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Reanalysis of microarray data reveals insights into altered transcriptional activity of T helper 17 and regulatory T cell signaling in psoriasis

Authors Kotb I, Meharg C, Barker RN, Ormerod A

Received 8 July 2013

Accepted for publication 19 August 2013

Published 12 December 2013 Volume 2013:3 Pages 31—47


Checked for plagiarism Yes

Review by Single-blind

Peer reviewer comments 2

Iman Kotb,1 Caroline Meharg,2 Robert N Barker,1 Anthony Ormerod1

1Institute of Medical Sciences, University of Aberdeen, Aberdeen, Scotland, UK; 2Institute for Global Food Security, Queen's University, Belfast, Northern Ireland

Abstract: Identifying differential expression of genes in psoriatic and healthy skin by microarray data analysis is a key approach to understand the pathogenesis of psoriasis. Analysis of more than one dataset to identify genes commonly upregulated reduces the likelihood of false positives and narrows down the possible signature genes. Genes controlling the critical balance between T helper 17 and regulatory T cells are of special interest in psoriasis. Our objectives were to identify genes that are consistently upregulated in lesional skin from three published microarray datasets. We carried out a reanalysis of gene expression data extracted from three experiments on samples from psoriatic and nonlesional skin using the same stringency threshold and software and further compared the expression levels of 92 genes related to the T helper 17 and regulatory T cell signaling pathways. We found 73 probe sets representing 57 genes commonly upregulated in lesional skin from all datasets. These included 26 probe sets representing 20 genes that have no previous link to the etiopathogenesis of psoriasis. These genes may represent novel therapeutic targets and surely need more rigorous experimental testing to be validated. Our analysis also identified 12 of 92 genes known to be related to the T helper 17 and regulatory T cell signaling pathways, and these were found to be differentially expressed in the lesional skin samples.

Keywords: psoriasis, gene array analysis, gene expression profiling

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