Age‐dependent white matter disruptions after military traumatic brain injury: Multivariate analysis results from ENIGMA brain injury. Issue 8 (15th March 2022)

• Record Type: Journal Article
• Authors: Bouchard, Heather C.; Sun, Delin; Dennis, Emily L.; Newsome, Mary R.; Disner, Seth G.; Elman, Jeremy; Silva, Annelise; Velez, Carmen; Irimia, Andrei; Davenport, Nicholas D.; Sponheim, Scott R.; Franz, Carol E.; Kremen, William S.; Coleman, Michael J.; Williams, M. Wright; Geuze, Elbert; Koerte, Inga K.; Shenton, Martha E.; Adamson, Maheen M.; Coimbra, Raul; Grant, Gerald; Shutter, Lori; George, Mark S.; Zafonte, Ross D.; McAllister, Thomas W.; Stein, Murray B.; Thompson, Paul M.; Wilde, Elisabeth A.; Tate, David F.; Sotiras, Aristeidis; Morey, Rajendra A.;
• Is Part Of: Human brain mapping. Volume 43:Issue 8(2022)
• Page Start: 2653
• Page End: 2667
• Publication Date: 2022-03-15
• Subjects: diffusion MRI -- ENIGMA -- military -- mTBI -- nonnegative matrix factorization -- traumatic brain injury; Brain mapping -- Periodicals; 611.81
• DOI: 10.1002/hbm.25811
• Languages: English
• ISSNs: 1065-9471

Abstract

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. Abstract : We used NMF, an unsupervised, data‐driven method, to capture patterns of fluctuation across the white matter in the brain in a sample of military personnel accessed through the ENIGMA Military Brain Injury working group. We identified significantly stronger age‐dependent effects of lower FA in the military personnel with a TBI compared to a military non‐TBI group. Use of data‐driven methods may help to uncover the heterogeneous patterns of white matter damage resulting from military‐related mTBI and may uncover injury patterns in the brain unrelated to our current understanding of brain structure.