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Comparative Analysis on Abnormal Methylome of Differentially Expressed Genes and Disease Pathways in the Immune Cells of RA and SLE

Fang, Qinghua (author)
Southern Medical University, Guangzhou, China
Li, Tingyue (author)
Erasmus Medical Center, Rotterdam, Netherlands
Chen, Peiya (author)
First Affiliated Hospital of Jinan University, Guangzhou, China
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Wu, Yuzhe (author)
Southern Medical University, Guangzhou, China
Wang, Tingting (author)
Southern Medical University, Guangzhou, China
Mo, Lixia (author)
Southern Medical University, Guangzhou, China
Ou, Jiaxin (author)
Southern Medical University, Guangzhou, China
Nandakumar, Kutty Selva, 1965- (author)
Southern Medical University, Guangzhou, China
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 (creator_code:org_t)
2021-05-17
2021
English.
In: Frontiers in Immunology. - : Frontiers Media SA. - 1664-3224. ; 12
  • Journal article (peer-reviewed)
Abstract Subject headings
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  • We identified abnormally methylated, differentially expressed genes (DEGs) and pathogenic mechanisms in different immune cells of RA and SLE by comprehensive bioinformatics analysis. Six microarray data sets of each immune cell (CD19+ B cells, CD4+ T cells and CD14+ monocytes) were integrated to screen DEGs and differentially methylated genes by using R package "limma." Gene ontology annotations and KEGG analysis of aberrant methylome of DEGs were done using DAVID online database. Protein-protein interaction (PPI) network was generated to detect the hub genes and their methylation levels were compared using DiseaseMeth 2.0 database. Aberrantly methylated DEGs in CD19+ B cells (173 and 180), CD4+ T cells (184 and 417) and CD14+ monocytes (193 and 392) of RA and SLE patients were identified. We detected 30 hub genes in different immune cells of RA and SLE and confirmed their expression using FACS sorted immune cells by qPCR. Among them, 12 genes (BPTF, PHC2, JUN, KRAS, PTEN, FGFR2, ALB, SERB-1, SKP2, TUBA1A, IMP3, and SMAD4) of RA and 12 genes (OAS1, RSAD2, OASL, IFIT3, OAS2, IFIH1, CENPE, TOP2A, PBK, KIF11, IFIT1, and ISG15) of SLE are proposed as potential biomarker genes based on receiver operating curve analysis. Our study suggests that MAPK signaling pathway could potentially differentiate the mechanisms affecting T- and B- cells in RA, whereas PI3K pathway may be used for exploring common disease pathways between RA and SLE. Compared to individual data analyses, more dependable and precise filtering of results can be achieved by integrating several relevant data sets.

Subject headings

MEDICIN OCH HÄLSOVETENSKAP  -- Medicinska och farmaceutiska grundvetenskaper -- Immunologi inom det medicinska området (hsv//swe)
MEDICAL AND HEALTH SCIENCES  -- Basic Medicine -- Immunology in the medical area (hsv//eng)

Keyword

bioinformatics analysis
immune cells
methylation
rheumatoid arthritis
systemic lupus erythematosus

Publication and Content Type

ref (subject category)
art (subject category)

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