OAS1: A Protective Mechanism for Alzheimer’s Disease? An Exploration of Data and Possible Mechanisms
Bibliographic record
Abstract
The immune system and neuroinflammation are now well established in the aetiology of neurodegeneration. Previous studies of transcriptomic and gene association studies have highlighted the potential of the 2′–5′ oligoadenylate synthetase 1 (OAS1) to play a role in Alzheimer’s disease. OAS1 is a viral response gene, interferon-induced, dsRNA activated enzyme, which binds RNase L to degrade dsRNA, and has been associated with COVID-19 response. This study explores whether a viral defence gene could play a vital role in neurodegeneration pathology. The genotyping of five SNPs across the OAS1 locus was conducted in the Brains for Dementia Research (BDR) Cohort for association with AD. RNA-sequencing data were explored for differences in OAS1 gene expression between phenotypes and genotypes. Finally, levels of dsRNA were measured in control cell lines, prior to and after exposure to amyloid oligomers and in cells harbouring a dementia-relevant mutation. No association of any of the OAS1 SNPs investigated were associated with the AD phenotype in the BDR cohort. However, gene expression data supported the previous observation that the minor allele haplotype was associated with higher levels of the OAS1 gene expression and the presence of an alternative transcript. Further to this, the presence of endogenous dsRNA was found to increase with exposure to amyloid oligomers and in the cell line with a dementia-relevant mutation. The data presented here suggest further exploration of the OAS1 gene in relation to dementia is warranted. Investigations of whether carriers of the protective OAS1 haplotype lower dsRNA presence and in turn lower inflammation and cell death are required to support the role of the gene as a moderator of neurodegeneration.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".