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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.
- COPD epidemiology
Data availability statement
Data may be obtained from a third party and are not publicly available. COPDGene Study data are available on the NCBI database of Genotypes and Phenotypes (accessions phs000179 and phs000765).
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Data availability statement
Data may be obtained from a third party and are not publicly available. COPDGene Study data are available on the NCBI database of Genotypes and Phenotypes (accessions phs000179 and phs000765).
Footnotes
Twitter @ajghosh, @MattMollpulmccm, @craig_hersh
Contributors Concept and design: AJG and CPH; data collection: PJC and CPH; data analysis: AJG, AS, MM, JM, JY, PJC and CPH; statistical support: AJG, AS, SL, RC, MM, JM, JY and CPH; manuscript writing/editing: AJG, AS, SL, RC, MM, JM, JY, PJC and CPH.
Funding Supported by National Institutes of Health grants (R01HL130512, R01HL125583, U01HL089856, U01HL089897, R01HL124233, R01HL147326 and T32HL007427). COPDGene is also supported by the COPD Foundation through contributions made to an Industry Advisory Board comprised of AstraZeneca, Boehringer-Ingelheim, Genentech, GlaxoSmithKline, Novartis, Pfizer, Siemens and Sunovion. PJC reports grants from GSK, personal fees from GSK and personal fees from Novartis, outside the submitted work. CPH reports grants from NHLBI, during the conduct of the study; grants from Bayer, Boehringer-Ingelheim, Novartis and Vertex, outside the submitted work.
Competing interests Dr Castaldi reports grants from GSK, personal fees from GSK, personal fees from Novartis, outside the submitted work. Dr Hersh reports grants from NHLBI, during the conduct of the study; grants from Bayer, grants from Boehringer-Ingelheim, grants from Novartis, grants from Vertex, outside the submitted work.
Provenance and peer review Not commissioned; externally peer reviewed.