O2‐13‐05: CSF Markers of Inflammation and Alzheimer's Disease Pathogenesis in the Cognitively Intact Prevent‐Ad Cohort
Bibliographic record
Abstract
The decades-long pre-symptomatic stages of AD offer a window of opportunity for evaluation of candidate interventions that may slow disease progression and defer onset of symptoms. Among such potential interventions are anti-inflammatory treatments. We therefore investigated the relationship of 45 inflammatory markers in CSF with a common metric for AD pathogenesis. We recruited >350 cognitively intact persons aged 60+ with a parental history of AD-like dementia (confers ∼3-fold increased risk of AD). From this “PREVENT-AD” cohort, we enrolled 210 into INTREPAD, a two-year placebo-controlled cognitive- and biomarker-endpoint trial of naproxen-sodium 220mg b.i.d. as a potential AD preventive. Among these, 107 participants agreed to serial lumbar punctures at baseline, 3, 12, and 24 months. In pilot work with 20 CSF samples, we assayed baseline CSF for 45 inflammatory markers using both the Luminex “Milliplex” and MesoScale Discovery (MSD) platforms. Using Innotest ELISA kits, we assayed the same CSF samples for Aβ42, total-tau (t-tau) and P-tau. The Luminex and MSD assays produced generally consistent results for 21 overlapping inflammatory markers (Figure 1C shows results for IP-10), although ceiling effects may limit MSD for some markers (Figure 1D). We analyzed the association of these and other markers with the ratio of CSF total-tau (t-tau) to Aβ42, a widely used index of disease progression. Even in this limited sample, we observed significant correlation (p <0.05) between IL-1β, IL-8, IP-10, MCP-1, or TNF-α (all measurable using both platforms) and log t-tau/Aβ42 (e.g., Figure 1A, 1B). MCP-4 and TARC were also correlated with log t-tau/Aβ42, but were measurable by MSD only. Changes in markers of AD progression may be used in high-risk populations to assess potential of candidate preventive interventions. The importance of inflammatory processes in AD pathogenesis is suggested by a strong association between several inflammatory markers and an established index of AD progression. Our results suggest a rationale for testing anti-inflammatory treatments as potential preventives that may delay onset of AD symptoms – now under investigation in INTREPAD. The longitudinal pattern of individual inflammatory markers and their response to NSAID treatment may reveal much about the etio-pathogenesis of 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".