Biomarkers For Systemic Lupus Erythematosus Research Articles

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.

Significance of Interleukin 23 in Systemic Lupus Patients: Relation to Disease Activity and Damage Indices

Dysregulation of both cellular and humoral immune responses is central in systemic lupus erythematosus (SLE) pathogenetic mechanisms. Proinflammatory cytokines, such as interleukin 23 (IL23), and their roles in promoting such dysregulation have recently been highly considered. This research compared IL23 serum levels in 85 Egyptian SLE patients and 85 healthy controls. Then, IL23 level was correlated to various SLE disease parameters, disease activity, and damage indices. IL23 serum levels were significantly elevated in SLE patients versus healthy individuals. Furthermore, IL23 levels were positively correlated with SLE disease activity index (SLEDAI) and were positively correlated with arthritis, seizures, consumption of complements (C3, C4), and with parameters of nephritis (hematuria, pyuria, casts, and proteinuria). A positive correlation was also found between IL23 levels and oral prednisolone dose. IL23 has higher levels in the serum of SLE patients, and is correlated to activity of the disease, especially lupus nephritis. Further researchis needed to explore its exact role in SLE pathogenesis and whether it can be considered a potential biomarker or therapeutic target in SLE.

Lupus, DNA Methylation, and Air Pollution: A Malicious Triad.

The pathogenesis of systemic lupus erythematosus (SLE) remains elusive to this day; however, genetic, epigenetic, and environmental factors have been implicated to be involved in disease pathogenesis. Recently, it was demonstrated that in systemic lupus erythematosus (SLE) patients, interferon-regulated genes are hypomethylated in naïve CD4+ T cells, CD19+ B lymphocytes, and CD14+ monocytes. This suggests that interferon-regulated genes may have been epigenetically poised in SLE patients for rapid expression upon stimulation by different environmental factors. Additionally, environmental studies have identified DNA (hypo)methylation changes as a potential mechanism of environmentally induced health effects in utero, during childhood and in adults. Finally, epidemiologic studies have firmly established air pollution as a crucial SLE risk factor, as studies showed an association between fine particulate matter (PM2.5) and traditional SLE biomarkers related to disease flare, hospital admissions, and an increased SLEDAI score. In this review, the relationship between aberrant epigenetic regulation, the environment, and the development of SLE will be discussed.

Urine Biomarkers of Systemic Lupus Erythematosus Identified Using Liquid and Gas Chromatography/Mass Spectrometry (LC-QTOF-MS and GC-QTOF-MS)

Urine Biomarkers of Systemic Lupus Erythematosus Identified Using Liquid and Gas Chromatography/Mass Spectrometry (LC-QTOF-MS and GC-QTOF-MS)

The Expression of Mirnas in Sudanese Patients with Systemic Lupus Erythematosus in Khartoum State

Background: MicroRNAs (miRs) are noncoding gene regulators that may have a role as diagnostic or prognostic biomarkers in systemic lupus erythematosus (SLE). Aim: To measure the blood levels of miR-146a, miR-126 and miR-30a in Sudanese SLE patients and to investigate their potential role in disease pathogenesis and utility as biomarkers for SLE. Material and Methods: A total of 48 SLE patients and 20 matched healthy individuals were enrolled in this study. SLE disease activity index (SLEDAI) was assessed. The blood levels of miR-146a, miR-126 and miR-30a were determined by Real-time polymerase chain reaction (PCR) in all participants. For γ-INF and IL-2 were analyzed by ELISA, and CD markers were used flowcytometery. Results: The mean age of the patients was 31.5 ± 8.5 years with disease duration &gt;5 years. In SLE patients, the mean blood level fold changes of miR-146a (0.33±0.277; P&lt;0.001), miR-126 (2.44±1.771; P=0.007) and miR-30a (1.56±1.40; P &gt;0.305) compared to controls. Down regulation of miR-146a increase expression of γ-INF (p &lt; 0.002), whereas the up regulation of miR-126 increase expression of CD markers (p&lt;0.000) in SLE patients. MiR-126 at a cut-off value 1.209 and miR-146a at cut-off value 0.9233 which can discriminate between SLE patients with significantly associated to SLE disease. Conversely, miR-30a was insignificantly associated with SLE disease (p value &gt;0.05) as no differences between the SLE patients and healthy control. Conclusion: Circulating miR-146a and miR-126 could be a potential noninvasive biomarker in SLE. This study providing an overview of the current state of research on the role of miRNAs in the immune pathogenesis and regulation of SLE. Further studies are needed in miRNAs profiling expressions of SLE diseases.

