The Trp64Arg polymorphism in the β <sub>3</sub> ‐adrenergic receptor gene is not associated with pulmonary function in cystic fibrosis
Bibliographic record
Abstract
OBJECTIVE As cystic fibrosis (CF) phenotypes are highly variable even in patients carrying the same CFTR mutations, it has been suggested that the course of CF lung disease is influenced by modifying genes other than CFTR. There is recent evidence that CFTR activity isalso regulated through β 3 ‐adrenergic receptor (β 3 ‐AR) stimulation. We therefore investigated whether polymorphisms in the β 3 ‐AR gene contribute to the course of pulmonary function in CF. METHODS The Trp64Arg β 3 ‐AR polymorphism was studied by RFLP analysis in 99 CF patients. β 3 ‐AR genotypes were related to the annual decline of FEV1, FVC and MEF50 and to age at first infection with P. aeruginosa . RESULTS Genotype distribution was Trp64Trp n=84, Trp64Arg n=14, and Arg64Arg n=1. Frequencies of the β 3 ‐AR alleles in CF patients were similar compared to healthy controls. Mean (±SD) follow‐up was 14.3±7.8 years. Mean (±SEM) annual decline of pulmonary function was 1.8±0.2 for FEV1, 1.3±0.2 for FVC, and 3.4±0.3 for MEF50. The course of pulmonary function was not different between β 3 ‐AR genotypes. There was also no difference in age at first P. aeruginosa infection . Median age at first infection was 7.5 years (quartiles 3.8‐15.2 years) in Trp64Trp and 5.7 years (quartiles 3.5‐9.4 years) in Trp64Arg patients (p=0.2, Wilcoxon sign rank test). CONCLUSIONS The Trp64Arg β 3 ‐AR gene polymorphism was not associated with the course of pulmonary function or with P. aeruginosa airway infection in CF. Therefore, these data do not suggest that the β 3 ‐AR gene acts as a modifier of CF lung disease.
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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 | 0.002 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".