The association between expression of IFIT1 in podocytes of MRL/lpr mice and the renal pathological changes it causes: An animal study

Mitochondrial Lon protease promotes CD4+ T cell activation by activating the cGAS-STING-TBK1 axis in systemic lupus erythematosus

Systemic lupus erythematosus (SLE) is an autoimmune disease in which autoreactive CD4+ T cells play an essential role. We extracted CD4+ T cells from SLE-prone Fcgr2b-/- mice to elaborate the mechanism of mitochondrial Lon protease in CD4+ T cell activation in SLE. Transcriptome sequencing was performed in SLE-prone Fcgr2b-/- mice, and the stimulator of interferon gene (STING) related to SLE was obtained. It was demonstrated that STING expression was elevated in CD4+ T cells in SLE-prone Fcgr2b-/- mice. The downstream genes and pathways of STING were predicted by GO and KEGG approaches. The data indicated that STING regulated IFN signaling to promote CD4+ T cell activation in SLE-prone Fcgr2b-/- mice. Next, the interaction of cGAS, STING, TBK1, and IFN-I was verified by Co-IP assay. Moreover, the roles of cGAS, STING, and TBK1 in activating CD4+ T cells from SLE-prone Fcgr2b-/- mice were evaluated using gain- or loss-of-function experiments. Mechanistically, cGAS upregulated the IFN-I signaling pathway by directly interacting with STING and TBK1, contributing to CD4+ T cell activation. Besides, cytosolic mtDNA could activate CD4+ T cell activation in SLE-prone Fcgr2b-/- mice by upregulating the cGAS-STING-TBK1 axis. The function of mitochondrial Lon protease in oxidative damage and mtDNA release in CD4+ T cells of SLE-prone Fcgr2b-/- mice were explored. Mitochondrial Lon protease enhanced mtDNA release into the cytoplasm under oxidative stress. Collectively, our work indicates that mitochondrial Lon protease enhances CD4+ T cell activation by inducing mtDNA leakage and offers new candidate targets for developing diagnostic and therapeutic strategies.

Clinical Values of the Identified Hub Genes in Systemic Lupus Erythematosus

Objective

This study was conducted to identify the biomarkers and mechanisms associated with systemic lupus erythematosus(SLE) at a transcriptome level.

Methods

Microarray datasets were downloaded, and differentially expressed genes (DEGs) were identified. Enrichment and protein-protein interaction networks were analyzed, and hub genes were discovered. The levels of top 10 hub genes were validated by another dataset. The diagnostic accuracy of the hub genes was evaluated with the area under the curve of the receiver operating characteristic curve (ROC-AUC). The odds ratios (OR) and 95% confidence intervals (CI) of the relationship between clinical manifestations and hub genes were estimated with multivariable logistic regression. The relationships between the expression levels of the 10 identified hub genes and SLEDAI scores were subjected to linear correlation analysis. Changes in the expression levels of the hub genes during patient follow-up were examined through one-way repeated measures ANOVA.

Results

A total of 136 DEGs were identified. Enrichment analysis indicated that DEGs were primarily enriched in type I interferon-associated pathways. The identified hub genes were verified by the GSE65391 dataset. The 10 hub genes had good diagnostic performances. Seven (except IFI6, OAS1 and IFIT3) of the 10 hub genes were positively associated with SLEDAI. The combination models of IFIT3, ISG15, MX2, and IFIH1 were effective in diagnosing mucosal ulcers among patients with SLE. The expression levels of IRF7, IFI35, IFIT3, and ISG15 decreased compared with the baseline expression (not significantly).

Conclusions

In this work, the clinical values of the identified hub genes in SLE were demonstrated.

Identification of key biomarkers and immune infiltration in systemic lupus erythematosus by integrated bioinformatics analysis

Background

Systemic lupus erythematosus (SLE) is a multisystemic, chronic inflammatory disease characterized by destructive systemic organ involvement, which could cause the decreased functional capacity, increased morbidity and mortality. Previous studies show that SLE is characterized by autoimmune, inflammatory processes, and tissue destruction. Some seriously-ill patients could develop into lupus nephritis. However, the cause and underlying molecular events of SLE needs to be further resolved.

Methods

The expression profiles of GSE144390, GSE4588, GSE50772 and GSE81622 were downloaded from the Gene Expression Omnibus (GEO) database to obtain differentially expressed genes (DEGs) between SLE and healthy samples. The gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichments of DEGs were performed by metascape etc. online analyses. The protein–protein interaction (PPI) networks of the DEGs were constructed by GENEMANIA software. We performed Gene Set Enrichment Analysis (GSEA) to further understand the functions of the hub gene, Weighted gene co‐expression network analysis (WGCNA) would be utilized to build a gene co‐expression network, and the most significant module and hub genes was identified. CIBERSORT tools have facilitated the analysis of immune cell infiltration patterns of diseases. The receiver operating characteristic (ROC) analyses were conducted to explore the value of DEGs for SLE diagnosis.

Results

In total, 6 DEGs (IFI27, IFI44, IFI44L, IFI6, EPSTI1 and OAS1) were screened, Biological functions analysis identified key related pathways, gene modules and co‐expression networks in SLE. IFI27 may be closely correlated with the occurrence of SLE. We found that an increased infiltration of moncytes, while NK cells resting infiltrated less may be related to the occurrence of SLE.

Conclusion

IFI27 may be closely related pathogenesis of SLE, and represents a new candidate molecular marker of the occurrence and progression of SLE. Moreover immune cell infiltration plays important role in the progession of SLE.

Potential protein biomarkers for systemic lupus erythematosus determined by bioinformatics analysis

Systemic lupus erythematosus (SLE) is a heterogeneous autoimmune disorder, and its pathogenesis in males and in cases without accompanying lupus nephritis (LN^-) is not fully understood. In this study, we identified 90 (82 up- and 8 downregulated) differentially expressed genes (DEGs) common to female LN^-, female LN⁺ and male LN⁺ using the GSE65391 and GSE49454 gene expression datasets from Gene Expression Omnibus database (GEO). The protein-protein interaction (PPI) network of 70 DEGs was constructed using STRING and cytoscape, and the Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis showed that the PPI network was significantly enriched in defense response to virus, cytosol, protein binding and measles. Sixteen hubgenes were identified from this PPI network, and Literature Mining Gene Networks molecular of GenCLiP 2.0 showed strong interaction between STAT1, DDX58 and IFIT1. Enrichment analysis of hubgenes in published literature showed the involvement of immune response and interferon-related genes in the pathogenesis of SLE. In addition, the transcription factors STAT1 & 2 and IRF6 & 9 had high Normalized Enrichment Score (NES). The 70 DEGs with PPI network and 16 hubgenes are potential biomarkers of SLE, and can help improve diagnosis and develop individualized therapies.

[Research advances in the protective effect of all-trans retinoic acid against podocyte injury]

All-trans retinoic acid (ATRA) is a vitamin A derivative and plays an important role in the regulation of cell aggregation, differentiation, apoptosis, proliferation, and inflammatory response. In recent years, some progress has been made in the role of ATRA in renal diseases, especially its protective effect on podocytes. This article reviews the research advances in podocyte injury, characteristics of ATRA, podocyte differentiation and regeneration induced by ATRA, and the protective effect of ATRA against proliferation, deposition of fibers, and apoptosis.