Gene expression analysis delineates the potential roles of multiple interferons in systemic lupus erythematosus

Examination of the shared genetic architecture between multiple sclerosis and systemic lupus erythematosus facilitates discovery of novel lupus risk loci

Systemic Lupus Erythematosus (SLE) is an autoimmune disease with heterogeneous manifestations, including neurological and psychiatric symptoms. Genetic association studies in SLE have been hampered by insufficient sample size and limited power compared to many other diseases. Multiple Sclerosis (MS) is a chronic relapsing autoimmune disease of the central nervous system (CNS) that also manifests neurological and immunological features. Here, we identify a method of leveraging large-scale genome wide association studies (GWAS) in MS to identify novel genetic risk loci in SLE. Statistical genetic comparison methods including linkage disequilibrium score regression (LDSC) and cross-phenotype association analysis (CPASSOC) to identify genetic overlap in disease pathophysiology, traditional 2-sample and novel PPI-based mendelian randomization to identify causal associations and Bayesian colocalization were applied to association studies conducted in MS to facilitate discovery in the smaller, more limited datasets available for SLE. Pathway analysis using SNP-to-gene mapping identified biological networks composed of molecular pathways with causal implications for CNS disease in SLE specifically, as well as pathways likely causal of both pathologies, providing key insights for therapeutic selection.

Alterations in genes associated with cytosolic RNA sensing in whole blood are associated with coronary microvascular disease in SLE

Systemic lupus erythematosus (SLE) patients are 90% women and over three times more likely to die of cardiovascular disease than women in the general population. Chest pain with no obstructive cardiac disease is associated with coronary microvascular disease (CMD), where narrowing of the small blood vessels can lead to ischemia, and frequently reported by SLE patients. Using whole blood RNA samples, we asked whether gene signatures discriminate SLE patients with coronary microvascular dysfunction (CMD) on cardiac MRI (n=4) from those without (n=7) and whether any signaling pathway is linked to the underlying pathobiology of SLE CMD. RNA-seq analysis revealed 143 differentially expressed (DE) genes between the SLE and healthy control (HC) groups, with virus defense and interferon (IFN) signaling being the key pathways identified as enriched in SLE as expected. We next conducted a comparative analysis of genes differentially expressed in SLE-CMD and SLE-non-CMD relative to HC samples. Our analysis highlighted differences in IFN signaling, RNA sensing and ADP-ribosylation pathways between SLE-CMD and SLE-non-CMD. This is the first study to investigate possible gene signatures associating with CMD in SLE, and our data strongly suggests that distinct molecular mechanisms underly vascular changes in CMD and non-CMD involvement in SLE.

An interpretable machine learning pipeline based on transcriptomics predicts phenotypes of lupus patients

Machine learning (ML) has the potential to identify subsets of patients with distinct phenotypes from gene expression data. However, phenotype prediction using ML has often relied on identifying important genes without a systems biology context. To address this, we created an interpretable ML approach based on blood transcriptomics to predict phenotype in systemic lupus erythematosus (SLE), a heterogeneous autoimmune disease. We employed a sequential grouped feature importance algorithm to assess the performance of gene sets, including immune and metabolic pathways and cell types, known to be abnormal in SLE in predicting disease activity and organ involvement. Gene sets related to interferon, tumor necrosis factor, the mitoribosome, and T cell activation were the best predictors of phenotype with excellent performance. These results suggest potential relationships between the molecular pathways identified in each model and manifestations of SLE. This ML approach to phenotype prediction can be applied to other diseases and tissues.

Characterization of virus-mediated autoimmunity and the consequences for pathological process in patients with systemic lupus erythematosus

INTRODUCTION/OBJECTIVES

This study aimed to identify differentially expressed genes (DEGs) of systemic lupus erythematosus (SLE) using gene expression-based computational methodologies to analyze disease-immune interactions, which affect the development and progression of SLE.

METHOD

Twenty-six patients with SLE and 46 healthy controls were selected from the Gene Expression Omnibus (GEO) database. The significantly enriched immune and virus-related gene lists were computed and visualized by using the DEGs from the gene set enrichment analysis (GSEA). Quantification of 38 immune cells was performed in determining the impact of immune cells on the virus mediated immunity in SLE by using ImmQuant algorithm.

RESULTS

Thirty-nine upregulated and 57 downregulated were identified in SLE patient compared to the healthy controls. Upregulated genes were significantly implicated in Gene Ontology gene sets as cytokine mediated signaling, secretion, and exocytosis in immune response pathways in 26 female SLE patients. In addition, these genes were enriched in hepatitis C, influenza A, measles, Epstein-Barr virus, and herpes simplex virus 1 infection in Kyoto Encyclopedia of Genes and Genomes pathways. Especially, FCGR1A, IRF7, OAS2, CAMP, MX1, OAS3, OAS1, DEFA3, ISG15, and RSAD2 were involved in virus mediated SLE mechanism, and the expression for OAS1, OAS2, and IRF7 was closely associated with the quantities of colony forming unit-monocyte and colony forming unit-granulocyte.

CONCLUSIONS

Identifying virus-mediated SLE genes and quantifies of immune cells were used to understand the pathological process and perform early diagnosis of female SLE, and will lead to clinical tools for treating SLE in patients. Key Points • Using gene expression-based computational methodologies, the 57 immune and viral genes were significantly upregulated in 26 SLE patients. • The identified three key  viral genes such as OAS1, OAS2, and IF7 were closely associated with colony-forming unit-monocytes and colony-forming unit-granulocytes, which affect the virus mediated immunity in SLE. • The viral genes and quantifies of immune cells are useful in understanding pathogenesis of SLE, and this will provide clinical strategies of potential treatment choices in SLE patients.

Differential regulation of the interferon response in systemic lupus erythematosus distinguishes patients of Asian ancestry

OBJECTIVES

Type I interferon (IFN) plays a role in the pathogenesis of systemic lupus erythematosus (SLE), but insufficient attention has been directed to the differences in IFN responses between ancestral populations. Here, we explored the expression of the interferon gene signatures (IGSs) in SLE patients of European ancestry (EA) and Asian ancestry (AsA).

METHODS

We used gene set variation analysis with multiple IGS encompassing the response to both type 1 and type 2 IFN in isolated CD14+ monocytes, CD19+B cells, CD4+T cells and Natural Killer (NK) cells from patients with SLE stratified by self-identified ancestry. The expression of genes upstream of the IGS and influenced by lupus-associated risk alleles was also examined. Lastly, we employed machine learning (ML) models to assess the most important features classifying patients by disease activity.

RESULTS

AsA patients with SLE exhibited greater enrichment in the IFN core and IFNA2 IGS compared with EA patients in all cell types examined and, in the presence and absence of autoantibodies. Overall, AsA patients with SLE demonstrated higher expression of genes upstream of the IGS than EA counterparts. ML with feature importance analysis indicated that IGS expression in NK cells, anti-dsDNA, complement levels and AsA status contributed to disease activity.

CONCLUSIONS

AsA patients with SLE exhibited higher IGS than EA patients in all cell types regardless of autoantibody status, with enhanced expression of genetically associated genes upstream of the IGS potentially contributing. AsA, along with the IGS in NK cells, anti-dsDNA and complement, independently influenced SLE disease activity.

Translational implications of newly characterized pathogenic pathways in systemic lupus erythematosus

Improved characterization of relevant pathogenic pathways in systemic lupus erythematosus (SLE) has been further delineated over the last decades. This led to the development of targeted treatments including belimumab and anifrolumab, which recently became available in clinics. Therapeutic targets in SLE encompass interferon (IFN) signaling, B-T costimulation including immune checkpoints, and increasing modalities of B lineage targeting, such as chimeric antigen receptor (CAR) T cells directed against CD19 or sequential anti-B cell targeting. Patient profiling based on characterization of underlying molecular abnormalities, often performed through comprehensive omics analyses, has recently been shown to better predict patients' treatment responses and also holds promise to unravel key molecular mechanisms driving SLE. SLE carries two key signatures, namely the IFN and B lineage/plasma cell signatures. Recent advances in SLE treatments clearly indicate that targeting innate and adaptive immunity is successful in such a complex autoimmune disease. Although those signatures may interact at the molecular level and provide the basis for the first selective treatments in SLE, it remains to be clarified whether these distinct treatments show different treatment responses among certain patient subsets. In fact, notwithstanding the remarkable amount of novel clues for innovative SLE treatment, harmonization of big data within tailored treatment strategies will be instrumental to better understand and treat this challenging autoimmune disorder. This review will provide an overview of recent improvements in SLE pathogenesis, related insights by analyses of big data and machine learning as well as technical improvements in conducting clinical trials with the ultimate goal that translational research results in improved patient outcomes.

