The men and women involved in rescue and recovery operations at the 9/11 World Trade Center (WTC) site have a greater prevalence (23%) of persistent, clinically significant post-traumatic stress disorder (PTSD). Recent structural and functional magnetic resonance imaging (MRI) studies demonstrate significant neural differences between WTC responders with and without PTSD. Here, we used brain age, a novel MRI-based data-driven biomarker optimized to detect accelerated structural aging, and examined the impact of PTSD on this process. Using BrainAgeNeXt, a novel convolutional neural network trained and validated on 11,574 magnetic resonance imaging (MRI) T1- weighted scans, we predicted brain age in WTC responders with PTSD (WTC-PTSD, n = 47) and age/sex matched responders without PTSD (non-PTSD, n = 52). Predicted Age Difference (PAD) was then calculated for each WTC responder by subtracting chronological age from brain age. A positive PAD indicates that the responder's brain is aging faster than expected for their chronological age. We found that PAD is significantly greater with WTC-PTSD compared to non-PTSD responders (p < 0.001). Further, we found that WTC exposure duration (months working on site) moderates the association between PTSD and PAD (p=0.0050). Our results suggested that brain age is a valid biomarker to compare aging trajectories in responders with and without PTSD. In particular, PTSD may be a substantial risk factor for accelerated neurodegeneration in this vulnerable and aging population.

The authors have declared no competing interest.

The authors would like to acknowledge support from the Centers for Disease Control and Prevention for supporting the neuroimaging study (CDC/NIOSH U01 OH011314), the National Institute on Aging that supports research on characterization and treatment of Alzheimers disease (NIH/NIA P50 AG005138), and aging-relates work in this population (NIH/NIA R01 AG049953). We would also like to acknowledge ongoing funding to monitor World Trade Center responders as part of the WTC Health and Wellness Program (CDC 200-2011-39361). This research was partially funded by the Swiss National Science Foundation (SNSF) Postdoc Mobility Fellowship (P500PB_206833). This work was supported in part through the computational and data resources and staff expertise provided by Scientific Computing and Data at the Icahn School of Medicine at Mount Sinai and supported by the Clinical and Translational Science Awards (CTSA) grant UL1TR004419 from the National Center for Advancing Translational Sciences. Research reported in this publication was also supported by the Office of Research Infrastructure of the National Institutes of Health under award number S10OD026880 and S10OD030463. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Additional support was provided by the Icahn School of Medicine Capital Campaign, BioMedical Engineering and Imaging Institute, and Department of Radiology, as well as by the Intramural Research Program of NINDS, NIH. This work was supported by the Office of the Assistant Secretary of Defense for Health Affairs through the Multiple Sclerosis Research Program under Award No. (HT9425-24-1-0857). Opinions, interpretations, conclusions, and recommendations are those of the author and are not necessarily endorsed by the Department of Defense.

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Ethics committee of Institutional Review Boards at both Stony Brook University and the Icahn School of Medicine at Mount Sinai gave ethical approval for this work

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