Dataset Information

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.

SUBMITTER: Bouchard HC

PROVIDER: S-EPMC9057089 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature

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

Bouchard Heather C HC Sun Delin D Dennis Emily L EL Newsome Mary R MR Disner Seth G SG Elman Jeremy J Silva Annelise A Velez Carmen C Irimia Andrei A Davenport Nicholas D ND Sponheim Scott R SR Franz Carol E CE Kremen William S WS Coleman Michael J MJ Williams M Wright MW Geuze Elbert E Koerte Inga K IK Shenton Martha E ME Adamson Maheen M MM Coimbra Raul R Grant Gerald G Shutter Lori L George Mark S MS Zafonte Ross D RD McAllister Thomas W TW Stein Murray B MB Thompson Paul M PM Wilde Elisabeth A EA Tate David F DF Sotiras Aristeidis A Morey Rajendra A RA

Human brain mapping 20220315 8

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) ...[more]

PMID: 35289463

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Project description:The purpose of this study was to analyze quantitative diffusion tensor imaging measures across the spectrum of traumatic brain injury severity and evaluate their trajectories in military service members. Participants were 96 U.S. military service members and veterans who had sustained a mild traumatic brain injury [including complicated mild traumatic brain injury (n = 16) and uncomplicated mild traumatic brain injury (n = 68)], moderate-severe traumatic brain injury (n = 12), and controls (with or without orthopaedic injury, n = 39). All participants had been scanned at least twice, with some receiving up to five scans. Both whole brain voxel-wise analysis and tract-of-interest analysis were applied to assess the group differences of diffusion tensor imaging metrics, and their trajectories between time points of scans and days since injury. Linear mixed modelling was applied to evaluate cross-sectional and longitudinal diffusion tensor imaging metrics changes within and between groups using both tract-of-interest and voxel-wise analyses. Participants with moderate to severe traumatic brain injury had larger white matter disruption both in superficial subcortical and deep white matter, mainly over the anterior part of cerebrum, than those with mild traumatic brain injury, both complicated and uncomplicated, and there was no evidence of recovery over the period of follow-ups in moderate-severe traumatic brain injury, but deterioration was possible. Participants with mild traumatic brain injury had white matter microstructural changes, mainly in deep central white matter over the posterior part of cerebrum, with more spatial involvement in complicated mild traumatic brain injury than in uncomplicated mild traumatic brain injury and possible brain repair through neuroplasticity, e.g. astrocytosis with glial processes and glial scaring. Our results did not replicate 'V-shaped' trajectories in diffusion tensor imaging metrics, which were revealed in a previous study assessing the sub-acute stage of brain injury in service members and veterans following military combat concussion. In addition, non-traumatic brain injury controls, though not demonstrating any evidence of sustaining a traumatic brain injury, might have transient white matter changes with recovery afterward. Our results suggest that white matter integrity following a remote traumatic brain injury may change as a result of different underlying mechanisms at the microstructural level, which can have a significant consequence on the long-term well beings of service members and veterans. In conclusion, longitudinal diffusion tensor imaging improves our understanding of the mechanisms of white matter microstructural changes across the spectrum of traumatic brain injury severity. The quantitative metrics can be useful as guidelines in monitoring the long-term recovery.

Project description:White matter disruption is an important determinant of cognitive impairment after brain injury, but conventional neuroimaging underestimates its extent. In contrast, diffusion tensor imaging provides a validated and sensitive way of identifying the impact of axonal injury. The relationship between cognitive impairment after traumatic brain injury and white matter damage is likely to be complex. We applied a flexible technique-tract-based spatial statistics-to explore whether damage to specific white matter tracts is associated with particular patterns of cognitive impairment. The commonly affected domains of memory, executive function and information processing speed were investigated in 28 patients in the post-acute/chronic phase following traumatic brain injury and in 26 age-matched controls. Analysis of fractional anisotropy and diffusivity maps revealed widespread differences in white matter integrity between the groups. Patients showed large areas of reduced fractional anisotropy, as well as increased mean and axial diffusivities, compared with controls, despite the small amounts of cortical and white matter damage visible on standard imaging. A stratified analysis based on the presence or absence of microbleeds (a marker of diffuse axonal injury) revealed diffusion tensor imaging to be more sensitive than gradient-echo imaging to white matter damage. The location of white matter abnormality predicted cognitive function to some extent. The structure of the fornices was correlated with associative learning and memory across both patient and control groups, whilst the structure of frontal lobe connections showed relationships with executive function that differed in the two groups. These results highlight the complexity of the relationships between white matter structure and cognition. Although widespread and, sometimes, chronic abnormalities of white matter are identifiable following traumatic brain injury, the impact of these changes on cognitive function is likely to depend on damage to key pathways that link nodes in the distributed brain networks supporting high-level cognitive functions.

Project description:BackgroundAlthough older traumatic brain injury (TBI) patients often exhibit cerebral autoregulatory impairment with high pressure reactivity index (PRx), the role of autoregulatory-guided management in these patients remains elusive. In this study, we aimed to explore if age affected the prognostic role of the autoregulatory variables, PRx and the PRx-derived optimal cerebral perfusion pressure (CPPopt), in a large TBI cohort.MethodsIn this observational study, 550 TBI patients who had been treated in the neurocritical care unit, Addenbrooke's Hospital, Cambridge, UK, between 2002 and 2022 with available data on age, intracranial pressure monitoring, and outcome (Glasgow Outcome Scale [GOS]) were included. The patients were classified into three age groups; youth and early adulthood (16-39 years), middle adulthood (40-59 years), and senior adulthood (60 years and above). Autoregulatory variables were studied in relation to outcome using heatmaps. Multivariate logistic regressions of mortality and favourable outcome (GOS 4 to 5) were performed with PRx and ΔCPPopt (CPP-CPPopt) in addition to baseline variables.ResultsTBI patients in the senior adulthood group exhibited higher PRx and lower ICP than younger patients. There was a transition towards worse outcome with higher PRx in heatmaps for all age groups. The combination of high PRx together with low CPP or negative ΔCPPopt was particularly associated with lower GOS. In multivariate logistic regressions, higher PRx remained independently associated with higher mortality and lower rate of favourable outcome in the senior adulthood cohort. There was a transition towards worse outcome for negative ΔCPPopt for all age groups, but it did not reach statistical significance for the senior adulthood group.ConclusionsPRx was found to be an independent outcome predictor and influenced the safe and dangerous CPP and ΔCPPopt interval for all age groups. Thus, TBI patients older than 60 years may also benefit from autoregulatory-guided management and should not necessarily be excluded from future trials on such therapeutic strategies.

Dataset Information

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

Publications

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

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