Pathogenesis of systemic lupus erythematosus: risks, mechanisms and therapeutic targets

Research elucidating the pathogenesis of systemic lupus erythematosus (SLE) has defined two critical families of mediators, type I interferon (IFN-I) and autoantibodies targeting nucleic acids and nucleic acid-binding proteins, as fundamental contributors to the disease. On the fertile background of significant genetic risk, a triggering stimulus, perhaps microbial, induces IFN-I, autoantibody production or most likely both. When innate and adaptive immune system cells are engaged and collaborate in the autoimmune response, clinical SLE can develop. This review describes recent data from genetic analyses of patients with SLE, along with current studies of innate and adaptive immune function that contribute to sustained IFN-I pathway activation, immune activation and autoantibody production, generation of inflammatory mediators and tissue damage. The goal of these studies is to understand disease mechanisms, identify therapeutic targets and stimulate development of therapeutics that can achieve improved outcomes for patients.

Locus specific endogenous retroviral expression associated with Alzheimer's disease

Introduction

Human endogenous retroviruses (HERVs) are transcriptionally-active remnants of ancient retroviral infections that may play a role in Alzheimer's disease.

Methods

We combined two, publicly available RNA-Seq datasets with a third, novel dataset for a total cohort of 103 patients with Alzheimer's disease and 45 healthy controls. We use telescope to perform HERV quantification for these samples and simultaneously perform gene expression analysis.

Results

We identify differentially expressed genes and differentially expressed HERVs in Alzheimer's disease patients. Differentially expressed HERVs are scattered throughout the genome; many of them are members of the HERV-K superfamily. A number of HERVs are correlated with the expression of dysregulated genes in Alzheimer's and are physically proximal to genes which drive disease pathways.

Discussion

Dysregulated expression of ancient retroviral insertions in the human genome are present in Alzheimer's disease and show localization patterns that may explain how these elements drive pathogenic gene expression.

Molecular endotypes of type 1 and type 2 SLE

OBJECTIVE

To character the molecular landscape of patients with type 1 and type 2 SLE by analysing gene expression profiles from peripheral blood.

METHODS

Full transcriptomic RNA sequencing was carried out on whole blood samples from 18 subjects with SLE selected by the presence of manifestations typical of type 1 and type 2 SLE. The top 5000 row variance genes were analysed by Multiscale Embedded Gene Co-expression Network Analysis to generate gene co-expression modules that were functionally annotated and correlated with various demographic traits, clinical features and laboratory measures.

RESULTS

Expression of specific gene co-expression modules correlated with individual features of type 1 and type 2 SLE and also effectively segregated samples from patients with type 1 SLE from those with type 2 SLE. Unique type 1 SLE enrichment included interferon, monocytes, T cells, cell cycle and neurotransmitter pathways, whereas unique type 2 SLE enrichment included B cells and metabolic and neuromuscular pathways. Gene co-expression modules of patients with type 2 SLE were identified in subsets of previously reported patients with inactive SLE and idiopathic fibromyalgia (FM) and also identified subsets of patients with active SLE with a greater frequency of severe fatigue.

CONCLUSION

Gene co-expression analysis successfully identified unique transcriptional patterns that segregate type 1 SLE from type 2 SLE and further identified type 2 molecular features in patients with inactive SLE or FM and with active SLE with severe fatigue.

Mendelian randomization and pathway analysis demonstrate shared genetic associations between lupus and coronary artery disease

Coronary artery disease (CAD) is a leading cause of death in patients with systemic lupus erythematosus (SLE). Despite clinical evidence supporting an association between SLE and CAD, pleiotropy-adjusted genetic association studies are limited and focus on only a few common risk loci. Here, we identify a net positive causal estimate of SLE-associated non-HLA SNPs on CAD by traditional Mendelian randomization (MR) approaches. Pathway analysis using SNP-to-gene mapping followed by unsupervised clustering based on protein-protein interactions (PPIs) identifies biological networks composed of positive and negative causal sets of genes. In addition, we confirm the casual effects of specific SNP-to-gene modules on CAD using only SNP mapping to each PPI-defined functional gene set as instrumental variables. This PPI-based MR approach elucidates various molecular pathways with causal implications between SLE and CAD and identifies biological pathways likely causative of both pathologies, revealing known and novel therapeutic interventions for managing CAD in SLE.

CD11b agonists offer a novel approach for treating lupus nephritis

Lupus nephritis (LN) develops in more than a third of all systemic lupus erythematosus (SLE) patients and is the strongest predictor of morbidity and mortality. Increased circulating levels of type I interferon (IFN I) and anti-double stranded DNA (anti-dsDNA) and anti-RNA binding protein (anti-RNP) antibodies lead to increased glomerular injury via leukocyte activation and glomerular infiltration. Uncontrolled Toll-like receptor (TLR) signaling in leukocytes results in increased production of IFN I and anti-dsDNA antibodies. ITGAM gene codes for integrin CD11b, the α-chain of integrin heterodimer CD11b/CD18, that is highly expressed in leukocytes and modulates TLR-dependent pro-inflammatory signaling. Three nonsynonymous SNPs in the ITGAM gene strongly correlate with increased risk for SLE and LN and with IFN I levels. Here we review the literature on the role of CD11b on leukocytes in LN. We also incorporate conclusions from several recent studies that show that these ITGAM SNPs result in a CD11b protein that is less able to suppress TLR-dependent pro-inflammatory pathways in leukocytes, that activation of CD11b via novel small molecule agonists suppresses TLR-dependent pathways, including reductions in circulating levels of IFN I and anti-dsDNA antibodies, and that CD11b activation reduces LN in model systems. Recent data strongly suggest that integrin CD11b is an exciting new therapeutic target in SLE and LN and that allosteric activation of CD11b is a novel therapeutic paradigm for effectively treating such autoimmune diseases.

Liposomes Bearing Non-Bilayer Phospholipid Arrangements Induce Specific IgG Anti-Lipid Antibodies by Activating NK1.1+, CD4+ T Cells in Mice

Liposomes are artificial models of cellular membranes that are used as delivery systems for genes, drugs and protein antigens. We have previously used them to study the antigenic properties of their phospholipids. Here, we used them to induce the production of IgG anti-non-bilayer phospholipid arrangements (NPAs) antibodies in mice; these antibodies cause cell lysis and trigger a lupus-like disease in mice. We studied the mechanisms that lead to the production of these antibodies, and provide evidence that NK1.1⁺, CD4⁺ T cells respond to NPA-bearing liposomes and deliver the help required for specific B cell activation and antibody class-switching to IgG. We found increased numbers of IL-4-producing NK1.1⁺, CD4⁺ T cells in the secondary lymphoid organs of mice administered with NPAs, and these cells also expressed CD40L, which is required for B cell activation. Additionally, we isolated and purified NK1.1⁺, CD4⁺ T cells from spleens and determined that they over-expressed 40 genes, which are key players in inflammatory processes and B cell stimulation and have TRAF6 and UNC39B1 as key nodes in their network. These results show that liposomes are membrane models that can be used to analyze the immunogenicity of lipids.

