Systemic Lupus Erythematosus Samples Research Articles

An interactive web application for exploring systemic lupus erythematosus blood transcriptomic diversity.

In the field of complex autoimmune diseases such as systemic lupus erythematosus (SLE), systems immunology approaches have proven invaluable in translational research settings. Large-scale datasets of transcriptome profiling have been collected and made available to the research community in public repositories, but remain poorly accessible and usable by mainstream researchers. Enabling tools and technologies facilitating investigators' interaction with large-scale datasets such as user-friendly web applications could promote data reuse and foster knowledge discovery. Microarray blood transcriptomic data from the LUPUCE cohort (publicly available on Gene Expression Omnibus, GSE49454), which comprised 157 samples from 62 adult SLE patients, were analyzed with the third-generation (BloodGen3) module repertoire framework, which comprises modules and module aggregates. These well-characterized samples corresponded to different levels of disease activity, different types of flares (including biopsy-proven lupus nephritis), different auto-antibody profiles and different levels of interferon signatures. A web application was deployed to present the aggregate-level, module-level and gene-level analysis results from LUPUCE dataset. Users can explore the similarities and heterogeneity of SLE samples, navigate through different levels of analysis, test hypotheses and generate custom fingerprint grids and heatmaps, which may be used in reports or manuscripts. This resource is available via this link: https://immunology-research.shinyapps.io/LUPUCE/. This web application can be employed as a stand-alone resource to explore changes in blood transcript profiles in SLE, and their relation to clinical and immunological parameters, to generate new research hypotheses.

Duplex Vertical-Flow Rapid Tests for Point-of-Care Detection of Anti-dsDNA and Anti-Nuclear Autoantibodies.

The goal of this study is to develop a rapid diagnostic test for rheumatic disease and systemic lupus erythematosus (SLE) screening. A novel rapid vertical flow assay (VFA) was engineered and used to assay anti-nuclear (ANA) and anti-dsDNA (αDNA) autoantibodies from systemic lupus erythematosus (SLE) patients and healthy controls (HCs). Observer scores and absolute signal intensities from the VFA were validated via ELISA. The rapid point-of-care VFA test that was engineered demonstrated a limit of detection of 0.5 IU/mL for ANA and αDNA autoantibodies in human plasma with an inter-operator CV of 19% for ANA and 12% for αDNA. Storage stability was verified over a three-month period. When testing anti-dsDNA and ANA levels in SLE and HC serum samples, the duplex VFA revealed 95% sensitivity, 72% specificity and an 84% ROC AUC value in discriminating disease groups, comparable to the gold standard, ELISA. The rapid αDNA/ANA duplex VFA can potentially be used in primary care clinics for evaluating patients or at-risk subjects for rheumatic diseases and for planning follow-up testing. Given its low cost, ease, and rapid turnaround, it can also be used to assess SLE prevalence estimates.

Toll-like receptor expression and functional behavior in platelets from patients with systemic lupus erythematosus

BackgroundMultiple blood cell abnormalities participate in the development of inflammation in systemic lupus erythematosus (SLE). Although platelets have been suggested as one of these contributors through the release of their content during activation, there are limited specific data about their role as immune players in SLE. Materials and MethodsThirteen SLE patients were included. Flow cytometry was used to measure Toll-like receptors (TLR) 2, 4, and 9 in resting platelets, platelet-activation markers (PAC-1 binding, P-selectin, CD63, and CD40 ligand -L) and platelet-leukocyte aggregates before and after specific TLR stimulation. Soluble CD40L and von Willebrand factor (vWf) release from stimulated platelets was measured using ELISA. ResultsIn resting conditions, SLE platelets showed normal expression levels of TLR 2, 4 and 9. Platelet surface activation markers, soluble CD40L, and vWf release were normal at baseline and after TLR stimulation. Platelet-monocyte aggregates were elevated in resting conditions in SLE samples and showed only a marginal increase after TLR stimulation, while baseline and stimulated platelet-neutrophil and platelet-lymphocyte aggregates were normal. C-reactive protein levels positively correlated with platelet-monocyte aggregates both at baseline and after stimulation with the TLR-2 agonist PAM3CSK4, suggesting these complexes could reflect the inflammatory activity in SLE. In our cohort, 12 of 13 patients received treatment with hydroxychloroquine (HCQ), a known inhibitor of endosomal activity and a potential inhibitor of platelet activation. The fact that SLE platelets showed an adequate response to TLR agonists suggests that, despite this treatment, they retain the ability to respond to the increased levels of damage-associated molecular patterns (DAMPs), which represent known TLR ligands, present in the circulation of SLE patients. Interestingly, elevated plasma levels of high mobility group box 1 (HMGB1), a classical DAMP, correlated with vWf release from TLR-stimulated platelets, suggesting that HMGB1 may also be released by platelets, thereby creating a positive feedback loop for platelet activation that contributes to inflammation. ConclusionOur study demonstrates normal platelet TLR expression and function together with increased circulating platelet-monocyte aggregates. In addition, a direct correlation was observed between plasma HMGB1 levels and platelet vWf release following TLR2 stimulation. This platelet behavior in a group of patients undergoing HCQ treatment suggests that platelets could play a role in the inflammatory state of SLE.

