Abstract The recurrent and often unpredictable course of affective disorders poses a critical challenge for long-term patient care. The CRC/TRR 393 consortium has established an ambitious longitudinal study, the German Mental Health Cohort (GEMCO), to systematically investigate the trajectories of symptom recurrence and remission in affective disorders. This article provides an overview of the core structural projects of the CRC/TRR 393 consortium that underpin this effort. Project S02 orchestrates the GEMCO, recruiting 1500 participants (approximately 900 with major depressive disorder, 300 with bipolar disorder, 300 healthy controls) and conducting comprehensive phenotyping, neuroimaging, and biobanking at baseline and follow-up time points. Project S01 provides an innovative mobile health infrastructure for continuous monitoring of patients’ mood, behavior, and environment in real time over a 2-year period, enabling detection of early warning signs (“inflection signals”) of mood episodes. Project INF implements a centralized information infrastructure, ensuring high-quality data capture, multisite data integration, and open-science data sharing. Project S03 serves as the advanced data analysis hub, developing machine learning models to predict individual illness trajectories and outcomes from the rich multimodal data. A research training group (RTG) provides funding and infrastructure for early-career scientists. Together, these structural projects establish a state-of-the-art framework for studying affective disorder trajectories, with the ultimate goal of identifying predictors and mechanisms of relapse and remission, and paving the way toward mechanism-based clinical interventions.
Dannlowski et al. (Wed,) studied this question.
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