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OP0054 High-Throughput DNA Methylation Analysis of Cell Sorted Blood Cell Populations Reveals Widespread Epigenetic Deregulation in Sjogren’s Syndrome
  1. J. Tost1,
  2. N. Touleimat1,
  3. S. Boudaoud2,
  4. C. Miceli2,
  5. X. Mariette2
  1. 1Laboratory for Epigenetics & Environment, CEA-Institut de Génomique, Centre National de Génotypage, Evry
  2. 2Institut National de la Santé et de la Recherche Médicale (INSERM) U1012, Université Paris-Sud 11, Hôpital Bicêtre, Assistance Publique-Hôpitaux de Paris (AP-HP), Le Kremlin Bicêtre, France


Background Autoimmune result from the interaction between genetic and environmental factors. Previous studies have demonstrated the implication of DNA methylation alterations in many autoimmune diseases.1 Sjögren’s Syndrome (SS) is a prototypic systemic autoimmune disease that can be primary or associated with other systemic connective tissue diseases. DNA methylation is almost exclusively found in the context of the dinucleotide sequence CpG. Methylation of regulatory sequences can lead to gene silencing and the interest in DNA methylation has been raised through multiple studies demonstrating its potential as biomarker containing valuable information for diagnosis, classification and prognosis of disease. Until now, very few data are available in pSS.

Objectives To date, no treatment has proven effective in SS. The identification of differentially methylated regions could provide information on novel key players involved in the pathogenesis of pSS and new targets for therapeutic intervention in the future.

Methods We analyzed genome-wide DNA methylation patterns in FACS sorted B and T-lymphocytes from 12 SS patients and 12 controls using the Illumina 450K Infinium Human Methylation 450K BeadChip monitoring quantitatively more than 480,000 CpG positions. Data was analyzed using a newly developed preprocessing pipeline for 450K data using an original subset quantile normalization approach that performs both sample normalization and efficient Infinium I/Infinium II shift correction.2 Differentially methylated regions of interest are validated in an additional set of 12 SS patients and 12 controls as well as salivary gland biopsies using pyrosequencing.

Results 1537 probes associated with 993 genes were differentially methylated between patients and controls in B lymphocytes, and 1129 probes associated with 723 genes were differentially methylated in T lymphocytes including genes from the MHC and genes associated with other autoimmune diseases. Pathway analysis showed a highly significant overlap of the genes identified in B lymphocytes with rheumatoid arthritis (p<10-8) and lupus associated genes (p<10-6) including SLC15A4 and IKFZ1, lymphomagenesis and regulation of apoptosis. Replication is currently ongoing, but the first genes replicated well in an independent biological samples.

Further, comparing our data to genes found differentially methylated in synviocytes from rheumatoid arthritis (RA) patients we show that the RA-signature classified reasonably well the B cell samples into pSS patients and controls. Although the separation was not perfect (as expected as different tissues were analyzed), these results raise the hypothesis of a common DNA methylation signature of autoimmune diseases.

Conclusions Genome-wide DNA methylation profiling identified widespread epigenetic deregulation which provide novel insight in the disease pathology and raises the possibility of a common epigenetic deregulation in AIDs.


  1. Myrtue Nielsen, H. and J. Tost (2012) Epigenetic changes in inflammatory and autoimmune diseases, Subcellular Biochemistry, 61, 455-78.

  2. Touleimat, N., and J. Tost (2012) A complete pipeline for Infinium Methylation 450K BeadChip data processing using subset quantile normalization for accurate DNA methylation estimation, Epigenomics, 4, 325-41.


Acknowledgements This work was supported by the Agence Nationale pour la Recherche (BLAN 2010 R11035LL).

Disclosure of Interest None Declared

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