Multi-Omics Studies Identified Genes And Regulatory Network For Rheumatoid Arthritis

Rheumatoid arthritis(RA)is a chronic systemic autoimmune disease,characterized by a chronic inflammation leading to tissue damage,functional impairment,severe disability,and premature mortality.It is determined by genetic,environmental and hormonal factors.The heritability of RA is approximately 65%.RA is more prevalent in woman than men(3:1).The molecular pathogenesis of RA is very complex and unclear yet.Currently,there is no definite treatment algorithms for RA,and the management of this disease depends on early diagnosis and aggressive treatment.Characterizing the underlying molecular characteristics may contribute to better understanding of the pathogenesis,and facilitate development of novel diagnostic and therapeutical strategies.Previous studies have extensively investigated the roles of variations in genomics,transcriptomics and proteomics involved in RA pathogenesis and evaluated the potential of these variations as biomarkers.However,most of these studies analyzed these variations in genomics,transcriptomics and proteomics separately.Recognition of significant epigenetic modifications,target genes,and their interaction networks may lead to better understanding of the molecular pathways involving in the pathogenesis of RA.The present study aimed to identify RA-associated genes,and to ascertain(epi)-genetic factors and functional mechanisms,as well as epigenetically-regulated networks underlying RA pathogenesis.In part Ⅰ,we utilized multi-omics datasets from the same set of RA cases and control samples,including peripheral blood mononuclear cells(PBMCs)transcriptome-wide mRNA expression data,genome-wide SNP genotyping data,and epigenome-wide miRNA expression data and DNA methylation data.The(epi)genetically-regulated genes and co-expression networks in PBMCs significant for RA were identified.In part Ⅱ,based on the quantitative proteomics Label-Free technology,we systematically identified potential RA protein biomarkers in PBMCs.In part Ⅲ,we identified RA-associated genes by integrative analysis of transcriptome and proteome datasets.Specific DEG,validated by RT-PCR,was followed-up by cellular functional assays to ascertain its downstream effects on behaviors of RA-relevant immune cells.Part ⅠObjectiveTo identify(epi-)genetic factors,(epi-)genetically-regulated genes and networks in peripheral blood mononuclear cells(PBMCs)significant for RA.MethodsMulti-omics microarray data(mRNA,miRNA and DNA methylation)were generated from PBMCs of a RA case-control sample.Differentially expressed mRNAs/miRNAs(DEMs/DEMis)and differentially methylated positions(DMPs)between cases and controls were identified.DMPs/DEMis significantly correlated with DEMs in PBMCs were identified using Pearson correlation analyses.Causal inference test(CIT)was conducted to identify causal epigenetic factors and intermediate genes for RA.Weighted gene co-expression network analysis(WGCNA)was conducted to annotate intermediate genes and identify pivotal gene.We also performed a genome-wide eQTL analysis by using genome-wide SNPs data and transcriptome-wide mRNA expression data.Public datasets were utilized to identify common eQTLs shared with PBMCs in lymphoblastoid,monocytes,liver,and brain.Allelic expression imbalance(AEI)assay was employed to validate representative eQTLs identified.ResultsA total of 181 DEMs(Fold Change>2.0,Bonferroni adjusted P<0.05)were identified in PBMCs.Among those DEMs,50 and 24 DEMs were significantly correlated with DMPs and DEMis,respectively(P<0.05).Six DEMs(e.g.,CRKL and SMURF1)were significantly regulated by both DMP and DEMi.CIT analyses identified 18 significant causal chains of DMP-DEM-RA,highlighting the intermediate effects of 16 key DEMs(e.g.,SOCS3,CISH,L2HGDH,PARP9,and BTN2A1),which were enriched in "protein kinase inhibitor activity"(GO:0004860,P=0.04).Notably,BTN2A1 was co-expressed with other 9 intermediate genes and 11 known RA-associated genes and played a pivotal