Semaphorin 4A as a Potential Biomarker for Diagnosis of Systemic Lupus Erythematosus

ABSTRACT Background Semaphorin 4A (Sema4A) is an immunoregulatory molecule that is closely related to the pathogenesis of some autoimmune diseases. However, the relationship between Sema4A and systemic lupus erythematosus (SLE) remains unknown. We therefore aimed to investigate the expression and clinical value of Sema4A in SLE patients. Methods Patients with SLE, rheumatoid arthritis (RA), and healthy controls (HC) were enrolled. The whole blood samples were collected from SLE (83), RA (29) and HC (85), and the expression of Sema4A on several types of leukocytes in peripheral blood was detected by flow cytometry. The serum samples were collected from SLE(77), RA (23) and HC (63), and the concentrations of soluble Sema4A in plasma were detected by ELISA. The diagnostic value of membrane-bound and soluble Sema4A in SLE patients was evaluated using a receiver operating characteristic (ROC) curve. Results The concentration of soluble Sema4A was significantly higher in plasma from SLE patients compared to that from HC and RA patients. In SLE patients, the ratio of CD4+CD11c+ myeloid dendritic cells (mDCs) expressing Sema4A increased significantly, and the levels of soluble Sema4A and membrane-bound Sema4A were negatively correlated with the levels of C3 and C4, respectively. The same result was observed for membrane-bound Sema4A on CD4+CD11c+ mDCs cells. In addition, the level of soluble Sema4A negatively correlated with the concentration of hemoglobin (Hb). Importantly, the expression ratio of membrane-bound Sema4A on CD4+CD11c+ mDCs was positively correlated with systemic lupus erythematosus disease activity index (SLEDAI). Finally, we revealed that soluble and membrane- bound Sema4A had high sensitivity and specificity for diagnosis of SLE, and had a greater ability to distinguish between SLE and RA. Conclusion Sema4A has potential as a new diagnostic biomarker for SLE, and is promising for distinguishing between SLE and RA.

Circular RNA expression profile of systemic lupus erythematosus and its clinical significance as a potential novel biomarker

BackgroundCircular RNAs (circRNAs) are a class of endogenous noncoding RNAs that are more abundant, specific, and highly organized than linear RNAs. Increasing evidence supports that circRNAs may serve as diagnostic biomarkers in many diseases, but their potential as biomarkers in systemic lupus erythematosus (SLE) remains unclear.ObjectiveWe investigated the critical circRNAs involved in SLE progression and explored their potential application as biomarkers in SLE.MethodRNA sequencing was conducted on peripheral blood mononuclear cells (PBMCs) from 4 SLE patients and 4 healthy volunteers. CircRNA profile data were analyzed to identify differentially expressed circRNAs and visualized via R software. After screening, qPCR analysis of target circRNA expression was performed using PBMCs from 31 SLE patients and 35 healthy volunteers. Correlations between circRNA expression levels and the SLEDAI score were assessed via Spearman correlation analysis. Finally, the performance of circRNAs as biomarkers in SLE was examined by receiver operating characteristic curve analysis.ResultsThe result identified six differentially expressed circRNAs between SLE patients and healthy controls: hsa_circ_0006689, hsa_circ_0070562, hsa_circ_0006117, hsa_circ_0007683, hsa_circ_0042519, and hsa_circ_0008647. The validation analysis showed differing relative expression levels of hsa_circ_0007683, hsa_circ_0042519, hsa_circ_0008647, and hsa_circ_0006689 between SLE patients and healthy volunteers (P < 0.05), and hsa_circ_0006689 expression in PBMCs correlated with the SLEDAI score (P < 0.05). Furthermore, addition of hsa_circ_0006689 expression increased the sensitivities of anti-dsDNA antibody and anti-Sm antibody levels for SLE diagnosis (from 29.03 to 61.30% and 32.26–71.00%, respectively).ConclusionOur results suggest hsa_circ_0006689 may be a useful circRNA biomarker for SLE diagnosis and prognosis.

