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Record W4406232169 · doi:10.1093/braincomms/fcaf009

Amyloid-β and tau deposition in traumatic brain injury: a study of Vietnam War veterans

2024· article· en· W4406232169 on OpenAlexfundno aff
Hannah de Bruin, Colin Groot, Suzie Kamps, Everard G.B. Vijverberg, Anna Steward, Amir Dehsarvi, Yolande A.L. Pijnenburg, Rik Ossenkoppele, Nicolai Franzmeier

Bibliographic record

VenueBrain Communications · 2024
Typearticle
Languageen
FieldMedicine
TopicAlzheimer's disease research and treatments
Canadian institutionsnot available
FundersNational Institute on AgingAvid RadiopharmaceuticalsParkinsonfondenGenentechNational Institutes of HealthIXICOH. Lundbeck A/SServierBioClinicaBiogenPfizerAlzheimer NederlandZonMwAlzheimerfondenEisaiNederlandse Organisatie voor Wetenschappelijk OnderzoekDeutsche ForschungsgemeinschaftCanadian Institutes of Health ResearchProthenaAlzheimer Forschung InitiativeNorthern California Institute for Research and EducationMeso Scale DiagnosticsCure Alzheimer's FundNovartis Pharmaceuticals CorporationF. Hoffmann-La RocheEli Lilly and CompanyBristol-Myers SquibbAlzheimer's AssociationStichting DioraphteFoundation for the National Institutes of Health
KeywordsVietnam WarTraumatic brain injuryAmyloid (mycology)Amyloid βDeposition (geology)MedicinePsychologyPathologyPsychiatryDiseasePolitical scienceBiology

Abstract

fetched live from OpenAlex

Abstract Traumatic brain injury is widely viewed as a risk factor for dementia, but the biological mechanisms underlying this association are still unclear. In previous studies, traumatic brain injury has been associated with the hallmark pathologies of Alzheimer’s disease, i.e. amyloid-β plaques and neurofibrillary tangles comprised of hyperphosphorylated tau. Depending on the type and location of trauma, traumatic brain injury can induce spatially heterogeneous brain lesions that may pre-dispose for the development of Alzheimer’s disease pathology in aging. Therefore, we hypothesized that a history of traumatic brain injury may be related to spatially heterogeneous amyloid-β and tau pathology patterns that deviate from the stereotypical temporo-parietal patterns in Alzheimer’s disease. To test this, we included 103 Vietnam War veterans of whom 65 had experienced traumatic brain injury (n = 40, 38.8% mild; n = 25, 24.3% moderate/severe). Most individuals had a history of 1 (n = 35, 53.8%) or 2 (n = 15, 23.1%) traumatic brain injury events. We included the group without a history of traumatic brain injury (n = 38, 36.9%) as controls. The majority was cognitively normal (n = 80, 77.7%), while a subset had mild cognitive impairment (n = 23, 22.3%). All participants underwent [18F]florbetapir/Amyvid amyloid-β PET and [18F]flortaucipir/Tauvid tau-PET 39.63 ± 18.39 years after their last traumatic brain injury event. We found no differences in global amyloid-β and tau-PET levels between groups, suggesting that a history of traumatic brain injury does not pre-dispose to accumulate amyloid-β or tau pathology in general. However, we found that traumatic brain injury was associated with altered spatial patterns of amyloid-β and tau, with relatively greater deposition in fronto-parietal brain regions. These regions are prone to damage in traumatic brain injury, while they are typically only affected in later stages of Alzheimer’s disease. Moreover, in our traumatic brain injury groups, the association between amyloid-β and tau was reduced in Alzheimer-typical temporal regions but increased in frontal regions that are commonly associated with traumatic brain injury. Altogether, while acknowledging the relatively small sample size and generally low levels of Alzheimer’s disease pathology in this sample, our findings suggest that traumatic brain injury induces spatial patterns of amyloid-β and tau that differ from patterns observed in typical Alzheimer’s disease. Furthermore, traumatic brain injury may be associated with a de-coupling of amyloid-β and tau in regions vulnerable in Alzheimer’s disease. These findings indicate that focal brain damage in early/mid-life may change neurodegenerative trajectories in late-life.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.608
Threshold uncertainty score0.351

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.065
GPT teacher head0.395
Teacher spread0.330 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2024
Admission routes1
Has abstractyes

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