Changes in Expression of Key Genes in Alzheimer’s Disease: A Specific Brain Tissue Change
Bibliographic record
Abstract
Alzheimer's disease (AD) is an irreversible and neurodegenerative disorder. Its etiology is not clear, but the involvement of genetic components plays a central role in the onset of the disease. In the present study, the expression of 10 genes (APP, PS1 and PS2, APOE, APBA2, LRP1, GRIN2B, INSR, GJB1, and IDE) involved in the main pathways related to AD were analyzed in auditory cortices and cerebellum from 29 AD patients and 29 healthy older adults. Raw analysis revealed tissue-specific changes in genes LRP1, INSR, and APP. A correlation analysis showed a significant effect also tissue-specific AD in APP, GRIN2B, INSR, and LRP1. Furthermore, the E4 allele of the APOE gene revealed a significant correlation with change expression tissue-specific in ABPA2, APP, GRIN2B, LRP1, and INSR genes. To assess the existence of a correction between changes in target gene expression and a probability of AD in each tissue (auditory cortices and cerebellum) an analysis of the effect of expressions was realized and showed that the reduction in the expression of the APP in auditory cortex and GRIN2B cerebellum had a significant effect in increasing the probability of AD, in the same logic, our result also suggesting that increased expression of the LRP1 and INSR genes had a significant effect on increasing the probability of AD. Our results showed tissue-specific gene expression alterations associated with AD and certainly opened new perspectives to characterize factors involved in gene regulation and to obtain possible biomarkers for AD.
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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) | 0.000 | 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) | 0.001 | 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".