Exploratory study on immune phenotypes in Alzheimer’s disease and vascular dementia
Bibliographic record
Abstract
Background and purpose The differentiation of Alzheimer’s disease (AD) dementia from vascular dementia (VaD) and mixed‐type dementia (mixed dementia) requires stepwise analysis and usually occurs late in the disease process. Early diagnosis and therapy monitoring would benefit greatly from the identification of biomarkers of neurodegeneration, especially blood biomarkers. To this end, the aim of the present pilot study was to investigate differences in the distribution of peripheral T‐cell populations in patients with AD compared to VaD and mixed dementia. Methods Flow cytometry was performed on blood samples from 11 patients with AD, six with VaD and six with mixed dementia, as well as 17 healthy control subjects (HCs). CD4+ and CD8+ T cells were typed for expression of CD45, CD27, CD28, CD25, FoxP3, CCR4 and CCR6; the other leukocytes were also assessed. Functionally, immune cell uptake of the β‐amyloid (Aβ) toxic fragment (Aβ 1–42 ) was also evaluated. Results A higher proportion of CD4+CD28− memory T cells and a reciprocal reduction of CD4+CD28+CD27+ naïve T lymphocytes was detected in all patient groups relative to controls. Significantly fewer CD4+CD25+FoxP3 regulatory T cells were present in patients with VaD, and significantly more CCR6+ and CCR4+ CD4+ T cells in those with AD. Higher CCR6+ T‐cell frequencies were also present in patients with mixed dementia, potentially due to the inflammation and immune cell chemoattraction triggered by Aβ. Conclusions The present study was a comprehensive investigation comparing different kinds of dementia, revealing differentially expressed peripheral markers that are potentially useful for early AD, VaD and mixed dementia diagnoses, and that would assist in proper treatments for these disparate diseases. Validation is now required.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".