The Intrarenal RAS Upregulates SGLT2 Expression and SGLT2 Inhibitors Attenuate Angiotensin-II Induced Hypertensive Kidney Injury in Mice
Bibliographic record
Abstract
Background: Clinical trials have shown that SGLT2 inhibitors (SGLT2i) improve both cardiac and renal outcome in several diseases. However, the mechanisms underlying regulation of SGLT2 gene expression remain unclear. Here, we studied whether the intrarenal renin-angiotensin-system (RAS) modulates SGLT2 expression and SGLT2i efficacy. Methods: We analyzed the association between RAS-related genes and SGLT2 gene expression in the tubulointerstitial compartment of the kidneys of adult non-diabetic patients in the Nephrotic Syndrome Study Network (NEPTUNE). We compared SGLT2 expression in transgenic mice overexpressing angiotensinogen (Agt) in their renal proximal tubular cells (RPTCs)(Agt-Tg) ± RAS blockers, and wild-type (WT) mice. We administered angiotensin II (AngII, 1000 ng/kg/min subcutaneously) in WT mice ± canagliflozin (Cana, 15mg/kg/day in drinking water- for 4 weeks). We also studied human immortalized RPTCs (HK2) as an in vitro model. Results: In human kidney samples (N=183 patients), SGLT2 mRNA was significantly correlated with AGT (r=0.55, p<0.001), Renin (r=0.46, p<0.001), ACE (r=0.47, p<0.001), and AT1R (r=-0.28, p<0.001), but not with AT2R. SGLT2-immunopositive staining was higher in RPTCs of Agt-Tg mice than in WT mice and this was attenuated by losartan treatment. Ang II infusion in WT mice significantly increased blood pressure, which was not reversed by Cana co-treatment. Ang II caused glomerulosclerosis, tubulointerstitial fibrosis, and albuminuria, which were all attenuated by Cana. Fractional glucose excretion was significantly higher in Ang II+Cana than WT+Cana. In vitro, AngII dose-dependently stimulated SGLT2 mRNA in HK2 cells, and these were inhibited by losartan. Conclusions: Our data demonstrate that the intrarenal RAS upregulates SGLT2 expression and show that SGLT2i ameliorate AngII-induced kidney injury independent of blood pressure. Funding: Government Support - Non-U.S.
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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 | 0.001 | 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) | 0.002 | 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".