Observational studyAnnals of the American Thoracic Society2026
Plasma proteomic profiles of lung volume-based phenotypes in tobacco-exposed individuals without spirometric chronic obstructive pulmonary disease.
Observational study in Annals of the American Thoracic Society, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT00608764 (Genetic Epidemiology of Chronic Obstructive Pulmonary Disease), which is not on this map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Genetic Epidemiology of Chronic Obstructive Pulmonary Disease (COPDGene)
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Abstract
backgroundAmong individuals with a history of smoking but preserved spirometry (tobacco exposed with preserved spirometry, or TEPS), lung volume-based stratification identifies 2 phenotypes at increased risk for chronic obstructive pulmonary disease (pre-COPD): those with a relatively elevated total lung capacity ([TLC]high) and those with a relatively elevated functional residual capacity-to-TLC ratio ([FRC/TLC]high). These subgroups exhibit distinct respiratory symptoms, radiographic abnormalities, and clinical trajectories.
objectiveThis study aimed to determine whether these lung volume-based pre-COPD phenotypes have distinct biological features reflected in their circulating proteomes.
methodsWe analyzed peripheral blood proteomic profiles (SomaScan v4.0; 4979 aptamers) from 1959 TEPS participants at the 5-year follow-up visit (visit 2) of the Genetic Epidemiology of COPD study cohort. Participants with [TLC]high and [FRC/TLC]high (based on computerized tomography scan-derived supine lung volumes) were compared with a low-COPD-risk reference group (without high TLC or high FRC/TLC). Analyses included covariate-adjusted regression, machine learning, and pathway enrichment modeling, with adjustment for age, sex, height, weight, smoking status and burden, leukocyte and platelet counts, forced expiratory volume in 1 second (percent predicted), and study site (random effect).
resultsUsing visit 2 data and visit 3 (10-year) follow-up outcomes, we confirmed the reproducibility and prognostic validity of the lung volume-based phenotypes in 1232 participants with longitudinal data. Over a mean (SD) of 5.3 (1.1) years, spirometric COPD developed in 17% (133 out of 761) of pre-COPD TEPS vs 8% (37 out of 471) of low-risk TEPS (adjusted odds ratio [aOR], 2.51; 95% confidence interval [CI], 1.69-3.75; P < .001). Among pre-COPD subgroups, [FRC/TLC]high TEPS showed greater progression to a Global Initiative for Chronic Obstructive Lung Disease stage 2 or higher (aOR, 2.90; 95% CI, 1.62-5.18; P < .001) and preserved ratio and impaired spirometry (aOR, 3.29; 95% CI, 1.41-7.69; P = .005). At baseline (n = 1959), plasma proteomic analysis identified 165 upregulated and 145 downregulated proteins in [TLC]high TEPS compared with low-COPD-risk TEPS, whereas only 22 proteins were differentially expressed in [FRC/TLC]high TEPS vs low-risk group. Comparison between the 2 pre-COPD phenotypes identified 269 differentially expressed proteins (116 upregulated and 153 downregulated in [FRC/TLC]high vs [TLC]high), including previously described COPD-related mediators (eg, soluble receptor for advanced glycation end products, insulin-like growth factor-binding protein) and novel candidates (eg, zymogen granule membrane protein 16). Pathway analysis highlighted immune signaling, cellular trafficking, and apoptotic pathways relevant to COPD pathogenesis.
conclusionsLung volume-based stratification in TEPS identifies biologically distinct subgroups with differing plasma proteomic signature and COPD risk, underscoring the heterogeneity of early disease and revealing potential circulating biomarkers of pre-COPD states. REGISTRATION: COPDGene study is registered with ClinicalTrials.gov: ID NCT00608764.Keywordspre-COPD, lung volumes, proteomics, biomarkers, chronic obstructive pulmonary disease.
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