The Mevalonate Cascade as a Target to Suppress Extracellular Matrix Synthesis by Human Airway Smooth Muscle
Bibliographic record
Abstract
Smooth muscle cells promote fibroproliferative airway remodeling in asthma, and transforming growth factor β1 (TGFβ1) is a key inductive signal. Statins are widely used to treat hyperlipidemia. Growing evidence indicates they also exert a positive impact on lung health, but the underlying mechanisms are unclear. We assessed the effects of 3-hydroxy-3-methlyglutaryl-coenzyme A (HMG-CoA) reductase inhibition with simvastatin on the fibrotic function of primary cultured human airway smooth muscle cells. Simvastatin blocked de novo cholesterol synthesis, but total myocyte cholesterol content was unaffected. Simvastatin also abrogated TGFβ1-induced collagen I and fibronectin expression, and prevented collagen I secretion. The depletion of mevalonate cascade intermediates downstream from HMG-CoA underpinned the effects of simvastatin, because co-incubation with mevalonate, geranylgeranylpyrophosphate, or farnesylpyrophosphate prevented the inhibition of matrix protein expression. We also showed that human airway myocytes express both geranylgeranyl transferase 1 (GGT1) and farnesyltransferase (FT), and the inhibition of GGT1 (GGTI inhibitor-286, 10 μM), but not FT (FTI inhibitor-277, 10 μM), mirrored the suppressive effects of simvastatin on collagen I and fibronectin expression and collagen I secretion. Moreover, simvastatin and GGTI-286 both prevented TGFβ1-induced membrane association of RhoA, a downstream target of GGT1. Our findings suggest that simvastatin and GGTI-286 inhibit synthesis and secretion of extracellular matrix proteins by human airway smooth muscle cells by suppressing GGT1-mediated posttranslational modification of signaling molecules such as RhoA. These findings reveal mechanisms related to evidence for the positive impact of statins on pulmonary health.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".