Machine learning reveals distinct gene signature profiles in lesional and nonlesional regions of inflammatory skin diseases

Analysis of gene expression from cutaneous lupus erythematosus, psoriasis, atopic dermatitis, and systemic sclerosis using gene set variation analysis (GSVA) revealed that lesional samples from each condition had unique features, but all four diseases displayed common enrichment in multiple inflammatory signatures. These findings were confirmed by both classification and regression tree analysis and machine learning (ML) models. Nonlesional samples from each disease also differed from normal samples and each other by ML. Notably, the features used in classification of nonlesional disease were more distinct than their lesional counterparts, and GSVA confirmed unique features of nonlesional disease. These data show that lesional and nonlesional skin samples from inflammatory skin diseases have unique profiles of gene expression abnormalities, especially in nonlesional skin, and suggest a model in which disease-specific abnormalities in "prelesional" skin may permit environmental stimuli to trigger inflammatory responses leading to both the unique and shared manifestations of each disease.

Anti-RNP antibodies are associated with the interferon gene signature but not decreased complement levels in SLE

OBJECTIVES

The goals of these studies were to elucidate the inter-relationships of specific anti-nuclear antibody (ANA), complement, and the interferon gene signature (IGS) in the pathogenesis of systemic lupus erythematosus (SLE).

METHODS

Data from the Illuminate trials were analysed for antibodies to dsDNA as well as RNA-binding proteins (RBP), levels of C3, C4 and various IGS. Statistical hypothesis testing, linear regression analyses and classification and regression trees analysis were employed to assess relationships between the laboratory features of SLE.

RESULTS

Inter-relationships of ANAs, complement and the IGS differed between patients of African Ancestry (AA) and European Ancestry (EA); anti-RNP and multiple autoantibodies were more common in AA patients and, although both related to the presence of the IGS, relationships between autoantibodies and complement differed. Whereas, anti-dsDNA had an inverse relationship to C3 and C4, levels of anti-RNP were not related to these markers. The IGS was only correlated with anti-dsDNA in EA SLE and complement was more correlated to the IGS in AA SLE. Finally, autoantibodies occurred in the presence and absence of the IGS, whereas the IGS was infrequent in anti-dsDNA/anti-RBP-negative SLE patients.

CONCLUSION

There is a complex relationship between autoantibodies and the IGS, with anti-RNP associated in AA and both anti-dsDNA and RNP associated in EA. Moreover, there was a difference in the relationship between anti-dsDNA, but not anti-RBP, with complement levels. The lack of a relationship of anti-RNP with C3 and C4 suggests that anti-RNP immune complexes (ICs) may drive the IGS without complement fixation, whereas anti-dsDNA ICs involve complement consumption.

Epigenomic and transcriptomic analyses reveal differences between low-grade inflammation and severe exhaustion in LPS-challenged murine monocytes

Emerging studies suggest that monocytes can be trained by bacterial endotoxin to adopt distinct memory states ranging from low-grade inflammation to immune exhaustion. While low-grade inflammation may contribute to the pathogenesis of chronic diseases, exhausted monocytes with pathogenic and immune-suppressive characteristics may underlie the pathogenesis of polymicrobial sepsis including COVID-19. However, detailed processes by which the dynamic adaption of monocytes occur remain poorly understood. Here we exposed murine bone-marrow derived monocytes to chronic lipopolysaccharide (LPS) stimulation at low-dose or high-dose, as well as a PBS control. The cells were profiled for genome-wide H3K27ac modification and gene expression. The gene expression of TRAM-deficient and IRAK-M-deficient monocytes with LPS exposure was also analyzed. We discover that low-grade inflammation preferentially utilizes the TRAM-dependent pathway of TLR4 signaling, and induces the expression of interferon response genes. In contrast, high dose LPS uniquely upregulates exhaustion signatures with metabolic and proliferative pathways. The extensive differences in the epigenomic landscape between low-dose and high-dose conditions suggest the importance of epigenetic regulations in driving differential responses. Our data provide potential targets for future mechanistic or therapeutic studies.

The interferon gene signature as a clinically relevant biomarker in autoimmune rheumatic disease

The interferon gene signature (IGS) is derived from the expression of interferon-regulated genes and is classically increased in response to type I interferon exposure. A raised whole blood IGS has increasingly been reported in rheumatic diseases as sequencing technology has advanced. Although its role remains unclear, we explore how a raised IGS can function as a clinically relevant biomarker, independent of whether it is a bystander effect or a key pathological process. For example, a raised IGS can act as a diagnostic biomarker when predicting rheumatoid arthritis in patients with arthralgia and anti-citrullinated protein antibodies, or predicting systemic lupus erythematous (SLE) in those with antinuclear antibodies; a theragnostic biomarker when predicting response for patients receiving disease modifying therapy, such as rituximab in rheumatoid arthritis; a biomarker of disease activity (early rheumatoid arthritis, dermatomyositis, systemic sclerosis, SLE); or finally a predictor of clinical characteristics, such as lupus nephritis in SLE or disease burden in primary Sjögren's syndrome. A high IGS does not uniformly predict worse clinical phenotypes across all diseases, as demonstrated by a reduced disease burden in primary Sjögren's syndrome, nor does it predict a universally poorer response to all therapies, as shown in rheumatoid arthritis. This dichotomy highlights both the complexity of type I interferon signalling in vivo and the current lack of standardisation when calculating the IGS. The IGS as a biomarker warrants further exploration, with beneficial clinical applications anticipated in multiple rheumatic diseases.

Long-term follow-up after lymphodepleting autologous hematopoietic cell transplantation for treatment-resistant systemic lupus erythematosus

OBJECTIVE

Autologous hematopoietic cell transplantation (AHSCT) improves immunologic dysfunction in patients with Systemic Lupus Erythematosus (SLE). However, the curative potential of this therapy remains uncertain. This study reports outcomes in SLE patients receiving a lymphodepleting reduced intensity regimen for AHSCT in SLE.

METHODS

Eight patients with SLE refractory to treatment, including intravenous cyclophosphamide, were enrolled. Five had lupus nephritis and three central nervous system involvement as primary indications for transplant. Hematopoietic cell mobilization with cyclophosphamide, G-CSF and rituximab was followed by collection of CD34+ positively selected cells. The conditioning regimen consisted of concurrent administration of cyclophosphamide, fludarabine, and rituximab. All immunosuppressive medications were discontinued at the start of mobilization and corticosteroids were rapidly tapered after the transplant.

RESULTS

Five of eight patients achieved a complete response, including a decline in the SLEDAI to zero, which was sustained in four patients for a median of 165 months (range 138-191). One patient achieved a partial response, which was followed by relapse at month 18. Two patients with nephritis and most underlying organ comorbidities had early deaths from infection and multiorgan failure. AHSCT resulted in profound lymphodepletion, followed by expansion of Treg cells and repopulation of naive T and B cells. Patients with CR showed a sustained suppression of the SLE-associated interferon-induced gene signature, marked depletion of memory and plasmablast B cells, and resultant sustained elimination of anti-dsDNA antibody.

CONCLUSION

Durable clinical and serologic remissions with suppression in the interferon gene signature can be achieved in refractory SLE following lymphodepleting AHSCT.

TRIAL REGISTRATION

ClinicalTrials.gov, https://clinicaltrials.gov, NCT00076752.

Cluster of highly expressed interferon-stimulated genes associate more with African ancestry than disease activity in patients with systemic lupus erythematosus. A systematic review of cross-sectional studies

Type I interferons (IFN) are central players in the pathogenesis of systemic lupus erythematosus (SLE) and the up-regulation of interferon-stimulated genes (ISGs) in SLE patients is subjected to increasing scrutiny as for its use in diagnosis, stratification and monitoring of SLE patients. Determinants of this immunological phenomenon are yet to be fully charted. The purpose of this systematic review was to characterize expressions of ISGs in blood of SLE patients and to analyze if they associated with core demographic and clinical features of SLE. Twenty cross-sectional, case-control studies comprising 1033 SLE patients and 602 study controls could be included. ISG fold-change expression values (SLE vs controls), demographic and clinical data were extracted from the published material and analyzed by hierarchical cluster analysis and generalized linear modelling. ISG expression varied substantially within each study with IFI27, IFI44, IFI44L, IFIT4 and RSAD2, being the top-five upregulated ISGs. Analysis of inter-study variation showed that IFI27, IFI44, IFI44L, IFIT1, PRKR and RSAD2 expression clustered with the fraction of SLE cases having African ancestry or lupus nephritis. Generalized linear models adjusted for prevalence of lupus nephritis and usage of hydroxychloroquine confirmed the observed association between African ancestry and IFI27, IFI44L, IFIT1, PRKR and RSAD2, whereas disease activity was associated with expression of IFI27 and RNASE2. In conclusion, this systematic review revealed that expression of ISGs often used for deriving an IFN signature in SLE patients were influenced by African ancestry rather than disease activity. This underscores the necessity of taking ancestry into account when employing the IFN signature for clinical research in SLE.

