Histone H3K27me3 demethylases regulate human Th17 cell development and effector functions by impacting on metabolism
Bibliographic record
Abstract
T helper (Th) cells are CD4+ effector T cells that play an instrumental role in immunity by shaping the inflammatory cytokine environment in a variety of physiological and pathological situations. Using a combined chemico-genetic approach we identify histone H3K27 demethylases KDM6A and KDM6B as central regulators of human Th subsets. The prototypic KDM6 inhibitor GSK-J4 increases genome-wide levels of the repressive H3K27me3 chromatin mark and leads to suppression of the key transcription factor RORγt during Th17 differentiation, whereas in mature Th17 cells an altered transcriptional program leads to a profound metabolic reprogramming with concomitant suppression of IL-17 cytokine levels and reduced proliferation. Single cell analysis reveals a specific shift from highly inflammatory cell subsets towards a resting state upon demethylase inhibition. The root cause of the observed anti-inflammatory phenotype in stimulated Th17 cells is reduced expression of key metabolic transcription factors, such as PPRC1 and c-myc. Overall, this leads to reduced mitochondrial biogenesis resulting in a metabolic switch with concomitant anti-inflammatory effects. These data are consistent with an opposing effect of GSK-J4 on Th17 T-cell differentiation pathways directly related to proliferation and effector cytokine profiles.
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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) | 0.003 | 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".