Cerebrospinal fluid ceruloplasmin levels predict cognitive decline and brain atrophy in people with underlying β-amyloid pathology
Bibliographic record
Abstract
The mechanisms leading to neurodegeneration in Alzheimer's disease (AD) may involve oxidative stress and neuroinflammation. Ceruloplasmin (Cp) is a circulating protein that intersects both these pathways, since its expression is increased during the acute phase response, and the protein acts to lower pro-oxidant iron in cells. Since the role of Cp in AD, and its potential for use as a biomarker is not established, we investigated CSF Cp and its association with longitudinal outcome measures related to AD. This was an observational study of 268 people from the Alzheimer's Disease Neuroimaging (ADNI) cohort. Subjects were classified clinically as having AD, mild cognitive impairment (MCI) or were cognitively normal (CN), and were also classified as being positive for β-amyloid using established thresholds in the CSF t-tau/Aβ42 ratio. Subjects underwent cognitive tests and MRI studies every 6 months for 2 years, then yearly thereafter for up to 6 years. At baseline, CSF Cp was not associated with clinical or pathological diagnosis, but we found an unexpected association between CSF Cp and levels of CSF apolipoprotein E. In longitudinal analysis, high level of CSF Cp was associated with accelerated cognitive decline (as assessed by ADAS-Cog, CDR-SB, and MMSE) and ventricular volume enlargement in people classified as MCI and who had underlying β-amyloid pathology. These results raise new questions into the role of Cp in neuroinflammation, oxidative stress, and APOE pathways involved in AD, and reveal the potential for this protein to be used as a biomarker in disease prognostication.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".