Cytochrome P450 1A1 influences obesity‐induced pulmonary hypertension
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: The contribution of obesity to pulmonary arterial hypertension (PAH) pathophysiology remains poorly understood. Adipose tissue synthesises estrogens via cytochrome P450 (CYP) 19A1 (aromatase), whereas circulating estrogens are metabolised in the lung by CYP1A1. This study investigated whether obesity predisposes to PAH through enhanced estrogen synthesis and metabolism. EXPERIMENTAL APPROACH: A normoxic, two-hit, rat model of obesity-associated pulmonary hypertension (PH) was developed, combining Sugen 5416 (Sugen, Su) with a high-fat diet (HFD). Estrogen levels in SuHFD rat plasma and epicardial adipose tissue (EAT) from PAH patients were quantified using LC-MS/MS. CYP1A1 expression was assessed in lung and cardiac adipose tissue from SuHFD rats and PAH patients. The therapeutic potential of the CYP1A1 inhibitor hesperetin was evaluated in vivo. Complementary studies used pulmonary artery smooth muscle cells (PASMCs) from PAH patients and Simpson-Golabi-Behmel syndrome (SGBS) adipocytes. KEY RESULTS: HFD-fed rats of both sexes developed mild PH, which Sugen moderately exacerbated. EAT from PAH patients exhibited up-regulated aromatase and CYP1A1 expression, along with elevated estrogen levels. Circulating estrone was increased in male SuHFD rats. Pulmonary CYP1A1 expression was elevated in SuHFD rats and PAH patients. Hesperetin attenuated obesity-associated PH, reducing CYP1A1 expression in SuHFD rat lungs and PAH PASMCs. CYP1A1 induction in female SuHFD rat pericardial adipose tissue and Sugen-treated SGBS adipocytes was also tempered. CONCLUSION AND IMPLICATIONS: These findings implicate augmented estrogen production by adipose tissue and elevated pulmonary CYP1A1 expression in the pathogenesis of obesity-associated PH. CYP1A1 may represent a novel therapeutic target in obese PAH patients.
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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 | 0.000 |
| 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 | 0.001 |
| 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".