Article Text

other Versions

PDF
Gene Expression profiling reveals a down-regulation in immune-associated genes in AS patients
  1. Ran Duan (ran.duan{at}uq.edu.au)
  1. Diamantina Institute for Cancer, Immunology & Metabolic Medicine, University of Queensland, Australia
    1. Paul Leo (p.leo{at}uq.edu.au)
    1. Diamantina Institute for Cancer, Immunology & Metabolic Medicine, University of Queensland, Australia
      1. Linda Bradbury (l.bradbury{at}uq.edu.au)
      1. Diamantina Institute for Cancer, Immunology & Metabolic Medicine, University of Queensland, Australia
        1. Matt A Brown (matt.brown{at}uq.edu.au)
        1. Diamantina Institute for Cancer, Immunology & Metabolic Medicine, University of Queensland, Australia
          1. Gethin P Thomas (gethin.thomas{at}uq.edu.au)
          1. Diamantina Institute for Cancer, Immunology & Metabolic Medicine, University of Queensland, Australia

            Abstract

            Objective: To identify differentially expressed genes in peripheral blood mononuclear cells (PBMCs) from patients with ankylosing spondylitis (AS) compared to healthy individuals.

            Methods: RNA was extracted from PBMCs collected from 18 AS patients with active disease and 18 gender- and age-matched controls. Expression profiles of these cells were determined using microarray. Candidate genes with differential expressions were confirmed in the same samples using quantitative reverse transcription-polymerase chain reaction (qRT-PCR). These genes were then validated in a different sample cohort of 35 AS and 18 patients by qRT-PCR.

            Results: Microarray analysis identified 452 genes detected with 485 probes which were expressed at significantly different levels (p<0.006) between AS patients and controls. Under-expression of NR4A2, TNFAIP3, and CD69 was confirmed. These genes were further validated in a different sample group where the AS patients had a wider range of disease activity. Predictive algorithms were also developed from the expression data using Receiver-Operator Characteristic (ROC) curves, which demonstrated that the 3 candidate genes have ~80% power to predict AS according to their expression levels.

            Conclusions: Our findings showed differences in global gene expression patterns between AS patients and controls suggesting an immunosuppressive phenotype in AS patients. Furthermore, we confirmed downregulated expression of 3 immune-related genes. These candidate genes were also shown to be strong predictive markers for AS.

            Statistics from Altmetric.com

            Request permissions

            If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.