Molecular determinants of lung function decline: a multi-level analysis of gene expression
Bibliographic record
Abstract
BACKGROUND: Chronic obstructive pulmonary disease (COPD) is characterized by progressive lung function decline, commonly measured by forced expiratory volume in one second (FEV1). Uncovering the genetic basis of FEV1 decline is essential for understanding COPD pathophysiology and for developing therapies. We hypothesized that gene expression patterns in inflammatory pathways are associated with FEV1 decline. METHODS: We analyzed whole blood RNA-sequencing data from the 5 (n = 4,147) and 10 year visits (n = 435) in the COPDGene Study. Gene expression was assessed in three analyses: cross-sectional associations with FEV1 at two separate time points, association between year 5 gene expression and FEV1 changes from year 5–10, and longitudinal changes in both gene expression and FEV1. A gene signature derived from the 5-year visit was linked to FEV1 decline across three intervals (baseline to 5 years, 5 to 10 years, and baseline to 10 years) and tested for validation in the ECLIPSE study. RESULTS: Distinct gene sets emerged in the three analyses (Cross-sectional: 961 genes; FEV1 Change: 179; Longitudinal: 532). Only two genes (NOV and AC009404.2) overlapped across all analyses, while unique genes (e.g., MMP9, IL1RL1, and CHI3L1) were context-specific. Pathway analysis of genes from the longitudinal analysis highlighted oxidative stress and immune processes. A 20-gene signature was derived, including 17 genes positively and three negatively associated with FEV1. These signatures were significantly associated with FEV1-related traits in COPDGene and ECLIPSE. CONCLUSIONS: These findings reveal molecular markers of FEV1 decline, offering insights into COPD pathophysiology and potential therapeutic targets.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| 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".