Novel eosinophilic gene expression networks associated with IgE in two distinct asthma populations

Clin Exp Allergy. 2018 Dec;48(12):1654-1664. doi: 10.1111/cea.13249. Epub 2018 Nov 21.

Abstract

Background: Asthma represents a significant public health burden; however, novel biological therapies targeting immunoglobulin E (IgE)-mediated pathways have widened clinical treatment options for the disease.

Objective: In this study, we sought to identify gene transcripts and gene networks involved in the determination of serum IgE levels in people with asthma that can help inform the development of novel therapeutic agents.

Methods: We analysed gene expression data from a cross-sectional study of 326 Costa Rican children with asthma, aged 6 to 12 years, from the Genetics of Asthma in Costa Rica Study and 610 young adults with asthma, aged 16 to 25 years, from the Childhood Asthma Management Program trial. We utilized differential gene expression analysis and performed weighted gene coexpression network analysis on 25 060 genes, to identify gene transcripts and network modules associated with total IgE, adjusting for age and gender. We used pathway enrichment analyses to identify key biological pathways underlying significant modules. We compared findings that replicated between both populations.

Results: We identified 31 transcripts associated with total IgE that replicated between the two study cohorts. These results were notable for increased eosinophil-related transcripts (including IL5RA, CLC, SMPD3, CCL23 and CEBPE). Pathway enrichment identified the regulation of T cell tolerance as important in the determination of total IgE levels, supporting a key role for IDO1.

Conclusions and clinical relevance: These results provide robust evidence that biologically meaningful gene expression profiles (relating to eosinophilic and regulatory T cell pathways in particular) associated with total IgE levels can be identified in individuals diagnosed with asthma during childhood. These profiles and their constituent genes may represent novel therapeutic targets.

Keywords: allergic asthma; computational biology; eosinophils; gene expression; network medicine.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Asthma / epidemiology
  • Asthma / genetics*
  • Asthma / immunology*
  • Child
  • Computational Biology / methods
  • Costa Rica / epidemiology
  • Eosinophilia / genetics
  • Eosinophilia / immunology
  • Eosinophils / immunology*
  • Eosinophils / metabolism*
  • Female
  • Gene Expression Profiling
  • Gene Expression Regulation
  • Gene Expression*
  • Gene Ontology
  • Gene Regulatory Networks*
  • Humans
  • Immunoglobulin E / immunology*
  • Male

Substances

  • Immunoglobulin E