LDLR, VLDLR and APOBR in the pathophysiology of sporadic Alzheimer’s disease
Bibliographic record
Abstract
Abstract Background Alzheimer’s disease (AD) and cholesterol homeostasis have long been linked, most notably by the identification of apolipoprotein E‐ε4 allele as the strongest risk factor. Yet the mechanism by which its pathogenic isoform ε4 impacts AD has remained elusive. Different GWA studies have identified other potential risk factors, many of which are also involved in the maintenance, homeostasis, mobilisation, and distribution of cholesterol. The aim of this study was to analyse three candidate genes involved in cholesterol metabolism, which showed preliminary significance and are strongly related to cholesterol processes and APOE neurobiology. Method The three candidates are the receptors LDLR, VLDLR and APOBR which were analysed using neocortical mRNA data from the Religious Orders study/ Memory and Aging Project ROSMAP cohort’s dataset. The receptor mRNA levels were contrasted against several AD pathological markers, such as Braak and CERAD stages. Other apolipoprotein mRNA levels were also analysed for significance. Age, Sex and ApoE4 genotype were also tested for effect. Result Preliminary analyses showed significant correlation between mRNA levels of these receptors (most strongly VLDLR) and Braak stages (VLDLR p < 0.008), CERAD stages (VLDLR p < 0.001) as well as several proteins known to be involved in AD pathophysiology. VLDLR expression levels did not correlate with APOE mRNA levels (VLDLR; R2=0.176, p > 0.05) and were only significant in APOε4 negative subjects when split for APOε4 genotype (VLDLR Braak p < 0.003). Conclusion The three receptors analysed so far appear to be involved at some level with AD pathophysiology. They will be further studied and investigated in both, symptomatic and pre‐symptomatic AD. The relationship between the receptors and APOE pathophysiology in sporadic AD remains unclear.
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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) | 0.000 | 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 | 0.000 |
| 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".