Transcriptomic Features of systemic lupus erythematosus Patients in Flare and Changes during Acute In-Hospital Treatment.

Systemic lupus erythematosus (SLE) is a complex autoimmune disease with varying symptoms and multi-organ damage. Relapse-remission cycles often persist for many patients for years with the current treatment. Improved understanding of molecular changes caused by SLE flare and intensive treatment may result in more targeted therapies. RNA-sequencing was performed on peripheral blood mononuclear cells (PBMCs) from 65 SLE patients in flare, collected both before (SLE1) and after (SLE2) in-hospital treatment, along with 15 healthy controls (HC). Differentially expressed genes (DEGs) were identified among the three groups. Enriched functions and key molecular signatures of the DEGs were analyzed and scored to elucidate the transcriptomic changes during treatment. Few upregulated genes in SLE1 vs HC were affected by treatment (SLE2 vs SLE1), mostly functional in interferon signalling (IFN), plasmablasts, and neutrophils. IFN and plasmablast signatures were repressed, but the neutrophil signature remained unchanged or enhanced by treatment. The IFN and neutrophil scores together stratified the SLE samples. IFN scores correlated well with leukopenia, while neutrophil scores reflected relative cell compositions but not cell counts. In-hospital treatment significantly relieved SLE symptoms with expression changes of a small subset of genes. Notably, IFN signature changes matched SLE flare and improvement, while enhanced neutrophil signature upon treatment suggested the involvement of low-density granulocytes (LDG) in disease development.

A comprehensive exploration of the heterogeneity of immune cells in Han and Zang systemic lupus erythematosus patients via single-cell RNA sequencing

Systemic Lupus Erythematosus (SLE) is an autoimmune sickness with unclear pathogenesis. The goal of this research was to reveal the heterogeneity of immune cells in SLE patients of Han and Zang nationality by single-cell RNA sequencing (scRNA-seq) and bioinformatics profiling. MethodsA total of 94,102 peripheral blood mononuclear cells (PBMCs) from six volunteers with SLE (3 Zang, 3 Han) and six healthy controls were first conducted through scRNA-seq analysis. The immune cell subsets in the pathogenesis of SLE were analyzed as well. Real-time quantitative PCR (RT-qPCR) was applied to confirm the results of sc-RNA seq analysis. ResultsFor the Tibetan samples, the ratios of Naïve CD4 RPS4Y1 cells, Naïve CD4 cells, Memory BC CD24 and Memory BC differed significantly between the SLE and control samples, while that of CD8 CTL MAL cells was significantly different between the two groups in Han nationality samples. Variable differentiation states of CD8 CTL MAL cells, CD8 CTL GZMK cells, and Naïve CD4 cells were detected through pseudotime analysis. Moreover, T-cell receptor (TCR) abundance was notably higher in Tibetan SLE specimens than that in controls, while B-cell receptor (BCR) abundance in Tibetan and Han samples was higher than in control groups. ConclusionsIn summary, the immune cellular heterogeneity of SLE patients both Han and Zang nationality was explored based on various bioinformatics approaches, providing new perspectives for immunological characteristics of SLE among different ethnic groups.

