Biomarkers For Systemic Lupus Erythematosus Research Articles

Identification and Characterization of CD8+ CD27+ CXCR3- T Cell Dysregulation and Progression-Associated Biomarkers in Systemic Lupus Erythematosus.

Systemic Lupus Erythematosus (SLE) etiopathogenesis highlights the contributions of overproduction of CD4+ T cells and loss of immune tolerance. However, the involvement of CD8+ T cells in SLE pathology and disease progression remains unclear. Here, the comprehensive immune cell dysregulation in total 263 clinical peripheral blood samples composed of active SLE (aSLE), remission SLE (rSLE) and healthy controls (HCs) is investigated via mass cytometry, flow cytometry and single-cell RNA sequencing. This is observed that CD8+ CD27+ CXCR3- T cells are increased in rSLE compare to aSLE. Meanwhile, the effector function of CD8+ CD27+ CXCR3- T cells are overactive in aSLE compare to HCs and rSLE, and are positively associated with clinical SLE activity. In addition, the response of peripheral blood mononuclear cells (PBMCs) is monitored to interleukin-2 stimulation in aSLE and rSLE to construct dynamic network biomarker (DNB) model. It is demonstrated that DNB score-related parameters can faithfully predict the remission of aSLE and the flares of rSLE. The abundance and functional dysregulation of CD8+ CD27+ CXCR3- T cells can be potential biomarkers for SLE prognosis and concomitant diagnosis. The DNB score with accurate prediction to SLE disease progression can provide clinical treatment suggestions especially for drug dosage determination.

Identification of potential biomarkers for SLE through mRNA expression profiling

ABSTRACT Background: Systemic lupus erythematosus (SLE) is an autoimmune disease that influences numerous body systems. Furin, tristetraprolin (TTP), and NOD, LRR, and pyrin domain-containing protein 3 (NLRP3) contribute in developing autoimmune illnesses. Aim: Understandthe role of furin, TTP, and NLRP3 mRNA gene expression in SLE pathogenesis and prognosis. Methods: Total 210 individuals were enrolled, divided in two group: cases and control; 105 participants in each group. Real-time quantitative PCR for furin, TTP,and NLRP3 mRNA gene expression were determined for each subject. Results: SLE patients showed significantly higher serum furin [median 20.10 (0.0–162.88) in comparison with control group [median 1.10 (0.33–8.64)] with significant pvalue (p < 0.001), for NLRP3 expression [median 7.03 (0.0–282.97) compared to control group [median 1.0 (0.44–9.48)] with significant p value (p = 0.006)but lower TTP [median 2.37 (0.0–30.13)] in comparison with control group [median 7.90 (1.0–29.29)] with significant p value (p < 0.001) . Elevated levels of Furin and NLRP3 and low levels of TTP were linked to increased illness activity. Conclusion: Furin and NLRP increase in SLE and higher with illness activity. TTP is lowerin SLE and negatively correlates with disease activity.

Downregulation of circETS1 disrupts Th17/Treg homeostasis by inhibiting FOXP3 transcription: A new potential biomarker in systemic lupus erythematosus.

Systemic lupus erythematosus (SLE) is an autoimmune disease associated with an imbalance of T helper 17 (Th17) to regulatory T cells (Tregs). However, the underlying mechanism remains unclear. Increasing evidence suggests that circular RNAs play a crucial role in SLE. Although circETS1 was discovered 30years ago, detailed exploration of its functions remains limited. In this study, we measured the expression levels of circETS1 in peripheral blood mononuclear cells (PBMCs) and CD4+ T cells of patients with SLE by quantitative polymerase chain reaction. The impact of circETS1 expression on the Th17/Treg balance and underlying mechanism were evaluated using double-luciferase reporter, gain-/loss-of-function, and rescue assays. Receiver operating characteristic (ROC) curve analysis was conducted to assess the diagnostic value of circETS1. Both circETS1 and FOXP3 expression were downregulated in the PBMCs and CD4+ T cells of patients with SLE (n = 28) compared with those in the cells of healthy controls (n = 20). Mechanistically, we found that circETS1 can bind directly to the microRNA miR-1205, acting as a sponge to upregulate the transcription of FOXP3, thereby maintaining the Th17/Treg balance. Notably, ROC analysis showed that the expression level of circETS1 in PBMCs had an area under the curve of 0.873 (95% confidence interval: 0.771-0.976; p < .001) for diagnosing SLE, with a sensitivity of 80.00% and a specificity of 89.29%. Finally, we found negative correlations between the level of circETS1 in PBMCs and disease severity (according to the Systemic Lupus Erythematosus Disease Activity Index) in patients with SLE (r = -0.7712, 95% CI: -0.8910 to -0.5509; p < .001). The imbalance in Th17/Treg cells in SLE may be attributed, in part, to the circETS1/miR-1205/FOXP3 pathway. CircETS1 has potential to serve as a valuable biomarker for the diagnosis and evaluation of SLE.

