Identification of potential ferroptosis-associated biomarkers in rheumatoid arthritis.

Rheumatoid arthritis (RA) is a chronic autoimmune disorder characterized by inflammation and gradual joint degeneration, resulting in function disability. Recently, ferroptosis, a novel form of regulated cell death that involves iron-dependent lipid peroxidation, has been implicated in the pathogenesis of RA. However, the underlying molecular mechanisms and key genes involved in ferroptosis in RA remain largely unknown. The GSE134420 and GSE77298 datasets were downloaded and DEGs were identified using R software. The DEGs were then mapped to the dataset of 619 ferroptosis-related genes obtained from the GeneCards database. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were conducted to investigate the possible biological functions. Protein-protein interaction (PPI) networks were constructed to identify the hub genes. The relationship between hub genes and immune infiltration was estimated using the CIBERSORT algorithms. Gene Set Enrichment Analysis (GSEA) was used to explore the underlying signaling pathways of hub genes. Genome-wide association studies (GWAS) analysis was performed to confirm the pathogenic regions of the hub genes. RcisTarget and Gene-motif ranking databases were used to identify transcription factors (TFs) associated with the hub genes. The miRcode databases were utilized to construct the microRNA (miRNA)-messenger RNA (mRNA) network. Single-cell analysis was utilized to cluster cells and display the expression of hub genes in cell clusters. Finally, the expression and potential mechanism of hub genes were investigated in human and experimental samples. Three hub genes PTGS2, ENO1, and GRN highly associated with ferroptosis were identified. Four pathogenic genes HLA-B, MIF, PSTPIP, TLR1 were identified that were significantly and positively correlated with the expression levels of hub genes. The results of the GSEA showed that the hub genes were significantly enriched in pathways related to immunity, lysosome, phagocytosis and infection. ENO1 and PTGS2 were enriched in the TF-binding motif of cisbp_M5493. The hub genes were validated in experimental and patient samples and highly level of ENO1 expression was found to inhibit ACO1, which reduces ferroptosis in proliferating fibroblast-like synoviocytes (FLS). PTGS2, ENO1 and GRN were identified and validated as potential ferroptosis-related biomarkers. Our work first revealed that ENO1 is highly expressed in RA synovium and that ferroptosis may be regulated by the ENO1-ACO1 axis, advancing the understanding of the underlying ferroptosis-related mechanisms of synovial proliferation and providing potential diagnostic and therapeutic targets for RA.

He X ，Zhang J ，Gong M ，Gu Y ，Dong B ，Pang X ，Zhang C ，Cui Y ... -  《Frontiers in Immunology》

Quercetin is a Potential Therapy for Rheumatoid Arthritis via Targeting Caspase-8 Through Ferroptosis and Pyroptosis.

Zheng Q ，Wang D ，Lin R ，Chen Y ，Xu Z ，Xu W ... -  《Journal of Inflammation Research》

Three hematologic/immune system-specific expressed genes are considered as the potential biomarkers for the diagnosis of early rheumatoid arthritis through bioinformatics analysis.

Cheng Q ，Chen X ，Wu H ，Du Y ... -  《Journal of Translational Medicine》

Identification of potential ferroptosis key genes and immune infiltration in rheumatoid arthritis by integrated bioinformatics analysis.

Ferroptosis is of vital importance in the development of Rheumatoid arthritis (RA). The purpose of this project is to clarify the potential ferroptosis-related genes, pathways, and immune infiltration in RA by bioinformatics analysis. We acquired ferroptosis-related genes (FRGs) from Ferroptosis database (FerrDb). We obtained the Gene dataset of RA (GSE55235) from the Gene Expression Omnibus (GEO) Database, screened the differentially expressed genes (DEGs) in RA and control samples, and then took the intersection of it and FRGs. Aiming to construct the protein-protein interaction (PPI) networks of the FRGs-DEGs, STRING database and Cytoscape software 3.7.0 would be used. Furthermore, hub genes were identified by CytoNCA, a Cytoscape plug-in. The gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment of FRGs-DEGs were performed. We identified 34 FRGs-DEGs, including 7 upregulated and 27 downregulated genes by taking the intersection of the FRGs and DEGs. PPI analysis identified a total of 3 hub genes(VEGFA, PTGS2, and JUN). GO enrichment analyses and KEGG Pathway enrichment displayed that the FRGs-DEGs are involved in the response to oxidative stress and corticosteroid, heme binding, FoxO-signal pathway. Results of immune infiltration displayed that increased infiltration of T cells, while Macrophages M2 less may be related to the occurrence of RA. The hub genes involved in ferroptosis in RA may be VEGFA, PTGS2, and JUN, which are mainly involved in FoxO-signal pathway. T cell, Mac, and plasma cells may be involved in the regulation of RA-joints-synovial-inflammation.

Fan Y ，Li Y ，Fu X ，Peng J ，Chen Y ，Chen T ，Zhang D ... -  《Heliyon》

Identification of hub genes in rheumatoid arthritis through an integrated bioinformatics approach.

Rheumatoid arthritis (RA) is a common chronic autoimmune disease characterized by inflammation of the synovial membrane. However, the etiology and underlying molecular events of RA are unclear. Here, we applied bioinformatics analysis to identify the key genes involved in RA. GSE77298 was downloaded from the Gene Expression Omnibus (GEO) database. We used the R software screen the differentially expressed genes (DEGs). Gene ontology enrichment analysis and Kyoto Encyclopedia of Genes and Genomes pathway were analyzed by using the DAVID online tool. The STRING database was used to analyze the interaction of differentially encoded proteins. PPI interaction network was divided into subnetworks using MCODE algorithm and was analyzed using Cytoscape. Gene set enrichment analysis (GSEA) was performed to identify relevant biological functions. qRT-PCR analysis was also performed to verify the expression of identified hub DEGs. A total of 4062 differentially expressed genes were selected, including 1847 upregulated genes and 2215 downregulated genes. In the biological process, DEGs were mainly concentrated in the fields of muscle filament sliding, muscle contraction, intracellular signal transduction, cardiac muscle contraction, signal transduction, and skeletal muscle tissue development. In the cellular components, DEGs were mainly concentrated in the parts of cytosol, Z disk, membrane, extracellular exosome, mitochondrion, and M band. In molecular functions, DEGs were mainly concentrated in protein binding, structural constituent of muscle, actin binding, and actin filament binding. KEGG pathway analysis shows that DEGs mainly focuses on pathways about lysosome, Wnt/β-catenin signaling pathway, and NF-κB signaling pathway. CXCR3, GNB4, and CXCL16 were identified as the core genes that involved in the progression of RA. By qRT-PCR analysis, we found that CXCR3, GNB4, and CXCL16 were significantly upregulated in RA tissue as compared to healthy controls. In conclusion, DEGs and hub genes identified in the present study help us understand the molecular mechanisms underlying the progression of RA, and provide candidate targets for diagnosis and treatment of RA.

Wu R ，Long L ，Zhou Q ，Su J ，Su W ，Zhu J ... -  《Journal of Orthopaedic Surgery and Research》