Type I interferon pathway activation across the antiphospholipid syndrome spectrum: associations with disease subsets and systemic antiphospholipid syndrome presentation

Perspective on Renal Involvement in Antiphospholipid Syndrome: Implications for Diagnosis, Pathogenesis, and Treatment

Antiphospholipid syndrome (APS) can affect the kidneys, leading to renal artery and vein thrombosis, allograft loss following transplantation, and microvascular damage referred to as aPL-nephropathy (aPL-N). APL-N is a complex and frequently underdiagnosed condition characterized by an incomplete understanding of its etiopathogenesis and associated with unfavorable renal outcomes. The 2023 ACR/EULAR classification criteria for APS included aPL-N within the microvascular domain. The gold standard for aPL-N is the biopsy, revealing lesions associated with acute thrombotic microangiopathy and chronic vascular changes. Nevertheless, reluctance for biopsies due to anticoagulation and thrombocytopenia underscores the need for noninvasive diagnostics. Common clinical features include hypertension, microscopic hematuria, proteinuria, and renal insufficiency. Antiphospholipid antibodies seem crucial to kidney damage through thrombotic and inflammatory processes. Studies and experimental models of thrombotic microangiopathy lesions suggest the involvement of the complement cascade, tissue factor, and mammalian target of the rapamycin complex activation pathway. Currently, the management of aPL-N is based mainly on expert opinion, with limited evidence supporting the use of anticoagulants, leading to controversy in their application. Treatment may include heparin, intravenous immunoglobulin, plasma exchange, and targeted therapies tailored to aPL-N mechanisms. Future multicenter studies are essential to clarify their roles. The goal of this review is to inform clinicians and create a research agenda to address the unmet needs in diagnosing and managing APL-N.

Identification of mitochondrial function and programmed cell death associated key biomarkers and the circRNA-miRNA-mRNA regulatory network in systemic lupus erythematosus

Objectives

Systemic Lupus Erythematosus (SLE) is a highly heterogeneous autoimmune disease with complex pathogenic mechanisms. Mitochondrial function and programmed cell death (PCD) play important roles in SLE. This study aims to screen biomarkers related to mitochondrial function and programmed cell death in SLE and analyze their underlying mechanisms.

Methods

SLE-related databases were derived from the GEO database, where three SLE databases were merged into one database as the training set. Genes related to mitochondrial function and PCD were sourced from the MitoCarta 3.0 database. Key genes were identified through bioinformatics and machine learning, and their expression levels and diagnostic efficacy were validated using two SLE-related datasets as the validation set. The relationship between diagnostic genes and immune cells was analyzed through CIBERSORT immune infiltration analysis. Diagnostic genes-related miRNAs were predicted using online databases. Differential circRNAs were screened in SLE circRNA datasets, and the relationship between circRNAs and miRNAs is predicted through circbank, finally constructing a circRNA-miRNA-mRNA ceRNA regulatory network.

Results

From the 448 differential genes in the SLE training set, two key genes, IFI27 and LAMP3, were identified through machine learning and WGCNA. Enrichment analysis revealed that they were mainly enriched in pathways such as cell cycle, systemic lupus erythematosus, cytosolic DNA sensing pathway, toll-like receptor (TLR) signaling pathway and nod-like receptor (NLR) signaling pathway. Immune infiltration analysis found that compared with normal group, 11 immune cells were differentially expressed, with IFI27 related 9 types of immune cells and LAMP3 related 10 types of immune cells. The final constructed circRNA-miRNA-mRNA ceRNA regulatory network consists of 2 mRNAs, 5 miRNAs, and 4 circRNAs.

Conclusion

Our study ultimately identified two biomarkers (IFI27 and LAMP3) related to mitochondrial function and programmed cell death that play an important role in SLE. In the future, IFI27 and LAMP3 have the potential to become important biomarkers in the diagnosis and treatment of SLE. Their role in the immune response may provide new strategies for the treatment of SLE.

Interferon-stimulated gene IFI27 as a multifaceted candidate target in precision medicine

IFI27, an interferon (IFN)-stimulated gene, is emerging as a crucial player in immune responses across various species, with significant implications for precision medicine. Commonly found among the most upregulated genes in infections, cancers, as well as inflammatory and autoimmune disorders, IFI27 is ready to be trialed in clinical practice for certain indications, and holds promise as an immunomodulatory target. We hypothesize that IFI27 plays a dual role, typically supporting immune defense but sometimes contributing to disease progression, which might render it a putative biomarker for diagnosis, prognosis, and treatment response. We advocate for focused research on IFI27 to unlock its potential in precision medicine and to contribute to a unifying framework of its mechanisms in the immune response. Our viewpoint is supported by numerous studies highlighting IFI27's involvement across various conditions and the possibilities for clinical application.

Macrophage Infiltration Correlated with IFI16, EGR1 and MX1 Expression in Renal Tubular Epithelial Cells Within Lupus Nephritis-Associated Tubulointerstitial Injury via Bioinformatics Analysis

Objective

A comprehensive bioinformatics analysis was conducted to investigate potential new diagnostic biomarkers and immune infiltration characteristics associated with tubulointerstitial injury in lupus nephritis (LN), and to examine possible correlations between key genes and infiltrating immune cells.

Methods

The GSE32591, GSE113342, and GSE200306 datasets were downloaded from the Gene Expression Omnibus database and differentially expressed genes (DEGs) were identified in the pooled dataset. Support vector machine-recursive feature elimination analysis and the least absolute shrinkage and selection operator regression model were used to screen for possible markers, and the compositional patterns of the 22 types of immune cell fractions in LN were determined using CIBERSORT. Finally, Western blotting, quantitative real-time polymerase chain reaction, and multiple immunofluorescence methods were used to confirm the significance of these feature genes in MRL/lpr mice and patients with LN.

Results

Seventeen DEGs were identified, of which 11 were considerably upregulated and six were markedly downregulated. Kyoto Encyclopedia of Genes and Genomes pathway analysis revealed significant enrichment in pertussis, complement and coagulation cascades, systemic lupus erythematosus, and other pathways. Based on the machine learning results, we identified IFI16, EGR1 and MX1 were key diagnostic genes for tubulointerstitial injury associated with LN. Immune cell infiltration analysis revealed that IFI16, EGR1 and MX1 were associated with M1 macrophages. Finally, the association between IFI16, EGR1, MX1 and macrophages in MRL/lpr mice and patients with LN were verified.

Conclusion

This study suggests that IFI16, EGR1 and MX1 which are highly expressed in renal tubular epithelial cells in LN and are associated with macrophage infiltration, may be a novel diagnostic and therapeutic target.