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

dc.contributor.author

Bouchard, Heather C

dc.contributor.author

Sun, Delin

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Dennis, Emily L

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Newsome, Mary R

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Disner, Seth G

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Elman, Jeremy

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Silva, Annelise

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Velez, Carmen

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Irimia, Andrei

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Davenport, Nicholas D

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Sponheim, Scott R

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Franz, Carol E

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Kremen, William S

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Coleman, Michael J

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Williams, M Wright

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Geuze, Elbert

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Koerte, Inga K

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Shenton, Martha E

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Adamson, Maheen M

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Coimbra, Raul

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Grant, Gerald

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Shutter, Lori

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George, Mark S

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Zafonte, Ross D

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McAllister, Thomas W

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Stein, Murray B

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Thompson, Paul M

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Wilde, Elisabeth A

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Tate, David F

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Sotiras, Aristeidis

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Morey, Rajendra A

dc.date.accessioned

2022-09-28T14:59:20Z

dc.date.available

2022-09-28T14:59:20Z

dc.date.issued

2022-06

dc.date.updated

2022-09-28T14:59:16Z

dc.description.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.

dc.identifier.issn

1065-9471

dc.identifier.issn

1097-0193

dc.identifier.uri

https://hdl.handle.net/10161/25868

dc.language

eng

dc.publisher

Wiley

dc.relation.ispartof

Human brain mapping

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10.1002/hbm.25811

dc.subject

Brain

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Humans

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Brain Injuries

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Brain Concussion

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Multivariate Analysis

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Stress Disorders, Post-Traumatic

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Military Personnel

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Veterans

dc.subject

White Matter

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Brain Injuries, Traumatic

dc.title

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

dc.type

Journal article

duke.contributor.orcid

Sun, Delin|0000-0003-3283-423X

duke.contributor.orcid

Grant, Gerald|0000-0002-2651-4603

pubs.begin-page

2653

pubs.end-page

2667

pubs.issue

8

pubs.organisational-group

Duke

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School of Medicine

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Clinical Science Departments

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Institutes and Centers

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Psychiatry & Behavioral Sciences

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Duke Cancer Institute

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Institutes and Provost's Academic Units

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University Institutes and Centers

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Duke Institute for Brain Sciences

pubs.organisational-group

Psychiatry, Child & Family Mental Health & Community Psychiatry

pubs.organisational-group

Duke-UNC Center for Brain Imaging and Analysis

pubs.organisational-group

Neurosurgery

pubs.publication-status

Published

pubs.volume

43

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