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Introduction: Systemic lupus erythematosus (SLE) is a clinically heterogeneous disease that presents a challenge for clinicians. To identify potential biomarkers for diagnosis and disease activity in SLE, we investigated a selected yet broad panel of cytokines and autoantibodies in patients with SLE, healthy controls (HC), and patients with other autoimmune diseases (AIDs)., Methods: Serum samples from 422 SLE patients, 546 HC, and 1223 other AIDs were analysed within the frame of the European PRECISESADS project (NTC02890121). Cytokine levels were determined using Luminex panels, and autoantibodies using different immunoassays., Results: Of the 83 cytokines analysed, 29 differed significantly between patients with SLE and HC. Specifically, CCL8, CXCL13, and IL-1RA levels were elevated in patients with active, but not inactive, SLE versus HC, as well as in patients with SLE versus other AIDs. The levels of these cytokines also correlated with SLE Disease Activity Index 2000 (SLEDAI-2K) scores, among five other cytokines. Overall, the occurrence of autoantibodies was similar across SLEDAI-2K organ domains, and the correlations between autoantibodies and activity in different organ domains were weak., Discussion: Our findings suggest that, upon validation, CCL8, CXCL13, and IL-1RA could serve as promising serum biomarkers of activity in SLE., Competing Interests: IP has received research funding and/or honoraria from Amgen, AstraZeneca, Aurinia, Elli Lilly, Gilead, GlaxoSmithKline, Janssen, Novartis, Otsuka, and Roche. The funders had no role in the design of the study, in the collection, analyses, or interpretation of data, in the writing of the manuscript, or in the decision to publish the results. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be constructed as a potential conflict of interest., (Copyright © 2023 Lindblom, Beretta, Borghi and PRECISESADS Clinical Consortium, Alarcón-Riquelme and Parodis.)

Systemic lupus erythematosus, systemic sclerosis, rheumatoid arthritis, and Sjögren's syndrome are four major autoimmune rheumatic diseases characterized by the presence of autoantibodies, caused by a dysregulation of the immune system that leads to a wide variety of clinical manifestations. These conditions present complex etiologies strongly influenced by multiple environmental and genetic factors. The human leukocyte antigen (HLA) region was the first locus identified to be associated and still represents the strongest susceptibility factor for each of these conditions, particularly the HLA class II genes, including DQA1, DQB1, and DRB1, but class I genes have also been associated. Over the last two decades, the genetic component of these disorders has been extensively investigated and hundreds of non-HLA risk genetic variants have been uncovered. Furthermore, it is widely accepted that autoimmune rheumatic diseases share molecular disease pathways, such as the interferon (IFN) type I pathways, which are reflected in a common genetic background. Some examples of well-known pleiotropic loci for autoimmune rheumatic diseases are the HLA region, DNASEL13, TNIP1, and IRF5, among others. The identification of the causal molecular mechanisms behind the genetic associations is still a challenge. However, recent advances have been achieved through mouse models and functional studies of the loci. Here, we provide an updated overview of the genetic architecture underlying these four autoimmune rheumatic diseases, with a special focus on the HLA region., (© 2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Introduction: Systemic lupus erythematosus is an autoimmune disease with multisystemic involvement including intestinal inflammation. Lupus-associated intestinal inflammation may alter the mucosal barrier where millions of commensals have a dynamic and selective interaction with the host immune system. Here, we investigated the consequences of the intestinal inflammation in a TLR7-mediated lupus model., Methods: IgA humoral and cellular response in the gut was measured. The barrier function of the gut epithelial layer was characterised. Also, microbiota composition in the fecal matter was analysed as well as the systemic humoral response to differential commensals., Results: The lupus-associated intestinal inflammation modifies the IgA + B cell response in the gut-associated lymphoid tissue in association with dysbiosis. Intestinal inflammation alters the tight junction protein distribution in the epithelial barrier, which correlated with increased permeability of the intestinal barrier and changes in the microbiota composition. This permeability resulted in a differential humoral response against intestinal commensals., Discussion: Lupus development can cause alterations in microbiota composition, allowing specific species to colonize only the lupus gut. Eventually, these alterations and the changes in gut permeability induced by intestinal inflammation could lead to bacterial translocation., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Botía-Sánchez, Galicia, Albaladejo-Marico, Toro-Domínguez, Morell, Marcos-Fernández, Margolles and Alarcón-Riquelme.)