Deconvoluting the heterogeneity of SLE: The contribution of ancestry

Systemic lupus erythematosus (SLE) is a multiorgan autoimmune disorder with a prominent genetic component. Evidence has shown that individuals of non-European ancestry experience the disease more severely, exhibiting an increased incidence of cardiovascular disease, renal involvement, and tissue damage compared with European ancestry populations. Furthermore, there seems to be variability in the response of individuals within different ancestral groups to standard medications, including cyclophosphamide, mycophenolate, rituximab, and belimumab. Although the widespread application of candidate gene, Immunochip, and genome-wide association studies has contributed to our understanding of the link between genetic variation (typically single nucleotide polymorphisms) and SLE, despite decades of research it is still unclear why ancestry remains a key determinant of poorer outcome in non-European-ancestry patients with SLE. Here, we will discuss the impact of ancestry on SLE disease burden in patients from diverse backgrounds and highlight how research efforts using novel bioinformatic and pathway-based approaches have begun to disentangle the complex genetic architecture linking ancestry to SLE susceptibility. Finally, we will illustrate how genomic and gene expression analyses can be combined to help identify novel molecular pathways and drug candidates that might uniquely impact SLE among different ancestral populations.

Transcriptomics data: pointing the way to subclassification and personalized medicine in systemic lupus erythematosus

PURPOSE OF REVIEW

To summarize recent studies stratifying SLE patients into subgroups based on gene expression profiling and suggest future improvements for employing transcriptomic data to foster precision medicine.

RECENT FINDINGS

Bioinformatic & machine learning pipelines have been employed to dissect the transcriptomic heterogeneity of lupus patients and identify more homogenous subgroups. Some examples include the use of unsupervised random forest and k-means clustering to separate adult SLE patients into seven clusters and hierarchical clustering of single-cell RNA-sequencing (scRNA-seq) of immune cells yielding four clusters in a cohort of adult SLE and pediatric SLE participants. Random forest classification of bulk RNA-seq data from sorted blood cells enabled prediction of high or low disease activity in European and Asian SLE patients. Inferred transcription factor activity stratified adult and pediatric SLE into two subgroups.

SUMMARY

Several different endotypes of SLE patients with differing molecular profiles have been reported but a global consensus of clinically actionable groups has not been reached. Moreover, heterogeneity between datasets, reproducibility of predictions as well as the most effective classification approach have not been resolved. Nevertheless, gene expression-based precision medicine remains an attractive option to subset lupus patients.

Abnormalities of the type I interferon signaling pathway in lupus autoimmunity

Type I interferons (IFNs), mostly IFNα and IFNβ, and the type I IFN Signature are important in the pathogenesis of Systemic Lupus Erythematosus (SLE), an autoimmune chronic condition linked to inflammation. Both IFNα and IFNβ trigger a signaling cascade that, through the activation of JAK1, TYK2, STAT1 and STAT2, initiates gene transcription of IFN stimulated genes (ISGs). Noteworthy, other STAT family members and IFN Responsive Factors (IRFs) can also contribute to the activation of the IFN response. Aberrant type I IFN signaling, therefore, can exacerbate SLE by deregulated homeostasis leading to unnecessary persistence of the biological effects of type I IFNs. The etiopathogenesis of SLE is partially known and considered multifactorial. Family-based and genome wide association studies (GWAS) have identified genetic and transcriptional abnormalities in key molecules directly involved in the type I IFN signaling pathway, namely TYK2, STAT1 and STAT4, and IRF5. Gain-of-function mutations that heighten IFNα/β production, which in turn maintains type I IFN signaling, are found in other pathologies like the interferonopathies. However, the distinctive characteristics have yet to be determined. Signaling molecules activated in response to type I IFNs are upregulated in immune cell subsets and affected tissues of SLE patients. Moreover, Type I IFNs induce chromatin remodeling leading to a state permissive to transcription, and SLE patients have increased global and gene-specific epigenetic modifications, such as hypomethylation of DNA and histone acetylation. Epigenome wide association studies (EWAS) highlight important differences between SLE patients and healthy controls in Interferon Stimulated Genes (ISGs). The combination of environmental and genetic factors may stimulate type I IFN signaling transiently and produce long-lasting detrimental effects through epigenetic alterations. Substantial evidence for the pathogenic role of type I IFNs in SLE advocates the clinical use of neutralizing anti-type I IFN receptor antibodies as a therapeutic strategy, with clinical studies already showing promising results. Current and future clinical trials will determine whether drugs targeting molecules of the type I IFN signaling pathway, like non-selective JAK inhibitors or specific TYK2 inhibitors, may benefit people living with lupus.

Altered expression of genes controlling metabolism characterizes the tissue response to immune injury in lupus

To compare lupus pathogenesis in disparate tissues, we analyzed gene expression profiles of human discoid lupus erythematosus (DLE) and lupus nephritis (LN). We found common increases in myeloid cell-defining gene sets and decreases in genes controlling glucose and lipid metabolism in lupus-affected skin and kidney. Regression models in DLE indicated increased glycolysis was correlated with keratinocyte, endothelial, and inflammatory cell transcripts, and decreased tricarboxylic (TCA) cycle genes were correlated with the keratinocyte signature. In LN, regression models demonstrated decreased glycolysis and TCA cycle genes were correlated with increased endothelial or decreased kidney cell transcripts, respectively. Less severe glomerular LN exhibited similar alterations in metabolism and tissue cell transcripts before monocyte/myeloid cell infiltration in some patients. Additionally, changes to mitochondrial and peroxisomal transcripts were associated with specific cells rather than global signal changes. Examination of murine LN gene expression demonstrated metabolic changes were not driven by acute exposure to type I interferon and could be restored after immunosuppression. Finally, expression of HAVCR1, a tubule damage marker, was negatively correlated with the TCA cycle signature in LN models. These results indicate that altered metabolic dysfunction is a common, reversible change in lupus-affected tissues and appears to reflect damage downstream of immunologic processes.

Distinct Microbiomes of Gut and Saliva in Patients With Systemic Lupus Erythematous and Clinical Associations

Alterations in the microbiome of the gut and oral cavity are involved in the etiopathogenesis of systemic lupus erythematosus (SLE). We aimed to assess whether both microbiome compositions in feces and saliva were specific in patients with SLE. A total of 35 patients with SLE, as well as sex- and age-matched asymptomatic subjects as healthy control (HC) group were recruited. Fecal swabs and saliva samples were collected from the participants. 16S ribosomal RNA gene sequencing was performed on the samples. Compared with the HC group, reduced bacterial richness and diversity were detected in the feces of patients with SLE, and increased bacterial diversity in their saliva. Both feces and saliva samples explained the cohort variation. The feces were characterized by enrichment of Lactobacillus, and depletion of an unclassified bacterium in the Ruminococcaceae family and Bifidobacterium. Lack of Bifidobacterium was observed in patients with arthritis. Akkermansia and Ruminococcus negatively correlated with the serum levels of C3. In saliva, Veillonella, Streptococcus, and Prevotella were dominant, and Bacteroides was negatively associated with disease activity. These findings can assist us to comprehensively understand the bacterial profiles of different body niches in SLE patients.