Performance analysis of Luminex and ELISA to profile serum IP-10 as a biomarker in systemic lupus erythematosus.

Interferon-γ inducible protein-10 (IP-10) is a promising biomarker in systemic lupus erythematosus (SLE). The optimal quantification platform has not yet been identified. We compared the performance of bead-based multiplex assay (Luminex) and high-sensitivity enzyme-linked immunosorbent assay (hs-ELISA) for profiling serum IP-10 as a biomarker of lupus activity. A cross-sectional study was conducted on outpatients with SLE. Serum IP-10 was measured simultaneously on Luminex and hs-ELISA, and correlation between platforms was assessed. Additionally, IP-10 levels were tested against disease activity and organ involvement. One-hundred and forty-one patients (88% women; 38 years old) were studied. Median IP-10 levels were 100.9 (125.2) pg/mL by Luminex and 156.5 (191.7) pg/mL by hs-ELISA. Correlation analysis showed Spearman's ρ = 0.621 (p < 0.0001) between Luminex and hs-ELISA. Quantification of IP-10 by Luminex showed a significant correlation (ρ = 0.198; p = 0.021) with disease activity, while this was not observed (ρ = 0.036; p = 0.683) when measured using hs-ELISA. Serum IP-10 levels were lower in quiescent patients than in those with active disease (70.8 [68.4] versus 114.3 [123.9] pg/mL; p = 0.024), with an AUC-ROC = 0.62 (p = 0.029), sensitivity = 47.9%, specificity = 77.5%, and positive likelihood ratio = 2.1. Patients with active arthritis had higher IP-10 levels than non-arthritis patients (158.1 [505.4] versus 94.1 [114.0] pg/mL; p = 0.008), with an AUC-ROC = 0.73 (p = 0.0009), sensitivity = 72.7%, specificity = 66.4%, and positive likelihood ratio = 2.1. No other type of organ involvement was identified by serum IP-10. Luminex performs better than hs-ELISA as a quantification platform for IP-10 as it correlates with disease activity and identifies active arthritis in SLE.

MX2: Identification and systematic mechanistic analysis of a novel immune-related biomarker for systemic lupus erythematosus.