Objective: Anti-Ro autoantibodies are among the most frequently detected extractable nuclear antigen autoantibodies, mainly associated with primary Sjögren's syndrome (SS), systemic lupus erythematosus (SLE), and undifferentiated connective tissue disease (UCTD). This study was undertaken to determine if there is a common signature for all patients expressing anti-Ro 60 autoantibodies regardless of their disease phenotype., Methods: Using high-throughput multiomics data collected from the cross-sectional cohort in the PRECISE Systemic Autoimmune Diseases (PRECISESADS) study Innovative Medicines Initiative (IMI) project (genetic, epigenomic, and transcriptomic data, combined with flow cytometry data, multiplexed cytokines, classic serology, and clinical data), we used machine learning to assess the integrated molecular profiling of 520 anti-Ro 60+ patients compared to 511 anti-Ro 60- patients with primary SS, patients with SLE, and patients with UCTD, and 279 healthy controls., Results: The selected clinical features for RNA-Seq, DNA methylation, and genome-wide association study data allowed for a clear distinction between anti-Ro 60+ and anti-Ro 60- patients. The different features selected using machine learning from the anti-Ro 60+ patients constituted specific signatures when compared to anti-Ro 60- patients and healthy controls. Remarkably, the transcript Z score of 3 genes (ATP10A, MX1, and PARP14), presenting with overexpression associated with hypomethylation and genetic variation and independently identified using the Boruta algorithm, was clearly higher in anti-Ro 60+ patients compared to anti-Ro 60- patients regardless of disease type. Our findings demonstrated that these signatures, enriched in interferon-stimulated genes, were also found in anti-Ro 60+ patients with rheumatoid arthritis and those with systemic sclerosis and remained stable over time and were not affected by treatment., Conclusion: Anti-Ro 60+ patients present with a specific inflammatory signature regardless of their disease type, suggesting that a dual therapeutic approach targeting both Ro-associated RNAs and anti-Ro 60 autoantibodies should be considered., (© 2022 The Authors. Arthritis & Rheumatology published by Wiley Periodicals LLC on behalf of American College of Rheumatology.)

Objectives: Systemic Lupus Erythematosus is a complex autoimmune disease that leads to significant worsening of quality of life and mortality. Flares appear unpredictably during the disease course and therapies used are often only partially effective. These challenges are mainly due to the molecular heterogeneity of the disease, and in this context, personalized medicine-based approaches offer major promise. With this work we intended to advance in that direction by developing MyPROSLE, an omic-based analytical workflow for measuring the molecular portrait of individual patients to support clinicians in their therapeutic decisions., Methods: Immunological gene-modules were used to represent the transcriptome of the patients. A dysregulation score for each gene-module was calculated at the patient level based on averaged z-scores. Almost 6100 Lupus and 750 healthy samples were used to analyze the association among dysregulation scores, clinical manifestations, prognosis, flare and remission events and response to Tabalumab. Machine learning-based classification models were built to predict around 100 different clinical parameters based on personalized dysregulation scores., Results: MyPROSLE allows to molecularly summarize patients in 206 gene-modules, clustered into nine main lupus signatures. The combination of these modules revealed highly differentiated pathological mechanisms. We found that the dysregulation of certain gene-modules is strongly associated with specific clinical manifestations, the occurrence of relapses or the presence of long-term remission and drug response. Therefore, MyPROSLE may be used to accurately predict these clinical outcomes., Conclusions: MyPROSLE (https://myprosle.genyo.es) allows molecular characterization of individual Lupus patients and it extracts key molecular information to support more precise therapeutic decisions., (© The Author(s) 2022. Published by Oxford University Press.)