Current Status of the Evaluation and Management of Lupus Patients and Future Prospects

The vastly diverse nature of systemic lupus erythematosus (SLE) poses great challenges to clinicians and patients, as well as to research and drug development efforts. Precise management of lupus patients would be advanced by the ability to identify specific abnormalities operative in individual patients at the time of encounter with the clinician. Advances in new technologies and bioinformatics have greatly improved the understanding of the pathophysiology of SLE. Recent research has focused on the discovery and classification of sensitive and specific markers that could aid early accurate diagnosis, better monitoring of disease and identification of appropriate therapy choices based on specific dysregulated molecular pathways. Here, we summarize some of the advances and discuss the challenges in moving toward precise patient-centric management modalities in SLE.

Expression of Human Endogenous Retroviruses in Systemic Lupus Erythematosus: Multiomic Integration With Gene Expression

Systemic lupus erythematosus (SLE) is a chronic autoimmune disease characterized by the production of autoantibodies predominantly to nuclear material. Many aspects of disease pathology are mediated by the deposition of nucleic acid containing immune complexes, which also induce the type 1interferon response, a characteristic feature of SLE. Notably, SLE is remarkably heterogeneous, with a variety of organs involved in different individuals, who also show variation in disease severity related to their ancestries. Here, we probed one potential contribution to disease heterogeneity as well as a possible source of immunoreactive nucleic acids by exploring the expression of human endogenous retroviruses (HERVs). We investigated the expression of HERVs in SLE and their potential relationship to SLE features and the expression of biochemical pathways, including the interferon gene signature (IGS). Towards this goal, we analyzed available and new RNA-Seq data from two independent whole blood studies using Telescope. We identified 481 locus specific HERV encoding regions that are differentially expressed between case and control individuals with only 14% overlap of differentially expressed HERVs between these two datasets. We identified significant differences between differentially expressed HERVs and non-differentially expressed HERVs between the two datasets. We also characterized the host differentially expressed genes and tested their association with the differentially expressed HERVs. We found that differentially expressed HERVs were significantly more physically proximal to host differentially expressed genes than non-differentially expressed HERVs. Finally, we capitalized on locus specific resolution of HERV mapping to identify key molecular pathways impacted by differential HERV expression in people with SLE.

Protein and DNA methylation-based scores as surrogate markers for interferon system activation in patients with primary Sjögren's syndrome

OBJECTIVE

Standard assessment of interferon (IFN) system activity in systemic rheumatic diseases depends on the availability of RNA samples. In this study, we describe and evaluate alternative methods using plasma, serum and DNA samples, exemplified in the IFN-driven disease primary Sjögren's syndrome (pSS).

METHODS

Patients with pSS seropositive or negative for anti-SSA/SSB and controls were included. Protein-based IFN (pIFN) scores were calculated from levels of PD-1, CXCL9 and CXCL10. DNA methylation-based (DNAm) IFN scores were calculated from DNAm levels at RSAD2, IFIT1 and IFI44L . Scores were compared with mRNA-based IFN scores measured by quantitative PCR (qPCR), Nanostring or RNA sequencing (RNAseq).

RESULTS

mRNA-based IFN scores displayed strong correlations between B cells and monocytes (r=0.93 and 0.95, p<0.0001) and between qPCR and Nanostring measurements (r=0.92 and 0.92, p<0.0001). The pIFN score in plasma and serum was higher in patients compared with controls (p<0.0001) and correlated well with mRNA-based IFN scores (r=0.62-0.79, p<0.0001), as well as with each other (r=0.94, p<0.0001). Concordance of classification as 'high' or 'low' IFN signature between the pIFN score and mRNA-based IFN scores ranged from 79.5% to 88.6%, and the pIFN score was effective at classifying patients and controls (area under the curve, AUC=0.89-0.93, p<0.0001). The DNAm IFN score showed strong correlation to the RNAseq IFN score (r=0.84, p<0.0001) and performed well in classifying patients and controls (AUC=0.96, p<0.0001).

CONCLUSIONS

We describe novel methods of assessing IFN system activity in plasma, serum or DNA samples, which may prove particularly valuable in studies where RNA samples are not available.

Transcriptomic studies of systemic lupus erythematosus

The management of systemic lupus erythematosus (SLE) remains challenging for clinicians because of the clinical heterogeneity of this disease. In attempts to identify useful biomarkers for the diagnosis of and treatment strategies for SLE, previous microarray and RNA sequencing studies have demonstrated several disease-relevant signatures in SLE. Of these, the interferon (IFN) signature is complex, involving IFNβ- and IFNγ-response genes in addition to IFNα-response genes. Some studies revealed that myeloid lineage/neutrophil and plasma cell signatures as well as the IFN signature were correlated with disease activity, lupus nephritis, and complications of pregnancy, although some of these findings remain controversial. Cell-type-specific gene expression analysis revealed the importance of an exhaustion signature in CD8+ T cells for SLE outcome. Recent single-cell RNA sequencing analyses of SLE blood and tissues demonstrated molecular heterogeneity and identified several distinct subpopulations as key players in SLE pathogenesis. Further studies are required to identify novel treatment targets and determine precise patient stratification in SLE. In this review, we discuss the findings and limitations of SLE transcriptomic studies.

Comprehensive transcriptomic analysis of COVID-19 blood, lung, and airway

SARS-CoV2 is a previously uncharacterized coronavirus and causative agent of the COVID-19 pandemic. The host response to SARS-CoV2 has not yet been fully delineated, hampering a precise approach to therapy. To address this, we carried out a comprehensive analysis of gene expression data from the blood, lung, and airway of COVID-19 patients. Our results indicate that COVID-19 pathogenesis is driven by populations of myeloid-lineage cells with highly inflammatory but distinct transcriptional signatures in each compartment. The relative absence of cytotoxic cells in the lung suggests a model in which delayed clearance of the virus may permit exaggerated myeloid cell activation that contributes to disease pathogenesis by the production of inflammatory mediators. The gene expression profiles also identify potential therapeutic targets that could be modified with available drugs. The data suggest that transcriptomic profiling can provide an understanding of the pathogenesis of COVID-19 in individual patients.

EZH2 Inhibition Interferes With the Activation of Type I Interferon Signaling Pathway and Ameliorates Lupus Nephritis in NZB/NZW F1 Mice

Enhancer of zeste homolog 2 (EZH2) is a histone-lysine N-methyltransferase mediating trimethylation of H3K27, which represses gene expression and is critical to immune regulation. Inhibition of EZH2 is proved to have the potential of treating many diseases. However, whether inhibition of EZH2 affects type I interferon (IFN-I) signaling pathway, the abnormality of which is an important pathogenic mechanism for SLE, is still elusive. Here, we report, unexpectedly, a positive regulatory function of EZH2 in IFN-I signaling pathway, which contributes to the overactivation of IFN-I signaling pathway in SLE. We show that the expression of EZH2 was upregulated and positively correlated with the overexpression of interferon stimulated genes (ISGs) in both peripheral blood mononuclear cells and renal tissues of SLE patients. In vitro inhibition of EZH2 by either siRNAs or chemical inhibitors reduced the phosphorylation of STAT1 and the induction of ISGs stimulated by IFN-I. Additionally, inhibition of EZH2 interfered with the in vivo and ex vivo activation of IFN-I signaling pathway elicited by intravenous injection of adenovirus vector expressing mouse IFN-α5 and exogeneous stimulation with IFN-α, respectively. We evaluated the therapeutic effects of EZH2 inhibitor in NZB/NZW F1 mice which depend on IFN-I signaling pathway for the lupus-like disease development. Administration of EZH2 inhibitor prolonged the survival, reduced the levels of anti-dsDNA autoantibodies, and improved lupus nephritis of the mice. What’s more, EZH2 inhibitor attenuated the expression of ISGs in the kidneys of these mice. In summary, we show that excessive EZH2 contributes to the overactivation of IFN-I signaling pathway in SLE. EZH2 inhibitor has the potential to inhibit IFN-I signaling pathway and alleviate lupus nephritis. Additionally, diverse disease driving pathways exist among systemic lupus erythematosus (SLE) patient, and even in the same patients. Common regulators of different pathogenic pathways can be multivalent therapeutic targets. Together with previous studies showing EZH2 is involved in T-cell and B-cell mediated immune responses, EZH2 could be a potent multivalent therapeutic target for SLE.

