Gene Expression Profiling in Patients with Chronic Idiopathic Urticaria Reveals Unique Gene Signature Distinct from Healthy Controls

Background: Chronic Idiopathic Urticaria (CIU) is a relatively common disease which accounts for up to 30% of office visits to allergists. Although designated idiopathic the pathophysiology and mechanism of disease is reported to result from immune activation due to variety of causes. CIU is a manifestation of immune activation with approximately 50% of CIU patients demonstrating autoimmunity as evidenced by presence of IgG antibody to the FceR1 receptor present on mast cells and basophils. Autoantibodies to thyroid tissue and many other cellular and cell surface receptors commonly coexist. Further elucidation is lacking at the genetic and molecular level.  Ideally, a better understanding of the underlying biology could improve not only prognostic indicators, but also provide a background for generating predictor models of treatment responders.

Methods: We collected peripheral blood mononuclear cells (PBMC’s) from 21 patients with active CIU disease and 10 non-atopic healthy controls. RNA was extracted from PBMC’s and prepared for Affymetrix GeneChip® Human Gene U133 plus 2.0 Array hybridization. The raw data were normalized and the gene expression of CIU patients was compared to that of normal controls. 

Results:  We found 149 genes that predicted CIU from normal controls (FDR<5%).  The genes in the predictor are differentially expressed (P<0.001) with a minimum 2-fold difference between CIU patients and controls.  The predictor was 100% successful in distinguishing patients with CIU from controls, and tested using leave one out cross-validation.  Additionally we found that the upregulated genes seen in CIU most strongly correlated with monocytes, identified as cells expressing CD14 cell surface marker (p<0.001, r >0.8). Gene set enrichment analysis of CIU patients further revealed activation of a specific arm of the MAP-Kinase pathway utilized by monocytes (p<0.001, r >0.8).

Conclusions: Gene expression profiling can reliably distinguish patients with CIU from healthy controls.  Our study findings suggest potential underlying mechanisms of CIU. These findings may provide guidance in developing biomarkers that would help determine subsets of patients who would be more likely to respond to variety of treatment options available.