Airway Aging and Methylation Disruptions in HIV-associated Chronic Obstructive Pulmonary Disease
Bibliographic record
Abstract
Abstract Rationale Age-related diseases like chronic obstructive pulmonary disease (COPD) occur at higher rates in people living with human immunodeficiency virus (PLWH) than in uninfected populations. Objectives To identify whether accelerated aging can be observed in the airways of PLWH with COPD, manifest by a unique DNA methylation signature. Methods Bronchial epithelial brushings from PLWH with and without COPD and HIV-uninfected adults with and without COPD (N = 76) were profiled for DNA methylation and gene expression. We evaluated global Alu and LINE-1 methylation and calculated the epigenetic age using the Horvath clock and the methylation telomere length estimator. To identify genome-wide differential DNA methylation and gene expression associated with HIV and COPD, robust linear models were used followed by an expression quantitative trait methylation (eQTM) analysis. Measurements and Main Results Epigenetic age acceleration and shorter methylation estimates of telomere length were found in PLWH with COPD compared with PLWH without COPD and uninfected patients with and without COPD. Global hypomethylation was identified in PLWH. We identified 7,970 cytosine bases located next to a guanine base (CpG sites), 293 genes, and 9 expression quantitative trait methylation–gene pairs associated with the interaction between HIV and COPD. Actin binding LIM protein family member 3 (ABLIM3) was one of the novel candidate genes for HIV-associated COPD highlighted by our analysis. Conclusions Methylation age acceleration is observed in the airway epithelium of PLWH with COPD, a process that may be responsible for the heightened risk of COPD in this population. Their distinct methylation profile, differing from that observed in patients with COPD alone, suggests a unique pathogenesis to HIV-associated COPD. The associations warrant further investigation to establish causality.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| 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) | 0.001 | 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".