BACKGROUND: To determine differences in the blood innate gene expression signatures of systemic lupus erythematosus (SLE) patients across various organ manifestations and disease activity, with a focus on lupus nephritis (LN) and central nervous system (CNS) involvement. METHODS: Toll-like receptor family (TLR 1-10) mRNA expression was investigated in peripheral blood mononuclear cells from patients with SLE (n = 74) and healthy controls (n = 34). We compared patients with histologically confirmed active LN or neuropsychiatric systemic lupus erythematosus (NPSLE) with patients without these symptoms. The expression of TLR mRNA was determined by RT‒qPCR using a high-throughput SmartChip Real-Time-qPCR system (WaferGen). Multivariate analysis and nonparametric statistics were used for data analysis to assess the associations between TLRs and disease activity and severity. RESULTS: TLR4 (0.044 vs. 0.081, p = 0.012) was upregulated and TLR10 (0.009 vs. 0.006, p = 0.0007) was downregulated in the whole cohort of SLE patients compared to healthy controls. A comparison of the active LN group with participants without kidney involvement revealed increased expression of TLR2 (0.078 vs. 0.03, p = 0.009), and TLR5 (0.035 vs. 0.017, p = 0.03). Moreover, a significant difference was observed in TLR9 expression between inactive LN and the control group (0.014 vs. 0.009, p = 0.01), together with borderline correlation in TLR2 expression (0.04 vs. 0.03, p = 0.06). Receiver operating characteristic (ROC) curve analysis revealed that TLR1 and TLR2 expression were the best potential diagnostic markers for active LN. The NPSLE group showed upregulation of TLR1 (0.088 vs. 0.048, p = 0.01), TLR4 (0.173 vs. 0.066, p = 0.0003) and TLR6 (0.087 vs. 0.036, 0.007). Our correlation analysis supported the close relationships among the expression of individual TLRs in the whole lupus cohort and its subgroups. CONCLUSION: Our study revealed differences in TLR expression between a lupus cohort and healthy controls. Additionally, our analysis provides insight into specific TLR expression in cases with severe organ manifestations, such as LN and NPSLE. The multiple mutual relationships of TLRs demonstrate the activation of innate immunity in SLE and suggest promising targets for future therapies or diagnostics.

• Keywords
• Disease activity, Innate immunity, Lupus nephritis, Systemic lupus erythematosus, Toll-like receptors,
• MeSH
• Adult MeSH
• Gene Expression MeSH
• Leukocytes, Mononuclear metabolism   MeSH
• Middle Aged MeSH
• Humans MeSH
• Young Adult MeSH
• Lupus Nephritis * genetics   blood   diagnosis   MeSH
• Lupus Erythematosus, Systemic * genetics   blood   MeSH
• Toll-Like Receptors * genetics   blood   biosynthesis   MeSH
• Lupus Vasculitis, Central Nervous System * genetics   blood   diagnosis   MeSH
• Check Tag
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Young Adult MeSH
• Male MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Names of Substances
• Toll-Like Receptors * MeSH

Analysing complex datasets while maintaining the interpretability and explainability of outcomes for clinicians and patients is challenging, not only in viral infections. These datasets often include a variety of heterogeneous clinical, demographic, laboratory, and personal data, and it is not a single factor but a combination of multiple factors that contribute to patient characterisation and host response. Therefore, multivariate approaches are needed to analyse these complex patient datasets, which are impossible to analyse with univariate comparisons (e.g., one immune cell subset versus one clinical factor). Using a SARS-CoV-2 infection as an example, we employed a patient similarity network (PSN) approach to assess the relationship between host immune factors and the clinical course of infection and performed visualisation and data interpretation. A PSN analysis of ~85 immunological (cellular and humoral) and ~70 clinical factors in 250 recruited patients with coronavirus disease (COVID-19) who were sampled four to eight weeks after a PCR-confirmed SARS-CoV-2 infection identified a minimal immune signature, as well as clinical and laboratory factors strongly associated with disease severity. Our study demonstrates the benefits of implementing multivariate network approaches to identify relevant factors and visualise their relationships in a SARS-CoV-2 infection, but the model is generally applicable to any complex dataset.