BackgroundSystemic lupus erythematosus (SLE) is an autoimmune disease that involves multiple organs. However, the current SLE-related biomarkers still lack sufficient sensitivity, specificity and predictive power for clinical application. Thus, it is significant to explore new immune-related biomarkers for SLE diagnosis and development.MethodsWe obtained seven SLE gene expression profile microarrays (GSE121239/11907/81622/65391/100163/45291/49454) from the GEO database. First, differentially expressed genes (DEGs) were screened using GEO2R, and SLE biomarkers were screened by performing WGCNA, Random Forest, SVM-REF, correlation with SLEDAI and differential gene analysis. Receiver operating characteristic curves (ROCs) and AUC values were used to determine the clinical value. The expression level of the biomarker was verified by RT‒qPCR. Subsequently, functional enrichment analysis was utilized to identify biomarker-associated pathways. ssGSEA, CIBERSORT, xCell and ImmuCellAI algorithms were applied to calculate the sample immune cell infiltration abundance. Single-cell data were analyzed for gene expression specificity in immune cells. Finally, the transcriptional regulatory network of the biomarker was constructed, and the corresponding therapeutic drugs were predicted.ResultsMultiple algorithms were screened together for a unique marker gene, MX2, and expression analysis of multiple datasets revealed that MX2 was highly expressed in SLE compared to the normal group (all P < 0.05), with the same trend validated by RT‒qPCR (P = 0.026). Functional enrichment analysis identified the main pathway of MX2 promotion in SLE as the NOD-like receptor signaling pathway (NES=2.492, P < 0.001, etc.). Immuno-infiltration analysis showed that MX2 was closely associated with neutrophils, and single-cell and transcriptomic data revealed that MX2 was specifically expressed in neutrophils. The NOD-like receptor signaling pathway was also remarkably correlated with neutrophils (r >0.3, P < 0.001, etc.). Most of the MX2-related interacting proteins were associated with SLE, and potential transcription factors of MX2 and its related genes were also significantly associated with the immune response.ConclusionOur study found that MX2 can serve as an immune-related biomarker for predicting the diagnosis and disease activity of SLE. It activates the NOD-like receptor signaling pathway and promotes neutrophil infiltration to aggravate SLE.

The potential role of serum expression profile of long non coding RNAs, Cox2 and HOTAIR as novel diagnostic biomarkers in systemic lupus erythematosus.

BackgroundThe role of the long non-coding RNAs (lncRNAs) in the pathogenesis of systemic lupus erythematosus (SLE) is mostly unknown, despite increasing evidence that lncRNAs extensively participate in physiological and pathological conditions.AimTo detect the level of lncRNA-Cox2, HOTAIR, IL-6, and MMP-9 in the serum of SLE patients and to correlate these levels with disease activity and patients’ clinical and laboratory data to evaluate the value of these biomarkers for SLE diagnosis and assessment of disease activity.MethodsBlood samples from 58 SLE patients, and 60 healthy controls (HCs) were used for detection of lncRNAs-Cox2 and HOTAIR expression levels by real-time polymerase chain reaction. Both IL-6 and MMP-9 serum levels were assayed by enzyme-linked immunosorbent assay. Lupus activity was assessed with the Systemic Lupus Erythematosus Disease Activity Index (SLEDAI).ResultsThe serum expression levels of lncRNA-Cox2 and HOTAIR were significantly up-regulated in SLE patients vs HCs (fold change [median (IQR) was 1.29(0.81–1.71, P<0.0001) and 2.68(0.95–3.67), P = 0.038) for lncRNA-Cox2 and HOTAIR, respectively. Serum levels of both IL-6 and MMP-9 were significantly high in SLE patients compared with HCs (P≤0.001 for each). The up-regulated lncRNA-Cox2 was positively associated with the presence of neurological manifestations in SLE patients (P = 0.007). Furthermore, HOTAIR expression level had significantly positive correlation with IL-6 (r = 0.578, P<0.0001), MMP-9 level (r = 0.762, P<0.0001), nephritis grades (r = 0.296, P = 0.024) and proteinuria (r = 0.287, P = 0.035). LncRNA-Cox2 showed sensitivity and specificity 72.4%, and 100.0% respectively. HOTAIR sensitivity was 60.3%, and specificity was 100.0%. By multiple logistic regression analysis, lncRNA-Cox2 and HOTAIR were found as SLE independent predictors.ConclusionLncRNA-COX2 and HOTAIR can be used as new non-invasive biomarkers for the diagnosis of SLE.

