Blood RNA sequencing shows overlapping gene expression across COPD phenotype domains. Issue 2 (24th June 2021)

• Record Type: Journal Article
• Authors: Ghosh, Auyon J; Saferali, Aabida; Lee, Sool; Chase, Robert; Moll, Matthew; Morrow, Jarrett; Yun, Jeong; Castaldi, Peter J; Hersh, Craig P
• Is Part Of: Thorax. Volume 77:Issue 2(2022)
• Page Start: 115
• Page End: 122
• Publication Date: 2021-06-24
• Subjects: COPD epidemiology; Chest -- Diseases -- Periodicals; Thorax; Chest -- Diseases; Periodicals; Periodicals; 617.54
• DOI: 10.1136/thoraxjnl-2020-216401
• Languages: English
• ISSNs: 0040-6376

Abstract

Abstract : Rationale: COPD can be assessed using multidimensional grading systems with components from three domains: pulmonary function tests, symptoms and systemic features. Clinically, measures may be used interchangeably, though it is not known if they share similar pathobiology. Objective: To use RNA sequencing (RNA-seq) to determine if there is an overlap in the underlying biological mechanisms and consequences driving different components of the multidimensional grading systems. Methods: Whole blood was collected for RNA-seq from current and former smokers in the Genetic Epidemiology of COPD study. We tested the overlap in gene expression and biological pathways associated with case–control status and quantitative COPD phenotypes within and between the three domains. Results: In 2647 subjects, there were 3030 genes differentially expressed in any of the three domains or case–control status. There were five genes that overlapped between the three domains and case–control status, including G protein-coupled receptor 15 ( GPR15 ), sestrin 1 ( SESN1 ) and interferon-induced guanylate-binding protein 1 ( GBP1 ), which were associated with longitudinal decline in FEV1 . The overlap between the three domains was enriched for pathways related to cellular components. Conclusions: We identified gene sets and pathways that overlap between 12 COPD-related phenotypes and case–control status. There were no pathways represented in the overlap between the three domains and case–control status, but we identified multiple genes that demonstrated a consistent pattern of expression across several of the phenotypes. Patterns of gene expression correlation were generally similar to the correlation of clinical phenotypes in the PFT and symptom domains but not the systemic features.