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Record W4312087783 · doi:10.1002/alz.064157

Plasma phospho‐tau predicts differences in white matter microstructural complexity and cognition in non‐demented older adults

2022· article· en· W4312087783 on OpenAlexaboutno aff
Andrew R. Bender, Kelly N. Dubois, Tessa Grabinski, Scott Peltier, Bruno Giordani, Henry L. Paulson, Nicholas M. Kanaan, Benjamin M. Hampstead

Bibliographic record

VenueAlzheimer s & Dementia · 2022
Typearticle
Languageen
FieldMedicine
TopicAdvanced Neuroimaging Techniques and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsWhite matterDementiaBiomarkerNeuropsychologyNeuroimagingPsychologyInternal medicineCognitionMedicineFornixMagnetic resonance imagingAudiologyDiseaseNeuroscienceBiologyHippocampusRadiology

Abstract

fetched live from OpenAlex

Abstract Background White matter (WM) measures from diffusion magnetic resonance imaging (dMRI) are sensitive to Alzheimer’s disease (AD) pathology and cognitive impairment. Whereas most extant dMRI studies focused on uniformly‐oriented WM fiber tracts, variations in crossing fiber regions also show sensitivity to mild cognitive impairment (MCI) and AD diagnoses. Such crossing fiber alterations may reflect differential disease effects on constituent fibers, suggesting that quantifying crossing fibers may provide unique markers of early WM changes and neurocognitive risk in AD and MCI. Although few methods exist for quantifying crossing fibers, recent findings show older age is associated with increased microstructural complexity (CX) a novel method to characterize in crossing fibers. The present study evaluated CX in relation to variation in plasma AD biomarkers and cognitive performance in older adults without dementia. Method Data from 48 participants included clinical evaluation, neuropsychological assessment, dMRI neuroimaging and venipuncture. SIMOA assays quantified the AD plasma biomarkers Aβ42, Aβ40, and tau phosphorylated at threonine181 (pTau‐181). Participants were clinically characterized as cognitively normal (n=19) or with MCI (amnestic: n=18; non‐amnestic: n=11). Diagnostic groups did not differ with respect to years of age and education, systolic and diastolic blood pressure, proportions of men and women, proportions of APOE ε4 allele carriers, or plasma biomarker levels. Processing of dMRI data followed the MRtrix fixel‐based analysis (FBA) framework to estimate voxelwise CX data for all participants. Result Voxelwise regression of whole‐brain CX on pTau‐181 levels revealed a significant positive effect in the dorsal cingulum bundle and adjacent corpus callosum. Post hoc regression of mean CX sampled from significant voxels on pTau‐181 showed greater pTau‐181 level strongly predicts higher CX in this region (partial‐R=0.579, p<0.001), even while controlling for age, education, and Montreal Cognitive Assessment (MoCA) score. Path analysis linking pTau‐181 and cognition showed elevated circulating pTau‐181 levels strongly predict increased white matter complexity in mid‐cingulum bundle, which in turn predicts reduced cognitive performance on measures of working memory, list learning, and semantic fluency. Conclusion Microstructural complexity in crossing fiber WM regions provides a sensitive marker of early WM alterations associated with elevated plasma phospho‐tau and cognitive decrements in non‐demented older adults.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.040
GPT teacher head0.293
Teacher spread0.253 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2022
Admission routes1
Has abstractyes

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