ADEPT, airway disease endotyping for personalized treatment: Interim analysis of asthma patients
Bibliographic record
Abstract
Background ADEPT is a non-interventional study to characterize the clinical and molecular profiles of healthy, asthmatic, and COPD patients Methods Gene signatures of steroid up- and down- regulated genes were generated from in vitro stimulations of primary human airway cells from commercial sources. These steroid gene signatures were evaluated in the ADEPT asthma biopsies using GSEA to evaluate steroid responsiveness. Results The interim analysis included 15 healthy nonatopic subjects and 15, 13, and 11 mild, moderate, and severe asthmatics, respectively. The steroid down-regulated gene signature was enriched in moderate and severe but not mild asthma. The up-regulated signature was suppressed in mild asthma, and enriched in moderate but not severe asthma (Table 1). Asthma-related genes, including ALOX15, MUC5AC, and periostin, were each over-expressed in at least 2 asthma groups. Expression of B cell, T cell, mast cell genes was decreased in moderate and severe asthma. Steroid gene signature enrichment in asthma Signature Mild Moderate Severe Steroid, Down regulation 0.30 (-0.59) 0.015 (-0.76) <0.0001 (-0.93) Steroid, Up regulation 0.098 (-0.53) 0.0073 (0.78) 0.74 (-0.32) Nominal p-value (enrichment score), with healthy nonatopic control group as reference Conclusions Differential enrichment of the steroid gene signature was detected and corresponded to severity group. Confirmation of the unique findings in the severe asthma group awaits testing with the complete dataset. The unexpected findings in severe asthma may help elucidate mechanisms underlying steroid resistance.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".