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Record W4406209728 · doi:10.1002/alz.092210

Association of Blood‐Based Biomarkers: GFAP, Amyloid 42/40 and Perivascular Spaces in Relation to Cognitive Domains in Vascular Cognitive Impairment Participants

2024· article· en· W4406209728 on OpenAlexaboutno aff
Jia Dong James Wang, Yi Jin Leow, Ashwati Vipin, Gurveen Kaur Sandhu, Pricilia Tanoto, Maleeha Azam, Fatin Zahra Zailan, Faith Phemie Hui En Lee, Smriti Ghildiyal, Shan Yao Liew, Isabelle Yu Zhen Tan, Nagaendran Kandiah

Bibliographic record

VenueAlzheimer s & Dementia · 2024
Typearticle
Languageen
FieldMedicine
TopicIntracranial Aneurysms: Treatment and Complications
Canadian institutionsnot available
Fundersnot available
KeywordsAssociation (psychology)Cognitive impairmentPerivascular spaceCognitionPathologyAmyloid (mycology)Relation (database)MedicinePsychologyDiseaseNeuroscienceComputer science

Abstract

fetched live from OpenAlex

Abstract Background Perivascular spaces (PVS) are fluid‐filled spaces in the brain, hypothesized in promoting clearance of metabolites implicated in dementia through glymphatic system drainage. PVS are classified according to Grades (0‐4). Blood‐based biomarkers including Glial fibrillary acidic protein (GFAP), Amyloid β 42/40 (Aβ42/40) ratio have shown promise in diagnosing and prognosing dementia. However, the association between blood‐based biomarkers and PVS remains relatively unexplored in Vascular Cognitive Impairment (VCI) participants. Thus, this study aims to characterize association between blood‐based biomarkers and PVS in relation to cognitive domains in VCI participants. Method Participants from the Biomarkers and Cognition Study, Singapore were included and VCI was defined in participants with confluent white matter hyperintensities (WMH), >1 lacunae and Montreal Cognitive Assessment (MoCA) score <26. 108 participants (mean age 67.3, education years 13.3, 51.9% females) were included. Normality tests, multivariate ordinal correlation analysis was performed to understand association between blood‐based biomarkers and PVS grade, with correction for age, diastolic blood pressure and WMH. Aβ42/40 and GFAP ratio values of 0.05 and 54.1pg/ml were utilized to segregate VCI participants to different subgroups (high vs low levels) and their association with cognitive domain performance was assessed. Result Higher GFAP (p=0.026) and lower Aβ42/40 ratio (p=0.049) was associated with higher PVS grade. In the low Aβ42/40 ratio subgroup, higher PVS grade was most significantly associated with executive function impairment (p = 0.045, β = 0.612). For the subgroups of high Aβ42/40 ratio (p=0.017, β = 0.325), low GFAP (p = 0.027, β = 0.610), high GFAP (p = 0.006, β = 0.375), higher PVS grade was most significantly associated with learning and memory impairment. Conclusion These results demonstrate that low Aβ42/40 ratio, high GFAP levels were associated with higher PVS grade in VCI participants, suggesting their utility as markers for VCI. Furthermore, higher PVS Grade in VCI participants with low Aβ42/40 ratio were associated with executive function impairment compared to other subgroups which were associated with learning and memory impairment. This could be an important clinical marker when examining patients with high PVS Grade as it could be associated with a more sinister disease progression.

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 score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.021
GPT teacher head0.282
Teacher spread0.261 · 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

Citations3
Published2024
Admission routes1
Has abstractyes

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