The relationship between the epigenetic aging biomarker “grimage” and lung function in both the airway and blood of people living with HIV: An observational cohort study
Bibliographic record
Abstract
Background Age-related comorbidities such as chronic obstructive pulmonary disease (COPD) are common in people living with human immunodeficiency virus (PLWH). We investigated the relationship between COPD and the epigenetic age of the airway epithelium and peripheral blood of PLWH. Methods Airway epithelial brushings from 34 PLWH enrolled in the St. Paul's Hospital HIV Bronchoscopy cohort and peripheral blood from 378 PLWH enrolled in The Strategic Timing of Antiretroviral Treatment (START) study were profiled for DNA methylation. The DNA methylation biomarker of age and healthspan, GrimAge, was calculated in both tissue compartments. We tested the association of GrimAge with COPD in the airway epithelium and airflow obstruction as defined by an FEV 1 /FVC<0.70, and FEV 1 decline over 6 years in blood. Findings The airway epithelium of PLWH with COPD was associated with greater GrimAge residuals compared to PLWH without COPD (Beta=3.18, 95%CI=1.06-5.31, P =0.005). In blood, FEV 1 /FVC P =0.019). FEV 1 decline was inversely correlated with GrimAge residuals in blood (r=−0.13, P =0.012). PLWH who had normal lung function but who subsequently developed an FEV 1 /FVC<0.70 over the course of 6 years had higher GrimAge residuals at baseline (Beta=2.33, 95%CI=0.23-4.44, P =0.031). Interpretation GrimAge may reflect lung and systemic epigenetic changes that occur with advanced airflow obstruction and may help to identify PLWH with a higher risk of developing COPD. Funding Canadian Institutes of Health Research and the British Columbia Lung Association. The START substudy was funded by NIH grants: UM1-AI068641, UM1-AI120197, and RO1HL096453.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".