Identifying a gene expression signature of frequent COPD exacerbations in peripheral blood using network methods

BMC Med Genomics. 2015 Jan 13:8:1. doi: 10.1186/s12920-014-0072-y.

Abstract

Background: Exacerbations of chronic obstructive pulmonary disease (COPD), characterized by acute deterioration in symptoms, may be due to bacterial or viral infections, environmental exposures, or unknown factors. Exacerbation frequency may be a stable trait in COPD patients, which could imply genetic susceptibility. Observing the genes, networks, and pathways that are up- and down-regulated in COPD patients with differing susceptibility to exacerbations will help to elucidate the molecular signature and pathogenesis of COPD exacerbations.

Methods: Gene expression array and plasma biomarker data were obtained using whole-blood samples from subjects enrolled in the Treatment of Emphysema With a Gamma-Selective Retinoid Agonist (TESRA) study. Linear regression, weighted gene co-expression network analysis (WGCNA), and pathway analysis were used to identify signatures and network sub-modules associated with the number of exacerbations within the previous year; other COPD-related phenotypes were also investigated.

Results: Individual genes were not found to be significantly associated with the number of exacerbations. However using network methods, a statistically significant gene module was identified, along with other modules showing moderate association. A diverse signature was observed across these modules using pathway analysis, marked by differences in B cell and NK cell activity, as well as cellular markers of viral infection. Within two modules, gene set enrichment analysis recapitulated the molecular signatures of two gene expression experiments; one involving sputum from asthma exacerbations and another involving viral lung infections. The plasma biomarker myeloperoxidase (MPO) was associated with the number of recent exacerbations.

Conclusion: A distinct signature of COPD exacerbations may be observed in peripheral blood months following the acute illness. While not predictive in this cross-sectional analysis, these results will be useful in uncovering the molecular pathogenesis of COPD exacerbations.

Publication types

  • Randomized Controlled Trial
  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Algorithms
  • Biomarkers / blood
  • Computational Biology / methods*
  • Cross-Sectional Studies
  • Emphysema / blood
  • Female
  • Gene Expression Profiling*
  • Genetic Predisposition to Disease*
  • Humans
  • Linear Models
  • Male
  • Middle Aged
  • Phenotype
  • Pulmonary Disease, Chronic Obstructive / blood
  • Pulmonary Disease, Chronic Obstructive / genetics*
  • Sequence Analysis, RNA
  • Severity of Illness Index
  • Transcriptome

Substances

  • Biomarkers