Much is said about precision medicine, but its real significance and potential are far from certain. Several studies in each of the autoimmune diseases have provided important insights into molecular pathways, but the use of molecular studies, particularly those looking into transcriptome pathways, has seldom approached the possibility of using the data for disease stratification and then for prediction, or for diagnosis. Only the type I IFN signature has been considered for therapeutic purposes, particularly in the case of SLE. This review provides an update on precision medicine, on what can be translated into clinical practice and on what single-cell molecular studies contribute to our knowledge of autoimmune diseases, focusing on a few examples. The main message is that we should try to move from precision medicine of established diseases to preventive medicine in order to predict the development of disease., (© The Author(s) 2021. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Objective: The effector T cell and B cell cytokine networks have been implicated in the pathogenesis of systemic autoimmune diseases, but the association of these cytokine networks with the heterogeneity of clinical manifestations and immune profiles has not been carefully examined. This study was undertaken to examine whether cytokine profiles can delineate distinct groups of patients in 4 systemic autoimmune diseases (systemic lupus erythematosus, Sjögren's syndrome, rheumatoid arthritis, and systemic sclerosis)., Methods: A total of 179 patients and 48 healthy volunteers were enrolled in the multicenter cross-sectional PRECISE Systemic Autoimmune Diseases (PRECISESADS) study. Multi-low-dimensional omics data (cytokines, autoantibodies, circulating immune cells) were examined. Coculture experiments were performed to test the impact of the cytokine microenvironment on T cell/B cell cross-talk., Results: A proinflammatory cytokine profile defined by high levels of CXCL10, interleukin-6 (IL-6), IL-2, and tumor necrosis factor characterized a distinct group of patients in the 4 systemic autoimmune diseases. In each disease, this proinflammatory cluster was associated with a specific circulating immune cell signature, more severe disease, and higher levels of autoantibodies, suggesting an uncontrolled proinflammatory Th1 immune response. We observed in vitro that B cells reinforce Th1 differentiation and naive T cell proliferation, leading to the induction of type 1 effector B cells and IgG production. This process was associated with an increase in CXCL10, IL-6, IL-2, and interferon-γ production., Conclusion: This composite analysis brings new insights into human B cell functional heterogeneity based on T cell/B cell cross-talk, and proposes a better stratification of patients with systemic autoimmune diseases, suggesting that combined biomarkers would be of great value for the design of personalized treatments., (© 2021, American College of Rheumatology.)

Background: Autoimmune diseases are heterogeneous pathologies with difficult diagnosis and few therapeutic options. In the last decade, several omics studies have provided significant insights into the molecular mechanisms of these diseases. Nevertheless, data from different cohorts and pathologies are stored independently in public repositories and a unified resource is imperative to assist researchers in this field., Results: Here, we present Autoimmune Diseases Explorer ( https://adex.genyo.es ), a database that integrates 82 curated transcriptomics and methylation studies covering 5609 samples for some of the most common autoimmune diseases. The database provides, in an easy-to-use environment, advanced data analysis and statistical methods for exploring omics datasets, including meta-analysis, differential expression or pathway analysis., Conclusions: This is the first omics database focused on autoimmune diseases. This resource incorporates homogeneously processed data to facilitate integrative analyses among studies.

Objective: Clinical heterogeneity, a hallmark of systemic autoimmune diseases, impedes early diagnosis and effective treatment, issues that may be addressed if patients could be classified into groups defined by molecular pattern. This study was undertaken to identify molecular clusters for reclassifying systemic autoimmune diseases independently of clinical diagnosis., Methods: Unsupervised clustering of integrated whole blood transcriptome and methylome cross-sectional data on 955 patients with 7 systemic autoimmune diseases and 267 healthy controls was undertaken. In addition, an inception cohort was prospectively followed up for 6 or 14 months to validate the results and analyze whether or not cluster assignment changed over time., Results: Four clusters were identified and validated. Three were pathologic, representing "inflammatory," "lymphoid," and "interferon" patterns. Each included all diagnoses and was defined by genetic, clinical, serologic, and cellular features. A fourth cluster with no specific molecular pattern was associated with low disease activity and included healthy controls. A longitudinal and independent inception cohort showed a relapse-remission pattern, where patients remained in their pathologic cluster, moving only to the healthy one, thus showing that the molecular clusters remained stable over time and that single pathogenic molecular signatures characterized each individual patient., Conclusion: Patients with systemic autoimmune diseases can be jointly stratified into 3 stable disease clusters with specific molecular patterns differentiating different molecular disease mechanisms. These results have important implications for future clinical trials and the study of nonresponse to therapy, marking a paradigm shift in our view of systemic autoimmune diseases., (© 2020, American College of Rheumatology.)

