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Published ahead of print on September 16, 2004, doi:10.1165/rcmb.2004-0273OC

Am. J. Respir. Cell Mol. Biol., Volume 31, Number 6, December 2004, 601-610

A more recent version of this article appeared on December 1, 2004
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Submitted on August 26, 2004
Revised on September 15, 2004

Gene Expression Profiling of Human Lung Tissue from Smokers with Severe Emphysema

Avrum E Spira1*, Jennifer Beane2, Victor Pinto-Plata3, Aran Kadar4, Gang Liu4, Vishal Shah2, Bartolome Celli3, and Jerome S Brody4

1 The Pulmonary Center and Department of Medicine, Boston University School of Medicine, Boston, MA, USA; Bioinformatics Program, Boston University, Boston, MA, USA, 2 Bioinformatics Program, Boston University, Boston, MA, USA, 3 COPD Center at St. Elizabeth's Medical Center, Tufts University School of Medicine, Boston, MA, USA, 4 The Pulmonary Center and Department of Medicine, Boston University School of Medicine, Boston, MA, USA

* To whom correspondence should be addressed. E-mail: aspira{at}bu.edu.

The mechanism by which inhaled smoke causes the anatomic lesions and physiologic impairment of chronic obstructive pulmonary disease (COPD) remains unknown. We used high-density microarrays to measure gene expression in severely emphysematous lung tissue removed from smokers at lung volume reduction surgery (LVRS) and normal or mildly emphysematous lung tissue from smokers undergoing resection of pulmonary nodules. Class prediction algorithms identified 102 genes that accurately distinguished severe emphysema from non/mild emphysematous lung tissue. We also defined a number of genes whose expression levels correlated tightly with diffusion capacity (DLCO) and/or forced expiratory volume (FEV1). Genes related to oxidative stress, extracellular matrix synthesis, and inflammation were increased in severe emphysema, while expression of endothelium-related genes was decreased. To identify candidate genes that might be causally involved in the pathogenesis of emphysema, we linked gene expression profiles to chromosomal regions previously associated with COPD in genome-wide linkage analyses. Unsupervised hierarchical clustering of the LVRS samples revealed distinct molecular subclasses of severe emphysema, with body mass index as the only clinical variable that differed between the groups. Class prediction models established a set of genes that predicted functional outcome at 6 months post-LVRS. Our findings suggest the gene expression profiles from human emphysematous lung tissue may provide insight into pathogenesis, uncover novel molecular subclasses of disease, predict response to LVRS, and may identify targets for therapeutic intervention.




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