Title
Peripheral blood gene expression profiles in COPD subjects.
Abstract
To identify non-invasive gene expression markers for chronic obstructive pulmonary disease (COPD), we performed genome-wide expression profiling of peripheral blood samples from 12 subjects with significant airflow obstruction and an equal number of non-obstructed controls. RNA was isolated from Peripheral Blood Mononuclear Cells (PBMCs) and gene expression was assessed using Affymetrix U133 Plus 2.0 arrays.Tests for gene expression changes that discriminate between COPD cases (FEV1< 70% predicted, FEV1/FVC < 0.7) and controls (FEV1> 80% predicted, FEV1/FVC > 0.7) were performed using Significance Analysis of Microarrays (SAM) and Bayesian Analysis of Differential Gene Expression (BADGE). Using either test at high stringency (SAM median FDR = 0 or BADGE p < 0.01) we identified differential expression for 45 known genes. Correlation of gene expression with lung function measurements (FEV1 & FEV1/FVC), using both Pearson and Spearman correlation coefficients (p < 0.05), identified a set of 86 genes. A total of 16 markers showed evidence of significant correlation (p < 0.05) with quantitative traits and differential expression between cases and controls. We further compared our peripheral gene expression markers with those we previously identified from lung tissue of the same cohort. Two genes, RP9and NAPE-PLD, were identified as decreased in COPD cases compared to controls in both lung tissue and blood. These results contribute to our understanding of gene expression changes in the peripheral blood of patients with COPD and may provide insight into potential mechanisms involved in the disease.
Year
DOI
Venue
2011
10.1186/2043-9113-1-12
J. Clinical Bioinformatics
Keywords
Field
DocType
pbmc,microarray biomarkers,bayesian analysis,quantitative trait,bioinformatics,gene expression,health informatics,peripheral blood mononuclear cell
COPD,RNA,Peripheral,Microarray,Immunology,Gene expression,Biomarker (medicine),Peripheral blood mononuclear cell,Bioinformatics,Medicine,Gene expression profiling,Pathology
Journal
Volume
Issue
ISSN
1
1
2043-9113
Citations 
PageRank 
References 
0
0.34
0
Authors
9