Rapid Progression from Mild Cognitive Impairment to Alzheimer’s Disease in Subjects with Elevated Levels of Tau in Cerebrospinal Fluid and the <i>APOE </i>ε<i>4</i>/ε<i>4</i> Genotype
Bibliographic record
Abstract
BACKGROUND/AIMS: Increased cerebrospinal fluid (CSF) tau, decreased CSF amyloid-beta42 (Abeta42) and the apolipoprotein E gene (APOE) epsilon4 allele predict progression from mild cognitive impairment (MCI) to Alzheimer's disease (AD). Here, we investigated these markers to assess their predictive value and influence on the rate of disease progression. METHODS: Using ELISA, we measured the CSF biomarkers in 47 AD patients, 58 patients with MCI and 35 healthy control subjects. Twenty-eight MCI patients revisited the clinic and half of them progressed to AD during a period of 3-12 years. RESULTS: The expected changes in CSF total (T)-tau, phosphorylated (P)-tau and Abeta42 levels were found in AD, confirming the diagnostic value of these biomarkers. We were also able to corroborate an increased risk for progression from MCI to AD with elevated CSF T-tau and P-tau and with the presence of the APOE epsilon4/epsilon4 genotype, but not with decreased Abeta42. Finally, for the first time we demonstrated that MCI subjects with high CSF T-tau or P-tau and APOE epsilon4 homozygosity progressed faster from MCI to AD. CONCLUSIONS: CSF T-tau and P-tau as well as the APOE epsilon4/epsilon4 genotype are robust predictors of AD and are also associated with a more rapid progression from MCI to AD.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".