Identification of monocyte-associated biomarkers in systemic lupus erythematosus and their pan-cancer analysis.

Immune dysregulation is not only a pathogenic mechanism in systemic lupus erythematosus (SLE) but also a potential cause of the link between SLE and cancer. The current understanding of SLE monocyte-associated biomarkers is limited, and the precise mechanism behind the link between SLE and cancer is uncertain. By using WGCNA and immune infiltration to analyze the GSE72326 dataset, we determined the most pertinent modules for monocytes and discovered eight candidate hub genes from them. The limma software was used to find genes that were differently expressed in SLE. The genes that overlapped between the two were chosen using a Venn diagram as the essential genes related to monocytes in SLE, and the essential genes were verified by several datasets. Correlation analysis and GSEA analysis were used to examine the probable immunological pathways connected to key genes. We examined the expression of hub genes in cancer and their interaction with monocytes using the GEPIA and TIMER databases to understand the significance of essential genes in tumorigenesis. In addition, we performed transcription factor identification. We discovered three biomarkers (IFI30, BLVRA, and RIN2) that are mostly involved in interferon-related signaling pathways and are associated with monocyte-mediated immune responses in SLE. The three important genes are also strongly expressed in a number of malignancies and have a relationship with monocytes. As a result, IFI30, BLVRA, and RIN2 may act as SLE-associated biomarkers of monocytes and as a bridge between SLE and tumors. We proposed that interferon-related signaling pathways might function as possible mediators of cancer risk in SLE.

Long Non-Coding RNA TUG1 Gene Polymorphism and TUG1 Expression Level as Molecular Biomarkers of Systemic Lupus Erythematosus and Lupus Nephritis.

Long non-coding RNA (lncRNA) TUG1 acts as a proto-oncogene, allowing the proliferation of tumor cells, and it has been related to inflammation. Therefore, we aimed in this study to investigate for the first time the role of TUG1 gene polymorphism and the TUG1 level as biomarkers in systemic lupus erythematosus (SLE) and their link to lupus nephritis 145 SLE. A total of 145 healthy controls were subjected to clinical and laboratory evaluation. The disease activity was assessed by the SLE disease activity index (SLEDAI) score. SLE patients were divided into two subgroups according to the presence of lupus nephritis. The TUG1 gene polymorphisms rs5749201 and rs886471 were determined by Sanger sequencing, and TUG1 expression was assessed by qRT-PCR. There was a significant increase in the risk of SLE AA, TA, dominant genotypes, and the A allele of rs5749201 (p < 0.001) by 4.9-, 10.1-, 6.5-, and 2.5-fold in comparison to the relative control. GG and TG, dominant genotypes and the G allele of rs886471 (p < 0.01) increased the risk by 5.09-, 11.9-, 6.5-, and 2.6-fold. AA, A allele, dominant and recessive rs5749201genotypes increased the risk of lupus nephritis by 16.6-, 7.4-, 7.1-, and 12.2-fold, respectively (p < 0.05). GG, dominant and recessive genotypes, and the G allele of rs886471 increased the risk of lupus nephritis by 17.04-, 7.8-, 9.4-, and 6.08-fold, respectively (p < 0.05). Additionally, the AG haplotype increased the risk of SLE and lupus nephritis by 2.7- and 7.8-fold, respectively. The AA rs5749201 and GG rs886471 variants are significantly associated with more severe disease (p < 0.001). TUG1 expression was significantly higher in SLE than in the control and in the lupus nephritis than in non-lupus nephritis cases (p < 0.05). Interestingly, AA rs5749201 and GG rs886471 were significantly associated with higher TUG1 levels (p < 0.001). It was also found that AA rs5749201 and high SLEDAI were predictors of lupus nephritis. Overall, our findings illustrated for the first time that TUG1 gene rs5749201 and rs886471 variants were associated with increased risk of SLE, more severe disease, and lupus nephritis, and the TUG1 level could be used as a diagnostic biomarker of SLE and lupus nephritis.

