BrainAge of patients with severe late-life depression referred for electroconvulsive therapy.

J Affect Disord

Amsterdam UMC location Vrije Universiteit Amsterdam, Department of Psychiatry, De Boelelaan 1117, Amsterdam, the Netherlands; Department of Psychiatry, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, the Netherlands and Amsterdam UMC.

Published: June 2023

AI Article Synopsis

  • Researchers looked at how severe depression affects the aging of the brain in older people getting a treatment called ECT.
  • They found that on average, the brains of depressed patients seemed older than their actual ages by about 1.8 years, but the results were pretty varied.
  • They didn’t find any strong links between how old the brain seemed and other factors like how long someone has been depressed or how serious their depression is.

Article 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 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.

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.jad.2023.02.047DOI Listing

Publication Analysis

Top Keywords

brainage gap
20
electroconvulsive therapy
12
brainage
10
patients severe
8
late-life depression
8
brain aging
8
associations clinical
8
gap
6
brainage patients
4
severe late-life
4

Similar Publications

Brain age in genetic and idiopathic Parkinson's disease.

Brain Commun

December 2024

Deutsches Zentrum für Neurodegenerative Erkrankungen (DZNE) Rostock-Greifswald, Rostock 18147, Germany.

The brain-age gap, i.e. the difference between the brain age estimated from structural MRI data and the chronological age of an individual, has been proposed as a summary measure of brain integrity in neurodegenerative diseases.

View Article and Find Full Text PDF

Metabolic Status Modulates Global and Local Brain Age Estimates in Overweight and Obese Adults.

Biol Psychiatry Cogn Neurosci Neuroimaging

November 2024

Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Palo Alto, CA, USA. Electronic address:

Article Synopsis
  • - The study examines how metabolic health impacts brain aging by comparing the predicted brain age from neuroimaging (brainAGE) with actual chronological age in healthy adults.
  • - Researchers used clustering methods on various metabolic markers and found two groups: one with favorable health and one with suboptimal health, the latter showing signs of insulin resistance and older brain aging.
  • - The results indicate that poor metabolic health correlates with faster brain aging, especially in areas of the brain with many insulin receptors, suggesting that improving metabolic health may help maintain brain function and extend healthy living.
View Article and Find Full Text PDF
Article Synopsis
  • - Brain Age Gap is related to dementia in older adults, but its link to dementia risk-factors and cognitive performance in middle-aged individuals is less explored.
  • - A study involving 552 cognitively healthy middle-aged participants showed that brain age gap correlates with factors like hypertension and alcohol intake, but not with genetic risk factors (like the APOE ε4 allele) or cognitive performance.
  • - Findings suggest that addressing modifiable risk factors may help in developing therapies to prevent dementia in middle-aged populations.
View Article and Find Full Text PDF

Disentangling Neurodegeneration From Aging in Multiple Sclerosis Using Deep Learning: The Brain-Predicted Disease Duration Gap.

