Gene expression analysis in asthma using a targeted multiplex array

Abstract

Background: Gene expression changes in the structural cells of the airways are thought to play a role in the development of asthma and airway hyperresponsiveness. This includes changes to smooth muscle contractile machinery and epithelial barrier integrity genes. We used a targeted gene expression arrays to identify changes in the expression and co-expression of genes important in asthma pathology.

Methods: RNA was isolated from the airways of donor lungs from 12 patients with asthma (8 fatal) and 12 non-asthmatics controls and analyzed using a multiplexed, hypothesis-directed platform to detect differences in gene expression. Genes were grouped according to their role in airway dysfunction: airway smooth muscle contraction, cytoskeleton structure and regulation, epithelial barrier function, innate and adaptive immunity, fibrosis and remodeling, and epigenetics.

Results: Differential gene expression and gene co-expression analyses were used to identify disease associated changes in the airways of asthmatics. There was significantly decreased abundance of integrin beta 6 and Ras-Related C3 Botulinum Toxin Substrate 1 (RAC1) in the airways of asthmatics, genes which are known to play an important role in barrier function. Significantly elevated levels of Collagen Type 1 Alpha 1 (COL1A1) and COL3A1 which have been shown to modulate cell proliferation and inflammation, were found in asthmatic airways. Additionally, we identified patterns of differentially co-expressed genes related to pathways involved in virus recognition and regulation of interferon production. 7 of 8 pairs of differentially co-expressed genes were found to contain CCCTC-binding factor (CTCF) motifs in their upstream promoters.

Conclusions: Changes in the abundance of genes involved in cell-cell and cell-matrix interactions could play an important role in regulating inflammation and remodeling in asthma. Additionally, our results suggest that alterations to the binding site of the transcriptional regulator CTCF could drive changes in gene expression in asthmatic airways. Several asthma susceptibility loci are known to contain CTCF motifs and so understanding the role of this transcription factor may expand our understanding of asthma pathophysiology and therapeutic options.

Keywords: Asthma; CTCF; Co-expression; Epithelium; Extracellular matrix; Nanostring; Remodeling; Smooth muscle; Targeted expression.

Fig. 1

Section of a frozen human lung core cut at 10 μm thickness. Blue arrows indicate airways. Red arrow indicates a blood vessel. The black lines show the outline of the tissue taken for isolation of total airway RNA. Scale bar = 5 mm

Fig. 2

Comparison of non-asthmatic airway (a) and asthmatic airway (b). Airways are stained using hematoxylin and eosin (H&E) to highlight remodeling changes within the airways. Scale bar is 200 μm

Fig. 3

Volcano plot summarizing the results of the gene expression analysis. Dotted vertical line indicates fold difference of zero. Fold differences greater than zero (positive) indicate increased gene expressed in asthmatics compared to non-asthmatics. Dotted horizontal line indicates significance at nominal p-value of 0.05

Fig. 4

Volcano plots summarizing the results of gene expression for each hypothesis group. Genes involved in (a) Contractile regulation, (b) Structure of the contractile apparatus, (c) Cytoskeletal regulation, (d) Structure of the cytoskeleton, (e) Epigenetic control, (f) Epithelial function, (g) Fibrosis and remodeling, (h) Innate and adaptive immunity. Some genes fall into more than one category and so are plotted in applicable categories. Dotted vertical line indicates fold differences of zero, dotted horizontal lines indicates significance at nominal p-value of 0.05

Fig. 5

Example of co-expression plots. Each line represents one gene in the cluster. Subjects are indicated along the x-axis, log expression values on the y-axis. P-values are for the significance of the co-expression in each group

Fig. 6

Individual correlation plots for the pairs of differentially co-expressed genes in asthmatics and non-asthmatics. a LAMB2 vs. MMP9, (b) BPIFA1 vs. DDX58, (c) BMP2 vs. NFACT2, (d) GNAS vs. NFACT2, (e) CHI3L1 vs. GSDMB, (F) CHI3L1 vs. HDAC10, (G) HDAC10 vs. THY1, (F) IDO1 vs. NFATC2. Each point represents a sample and the values on the axes are gene counts. Lines of best fit are plotted with the 95% confidence interval (grey shaded area) for each correlation. Each of the correlations is significant (p < 0.05) and the direction indicates a positive or negative correlation