role in the co-expression network.Besides,a transcriptome-wide expression regulation network was constructed,highlighting the importance of 28 pleiotropic eSNPs and 18 dually(cis-and trans-)regulated genes.Among 8,904 eQTLs(P<0.001)identified herein in PBMCs,a minority(163)was overlapped with lymphoblastoid,monocytes,liver,and/or brain.Besides,two cis-eSNPs in PBMC were confirmed by AEI.ConclusionsA cluster of genes were epigenetically regulated and co-expressed in PBMCs and contributed to RA.The causal DMPs,e.g.,cg23371570,and key intermediate genes,e.g.,BTN2A1 and SOCS3,may serve as potential biomarkers for RA.Besides,the present results demonstrated a comprehensive expression regulation network for human PBMCs and may provide novel insights into the pathogenesis of immunological diseases related to PBMCs.Part ⅡObjectiveTo identify potential RA protein biomarkers in PBMCs in a RA case and control sample,and to assess its performance in discriminating RA cases and controls.MethodsRA protein biomarkers were identified in PBMCs in a RA case and control sample by utilizing quantitative proteomics Label-Free technology,then validated in an independent sample by conducting Western blot.Protein biomarker in plasma was quantitated by ELISA to assess its performance in discriminating RA cases and controls.ResultsA total of 64 differentially expressed proteins(P<0.05)were identified in PBMCs.These differentially expressed proteins were significantly enriched in biological processes,including "positive regulation of NIK/NF-kappaB signaling"(P=0.018),"positive regulation of neutrophil chemotaxis"(P=0.032),"positive regulation of phagocytosis"(P=0.037),and significantly enriched in the Leukocyte transendothelial migration(KEGG ID 04670).ITGA2 up-regulated with RA,were validated.Another independent ELISA assay showed that ITGA2 was significantly up-regulated in RA.Plasma ITGA2 protein demonstrated superior performances in discriminating RA cases and controls(AUC=0.80,P<0.05).ConclusionsITGA2 protein may serve as a novel protein biomarker for RA diagnosis.Part ⅢObjectiveTo identify RA-associated genes and to ascertain epigenetic factors and functional mechanisms underlying RA pathogenesis.MethodsWe used peripheral blood mononuclear cells(PBMC)transcriptome-and proteome-wide gene expressions to identify RA-associated genes in a case-control study sample(25 cases and 18 controls),and then validated the most significant differentially expressed gene(DEG)in an independent sample(35 cases and 35 controls).The most significant DEG,i.e.,RPN2,was validated to be up-regulated with RA independently.In-house genome-wide SNP genotyping data,miRNA expression data and DNA methylation data in the same discovery sample were utilized to assess the association between the key DEG,RPN2,and SNPs(eQTLs and pQTLs),miRNAs,and DNA methylation positions(DMPs).A complex regulatory network for RPN2 gene expression in PBMCs was constructed.Specific DEG,RPN2,validated by RT-PCR,was followed-up by cellular functional assays to ascertain its downstream effects on behaviors of RA-relevant immune cells.Furthermore,the RPN2 was assessed and evaluated for its diagnostic value for RA.ResultsA total of 22 DEGs were discovered in PBMCs.The most significant DEG,i.e.,RPN2,was validated to be up-regulated with RA in PBMCs.A complex regulatory network for RPN2 gene expression in PBMCs was constructed,which consists of 38 eQTL and 53 pQTL SNPs,3 miRNAs and 2 DMPs.Besides,RPN2 expression was significantly up-regulated with RA in primary T lymphocytes,as well as in PHA-activated T lymphocytes.RPN2 over-expression in T lymphocytes significantly inhibited apoptosis and promoted proliferation and activation.PBMCs-expressed RPN2 mRNA and plasma Rpn2 protein demonstrated superior and modest performances in discriminating RA cases and controls,respectively(P<0.05).ConclusionsRPN2 gene influences T lymphocyte growth and activation and is involved in the pathogenesis of RA.Rpn2 may serve as a novel biomarker for RA diagnosis.