The B cell scaffold protein with ankyrin repeats (BANK1) is expressed primarily in B cells and with multiple but discrete roles in B cell signaling, including B cell receptor signaling, CD40-related signaling, and Toll-like receptor (TLR) signaling. The gene for BANK1, located in chromosome 4, has been found to contain genetic variants that are associated with several autoimmune diseases and also other complex phenotypes, in particular, with systemic lupus erythematosus. Common genetic variants are associated with changes in BANK1 expression in B cells, while rare variants modify their capacity to bind efferent effectors during signaling. A BANK1-deficient model has shown the importance of BANK1 during TLR7 and TLR9 signaling and has confirmed its role in the disease. Still, much needs to be done to fully understand the function of BANK1, but the main conclusion is that it may be the link between different signaling functions within the B cells and they may act to synergize the various pathways within a cell. With this review, we hope to enhance the interest in this molecule.

Systemic autoimmune diseases (SADs) are characterized by dysfunctioning of the immune system, which causes damage in several tissues and organs. Among these pathologies are systemic lupus erythematosus (SLE), systemic sclerosis or scleroderma, Sjögren's syndrome, rheumatoid arthritis, primary antiphospholipid syndrome (PAPS), mixed connective tissue disease (MCTD), and undifferentiated connective tissue disease (UCTD). Early diagnosis is difficult due to similarity in symptoms, signs, and clinical test results. Hence, our aim was to search for differentiating metabolites of these diseases in plasma and urine samples. We performed metabolomic profiling by liquid chromatography-mass spectrometry (LC-MS) of samples from 228 SADs patients and 55 healthy volunteers. Multivariate PLS models were applied to investigate classification accuracies and identify metabolites differentiating SADs and healthy controls. Furthermore, we specifically investigated UCTD against the other SADs. PLS models were able to classify most SADs vs healthy controls (area under the roc curve (AUC) > 0.7), with the exception of MCTD and PAPS. Differentiating metabolites consisted predominantly of unsaturated fatty acids, acylglycines, acylcarnitines, and amino acids. In accordance with the difficulties in defining UCTD, the UCTD metabolome did not differentiate well from the other SADs. However, most UCTD cases were classified as SLE, suggesting that metabolomics may provide a tool to reassess UCTD diagnosis into other conditions for more well-informed therapeutic strategies.

BANK1 is a susceptibility gene for several systemic autoimmune diseases in several populations. Using the genome-wide association study (GWAS) data from Europeans (EUR) and African Americans (AA), we performed an extensive fine mapping of ankyrin repeats 1 ( BANK1 ). To increase the SNP density, we used imputation followed by univariate and conditional analysis, combined with a haplotypic and expression quantitative trait locus (eQTL) analysis. The data from Europeans showed that the associated region was restricted to a minimal and dependent set of SNPs covering introns two and three, and exon two. In AA, the signal found in the Europeans was split into two independent effects. All of the major risk associated SNPs were eQTLs, and the risks were associated with an increased BANK1 gene expression. Functional annotation analysis revealed the enrichment of repressive B cell epigenomic marks (EZH2 and H3K27me3) and a strong enrichment of splice junctions. Furthermore, one eQTL located in intron two, rs13106926, was found within the binding site for RUNX3, a transcriptional activator. These results connect the local genome topography, chromatin structure, and the regulatory landscape of BANK1 with co-transcriptional splicing of exon two. Our data defines a minimal set of risk associated eQTLs predicted to be involved in the expression of BANK1 modulated through epigenetic regulation and splicing. These findings allow us to suggest that the increased expression of BANK1 will have an impact on B-cell mediated disease pathways.

