Introduction: Despite growing evidence that large intergenic noncoding RNAs (lincRNAs) can regulate gene expression and widely take part in normal physiological and disease conditions, our knowledge of systemic lupus erythematosus (SLE)-related lincRNAs remains limited. The aim of this study was to detect the levels of four lincRNAs (ENST00000500949: linc0949, ENST00000500597: linc0597, ENST00000501992: linc1992, and ENST00000523995: linc3995) involved in innate immunity in the peripheral blood mononuclear cells (PBMCs) of patients with SLE and correlate these lincRNA levels with disease activity, organ damage, clinical features and medical therapies. Methods: PBMCs were obtained from 102 patients with SLE, 54 patients with rheumatoid arthritis (RA) and 76 healthy donors. lincRNA expression levels were measured by real-time quantitative polymerase chain reaction. Disease activity was assessed using the Systemic Lupus Erythematosus Disease Activity Index 2000 (SLEDAI-2K) scores, and organ damage was evaluated with the Systemic Lupus International Collaborating Clinics/American College of Rheumatology Damage Index. Results: linc0949 and linc0597 were significantly decreased in patients with SLE compared with patients with RA and healthy control subjects. linc0949 was correlated with SLEDAI-2K score (r = −0.329, P = 0.0007), as well as with complement component C3 level (r = 0.348, P = 0.0003). The level of linc0949 was also reduced in patients with SLE who had the presence of cumulative organ damage. In addition, decreasing expression of linc0949 was associated with lupus nephritis. linc0949 expression significantly increased after treatment, whereas neither disease activity nor organ damage correlated with linc0597 expression. Conclusions: Our results provide novel empirical evidence that linc0949 could be a potential biomarker for diagnosis, disease activity and therapeutic response in SLE.

Objective: Systemic lupus erythematosus (SLE) is a disease characterised by immune inflammation and damage to multiple organs. Recent investigations have linked competing endogenous RNAs (ceRNAs) to lupus. However, the exact mechanism through which the ceRNAs network affects SLE is still unclear. This study aims to investigate the regulatory functions of the ceRNAs network, which are important pathways that control the pathophysiological processes of SLE.Methods: CircRNA microarray for our tested assays were derived from bone marrow samples from three healthy individuals and three SLE patients in our hospital. The other sequencing data of circRNA, miRNA and mRNA were obtained from Gene Expression Omnibus (GEO) datasets. Using the limma package of R program, the differential expression of mRNA and miRNA in the GEO database was discovered. Then predicted miRNA-mRNA and circRNA-miRNA were established using miRMap, miRanda, miRDB, TargetScan, and miTarBase. CircRNA-miRNA-mRNA ceRNA network was constructed using Cytoscape, and hub genes were screened using a protein-protein interaction network. Immune infiltration analysis of the hub gene was also performed by CIBERSORT and GSEA.Results: 230 overlapped circRNAs, 86 DEmiRNAs and 2083 DEmRNAs were identified in SLE patients as compared to healthy controls. We constructed a circRNA–miRNA–mRNA ceRNAs network contained 11 overlapped circRNAs, 9 miRNAs and 51 mRNAs. ESR1 and SIRT1 were the most frequently associated protein-protein interactions in the PPI network. KEGG analysis showed that DEGs was enriched in FoxO signaling pathway as well as lipids and atherosclerosis. We constructed a novel circRNA-miRNA-mRNA ceRNA network (HSA circ 0000345- HSA miR-22-3-P-ESR1/SIRT1) that may have a major impact on SLE.Conclusion: Through this bioinformatics and integrated analysis, we suggest a regulatory role for ceRNA network in the pathogenesis and treatment of SLE.

Introduction: The molecular mechanism of systemic sclerosis (SSc) remains unclear. Ferroptosis participates in a series of cell activities, such as inflammatory progression, by regulating cell death; unfortunately, there aren’t many research that discuss the connection between ferroptosis and SSc. Objectives: This study used bioinformatics analysis to report a potential relationship between ferroptosis and SSc. Methods: The SSc and control datasets GSE125362 and GSE76807 were obtained from the gene expression omnibus database. The differentially expressed genes (DEGs) were identified using the R software. By the Venn diagram, ferroptosis DEGs were detected. The chosen candidate genes were then subjected to analyses of protein-protein interactions, gene ontology enrichment, and Kyoto Encyclopedia of Genes and Genomes pathway enrichment. With the Molecular Complex Detection plugin program, the hub genes were investigated. A multifactor regulatory network was constructed depending on key hub genes, and immune infiltration was also evaluated. Finally, quantitative real-time polymerase chain reaction (RT-PCR) and enzyme linked immunosorbent assay were used to validate the bioinformatic results. Results: Twenty-four ferroptosis-related differentially expressed genes were detected in patients with SSc versus the normal controls. The biological processes of FRGs in patients with SSc focused on the negative regulation of cell proliferation and inflammatory response. The signaling pathways were enriched in necroptosis. The core genes of SSc were CYBB, IL-6, NOX4,TLR4, CXCL2, JUN, and LY96. Three miRNAs, two lncRNAs, and five transcription factors were predicted. The evaluation of immune infiltration showed that the number of activated natural killer (NK) cells increased in SSc skin tissues, whereas the number of resting dendritic, NK, and mast cells decreased. The bioinformatics prediction results from the mRNA chip were in line with the expression levels of IL-6 and CYBB. Conclusions: Necroptosis and ferroptosis were upregulated in patients with SSc and involved in modulating cell proliferation, differentiation, and migration. IL-6 and CYBB are key ferroptosis-related genes in SSc. Ferroptosis and related genes might be promising targets in the treatment of SSc.

