Neuroinflammatory fluid biomarkers in patients with Alzheimer’s disease: a systematic literature review
Bibliographic record
Abstract
INTRODUCTION: Neuroinflammation is associated with both early and late stages of the pathophysiology of Alzheimer's disease (AD). Fluid biomarkers are gaining significance in clinical practice for diagnosis in presymptomatic stages, monitoring, and disease prognosis. This systematic literature review (SLR) aimed to identify fluid biomarkers for neuroinflammation related to clinical stages across the AD continuum and examined long-term outcomes associated with changes in biomarkers. METHODS: The SLR was conducted per the Cochrane Handbook for Systematic Reviews of Interventions and Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. We used PubMed®, Embase®, and Cochrane Collaboration databases to search for articles in English (between 2012 and 2022) on AD or mild cognitive impairment due to AD, using "neuroinflammation" or other "immune" search strings. Two independent reviewers screened titles and examined data from full-text articles for the SLR. RESULTS: After the initial screening, 54 studies were prioritized for data extraction based upon their relevance to the SLR research questions. Nine studies for YKL-40, seven studies for sTREM2, and 11 studies for GFAP examined the relationship between the neuroinflammatory biomarkers and the clinical stage of the disease. Nine longitudinal studies further explored the association of fluid biomarkers with long-term clinical outcomes of disease. Cerebrospinal fluid (CSF) levels of YKL-40 were elevated in patients with AD dementia, while CSF sTREM2 levels were more strongly associated with preclinical and early symptomatic stages of AD. Plasma GFAP levels remained consistently elevated both in patients with AD dementia and individuals in preclinical stages with β-amyloid pathology. Longitudinal changes in plasma GFAP appeared to be predictive of cognitive decline in patients over time. DISCUSSION: Neuroinflammatory biomarkers are associated with AD progression. More longitudinal studies in the preclinical and MCI stages of AD are needed to validate fluid biomarkers for diagnosis, disease monitoring, and prognosis in clinical practice.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.038 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.010 |
| Bibliometrics | 0.012 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 source (direct Gemma or distilled Codex), 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".