1. BrainAge of patients with severe late-life depression referred for electroconvulsive therapy
- Author
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Margot J. Wagenmakers, Mardien L. Oudega, Federica Klaus, David Wing, Gwendolyn Orav, Laura K.M. Han, Julia Binnewies, Aartjan T.F. Beekman, Dick J. Veltman, Didi Rhebergen, Eric van Exel, Lisa T. Eyler, Annemieke Dols, Psychiatry, APH - Aging & Later Life, Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep, APH - Mental Health, Anatomy and neurosciences, Amsterdam Neuroscience - Brain Imaging, Amsterdam Neuroscience - Neurodegeneration, Central Academic Services, and Faculty of Physical Education and Physical Therapy
- Subjects
Psychiatry and Mental health ,Clinical Psychology - Abstract
BACKGROUND: Severe depression is associated with accelerated brain aging. BrainAge gap, the difference between predicted and observed BrainAge was investigated in patients with late-life depression (LLD). We aimed to examine BrainAge gap in LLD and its associations with clinical characteristics indexing LLD chronicity, current severity, prior to electroconvulsive therapy (ECT) and ECT outcome. METHODS: Data was analyzed from the Mood Disorders in Elderly treated with Electroconvulsive Therapy (MODECT) study. A previously established BrainAge algorithm (BrainAge R by James Cole, (https://github.com/james-cole/brainageR)) was applied to pre-ECT T1-weighted structural MRI-scans of 42 patients who underwent ECT. RESULTS: A BrainAge gap of 1.8 years (SD = 5.5) was observed, Cohen's d = 0.3. No significant associations between BrainAge gap, number of previous episodes, current episode duration, age of onset, depression severity, psychotic symptoms or ECT outcome were observed. LIMITATIONS: Limited sample size. CONCLUSIONS: Our initial findings suggest an older BrainAge than chronological age in patients with severe LLD referred for ECT, however with high degree of variability and direction of the gap. No associations were found with clinical measures. Larger samples including are needed to better understand brain aging and to evaluate the usability of BrainAge gap as potential biomarker of prognosis an treatment-response in LLD. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT02667353.
- Published
- 2023
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