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. 2022 Sep 15:13:1013322.
doi: 10.3389/fimmu.2022.1013322. eCollection 2022.

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

Qingcong Zheng  1 , Du Wang  2 , Rongjie Lin  1 , Qi Lv  1 , Wanming Wang  1
Affiliations

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

Qingcong Zheng et al. Front Immunol. .

Abstract

Background: Severe 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.

Methods: The 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.

Results: A 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.

Conclusions: IFI144 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.

Keywords: 1,25-dihydroxy vitamin D3; COVID-19; IFI44; Rheumatoid arthritis; SARS-CoV-2; Staphylococcus aureus; dendritic cells.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
The schematic block diagram of the entire workflow of this study.
Figure 2
Figure 2
DEGs identification. (A) Gray dots represent genes not substantially differently expressed in RA and HC groups (P > 0.05), red triangles represent upregulated genes (P < 0.05), and green triangles represent downregulated genes (P < 0.05) in the GSE93272 dataset. (B) Gray dots represent genes not substantially differently expressed in S. aureus and HC groups (P > 0.05), red triangles represent upregulated genes (P < 0.05), and green triangles represent downregulated genes (P < 0.05) in the GSE33341 dataset.
Figure 3
Figure 3
DEG distribution. (A) The clustering heat map shows the DEGs in the GSE93272 dataset. The RA group’s samples are colored blue, whereas the HC group’s samples are colored red. Red rectangles indicate elevated genes (P < 0.05), whereas blue rectangles indicate downregulated genes (P < 0.05). (B) The clustering heat map shows the intersection of DEGs in the GSE33341 dataset. The SA group’s samples are colored blue, whereas the HC group’s samples are colored red. Red rectangles indicate elevated genes (P < 0.05), whereas blue rectangles indicate downregulated genes (P < 0.05).
Figure 4
Figure 4
Common DEG screening. (A) Venn diagram on GSE93272 DEGs and GSE33341 DEGs. (B) Clustered heat map of common DEGs belonging to the RA group. (C) Clustered heat map of common DEGs in the SA group, with the RA/SA group colored blue and the HC group colored red. Red rectangles indicate elevated genes (P < 0.05), whereas blue rectangles indicate downregulated genes (P < 0.05).
Figure 5
Figure 5
Functional enrichment analysis: GO, KEGG, and ClueGO analysis of DEGs. (A) BP gene enrichment of DEGs. (B) CC gene enrichment of DEGs. (C) MF gene enrichment of DEGs. (D) Analysis of DEGs using KEGG. (E) Analysis of DEGs using ClueGO.
Figure 6
Figure 6
PPI interworking networks. (A) PPI network with 184 nodes and 750 edges. The green hexagon in the lower right corner is the top 10 hub genes derived using the CytoHubba analysis method. (B) Analysis of the top 10 hub genes with CytoHubba of Cytoscape.
Figure 7
Figure 7
Functional enrichment analysis: Metascape and GeneMANIA of top 10 hub genes. (A) Pathway and process richness analysis of the Metascape platform. (B) Summary of enrichment analysis of DisGeNET 13 on Metascape platform. (C) The network is visualized using Cytoscape 5, colored by cluster IDs, and nodes sharing the same cluster ID are usually close to each other. (D) The gene–gene interaction network of the top 10 hub genes with the 20 most adjacent genes was analyzed using the GeneMANIA database. Each node represents a gene. The color of the linkage of the nodes represents the linkage between the corresponding genes.
Figure 8
Figure 8
Identification of the hub gene between RA, COVID-19, and SAB. (A) Venn diagram of the top 10 hub genes and the SARS-CoV-2 gene set. (B, C) The expression of IFI44, OAS1, IFI44L, ISG15, and HERC5 in the GSE93272 and GSE33341 datasets was analyzed using split-face violin plots. Red indicates the RA group, yellow indicates the S. aureus group, and blue indicates the HC group.
Figure 9
Figure 9
Functional enrichment analysis: Metascape and GeneMANIA of five hub genes. (A) Pathway and process richness analysis of the Metascape platform. (B) Summary of enrichment analysis of DisGeNET 13 on Metascape platform. (C) The network is visualized using Cytoscape 5, colored by cluster IDs, and nodes sharing the same cluster ID are usually close to each other. (D) The gene–gene interaction network of the five hub genes with the 20 most adjacent genes was analyzed using the GeneMANIA database. Each node represents a gene. The color of the linkage of the nodes represents the linkage between the corresponding genes.
Figure 10
Figure 10
Construction of TF-hub gene and miRNA-hub gene network using NetworkAnalyst. (A, B) TF-hub gene network and simplified diagram. Red circles are genes, and yellow squares are TF. (C, D) miRNA-hub gene network (miRTarBase v8.0) and simplified diagram. (E, F) miRNA-hub gene network (TarBase v8.0) and simplified diagram. Circles are genes, and squares are miRNAs.
Figure 11
Figure 11
Screening for key genes. (A, B) Gray dots represent genes not substantially differently expressed in RA and HC groups (P > 0.05), red triangles represent upregulated genes (P < 0.05), and green triangles represent downregulated genes (P < 0.05) in GSE17755 and GSE55235 datasets. (C) Gray dots represent genes not substantially differently expressed in S. aureus and HC groups (P > 0.05), red triangles represent upregulated genes (P < 0.05), and green triangles represent downregulated genes (P < 0.05) in the GSE13670 dataset. (D) The Venn diagram of five hub genes with the three validation sets of DEGs.
Figure 12
Figure 12
Validation of key genes. (A–C) The expression of IFI44 in GSE17755, GSE55235, and GSE13670. Red for RA/S. aureus group, and cyan for HC group. (D–F) The AUC of the ROC curve verifies the diagnostic validity of IFI44 in GSE17755, GSE55235, and GSE13670 (P < 0.05).
Figure 13
Figure 13
Analysis of immune cell infiltration. (A) A histogram of the proportion of LM22 in RA samples is depicted using the CIBERSORT algorithm, with the horizontal coordinate representing the sample and the vertical coordinate representing the percentage of individual immune cells. (B) Comparison of immune infiltrating cells between the RA and HC groups; red represents RA and cyan represents HC. (C) Correlation matrix between immune cells within the RA group. The horizontal and vertical coordinates are LM22, with red representing positive correlations and blue representing negative correlations (*P < 0.05, ** P < 0.01, and *** P < 0.001). (D) Correlation analysis between the expression of IFI44 and LM22.
Figure 14
Figure 14
RA, SAB, and COVID-19 are often associated with vitamin D deficiency. This diagram shows that 1,25(OH)2VD3 is the common target drug for RA, SAB, COVID-19, IFI44, and dendritic cells.
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