Published ahead of print on February 23, 2006, doi:10.1165/rcmb.2004-0261OC
© 2006 American Thoracic Society DOI: 10.1165/rcmb.2004-0261OC Human Lung Project: Evaluating Variance of Gene Expression in the Human LungDivision of Pulmonary Sciences and Critical Care Medicine and Section of Biometrics and Informatics, University of Colorado Health Sciences Center; and National Jewish Medical and Research Center, Denver, Colorado Correspondence and requests for reprints should be addressed to Mark W. Geraci, M.D., University of Colorado Health Sciences Center, Division of Pulmonary Sciences and Critical Care Medicine, 4200 East Ninth Ave, C-272, Denver, CO 80262. E-mail: mark.geraci{at}uchsc.edu Nondiseased tissue is an important reference for microarray studies of pulmonary disease. We obtained 23 single lungs from multiorgan donors at time of procurement. Donors varied in age, sex, smoking history, and ethnicity. Lungs were dissected into upper and lower lobe peripheral sections for RNA extraction. Microarray analysis was performed using Affymetrix Hu-133 Plus 2.0 arrays. We observed that the relative variability of gene expression increased rapidly from technical (lowest), to regional, to population (highest). In addition, age and sex have measurable effects on gene expression. Gene expression variability is heterogeneously distributed among biologic categories. We conclude that gene expression variability is greater between individuals than within individuals and that population variability is the most important factor in the study design of microarray experiments of the human lung. Classes of genes with high population variability are biologically important and provide a novel perspective into lung physiology and pathobiology. Our study represents the first comprehensive analysis of nondiseased lung tissue. The generation of this robust dataset has important implications for the design and implementation of future comparative expression analysis with pulmonary disease states.
Key Words: Keywords: lung • microarray • genomics • variability This article has been cited by other articles:
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