Logo image
Back
D30-02 Exposure to Fine Particulate Matter (PM2.5) Is Associated With Ground-glass Opacity (GGO) Texture in COPDGene
Abstract   Peer reviewed

D30-02 Exposure to Fine Particulate Matter (PM2.5) Is Associated With Ground-glass Opacity (GGO) Texture in COPDGene

H Awan, S E Gerard, J Guo, E A Hoffman, A P Comellas, E A Regan, J L Crooks and J M Reinhardt
American journal of respiratory and critical care medicine, Vol.212(Supplement_1), aamag1622049
05/01/2026
DOI: 10.1093/ajrccm/aamag162.2049

View Online

Abstract

Rationale Air pollution is a major environmental risk factor for respiratory morbidity and mortality, with chronic exposure to outdoor pollutants implicated in the development and progression of chronic obstructive pulmonary disease (COPD). Fine particulate matter (PM2.5), the most impactful and widely studied pollutant in the U.S., penetrates deep into the lungs where it induces inflammation, oxidative stress, and structural injury. While PM2.5 has been linked to accelerated lung function decline, its relationship to quantitative CT (QCT) imaging biomarkers remains less defined. Ground-glass opacities (GGOs) capture subtle parenchymal abnormalities including alveolar collapse, interstitial thickening, and inflammatory changes. This feature may represent COPD-related injury and provide new insights into the impact of environmental exposures on lung structure. Methods We examined the association between baseline PM2.5 exposure, calculated as the individual mean exposure during the year preceding study enrollment, and CT-derived GGO texture in participants from COPDGene (n = 1,470), a large multicenter, COPD-enriched cohort. PM2.5 exposure is estimated based on geocoded residential addresses, providing individualized exposure assessment. GGOs were quantified using the adaptive multiple feature method (AMFM), a validated approach for characterizing CT texture patterns. Univariate and multivariable linear regression models were used to evaluate the relationship between air pollution and GGO texture. Multivariable models were adjusted for demographic and clinical covariates, including age, sex, race, body mass index, smoking history, lung function, lung volume, and CT-measured emphysema. Stratified analyses were conducted to identify potentially susceptible subgroups based on sex and airway-to-lung ratio, with models adjusted for the same covariates described above. Results Higher PM2.5 exposure was significantly associated with increased GGO texture (β = 0.009, 95% CI: 0.001, 0.018, P = 0.03) after adjustment for all the covariates, suggesting that chronic particulate exposure contributes to early structural lung alterations (Figure). Stratified analyses indicated relatively stronger associations in females (β = 0.010, 95% CI: -0.000, 0.021, P = 0.06) than in males (β = 0.009, 95% CI: -0.004, 0.023, P = 0.18), and the strongest effect among participants in the lowest airway-to-lung ratio quartile (β = 0.019, 95% CI: 0.001, 0.037, P = 0.04). These findings suggest potential sex-based and structural modifiers of susceptibility to pollution-related lung injury. Conclusion Exposure to fine particulate matter (PM2.5) is associated with subtle increases in CT-derived GGO texture. CT-based imaging biomarkers can enhance our understanding of how air pollution contributes to COPD pathogenesis and help identify high-risk subgroups for targeted prevention. This abstract is funded by: NIH and The Roy J Carver Charitable Trust
 Air Pollution Biomarkers Chronic obstructive pulmonary disease

Details

Metrics

1 Record Views
Logo image