Coordinating Global Multi-Site Studies of Military-Relevant Traumatic Brain Injury: Opportunities, Challenges, and Harmonization Guidelines

Tate, David F.; Dennis, Emily; Adams, John T.; Adamson, Maheen; Belanger, Heather G.; Bigler, Erin D.; Bouchard, Heather C; Clark, Alexandra L.; Delano‐Wood, Lisa; Disner, Seth G.; Eapen, Blessen C.; Franz, Carol E.; Geuze, Elbert; Goodrich-Hunsaker, Naomi J.; Han, Kihwan; Hayes, Jasmeet P.; Hinds, Sidney; Hodges, Cooper B.; Hovenden, Elizabeth; Irimia, Andrei; Kenney, Kimbra; Koerte, Inga K.; Kremen, William S.; Levin, Harvey S.; Lindsey, Hannah M.; Morey, Rajendra A.; Newsome, Mary R.; Ollinger, John M.; Pugh, Mary Jo; Scheibel, Randall S.; Shenton, Martha E.; Sullivan, Danielle R.; Taylor, Brian; Troyanskaya, Maya; Vélez, Carmen; Wade, Benjamin; Wang, Xin; Ware, Ashley L.; Zafonte, Ross; Thompson, Paul M.; Wilde, Elisabeth A.

doi:10.1007/s11682-020-00423-2

Cited by 14 publications

(8 citation statements)

References 216 publications

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“…However, most prior reports on exposed military personnel have yielded inconsistent findings on the WM regions affected by TBI (Asken, DeKosky, Clugston, Jaffee, & Bauer, 2018). This lack of consensus, particularly pertaining to blast-related mTBI, may stem from the tremendous spatial and individual heterogeneity due to the variability of biomechanical parameters related to blasts, including the directions and magnitudes of concussive forces, the presence of nearby rigid surfaces, the presence of protective gear, and other factors (Tate et al, 2021). Inconclusive findings in the literature may be partially explained by the presence of small statistical effects that are detectable only in large samples (Open Science Collaboration, 2015).…”

Section: Introductionmentioning

confidence: 99%

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

Bouchard

Sun

Dennis

et al. 2022

Human Brain Mapping

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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.

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Section: Introductionmentioning

confidence: 99%

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

Bouchard

Sun

Dennis

et al. 2022

Human Brain Mapping

Self Cite

View full text Add to dashboard Cite

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“…If unaddressed, these concerns introduce magnified noise or systematic bias masquerading as high-powered findings ( Maikusa et al, 2021 ). However, well-designed data sharing efforts with rigorous harmonization approaches (e.g., Fortin et al, 2017 ; Tate et al, 2021 ) hold opportunities for falsification through meta-analyses, mega-analyses, and between site data comparisons ( Thompson et al, 2022 ). Data sharing and team science also provide realistic opportunities to address sample heterogeneity and site-level idiosyncrasies in method.…”

Section: Accelerating Science By Falsifying Strong Hypothesesmentioning

confidence: 99%

How failure to falsify in high-volume science contributes to the replication crisis

Rajtmajer

Errington

Hillary

2022

eLife

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The number of scientific papers published every year continues to increase, but scientific knowledge is not progressing at the same rate. Here we argue that a greater emphasis on falsification - the direct testing of strong hypotheses - would lead to faster progress by allowing well-specified hypotheses to be eliminated. We describe an example from neuroscience where there has been little work to directly test two prominent but incompatible hypotheses related to traumatic brain injury. Based on this example, we discuss how building strong hypotheses and then setting out to falsify them can bring greater precision to the clinical neurosciences, and argue that this approach could be beneficial to all areas of science.

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“…From its inception, it was clear that the complexity of brain injury would necessitate specialized groups that could more readily address unique features of the varying cohorts. Within the first year, multiple subgroups were identified, including Pediatric Moderate/Severe Traumatic Brain Injury (TBI) (msTBI) (Dennis et al 2020), Military-Relevant TBI (Tate et al 2020), and Sport-Related Head Injury (Koerte et al 2020). Soon after, groups for Adult msTBI (Olsen et al 2020) and Acute Emergency Department (Civilian) Mild TBI were formed, followed by a group focusing on Intimate Partner Violence (Esopenko et al 2020).…”

Section: Formation Of Enigma Brain Injurymentioning

confidence: 99%

The ENIGMA Brain Injury working group: approach, challenges, and potential benefits

Wilde

Dennis

Tate

2021

Brain Imaging and Behavior

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The Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) consortium brings together researchers from around the world to try to identify the genetic underpinnings of brain structure and function, along with robust, generalizable effects of neurological and psychiatric disorders. The recently-formed ENIGMA Brain Injury working group includes 10 subgroups, based largely on injury mechanism and patient population. This introduction to the special issue summarizes the history, organization, and objectives of ENIGMA Brain Injury, and includes a discussion of strategies, challenges, opportunities and goals common across 6 of the subgroups under the umbrella of ENIGMA Brain Injury. The following articles in this special issue, including 6 articles from different subgroups, will detail the challenges and opportunities specific to each subgroup.

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Coordinating Global Multi-Site Studies of Military-Relevant Traumatic Brain Injury: Opportunities, Challenges, and Harmonization Guidelines

Cited by 14 publications

References 216 publications

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

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

How failure to falsify in high-volume science contributes to the replication crisis

The ENIGMA Brain Injury working group: approach, challenges, and potential benefits

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