The lung proteome in HIV-associated obstructive lung disease
Bibliographic record
Abstract
Rationale Obstructive lung disease is increasingly common among persons living with HIV (PLWH). There are currently no validated biomarkers that identify individuals at risk of developing obstructive lung disease (OLD), and specific mechanisms contributing to HIV-associated OLD remain elusive, independent of smoking. We sought to identify biomarkers and biological pathways associated with OLD using a broad proteomic approach. Methods We performed tandem mass tagging and mass spectrometry (MS) analysis on bronchoalveolar lavage fluid samples from persons living with HIV with OLD (n=26) and without OLD (n=26). We combined untargeted MS with a targeted SomaScan aptamer-based approach. We used Pearson correlation tests to identify associations between each protein and lung function (forced expiratory volume in 1 s (FEV 1 ) % pred). We adjusted for multiple comparisons using a false discovery rate adjustment. Significant proteins were entered into a pathway over-representation analysis. Protein-driven endotypes were constructed using K-means clustering. Measurements and main results We identified over 3800 proteins by MS and identified 254 proteins that correlated with FEV 1 % pred when we combined the MS and SomaScan proteomes when adjusting for smoking status. Pathway analysis revealed cell adhesion molecules as significant. Conclusions Protein expression differs in the lung of PLWH and decreased lung function (FEV 1 % pred). Pathway analysis reveals cell adhesion molecules having potentially important roles in this process.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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".