Long genes are more frequently affected by somatic mutations and show reduced expression in Alzheimer's disease: Implications for disease etiology
Bibliographic record
Abstract
Aging, the greatest risk factor for Alzheimer's disease (AD), may lead to the accumulation of somatic mutations in neurons. We investigated whether somatic mutations, specifically in longer genes, are implicated in AD etiology. First, we modeled the theoretical likelihood of genes being affected by aging-induced somatic mutations, dependent on their length. We then tested this model and found that long genes are indeed more affected by somatic mutations and that their expression is more frequently reduced in AD brains. Furthermore, using gene-set enrichment analysis, we investigated the potential consequences of such long gene disruption. We found that long genes are involved in synaptic adhesion and other synaptic pathways that are predicted to be inhibited in the brains of AD patients. Taken together, our findings indicate that long gene-dependent synaptic impairment may contribute to AD pathogenesis.
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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".