Multi-cell type gene coexpression network analysis reveals coordinated interferon response and cross-cell type correlations in systemic lupus erythematosus

Systemic lupus erythematosus (SLE) is an incurable autoimmune disease disproportionately affecting women. A major obstacle in finding targeted therapies for SLE is its remarkable heterogeneity in clinical manifestations as well as in the involvement of distinct cell types. To identify cell-specific targets as well as cross-correlation relationships among expression programs of different cell types, we here analyze six major circulating immune cell types from SLE patient blood. Our results show that presence of an interferon response signature stratifies patients into two distinct groups (IFNneg vs. IFNpos). Comparing these two groups using differential gene expression and differential gene coexpression analysis, we prioritize a relatively small list of genes from classical monocytes including two known immune modulators: TNFSF13B/BAFF (target of belimumab, an approved therapeutic for SLE) and IL1RN (the basis of anakinra, a therapeutic for rheumatoid arthritis). We then develop a multi-cell type extension of the weighted gene coexpression network analysis (WGCNA) framework, termed mWGCNA. Applying mWGCNA to RNA-seq data from six sorted immune cell populations (15 SLE, 10 healthy donors), we identify a coexpression module with interferon-stimulated genes (ISGs) among all cell types and a cross-cell type correlation linking expression of specific T helper cell markers to B cell response as well as to TNFSF13B expression from myeloid cells, all of which in turn correlates with disease severity of IFNpos patients. Our results demonstrate the power of a hypothesis-free and data-driven approach to discover drug targets and to reveal novel cross-correlation across cell types in SLE with implications for other autoimmune diseases.

Making Sense of Intracellular Nucleic Acid Sensing in Type I Interferon Activation in Sjögren's Syndrome

Primary Sjögren's syndrome (pSS) is a systemic autoimmune rheumatic disease characterized by dryness of the eyes and mucous membranes, which can be accompanied by various extraglandular autoimmune manifestations. The majority of patients exhibit persistent systemic activation of the type I interferon (IFN) system, a feature that is shared with other systemic autoimmune diseases. Type I IFNs are integral to anti-viral immunity and are produced in response to stimulation of pattern recognition receptors, among which nucleic acid (NA) receptors. Dysregulated detection of endogenous NAs has been widely implicated in the pathogenesis of systemic autoimmune diseases. Stimulation of endosomal Toll-like receptors by NA-containing immune complexes are considered to contribute to the systemic type I IFN activation. Accumulating evidence suggest additional roles for cytosolic NA-sensing pathways in the pathogenesis of systemic autoimmune rheumatic diseases. In this review, we will provide an overview of the functions and signaling of intracellular RNA- and DNA-sensing receptors and summarize the evidence for a potential role of these receptors in the pathogenesis of pSS and the sustained systemic type I IFN activation.

Interferon Beta Activity Is Modulated via Binding of Specific S100 Proteins

Interferon-β (IFN-β) is a pleiotropic cytokine used for therapy of multiple sclerosis, which is also effective in suppression of viral and bacterial infections and cancer. Recently, we reported a highly specific interaction between IFN-β and S100P lowering IFN-β cytotoxicity to cancer cells (Int J Biol Macromol. 2020; 143: 633–639). S100P is a member of large family of multifunctional Ca²⁺-binding proteins with cytokine-like activities. To probe selectivity of IFN-β—S100 interaction with respect to S100 proteins, we used surface plasmon resonance spectroscopy, chemical crosslinking, and crystal violet assay. Among the thirteen S100 proteins studied S100A1, S100A4, and S100A6 proteins exhibit strictly Ca²⁺-dependent binding to IFN-β with equilibrium dissociation constants, K_d, of 0.04–1.5 µM for their Ca²⁺-bound homodimeric forms. Calcium depletion abolishes the S100—IFN-β interactions. Monomerization of S100A1/A4/A6 decreases K_d values down to 0.11–1.0 nM. Interferon-α is unable of binding to the S100 proteins studied. S100A1/A4 proteins inhibit IFN-β-induced suppression of MCF-7 cells viability. The revealed direct influence of specific S100 proteins on IFN-β activity uncovers a novel regulatory role of particular S100 proteins, and opens up novel approaches to enhancement of therapeutic efficacy of IFN-β.

Analysis of Trans-Ancestral SLE Risk Loci Identifies Unique Biologic Networks and Drug Targets in African and European Ancestries

Systemic lupus erythematosus (SLE) is a multi-organ autoimmune disorder with a prominent genetic component. Individuals of African ancestry (AA) experience the disease more severely and with an increased co-morbidity burden compared to European ancestry (EA) populations. We hypothesize that the disparities in disease prevalence, activity, and response to standard medications between AA and EA populations is partially conferred by genomic influences on biological pathways. To address this, we applied a comprehensive approach to identify all genes predicted from SNP-associated risk loci detected with the Immunochip. By combining genes predicted via eQTL analysis, as well as those predicted from base-pair changes in intergenic enhancer sites, coding-region variants, and SNP-gene proximity, we were able to identify 1,731 potential ancestry-specific and trans-ancestry genetic drivers of SLE. Gene associations were linked to upstream and downstream regulators using connectivity mapping, and predicted biological pathways were mined for candidate drug targets. Examination of trans-ancestral pathways reflect the well-defined role for interferons in SLE and revealed pathways associated with tissue repair and remodeling. EA-dominant genetic drivers were more often associated with innate immune and myeloid cell function pathways, whereas AA-dominant pathways mirror clinical findings in AA subjects, suggesting disease progression is driven by aberrant B cell activity accompanied by ER stress and metabolic dysfunction. Finally, potential ancestry-specific and non-specific drug candidates were identified. The integration of all SLE SNP-predicted genes into functional pathways revealed critical molecular pathways representative of each population, underscoring the influence of ancestry on disease mechanism and also providing key insight for therapeutic selection.

Analysis of gene expression from systemic lupus erythematosus synovium reveals myeloid cell-driven pathogenesis of lupus arthritis

Arthritis is a common manifestation of systemic lupus erythematosus (SLE) yet understanding of the underlying pathogenic mechanisms remains incomplete. We, therefore, interrogated gene expression profiles of SLE synovium to gain insight into the nature of lupus arthritis (LA), using osteoarthritis (OA) and rheumatoid arthritis (RA) as comparators. Knee synovia from SLE, OA, and RA patients were analyzed for differentially expressed genes (DEGs) and also by Weighted Gene Co-expression Network Analysis (WGCNA) to identify modules of highly co-expressed genes. Genes upregulated and/or co-expressed in LA revealed numerous immune/inflammatory cells dominated by a myeloid phenotype, in which pathogenic macrophages, myeloid-lineage cells, and their secreted products perpetuate inflammation, whereas OA was characterized by fibroblasts and RA of lymphocytes. Genes governing trafficking of immune cells into the synovium by chemokines were identified, but not in situ generation of germinal centers (GCs). Gene Set Variation Analysis (GSVA) confirmed activation of specific immune cell types in LA. Numerous therapies were predicted to target LA, including TNF, NFκB, MAPK, and CDK inhibitors. Detailed gene expression analysis identified a unique pattern of cellular components and physiologic pathways operative in LA, as well as drugs potentially able to target this common manifestation of SLE.

Increased MLKL mRNA level in the PBMCs is correlated with autoantibody production, renal involvement, and SLE disease activity

Background

Necroptosis is a form of regulated necrosis that is involved in various autoimmune diseases. Mixed lineage kinase domain-like pseudokinase (MLKL) has been identified as a key executor of necroptosis; however, the significance of MLKL in peripheral blood mononuclear cells (PBMCs) of systemic lupus erythematosus (SLE) has not been investigated. In this study, we aimed to determine the mRNA level of MLKL in PBMCs and examine its relationship with clinical features and serological parameters in SLE.

Methods

Real-time transcription-polymerase chain reaction (RT-PCR) analysis was used to determine the expression of MLKL mRNA in PBMCs from 59 patients with SLE, 25 patients with rheumatoid arthritis (RA), and 30 age- and sex-matched healthy controls (HC). Spearman’s correlation test was performed to assess the correlation of MLKL mRNA with clinical variables. The receiver operating characteristic (ROC) curve was created to evaluate the diagnostic value.

