Do physiological triggers of Major Depressive Disorder fluctuate over multiday cycles?
Poster No:
509
Submission Type:
Abstract Submission
Authors:
Jodie Naim-Feil1,2, Rachel Stirling1,2, Shivam Puri1,2, Rochelle De Silva1,2, Luca Cocchi3, Lachlan Webb3, Robin Cash1,4, Andrew Zalesky1,4, Mark Cook5,2, Philippa Karoly1,2
Institutions:
1Department of Biomedical Engineering, University of Melbourne, Melbourne, Australia, 2Graeme Clark Institute, University of Melbourne, Melbourne, Australia, 3Clinical Brain Networks Group, QIMR Berghofer, Brisbane, Australia, 4Melbourne Neuropsychiatry Centre, The University of Melbourne, Melbourne, Australia, 5Department of Medicine, St. Vincent’s Hospital Melbourne, University of Melbourne, Melbourne, Australia
First Author:
Jodie Naim-Feil, PhD
Department of Biomedical Engineering, University of Melbourne|Graeme Clark Institute, University of Melbourne
Melbourne, Australia|Melbourne, Australia
Department of Biomedical Engineering, University of Melbourne|Graeme Clark Institute, University of Melbourne
Melbourne, Australia|Melbourne, Australia
Co-Author(s):
Rachel Stirling, PhD, MEng, BSc
Department of Biomedical Engineering, University of Melbourne|Graeme Clark Institute, University of Melbourne
Melbourne, Australia|Melbourne, Australia
Department of Biomedical Engineering, University of Melbourne|Graeme Clark Institute, University of Melbourne
Melbourne, Australia|Melbourne, Australia
Shivam Puri
Department of Biomedical Engineering, University of Melbourne|Graeme Clark Institute, University of Melbourne
Melbourne, Australia|Melbourne, Australia
Department of Biomedical Engineering, University of Melbourne|Graeme Clark Institute, University of Melbourne
Melbourne, Australia|Melbourne, Australia
Rochelle De Silva
Department of Biomedical Engineering, University of Melbourne|Graeme Clark Institute, University of Melbourne
Melbourne, Australia|Melbourne, Australia
Department of Biomedical Engineering, University of Melbourne|Graeme Clark Institute, University of Melbourne
Melbourne, Australia|Melbourne, Australia
Robin Cash, PhD
Department of Biomedical Engineering, University of Melbourne|Melbourne Neuropsychiatry Centre, The University of Melbourne
Melbourne, Australia|Melbourne, Australia
Department of Biomedical Engineering, University of Melbourne|Melbourne Neuropsychiatry Centre, The University of Melbourne
Melbourne, Australia|Melbourne, Australia
Andrew Zalesky
Department of Biomedical Engineering, University of Melbourne|Melbourne Neuropsychiatry Centre, The University of Melbourne
Melbourne, Australia|Melbourne, Australia
Department of Biomedical Engineering, University of Melbourne|Melbourne Neuropsychiatry Centre, The University of Melbourne
Melbourne, Australia|Melbourne, Australia
Mark Cook
Department of Medicine, St. Vincent’s Hospital Melbourne, University of Melbourne|Graeme Clark Institute, University of Melbourne
Melbourne, Australia|Melbourne, Australia
Department of Medicine, St. Vincent’s Hospital Melbourne, University of Melbourne|Graeme Clark Institute, University of Melbourne
Melbourne, Australia|Melbourne, Australia
Philippa Karoly, PhD
Department of Biomedical Engineering, University of Melbourne|Graeme Clark Institute, University of Melbourne
Melbourne, Australia|Melbourne, Australia
Department of Biomedical Engineering, University of Melbourne|Graeme Clark Institute, University of Melbourne
Melbourne, Australia|Melbourne, Australia
Introduction:
Major Depressive Disorder (MDD) is a debilitating, and often chronic condition characterized by recurrent episodes. While a range of triggers (stress, brain excitability, hormones, sleep) for depressive episodes are well-documented, limited research exists on whether these triggers fluctuate over longer-term patterns (spanning weeks, months, years). Advances in neural-engineering techniques (developed in the field of Epilepsy) led to the development of a mathematical framework capable of capturing these longer-term physiological rhythms (Karoly et al., 2021a). These individual-specific biological rhythms (multiday cycles) exhibit almost periodic, cyclic patterns and are detectable via wearable sensors (Karoly et al., 2021b), however are yet to be explored within a psychiatric cohort. The integration of wearable sensor data with cognitive/brain and hormonal measurements, alongside clinical/mood assessments will provide previously unattainable insight into an individuals' personalised NeuroRhythmo profile. This profile will map the long-term fluctuations in triggers, enabling assessment of how these triggers interact with periods of increased symptom risk. In the first step towards piloting this innovative NeuroRhythmo framework within a psychiatric cohort, this study explored whether 'trigger' features such as stress and hormones fluctuate over multiday cycles, followed by an assessment of the presence of these multiday cycles within a cohort of MDD patients and whether brain excitability measures (in MDD) fluctuate over these multiday cycles.
