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High resolution DNA methylation signature in rheumatoid arthritis

High resolution DNA methylation signature in rheumatoid arthritis
类风湿性关节炎的高分辨率 DNA 甲基化特征
批准号:
8760169
负责人:
GARY S FIRESTEIN
金额:
$34.1万
依托单位国家:
美国
项目类别:
财政年份:
2014
资助国家:
美国
项目状态:
已结题
起止时间:
2014-08-01 至 2019-07-31

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DESCRIPTION (provided by applicant): Joint damage and synovial inflammation in rheumatoid arthritis (RA) are influenced by genetic and environmental factors. Epigenetics offers new ways to think about how environmental exposure and stress in inflamed tissues can alter gene expression and cellular function. One of the best-studied mechanisms is DNA methylation, which can profoundly alter cellular function by repressing gene expression. Methylation typically occurs on CpG loci and is mediated by DNA methyltransferases (DNMTs). Methylation status is influenced by the environment or through pre-programmed events during embryonic development. DNMT expression can maintain methylation during cell division, thus preserving the cellular imprinting from the environment in daughter cells. Abnormalities in methylation patterns have been described in a variety of diseases, most notably cancer where hyper- and hypo-methylated CpG loci can de-repress critical oncogenes. Autoimmunity has also been associated with altered methylation, such as lupus-like diseases in mice, RA synovium, and possibly RA synoviocytes. We recently showed that RA synoviocytes exhibit a distinct DNA methylation pattern that can regulate expression of key genes. In this proposal, we will expand the DNA methylation signature of RA and integrate this information with genomic and transcriptomic data to identify key genes that participate in the disease. Additional studies will be performed to determine how transcription factor motifs can shape disease specific methylation pattern even though there are a limited number of DNMT enzymes. This hypothesis will be explored by 1) refining the DNA methylation to create a high resolution map in RA fibroblast- like synoviocytes (FLS); 2) integrating genomic, epigenomic, and transcriptomic data to create a unified approach to understanding RA FLS function; and 3) determine how transcription factor motifs contribute to the unique RA methylome signature.
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