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Record W7117137527 · doi:10.1002/alz70856_102306

Relationships between plasma biomarkers, neuroimaging markers and cognition in cerebral amyloid angiopathy

2025· article· en· W7117137527 on OpenAlexaffabout
Ryan T. Muir, Andrew E. Beaudin, Cheryl R. McCreary, Myrlene Gee, Krista Nelles, Nikita Nukala, Janina Valencia, Sophie Stukas, Jennifer G Cooper, Kristopher M. Kirmess, Sandra E. Black, M Hill, Cheryl L. Wellington, Richard Camicioli, Eric E. Smith

Bibliographic record

VenueAlzheimer s & Dementia · 2025
Typearticle
Languageen
FieldMedicine
TopicIntracerebral and Subarachnoid Hemorrhage Research
Canadian institutionsSunnybrook Health Science CentreUniversity of British ColumbiaUniversity of AlbertaUniversity of CalgarySunnybrook HospitalHotchkiss Brain InstituteOntario Brain InstituteUniversity of Toronto
Fundersnot available
KeywordsCerebral amyloid angiopathyCognitionNeuroimagingWhite matterCognitive declineCognitive impairmentAmyloid (mycology)Magnetic resonance imaging

Abstract

fetched live from OpenAlex

Abstract Background This study examined whether plasma Aβ 42/40, phosphorylated‐tau ( p ‐tau), neurofilament light chain (NfL) and glial fibrillary acidic protein (GFAP) may relate to cognitive function and other neuroimaging biomarkers in cerebral amyloid angiopathy. Method This is a cross‐sectional analysis of a prospective cohort study of participants with CAA who had plasma collected, underwent magnetic resonance imaging (MRI) and cognitive evaluation. Plasma Aβ was quantified independently through Simoa and immunoprecipitation‐mass spectrometry (IP‐MS), while p ‐tau181, NfL and GFAP were quantified through Simoa. Result There were 45 participants with probable CAA (Boston criteria v2.0) eligible for analysis. In multivariable linear regression, adjusting for age, sex, and years of education, higher NfL levels were associated with lower Montreal Cognitive Assessment (MoCA) total score (β=‐1.85, p = 0.02) while lower Aβ 42/40 was associated with lower speed of processing both with IP‐MS (β =0.63, p = 0.003) and Simoa (β =0.38, p = 0.02) methodology. After adjustment for age and sex, higher white matter hyperintensity (WMH) volume was associated with lower Aβ 42/40 (IP‐MS), β =‐0.48, p = 0.009 and higher p ‐tau181, β =0.35, p = 0.04, but not NfL or GFAP. Higher concentrations of plasma GFAP were associated with lower total cortical volumes (β =‐0.40, p = 0.042). Furthermore, higher levels of NfL were associated with lower global cerebrovascular reactivity (β=‐0.46, p = 0.008) and higher ordinal CAA severity scale score (aOR = 2.25, 95% CI: 1.17, 4.36, p = 0.02). Conclusion Lower plasma Aβ 42/40 was associated with lower speed of processing function, while plasma NfL was associated with worse performance on a global measure of cognitive performance, lower cerebrovascular reactivity, and higher CAA severity score. Interestingly, higher p ‐tau181 and lower Aβ 42/40 (IP‐MS) was associated with higher WMH volumes. These findings suggest that cognitive impairment in patients with CAA may be associated with markers of progressive white matter damage rather than tau‐related cortical injury.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.035
GPT teacher head0.291
Teacher spread0.256 · 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
Published2025
Admission routes2
Has abstractyes

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