ACR Meeting Abstracts

ACR Meeting Abstracts

Abstract Number: 2532

Whole Transcriptome Analysis in Relapsing Polychondritis: A Single-Center Analysis of 35 Patients

Laurent Arnaud1, Alexis Mathian2, Bruno Faivre3, Karim Dorgham3, Julien Haroche2, Nathalie Costedoat-Chalumeau1, Jean-Charles Piette2, Guy Gorochov4 and Zahir Amoura1, 1Internal Medicine, Hôpital Pitié-Salpêtrière, AP-HP & UPMC Univ Paris 06, Paris, France, 2Department of Internal Medicine 2. Referal center for SLE/APS, Hôpital Pitié-Salpêtrière, AP-HP & UPMC Univ Paris 06, Paris, France, 3Institut National de la Santé et de la Recherche Médicale, INSERM UMR-S 945, Paris, France, 4Inserm UMRS945, Institut National de la Santé et de la Recherche Médicale, INSERM UMR-S 945, Paris, France

Meeting: 2012 ACR/ARHP Annual Meeting

Keywords: , ,

Session Information

Title: Miscellaneous Rheumatic and Inflammatory I

Session Type: Abstract Submissions (ACR)

Background/Purpose: Relapsing polychondritis (RP) is a severe and episodic inflammatory condition involving cartilaginous structures, predominantly those of the ears, nose, and laryngotracheobronchial tree. Other affected structures may include the eyes, cardiovascular system, peripheral joints, skin, middle and inner ear, and CNS. To date, gene expression profiling has not been performed in RP. The aim of this study was to analyze the transcriptome of RP compared to healthy individuals, as a manner to identify new pathways involved in the pathogenesis of the disease as well as new therapeutic targets.

Methods: Total RNA was extracted from peripheral blood mononuclear cell (PBMC) obtained in 35 patients with RP (according to Michet criteria) and 36 healthy individuals. Complementary DNA (cDNA) was hybridized in Illumina Human HT-12® v4 Expression Bead Chips. Statistical analysis of Microarray (SAM) algorithm with Benjamini and Hochberg multiple testing correction was used to determine the statistical significance of the differences in gene expression while controlling the false-discovery rate. Cluster analysis was also performed with JMP8 software. Differentially expressed genes were analyzed to identify potential functional pathways using Ingenuity® Pathway Analysis (IPA).

Results: Gene expression analysis using SAM showed 165 significantly down- or up-regulated transcripts between RP patients and controls. Cluster analysis of these transcripts by similarity on gene expression patterns identified several clusters containing only RP patients, healthy individuals, or both, underlining the strong heterogeneity of the disease. The set of genes statistically different between RP and healthy individuals was further analyzed with IPA Analysis, which revealed a role for genes related to growth factor and cytokine activities, control of the cell-cycle, and kinase-phosphorylation.

Conclusion: This transcriptome analysis of 35 patients with relapsing polychondritis reveals that complex gene expression patterns are involved in the pathogenesis of the disease. This may be seen as a significant advance in this under researched disease with complex clinical presentation and non-formally codified therapeutic management.

Disclosure:

L. Arnaud,
None;

A. Mathian,
None;

B. Faivre,
None;

K. Dorgham,
None;

J. Haroche,
None;

N. Costedoat-Chalumeau,
None;

J. C. Piette,
None;

G. Gorochov,
None;

Z. Amoura,
None.

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