Open AccessProfiling of genes expressed in peripheral blood mononuclear cells predicts glucocorticoid sensitivity in asthma patients
Author(s) -
Hákon Hákonarson,
Unnur Steina Björnsdóttir,
Eva Halapi,
Jonathan P. Bradfield,
Florian Zink,
Magali Mouy,
Hildur Helgadóttir,
Asta Solilja Gudmundsdottir,
Hjalti Andrason,
Asdis E. Adalsteinsdottir,
Kristleifur Kristjánsson,
Illugi Birkisson,
T. J. Arnason,
Margrét B. Andrésdóttir,
Davíð Gíslason,
Þórarinn Gíslason,
Jeffrey R. Gulcher,
Kāri Stefánsson
Publication year - 2005
Publication title -
proceedings of the national academy of sciences of the united states of america
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 5.011
H-Index - 771
eISSN - 1091-6490
pISSN - 0027-8424
DOI - 10.1073/pnas.0409904102
Subject(s) - peripheral blood mononuclear cell , gene , glucocorticoid , gene expression , gene expression profiling , immunology , asthma , medicine , microarray , biology , in vitro , genetics
Gene expression profiles were examined in freshly isolated peripheral blood mononuclear cells (PBMC) from two independent cohorts (training and test sets) of glucocorticoid (GC)-sensitive (n = 64) and GC-resistant (n = 42) asthma patients in search of genes that accurately predict responders and nonresponders to inhaled corticosteroids. A total of 11,812 genes were examined with high-density oligonucleotide microarrays in both resting PBMC (106 patients) and cells treated in vitro with IL-1beta and TNF-alpha combined (88 patients), with or without GC. A total of 5,011 genes were expressed at significant levels in the PBMC, and 1,334 of those were notably up-regulated or down-regulated by IL-1beta/TNF-alpha treatment. The expression changes of 923 genes were significantly reversed in GC responders in the presence of GC. The expression pattern of 15 of these 923 genes that most accurately separated GC responders (n = 26) from the nonresponders (n = 18) in the training set, based on the weighted voting algorithm, predicted the independent test set of equal size with 84% accuracy. The expression accuracy of these genes was confirmed by real-time-quantitative PCR, wherein 11 of the 15 genes predicted GC sensitivity at baseline with 84% accuracy, with one gene predicting at 81% in an independent cohort of 79 patients. We conclude that we have uncovered gene expression profiles in PBMC that predict clinical response to inhaled GC therapy with meaningful accuracy. Upon validation in an independent study, these results support the development of a diagnostic test to guide GC therapy in asthma patients.