Increased formation of neutrophil extracellular traps induced by autophagy and identification of autophagy-related biomarkers in systemic lupus erythematosus.

Abnormal death of neutrophils and the subsequent ineffective clearance of cell fragments result in production of autoantigens that can lead to systemic lupus erythematosus (SLE). Excessive formation of neutrophil extracellular traps (NETs) can trigger the synthesis of pro-inflammatory cytokines such as type I interferons, leading to tissue damage and immune dysfunction in SLE patients. In this study, we found that a decrease in neutrophil counts in the peripheral blood was correlated with clinical parameters in SLE patients. Patients with low neutrophil counts had high renal activity index and chronicity index scores. NET formation and neutrophil autophagy in SLE patients were increased. The autophagy inhibitor hydroxychloroquine was shown to restrict NET formation. Using comprehensive bioinformatics analysis, we found that the expression of the autophagy-related gene, hypoxia-inducible factor 1A (HIF1A), was enhanced in peripheral neutrophils and in the renal glomeruli in SLE patients. Targeting HIF1A could be a potential therapeutic approach for SLE.

Comprehensive bioinformatics analysis reveals the crosstalk genes and immune relationship between the systemic lupus erythematosus and venous thromboembolism.

It is well known that patients with systemic lupus erythematosus (SLE) had a high risk of venous thromboembolism (VTE). This study aimed to identify the crosstalk genes between SLE and VTE and explored their clinical value and molecular mechanism initially. We downloaded microarray datasets of SLE and VTE from the Gene Expression Omnibus (GEO) dataset. Differential expression analysis was applied to identify the crosstalk genes (CGs). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed on the shared genes. The shared diagnostic biomarkers of the two diseases were further screened from CGs using least absolute shrinkage and selection operator (Lasso) regression. Two risk scores for SLE and VTE were constructed separately to predict the likelihood of illness according to the diagnostic biomarkers using a logical regression algorithm. The immune infiltration levels of SEL and VTE were estimated via the CIBERSORT algorithm and the relationship of CGs with immune cell infiltration was investigated. Finally, we explored potential phenotype subgroups in SLE and VTE based on the expression level of CGs through the consensus clustering method and studied immune cell infiltration in different subtypes. A total of 171 CGs were obtained by the intersection of differentially expressed genes (DEGs) between SLE and VTE cohorts. The functional enrichment shown these CGs were mainly related to immune pathways. After screening by lasso regression, we found that three hub CGs (RSAD2, HSP90AB1, and FPR2) were the optimal shared diagnostic biomarkers for SLE and VTE. Based on the expression level of RSAD2 and HSP90AB1, two risk prediction models for SLE and VTE were built by multifactor logistic regression and systemically validated in internal and external validation datasets. The immune infiltration results revealed that CGs were highly correlated with multiple infiltrated immunocytes. Consensus clustering was used to respectively regroup SLE and VTE patients into C1 and C2 clusters based on the CGs expression profile. The levels of immune cell infiltration and immune activation were higher in C1 than in C2 subtypes. In our study, we further screen out diagnostic biomarkers from crosstalk genes SLE and VTE and built two risk scores. Our findings reveal a close relationship between CGs and the immune microenvironment of diseases. This provides clues for further exploring the common mechanism and interaction between the two diseases.

NR_103776.1 as a novel diagnostic biomarker for systemic lupus erythematosus.

