DNA methylome signature in rheumatoid arthritis

Abstract

Objectives Epigenetics can influence disease susceptibility and severity. While DNA methylation of individual genes has been explored in autoimmunity, no unbiased systematic analyses have been reported. Therefore, a genome-wide evaluation of DNA methylation loci in fibroblast-like synoviocytes (FLS) isolated from the site of disease in rheumatoid arthritis (RA) was performed. Methods Genomic DNA was isolated from six RA and five osteoarthritis (OA) FLS lines and evaluated using the Illumina HumanMethylation450 chip. Cluster analysis of data was performed and corrected using Benjamini–Hochberg adjustment for multiple comparisons. Methylation was confirmed by pyrosequencing and gene expression was determined by qPCR. Pathway analysis was performed using the Kyoto Encyclopedia of Genes and Genomes. Results RA and control FLS segregated based on DNA methylation, with 1859 differentially methylated loci. Hypomethylated loci were identified in key genes relevant to RA, such as CHI3L1, CASP1, STAT3, MAP3K5, MEFV and WISP3. Hypermethylation was also observed, including TGFBR2 and FOXO1. Hypomethylation of individual genes was associated with increased gene expression. Grouped analysis identified 207 hypermethylated or hypomethylated genes with multiple differentially methylated loci, including COL1A1, MEFV and TNF. Hypomethylation was increased in multiple pathways related to cell migration, including focal adhesion, cell adhesion, transendothelial migration and extracellular matrix interactions. Confirmatory studies with OA and normal FLS also demonstrated segregation of RA from control FLS based on methylation pattern. Conclusions Differentially methylated genes could alter FLS gene expression and contribute to the pathogenesis of RA. DNA methylation of critical genes suggests that RA FLS are imprinted and implicate epigenetic contributions to inflammatory arthritis.

Epigenome Analysis Reveals TBX5 as a Novel Transcription Factor Involved in the Activation of Rheumatoid Arthritis Synovial Fibroblasts

“…In systemic lupus erythematosus, the promoters of CD70 and perforin were reported to be hypomethylated in T cells (10). Recently, two independent groups published their DNA methylation signature studies analyzing RASF using the Illumina Human Methylation 450 chip (11,12). IL6R, CAPN8, DPP4, and several HOX genes were identified as methylated target genes (12).…”

“…IL6R, CAPN8, DPP4, and several HOX genes were identified as methylated target genes (12). In addition, hypomethylation was suggested to be connected with alterations in cellular behavior, such as cell migration, cell adhesion, and extracellular matrix interactions (11). Although these studies revealed novel differentially methylated, and, thus, deregulated, genes in RASF, their function was not evaluated on a single-gene level.…”

How to interpret epigenetic association studies: a guide for clinicians

“…Thus, as it was the case in some recent studies, bone samples are preferable in principle to study osteoporosis-related epigenetic markers, whereas cartilage samples or synovial samples are preferable in studies of osteoarthritis or rheumatoid arthritis. 30,[32][33][34] Nevertheless, some intriguing similarities in the methylation of some genes in cartilage and bone have been recently reported. 35 There are very scarce data about the correlation of epigenetic marks in blood and the skeleton, but, in view of other studies, caution is recommended before extrapolating blood signatures to bone signatures.…”

“…However, these concerns have not been usually addressed in studies about skeletal epigenetics. 30,32 The analysis of a single type of cells, including immortalized cell lines and primary cell cultures (for example, primary osteoblasts grown from bone pieces), could emerge as an interesting alternative to avoid the problem of heterogeneity. However, the results of those studies must be interpreted with caution, because of the modifications of epigenetic signatures that experience cells in culture.…”

“…This was the method for correction used in several epigenome-wide studies in the bone field (Box 2). 30,32,56 Nevertheless, any procedure increasing the statistical stringency to avoid the inflation of type I error implicates increasing the chances of type II error. This is the error occurring when true differences or associations are not identified because they do not appear to be 'significant' in the study.…”