Epigenetic regulation of TXNIP-mediated oxidative stress and NLRP3 inflammasome activation contributes to SAHH inhibition-aggravated diabetic nephropathy
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Bibliographic record
Abstract
S-adenosylhomocysteine (SAH) is hydrolyzed by SAH hydrolase (SAHH) to homocysteine and adenosine. Increased plasma SAH levels were associated with disturbed renal function in patients with diabetes. However, the role and mechanism of SAHH in diabetic nephropathy is still unknown. In the present study, we found that inhibition of SAHH by using its inhibitor adenosine dialdehyde (ADA) accumulates intracellular or plasma SAH levels and increases high glucose-induced podocyte injury and aggravates STZ-induced diabetic nephropathy, which is associated with Nod-like receptor protein 3 (NLRP3) inflammasome activation. Inhibition or knockout of NLRP3 attenuates SAHH inhibition-aggravated podocyte injury and diabetic nephropathy. Additionally, SAHH inhibition increases thioredoxin-interacting protein (TXNIP)-mediated oxidative stress and NLRP3 inflammasome activation, but these effects were not observed in TXNIP knockout mice. Mechanistically, SAHH inhibition increased TXNIP by inhibiting histone methyltransferase enhancer of zeste homolog 2 (EZH2) and reduced trimethylation of histone H3 lysine 27 and its enrichment at promoter of early growth response 1 (EGR1). Moreover, EGR1 is activated and enriched at promoters of TXNIP by SAHH inhibition and is essential for SAHH inhibition-induced TXNIP expression. Inhibition of EGR1 protected against SAHH inhibition-induced NLRP3 inflammasome activation and oxidative stress and diabetic nephropathy. Finally, the harmful effects of SAHH inhibition on inflammation and oxidative stress and diabetic nephropathy were also observed in heterozygote SAHH knockout mice. These findings suggest that EZH2/EGR1/TXNIP/NLRP3 signaling cascade contributes to SAHH inhibition-aggravated diabetic nephropathy. Our study firstly provides a novel insight into the role and mechanism of SAHH inhibition in diabetic nephropathy.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 it