With the development of sequencing technologies, there is increasing evidence that long noncoding RNAs (lncRNAs) are involved in systemic lupus erythematosus (SLE). The level of NR_103776.1 expression in SLE and its clinical associations are still not well defined. To identify differentially expressed lncRNAs and explore their functional roles in SLE. Transcriptome sequencing was used to screen differentially expressed lncRNAs and mRNAs. Expression validation of clinical samples was performed by QRT-PCR. Bioinformatics was used to analyze its prognostic value and potential function. Of the 231 significantly differentially expressed lncRNAs, NR_103776.1 could be used to distinguish not only SLE patients and rheumatoid arthritis patients but also active SLE patients, stable SLE patients, and healthy controls. NR_103776.1 was significantly and negatively correlated with inflammatory indexes (CRP and ESR). NR_103776.1 dysregulation might contribute to the metabolism of RNA and proteins in SLE patients. This study not only provided a transcriptome profile of lncRNAs aberrantly expressed in individual nucleated cells of SLE patients but also suggested NR_103776.1 as a novel potential diagnostic biomarker.

Exploring the potential common denominator pathogenesis of system lupus erythematosus with COVID-19 based on comprehensive bioinformatics analysis.

Evidences show that there may be a link between SLE and COVID-19. The purpose of this study is to screen out the diagnostic biomarkers of systemic lupus erythematosus (SLE) with COVID-19 and explore the possible related mechanisms by the bioinformatics approach. SLE and COVID-19 datasets were extracted separately from the NCBI Gene Expression Omnibus (GEO) database. The limma package in R was used to obtain the differential genes (DEGs). The protein interaction network information (PPI) and core functional modules were constructed in the STRING database using Cytoscape software. The hub genes were identified by the Cytohubba plugin, and TF-gene together with TF-miRNA regulatory networks were constructed via utilizing the Networkanalyst platform. Subsequently, we generated subject operating characteristic curves (ROC) to verify the diagnostic capabilities of these hub genes to predict the risk of SLE with COVID-19 infection. Finally, a single-sample gene set enrichment (ssGSEA) algorithm was used to analyze immune cell infiltration. A total of 6 common hub genes (CDC6, PLCG1, KIF15, LCK, CDC25C, and RASGRP1) were identified with high diagnostic validity. These gene functional enrichments were mainly involved in cell cycle, and inflammation-related pathways. Compared to the healthy controls, abnormal infiltration of immune cells was found in SLE and COVID-19, and the proportion of immune cells linked to the 6 hub genes. Our research logically identified 6 candidate hub genes that could predict SLE complicated with COVID-19. This work provides a foothold for further study of potential pathogenesis in SLE and COVID-19.

Agomir miRNA-150-5p alleviates pristane-induced lupus by suppressing myeloid dendritic cells activation and inflammation via TREM-1 axis.

Triggering receptors expressed on myeloid cells-1 (TREM-1) has been shown to participate in inflammatory autoimmune diseases. Nevertheless, the detailed underlying mechanisms and therapeutic benefits by targeting TREM-1 remain elusive, especially in myeloid dendritic cells (mDCs) and systemic lupus erythematosus (SLE). Disorders of epigenetic processes including non-coding RNAs give rise to SLE, resulting in complicated syndromes. Here, we aim to address this issue and explore the miRNA to inhibit the activation of mDCs and alleviate the progress of SLE by targeting TREM-1 signal axis. Bioinformatics methods were used to analyze the differentially expressed genes (DEGs) between patients with SLE and healthy individuals by four mRNA microarray datasets from Gene Expression Omnibus (GEO). Then we identified the expression of TREM-1 and its soluble form (sTREM-1) in clinical samples by ELISA, quantitative real-time PCR and Western blot. Phenotypic and functional changes of mDCs elicited by TREM-1 agonist were determined. Three databases of miRNAs target prediction and a dual-luciferase reporter assay were used to screen and verify miRNAs that can directly inhibit TREM-1 expression in vitro. Moreover, pristane-induced lupus mice were injected with miR-150-5p agomir to evaluate the effects of miR-150-5p on mDCs in lymphatic organs and disease activity in vivo. We screened TREM-1 as one of the hub genes closely correlated with the progression of SLE and identified sTREM-1 in serum as a valuable diagnostic biomarker for SLE. Moreover, activation of TREM-1 by its agonist promoted activation and chemotaxis of mDCs and increased the production of inflammatory cytokines and chemokines, showing higher expression of IL-6, TNF-α, and MCP-1. We showed that lupus mice displayed a unique miRNA signature in spleen, among which miR-150 was the most significantly expressed miRNA that targeting TREM-1 compared with wild type group. Transfection of miRNA-150-5p mimics directly suppressed the expression of TREM-1 by binding to its 3' UTR. Our in vivo experiments first indicated that administration of miR-150-5p agomir effectively ameliorated lupus symptoms. Intriguingly, miR-150 inhibited the over activation of mDCs through TREM-1 signal pathway in lymphatic organs and renal tissues. TREM-1 represents a potentially novel therapeutic target and we identify miR-150-5p as one of the mechanisms to alleviate lupus disease, which is attributable for inhibiting mDCs activation through TREM-1 signaling pathway.

