Age-dependent white matter disruptions after military traumatic brain injury: Multivariate analysis results from ENIGMA brain injury.

Abstract

Mild Traumatic brain injury (mTBI) is a signature wound in military personnel, and repetitive mTBI has been linked to age-related neurogenerative disorders that affect white matter (WM) in the brain. However, findings of injury to specific WM tracts have been variable and inconsistent. This may be due to the heterogeneity of mechanisms, etiology, and comorbid disorders related to mTBI. Non-negative matrix factorization (NMF) is a data-driven approach that detects covarying patterns (components) within high-dimensional data. We applied NMF to diffusion imaging data from military Veterans with and without a self-reported TBI history. NMF identified 12 independent components derived from fractional anisotropy (FA) in a large dataset (n = 1,475) gathered through the ENIGMA (Enhancing Neuroimaging Genetics through Meta-Analysis) Military Brain Injury working group. Regressions were used to examine TBI- and mTBI-related associations in NMF-derived components while adjusting for age, sex, post-traumatic stress disorder, depression, and data acquisition site/scanner. We found significantly stronger age-dependent effects of lower FA in Veterans with TBI than Veterans without in four components (q < 0.05), which are spatially unconstrained by traditionally defined WM tracts. One component, occupying the most peripheral location, exhibited significantly stronger age-dependent differences in Veterans with mTBI. We found NMF to be powerful and effective in detecting covarying patterns of FA associated with mTBI by applying standard parametric regression modeling. Our results highlight patterns of WM alteration that are differentially affected by TBI and mTBI in younger compared to older military Veterans.

Department

Description

Provenance

Citation

Published Version (Please cite this version)

10.1002/hbm.25811

Publication Info

Bouchard, Heather C, Delin Sun, Emily L Dennis, Mary R Newsome, Seth G Disner, Jeremy Elman, Annelise Silva, Carmen Velez, et al. (2022). Age-dependent white matter disruptions after military traumatic brain injury: Multivariate analysis results from ENIGMA brain injury. Human brain mapping, 43(8). pp. 2653–2667. 10.1002/hbm.25811 Retrieved from https://hdl.handle.net/10161/25868.

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Scholars@Duke

Sun

Delin Sun

Assistant Professor in Psychiatry and Behavioral Sciences

I am interested in the neuropsychological and behavioral correlates of posttraumatic stress disorder (PTSD) and adolescent trauma. With a multidisciplinary background in psychology, physics, and biology, I have specific training and expertise in neuroimaging methods and secondary data analysis of neural changes in PTSD and childhood trauma. I systematically study PTSD-related structural and functional brain images using methods that focus on different levels including regional changes, connectivity, and brain networks, respectively, to build a complete behavioral-brain map. I also study the relationship between adolescent brain development and trauma as well as alcohol by using brain structure network graphs, longitudinal studies, and machine learning research methods. Besides, I utilize neuroimaging and neurophysiological techniques to investigate the neural underpinnings of social cognitive and affective functions in both healthy volunteers and patients with mental disorders including excessive internet usage, smoking addiction, Alzheimer’s Disease, and depression. I have successfully collaborated with researchers locally or from other institutions and have had several peer-reviewed publications in each project. 

Grant

Gerald Arthur Grant

Allan H. Friedman Distinguished Professor of Neurosurgery
Morey

Rajendra A. Morey

Professor of Psychiatry and Behavioral Sciences

Research in my lab is focused on brain changes associated with posttraumatic stress disorder (PTSD), traumatic brain injury (TBI), and other neuropsychiatric disorders. We apply several advanced methods for understanding brain function including functional MRI, structural MRI, diffusion tensor imaging, and genetic effects.


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