Abstract 13142: Combined Treatment With Dapagliflozin and Exenatide is More Cardioprotective Than Either Agent Alone in a Non-Diabetic Mouse Model of Ischemia-Reperfusion Injury
Bibliographic record
Abstract
Introduction: Sodium-glucose cotransporter 2 inhibitors (SGLT2i) and glucagon-like peptide-1 receptor agonists (GLP-1RA) have individually shown cardiovascular benefits in patients with type 2 diabetes (T2D). SGLT2i also reduced events in patients with reduced ejection fraction heart failure, with or without T2D. However, it is not known whether the cardiovascular effects of SGLT2i and GLP-1RA are through shared or distinct mechanisms, and whether combining these agents would confer additive cardioprotection against ischemia-reperfusion injury (IRI) in the absence of diabetes. Methods & Results: Non-diabetic male C56BL/6-J mice randomized to 7-d treatment with SGLT2i dapagliflozin (Dapa) and/or GLP-1RA exenatide (Ex-4) or vehicle-controls underwent IRI via 30-min left anterior descending (LAD) artery ligation. Analysis of late cardiac remodeling at d-28 post-IRI revealed preserved ejection fraction (EF) in mice treated with Dapa+Ex4 (50±2%; n=12, P<0.05) vs. vehicle-treated controls (36±3; n=11, P<0.05), whereas treatment with Dapa- and Ex-4-alone showed no such benefit. These improvements in LV function were associated with reduced infarct size (%LV) in mice treated with Dapa+Ex4 (17±3; n=8, P<0.001) and Ex-4-alone (29±3; n=10, P<0.05) vs. vehicle-control (44±5; n=10). Metabolome and merged proteome+phosphoproteome analyses revealed systemic and myocardial metabolic modulation following 7-d Dapa+Ex-4 treatment, with distinct enrichment of mitochondrial electron transport chain pathways. Cardiomyocytes isolated from mice treated in vivo for 7-d also showed enhanced aerobic respiration as measured by oxygen consumption rate (OCR;17.6±1.7 pmol/min/μg protein; n=4 mice) compared Dapa- (8.9±0.8; n=3, P<0.001), Ex-4-alone (11.4±0.9; n=3, P<0.01) and vehicle-treated controls (9.5±0.6; n=5, P<0.001). Conclusions: Combined therapy with SGLT2i+GLP-1RA in non-diabetic mice better prevented late cardiac remodeling after IRI compared to either agent alone or vehicle controls. These findings provide rationale for the combined use of these agents in a condition (IRI) for which there remains no approved therapy, and implicate metabolic modulation as a cardioprotective strategy in the absence of diabetes.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 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 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".