Validation of a translatable chronobiological signature of early relapse in bipolar disorder

The aim of this multi-national project is to provide a quantum advance in understanding the mechanisms of sleep and circadian rhythm disruption amongst people with established bipolar disorder (BD). Our methodological focus is a high-resolution signal of specific relevance to BD - the 24-hour rest-activity rhythm as measured by actigraphy. Across four work packages, distinct sleep and circadian features from this signal will be parsed through a machine learning approach called network analysis, and validated as a predictor of early relapse amongst inter-episode patients (Study 1 Australia), as a covariate of recovery from acute manic and depressive illness (Study 2 New Zealand), and as a proxy of endogenous circadian pathogenesis of BD (Study 3 India). In the integrative Work Package 4, findings from these complementary investigations will be cross-validated and synthesised into a theoretically and empirically grounded chronobiological signature of early relapse in BD. This biosignature could be the basis for a future automated early warning technology for BD (our long-term goal). Work Package 4 will also generate a new multi-national dataset and data processing pipelines to be shared with future researchers. Our multi-disciplinary team is uniquely qualified to undertake this project in collaboration with our long-standing lived experience collaborators.