TMT-based quantitative proteomics analysis and potential serum protein biomarkers for systemic lupus erythematosus

Systemic lupus erythematosus (SLE) was not only a typical systemic autoimmune disease, but also one of the most challenging heterogeneous diseases for physicians. Currently, the pathogenesis of SLE was unclear, and there were no accurate, universal or easy-to-use diagnostic criteria for assessing SLE activity and predicting SLE severity. Proteins were direct effectors of biological mechanisms, and were closer to clinical phenotypes than the other discovered biomarkers. Moreover, proteins were widely used as biomarkers for clinical diagnosis and mechanism research of many diseases. Herein, we compared the proteins profiles of healthy individuals (HCs) and SLE patients to reveal the pathogenesis and provide evidence for diagnosis and management of persons with SLE. Serum samples were collected from 28 SLE patients and 30 HCs. Tandem mass tag (TMT)-based quantitative proteomics method was used to identify, screen and detect differentially expressed proteins (DEPs) in the collected serum samples. A total of 744 proteins were identified, and 84 of them were considered as DEPs with 71 upregulated and 13 downregulated. Bioinformatics analysis suggested that these DEPs were mainly involved in many biological processes, including immune response, signal transduction, inflammatory response, proteolysis, innate immune response and apoptosis, which were closely related to the pathogenesis of SLE. After comprehensive analysis, serum amyloid A1 (SAA1) and endothelin (CD248) were identified as specific biomarkers for the diagnosis of SLE, and were confirmed by subsequent enzyme-linked immunosorbent assays (ELISA), indicating a high reliability of TMT-based quantitative proteomics results. Areas under the ROC curve (AUC) results confirmed that SAA1 and CD248 combination as early immune diagnosis biomarkers of SLE presented excellent sensitivity and specificity.

Identification of Key Biomarkers in Systemic Lupus Erythematosus by a Multi-Cohort Analysis.

Systemic lupus erythematosus (SLE) is an autoimmune disease that affects multiple body systems with heterogeneous clinical manifestations. Since gene expression analyses have been accomplished on diverse types of samples to specify SLE-related genes, single-cohort transcriptomics have not produced reliable results. Using an integrated multi-cohort analysis framework, we analyzed whole blood cells from SLE patients from three transcriptomics cohorts (n=1222) and identified a five-gene signature that distinguished SLE patients from controls. We validated the diagnostic performance of this five-gene signature in six independent validation cohorts (n= 469), with an area under the receiver operating characteristic curve of 0.88 [95% CI 0.7 − 0.96]. This five-gene signature may be associated with the proportion of SLE immune cells, and generalizable across ages and sample types with real diagnostic value for clinical application.

Significance of circRNAs as biomarkers for systemic lupus erythematosus: a systematic review and meta-analysis.

ObjectiveTo comprehensively evaluate the significance of circular RNAs (circRNAs) as potential diagnostic biomarkers for systemic lupus erythematosus (SLE) via pooled analyses of data from published studies that focussed on the association between circRNAs and SLE.MethodsThe systematic review and meta-analysis protocol was registered in PROSPERO (registration No. CRD42021229383). Relevant studies published before 3 April 2022 were selected to verify the relationship between circRNA expression levels and SLE. Extracted data were analysed using a random-effects model with Meta-DiSc 1.4 and Stata 16 software. Transcription factors related to hsa_circ_0000479 and its parental gene were extracted from the TRCirc and hTFtarget databases, respectively.ResultsA total of 10 studies, involving 438 patients with SLE and 434 controls, were included in the meta-analysis. The pooled sensitivity, specificity, and diagnostic odds ratio of circRNAs in detecting SLE were 0.66 (95% confidence interval [CI] 0.63, 0.70), 0.79 (95% CI 0.76, 0.82), and 10.80 (95% CI 6.58, 17.73), respectively. The area under the summary receiver operating characteristic curve was 0.8366.ConclusionsMeta-analysis of pooled data indicated a moderate accuracy of circRNAs in diagnosing SLE. The exact diagnostic value of circRNAs and the mechanisms of interaction between circRNAs and their parental genes should be confirmed in further studies.