• Keywords
• COVID-19 severity, IgM and IgG levels, data visualisation, minimal immune signature, multivariate data analysis, patient similarity network,
• MeSH
• COVID-19 * MeSH
• Humans MeSH
• Antibodies, Viral MeSH
• SARS-CoV-2 * MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Names of Substances
• Antibodies, Viral MeSH

N-acetylcysteine (NAC), often used as an antioxidant-scavenging reactive oxygen species (ROS) in vitro, was recently shown to increase the cytotoxicity of other compounds through ROS-dependent and ROS-independent mechanisms. In this study, NAC itself was found to induce extensive ROS production in human leukemia HL-60 and U937 cells. The cytotoxicity depends on ROS-modulating enzyme expression. In HL-60 cells, NAC activated NOX2 to produce superoxide (O2•-). Its subsequent conversion into H2O2 by superoxide dismutase 1 and 3 (SOD1, SOD3) and production of ClO- from H2O2 by myeloperoxidase (MPO) was necessary for cell death induction. While the addition of extracellular SOD potentiated NAC-induced cell death, extracellular catalase (CAT) prevented cell death in HL-60 cells. The MPO inhibitor partially reduced the number of dying HL-60 cells. In U937 cells, the weak cytotoxicity of NAC is probably caused by lower expression of NOX2, SOD1, SOD3, and by the absence of MOP expression. However, even here, the addition of extracellular SOD induced cell death in U937 cells, and this effect could be reversed by extracellular CAT. NAC-induced cell death exhibited predominantly apoptotic features in both cell lines. Conclusions: NAC itself can induce extensive production of O2•- in HL-60 and U937 cell lines. The fate of the cells then depends on the expression of enzymes that control the formation and conversion of ROS: NOX, SOD, and MPO. The mode of cell death in response to NAC treatment bears apoptotic and apoptotic-like features in both cell lines.

• Keywords
• HL-60 cells, MPO, N-acetylcysteine, NOX, SOD, U937 cells, oxidative stress,
• MeSH
• Acetylcysteine pharmacology   MeSH
• HL-60 Cells MeSH
• Catalase genetics   MeSH
• Leukemia drug therapy   genetics   metabolism   MeSH
• Humans MeSH
• NADPH Oxidase 2 genetics   MeSH
• Oxidative Stress drug effects   MeSH
• Peroxidase genetics   MeSH
• Cell Proliferation drug effects   MeSH
• Reactive Oxygen Species metabolism   MeSH
• Gene Expression Regulation, Neoplastic drug effects   MeSH
• Gene Expression Profiling MeSH
• Superoxide Dismutase genetics   MeSH
• U937 Cells MeSH
• Cell Survival drug effects   MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Names of Substances
• Acetylcysteine MeSH
• CYBB protein, human MeSH Browser
• Catalase MeSH
• MPO protein, human MeSH Browser
• NADPH Oxidase 2 MeSH
• Peroxidase MeSH
• Reactive Oxygen Species MeSH
• Superoxide Dismutase MeSH

Overactivation of the innate immune system together with the impaired downstream pathway of type I interferon-responding genes is a hallmark of rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), and systemic sclerosis (SSc). To date, limited data on the cross-disease innate gene signature exists among those diseases. We compared therefore an innate gene signature of Toll-like receptors (TLRs), seven key members of the interleukin (IL)1/IL1R family, and CXCL8/IL8 in peripheral blood mononuclear cells from well-defined patients with active stages of RA (n = 36, DAS28 ≥ 3.2), SLE (n = 28, SLEDAI > 6), and SSc (n = 22, revised EUSTAR index > 2.25). Emerging diversity and abundance of the innate signature in RA patients were detected: RA was characterized by the upregulation of TLR3, TLR5, IL1RAP/IL1R3, IL18R1, and SIGIRR/IL1R8 when compared to SSc (P corr < 0.02) and of TLR2, TLR5, and SIGIRR/IL1R8 when compared to SLE (P corr < 0.02). Applying the association rule analysis, six rules (combinations and expression of genes describing disease) were identified for RA (most frequently included high TLR3 and/or IL1RAP/IL1R3) and three rules for SLE (low IL1RN and IL18R1) and SSc (low TLR5 and IL18R1). This first cross-disease study identified emerging heterogeneity in the innate signature of RA patients with many upregulated innate genes compared to that of SLE and SSc.

• MeSH
• Adult MeSH
• Interleukin-1 genetics   metabolism   MeSH
• Interleukin-8 genetics   metabolism   MeSH
• Leukocytes, Mononuclear metabolism   MeSH
• Middle Aged MeSH
• Humans MeSH
• Immunity, Innate genetics   MeSH
• Receptors, Interleukin-1 Type I genetics   metabolism   MeSH
• Arthritis, Rheumatoid blood   genetics   immunology   MeSH
• Aged, 80 and over MeSH
• Aged MeSH
• Scleroderma, Systemic blood   genetics   immunology   MeSH
• Lupus Erythematosus, Systemic blood   genetics   immunology   MeSH
• Toll-Like Receptors genetics   metabolism   MeSH
• Transcriptome MeSH
• Check Tag
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Male MeSH
• Aged, 80 and over MeSH
• Aged MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Names of Substances
• Interleukin-1 MeSH
• Interleukin-8 MeSH
• Receptors, Interleukin-1 Type I MeSH
• Toll-Like Receptors MeSH