Alterations in Gene Expression in Mutant Amyloid Precursor Protein Transgenic Mice Lacking Niemann-Pick Type C1 Protein
Bibliographic record
Abstract
Niemann-Pick type C (NPC) disease, a rare autosomal recessive disorder caused mostly by mutation in NPC1 gene, is pathologically characterized by the accumulation of free cholesterol in brain and other tissues. This is accompanied by gliosis and loss of neurons in selected brain regions, including the cerebellum. Recent studies have shown that NPC disease exhibits intriguing parallels with Alzheimer's disease, including the presence of neurofibrillary tangles and increased levels of amyloid precursor protein (APP)-derived β-amyloid (Aβ) peptides in vulnerable brain neurons. To evaluate the role of Aβ in NPC disease, we determined the gene expression profile in selected brain regions of our recently developed bigenic ANPC mice, generated by crossing APP transgenic (Tg) mice with heterozygous Npc1-deficient mice. The ANPC mice exhibited exacerbated neuronal and glial pathology compared to other genotypes [i.e., APP-Tg, double heterozygous (Dhet), Npc1-null and wild-type mice]. Analysis of expression profiles of 86 selected genes using real-time RT-PCR arrays showed a wide-spectrum of alterations in the four genotypes compared to wild-type controls. The changes observed in APP-Tg and Dhet mice are limited to only few genes involved mostly in the regulation of cholesterol metabolism, whereas Npc1-null and ANPC mice showed alterations in the expression profiles of a number of genes regulating cholesterol homeostasis, APP metabolism, vesicular trafficking and cell death mechanism in both hippocampus and cerebellum compared to wild-type mice. Intriguingly, ANPC and Npc1-null mice, with some exceptions, exhibited similar changes, although more genes were differentially expressed in the affected cerebellum than the relatively spared hippocampus. The altered gene profiles were found to match with the corresponding protein levels. These results suggest that lack of Npc1 protein can alter the expression profile of selected transcripts as well as proteins, and APP overexpression influences cerebral pathology by enhancing changes triggered by Npc1 deficiency in the bigenic line.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| 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".