Results

Our results showed MLKL mRNA in PBMCs was upregulated in SLE patients compared to that in RA and HC individuals. SLE patients positive for antinuclear antibodies had significantly higher MLKL mRNA than antibody-negative patients. In SLE patients, MLKL mRNA was found to be upregulated in patients with lupus nephritis (LN) as compared with patients without LN, and also higher in active patients than in stable patients. MLKL mRNA level was significantly and positively correlated with c-reaction protein (CRP) (r = 0.3577, p = 0.0237), erythrocyte sedimentation rate (ESR) (r = 0.4091, p = 0.0043), serum immunoglobulin G (IgG) concentration (r = 0.3546, p = 0.0289), and the numbers of positive antinuclear antibodies (ANAs) (r = 0.3945, p = 0.0432). ROC analysis showed that MLKL mRNA in PBMCs had an area under the curve of 0.9277 (95% CI 0.8779–0.9775, p < 0.001) to discriminate SLE from controls.

Conclusions

These results suggest that increased MLKL mRNA level in the PBMCs of SLE patients is correlated with renal involvement and disease activity, identifying a subgroup of patients with SLE or LN who may benefit from early diagnosis and therapies targeting MLKL.

An Update on the Pathogenesis of Cutaneous Lupus Erythematosus and Its Role in Clinical Practice

PURPOSE OF REVIEW

Understanding the pathogenesis of cutaneous lupus erythematosus (CLE) is an important step in developing new medications and providing effective treatment to patients. This review focuses on novel research within CLE pathogenesis, as well as some of the medications being developed based on this knowledge.

RECENT FINDINGS

The subtle differences between systemic lupus erythematosus (SLE) and CLE pathogenesis are highlighted by differences in the circulating immune cells found in each disease, as well as the specific pathways activated by ultraviolet light. Plasmacytoid dendritic cells and the related type I interferon pathway are major components of CLE pathogenesis, and as such, therapies targeting components of this pathway have been successful in recent clinical trials. B cell-depleting therapies have shown success in SLE; however, their role in CLE is less clear. Understanding the differences between these manifestations of lupus allows for the development of therapies that are more effective in skin-specific disease. Discovering key pathways in CLE pathogenesis is critical for understanding the clinical features of the disease and ultimately developing new and effective therapies.

Patient ancestry significantly contributes to molecular heterogeneity of systemic lupus erythematosus

Gene expression signatures can stratify patients with heterogeneous diseases, such as systemic lupus erythematosus (SLE), yet understanding the contributions of ancestral background to this heterogeneity is not well understood. We hypothesized that ancestry would significantly influence gene expression signatures and measured 34 gene modules in 1566 SLE patients of African ancestry (AA), European ancestry (EA), or Native American ancestry (NAA). Healthy subject ancestry-specific gene expression provided the transcriptomic background upon which the SLE patient signatures were built. Although standard therapy affected every gene signature and significantly increased myeloid cell signatures, logistic regression analysis determined that ancestral background significantly changed 23 of 34 gene signatures. Additionally, the strongest association to gene expression changes was found with autoantibodies, and this also had etiology in ancestry: the AA predisposition to have both RNP and dsDNA autoantibodies compared with EA predisposition to have only anti-dsDNA. A machine learning approach was used to determine a gene signature characteristic to distinguish AA SLE and was most influenced by genes characteristic of the perturbed B cell axis in AA SLE patients.

Transcriptional profiling of lupus patients and healthy controls reveals ancestry-related differences and transcriptional heterogeneity among lupus patients.

Integrated urine proteomics and renal single-cell genomics identify an IFN-γ response gradient in lupus nephritis

Lupus nephritis, one of the most serious manifestations of systemic lupus erythematosus (SLE), has a heterogeneous clinical and pathological presentation. For example, proliferative nephritis identifies a more aggressive disease class that requires immunosuppression. However, the current classification system relies on the static appearance of histopathological morphology, which does not capture differences in the inflammatory response. Therefore, a biomarker grounded in the disease biology is needed in order to understand the molecular heterogeneity of lupus nephritis and identify immunologic mechanism and pathways. Here, we analyzed the patterns of 1000 urine protein biomarkers in 30 patients with active lupus nephritis. We found that patients stratify over a chemokine gradient inducible by IFN-γ. Higher values identified patients with proliferative lupus nephritis. After integrating the urine proteomics with the single-cell transcriptomics of kidney biopsies, we observed that the urinary chemokines defining the gradient were predominantly produced by infiltrating CD8+ T cells, along with natural killer and myeloid cells. The urine chemokine gradient significantly correlated with the number of kidney-infiltrating CD8+ cells. These findings suggest that urine proteomics can capture the complex biology of the kidney in lupus nephritis. Patient-specific pathways could be noninvasively tracked in the urine in real time, enabling diagnosis and personalized treatment.

The early local and systemic Type I interferon responses to ultraviolet B light exposure are cGAS dependent

Most systemic lupus erythematosus (SLE) patients are photosensitive and ultraviolet B light (UVB) exposure worsens cutaneous disease and precipitates systemic flares of disease. The pathogenic link between skin disease and systemic exacerbations in SLE remains elusive. In an acute model of UVB-triggered inflammation, we observed that a single UV exposure triggered a striking IFN-I signature not only in the skin, but also in the blood and kidneys. The early IFN-I signature was significantly higher in female compared to male mice. The early IFN-I response in the skin was almost entirely, and in the blood partly, dependent on the presence of cGAS, as was skin inflammatory cell infiltration. Inhibition of cGAMP hydrolysis augmented the UVB-triggered IFN-I response. UVB skin exposure leads to cGAS-activation and both local and systemic IFN-I signature and could contribute to acute flares of disease in susceptible subjects such as patients with SLE.

Higher interferon score and normal complement levels may identify a distinct clinical subset in children with systemic lupus erythematosus

Background

Systemic lupus erythematosus (SLE) is a complex multi-system disease, characterized by both autoimmune and autoinflammatory clinical and laboratory features. The role of type I interferon (IFN) in SLE has been demonstrated from the 2000s, by gene expression analyses showing significant over-expression of genes related to type I IFN signalling pathway (IFN signature). However, several studies questioned the role of measuring the intensity of IFN signature (IFN score) to chase SLE activity.

We would assess if the IFN signature can help the clinical and therapeutic stratification of patients with pediatric SLE.

Methods

We measured the IFN score in peripheral whole blood from a series of subjects with childhood-onset SLE and correlated the results with clinical and laboratory parameters.

Results

Thirty-one subjects were included in the study, among which the 87% displayed a positive IFN score. The only significant relation was found for high IFN score in subjects with normocomplementemia. No correlation was observed between IFN score and SLEDAI-2K, BILAG-2004 and SLICC. Patients with high IFN score and normal complement levels also presented lower anti-dsDNA antibodies.

Conclusions

The integration between IFN signature analysis and complement levels may easily distinguish two groups of subjects, in which the autoimmune or autoinflammatory component of the disease seems to be prevalent.

The basic and translational science year in review: Confucius in the era of Big Data

Personalized medicine is an important goal for the treatment of rheumatic disease that seeks to improve outcomes by matching therapy more precisely with the underlying pathogenetic disturbances in the individual patient. Realization of this goal requires actionable biomarkers to identify these disturbances as well as pathways that can be targeted for novel therapy. Among advances in characterizing pathogenesis, Big Data provides an unprecedented picture of pathogenesis, with analysis of tissue lesions revealing disturbances that may not be apparent in blood. Big Data approaches include single cell RNAseq (scRNAseq) which can elucidate patterns of gene expression by individual cells. Galvanized by the Accelerating Medicines Partnership, a public-private initiative of the NIH, investigative teams have analyzed gene expression in cells in the synovium for rheumatoid arthritis and kidney for systemic lupus erythematosus. A review of basic and translational research for 2018-2019 provides the progress in these areas. Thus, the studies on rheumatoid arthritis have identified subpopulations of immune cells and fibroblasts implicated in synovitis. For lupus, transcriptomic studies have provided evidence for widespread effects of type 1 interferon. Studies in progressive sclerosis have demonstrated changes associated with stem cell therapy as well as potential new targets for anti-fibrotic agents. Other studies using molecular approaches have defined new mechanisms for vasculitis as well as the potential role of the microbiome in inflammatory arthritis and systemic lupus erythematosus. Future studies with Big Data will incorporate the spatial relationships of cells in inflammation as well as changes in gene expression over time.

