Host Response to the Lung Microbiome in Chronic Obstructive Pulmonary Disease
Bibliographic record
Abstract
RATIONALE: The relatively sparse but diverse microbiome in human lungs may become less diverse in chronic obstructive pulmonary disease (COPD). This article examines the relationship of this microbiome to emphysematous tissue destruction, number of terminal bronchioles, infiltrating inflammatory cells, and host gene expression. METHODS: Culture-independent pyrosequencing microbiome analysis was used to examine the V3-V5 regions of bacterial 16S ribosomal DNA in 40 samples of lung from 5 patients with COPD (Global Initiative for Chronic Obstructive Lung Disease [GOLD] stage 4) and 28 samples from 4 donors (controls). A second protocol based on the V1-V3 regions was used to verify the bacterial microbiome results. Within lung tissue samples the microbiome was compared with results of micro-computed tomography, infiltrating inflammatory cells measured by quantitative histology, and host gene expression. MEASUREMENTS AND MAIN RESULTS: Ten operational taxonomic units (OTUs) was found sufficient to discriminate between control and GOLD stage 4 lung tissue, which included known pathogens such as Haemophilus influenzae. We also observed a decline in microbial diversity that was associated with emphysematous destruction, remodeling of the bronchiolar and alveolar tissue, and the infiltration of the tissue by CD4(+) T cells. Specific OTUs were also associated with neutrophils, eosinophils, and B-cell infiltration (P < 0.05). The expression profiles of 859 genes and 235 genes were associated with either enrichment or reductions of Firmicutes and Proteobacteria, respectively, at a false discovery rate cutoff of less than 0.1. CONCLUSIONS: These results support the hypothesis that there is a host immune response to microorganisms within the lung microbiome that appears to contribute to the pathogenesis of COPD.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".