TY - JOUR
T1 - Comparative Analysis on Abnormal Methylome of Differentially Expressed Genes and Disease Pathways in the Immune Cells of RA and SLE
AU - Fang, Qinghua
AU - Li, Tingyue
AU - Chen, Peiya
AU - Wu, Yuzhe
AU - Wang, Tingting
AU - Mo, Lixia
AU - Ou, Jiaxin
AU - Nandakumar, Kutty Selva
N1 - Funding Information:
This project was supported by project grants from Southern Medical University, Guangzhou, China (Grant numbers C1034211, C1051004) given to KSN.
Publisher Copyright:
© Copyright © 2021 Fang, Li, Chen, Wu, Wang, Mo, Ou and Nandakumar.
PY - 2021/5/17
Y1 - 2021/5/17
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85107232048&partnerID=8YFLogxK
U2 - 10.3389/fimmu.2021.668007
DO - 10.3389/fimmu.2021.668007
M3 - Article
C2 - 34079550
AN - SCOPUS:85107232048
SN - 1664-3224
VL - 12
JO - Frontiers in Immunology
JF - Frontiers in Immunology
M1 - 668007
ER -