Literature DB >> 28882568

Identification of pathogenic genes related to rheumatoid arthritis through integrated analysis of DNA methylation and gene expression profiling.

Lei Zhang1, Shiyun Ma2, Huailiang Wang2, Hang Su2, Ke Su2, Longjie Li2.   

Abstract

The purpose of our study was to identify new pathogenic genes used for exploring the pathogenesis of rheumatoid arthritis (RA). To screen pathogenic genes of RA, an integrated analysis was performed by using the microarray datasets in RA derived from the Gene Expression Omnibus (GEO) database. The functional annotation and potential pathways of differentially expressed genes (DEGs) were further discovered by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Afterwards, the integrated analysis of DNA methylation and gene expression profiling was used to screen crucial genes. In addition, we used RT-PCR and MSP to verify the expression levels and methylation status of these crucial genes in 20 synovial biopsy samples obtained from 10 RA model mice and 10 normal mice. BCL11B, CCDC88C, FCRLA and APOL6 were both up-regulated and hypomethylated in RA according to integrated analysis, RT-PCR and MSP verification. Four crucial genes (BCL11B, CCDC88C, FCRLA and APOL6) identified and analyzed in this study might be closely connected with the pathogenesis of RA.
Copyright © 2017. Published by Elsevier B.V.

Entities:  

Keywords:  DNA methylation; Pathogenesis; Pathogenic genes; Rheumatoid arthritis

Mesh:

Year:  2017        PMID: 28882568     DOI: 10.1016/j.gene.2017.08.032

Source DB:  PubMed          Journal:  Gene        ISSN: 0378-1119            Impact factor:   3.688


  2 in total

1.  Integrating genome-wide DNA methylation and mRNA expression profiles identified different molecular features between Kashin-Beck disease and primary osteoarthritis.

Authors:  Yan Wen; Ping Li; Jingcan Hao; Chen Duan; Jing Han; Awen He; Yanan Du; Li Liu; Xiao Liang; Feng Zhang; Xiong Guo
Journal:  Arthritis Res Ther       Date:  2018-03-07       Impact factor: 5.156

2.  Comparison of immune cells and diagnostic markers between spondyloarthritis and rheumatoid arthritis by bioinformatics analysis.

Authors:  Jiaqian Wang; Yuan Xue; Liang Zhou
Journal:  J Transl Med       Date:  2022-05-04       Impact factor: 8.440

  2 in total

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