Autoimmune rheumatic diseases pose many problems that have, in general, already been solved in the field of cancer. The heterogeneity of each disease, the clinical similarities and differences between different autoimmune rheumatic diseases and the large number of patients that remain without a diagnosis underline the need to reclassify these diseases via new approaches. Knowledge about the molecular basis of systemic autoimmune diseases, along with the availability of bioinformatics tools capable of handling and integrating large volumes of various types of molecular data at once, offer the possibility of reclassifying these diseases. A new taxonomy could lead to the discovery of new biomarkers for patient stratification and prognosis. Most importantly, this taxonomy might enable important changes in clinical trial design to reach the expected outcomes or the design of molecularly targeted therapies. In this Review, we discuss the basis for a new molecular taxonomy for autoimmune rheumatic diseases. We highlight the evidence surrounding the idea that these diseases share molecular features related to their pathogenesis and development and discuss previous attempts to classify these diseases. We evaluate the tools available to analyse and combine different types of molecular data. Finally, we introduce PRECISESADS, a project aimed at reclassifying the systemic autoimmune diseases.

In this issue of Cell Stem Cell, Thomas et al. (2017) define the nature of accumulated ssDNA present in the neuron and astrocyte cytoplasm of TREX1 mutated stem cell-derived organoids. Accumulated ssDNAs are derived from LINE-1 endogenous retroelements, providing new clues as to the development of Aicardi-Goutières syndrome in the neural system., (Copyright © 2017 Elsevier Inc. All rights reserved.)

The implementation of precision medicine requires the recruiting of patients in statistically enough numbers, the possibility of obtaining enough materials, and the integration of data from various platforms, which are all real limitations. These types of studies have been performed extensively in cancer but barely on systemic lupus erythematosus (SLE) or other rheumatic diseases. To consider the practical use of the information obtained from such studies, we have to take into account the best biological fluid to use, the ease to perform the analysis in clinical practice, and its relevance to clinical practice. Here we review the most relevant studies that have performed analyses that attempt to classify or stratify SLE. We focus on two types of studies: those that stratify individuals diagnosed with SLE and those that compare SLE with other autoimmune diseases, defining differences and similarities that may be clinically relevant in the future., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

Omics studies of systemic autoimmune diseases (SADs) in general, and SLE in particular, have delivered isolated information from transcriptome, epigenome, genome, cytokine and metabolome analyses. Such analyses have resulted in the identification of disease susceptibility genes and the description of IFN expression signatures, allowing extensive insight into the mechanisms of disease and the development of new therapies. Access to such technologies allows the recognition of patterns of disease at a pathway level, thereby, to reclassify SLE and other SADs and to develop new therapeutics from a personalized perspective. The use of omic information allows the discovery of correlative patterns involving drugs not currently suspected to be of value in SADs. In this review, we summarize the omics findings for SLE and propose ways of using the data for the identification of new biomarkers, finding new drugs and reclassifying patients not only with SLE, but also with other SADs., (© The Author 2016. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

The innovative medicine initiative project called PRECISESADS will study 2.500 individuals affected by systemic autoimmune diseases (SADs) and controls. Among extensive OMICS approaches, multi-parameter flow cytometry analyses will be performed in eleven different centers. Therefore, the integration of all data in common bioinformatical and biostatistical investigations requires a fine mirroring of all instruments. We describe here the procedure elaborated to achieve this prerequisite. One flow cytometer chosen as reference instrument fixed the mean fluorescence intensities (MFIs) of 8 different fluorochrome-conjugated antibodies (Abs) using VersaComp Ab capture beads. The ten other centers adjusted their own PMT voltages to reach the same MFIs. Subsequently, all centers acquired Rainbow 8-peak beads data on a daily basis to follow the stability of their instrument overtime. One blood sample has been dispatched and concomitantly stained in all centers. Comparison of leukocytes frequencies and cell surface marker MFIs demonstrated the close sensitivity of all flow cytometers, allowing a multicenter analysis. The effective multi-center harmonization enables the constitution of a workable wide flow cytometry database for the identification of specific molecular signatures in individuals with SADs., (Copyright © 2016 Elsevier B.V. All rights reserved.)

Consortia have begun to establish 'mechanism-based taxonomies' for inflammatory and neurodegenerative diseases that could aid drug development and personalized therapy.

