Effect of Semaglutide on Vascular Regenerative Cells in People at Elevated Risk for Atherosclerosis
Bibliographic record
Abstract
Background: Cardiovascular outcome trials demonstrated that glucagon-like peptide-1 receptor agonist (GLP-1RA) treatment can reduce major adverse cardiovascular events (MACE) in people with type 2 diabetes (T2D) and/or obesity. However, the mechanisms of vascular benefit remain unknown. In particular, the mechanisms of semaglutide, a potently cardio-protective GLP-1RA that can reduce MACE by up to 26%, requires further elucidation from an immune and vascular standpoint. While the effect of semaglutide on reducing key biomarkers of inflammation are well-established, impact on broader immunomodulatory processes such as hematopoieisis remains elusive. The objective of this thesis was to understand the relationship between GLP-1RA therapy and circulating vascular regenerative (VR) progenitor cells with potent pro-angiogenic,vasculogenic and arteriogenic activity. Aims and Methods: We aimed to determine: 1) the correlation between GLP-1RA use and VR cell content in people with T2D through a retrospective analysis of 92 individuals with T2D sub-classified based on ongoing medication use; 2) whether semaglutide administration could increase VR cell content over 6 months through SEMA-VR CardioLink-15, an open-label, randomized controlled trial that compared the effects of usual care (n=24) versus subcutaneous semaglutide (n=22) in adults with T2D and/or obesity; and 3) the effect of semaglutide across a network of immunomodulatory pathways, using an exploratory serum proteomic analysis of 89 circulating proteins measured through Olink®. Results: In individuals with T2D, background use of GLP-1RA (n=22) was associated with greater VR cell content compared to SGLT2i use (n=42) or use of neither therapy (n=30). SEMA-VR CardioLink-15 confirmed this association, demonstrating that 6-month semaglutide led to increased number of circulating VR cells (hematopoietic myeloid and endothelial precursor cells), while reducing pro-inflammatory granulocyte precursors expressing the neutrophil activation marker CD66b and chemokine receptor CXCR2. Olink® serum proteomic analyses revealed semaglutide induced differential expression of 16 proteins involved in cytokine signaling and immune surveillance, corresponding with a downregulation of biological processes involved in pro-inflammatory TNF and interleukin-signaling via NF-kB, while also regulating hematopoietic differentiation pathways. Conclusion: This thesis provides novel insight into the mechanisms of cardiovascular protection mediated by semaglutide through the enhancement of vessel-regenerative progenitor cell content and regulation of inflammatory networks.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.002 | 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 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".