Journal
BRAIN AND BEHAVIOR
Volume 12, Issue 1, Pages -Publisher
WILEY
DOI: 10.1002/brb3.2413
Keywords
aging; machine learning; mega-analysis; neuroimaging; posttraumatic stress disorder; trauma
Categories
Funding
- Academic Medical Center Research Council
- Center for Brain and Behavior Research Pilot Grant
- National Center for Advancing Translational Sciences
- Department of Veterans Affairs RRD
- Canadian Institute for Military and Veteran Health Research
- National Center for Research Resources [CX001600]
- National Institutes of Health [K01MH122774, R01 MH106574]
- Brain and Behavior Research Foundation [07040]
- VA Career Development Award
- National Institute on Alcohol Abuse and Alcoholism
- South Dakota Governor's Research Center Grant
- National Institute of Mental Health [F31MH113271, K23MH112873, R01-MH043454, T32MH018931, T32MH13043]
- Trauma Scholars Fund
- NIH from the Big Data to Knowledge (BD2K) program [U54 EB020403]
- German Research Society
- U.S. Department of Defense [W81XWH-10-1-0925, W81XWH082-0159]
- NHMRC Career Development Fellowship
- Deutsche Forschungsgemeinschaft [DA1222/4-1, SFB/TRR 58, WA1539/8-2]
- U.S. Department of Veterans Affairs
- Barlow Family Fund
- Veterans Affairs Merit Review Program
- Institute of Neurosciences, Mental Health and Addiction
- German Federal Ministry of Education and Research
- Congressionally Directed Medical Research Programs [W81XWH08-2-0038]
- Kasparian Fund
- Netherlands organization for Health Research and Development
- MRC/UKRI Innovation Fellowship
- VISN6 MIRECC
- Bijzonder Onderzoeksfonds UGent
- Anonymous Women's Health Fund
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PTSD is associated with accelerated aging markers. Young males with PTSD showed higher brain age difference compared to male controls, while old males with PTSD exhibited lower brain age difference compared to male controls of all ages.
Background Posttraumatic stress disorder (PTSD) is associated with markers of accelerated aging. Estimates of brain age, compared to chronological age, may clarify the effects of PTSD on the brain and may inform treatment approaches targeting the neurobiology of aging in the context of PTSD. Method Adult subjects (N = 2229; 56.2% male) aged 18-69 years (mean = 35.6, SD = 11.0) from 21 ENIGMA-PGC PTSD sites underwent T1-weighted brain structural magnetic resonance imaging, and PTSD assessment (PTSD+, n = 884). Previously trained voxel-wise (brainageR) and region-of-interest (BARACUS and PHOTON) machine learning pipelines were compared in a subset of control subjects (n = 386). Linear mixed effects models were conducted in the full sample (those with and without PTSD) to examine the effect of PTSD on brain predicted age difference (brain PAD; brain age - chronological age) controlling for chronological age, sex, and scan site. Results BrainageR most accurately predicted brain age in a subset (n = 386) of controls (brainageR: ICC = 0.71, R = 0.72, MAE = 5.68; PHOTON: ICC = 0.61, R = 0.62, MAE = 6.37; BARACUS: ICC = 0.47, R = 0.64, MAE = 8.80). Using brainageR, a three-way interaction revealed that young males with PTSD exhibited higher brain PAD relative to male controls in young and old age groups; old males with PTSD exhibited lower brain PAD compared to male controls of all ages. Discussion Differential impact of PTSD on brain PAD in younger versus older males may indicate a critical window when PTSD impacts brain aging, followed by age-related brain changes that are consonant with individuals without PTSD. Future longitudinal research is warranted to understand how PTSD impacts brain aging across the lifespan.
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