Autoimmune diseases such as rheumatoid arthritis, systemic lupus erythematosus, multiple sclerosis and inflammatory bowel disease, have complex pathogeneses and likely multifactorial etiologies. The current paradigm for understanding their development is that the disease is triggered in genetically-susceptible individuals by exposure to environmental factors. Some of these environmental factors have been specifically identified, while others are hypothesized and not yet proven, and it is likely that most have yet to be identified. One interesting hypothesis is that environmental effects on immune responses could be mediated by changes in epigenetic regulation. Major mechanisms of epigenetic gene regulation include DNA methylation and histone modification. In these cases, gene expression is modified without involving changes in DNA sequence. Epigenetics is a new and interesting research field in autoimmune diseases. We review the roles of genetic factors, epigenetic regulation and the most studied environmental risk factors such as cigarette smoke, crystalline silica, Epstein-Barr virus, and reproductive hormones in the pathogenesis of autoimmune disease., (Copyright © 2011 Elsevier B.V. All rights reserved.)

In spite of the well-known clustering of multiple autoimmune disorders in families, analyses of specific shared genes and polymorphisms between systemic lupus erythematosus (SLE) and other autoimmune diseases (ADs) have been limited. Therefore, we comprehensively tested autoimmune variants for association with SLE, aiming to identify pleiotropic genetic associations between these diseases. We compiled a list of 446 non-Major Histocompatibility Complex (MHC) variants identified in genome-wide association studies (GWAS) of populations of European ancestry across 17 ADs. We then tested these variants in our combined Caucasian SLE cohorts of 1,500 cases and 5,706 controls. We tested a subset of these polymorphisms in an independent Caucasian replication cohort of 2,085 SLE cases and 2,854 controls, allowing the computation of a meta-analysis between all cohorts. We have uncovered novel shared SLE loci that passed multiple comparisons adjustment, including the VTCN1 (rs12046117, P = 2.02×10(-06)) region. We observed that the loci shared among the most ADs include IL23R, OLIG3/TNFAIP3, and IL2RA. Given the lack of a universal autoimmune risk locus outside of the MHC and variable specificities for different diseases, our data suggests partial pleiotropy among ADs. Hierarchical clustering of ADs suggested that the most genetically related ADs appear to be type 1 diabetes with rheumatoid arthritis and Crohn's disease with ulcerative colitis. These findings support a relatively distinct genetic susceptibility for SLE. For many of the shared GWAS autoimmune loci, we found no evidence for association with SLE, including IL23R. Also, several established SLE loci are apparently not associated with other ADs, including the ITGAM-ITGAX and TNFSF4 regions. This study represents the most comprehensive evaluation of shared autoimmune loci to date, supports a relatively distinct non-MHC genetic susceptibility for SLE, provides further evidence for previously and newly identified shared genes in SLE, and highlights the value of studies of potentially pleiotropic genes in autoimmune diseases., Competing Interests: RRG is an employee of Genentech.

Association studies of over 1 million SNPs capturing most of the human genome common variation became possible thanks to the information provided by the HapMap International project and the development of high-throughput genotyping technologies at accessible prices. Genome-wide scans analyzing thousands of individuals have now identified most if not all of the major genes involved in susceptibility for several systemic autoimmune diseases. In particular, results for rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), and systemic sclerosis (SSc) are reviewed here. While most genes are shared between diseases, few seem to be unique reflecting that we still are long before knowing all genes, their interactions with other genes and the environment and their impact on biological functions., (Copyright © 2010 Elsevier Ltd. All rights reserved.)

Type I interferons play an outstanding role in innate and adaptive immunity by enhancing functions of dendritic cells, inducing differentiation of monocytes, promoting immunoglobulin class switching in B cells and stimulating effector functions of T cells. The increased production of IFNα/β by plasmacytoid dendritic cells could be responsible for not only efficient antiviral defence, but it also may be a pathological factor in the development of various autoimmune disorders. The first evidence of a genetic link between type I interferons and autoimmune diseases was the observation that elevated IFNα activity is frequently detected in the sera of patients with systemic lupus erythematosus, and that this trait shows high heritability and familial aggregation in their first-degree healthy relatives. To date, a number of genes involved in interferon signalling have been associated with various autoimmune diseases. Patients with systemic lupus erythematosus, Sjögren's syndrome, dermatomyositis, psoriasis, and a fraction of patients with rheumatoid arthritis display a specific expression pattern of interferon-dependent genes in their leukocytes, termed the interferon signature. Here, in an attempt to understand the role of type I interferons in the pathogenesis of autoimmunity, we review the recent advances in the genetics of autoimmune diseases focusing on the association of genes involved in type I interferon pathways.

