Meta-Analysis of Expression Profiling Data Indicates Need for Combinatorial Biomarkers in Pediatric Ulcerative Colitis

Abstract

Background: Unbiased studies using different genome-wide methods have identified a great number of candidate biomarkers for diagnosis and treatment response in pediatric ulcerative colitis (UC). However, clinical translation has been proven difficult. Here, we hypothesized that one reason could be differences between inflammatory responses in an inflamed gut and in peripheral blood cells.

Methods: We performed meta-analysis of gene expression microarray data from intestinal biopsies and whole blood cells (WBC) from pediatric patients with UC and healthy controls in order to identify overlapping pathways, predicted upstream regulators, and potential biomarkers.

Results: Analyses of profiling datasets from colonic biopsies showed good agreement between different studies regarding pathways and predicted upstream regulators. The most activated predicted upstream regulators included TNF, which is known to have a key pathogenic and therapeutic role in pediatric UC. Despite this, the expression levels of TNF were increased in neither colonic biopsies nor WBC. A potential explanation was increased expression of TNFR2, one of the membrane-bound receptors of TNF in the inflamed colon. Further analyses showed a similar pattern of complex relations between the expression levels of the regulators and their receptors. We also found limited overlap between pathways and predicted upstream regulators in colonic biopsies and WBC. An extended search including all differentially expressed genes that overlapped between colonic biopsies and WBC only resulted in identification of three potential biomarkers involved in the regulation of intestinal inflammation. However, two had been previously proposed in adult inflammatory bowel diseases (IBD), namely, MMP9 and PROK2.

Conclusions: Our findings indicate that biomarker identification in pediatric UC is complicated by the involvement of multiple pathways, each of which includes many different types of genes in the blood or inflamed intestine. Therefore, further studies for identification of combinatorial biomarkers are warranted. Our study may provide candidate biomarkers for such studies.

Figure 1

Analysis of shared pathways and upstream regulators in two expression profiling datasets of colonic biopsies from patients with ulcerative colitis. (a) Venn diagram of differentially expressed genes from the two datasets. (b) Canonical pathway comparisons between the two datasets. Orange indicates upregulated, and blue indicates downregulated pathways. Color intensity corresponds to significance, as indicated by the activation z-score bars below the pathways and upstream regulators. (c) Predicted upstream regulators of the mapped differentially expressed genes. (d) Venn diagram of predicted overlapping biomarkers from the two datasets. Dots mean nonsignificant values.

Figure 2

Expression levels of the receptors of predicted upstream regulators in pediatric ulcerative colitis. The expression levels are derived from the relative fluorescence of each transcript on the microarray chips. ^∗P < 1 × 10⁻³, ^∗∗P < 1 × 10⁻⁴, ^∗∗∗P < 1 × 10⁻⁵. IFNGR1: interferon gamma receptor 1; TNFRSF1B: tumor necrosis factor receptor superfamily member 1B; OSMR: oncostatin M receptor; IFNAR2: interferon alpha and beta receptor subunit 2; CSF2RA: colony-stimulating factor 2 receptor alpha subunit.

Figure 3

Ingenuity pathway analysis of expression profiling datasets of whole blood cells and colon biopsies from patients with ulcerative colitis. GSE119600 was the dataset of whole blood cells and GSE9686 and GSE10616 were datasets of colon biopsies. (a) Venn diagram of differentially expressed genes from the three datasets. (b) Canonical pathway comparisons between the three datasets. Orange indicates upregulated, and blue indicates downregulated pathways. Color intensity corresponds to significance. (c) Predicted upstream regulators of the mapped differentially expressed genes. (d) Venn diagram of predicted overlapped biomarkers from the three datasets. Dots mean a nonsignificant value.