Brain aging in major depressive disorder: results from the ENIGMA major depressive disorder working group

Jan 1, 2021·
Laura K. M. Han
,
Richard Dinga
,
Tim Hahn
,
Christopher R. K. Ching
,
Lisa T. Eyler
,
Lyubomir Aftanas
,
Moji Aghajani
,
André Aleman
,
Bernhard T. Baune
,
Klaus Berger
,
Ivan Brak
,
Geraldo Busatto Filho
,
Angela Carballedo
,
Colm G. Connolly
,
Baptiste Couvy-Duchesne
,
Kathryn R. Cullen
,
Udo Dannlowski
,
Christopher G. Davey
,
Danai Dima
,
Fabio L. S. Duran
,
Verena Enneking
,
Elena Filimonova
,
Stefan Frenzel
,
Thomas Frodl
,
Cynthia H. Y. Fu
,
Beata R. Godlewska
,
Ian H. Gotlib
,
Hans J. Grabe
,
Nynke A. Groenewold
,
Dominik Grotegerd
,
Oliver Gruber
,
Geoffrey B. Hall
,
Ben J. Harrison
,
Sean N. Hatton
,
Marco Hermesdorf
,
Ian B. Hickie
,
Tiffany C. Ho
,
Norbert Hosten
,
Andreas Jansen
,
Claas Kähler
,
Tilo Kircher
,
Bonnie Klimes-Dougan
,
Bernd Krämer
,
Axel Krug
,
Jim Lagopoulos
,
Ramona Leenings
,
Frank P. MacMaster
,
Glenda MacQueen
,
Andrew McIntosh
,
Quinn McLellan
,
Katie L. McMahon
,
Sarah E. Medland
,
Bryon A. Mueller
,
Benson Mwangi
,
Evgeny Osipov
,
Maria J. Portella
,
Elena Pozzi
,
Liesbeth Reneman
,
Jonathan Repple
,
Pedro G. P. Rosa
,
Matthew D. Sacchet
,
Philipp G. Sämann
,
Knut Schnell
,
Anouk Schrantee
,
Egle Simulionyte
,
Jair C. Soares
,
Jens Sommer
,
Dan J. Stein
,
Olaf Steinsträter
,
Lachlan T. Strike
,
Sophia I. Thomopoulos
,
Marie-José Van Tol
,
Ilya M. Veer
,
Robert R. J. M. Vermeiren
,
Henrik Walter
,
Nic J. A. Van Der Wee
,
Steven J. A. Van Der Werff
,
Heather Whalley
,
Nils R. Winter
,
Katharina Wittfeld
,
Margaret J. Wright
,
Mon-Ju Wu
,
Henry Völzke
,
Tony T. Yang
,
Vasileios Zannias
,
Greig I. De Zubicaray
,
Giovana B. Zunta-Soares
,
Christoph Abé
,
Martin Alda
,
Ole A. Andreassen
,
Erlend Bøen
,
Caterina M. Bonnin
,
Erick J. Canales-Rodriguez
,
Dara Cannon
,
Xavier Caseras
,
Tiffany M. Chaim-Avancini
,
Torbjørn Elvsåshagen
,
Pauline Favre
,
Sonya F. Foley
,
Janice M. Fullerton
,
Jose M. Goikolea
,
Bartholomeus C. M. Haarman
,
Tomas Hajek
,
Chantal Henry
,
Josselin Houenou
,
Fleur M. Howells
,
Martin Ingvar
,
Rayus Kuplicki
,
Beny Lafer
,
Mikael Landén
,
Rodrigo Machado-Vieira
,
Ulrik F. Malt
,
Colm McDonald
,
Philip B. Mitchell
,
Leila Nabulsi
,
Maria Concepcion Garcia Otaduy
,
Bronwyn J. Overs
,
Mircea Polosan
,
Edith Pomarol-Clotet
,
Joaquim Radua
,
Maria M. Rive
,
Gloria Roberts
,
Henricus G. Ruhe
,
Raymond Salvador
,
Salvador Sarró
,
Theodore D. Satterthwaite
,
Jonathan Savitz
,
Aart H. Schene
,
Peter R. Schofield
,
Mauricio H. Serpa
,
Kang Sim
,
Marcio Gerhardt Soeiro-De-Souza
,
Ashley N. Sutherland
,
Henk S. Temmingh
,
Garrett M. Timmons
,
Anne Uhlmann
,
Eduard Vieta
,
Daniel H. Wolf
,
Marcus v. Zanetti
,
Neda Jahanshad
,
Paul M. Thompson
,
Dick J. Veltman
,
Brenda W. J. H. Penninx
,
Andre F. Marquand
,
James H. Cole
,
Lianne Schmaal
· 0 min read
Abstract
Major depressive disorder (MDD) is associated with an increased risk of brain atrophy, aging-related diseases, and mortality. We examined potential advanced brain aging in adult MDD patients, and whether this process is associated with clinical characteristics in a large multicenter international dataset. We performed a mega-analysis by pooling brain measures derived from T1-weighted MRI scans from 19 samples worldwide. Healthy brain aging was estimated by predicting chronological age (18–75 years) from 7 subcortical volumes, 34 cortical thickness and 34 surface area, lateral ventricles and total intracranial volume measures separately in 952 male and 1236 female controls from the ENIGMA MDD working group. The learned model coefficients were applied to 927 male controls and 986 depressed males, and 1199 female controls and 1689 depressed females to obtain independent unbiased brain-based age predictions. The difference between predicted “brain age” and chronological age was calculated to indicate brain-predicted age difference (brain-PAD). On average, MDD patients showed a higher brain-PAD of +1.08 (SE 0.22) years (Cohen’s d = 0.14, 95% CI: 0.08–0.20) compared with controls. However, this difference did not seem to be driven by specific clinical characteristics (recurrent status, remission status, antidepressant medication use, age of onset, or symptom severity). This highly powered collaborative effort showed subtle patterns of age-related structural brain abnormalities in MDD. Substantial within-group variance and overlap between groups were observed. Longitudinal studies of MDD and somatic health outcomes are needed to further assess the clinical value of these brain-PAD estimates.
Type
Publication
Molecular Psychiatry
Neuroimaging Machine Learning Depression Brain Age MDD ENIGMA