Clustering-based COPD subtypes have distinct longitudinal outcomes and multi-omics biomarkers

Andrew Gregory, Zhonghui Xu, Katherine Pratte, Sool Lee, Congjian Liu, Robert Chase, Jeong Yun, Aabida Saferali, Craig P Hersh, Russell Bowler, Edwin Silverman, Peter J Castaldi, Adel Boueiz, Andrew Gregory, Zhonghui Xu, Katherine Pratte, Sool Lee, Congjian Liu, Robert Chase, Jeong Yun, Aabida Saferali, Craig P Hersh, Russell Bowler, Edwin Silverman, Peter J Castaldi, Adel Boueiz

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 radiological 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 the associations of these subtypes to longitudinal COPD-related health measures as well as blood transcriptomic and plasma proteomic biomarkers.

Methods: We included 8266 non-Hispanic white and African-American smokers from the COPDGene study. We used linear regression to investigate cluster associations to 5-year prospective changes in spirometric and radiological measures and to gene expression and protein levels. We used Cox-proportional hazard test to test for cluster 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 FEV1 (forced expiratory volume in 1 s) and emphysema progression, and the highest risks of exacerbations, cardiovascular disease and mortality. The AD cluster had the highest diabetes risk. After adjustments, only the SE cluster had an elevated respiratory mortality risk, while the ULE, AD and SE clusters had elevated all-cause mortality risks. These clusters also demonstrated differential protein and gene expression biomarker associations, mostly related to inflammatory and immune processes.

Conclusion: COPD k-means subtypes demonstrate varying rates of disease progression, prospective comorbidities, mortality and associations to transcriptomic and proteomic biomarkers. These findings emphasise the clinical and biological relevance of these subtypes, which call for more study for translation into clinical practice.

Trail registration number: NCT00608764.

Keywords: COPD Exacerbations; COPD epidemiology; Emphysema; Imaging/CT MRI etc.

Conflict of interest statement

Competing interests: None declared.

© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

Figures

Figure 1
Figure 1
Study design. The goal of the study was to analyse chronic obstructive pulmonary disease (COPD) progression, differential blood gene expression, differential plasma protein associations and gene ontology enrichment characteristics of the four clusters that we identified in our previous k-means clustering analysis in the COPDGene study (Castaldi et al, Thorax 2014).
Figure 2
Figure 2
Disease progression by k-means cluster. (A) Absolute change in FEV1 (mL/year). (B) Relative change in FEV1 (change as % of baseline value/year). (C) Absolute change in emphysema measured as adjusted Perc15 density change/year. (D) Relative change in emphysema measured as adjusted Perc15 density change (% of baseline value/year). P- values <0.05 are indicated by an asterisk. AD, airway-predominant disease; FEV1, forced expiratory volume in 1 s; Perc15, 15th percentile; RRS, relatively resistant smokers; SE, severe emphysema; ULE, upper lobe-predominant emphysema.
Figure 3
Figure 3
Kaplan-Meier plots of COPD-related events by k-means cluster. (A) COPD exacerbation, defined as the acute worsening of respiratory symptoms that required antibiotics and/or systemic steroids. (B) Cardiovascular disease (CVD) event, defined as a composite endpoint of stroke, heart attack, coronary artery disease, coronary artery bypass graft surgery, peripheral artery disease and/or cardiac angina. (C) Diabetes. (D) All-cause mortality. For CVD events and diabetes, subjects who had a history of CVD or diabetes at Visit 1 were excluded from the analysis. AD, airway-predominant disease; COPD, chronic obstructive pulmonary disease; RRS, relatively resistant smokers; SE, severe emphysema; ULE, upper lobe-predominant emphysema.
Figure 4
Figure 4
Bland-Altman (MA) plots of the log ratio versus mean gene expression for the differential expression analysis results between k-means clusters. The cluster following the ‘versus’ is the reference group. (A) ULE versus RRS. (B) AD versus RRS. (C) SE versus RRS. (D) AD versus ULE. (E) SE versus ULE. (F) SE versus AD. AD, airway-predominant disease; RRS, relatively resistant smokers; SE, severe emphysema; ULE, upper lobe-predominant emphysema.

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