Immune Phenotype as a Biomarker for Systemic Lupus Erythematosus.

The treatment of rheumatoid arthritis was revolutionized with the use of molecular-targeted drugs that target immunoregulatory molecules. The success of treatment with these drugs prompted the development of molecular-targeted drugs for systemic lupus erythematosus. However, systemic lupus erythematosus is a disease with high heterogeneous immune abnormalities, and diverse cells or molecules can be treatment targets. Thus, the identification of subpopulations based on immune abnormalities is essential for the development of effective treatment. One analytical method used to identify subpopulations is the immunophenotyping of peripheral blood samples of patients. This analysis evaluates the validity of target molecules for peripheral blood immune cell subsets, which are expected to be developed as biomarkers for precision medicine in which appropriate treatment targets are set for each subpopulation.

Inflammation-based biomarkers for the prediction of nephritis in systemic lupus erythematosus

Background/Aim: Inflammation is a crucial component in the pathophysiology of systemic lupus erythematosus (SLE) nephritis. Immune-based scores, such as the neutrophil-lymphocyte and the platelet-lymphocyte ratios (NLR and PLR, respectively) have been suggested as predictors of inflammation and prognosis in SLE. This study aimed to investigate the value of the systemic immune-inflammation index (SII), inflammatory prognostic index (IPI), and systemic inflammatory response index (SIRI) in SLE and lupus nephritis (LN). Methods: This case-control study consisted of 108 newly diagnosed SLE patients (separated into two subgroups, which included 34 patients with biopsy-proven LN and 74 without nephritis) and 108 age- and gender-matched healthy controls who presented to our outpatient clinic between October 2015 and June 2020. Patients with malignancy, lymphoproliferative and hematologic disorders, active infection, and autoimmune diseases other than SLE were excluded. Inflammation-based biomarkers were calculated at the first presentation of the disease and before any medication was administered. SII was calculated as Neutrophil/Lymphocyte x Platelet, SIRI as Neutrophil x Monocyte/Lymphocyte, and IPI as CRP x NLR/serum albumin. The Systemic Lupus Erythematosus Disease Activity Index 2000 (SLEDAI-2K) was used to measure disease activity. The capability of SII, SIRI, NLR, PLR, and IPI to distinguish between SLE patients with or without nephritis was assessed using receiver operating characteristic (ROC) curves. Correlations of inflammation-based scores (SII, SIRI, IPI, NLR) with disease activity and laboratory data of SLE patients were analyzed. Results: SII, SIRI, and IPI were significantly higher in SLE patients than in healthy controls (P=0.003, P=0.019, and P&lt;0.001, respectively) and also significantly higher in patients with nephritis than in those without (P&lt;0.001, P=0.009, and P=0.007, respectively). The area under the curve (AUC) for SII, SIRI, and IPI in terms of differentiating SLE patients with or without nephritis was 0.748, 0.690, and 0.663, respectively. The cut-off value of SII, SIRI, and IPI to predict LN was 552.25 (sensitivity: 64.7%; specificity: 64.9%; P&lt;0.001), 1.08 (sensitivity: 61.8%; specificity: 62.2%; P=0.002), and 4.48 (sensitivity: 61.8%; specificity, 62.2%; P=0.007), respectively. Conclusion: SII, SIRI, and IPI may be valuable and promising inflammation-based biomarkers in SLE and for the presence of nephritis in SLE patients. SII was found to be the most reliable predictor of SLE among the inflammation-based biomarkers in our study.

Role of autotaxin in systemic lupus erythematosus.

