CDC42-related genes are upregulated in helper T cells from obese asthmatic children

Abstract

Background: Pediatric obesity-related asthma is more severe and less responsive to medications than asthma in normal-weight children. Obese asthmatic children have nonatopic T_H1-polarized systemic inflammation that correlates with pulmonary function deficits, but the pathways underlying T_H1-polarized inflammation are not well understood.

Objective: We compared the CD4⁺ T-cell transcriptome in obese children with asthma with that in normal-weight children with asthma to identify key differentially expressed genes associated with T_H1-polarized inflammation.

Methods: CD4⁺ T-cell transcriptome-wide differential gene expression was compared between 21 obese and 21 normal-weight children by using directional RNA sequencing. High-confidence differentially expressed genes were verified in the first cohort and validated in a second cohort of 20 children (10 obese and 10 normal-weight children) by using quantitative RT-PCR.

Results: Transcriptome-wide differential gene expression among obese asthmatic children was enriched for genes, including VAV2, DOCK5, PAK3, PLD1, CDC42EP4, and CDC42PBB, which are associated with CDC42, a small guanosine triphosphate protein linked to T-cell activation. Upregulation of MLK3 and PLD1, genes downstream of CDC42 in the mitogen-activated protein kinase and mammalian target of rapamycin pathways and the inverse correlation of CDC42EP4 and DOCK5 transcript counts with FEV₁/FVC ratio together support a role of CDC42 in the T_H1 polarization and pulmonary function deficits found in patients with obesity-related asthma.

Conclusions: Our study identifies the CDC42 pathway as a novel target that is upregulated in T_H cells of obese asthmatic children, suggesting its role in nonatopic T_H1-polarized systemic inflammation and pulmonary function deficits found in patients with pediatric obesity-related asthma.

Keywords: Asthma; children; helper T cell transcriptome; obesity.

Figure 1

Principal component analysis of biological and technical covariates. Principal component 1 was the most important component as seen in the bar graph. The heatmap depicts the strength of the contribution of the study group, and of the biologic and technical covariates, on the variance of gene count for each of the top 6 principal components, highlighting the individual factors that contribute to principal component 1. The darker the intensity of blue color, the stronger was the contribution of the covariate in the variance of the gene count in each principal component as shown in the color key.

Figure 2

MA plot of fold change and mean gene expression using DESeq analysis, a) before adjustment for biological and technical co-variates (univariate analysis) and b) after adjustment for biological and technical co-variates (multivariate analysis). The red dots denote differentially expressed genes among obese asthmatics at FDR q-value<0.05.

Figure 3

Association between differentially expressed high confidence genes. The thickness of the connecting lines reflects the strength of the association.

Figure 4

Verification of a subset of genes in the first cohort of samples by qRT-PCR. Log₁₀ fold differential gene expression is compared between obese and normal-weight children with asthma.

Figure 5

Validation of the subset of genes in the second cohort of samples by qRT-PCR. Log₁₀ fold differential gene expression was compared between obese asthmatic and normal-weight asthmatic Th cells. In addition to genes investigated in the verification experiment (Figure 4), differential expression of additional genes downstream of CDC42 including MLK3 and cRAF1 were investigated. While expression of MLK3 was higher in obese asthmatic Th cells, that of cRAF1 did not differ between obese and normal-weight asthmatic Th cells.

Figure 6

Association of CDC42EP4 and DOCK5 gene counts with FEV₁/FVC ratio. Log₁₀ transformed CDC42EP4 and DOCK5 gene counts were inversely correlated with FEV₁/FVC ratio only in obese asthmatic children.