Epigenetic modulation of β cells by interferon-α via PNPT1/mir-26a/TET2 triggers autoimmune diabetes
Bibliographic record
Abstract
Type 1 diabetes (T1D) is caused by autoimmune destruction of pancreatic β cells. Mounting evidence supports a central role for β cell alterations in triggering the activation of self-reactive T cells in T1D. However, the early deleterious events that occur in β cells, underpinning islet autoimmunity, are not known. We hypothesized that epigenetic modifications induced in β cells by inflammatory mediators play a key role in initiating the autoimmune response. We analyzed DNA methylation (DNAm) patterns and gene expression in human islets exposed to IFN-α, a cytokine associated with T1D development. We found that IFN-α triggers DNA demethylation and increases expression of genes controlling inflammatory and immune pathways. We then demonstrated that DNA demethylation was caused by upregulation of the exoribonuclease, PNPase old-35 (PNPT1), which caused degradation of miR-26a. This in turn promoted the upregulation of ten-eleven translocation 2 (TET2) enzyme and increased 5-hydroxymethylcytosine levels in human islets and pancreatic β cells. Moreover, we showed that specific IFN-α expression in the β cells of IFNα-INS1CreERT2 transgenic mice led to development of T1D that was preceded by increased islet DNA hydroxymethylation through a PNPT1/TET2-dependent mechanism. Our results suggest a new mechanism through which IFN-α regulates DNAm in β cells, leading to changes in expression of genes in inflammatory and immune pathways that can initiate islet autoimmunity in T1D.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".