Systemic lupus erythematosus (SLE) is a prototypic systemic autoimmune disease characterized by the production of various autoantibodies and deposition of immune complexes. SLE is a heterogenous disease, and the pattern of organ involvement and response to treatment differs significantly among patients. Novel biological markers are necessary to assess the extent of organ involvement and predict treatment response in SLE. Lysophosphatidic acid is a lysophospholipid involved in various biological processes, and autotaxin (ATX), which catalyzes the production of lysophosphatidic acid in the extracellular space, has gained attention in various diseases as a potential biomarker. The concentration of ATX is increased in the serum and urine of patients with SLE and lupus nephritis. Recent evidence suggests that ATX produced by plasmacytoid dendritic cells may play an important role in the immune system and pathogenesis of SLE. Furthermore, the production of ATX is associated with type I interferons, a key cytokine in SLE pathogenesis, and ATX may be a potential biomarker and key molecule in SLE.

Salivary IgA subtypes as novel disease biomarkers in systemic lupus erythematosus.

Immunoglobulin A (IgA) is the main antibody isotype in body fluids such as tears, intestinal mucous, colostrum, and saliva. There are two subtypes of IgA in humans: IgA1, mainly present in blood and mucosal sites, and IgA2, preferentially expressed in mucosal sites like the colon. In clinical practice, immunoglobulins are typically measured in venous or capillary blood; however, alternative samples, including saliva, are now being considered, given their non-invasive and easy collection nature. Several autoimmune diseases have been related to diverse abnormalities in oral mucosal immunity, such as rheumatoid arthritis, Sjogren's syndrome, and systemic lupus erythematosus (SLE). We decided to evaluate the levels of both IgA subtypes in the saliva of SLE patients. A light chain capture-based ELISA measured specific IgA1 and IgA2 levels in a cohort of SLE patients compared with age and gender-matched healthy volunteers. Surprisingly, our results indicated that in the saliva of SLE patients, total IgA and IgA1 subtype were significantly elevated; we also found that salivary IgA levels, particularly IgA2, positively correlate with anti-dsDNA IgG antibody titers. Strikingly, we also detected the presence of salivary anti-nucleosome IgA antibodies in SLE patients, a feature not previously reported elsewhere. According to our results and upon necessary validation, IgA characterization in saliva could represent a potentially helpful tool in the clinical care of SLE patients with the advantage of being a more straightforward, faster, and safer method than manipulating blood samples.

Complement as a Biomarker for Systemic Lupus Erythematosus.

Systemic lupus erythematosus (SLE) is a disease of immune complex deposition; therefore, complement plays a vital role in the pathogenesis of SLE. In general, complement levels in blood and complement deposition in histological tests are used for the management of SLE. Thus, the evaluation of complement status can be useful in the diagnosis of SLE, assessment of disease activity, and prediction of treatment response and prognosis. In addition, novel complement biomarkers, such as split products and cell-bound complement activation products, are considered to be more sensitive than traditional complement markers, such as serum C3 and C4 levels and total complement activity (CH50), which become more widely used. In this review, we report the complement testing in the management of SLE over the last decade and summarize their utility.

Alterations in the human oral microbiota in systemic lupus erythematosus

BackgroundAlterations in oral microbiota in patients with systemic lupus erythematosus (SLE) is less evaluated. The aim of this study was to compare the characteristics of the oral microbiome in SLE patients and healthy controls, and construct an SLE classifier based on the oral microbiota.MethodsWe sequenced tongue-coating samples of individuals in treatment-naïve SLE (n = 182) and matched healthy controls (n = 280). We characterized the oral microbiome and constructed a microbial classifier in the derivation cohort and validated the results in the validation cohorts. Furthermore, the oral microbiome of posttreatment SLE (n = 73) was characterized.ResultsThe oral microbial diversity of SLE was increased, and the microbial community was different between SLE and healthy controls. The genera Prevotella and Veillonella were enriched, while Streptococcus and Porphyromonas were reduced in SLE. In addition, an increase was noted in 27 predicted microbial functions, while a decrease was noted in 34 other functions. Thirty-nine operational taxonomy units (OTUs) were identified to be related with seven clinical indicators. Two OTUs were identified to construct a classifier, which yielded area under the curve values of 0.9166 (95% CI 0.8848–0.9483, p < 0.0001), 0.8422 (95% CI 0.7687–0.9157, p < 0.0001), and 0.8406 (95% CI 0.7677–0.9135, p < 0.0001) in the derivation, validation, and cross-regional validation groups, respectively. Moreover, as disease activity increased, Abiotrophia and Lactobacillales increased, while Phyllobacterium and unclassified Micrococcusaceae decreased. Finally, nine OTUs were selected to construct a classifier distinguishing posttreatment SLE patients from healthy controls, which achieved a diagnostic efficacy of 0.9942 (95% CI 0.9884–1, p < 0.0001).ConclusionsOur study comprehensively characterizes the oral microbiome of SLE and shows the potential of the oral microbiota as a non-invasive diagnostic biomarker in SLE.