Neurology

November 2024

From the Queen Square Multiple Sclerosis Centre (G.P., F.P., J.C., B.K., O.A.-M., S.A.-A., A. Bianchi, W.J.B., R. Christensen, E.C., S. Collorone, M.A.F., Y.H., A.H., S. Mohamud, R.N., A.T.T., J.W., C.Y., O.C., F.B.), Department of Neuroinflammation, UCL Queen Square Institute of Neurology, University College London, United Kingdom; MS Center Amsterdam (G.P., H.V., F.B.), Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC location VUmc, the Netherlands; Departments of Advanced Biomedical Sciences and Electrical Engineering and Information Technology (G.P., A. Brunetti, S. Cocozza), University of Naples "Federico II," Italy; Centre for Medical Image Computing (F.P., B.K., F.B.), Department of Medical Physics and Biomedical Engineering, University College London, United Kingdom; E-Health Center (F.P.), Universitat Oberta de Catalunya, Barcelona, Spain; Institute of Neuroradiology (B.B., C.L.), St. Josef Hospital, Ruhr-University Bochum, Germany; Department of Advanced Medical and Surgical Sciences (A. Bisecco, A.G.), University of Campania "Luigi Vanvitelli," Naples, Italy; Translational Imaging in Neurology (ThINK) Basel (A.C., C. Granziera), Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel, University of Basel; Neurologic Clinic and Policlinic (A.C., C. Granziera, J.K.), MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel, University of Basel, Switzerland; Department of Neurosciences, Biomedicine and Movement Sciences (M. Calabrese, M. Castellaro), University of Verona; Department of Information Engineering (M. Castellaro), University of Padova; Department of Medicine, Surgery and Neuroscience (R. Cortese, N.D.S.), University of Siena, Italy; Department of Neurology (C.E., D.P.), Medical University of Graz, Austria; Neuroimaging Research Unit (M.F., M.A.R., P.V.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Neurology Unit, Neurorehabilitation Unit, Neurophysiology Service, IRCCS San Raffaele Scientific Institute; Vita-Salute San Raffaele University (M.F., M.A.R., P.V.), Milan; Department of Neurosciences (C. Gasperini, S.R.), San Camillo-Forlanini Hospital, Rome, Italy; Department of Neurology (G.G.-E., S.G.), Focus Program Translational Neuroscience (FTN) and Immunotherapy (FZI), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Germany; Department of Neurology (H.F.F.H., E.A.H., G.O.N.), Oslo University Hospital; Institute of Clinical Medicine (H.F.F.H., E.A.H., G.O.N.), and Department of Psychology (E.A.H.), University of Oslo, Norway; Neuroimmunology and Multiple Sclerosis Unit Laboratory of Advanced Imaging in Neuroimmunological Diseases (ImaginEM) (S.L., E.M.-H.), Hospital Clinic Barcelona, Fundació de Recerca Clínic Barcelona-Institut d'Investigacions Biomèdiques August Pi i Su, Barcelona, Spain; Department of Neurology (C.L.), St. Josef Hospital, Ruhr-University Bochum, Germany; Nuffield Department of Clinical Neurosciences (S. Messina, J.P.), University of Oxford, United Kingdom; Department of Molecular Medicine and Medical Biotechnology (M.M.), and Department of Neurosciences and Reproductive and Odontostomatological Sciences (M.P.), University of Naples "Federico II"; Department of Human Neurosciences (M.P.), Sapienza University of Rome, Italy; Section of Neuroradiology (A.R.), Department of Radiology, and Centre d'Esclerosi Múltiple de Catalunya (Cemcat) (J.S.-G.), Department of Neurology/Neuroimmunology, Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Spain; MS Center Amsterdam (E.M.M.S.), Neurology, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC location VUmc, the Netherlands; Department of Neurology and Center of Clinical Neuroscience (T.U.), and Department of Radiology (M.V.), First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic; MS Center Amsterdam (M.M.S.), Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC location VUmc, the Netherlands; Centre for Medical Image Computing (J.H.C.), Department of Computer Science, and Dementia Research Centre (J.H.C., F.B.), UCL Queen Square Institute of Neurology, University College London, United Kingdom.

Background And Objectives: Disentangling brain aging from disease-related neurodegeneration in patients with multiple sclerosis (PwMS) is increasingly topical. The brain-age paradigm offers a window into this problem but may miss disease-specific effects. In this study, we investigated whether a disease-specific model might complement the brain-age gap (BAG) by capturing aspects unique to MS.

View Article and Find Full Text PDF
Article Synopsis
  • The study investigates how chronic pelvic pain affects brain aging using data from the Multidisciplinary Approach to the Study of Chronic Pelvic Pain Research Network.
  • Researchers analyzed brain-predicted ages of 492 patients with chronic pelvic pain and 72 controls via MRI scans and assessed the differences based on sex.
  • Findings indicate that women with chronic pelvic pain have a higher brainAGE compared to female controls, while men showed lower brainAGE trends, suggesting potential links between inflammatory factors and brain aging, though more research is needed.
View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!