Identification of differentially expressed and methylated genes associated with rheumatoid arthritis based on network
Di Zhang,
ZhaoFang Li,
RongQiang Zhang,
XiaoLi Yang,
DanDan Zhang,
Qiang Li,
Chen Wang,
Xuena Yang,
YongMin Xiong
Affiliations
Di Zhang
Institute of Endemic Diseases and Key Laboratory of Trace Elements and Endemic Diseases, National Health Commission of the People’s Republic of China, School of Public Health, Xi’an Jiaotong University Health Science Center
ZhaoFang Li
Institute of Endemic Diseases and Key Laboratory of Trace Elements and Endemic Diseases, National Health Commission of the People’s Republic of China, School of Public Health, Xi’an Jiaotong University Health Science Center
RongQiang Zhang
Shaanxi University of Chinese Medicine
XiaoLi Yang
Institute of Endemic Diseases and Key Laboratory of Trace Elements and Endemic Diseases, National Health Commission of the People’s Republic of China, School of Public Health, Xi’an Jiaotong University Health Science Center
DanDan Zhang
Institute of Endemic Diseases and Key Laboratory of Trace Elements and Endemic Diseases, National Health Commission of the People’s Republic of China, School of Public Health, Xi’an Jiaotong University Health Science Center
Qiang Li
Institute of Endemic Diseases and Key Laboratory of Trace Elements and Endemic Diseases, National Health Commission of the People’s Republic of China, School of Public Health, Xi’an Jiaotong University Health Science Center
Chen Wang
Institute of Endemic Diseases and Key Laboratory of Trace Elements and Endemic Diseases, National Health Commission of the People’s Republic of China, School of Public Health, Xi’an Jiaotong University Health Science Center
Xuena Yang
Institute of Endemic Diseases and Key Laboratory of Trace Elements and Endemic Diseases, National Health Commission of the People’s Republic of China, School of Public Health, Xi’an Jiaotong University Health Science Center
YongMin Xiong
Institute of Endemic Diseases and Key Laboratory of Trace Elements and Endemic Diseases, National Health Commission of the People’s Republic of China, School of Public Health, Xi’an Jiaotong University Health Science Center
Rheumatoid arthritis (RA) is a multi-systemic inflammatory autoimmune disease involving peripheral joints, and the pathogenesis is not clear. Studies showed that DNA methylation and expression might also be involved in the pathogenesis of RA. This study integrated three expression profile datasets (GSE55235, GSE12021, and GSE55457) and one methylation profile dataset GSE111942 to elucidate the potential essential candidate genes and pathways in RA. Differentially expressed genes (DEGs) and differentially methylation genes (DMGs) were identified by R programming software, using Limma package and ChAMP package, respectively. DAVID performed gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway enrichment analysis of DEGs. Functional annotation and construction of a protein–protein interaction (PPI) network and the Molecular Complex Detection Algorithm (MCODE) were analysed by STRING and Cystoscope, respectively. Then the connection analysis of DEGs and DMGs was carried out, and further to analyse the relationship between methylation and gene expression, aiming to screen out the potential genes. In this study, 288 DEGs and 228 DMGs were identified, and the majority of DEGs were up-regulated. Enrichment analysis represented that DEGs mainly involved immune response and participated in the Cytokine–cytokine receptor interaction signal pathway. 282 nodes were identified from DEGs PPI network and MCODE, filtering the most significant 2 modules, 23 core node genes were identified and most of them are involved in the T cell receptor signalling pathway and chemokine-mediated signalling pathway. Cross-analysis revealed 4 genes [KNTC1 (cg 01277763), LRRC8D (cg 07600884), DHRS9 (cg 05961700), and UCP2 (cg 05205664)] that exhibited differential expression and methylation in RA simultaneously. Therefore, the four genes could be used as the target for RA.
