and functioning outcomes were assessed in year six. Results: Among 481 participants, low, moderate, and high mood instability classes were identified. Neuroticism, sleep quality, childhood emotional neglect and physical abuse, stimulant abuse, hypomania age of onset, and number of depressive episodes were the most influential predictors. Being in the high instability class (based on mood from years 1-5) predicted greater suicidal ideation and functional impairment in year six. Conclusion: Here we show that mood instability represents a core phenotype of BD with distinct predictors and long-term implications. Routine assessment may improve personalization in BD treatment and research.