Methods:
At baseline, physiological features such as heart rate, wrist temperature and sleep patterns (continuously monitored via a wearable device such as a smartwatch) are collected for up to 6-months. Mathematical signal processing techniques, including continuous wavelet transform, are then applied to extract long-term physiological rhythms (Karoly et al., 2021b; Baud et al., 2018), with significant cycles identified as peaks in the periodogram. Once robust multiday cycles are identified, it is possible to index changes in cognition, cortical excitability (using brain stimulation protocols for brain mapping) and hormonal features (salivary cortisol) at different phases (peak, trough, etc.) of the multiday cycle (demonstrated in Figure 1).
·Figure 1. NeuroRhythmo pipeline
Results:
Early results from this study show that stress, hormones, and brain excitability fluctuate over multiday cycles. Multiday cycles were extracted from wearable data collected over 12 months with stress features assessed at 4-timepoints (peak/trough of multiday cycles) in 15 individuals and cortisol levels indexed via 24-salivary cortisol samples in 3 individuals (see Figure 2A), both stress and cortisol fluctuated over multiday heart rate cycles. In 6 patients diagnosed with MDD, robust multiday cycles in wrist temperature were identified from up to 2 months of wearable data (see Figure 2B). From the MDD cohort, 1 patient had brain excitability (resting motor threshold following brain stimulation) mapped at 4-timepoints over the multiday cycle, with a similar brain response observed when brain excitability was measured at the same phase of the multiday cycle.
·Figure 2. Physiological features and multiday cycles
Conclusions:
This study provides preliminary evidence that 'triggers' such as stress, hormones, and brain excitability fluctuate over multiday cycles, with multiday patterns observed in patients with MDD. This research introduces an innovative approach for extracting multiday cycles and establishes a robust protocol for mapping how trigger features oscillate over these longer-term rhythms. Successfully integrating wearable sensor data with a range of physiological/neural measurements marks a significant step forward in the methodology required to develop personalised NeuroRhythmo profiles. Development of this innovative model within MDD holds promise for identifying novel, long-term biomarkers of symptom risk, while offering insight into physiological and neural rhythms previously inaccessible with traditional approaches.
Disorders of the Nervous System:
Psychiatric (eg. Depression, Anxiety, Schizophrenia) 1
Modeling and Analysis Methods:
Exploratory Modeling and Artifact Removal
Methods Development 2
Physiology, Metabolism and Neurotransmission:
Neurophysiology of Imaging Signals
Keywords:
Cortex
Modeling
Psychiatric Disorders
Other - Brain rhythms
1|2Indicates the priority used for review
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Provide references using APA citation style.
Karoly, P. J., Rao, V. R., Gregg, N. M., Worrell, G. A., Bernard, C., Cook, M. J., & Baud, M. O. (2021). Cycles in epilepsy. Nature reviews. Neurology, 17(5), 267–284
Karoly PJ, Stirling RE, Freestone DR, Nurse ES, Maturana MI, Halliday AJ, et al. (2021). Multiday cycles of heart rate are associated with seizure likelihood: An observational cohort study. EBioMedicine.1;72