Multi-Omic Insights into the Mutational Landscape and Dysregulated Transcriptional Programs of Autoimmune B-Cells in Systemic Lupus Erythematosus

Systemic Lupus Erythematosus (SLE) is an autoimmune disease with diverse manifestations, from mild and sporadic to severe and life-threatening. SLE heterogeneity arises from various factors, including genetic, epigenetic, and immune niche-related features (Kaul et al., 2016; Jenks et al., 2018). However, the exact interactions and hierarchy between these features remain unclear. Recent studies have found somatic mutations in genes typically mutated in B-cell lymphomas, in subsets of B-cells that are associated with SLE pathogenesis (Piotrowski et al., 2015; Pullabhatla et al., 2018; Singh et al., 2020; Brown et al., 2022). These mutations may support B-cell clonal bursts, but direct information from clinical specimens on the impact of these mutations on B-cell lineages and their influence on SLE progression or malignant transformation is missing. To define the somatic mutational landscape of B-cells in SLE, we first profiled peripheral blood mononuclear cells obtained from a pilot cohort of four SLE patients using whole-exome sequencing (WES; 200X depth). Following GATK best practices (Van der Auwera and O'Connor, 2020), we identified somatic alterations in DDX11 [variant allele frequency (VAF): 10.2%], DNMT3A [VAF: 3.4%]; PMS2 [VAF: 47.9%], and BICD1 [VAF: 47.3%]; these genes have been linked to lymphoid malignancies and SLE pathogenesis (Piotrowski et al., 2015; Pullabhatla et al., 2018; Niroula et al., 2021; Saeed et al., 2021). We validated the presence of the top-identified mutations using droplet digital PCR technology on sorted B-cell subsets (naïve, memory, and double-negative [DN; CD19 hiIgD loCD27 lo]) from these SLE patients. DN cells are a heterogeneous subtype of autoreactive memory B-cells that play a crucial role in SLE pathogenesis being the precursors of autoantibody producing plasma cells (Wei et al., 2007; Jenks et al., 2018). To investigate the transcriptional and epigenetic alterations in the mutation-harboring B-cells, we then conducted single-cell multi-omic sequencing. We profiled sorted activated B-cells (CD19 hiIgD lo) from the four SLE cases, to largely exclude non-autoreactive naïve B-cells. To maintain a comparison with naïve B cells, we included a small proportion of these cells in the input. In total, we analyzed 35,339 cells, and identified different B-cell subsets with distinct gene expression patterns, including DN cells ( n = 1,437 cells; ZEB2 hiTRAF5 lo, Jenks et al., 2018). To uncover, in an unbiased way, transcriptional differences between B-cell subsets, we catalogued variation in transcriptomic signatures derived from the scRNA data using consensus non-negative matrix factorization. We found a unique gene expression program exclusively present in DN cells ( Panel A), which includes key genes implicated in immune regulation and the development of autoimmunity, such as PTPN22 (Chung & Criswell, 2007; Tizaoui et al., 2021) . Pathway analysis of the DN-specific program revealed an enrichment of complement system genes (FDR = 0.074; Hallmark), which are crucial for immune regulation and tolerance, such as CBLB (Tang et al., 2019). Notably, in DN cells from one of the SLE samples carrying lymphoma/SLE-associated mutations in BICD1, PMS2, DDX11, we observed an altered expression of this gene program compared to DN cells from other samples ( P-value = 3.6x10 -11; Panel A, inset), suggesting that a malfunctioning complement system in DN cells may lead to an overly active immune response (Weinstein et al., 2021). In line with this notion, using chromatin accessibility profiles as a measure of transcription factor (TF) regulatory activities, we showed increased activity of TFs involved in interferon-dependent innate immune response and in B-cell activation and differentiation (RFX and OCT-1, respectively; FDR < 0.05), in the DN B-cells of this sample ( Panel B). In summary, we uncovered a unique transcriptional program associated with autoimmune DN B-cells. This program showed enrichment in key genes and pathways involved in immune response regulation. The disruption of this program, accompanied by the somatic SLE-associated mutations, may lead to overactivation of DN B cells, ultimately contributing to autoimmunity. Further analyses involving a larger cohort of clinical specimens are needed to directly link B-cell genotypes with their transcriptional and epigenetic programs and to elucidate the role of the identified mutations in SLE pathobiology.

Novel insights into molecular signatures and pathogenic cell populations shared by systemic lupus erythematosus and vascular dementia.