Autoimmune diseases in general are complex genetic diseases where genes and environment interact in unknown ways. In recent years technologies have advanced our knowledge and new genes are being identified very rapidly. We can expect that most genes of major importance for the various autoimmune diseases will be discovered in the coming 5 years. The real challenge comes when we try to understand the mechanisms through which these genes confer disease susceptibility and how the interaction with environment takes place such that clinical expression of the disease results.

The aim of this study was to investigate whether a genetic polymorphism of Fc gammaRIII exists in mice, which could explain the different susceptibility to pathogenic IgG anti-collagen type II (CII) antibodies in mice carrying the collagen-induced arthritis (CIA)-susceptible H-2q haplotype. The gene for Fc gammaRIII was sequenced in 11 common mouse strains, and the results revealed three different haplotypes of mouse Fc gammaRIII: Fc gammaRIII:V, Fc gammaRIII:H and Fc gammaRIII:T. To study the consequences of this polymorphism, we generated mice carrying the Fc gammaRIII:H haplotype from the CIA-susceptible, H-2q-positive DBA/1 mouse or the Fc gammaRIII:V haplotype from the CIA-resistant, H-2q-positive SWR mouse. After CII immunization or transfer of IgG anti-CII antibodies, Fc gammaRIII:H-expressing mice, but not Fc gammaRIII:V-expressing mice, developed progressively severe arthritis. We also investigated if C5, in addition to Fc gammaRIII polymorphism, could affect the susceptibility to the pathogenic IgG anti-CII antibodies in H-2q-positive mice. Here we show that SWR mice, naturally deficient in C5, can develop CIA when supplemented with C5 and that anti-C5 antibody treatment of Fc gammaRIII:H-expressing mice inhibits arthritis development. These data demonstrate for the first time a genetic polymorphism of Fc gammaRIII in mice that may, together with C5, regulate induction of autoimmune disease.

Recent studies investigating the genetic susceptibility of systemic lupus erythematosus, rheumatoid arthritis and psoriasis have revealed a potential role for the RUNX proteins in the development of autoimmune disease. A new pathway of disease pathogenesis opens new avenues of research with thousands of questions that remain to be answered. In this review I attempt to propose how the RUNX proteins might be involved in these diseases and review current knowledge on this very interesting trio of transcription factors that was previously only suspected to be involved in cancer.

Functional genomics can be defined as a series of new biotechnological tools based on whole-genome information that can be used to understand basic mechanisms of gene regulation, structure and function. Most of these tools have been used and modeled in research of lower organisms such as the yeast C. Elegans. The time has come for their use in human genome research and there is hope that the new technologies and possibilities will provide with new knowledge on disease pathogenesis and the development of new drugs.

ObjectiveImmune-mediated inflammatory diseases (IMIDs) are heterogeneous and complex conditions with overlapping clinical symptoms and elevated familial aggregation, which suggests the existence of a shared genetic component. In order to identify this genetic background in a systematic fashion, we performed the first cross-disease genome-wide meta-analysis in systemic seropositive rheumatic diseases, namely, systemic sclerosis, systemic lupus erythematosus, rheumatoid arthritis and idiopathic inflammatory myopathies.MethodsWe meta-analysed ~6.5 million single nucleotide polymorphisms in 11 678 cases and 19 704 non-affected controls of European descent populations. The functional roles of the associated variants were interrogated using publicly available databases.ResultsOur analysis revealed five shared genome-wide significant independent loci that had not been previously associated with these diseases: NAB1, KPNA4-ARL14, DGQK, LIMK1 and PRR12. All of these loci are related with immune processes such as interferon and epidermal growth factor signalling, response to methotrexate, cytoskeleton dynamics and coagulation cascade. Remarkably, several of the associated loci are known key players in autoimmunity, which supports the validity of our results. All the associated variants showed significant functional enrichment in DNase hypersensitivity sites, chromatin states and histone marks in relevant immune cells, including shared expression quantitative trait loci. Additionally, our results were significantly enriched in drugs that are being tested for the treatment of the diseases under study.ConclusionsWe have identified shared new risk loci with functional value across diseases and pinpoint new potential candidate loci that could be further investigated. Our results highlight the potential of drug repositioning among related systemic seropositive rheumatic IMIDs.

