Endothelin-1 Pathway Polymorphisms and Outcomes in Pulmonary Arterial Hypertension
Bibliographic record
Abstract
RATIONALE: Pulmonary arterial hypertension (PAH) is a progressive fatal disease. Variable response and tolerability to PAH therapeutics suggests that genetic differences may influence outcomes. The endothelin pathway is central to pulmonary vascular function, and several polymorphisms and/or mutations in the genes coding for endothelin (ET)-1 and its receptors correlate with the clinical manifestations of other diseases. OBJECTIVES: To examine the interaction of ET-1 pathway polymorphisms and treatment responses of patients with PAH treated with ET receptor antagonists (ERAs). METHODS: A total of 1,198 patients with PAH were prospectively enrolled from 45 U.S. and Canadian pulmonary hypertension centers or retrospectively from global sites participating in the STRIDE (Sitaxsentan To Relieve Impaired Exercise) trials. Comprehensive objective measures including a 6-minute-walk test, Borg dyspnea score, functional class, and laboratory studies were completed at baseline, before the initiation of ERAs, and repeated serially. Single-nucleotide polymorphisms from ET-1 pathway candidate genes were selected from a completed genome-wide association study performed on the study cohort. MEASUREMENTS AND MAIN RESULTS: Patient efficacy outcomes were analyzed for a relationship between ET-1 pathway polymorphisms and clinical efficacy using predefined, composite positive and negative outcome measures in 715 European descent samples. A single-nucleotide polymorphism (rs11157866) in the G-protein alpha and gamma subunits gene was significantly associated, accounting for multiple testing, with a combined improvement in functional class and 6-minute-walk distance at 12 and 18 months and marginally significant at 24 months. CONCLUSIONS: ET-1 pathway associated polymorphisms may influence the clinical efficacy of ERA therapy for PAH. Further prospective studies are needed.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".