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Record W4407931128 · doi:10.1093/braincomms/fcaf094

Plasma biomarkers for diagnosis and differentiation and their cognitive correlations in patients with Alzheimer’s disease

2025· article· en· W4407931128 on OpenAlexaboutno aff
Wenhao Sun, Shan Ye, Yu Wang, Huifeng Chen, Ping Che, Jingshan Chen, Nan Zhang

Bibliographic record

VenueBrain Communications · 2025
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsDementiaInternal medicineFrontotemporal lobar degenerationVascular dementiaFrontotemporal dementiaAlzheimer's diseaseMedicineDiseaseGastroenterologyNeuropsychologyNeurologyBiomarkerPathologyCognitionPsychologyPsychiatryChemistryBiochemistry

Abstract

fetched live from OpenAlex

Abstract Increasing evidence has shown the potential value of plasma biomarkers in Alzheimer’s disease diagnosis. This study aimed to determine the diagnostic and differential values of emerging plasma biomarkers for different types of dementia in a Chinese population and to explore their cognitive correlations. One hundred twenty patients with dementia, including 51 Alzheimer’s disease patients, 54 subcortical ischaemic vascular dementia (SIVD) patients and 15 frontotemporal lobar degeneration (FTLD) patients were recruited alongside 27 cognitively unimpaired (CU) control subjects. Global and domain-specific cognition was assessed in all participants by a battery of neuropsychological tests. Plasma amyloid-beta (Αβ)42, Aβ40 and total tau (in CU controls and Alzheimer’s disease patients) and phosphorylated tau at threonine-181 (P-tau181), neurofilament light (NfL) and glial fibrillar acidic protein (GFAP) levels (in all participants) were measured using the single-molecule array platform. The levels of all biomarkers differed between Alzheimer’s disease patients and CU controls, with P-tau181 and GFAP levels and the Aβ42/P-tau181 ratio best differentiating the two groups [area under the curve (AUC) = 0.966, 0.932 and 0.927, respectively]. P-tau181 and GFAP levels were greater in the Alzheimer’s disease group than in the other two patient groups and showed the best performance in distinguishing Alzheimer’s disease patients from SIVD (AUC = 0.922) and FTLD patients (AUC = 0.894), respectively. Moreover, compared with that in the CU group, the GFAP level was elevated in the SIVD group, and the NfL level was elevated in all patient groups. Compared with other single biomarkers, the plasma Aβ42/P-tau181 ratio correlated with broader cognitive domains, including global cognition [Mini-Mental Status Examination (MMSE), r = 0.314, P = 0.027; Montreal Cognitive Assessment (MoCA), r = 0.313, P = 0.043], memory (r = 0.339, P = 0.016), language (r = 0.333, P = 0.020), attention and information processing speed (r = 0.369, P = 0.008), executive function (r = 0.305, P = 0.031) and visuospatial function memory (r = 0.453, P = 0.001). P-tau181 was an optimal plasma biomarker for identifying Alzheimer’s disease patients and differentiating Alzheimer’s disease patients from SIVD and FTLD patients. Moreover, the GFAP level and the Aβ42/P-tau181 ratio showed potential diagnostic and progression monitoring value, respectively, for Alzheimer’s disease patients.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.039
Threshold uncertainty score0.296

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 head0.031
GPT teacher head0.326
Teacher spread0.295 · 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

Citations5
Published2025
Admission routes1
Has abstractyes

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