Growth Hormone Replacement Decreases Plasma Levels of Matrix Metalloproteinases (2 and 9) and Vascular Endothelial Growth Factor in Growth Hormone–Deficient Individuals
Bibliographic record
Abstract
BACKGROUND: Matrix metalloproteinases (MMP) are implicated in cardiovascular disease. Growth hormone (GH) deficiency is associated with increased cardiovascular mortality. We assessed whether GH replacement, in GH-deficient adults, has any effect on plasma levels of MMP-2 and MMP-9 and on vascular endothelial growth factor (VEGF), known to activate MMPs. METHODS AND RESULTS: The study comprised 66 GH-deficient adults, 37.8+/-14.7 years of age (37 female). Plasma MMP-2 and MMP-9, VEGF, and insulin-like growth factor-1 (IGF-1) were measured at baseline (V1), at 12 months (V2), and at 24 months of GH treatment (V3). IGF-1 levels rose under GH replacement (mean+/-SD): V1, 151.6+/-91.9 microg/mL; V2, 270.2+/-114.8 microg/mL; and V3, 266.2+/-109.8 (V1 versus V2; P<0.001: V2 versus V3; P=0.76). MMP-9 exhibited the most pronounced and sustained decline from 1248.0+/-651.1 ng/mL at V1, 949.2+/-457.7 ng/mL at V2, and 760.8+/-386.1 ng/mL at V3 (P<0.001 at all time points). A similar pattern was detected for VEGF levels: 358.5+/-209.0 pg/mL at V1, 310.6+/-225.7 pg/mL at V2 (P<0.001), and 283.7+/-202.7 pg/mL at V3 (V2 versus V3; P=0.005). MMP-2 demonstrated a significant decline initially from V1 to V2 (1134.4+/-217.8 ng/mL versus 1074.5+/-203.0 ng/mL, respectively; P=0.031), reaching a plateau at V3 (1072.3+/-220.2 ng/mL) (V2 versus V3; P=0.93). A negative relation existed between MMP-9 versus IGF-1 and MMP-2 versus IGF-1 (P<0.001 and P=0.007, respectively) as well as between VEGF and IGF-1 (P<0.001). CONCLUSIONS: These changes in MMPs and VEGF may contribute to the anticipated reduction in vascular mortality in hypopituitary adults receiving GH replacement.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.001 | 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".