Anifrolumab in systemic lupus erythematosus: current knowledge and future considerations

Systemic lupus erythematosus (SLE) is a chronic autoimmune disease that is potentially life-threatening and can affect any organ. The complex pathogenesis and heterogeneity of the disease, among other factors, present significant challenges in developing new therapies. Knowledge gained over many years has implicated type I interferon (IFN) in the pathogenesis of SLE and anti-IFN therapies hold promise as a much-needed future treatment for SLE. Anifrolumab, a human monoclonal antibody against the type I IFN receptor, has recently been evaluated in two Phase III clinical trials for the treatment of moderate-to-severe SLE. Here, we review the clinical efficacy and safety of anifrolumab and discuss the potential challenges in determining the optimal SLE patient subgroup for treatment.

The pathogenesis of systemic lupus erythematosus: Harnessing big data to understand the molecular basis of lupus

Systemic lupus erythematosus (SLE) is a chronic, systemic autoimmune disease that causes damage to multiple organ systems. Despite decades of research and available murine models that capture some aspects of the human disease, new treatments for SLE lag behind other autoimmune diseases such as Rheumatoid Arthritis and Crohn's disease. Big data genomic assays have transformed our understanding of SLE by providing important insights into the molecular heterogeneity of this multigenic disease. Gene wide association studies have demonstrated more than 100 risk loci, supporting a model of multiple genetic hits increasing SLE risk in a non-linear fashion, and providing evidence of ancestral diversity in susceptibility loci. Epigenetic studies to determine the role of methylation, acetylation and non-coding RNAs have provided new understanding of the modulation of gene expression in SLE patients and identified new drug targets and biomarkers for SLE. Gene expression profiling has led to a greater understanding of the role of myeloid cells in the pathogenesis of SLE, confirmed roles for T and B cells in SLE, promoted clinical trials based on the prominent interferon signature found in SLE patients, and identified candidate biomarkers and cellular signatures to further drug development and drug repurposing. Gene expression studies are advancing our understanding of the underlying molecular heterogeneity in SLE and providing hope that patient stratification will expedite new therapies based on personal molecular signatures. Although big data analyses present unique interpretation challenges, both computationally and biologically, advances in machine learning applications may facilitate the ability to predict changes in SLE disease activity and optimize therapeutic strategies.

Interferon target-gene expression and epigenomic signatures in health and disease

Multiple type I interferons and interferon-γ (IFN-γ) are expressed under physiological conditions and are increased by stress and infections, and in autoinflammatory and autoimmune diseases. Interferons activate the Jak-STAT signaling pathway and induce overlapping patterns of expression, called 'interferon signatures', of canonical interferon-stimulated genes (ISGs) encoding molecules important for antiviral responses, antigen presentation, autoimmunity and inflammation. It has now become clear that interferons also induce an 'interferon epigenomic signature' by activating latent enhancers and 'bookmarking' chromatin, thus reprogramming cell responses to environmental cues. The interferon epigenomic signature affects ISGs and other gene sets, including canonical targets of the transcription factor NF-κB that encode inflammatory molecules, and is involved in the priming of immune cells, tolerance and the training of innate immune memory. Here we review the mechanisms through which interferon signatures and interferon epigenomic signatures are generated, as well as the expression and functional consequences of these signatures in homeostasis and autoimmune diseases, including systemic lupus erythematosus, rheumatoid arthritis and systemic sclerosis.

Th1, Th2, and Th17 cytokines in systemic lupus erythematosus

Systemic lupus erythematosus (SLE) is an autoimmune disease characterized by the breakdown of immune tolerance leading to excessive inflammation and tissue damage. Imbalance in the levels of cytokines represents one of the multifactorial causes of SLE pathogenesis and it contributes to disease severity. Deregulated levels of T helper type 1 (Th1), type 2 (Th2), and type 17 (Th17) cytokines have been associated with autoimmune inflammation. Growing evidence has shown deregulated levels of Th1, Th2, and Th17 cytokines in SLE patients compared to healthy controls associated with disease activity and severity. In this review, we describe and discuss the levels of Th1, Th2, and Th17 cytokines in SLE patients, and clinical trials involving Th1, Th2, and Th17 cytokines in SLE patients. In particular, with the exception of IL-2, IL-4, and TGF-β1, the levels of Th1, Th2, and Th17 cytokines are increased in SLE patients associated with disease severity. Current phase II or III studies involve therapeutic antibodies targeting IFN-α and type I IFN receptor, while low-dose IL-2 therapy is assessed in phase II clinical trials.

Uncovering potential lncRNAs and nearby mRNAs in systemic lupus erythematosus from the Gene Expression Omnibus dataset

Aim: The aim of this study was to find potential differentially expressed long noncoding RNAs (lncRNAs) and mRNAs in systemic lupus erythematosus. Materials & methods: Differentially expressed lncRNAs and mRNAs were obtained in the Gene Expression Omnibus dataset. Functional annotation of differentially expressed mRNAs was performed, followed by protein-protein interaction network analysis. Then, the interaction network of lncRNA-nearby targeted mRNA was built. Results: Several interaction pairs of lncRNA-nearby targeted mRNA including NRIR-RSAD2, RP11-153M7.5-TLR2, RP4-758J18.2-CCNL2, RP11-69E11.4-PABPC4 and RP11-496I9.1-IRF7/HRAS/PHRF1 were identified. Measles and MAPK were significantly enriched signaling pathways of differentially expressed mRNAs. Conclusion: Our study identified several differentially expressed lncRNAs and mRNAs. And their interactions may play a crucial role in the process of systemic lupus erythematosus.

Autoreactive B cells in SLE, villains or innocent bystanders?

The current concepts for development of autoreactive B cells in SLE (systemic lupus erythematosus) focus on extrinsic stimuli and factors that provoke B cells into tolerance loss. Traditionally, major tolerance loss pathways are thought to be regulated by factors outside the B cell including autoantigen engagement of the B-cell receptor (BCR) with simultaneous type I interferon (IFN) produced by dendritic cells, especially plasmacytoid dendritic cells (pDCs). Later, in autoreactive follicles, B-cells encounter T-follicular helper cells (Tfh) that produce interleukin (IL)-21, IL-4 and pathogenic cytokines, IL-17 and IFN gamma (IFNɣ). This review discusses these mechanisms and also highlights recent advances pointing to the peripheral transitional B-cell stage as a major juncture where transient autocrine IFNβ expression by developing B-cells imprints a heightened susceptibility to external factors favoring differentiation into autoantibody-producing plasmablasts. Recent studies highlight transitional B-cell heterogeneity as a determinant of intrinsic resistance or susceptibility to tolerance loss through the shaping of B-cell responsiveness to cytokines and other environment factors.

Interferon pathway in SLE: one key to unlocking the mystery of the disease

SLE is characterised by an activation of the interferon (IFN) system, which leads to an increased expression of IFN-regulated genes. The reasons behind the IFN signature in SLE are (1) the existence of endogenous IFN inducers, (2) activation of several IFN-producing cell types, (3) production of many different IFNs, (4) a genetic setup promoting IFN production and (5) deficient negative feedback mechanisms. The consequences for the immune system is a continuous stimulation to an immune response, and for the patient a number of different organ manifestations leading to typical symptoms for SLE. In the current review, we will present the existing knowledge of the IFN system and pathway activation in SLE. We will also discuss how this information can contribute to our understanding of both the aetiopathogenesis and some organ manifestations of the disease. We will put forward some issues that are unresolved and should be clarified in order to make a proper stratification of patients with SLE, which seems important when selecting a therapy aiming to downregulate the IFN system.