Phenotypic characteristics of asthma and morbidity are associated with distinct longitudinal changes in L-arginine metabolism
Bibliographic record
Abstract
BACKGROUND: The L-arginine metabolome is dysregulated in asthma, though it is not understood how longitudinal changes in L-arginine metabolism differ among asthma phenotypes and relate to disease outcomes. OBJECTIVES: To determine the longitudinal associations between phenotypic characteristics with L-arginine metabolites and their relationships with asthma morbidity. METHODS: This is a prospective cohort study of 321 patients with asthma followed semiannually for over 18 months with assessments of plasma L-arginine metabolites, asthma control, spirometry, quality of life and exacerbations. Metabolite concentrations and ratios were transformed using the natural logarithm. RESULTS: There were many differences in L-arginine metabolism among asthma phenotypes in the adjusted models. Increasing body mass index was associated with increased asymmetric dimethylarginine (ADMA) and depleted L-citrulline. Latinx was associated with increased metabolism via arginase, with higher L-ornithine, proline and L-ornithine/L-citrulline levels, and was found to have higher L-arginine availability compared with white race. With respect to asthma outcomes, increasing L-citrulline was associated with improved asthma control and increasing L-arginine and L-arginine/ADMA were associated with improved quality of life. Increased variability in L-arginine, L-arginine/ADMA, L-arginine/L-ornithine and L-arginine availability index over 12 months were associated with increased exacerbations, OR 4.70 (95% CI 1.35 to 16.37), OR 8.69 (95% CI 1.98 to 38.08), OR 4.17 (95% CI 1.40 to 12.41) and OR 4.95 (95% CI 1.42 to 17.16), respectively. CONCLUSIONS: Our findings suggest that L-arginine metabolism is associated with multiple measures of asthma control and may explain, in part, the relationship between age, race/ethnicity and obesity with asthma outcomes.
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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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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".