Biomarkers of Underlying Alzheimer Disease Pathology & Neuro-inflammation, But Not Peripheral Inflammation, Predict Disease Clinically-Significant Progression in Mild-Moderate Alzheimer's Disease
Bibliographic record
Abstract
Abstract Background Novel prognostic biomarkers are urgently needed in older adults with Alzheimer Disease (AD). Peripheral inflammation, systemic inflammatory events (SIEs) and delirium are increasingly recognised as AD risk factors, but their impact on progression in established AD and temporal relationships with AD progression remains unclear. Further, whether SIEs, adverse events and delirium interact with peripheral inflammation to accelerate AD is unknown. Methods We analysed >1,000 plasma/cerebrospinal fluid samples from 333 patients with mild to moderate dementia due to AD with 18-months of follow-up. Ten cytokines/chemokines (IFN-γ, IL-6, IL-10, IL-12p70, IL-17A, TNF-α, Eotaxin, IP-10, MCP-1, MIP-1β) were quantified at baseline, 12, and 18-months using ultra-sensitive immunoassays. Baseline neurodegenerative biomarkers (p-tau217, p-tau181, t-tau, Neurofilament Light [NfL], Glial Fibrillary Acidic Protein [GFAP]) were measured using validated immunoassays. Clinical progression was assessed using Clinical Dementia Rating Scale (CDR-Sb). Results of linear and logistic regression models are reported as Beta Coefficients (B) and Odds Ratios (OR), respectively, with 95% Confidence Intervals and p-values and adjustment for important clinical confounders. Results Baseline peripheral inflammatory biomarkers (particularly IL-6 and IP-10) correlated significantly with age and sociodemographic factors but not AD severity. Peripheral inflammatory biomarkers remained remarkably stable over 18-months despite clinical-significant decline. Conversely, plasma biomarkers of AD pathophysiology (p-tau217) and neuro-inflammation (GFAP) at baseline strongly predicted accelerated AD progression (p-tau217: B:0.54, 0.18-1.08, p=0.02; GFAP: B:0.53, 0.18-0.90, p=0.002). Single (OR:2.63, 1.55-3.71, p<0.001) or multiple episodes of delirium (OR:3.45, 1.77-5.13, p<0.001), but not SIEs or adverse events, predicted greater progression on the CDR-Sb. Conclusion Biomarkers specific to AD pathology (p-tau217, GFAP) rather than peripheral inflammation had robust prognostic value in established AD. Delirium was consistently associated with clinically-meaningful decline, highlighting the importance of delirium prevention efforts in older adults with AD. Our findings add strong evidence supporting the prognostic utility of p-tau217 and GFAP in older adults with established AD.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".