Immune profile alterations of systemic lupus erythematosus patients with infections.

This study aimed to elucidate the immune status of systemic lupus erythematosus (SLE) patients with infections. We enrolled 253 SLE patients including 77 patients with infections. Clinical features and immunological parameters were analyzed, with particular reference to neutrophil CD64 (nCD64) expression, myeloid-derived suppressor cells (MDSCs), activated T cells and multiple cytokines. Among the 77 SLE patients with infections, 32 patients (41.56%) developed fever and 20 patients (25.97%) developed serositis, which were higher compared to the non-infection group. A considerably higher level of nCD64 was found in the infection group (4.65 vs 1.01, P < 0.001). In addition, the infection group exhibited higher percentages of total MDSCs (6.99 vs 4.30%, P = 0.003), polymorphonuclear MDSCs (PMN-MDSCs) (P = 0.032) and monocytic MDSCs (M-MDSCs) (P = 0.015). T cells were more activated during infections, with an elevated level of IL-2R (P < 0.001). Specifically, higher percentages of CD4+CD38+ T cells (55.73 vs 50.17%, P = 0.036), CD8+HLA-DR+ T cells (59.82 vs 47.99%, P < 0.001) and CD8+CD38+ T cells (68.59 vs 63.90%, P = 0.044) were identified in the infection group. Furthermore, the serum levels of IL-6, IL-8 and IL-10 were elevated in the infection group (all P < 0.001). Higher proportions of neutrophils, CD4+ and CD8+ T cells, and MDSCs were activated during infections in SLE patients. Additionally, the serum cytokines altered during infections, with noticeably elevated levels of IL-6, IL-8 and IL-10. Infections may lead to the amplification of immune alterations in SLE.

Bulk RNA Sequencing With Integrated Single-Cell RNA Sequencing Identifies BCL2A1 as a Potential Diagnostic and Prognostic Biomarker for Sepsis.

Background: Sepsis is one of the leading causes of morbidity and mortality worldwide in the intensive care unit (ICU). The prognosis of the disease strongly depends on rapid diagnosis and appropriate treatment. Thus, some new and accurate sepsis-related biomarkers are pressing needed and their efficiency should be carefully demonstrated. Methods: Differential expression analysis and weighted gene co-expression network analysis (WGCNA) were applied to detect sepsis and monocyte/macrophage-related genes. Least absolute shrinkage and selection operator (LASSO) and random forest regression analyses were used in combination to screen out prognostic genes. Single-cell RNA sequence profiling was utilized to further verify the expression of these genes on a single cell level. Receiver operating characteristic (ROC) curve and decision curve analysis (DCA) were also applied to verify the diagnostic value of the target biomarkers. Results: The intersections of the genes detected by differential expression and WGCNA analyses identified 141 overlapping candidate genes that were closely related to sepsis and macrophages. The LASSO and random forest regression analyses further screened out 17 prognostic genes. Single-cell RNA sequencing analysis detected that FCGR1A and BCL2A1 might be potential biomarkers for sepsis diagnosis and the diagnostic efficacy of BCL2A1 was further validated by ROC curve and DCA. Conclusions: It was revealed that BCL2A1 had good diagnostic and prognostic value for sepsis, and that it can be applied as a potential and novel biomarker for the management of the disease.