Although vascular dementia (VD) and systemic lupus erythematosus (SLE) may share immune-mediated pathophysiologic processes, the underlying mechanisms are unclear. This study investigated shared gene signatures in SLE versus VD, as well as their potential molecular mechanisms. Bulk RNA sequencing (RNAseq) and single-cell or single-nucleus RNAseq (sc/snRNAseq) datasets from SLE blood samples and VD brain samples were obtained from Gene Expression Omnibus. The identification of genes associated with both SLE and VD was performed using the weighted gene co-expression network analysis (WGCNA) and machine learning algorithms. For the sc/snRNAseq data, an unbiased clustering pipeline based on Seurat and CellChat was used to determine the cellular landscape profile and examine intracellular communication, respectively. The results were subsequently validated using a mice model of SLE with cognitive dysfunction (female MRL/lpr mice). WGCNA and machine learning identified C1QA, LY96, CD163, and MS4A4A as key genes for SLE and VD. sc/snRNAseq analyses revealed that CD163 and MS4A4A were upregulated in mononuclear phagocytes (MPs) from SLE and VD samples and were associated with monocyte-macrophage differentiation. Intriguingly, LGALS9-associated molecular pathway, as the only signaling pathway common between SLE and VD via CellChat analysis, exhibited significant upregulation in cortical microglia of MRL/lpr mice. Our analyses identified C1QA, LY96, CD163, and MS4A4A as potential biomarkers for SLE and VD. Moreover, the upregulation of CD163/MS4A4A and activation of LGALS9 signaling in MPs may contribute to the pathogenesis of VD with SLE. These findings offer novel insight into the mechanisms underlying VD in SLE patients.

Elevated Antibody Titers to Epstein-Barr Virus and Cytomegalovirus in Patients with Drug-Induced Lupus.

Systemic lupus erythematosus (SLE) is an autoimmune disease, which has been associated with Epstein-Barr virus (EBV) and Cytomegalovirus (CMV) infection. Drug-induced lupus (DIL) is a lupus-like disease caused by the intake of therapeutic drugs, which has been estimated to cause approximately 10-15% of lupus-like cases. Although SLE and DIL share common clinical symptoms, there are some fundamental differences between DIL and SLE onset. Moreover, it remains to be examined whether environmental factors, such as EBV and CMV infections, may contribute to the development of DIL. This study focused on examining the possible association between DIL and EBV and CMV infections, by examining IgG titers to EBV and CMV antigens in serum samples by enzyme-linked immunosorbent assays. Antibody titers to EBV early antigen-diffuse and CMV pp52 were found to be significantly elevated in both SLE and DIL patients compared to healthy controls, although no correlation was found for antibodies to the two virus antigens in the respective disease groups. Moreover, total IgG titers were reduced in SLE and DIL serum samples, which may reflect a general lymphocytopenia, which commonly is associated with SLE. The current findings support that EBV and CMV infections may contribute to the development of DIL and that onset of both diseases are related.

Autoantibody repertoire characterization provides insight into the pathogenesis of monogenic and polygenic autoimmune diseases.

Autoimmune diseases vary in the magnitude and diversity of autoantibody profiles, and these differences may be a consequence of different types of breaks in tolerance. Here, we compared the disparate autoimmune diseases autoimmune polyendocrinopathy-candidiasis-ecto-dermal dystrophy (APECED), systemic lupus erythematosus (SLE), and Sjogren's syndrome (SjS) to gain insight into the etiology of breaks in tolerance triggering autoimmunity. APECED was chosen as a prototypical monogenic disease with organ-specific pathology while SjS and SLE represent polygenic autoimmunity with focal or systemic disease. Using protein microarrays for autoantibody profiling, we found that APECED patients develop a focused but highly reactive set of shared mostly anti-cytokine antibodies, while SLE patients develop broad and less expanded autoantibody repertoires against mostly intracellular autoantigens. SjS patients had few autoantibody specificities with the highest shared reactivities observed against Ro-52 and La. RNA-seq B-cell receptor analysis revealed that APECED samples have fewer, but highly expanded, clonotypes compared with SLE samples containing a diverse, but less clonally expanded, B-cell receptor repertoire. Based on these data, we propose a model whereby the presence of autoreactive T-cells in APECED allows T-dependent B-cell responses against autoantigens, while SLE is driven by breaks in peripheral B-cell tolerance and extrafollicular B-cell activation. These results highlight differences in the autoimmunity observed in several monogenic and polygenic disorders and may be generalizable to other autoimmune diseases.

Establishment and analysis of a disease risk prediction model for the systemic lupus erythematosus with random forest.

