Clustering-based COPD subtypes have distinct longitudinal outcomes and multi-omics biomarkers
Year: 2022
Type: article
Abstract: Introduction Chronic obstructive pulmonary disease (COPD) can progress across several domains, complicating the identification of the determinants of disease progression. In our previous work, we applied k-means clustering to spirometric and chest radiologic measures to identify four COPD-related subtypes: “Relatively resistant smokers (RRS)”, “mild upper lobe predominant emphysema (ULE)”, “airway-predominant disease (AD)”, and “severe emphysema (SE)”. In the current study, we examined longitudinal spirometric and radiologic emphysema changes and prospective risks of COPD exacerbations, incident comorbidities, and mortality of these clusters. We also compared their associations to protein and transcriptomic biomarkers. Methods We included 8,266 non-Hispanic white and African-American smokers from the COPDGene study. We used linear regression to investigate associations to five-year prospective changes in spirometric and radiologic measures and to plasma protein and blood gene expression levels. We used Cox-proportional hazard modeling to test for associations to prospective exacerbations, comorbidities, and mortality. Results The RRS, ULE, AD, and SE clusters represented 39%, 15%, 26%, and 20% of the studied cohort at baseline, respectively. The SE cluster had the greatest 5-year FEV 1 and emphysema progression, and the highest risks of exacerbations, cardiovascular disease (CVD), and mortality. The AD cluster had the highest diabetes risk. After adjustments, only the ULE and AD clusters had elevated CVD mortality risks, while only the ULE cluster had the highest cancer-related mortality risk. These clusters also demonstrated differential protein and gene expression biomarker associations. Conclusion COPD k-means subtypes demonstrate varying rates of disease progression, prospective comorbidities, mortality, and associations to proteomic and transcriptomic biomarkers. Funding Sources This work was supported by NHLBI K08 HL141601, K08 HL146972, R01 HL116931, R01 HL124233, R01 HL126596, R01 HL116473, U01 HL089897, R01 HL147326, R01 HL130512, and U01 HL089856. The COPDGene study ( NCT00608764 ) is also supported by the COPD Foundation through contributions made to an Industry Advisory Committee comprised of AstraZeneca, Bayer, Boehringer-Ingelheim, Genentech, GlaxoSmithKline, Novartis, Pfizer, Siemens, and Sunovion.
Source: BMJ Open Respiratory Research
Language: English
Subfield: Pulmonary and Respiratory Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $2,085
Funders: Pfizer, AstraZeneca, GlaxoSmithKline, Brigham and Women's Hospital, University of Minnesota, Johns Hopkins University, University of Pittsburgh, COPD Foundation, Sunovion, Temple University, National Jewish Health, Morehouse School of Medicine, Genentech, University of California, San Diego, Anschutz Medical Campus, University of Colorado, National Heart, Lung, and Blood Institute
Awards: G1536959855, G2168838001, Prospective Health Outcomes and Inflammatory Biomarkers Associated with e-Cigarette Use, Multi-omic networks associated with COPD progression in TOPMed Cohorts, The clinical impact of longitudinal measures of cardiac and pulmonary vascular morphology in smokers, G5258357286, G5326023800, (2 of 2) Genetic Epidemiology of COPD, Using Integrative Genomics To Identify and Characterize Emphysema-Associated eQTL, (1 of 2) Genetic Epidemiology of COPD, SYSTEMS GENOMICS OF THE ASTHMA-COPD OVERLAP SYNDROME, The role of COPD genetic risk factor HHIP on lymphocytic inflammation, G8354759825, Clinical significance and genetic determinants of novel imaging measures of emphysema distribution in 9,743 smokers, Genetics of Smoke-Altered LTA4H in COPD, G8643874822, Airway Inspector: a chest imaging biomarker software platform for COPD, G8819318481
OpenAlex ID: W4292840775