Systemic lupus erythematosus (SLE) patients are at greater risk of developing osteoporosis (OP) than the general population. This study aimed to identify crosstalk genes between SLE and OP and to validate their diagnostic accuracy as biomarkers. Data analysis based on Gene Expression Omnibus (GEO) datasets was conducted. We utilized Weighted Gene Co-Expression Network Analysis (WGCNA) and differential expression analysis to identify crosstalk genes (CGs). Machine learning algorithms and consensus clustering were applied to screen shared diagnostic biomarkers and construct two predictive models featuring key genes. We also investigated potential subgroups, immune infiltration across different subtypes, and validated hub mRNAs using quantitative real-time PCR (qPCR). Molecular docking was performed to simulate the interaction of a small molecule compound with its target. We identified 19 CGs and developed two predictive models: the IL1R2-GADD45B and CHI3L1-IL1R2-SPTLC2 diagnostic score thresholds. The CHI3L1-IL1R2-SPTLC2 model showed improved predictive accuracy for lupus-associated osteoporosis. The C2 subtype was found to potentially regulate bone metabolism in SLE patients. Immune infiltration analysis indicated a strong association between CGs and multiple immunocytes, with IL1R2 being a common element in both models. Molecular docking suggests that Anakinra’s therapeutic effect may involve IL1R2. Our study introduces novel diagnostic biomarkers and predictive models for lupus-associated osteoporosis, with a particular focus on IL1R2 as an innovative biomarker and therapeutic target. These are anticipated to aid early screening and risk assessment in SLE patients, pending large-scale clinical validation.

Full Papers; Authors: Z. Chen, Y. Dai, Y. Lai, F. Gao, Y. Wu

Background: Lupus nephritis (LN) is a severe complication of systemic lupus erythematosus. Mitochondrial dysfunction and inflammation are key contributors to its pathogenesis, yet the underlying mechanisms remain incompletely understood and reliable biomarkers are limited. This study investigates mitochondrial-related genes (MRGs) in LN and evaluates their potential as biomarkers. Methods: Differentially expressed genes (DEGs) were obtained from the Gene Expression Omnibus database and MRGs were derived from the MitoCarta3.0 dataset. Weighted gene co-expression network analysis identified key modules, followed by Gene Ontology and Kyoto Encyclopaedia of Genes and Genomes enrichment analyses of mitochondrial DEGs (MitoDEGs). Protein-protein interaction network analysis and random forest modelling were applied to identify hub MitoDEGs. Their diagnostic performance was evaluated using receiver operating characteristic curves. Immune cell infiltration was estimated using single-sample gene set enrichment analysis and correlations with hub MitoDEGs were analysed. Immunofluorescence staining and functional assays in HK-2 cells were performed to validate the expression and biological roles of the hub genes. Results: Among the 36 MitoDEGs, synthesis of cytochrome c oxidase 1 (SCO1) was identified. SCO1 exhibited strong discriminatory power in both the training and validation sets. After false discovery rate correction, SCO1 showed significant positive correlations with CD8+T cells, naive CD4+T cells and resting memory CD4+T cells. Immunofluorescence staining confirmed that SCO1 was predominantly expressed in renal tubules and was significantly upregulated in patients with LN compared with healthy controls. Functional validation demonstrated that SCO1 overexpression enhanced cell viability, whereas its knockdown reduced cell viability, increased mitochondrial reactive oxygen apecies and decreased mitochondrial membrane potential, without affecting ATP levels. SCO1 modulation altered P62 expression but did not significantly affect PARKIN, PINK1, or LC3B levels. Conclusion: SCO1 showed elevated expression in renal tubules and strong discriminatory ability. It may help preserve tubular cell viability and mitochondrial homeostasis under inflammatory stress, highlighting its potential as a diagnostic biomarker and a candidate for further mechanistic investigation in LN.