Systemic lupus erythematosus (SLE) is a latent, insidious autoimmune disease, and with the development of gene sequencing in recent years, our study aims to develop a gene-based predictive model to explore the identification of SLE at the genetic level. First, gene expression datasets of SLE whole blood samples were collected from the Gene Expression Omnibus (GEO) database. After the datasets were merged, they were divided into training and validation datasets in the ratio of 7:3, where the SLE samples and healthy samples of the training dataset were 334 and 71, respectively, and the SLE samples and healthy samples of the validation dataset were 143 and 30, respectively. The training dataset was used to build the disease risk prediction model, and the validation dataset was used to verify the model identification ability. We first analyzed differentially expressed genes (DEGs) and then used Lasso and random forest (RF) to screen out six key genes (OAS3, USP18, RTP4, SPATS2L, IFI27 and OAS1), which are essential to distinguish SLE from healthy samples. With six key genes incorporated and five iterations of 10-fold cross-validation performed into the RF model, we finally determined the RF model with optimal mtry. The mean values of area under the curve (AUC) and accuracy of the models were over 0.95. The validation dataset was then used to evaluate the AUC performance and our model had an AUC of 0.948. An external validation dataset (GSE99967) with an AUC of 0.810, an accuracy of 0.836, and a sensitivity of 0.921 was used to assess the model's performance. The external validation dataset (GSE185047) of all SLE patients yielded an SLE sensitivity of up to 0.954. The final high-throughput RF model had a mean value of AUC over 0.9, again showing good results. In conclusion, we identified key genetic biomarkers and successfully developed a novel disease risk prediction model for SLE that can be used as a new SLE disease risk prediction aid and contribute to the identification of SLE.

Upregulation of microRNA-762 suppresses the expression of GIPC3 in systemic lupus erythematosus and neuropsychiatric systemic lupus erythematosus.

BackgroundSystemic lupus erythematosus (SLE), especially neuropsychiatric SLE (NPSLE), is a complex systemic autoimmune disease, characterized by variable course and multiple organ dysfunction. Our study aimed to identify crucial microRNA (miRNAs) in SLE and NPSLE.MethodsTotally 12 cases of serum specimens were collected from General Hospital of Ningxia Medical University (SLE = 4, NPSLE = 4, control = 4). After miRNA sequencing, differential expression analysis, miRNA target prediction, and miRNA‐messenger RNA (mRNA) regulatory network construction were performed to identify the hub miRNAs. The expression of target gene was determined by quantitative reverse transcription‐polymerase chain reaction and Western blot.ResultsThere were 79 and 59 differentially expressed miRNAs (DEmiRNAs) in NPSLE versus Control, and SLE versus Control, respectively. Among 35 overlapped DEmiRNAs, 5 upregulated miRNAs' (hsa‐miR‐762, hsa‐miR‐4270, hsa‐miR‐3663‐3p, hsa‐miR‐4778‐5p, and hsa‐miR‐4516) target genes were supported by at least six databases. The miRNA‐mRNA network indicated that core miRNA hsa‐miR‐762 regulated 1270 target genes. MiR‐762 was significantly upregulated in SLE and NPSLE, and over expression of miR‐762 significantly suppressed GIPC PDZ domain containing family member 3 (GIPC3) expression in SLE and NPSLE.ConclusionsUpregulation of hub miRNA miR‐762 can suppress the expression of GIPC3 in both SLE and NPSLE samples, which is probably involved in the development of SLE and NPSLE. Meanwhile, along with the development from SLE to NPSLE, miR‐762 exhibits higher expression.

Immune-relevant genes of systemic lupus erythematosus by transcriptome profiling analysis

