Bi-directional Association of Cerebrospinal Fluid Immune Markers with Stage of Alzheimer’s Disease Pathogenesis
Bibliographic record
Abstract
Immune mechanisms may be important in the pathogenesis of Alzheimer's disease (AD). Yet, studies comparing cerebrospinal fluid (CSF) and plasma immune marker levels of healthy and demented individuals have yielded conflicting results. We analyzed CSF from 101 members of the parental history-positive PREVENT-AD cohort of healthy aging adults, and 237 participants without dementia from the initial cohort of the Alzheimer's Disease Neuroimaging Initiative (ADNI-1). Following recent practice, we used the biomarkers total-tau and amyloid-β1-42 to allocate participants from each study into four stages of AD pathogenesis: Stage 0 (no abnormality), Stage 1 (reduced amyloid-β1-42), Stage 2 (reduced amyloid-β1-42 and increased total-tau), or "Suspected Non-Alzheimer Pathology" (elevated total-tau only). Investigating the PREVENT-AD participants' CSF assay results for 19 immune/inflammatory markers, we found six that showed a distinct bi-directional relationship with pathogenetic stage. Relative to Stage 0, these were diminished at Stage 1 but strongly increased at Stage 2. Among the ADNI participants (90 healthy controls and 147 with mild cognitive impairment), we found that 23 of 83 available CSF markers also showed this distinct pattern. These results support recent observations that immune activation may become apparent only after the onset of both amyloid and tau pathologies. Unexpectedly, they also suggest that immune marker activity may diminish along with earliest appearance of amyloid-β plaque pathology. These findings may explain discordant results from past studies, and suggest the importance of characterizing the extent of AD pathology when comparing clinical groups.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".