Integrative Bioinformatics Analysis Identifies DDX60 as a Potential Biomarker for Systemic Lupus Erythematosus.

Systemic lupus erythematosus (SLE) is an autoimmune disease with strong heterogeneity, leading to variable clinical symptoms, which makes diagnosis and activity evaluation difficult. The original dataset of GSE88884 was analyzed to screen differentially expressed genes (DEGs) of SLE and the correlation between DEGs and clinical parameters (SLEDAI, anti-dsDNA, C3, and C4). The result was validated by microarray GSE121239 and SLE patients with RT-qPCR. Next, receiver operator characteristic (ROC) analysis, correlation analysis, and ordinal logistic regression were applied, respectively, to evaluate the capability of diagnosis and prediction of the candidate biomarker. Subsequently, the biological functions of the candidate biomarker were investigated through KEGG and GO enrichment, protein-protein interaction network, and the correlation matrix. A total of 283 DEGs were screened, and seven of them were overlapped with SLE-related genes. DDX60 was identified as the candidate biomarker. Analyses of GSE88884, GSE121239, and SLE patients with RT-qPCR indicated that DDX60 expression level is significantly higher in patients with high disease activity. ROC analysis and the area under the ROC curve (AUC = 0.8818) suggested that DDX60 has good diagnostic performance. DDX60 expression level was positively correlated with SLEDAI scores (r = 0.24). For every 1-unit increase in DDX60 expression value, the odds of a higher stage of activity of SLE disease are multiplied by 1.47. The function of DDX60 mainly focuses on IFN-I-induced antiviral activities, RIG-I signaling, and innate immune. Moreover, DDX60 plays a synergistic role with DDX58, IFIH1, OASL, IFIT1, and other related genes in the SLE pathogenesis. Conclusions. DDX60 is differently expressed in SLE, and it is significantly related to both serological indicators and the disease activity of SLE. We suggested that DDX60 might be a potential biomarker for SLE diagnosis and management.

Identification of potential biomarkers for systemic lupus erythematosus by integrated analysis of gene expression and methylation data.

Systemic lupus erythematosus (SLE) is a heterogeneous and chronic autoimmune disease. Aberrant DNA methylation occurs during various processes of SLE development regulating the mRNA expression of interrelated genes. This study aims to screen potential DNA methylation markers for SLE. Gene expression and methylation datasets were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) between SLE patients and healthy controls were screened using the limma R package, and differentially methylated positions (DMPs) and regions (DMRs) were identified using dmpfinder and bumphunter (minfi). Additionally, the DNA methylation markers to distinguish SLE patients from healthy controls were explored through receiver operating characteristic (ROC) curves and logistic regression analyses. Finally, we validated the results of the bioinformatic analysis by pyrosequencing. In total, 91 DEGs, 90,092 DMPs, 15 DMRs, and 13 DMR-associated genes were identified. Through the integrative analysis of DEG- and DMR-associated genes, we identified five type I interferon (IFN)-related genes as key epigenetic-driven genes in SLE. GO enrichment analysis showed that the five SLE-associated epigenetic-driven genes were mainly enriched in the type I IFN signaling pathway involved in immune response and defense response to virus. Moreover, we identified two SLE-specific DNA methylation markers, three SLE without lupus nephritis (SLE-LN-)-specific DNA methylation markers, and two SLE with lupus nephritis (SLE-LN+)-specific DNA methylation markers by stepwise logistic regression. Overall, our study demonstrates potential DNA methylation markers of SLE, SLE-LN-, and SLE-LN+, which may help the diagnosis, boost the development of new epigenetic therapy, and contribute to individualized treatment. Key Points • This study identified five type I IFN-related genes as key epigenetic-driven genes in SLE, which support the importance of the type I IFN pathway in the pathogenesis of SLE • We identified novel DNA methylation biomarkers in SLE, SLE-LN-, and SLE-LN+ by a comprehensive analysis of bioinformatics methods and executed experimental validation, and binary logistic regression analysis showed that they have excellent potential • These results may provide new insights into the biological mechanisms of SLE, and identify reliable biomarkers for SLE, SLE-LN-, and SLE-LN+, which may contribute to diagnosis and individualized treatment.