ObjectiveOur study aimed to reveal the roles of long noncoding RNA (lncRNA) and immune-relevant genes in systemic lupus erythematosus (SLE). MethodsExpression profiling dataset GSE65391 consisted of 72 healthy blood samples and 924 SLE blood samples was downloaded from the Gene Expression Omnibus. Differentially expressed RNAs (DERs) in SLE samples were identified using the Limma package. Immune-relevant DERs were uncovered after assessing the immune cell infiltration types of different samples. Modules significantly related to the disease were extracted via weighted gene co-expression network analysis (WGCNA), followed by module–trait analysis. LncRNA–mRNA co-expression network was constructed for DERs in immune-relevant modules. Genes related to SLE were further revealed via the Comparative Toxicogenomics Database (CTD). Validation assay was conducted by another independent expression profiling dataset, GSE46907 (consisted of 5 healthy blood samples and 5 SLE blood samples) and quantitative reverse transcription-polymerase chain reaction (qRT-PCR) analysis of 15 healthy blood samples and 15 SLE blood samples. ResultsA total of 606 DERs, including 19 lncRNAs and 587 mRNAs, were identified. Obvious differences were observed in the proportions of 20 immune cell types, and 378 immune-relevant DERs were revealed. Genes in the lncRNA–mRNA co-expression network were significantly enriched in primary immunodeficiency, hematopoietic cell lineage, B cell receptor signaling pathway, SLE (up-regulated FCGR3A, down-regulated CD40LG, up-regulated HIST1H2BE, down-regulated human leukocyte antigen [HLA]-DOA, down-regulated HLA-DOB, up-regulated HIST1H3D, and up-regulated HIST1H2BC), and intestinal immune network for IgA production. SLE-related gene, CD40LG, retrieved from CTD has co-expression interactions with seven differentially expressed lncRNAs (HCG27, LINC02555, LINC02210, DHRS4-AS1, MIR600HG, DANCR, and LINC01278). CD40LG and HLA-DOA, were observed down-regulated, and FCGR3A, and HIST1H2BE were up-regulated in validation dataset GES46907. Moreover, CD40LG was validated to be down-regulated using qRT-PCR. ConclusionsOur results provide new insight in understanding the pathogenesis of SLE and might be helpful for developing new therapeutic approaches of SLE by modulating immune response.

Comparison of circulating miR-148a and miR-126 with autoantibodies as biomarkers of lupus nephritis in patients with SLE

ABSTRACT Lupus nephritis (LN) is the main manifestation of systemic Lupus Erythematosus (SLE). MicroRNAs (miRNAs) and autoantibodies could be suitable candidate biomarkers of LN. This study evaluates the expression of circulating miR-148a and miR-126 along with anti-dsDNA, anti-C1q, and anti-C3b autoantibodies in SLE patients with LN (SLE + LN). 30 women with SLE, 30 women with SLE + LN, and 25 women as healthy controls (HCs) were enrolled in this study. The plasma expression of selected miRNAs was evaluated by real-time PCR. The serum level of anti-dsDNA, C1q, and C3b antibodies was measured by the ELISA. The expression of miR-148a was significantly increased in SLE and SLE+LN groups compared with the control group. No significant difference was found in the expression of miR-126 among the groups. The frequency of autoantibodies was significantly higher in the SLE + LN group than SLE. The Higher levels of circulating miR-148a in the SLE samples compared with the HCs suggest that this miRNA could be a reliable biomarker for SLE patients (with or without LN). Also, autoantibodies against dsDNA, C1q, and, C3 could be used for the prediction of SLE nephritis, independently. However, further studies are needed to confirm these findings.

Generation of evidence supporting the content validity of SF-36, FACIT-F, and LupusQoL, and novel patient-reported symptom items for use in patients with systemic lupus erythematosus (SLE) and SLE with lupus nephritis (LN)

ObjectiveSLE and lupus nephritis (LN) have significant impacts on the health-related quality of life of patients living with the condition, which are important to capture from the patient’s perspective using...

Identification of Diagnostic Biomarkers in Systemic Lupus Erythematosus Based on Bioinformatics Analysis and Machine Learning.

Systemic lupus erythematosus (SLE) is a complex autoimmune disease that affects several organs and causes variable clinical symptoms. Exploring new insights on genetic factors may help reveal SLE etiology and improve the survival of SLE patients. The current study is designed to identify key genes involved in SLE and develop potential diagnostic biomarkers for SLE in clinical practice. Expression data of all genes of SLE and control samples in GSE65391 and GSE72509 datasets were downloaded from the Gene Expression Omnibus (GEO) database. A total of 11 accurate differentially expressed genes (DEGs) were identified by the “limma” and “RobustRankAggreg” R package. All these genes were functionally associated with several immune-related biological processes and a single KEGG (Kyoto Encyclopedia of Genes and Genome) pathway of necroptosis. The PPI analysis showed that IFI44, IFI44L, EIF2AK2, IFIT3, IFITM3, ZBP1, TRIM22, PRIC285, XAF1, and PARP9 could interact with each other. In addition, the expression patterns of these DEGs were found to be consistent in GSE39088. Moreover, Receiver operating characteristic (ROC) curves analysis indicated that all these DEGs could serve as potential diagnostic biomarkers according to the area under the ROC curve (AUC) values. Furthermore, we constructed the transcription factor (TF)-diagnostic biomarker-microRNA (miRNA) network composed of 278 nodes and 405 edges, and a drug-diagnostic biomarker network consisting of 218 nodes and 459 edges. To investigate the relationship between diagnostic biomarkers and the immune system, we evaluated the immune infiltration landscape of SLE and control samples from GSE6539. Finally, using a variety of machine learning methods, IFI44 was determined to be the optimal diagnostic biomarker of SLE and then verified by quantitative real-time PCR (qRT-PCR) in an independent cohort. Our findings may benefit the diagnosis of patients with SLE and guide in developing novel targeted therapy in treating SLE patients.

