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Identifying targets for COPD treatment through gene expression analyses.

ABSTRACT: Despite the status of chronic obstructive pulmonary disease (COPD) as a major global health problem, no currently available therapies can limit COPD progression. Therefore, an urgent need exists for the development of new and effective treatments for COPD. An improved understanding in the molecular pathogenesis of COPD can potentially identify molecular targets to facilitate the development of new therapeutic modalities. Among the best approaches for understanding the molecular basis of COPD include gene expression profiling techniques, such as serial analysis of gene expression or microarrays. Using these methods, recent studies have mapped comparative gene expression profiles of lung tissues from patients with different stages of COPD relative to healthy smokers or non-smokers. Such studies have revealed a number of differentially-regulated genes associated with COPD progression, which include genes involved in the regulation of inflammation, extracellular matrix, cytokines, chemokines, apoptosis, and stress responses. These studies have shed new light on the molecular mechanisms of COPD, and suggest novel targets for clinical treatments.

SUBMITTER: Chen ZH

PROVIDER: S-EPMC2629979 | biostudies-literature | 2008

REPOSITORIES: biostudies-literature

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Identifying targets for COPD treatment through gene expression analyses.

Chen Zhi-Hua ZH Kim Hong Pyo HP Ryter Stefan W SW Choi Augustine M K AM

International journal of chronic obstructive pulmonary disease 20080101 3

Despite the status of chronic obstructive pulmonary disease (COPD) as a major global health problem, no currently available therapies can limit COPD progression. Therefore, an urgent need exists for the development of new and effective treatments for COPD. An improved understanding in the molecular pathogenesis of COPD can potentially identify molecular targets to facilitate the development of new therapeutic modalities. Among the best approaches for understanding the molecular basis of COPD inc ...[more]

PMID: 18990963

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Project description:Hyperinflation contributes to dyspnea intensity in COPD. Little is known about the molecular mechanisms underlying hyperinflation and how inhaled corticosteroids (ICS) affect this important aspect of COPD pathophysiology. To investigate the effect of ICS/long-acting β2-agonist (LABA) treatment on both lung function measures of hyperinflation, and the nasal epithelial gene-expression profile in severe COPD. 117 patients were screened and 60 COPD patients entered a 1-month run-in period on low-dose ICS/LABA budesonide/formoterol (BUD/F) 200/6 one inhalation b.i.d. Patients were then randomly assigned to 3-month treatment with either a high dose BDP/F 100/6 two inhalations b.i.d. (n = 31) or BUD/F 200/6 two inhalations b.i.d. (n = 29). Lung function measurements and nasal epithelial gene-expression were assessed before and after 3-month treatment and validated in independent datasets. After 3-month ICS/LABA treatment, residual volume (RV)/total lung capacity (TLC)% predicted was reduced compared to baseline (p < 0.05). We identified a nasal gene-expression signature at screening that associated with higher RV/TLC% predicted values. This signature, decreased by ICS/LABA treatment was enriched for genes associated with increased p53 mediated apoptosis was replicated in bronchial biopsies of COPD patients. Finally, this signature was increased in COPD patients compared to controls in nasal, bronchial and small airways brushings. Short-term ICS/LABA treatment improves RV/TLC% predicted in severe COPD. Furthermore, it decreases the expression of genes involved in the signal transduction by the p53 class mediator, which is a replicable COPD gene expression signature in the upper and lower airways.Trial registration: ClinicalTrials.gov registration number NCT01351792 (registration date May 11, 2011), ClinicalTrials.gov registration number NCT00848406 (registration date February 20, 2009), ClinicalTrials.gov registration number NCT00158847 (registration date September 12, 2005).

Project description: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.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.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.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.

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Identifying targets for COPD treatment through gene expression analyses.

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Identifying targets for COPD treatment through gene expression analyses.

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