2D Visualization of the Psoriasis Transcriptome Fails to Support the Existence of Dual-Secreting IL-17A/IL-22 Th17 T Cells

Stephanie T. Le, Alexander A. Merleev, Guillaume Luxardi, Michiko Shimoda, Iannis Adamopoulos, Lam C. Tsoi, Jenny Z. Wang, Claire Alexanian, Siba P Raychaudhuri, Samuel T Hwang, Johann Gudjonsson, Alina I. Marusina, Emanual Michael Maverakis

Research output: Contribution to journalArticle

3 Scopus citations

Abstract

The present paradigm of psoriasis pathogenesis revolves around the IL-23/IL-17A axis. Dual-secreting Th17 T cells presumably are the predominant sources of the psoriasis phenotype-driving cytokines, IL-17A and IL-22. We thus conducted a meta-analysis of independently acquired RNA-seq psoriasis datasets to explore the relationship between the expression of IL17A and IL22. This analysis failed to support the existence of dual secreting IL-17A/IL-22 Th17 cells as a major source of these cytokines. However, variable relationships amongst the expression of psoriasis susceptibility genes and of IL17A, IL22, and IL23A were identified. Additionally, to shed light on gene expression relationships in psoriasis, we applied a machine learning nonlinear dimensionality reduction strategy (t-SNE) to display the entire psoriasis transcriptome as a 2-dimensonal image. This analysis revealed a variety of gene clusters, relevant to psoriasis pathophysiology but failed to support a relationship between IL17A and IL22. These results support existing theories on alternative sources of IL-17A and IL-22 in psoriasis such as a Th22 cells and non-T cell populations.

Original languageEnglish (US)
Number of pages1
JournalFrontiers in immunology
Volume10
DOIs
StatePublished - Jan 1 2019

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Keywords

  • IL17
  • IL22
  • machine learning
  • neutrophil
  • psoriasis
  • RNA-seq
  • T cell
  • transcriptome

ASJC Scopus subject areas

  • Immunology and Allergy
  • Immunology

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