Identifying circRNA-associated-ceRNA networks in juvenile spondyloarthropathies patients

BACKGROUND

Juvenile spondyloarthropathies (JSpA) are defined as a heterogeneous group of diseases that start before the age of 16. The study aimed to identify key genes and pathways that are influenced by circRNAs and to screen potential therapeutic agents for JSpA. The study involved the analysis of circRNA expression profiles, identification of circRNA-miRNA-mRNA regulatory networks, and functional annotation of differentially expressed genes. The results of the study may have provided insights into the molecular mechanisms underlying JSpA and potential therapeutic targets for this disease.

METHODS

In this study, sequencing data of circRNA, miRNA, and mRNA were obtained from the GEO datasets. The data were then analyzed to identify candidates for constructing a circRNA-miRNA-mRNA network based on circRNA-miRNA interactions and miRNA-mRNA interactions. Functional enrichments of genes were performed using the DAVID database. A PPI network was constructed using the STRING database and visualized using Cytoscape software. The MCODE plugin app was used to explore hub genes in the PPI network. The expression changes in immune cells were assessed using the online CIBERSORT algorithm to obtain the proportion of various types of immune cells. Finally, the Connectivity Map L1000 platform was used to identify potential agents for JSpA treatment. Overall, this study aimed to provide a comprehensive understanding of the molecular mechanisms underlying JSpA and to identify potential therapeutic agents for this disease.

RESULTS

A total of 225 differentially expressed circRNAs (DEcircRNAs), 23 differentially expressed miRNAs (DEmiRNAs) and 1324 differentially expressed mRNAs (DEmRNAs) were identified. We integrated 5 overlapped circRNAs, 7 miRNAs and 299 target mRNAs into a circRNA-miRNA-mRNA network. We next identified 10 hub genes based on the PPI network. KEGG pathway analysis revealed that the DEGs were mainly associated with JAK-STAT signal pathway. We found that neutrophils accounted for the majority of all enriched cells. In addition, we discovered several chemicals as potential treatment options for JSpA.

CONCLUSIONS

Through this bioinformatics analysis, we suggest a regulatory role for circRNAs in the pathogenesis and treatment of JSpA from the view of a competitive endogenous RNA (ceRNA) network.

Glomerular Expression of S100A8 in Lupus Nephritis: An Integrated Bioinformatics Analysis

Introduction

Lupus nephritis (LN) is a major risk factor of morbidity and mortality. Glomerular injury is associated with different pathogeneses and clinical presentations in LN patients. However, the molecular mechanisms involved are not well understood. This study aimed to explore the molecular characteristics and mechanisms of this disease using bioinformatics analysis.

Methods

To characterize glomeruli in LN, microarray datasets GSE113342 and GSE32591 were downloaded from the Gene Expression Omnibus database and analyzed to determine the differentially expressed genes (DEGs) between LN glomeruli and normal glomeruli. Functional enrichment analyses and protein–protein interaction network analyses were then performed. Module analysis was performed using the Search Tool for the Retrieval of Interacting Genes/Proteins and Cytoscape software. Immunofluorescence staining was performed to identify the glomerular expression of S100A8 in various International Society of Nephrology/Renal Pathology Society (ISN/RPS) class LN patients. The image of each glomerulus was acquired using a digital imaging system, and the green fluorescence intensity was quantified using Image-Pro Plus software.

Results

A total of 13 DEGs, consisting of 12 downregulated genes and one upregulated gene (S100A8), were identified in the microarray datasets. The functions and pathways associated with the DEGs mainly include inflammatory response, innate immune response, neutrophil chemotaxis, leukocyte migration, cell adhesion, cell–cell signaling, and infection. We also found that monocytes and activated natural killer cells were upregulated in both GSE113342 and GSE32591. Glomerular S100A8 staining was significantly enhanced compared to that in the controls, especially in class IV.

Conclusions

The DEGs identified in the present study help us understand the underlying molecular mechanisms of LN. Our results show that glomerular S100A8 expression varies in different pathological types; however, further research is required to confirm the role of S100A8 in LN.

Antiphospholipid antibodies and osteonecrosis in systemic lupus erythematosus: a meta-analysis

Objectives: The present meta-analysis aimed to assess the relationship between antiphospholipid antibodies (aPLs) or antiphospholipid antibody syndrome (APS) and the incidence of osteonecrosis (ON) in systemic lupus erythematosus (SLE) patients.Methods: MEDLINE/Pubmed, EMBASE, Web of science, the Chinese Biomedical Literature Database (CBM), the Wan-Fang Database, and the China National Knowledge Infrastructure (CNKI) were searched from their inception up until 26 December 2020. Studies in English were included. Case-control studies and cohort studies were included. Studies pertaining to the link between aPLs or APS and ON patients were slated for inclusion in the current analysis.Results: Twenty-two studies involving a total of 3054 SLE patients were included. The positivities of anticardiolipin antibody (ACL), IgG ACL, IgM ACL, LA and APS in SLE is not associated with ON. One study showed that IgG or IgM β2GP1 had no association with ON. No publication bias was detected. The quality of this evidence was low because of the high risk of bias across studies, and therefore robust inferences cannot be made.Conclusion: SLE patients demonstrated a weak association between aPLs and ON. The nature of the association between aPLs and ON in SLE needs to be investigated in-depth in future research.