Endothelial GLP-1 (Glucagon-Like Peptide-1) Receptor Mediates Cardiovascular Protection by Liraglutide In Mice With Experimental Arterial Hypertension
Bibliographic record
Abstract
Objective: Cardiovascular outcome trials demonstrated that GLP-1 (glucagon-like peptide-1) analogs including liraglutide reduce the risk of cardiovascular events in type 2 diabetes mellitus. Whether GLP-1 analogs reduce the risk for atherosclerosis independent of glycemic control is challenging to elucidate as the GLP-1R (GLP-1 receptor) is expressed on different cell types, including endothelial and immune cells. Approach and Results: Here, we reveal the cardio- and vasoprotective mechanism of the GLP-1 analog liraglutide at the cellular level in a murine, nondiabetic model of arterial hypertension. Wild-type (C57BL/6J), global ( Glp1r −/− ), as well as endothelial ( Glp1r f lox/floxxCdh5 cre ) and myeloid cell–specific knockout mice ( Glp1r flox/flox xLysM cre ) of the GLP-1R were studied, and arterial hypertension was induced by angiotensin II. Liraglutide treatment normalized blood pressure, cardiac hypertrophy, vascular fibrosis, endothelial dysfunction, oxidative stress, and vascular inflammation in a GLP-1R–dependent manner. Mechanistically, liraglutide reduced leukocyte rolling on the endothelium and infiltration of myeloid Ly6G − Ly6C + and Ly6G + Ly6C + cells into the vascular wall. As a consequence, liraglutide prevented vascular oxidative stress, reduced S-glutathionylation as a marker of eNOS (endothelial NO synthase) uncoupling, and increased NO bioavailability. Importantly, all of these beneficial cardiovascular effects of liraglutide persisted in myeloid cell GLP-1R-deficient ( Glp1r flox/flox xLysM cre ) mice but were abolished in global ( Glp1r −/− ) and endothelial cell–specific ( Glp1r flox/flox xCdh5 cre ) GLP-1R knockout mice. Conclusions: GLP-1R activation attenuates cardiovascular complications of arterial hypertension by reduction of vascular inflammation through selective actions requiring the endothelial but not the myeloid cell GLP-1R.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| 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".