Shifts in podocyte histone H3K27me3 regulate mouse and human glomerular disease
Bibliographic record
Abstract
Histone protein modifications control fate determination during normal development and dedifferentiation during disease. Here, we set out to determine the extent to which dynamic changes to histones affect the differentiated phenotype of ordinarily quiescent adult glomerular podocytes. To do this, we examined the consequences of shifting the balance of the repressive histone H3 lysine 27 trimethylation (H3K27me3) mark in podocytes. Adriamycin nephrotoxicity and subtotal nephrectomy (SNx) studies indicated that deletion of the histone methylating enzyme EZH2 from podocytes decreased H3K27me3 levels and sensitized mice to glomerular disease. H3K27me3 was enriched at the promoter region of the Notch ligand Jag1 in podocytes, and derepression of Jag1 by EZH2 inhibition or knockdown facilitated podocyte dedifferentiation. Conversely, inhibition of the Jumonji C domain-containing demethylases Jmjd3 and UTX increased the H3K27me3 content of podocytes and attenuated glomerular disease in adriamycin nephrotoxicity, SNx, and diabetes. Podocytes in glomeruli from humans with focal segmental glomerulosclerosis or diabetic nephropathy exhibited diminished H3K27me3 and heightened UTX content. Analogous to human disease, inhibition of Jmjd3 and UTX abated nephropathy progression in mice with established glomerular injury and reduced H3K27me3 levels. Together, these findings indicate that ostensibly stable chromatin modifications can be dynamically regulated in quiescent cells and that epigenetic reprogramming can improve outcomes in glomerular disease by repressing the reactivation of developmental pathways.
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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) | 0.002 | 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".