Bronchial gene expression signature associated with rate of subsequent FEV<sub>1</sub> decline in individuals with and at risk of COPD
Bibliographic record
Abstract
Background COPD is characterised by progressive lung function decline. Leveraging prior work demonstrating bronchial airway COPD-associated gene expression alterations, we sought to determine if there are alterations associated with differences in the rate of FEV 1 decline. Methods We examined gene expression among ever smokers with and without COPD who at baseline had bronchial brushings profiled by Affymetrix microarrays and had longitudinal lung function measurements (n=134; mean follow-up=6.38±2.48 years). Gene expression profiles associated with the rate of FEV 1 decline were identified by linear modelling. Results Expression differences in 171 genes were associated with rate of FEV 1 decline (false discovery rate <0.05). The FEV 1 decline signature was replicated in an independent dataset of bronchial biopsies from patients with COPD (n=46; p=0.018; mean follow-up=6.76±1.32 years). Genes elevated in individuals with more rapid FEV 1 decline are significantly enriched among the genes altered by modulation of XBP1 in two independent datasets (Gene Set Enrichment Analysis (GSEA) p<0.05) and are enriched in mucin-related genes (GSEA p<0.05). Conclusion We have identified and replicated an airway gene expression signature associated with the rate of FEV 1 decline. Aspects of this signature are related to increased expression of XBP1-regulated genes, a transcription factor involved in the unfolded protein response, and genes related to mucin production. Collectively, these data suggest that molecular processes related to the rate of FEV 1 decline can be detected in airway epithelium, identify a possible indicator of FEV 1 decline and make it possible to detect, in an early phase, ever smokers with and without COPD most at risk of rapid FEV 1 decline.
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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 | 0.000 | 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 | 0.000 |
| 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".