ZBP1 is a significant pyroptosis regulator for systemic lupus erythematosus.

BackgroundSystemic lupus erythematosus (SLE) is a common autoimmune disease that affects all organs. Recently, several studies have shown that pyroptosis playsa significant process in the occurrence and progression of SLE. However, no study has investigated the association between pyroptosis genes and SLE. We conducted this study to examine this association.MethodsThe GSE11090, GSE20864, and GSE112087 gene microarrays of normal and SLE patient samples were downloaded from the Gene Expression Omnibus database. A differentially expressed gene (DEG) analysis was performed using the LIMMA package in R software. Log2 fold change |logFC| >0.5 and a false discovery rate (FDR) <0.05 setting for DEGs’ screening value. We also performed an enrichment function analysis of the DEGs. To explore the role of pyroptosis genes in SLE, we selected pyroptosis genes that intersected with the DEGs for further analysis, we also examined the expression levels of the selected genes, their association with immune cell infiltration, and conducted western blotting and polymerase chain reaction analyses to confirm the selected genes expression levels in the SLE and normal samples.ResultsA total of 3,398 identical genes were obtained from 3 datasets for the differential analysis. 84 upregulated genes and 52 downregulated genes were identified in SLE. The enrichment function analysis revealed that DEGs act as key regulators of nicotinamide adenine dinucleotide (NADH) dehydrogenase activity, phospholipid scramblase activity, double-stranded ribonucleic acid (RNA) binding, and the interferon signaling pathway. We identified the SLE-related pyroptosis gene, Z-DNA binding protein 1 (ZBP1), by intersecting the DEGs of SLE and 40 pyroptosis genes. The differential analysis indicated that ZBP1 was more highly expressed in SLE patients compared to normal samples (P<0.001). Additionally, the expression of ZBP1 was higher in females than males (P=0.008). The SLE samples had different immune cell infiltration than the normal samples, and ZBP1 was significantly correlated with immune cell infiltration in the SLE samples. Finally, the validation experiments results showed that ZBP1 expression levels were significantly more highly expressed in female and SLE patients, than male and normal patients.ConclusionsZBP1 may indicate that females have a high incidence rate of SLE, and it plays a significant role in the occurrence and progression of SLE.

Coordination of retrotransposons and type I interferon with distinct interferon pathways in dermatomyositis, systemic lupus erythematosus and autoimmune blistering disease

Type I interferon (IFN) plays a crucial role in innate and adaptive immunity, and aberrant IFN responses are involved in systemic autoimmune diseases, such as systemic lupus erythematosus (SLE) and dermatomyositis (DM). Type I IFNs can be induced by transcribed retrotransposons. The regulation of retrotransposons and type I IFN and the downstream IFN pathways in SLE, DM, and autoimmune blistering disease (AIBD) were investigated. The gene expression levels of retrotransposons, including LINE-1, type I-III IFNs, and IFN-stimulated genes (ISGs) in peripheral blood cells from patients with DM (n = 24), SLE (n = 19), AIBD (n = 14) and healthy controls (HCs, n = 10) were assessed by quantitative polymerase chain reaction. Upregulation of retrotransposons and IFNs was detected in DM patient samples, as is characteristic, compared to HCs; however, ISGs were not uniformly upregulated. In contrast, retrotransposons and IFNs, except for type II IFN, such as IFN-γ, were not upregulated in SLE. In AIBD, only some retrotransposons and type I interferons were upregulated. The DM, SLE, and AIBD samples showed coordinated expression of retrotransposons and type I IFNs and distinct spectra of IFN signaling. A positive correlation between LINE-1 and IFN-β1 was also detected in human cell lines. These factors may participate in the development of these autoimmune diseases.

