Table_2_Epigenetic Regulation of Immune and Inflammatory Responses in Rheumatoid Arthritis.xlsx

PurposeRheumatoid arthritis (RA) is a disease associated with multiple factors. Epigenetics can affect gene expression without altering the DNA sequence. In this study, we aimed to comprehensively analyze epigenetic regulation in RA.
MethodsUsing the Gene Expression Omnibus database, we identified a methylation chip, RNA-sequencing, and miRNA microarray for RA. First, we searched for DNA methylation, genes, and miRNAs associated with RA using differential analysis. Second, we determined the regulatory networks for RA-specific methylation, miRNA, and m6A using cross-analysis. Based on these three regulatory networks, we built a comprehensive epigenetic regulatory network and identified hub genes.
ResultsUsing a differential analysis, we identified 16,852 differentially methylated sites, 4877 differentially expressed genes, and 32 differentially expressed miRNAs. The methylation-expression regulatory network was mainly associated with the PI3K-Akt and T-cell receptor signaling pathways. The miRNA expression regulatory network was mainly related to the MAPK and chemokine signaling pathways. M6A regulatory network was mainly associated with the MAPK signaling pathway. Additionally, five hub genes were identified in the epigenetic regulatory network: CHD3, SETD1B, FBXL19, SMARCA4, and SETD1A. Functional analysis revealed that these five genes were associated with immune cells and inflammatory responses.
ConclusionWe constructed a comprehensive epigenetic network associated with RA and identified core regulatory genes. This study provides a new direction for future research on the epigenetic mechanisms of RA.

研究目的：类风湿关节炎（Rheumatoid arthritis，以下简称RA）是一种多因素关联的疾病。表观遗传学（Epigenetics）可在不改变DNA序列的前提下调控基因表达。本研究旨在全面解析RA中的表观遗传调控机制。
研究方法：本研究依托基因表达综合数据库（Gene Expression Omnibus database），检索并筛选得到针对RA的甲基化芯片、RNA测序（RNA-sequencing）及miRNA微阵列（miRNA microarray）数据集。首先通过差异分析筛选出与RA相关的DNA甲基化位点、基因及miRNA；其次通过交叉分析构建RA特异性的甲基化、miRNA及m6A调控网络；基于上述三类调控网络，搭建综合表观遗传调控网络并鉴定核心基因（hub gene）。
研究结果：经差异分析，本研究共筛选得到16852个差异甲基化位点、4877个差异表达基因及32个差异表达miRNA。甲基化-表达调控网络主要富集于PI3K-Akt信号通路与T细胞受体信号通路；miRNA表达调控网络主要与MAPK信号通路及趋化因子信号通路相关；m6A调控网络则主要富集于MAPK信号通路。此外，在表观遗传调控网络中鉴定出5个核心基因：CHD3、SETD1B、FBXL19、SMARCA4及SETD1A。功能分析显示，上述5个基因均与免疫细胞及炎症反应密切相关。
研究结论：本研究构建了与RA相关的综合表观遗传调控网络并鉴定出核心调控基因，该研究为未来RA表观遗传机制的相关研究提供了全新方向。