LABORATORY BIOMARKERS FOR SYSTEMIC LUPUS ERYTHEMATOSUS

The development of innovative technologies using mono- and multiplex methods of immune analysis contributed to an increase in the sensitivity and specificity of laboratory tests and a significant expansion of the range of laboratory biomarkers of systemic lupus erythematosus (SLE). The article presents modern aspects of laboratory diagnosis of SLE. Screening and confirmatory methods for the study of antinuclear antibodies (ANA), the main immunological marker of SLE, are considered in detail. New classification criteria for SLE are discussed (EULAR/ACR, 2019), which for the first time single out “seropositivity” for the antinuclear factor as a mandatory “incoming” criterion that allows diagnosing the disease as SLE. The characteristics of clinical and laboratory subtypes of SLE associated with the detection of various autoantibodies in serum (antibodies to dsDNA, histones, nucleosomes, Sm, Ro/SSA and La/SSB, U1 ribonucleoprotein,ribosomal protein P, antiphospholipid antibodies, antibodies to C1q) are given. The diagnostic value of defects in the components of the complement system in SLE is indicated. The relationship between ANA and cytokine profiles in SLE patients using multiplex immunoassay of these biomarkers based on xMAP microarray technology is described. It has been shown that the formation of ANA and high activity of SLE are associated with overexpression of the IP-10 and MCP-1 chemokines induced by IFN. The clinical and pathogenetic significance of subpopulations of B-lymphocytes and CD4+ CD25high+ FoxP3+ regulatory T-cells (Treg) of peripheral blood in SLE was noted. SLE is characterized by an increase in the number of double negative memory B cells (CD19+ CD27-IgD-) and plasma cells, a decrease in the levels of naive and transitional B cells in the blood. A positive correlation was found between the number of double negative B cells and the activity of SLE and ESR. The effect of therapy with genetically engineered biological agents (rituximab and belimumab) on B-cell subpopulations in patients with SLE was analyzed. The decrease in the number of Tregs is most pronounced in patients with an acute variant of the course of the disease, high activity of the pathological process, hyperproduction of IgG and expansion of autoreactive B-cells. The study of modern molecularcellular biomarkers allows diagnosing, assessing activity, the nature of the course, clinical and laboratory subtypes of SLE, and predicting the effectiveness of therapy for this disease at a qualitatively new level.

Serum miR-342-3p Acts as a Biomarker for Systemic Lupus Erythematosus and Participates in the Disease Progression

The aim of this study was to investigate the diagnostic ability and prognostic value of miR-342-3p in SLE patients by detecting the expression level of serum miR-342-3p in SLE patients. The expression level of serum miR-342-3p in all subjects was determined by qRT-PCR technology, and the correlation of miR-342-3p with SLEDAI scores was evaluated using Spearman correlation coefficient. The diagnostic value of miR-342-3p in SLE was assessed using ROC curve. The prognostic value of miR-342-3p in SLE patients was analyzed by Kaplan-Meier survival curve and multivariate COX regression. The qRT-PCR results showed that the expression level of serum miR-342-3p in SLE patients was significantly lower than that in healthy controls (P < 0.001). Serum miR-342-3p expression level was negatively correlated with SLEDAI scores (r = - 0.810, P < 0.001). The ROC curve suggested that serum miR-342-3p expression level was discriminative between SLE patients and healthy controls. Survival analysis results indicated that SLE patients with low serum miR-342-3p expression had a higher probability of poor prognosis of SLE (Log rank P = 0.003). The expression level of serum miR-342-3p was valuable in the diagnosis of SLE. Meanwhile, the low expression level of serum miR-342-3p was associated with the poor prognosis of SLE.