Journal Article

IFI44 is an immune evasion biomarker for SARS-CoV-2 and Staphylococcus aureus infection in patients with RA

Lin, Rongjie, Zheng, Qingcong, Wang, Wanming, Lv, Qi, Wang, Du

2022

Overview

BackgroundSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused a global pandemic of severe coronavirus disease 2019 (COVID-19). Staphylococcus aureus is one of the most common pathogenic bacteria in humans, rheumatoid arthritis (RA) is among the most prevalent autoimmune conditions. RA is a significant risk factor for SARS-CoV-2 and S. aureus infections, although the mechanism of RA and SARS-CoV-2 infection in conjunction with S. aureus infection has not been elucidated. The purpose of this study is to investigate the biomarkers and disease targets between RA and SARS-CoV-2 and S. aureus infections using bioinformatics analysis, to search for the molecular mechanisms of SARS-CoV-2 and S. aureus immune escape and potential drug targets in the RA population, and to provide new directions for further analysis and targeted development of clinical treatments.MethodsThe RA dataset (GSE93272) and the S. aureus bacteremia (SAB) dataset (GSE33341) were used to obtain differentially expressed gene sets, respectively, and the common differentially expressed genes (DEGs) were determined through the intersection. Functional enrichment analysis utilizing GO, KEGG, and ClueGO methods. The PPI network was created utilizing the STRING database, and the top 10 hub genes were identified and further examined for functional enrichment using Metascape and GeneMANIA. The top 10 hub genes were intersected with the SARS-CoV-2 gene pool to identify five hub genes shared by RA, COVID-19, and SAB, and functional enrichment analysis was conducted using Metascape and GeneMANIA. Using the NetworkAnalyst platform, TF-hub gene and miRNA-hub gene networks were built for these five hub genes. The hub gene was verified utilizing GSE17755, GSE55235, and GSE13670, and its effectiveness was assessed utilizing ROC curves. CIBERSORT was applied to examine immune cell infiltration and the link between the hub gene and immune cells.ResultsA total of 199 DEGs were extracted from the GSE93272 and GSE33341 datasets. KEGG analysis of enrichment pathways were NLR signaling pathway, cell membrane DNA sensing pathway, oxidative phosphorylation, and viral infection. Positive/negative regulation of the immune system, regulation of the interferon-I (IFN-I; IFN-α/β) pathway, and associated pathways of the immunological response to viruses were enriched in GO and ClueGO analyses. PPI network and Cytoscape platform identified the top 10 hub genes: RSAD2, IFIT3, GBP1, RTP4, IFI44, OAS1, IFI44L, ISG15, HERC5, and IFIT5. The pathways are mainly enriched in response to viral and bacterial infection, IFN signaling, and 1,25-dihydroxy vitamin D3. IFI44, OAS1, IFI44L, ISG15, and HERC5 are the five hub genes shared by RA, COVID-19, and SAB. The pathways are primarily enriched for response to viral and bacterial infections. The TF-hub gene network and miRNA-hub gene network identified YY1 as a key TF and hsa-mir-1-3p and hsa-mir-146a-5p as two important miRNAs related to IFI44. IFI44 was identified as a hub gene by validating GSE17755, GSE55235, and GSE13670. Immune cell infiltration analysis showed a strong positive correlation between activated dendritic cells and IFI44 expression.ConclusionsIFI144 was discovered as a shared biomarker and disease target for RA, COVID-19, and SAB by this study. IFI44 negatively regulates the IFN signaling pathway to promote viral replication and bacterial proliferation and is an important molecular target for SARS-CoV-2 and S. aureus immune escape in RA. Dendritic cells play an important role in this process. 1,25-Dihydroxy vitamin D3 may be an important therapeutic agent in treating RA with SARS-CoV-2 and S. aureus infections.

• Publisher: Frontiers Media SA,Frontiers Media S.A
• Subject: Autoimmune diseases / Bacteremia / Bacterial infections / Bioinformatics / Biomarkers / Cell membranes / Cohort analysis / Coronaviruses / COVID-19 / Datasets / Dendritic cells / Disease / Gene pool / Gene set enrichment analysis / Genes / Health care / IFI44 / Immune evasion / Immune system / Immunology / Infiltration / Joint replacement surgery / Machine learning / Microorganisms / miRNA / Molecular modelling / Mortality / Oxidative phosphorylation / Pandemics / Phosphorylation / Public health / Rheumatoid arthritis / Risk factors / SARS-CoV-2 / Severe acute respiratory syndrome coronavirus 2 / Signal transduction / Staphylococcus aureus / Staphylococcus infections / Streptococcus infections / Therapeutic targets / Vitamin D3 / α-Interferon