Reduction of SorLA/LR11, a Sorting Protein Limiting β-Amyloid Production, in Alzheimer Disease Cerebrospinal Fluid
Bibliographic record
Abstract
BACKGROUND: The sortilin-related receptor SorLA/LR11 (LR11) is a transmembrane neuronal sorting protein that reduces beta-amyloid precursor protein trafficking to secretases, notably BACE1 that generates beta-amyloid, the principal component of senile plaques in Alzheimer disease (AD). LR11 protein is reduced in patients with late-onset AD, and LR11 polymorphisms have been associated with late-onset AD. OBJECTIVE: T o detect soluble LR11 and APP in cerebrospinal fluid (CSF) from patients with AD and control subjects, as (like beta-amyloid precursor protein) LR11 is cleaved near the membrane to release a large N-terminal fragment that is secreted to media from cultured cells. DESIGN: Case-control study. SETTING: Academic research. PARTICIPANTS: Patients with AD and control subjects. MAIN OUTCOME MEASURES: We evaluated CSF LR11, beta-amyloid precursor protein, and apolipoprotein E levels by Western blot in lumbar and postmortem CSF samples. RESULTS: LR11 levels were detectable and stable during 6 months in the CSF of patients with AD. LR11 levels were significantly reduced in lumbar samples from patients with mild to moderate probable AD, as well as in ventricular CSF from patients with autopsy-confirmed AD (predominantly Braak stage III-IV). Bivariate analysis with beta-amyloid 42 and LR11 levels improved diagnostic specificity for AD. Reduced LR11 levels are significantly correlated with soluble beta-amyloid precursor protein but not apolipoprotein E levels. CONCLUSION: Reduced LR11 levels in CSF of patients with AD may have potential as a diagnostic biomarker for patients with LR11 deficits that promote beta-amyloid production or as an index of therapeutic response in late-onset AD.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".