Characterisation of asthma subgroups associated with circulating YKL-40 levels
Bibliographic record
Abstract
The chitinase-like protein YKL-40 mediates airway inflammation and serum levels are associated with asthma severity. However, asthma phenotypes associated with YKL-40 levels have not been precisely defined.We conducted an unsupervised cluster analysis of asthma patients treated at the Yale Center for Asthma and Airways Disease (n=156) to identify subgroups according to YKL-40 level. The resulting YKL-40 clusters were cross-validated in cohorts from the Severe Asthma Research Programme (n=167) and the New York University/Bellevue Asthma Repository (n=341). A sputum transcriptome analysis revealed molecular pathways associated with YKL-40 subgroups.Four YKL-40 clusters (C1-C4) were identified. C3 and C4 had high serum YKL-40 levels compared with C1 and C2. C3 was associated with earlier onset and longer duration of disease, severe airflow obstruction, and near-fatal asthma exacerbations. C4 had the highest serum YKL-40 levels, adult onset and less airflow obstruction, but frequent exacerbations. An airway transcriptome analysis in C3 and C4 showed activation of non-type 2 inflammatory pathways.Elevated serum YKL-40 levels were associated with two distinct clinical asthma phenotypes: one with irreversible airway obstruction and another with severe exacerbations. The YKL-40 clusters are potentially useful for identification of individuals with severe or exacerbation-prone asthma.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".