AGTR2 absence or antagonism prevents cystic fibrosis pulmonary manifestations
Bibliographic record
Abstract
BACKGROUND: Pulmonary disease remains the primary cause of morbidity and mortality for individuals with cystic fibrosis (CF). Variants at a locus on the X-chromosome containing the type 2 angiotensin II receptor gene (AGTR2) were identified by a large GWAS as significantly associating with lung function in CF patients. We hypothesized that manipulating the angiotensin-signaling pathway may yield clinical benefit in CF. METHODS: Genetic subset analysis was conducted on a local CF cohort to extend the GWAS findings. Next, we evaluated pulmonary function in CF mice with a deleted AGTR2 gene, and in those who were given subcutaneous injections of PD123,319, a selective AGTR2 antagonist for 12 weeks beginning at weaning. RESULTS: The genetic subset analysis replicated the initial GWAS identified association, and confirmed the association of this locus with additional lung function parameters. Studies in genetically modified mice established that absence of the AGTR2 gene normalized pulmonary function indices in two independent CF mouse models. Further, we determined that pharmacologic antagonism of AGTR2 improved overall pulmonary function in CF mice to near wild-type levels. CONCLUSIONS: These results identify that reduced AGTR2 signaling is beneficial to CF lung function, and suggest the potential of manipulating the angiotensin-signaling pathway for treatment and/or prevention of CF pulmonary disease. Importantly, the beneficial effects were not CF gene mutation dependent, and were able to be reproduced with pharmacologic antagonism. As there are clinically approved drugs available to target the renin-angiotensin signaling system, these findings may be quickly translated to human clinical trials.
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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".