Whole blood and leukocyte RNA isolation for gene expression analyses

1 Department of Surgery, University of Florida College of Medicine, Gainesville, Florida 2 Department of Molecular Genetics and Microbiology, University of Florida College of Medicine, Gainesville, Florida 3 Stanford Genome Technology Center, Palo Alto, California 4 Department of Surgery, Shriners B...

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Published in:Physiological genomics 2004-11, Vol.19 (3), p.247-254
Main Authors: Feezor, Robert J, Baker, Henry V, Mindrinos, Michael, Hayden, Doug, Tannahill, Cynthia L, Brownstein, Bernard H, Fay, Adrian, MacMillan, Sandra, Laramie, Jason, Xiao, Wenzhong, Moldawer, Lyle L, Cobb, J. Perren, Laudanski, Krzysztof, Miller-Graziano, Carol L, Maier, Ronald V, Schoenfeld, David, Davis, Ronald W, Tompkins, Ronald G, Inflammation and Host Response to Injury, Large-Scale Collaborative Research Program
Format: Article
Language:English
Subjects:
Adolescent
Adult
Aged
Antigens, Bacterial - metabolism
Blood Specimen Collection - standards
Cluster Analysis
Enterotoxins - metabolism
Female
Gene Expression Profiling - methods
Gene Expression Profiling - standards
Gene Expression Profiling - statistics & numerical data
Humans
Leukocytes - chemistry
Male
Middle Aged
Oligonucleotide Array Sequence Analysis - methods
Oligonucleotide Array Sequence Analysis - standards
Oligonucleotide Array Sequence Analysis - statistics & numerical data
Reproducibility of Results
Research Design - standards
RNA - blood
RNA - genetics
Specimen Handling - standards
Staphylococcus
Wounds and Injuries - blood
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Summary:1 Department of Surgery, University of Florida College of Medicine, Gainesville, Florida 2 Department of Molecular Genetics and Microbiology, University of Florida College of Medicine, Gainesville, Florida 3 Stanford Genome Technology Center, Palo Alto, California 4 Department of Surgery, Shriners Burn Center and Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts 5 Department of Surgery, Washington University in St. Louis, School of Medicine, St. Louis, Missouri 6 Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 7 Department of Surgery, University of Rochester, School of Medicine and Dentistry, Rochester, New York 8 Department of Surgery, Harborview Medical Center, University of Washington, Seattle, Washington The analysis of gene expression data in clinical medicine has been plagued by the lack of a critical evaluation of accepted methodologies for the collection, processing, and labeling of RNA. In the present report, the reliability of two commonly used techniques to isolate RNA from whole blood or its leukocyte compartment was compared by examining their reproducibility, variance, and signal-to-noise ratios. Whole blood was obtained from healthy subjects and was either untreated or stimulated ex vivo with Staphylococcus enterotoxin B (SEB). Blood samples were also obtained from trauma patients but were not stimulated with SEB ex vivo. Total RNA was isolated from whole blood with the PAXgene proprietary blood collection system or from isolated leukocytes. Biotin-labeled cRNA was hybridized to Affymetrix GeneChips. The Pearson correlation coefficient for gene expression measurements in replicates from healthy subjects with both techniques was excellent, exceeding 0.985. Unsupervised analyses, including hierarchical cluster analysis, however, revealed that the RNA isolation method resulted in greater differences in gene expression than stimulation with SEB or among different trauma patients. The intraclass correlation, a measure of signal-to-noise ratio, of the difference between SEB-stimulated and unstimulated blood from healthy subjects was significantly higher in leukocyte-derived samples than in whole blood: 0.75 vs. 0.46 ( P = 0.002). At the P < 0.001 level of significance, twice as many probe sets discriminated between SEB-stimulated and unstimulated blood with leukocyte isolation than with PAXgene. The findings suggest that the method of RNA isolation from whole blood is
ISSN:1094-8341
1531-2267
DOI:10.1152/physiolgenomics.00020.2004