Characterization of drug binding with alpha1-acid glycoprotein in clinical samples using ultrafast affinity extraction

Many drugs bind to serum transport proteins, which can affect both drug distribution and activity in the body. α1-Acid glycoprotein (AGP) is a key transport protein for basic and neutral drugs. Both elevated levels and altered glycosylation patterns of AGP have been seen in clinical conditions such as systemic lupus erythematosus (SLE). This study developed, optimized, and used the method of ultrafast affinity extraction (UAE) to examine whether these changes in AGP are associated with changes in the binding by some drugs to this transport protein. This approach used affinity microcolumns to capture and measure, in serum, the free fractions of several drugs known to bind AGP. These measurements were made with pooled normal control serum and serum samples from individuals with SLE. Immunoaffinity chromatography was used to obtain the content of AGP and HSA in these samples, and CE was used to examine the glycoform pattern for AGP in each serum sample. The free drug fractions measured for normal control serum ranged from 3.5 to 29.1%, in agreement with the results of ultrafiltration, and provided binding constants of ~105–106 M−1 for the given drugs with AGP at 37⁰C. Analysis of a screening set of SLE serum samples by UAE gave decreased free fractions (relative change, 12-55%) vs normal serum when spiked with the same types and amounts of drugs. These changes were related in some cases to AGP content, with some SLE samples having AGP levels 1.3- to 2.1-fold above the upper end of the normal range. In other cases, the changes in free fractions appeared to be linked to alterations in the glycoforms and binding constants of AGP, with some affinities differing by 1.2- to 1.5-fold vs normal AGP. This approach can be employed with other solute-protein systems and to investigate binding by other drugs or transport proteins directly in clinical samples.

Transcription Factor Activity Inference in Systemic Lupus Erythematosus.

Background: Systemic Lupus Erythematosus (SLE) is a systemic autoimmune disease with diverse clinical manifestations. Although most of the SLE-associated loci are located in regulatory regions, there is a lack of global information about transcription factor (TFs) activities, the mode of regulation of the TFs, or the cell or sample-specific regulatory circuits. The aim of this work is to decipher TFs implicated in SLE. Methods: In order to decipher regulatory mechanisms in SLE, we have inferred TF activities from transcriptomic data for almost all human TFs, defined clusters of SLE patients based on the estimated TF activities and analyzed the differential activity patterns among SLE and healthy samples in two different cohorts. The Transcription Factor activity matrix was used to stratify SLE patients and define sets of TFs with statistically significant differential activity among the disease and control samples. Results: TF activities were able to identify two main subgroups of patients characterized by distinct neutrophil-to-lymphocyte ratio (NLR), with consistent patterns in two independent datasets—one from pediatric patients and other from adults. Furthermore, after contrasting all subgroups of patients and controls, we obtained a significant and robust list of 14 TFs implicated in the dysregulation of SLE by different mechanisms and pathways. Among them, well-known regulators of SLE, such as STAT or IRF, were found, but others suggest new pathways that might have important roles in SLE. Conclusions: These results provide a foundation to comprehend the regulatory mechanism underlying SLE and the established regulatory factors behind SLE heterogeneity that could be potential therapeutic targets.

Potential role of viral infection and B cells as a linker between innate and adaptive immune response in systemic lupus erythematosus.

Systemic lupus erythematosus (SLE) is an autoimmune disease that involves several organ systems. Although B cells play a key role in SLE pathogenesis, the mechanisms behind B cell dysregulation in SLE development remained controversial. Finding the modules containing highly co-expressed genes in B cells could explain biological pathways involved in the pathogenesis of SLE, which may further support the reasons for the altered function of B cells in SLE disease. A total of three microarray gene expression datasets were downloaded from Gene Expression Omnibus. SLE samples were prepared from the purified B lymphocyte cells of the patients who have not received immunosuppressive drugs as well as high dose immunocytotoxic therapies or steroids. A weighted gene co-expression network was then constructed to find the relevant modules implicated in the SLE progression. Among 17 identified modules, 3 modules were selected through mapping to STRING and finding the ones that had highlyconnection at the protein level. These modules clearly indicate the involvement of several pathways in the pathogenesis of SLE including viral infection, adaptive immune response, and innate immune response in B lymphocytes. The WGCN analysis further revealed the co-expressed genes involved in both innate and adaptive immune systems. Mix infections and primary immunodeficiency might also dysregulate B lymphocytes, which may facilitate SLE development. As such, identifying novel biomarkers and pathways in lupus would be of importance.