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-1␤ and TNF-␣ 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-1␤͞TNF-␣ 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.

Asthma genetics 2006: the long and winding road to gene discovery

“…Complementary approaches may also be required to fully characterize the underlying architecture. For example, expression profiling in human tissues and animal models 51,52 can identify interacting sets of genes that could serve as candidates or provide quantitative phenotypes (eQTLs) 53 for genetic studies; bioinformatic 54 or systems-based approaches 55 can identify disease-related variants that interact in molecular or biochemical pathways; and functional analyses of associated variants or haplotypes can provide clues to pathogenesis. 43,56 Such 'molecular phenotyping' of patients with asthma or atopic diseases may inform decisions regarding treatment, and thereby laying the foundation for genomic medicine in the next decade.…”

Discovery of novel markers in allergic lung inflammation through proteomic-based technologies

“…Therefore, current research in asthma has focused on the discovery of novel, more specific pathways that coordinate airway-obstructive disease in the setting of allergic inflammation and narrow-spectrum modulators of pathways critical to the disease phenotype. Widely used as part of these endeavors are proteomics-and genomics-based approaches, which have indeed identified novel inflammatory biomarkers in human and experimental asthma [5][6][7]. Bronchoalveolar lavage (BAL) fluid is perhaps the most widely used biological sample for the identification of novel asthma biomarkers through proteomics, although serum, whole lung and CD3 + T cells have also been used [8][9][10][11].…”

Genome-wide association studies in asthma: progress and pitfalls

“…These results are in keeping with results from an expression gene-array study profiling genes expressed in peripheral blood mononuclear cells from glucocorticoid-sensitive and -resistant asthma patients. 41 A second GWA study, using self-reported asthmadiary entries from child subjects, identified and replicated three SNPs (rs1558726, rs2388639, and rs10044254) that associated specifically with ICS-induced improvements in self-reported asthma scores in pediatric asthma patients. 42 The SNP rs10044254 lies within the FBXL7 gene, and is associated with decreased expression of the transcript.…”