Profiling of genes expressed in peripheral blood mononuclear cells predicts glucocorticoid sensitivity in asthma patients

Abstract

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.

Fig. 1.

PBMC-derived gene expression profile predicting GC-R from GC-S asthma patients after exposure to IL-1β/TNF-α. (A) Differential expression of 15 genes that most accurately separated GC responders from nonresponders in the training set after cytokine treatment is shown. Genes were ranked by a metric similar to signal to noise and were considered the most differentially expressed genes according to the metric used. For each gene shown, red indicates a high level of expression relative to the mean; blue indicates a low level of expression relative to the mean. (B) Values expressed as mean ± SD are shown for the independent group. P values were obtained with a Student's t test with (P-MTC) or without (P) Bonferroni multiple testing correction. P < 0.05 is considered significant.

Fig. 2.

PBMC-derived gene expression profile predicting GC-R from GC-S asthma patients by using RT-PCR. (A) Differential expression of 11 of the 15 best genes identified by the microarray approach based on TaqMan RT-PCR measurements in the baseline samples is shown. Genes were ranked by a metric similar to signal to noise and were considered the most differentially expressed genes according to the metric used. For each gene shown, red indicates a high level of expression relative to the mean; blue indicates a low level of expression relative to the mean. (B) Values are expressed as mean ± SD.