Objectives: Genomic Risk Scores (GRS) successfully demonstrated the ability of genetics to identify those individuals at high risk for complex traits including immune-mediated inflammatory diseases (IMIDs). We aimed to test the performance of GRS in the prediction of risk for systemic sclerosis (SSc) for the first time.Methods: Allelic effects were obtained from the largest SSc Genome-Wide Association Study (GWAS) to date (9 095 SSc and 17 584 healthy controls with European ancestry). The best-fitting GRS was identified under the additive model in an independent cohort that comprised 400 patients with SSc and 571 controls. Additionally, GRS for clinical subtypes (limited cutaneous SSc and diffuse cutaneous SSc) and serological subtypes (anti-topoisomerase positive (ATA+) and anti-centromere positive (ACA+)) were generated. We combined the estimated GRS with demographic and immunological parameters in a multivariate generalised linear model.Results: The best-fitting SSc GRS included 33 single nucleotide polymorphisms (SNPs) and discriminated between patients with SSc and controls (area under the receiver operating characteristic (ROC) curve (AUC)=0.673). Moreover, the GRS differentiated between SSc and other IMIDs, such as rheumatoid arthritis and Sjögren's syndrome. Finally, the combination of GRS with age and immune cell counts significantly increased the performance of the model (AUC=0.787). While the SSc GRS was not able to discriminate between ATA+ and ACA+ patients (AUC<0.5), the serological subtype GRS, which was based on the allelic effects observed for the comparison between ACA+ and ATA+ patients, reached an AUC=0.693.Conclusions: GRS was successfully implemented in SSc. The model discriminated between patients with SSc and controls or other IMIDs, confirming the potential of GRS to support early and differential diagnosis for SSc. [ABSTRACT FROM AUTHOR]

Objectives: The analysis of annotated transcripts from genome-wide expression studies may help to understand the pathogenesis of complex diseases, such as systemic sclerosis (SSc). We performed a whole blood (WB) transcriptome analysis on RNA collected in the context of the European PRECISESADS project, aiming at characterising the pathways that differentiate SSc from controls and that are reproducible in geographically diverse populations.Methods: Samples from 162 patients and 252 controls were collected in RNA stabilisers. Cases and controls were divided into a discovery (n=79+163; Southern Europe) and validation cohort (n=83+89; Central-Western Europe). RNA sequencing was performed by an Illumina assay. Functional annotations of Reactome pathways were performed with the Functional Analysis of Individual Microarray Expression (FAIME) algorithm. In parallel, immunophenotyping of 28 circulating cell populations was performed. We tested the presence of differentially expressed genes/pathways and the correlation between absolute cell counts and RNA transcripts/FAIME scores in regression models. Results significant in both populations were considered as replicated.Results: Overall, 15 224 genes and 1277 functional pathways were available; of these, 99 and 225 were significant in both sets. Among replicated pathways, we found a deregulation in type-I interferon, Toll-like receptor cascade, tumour suppressor p53 protein function, platelet degranulation and activation. RNA transcripts or FAIME scores were jointly correlated with cell subtypes with strong geographical differences; neutrophils were the major determinant of gene expression in SSc-WB samples.Conclusions: We discovered a set of differentially expressed genes/pathways validated in two independent sets of patients with SSc, highlighting a number of deregulated processes that have relevance for the pathogenesis of autoimmunity and SSc. [ABSTRACT FROM AUTHOR]

Mixed Connective Tissue Disease (MCTD) is a rare complex systemic autoimmune disease (SAD) characterized by the presence of increased levels of anti-U1 ribonucleoprotein autoantibodies and signs and symptoms that resemble other SADs such as systemic sclerosis (SSc), rheumatoid arthritis (RA), and systemic lupus erythematosus (SLE). Due to its low prevalence, this disease has been very poorly studied at the molecular level. We performed for the first time an epigenome-wide association study interrogating DNA methylation data obtained with the Infinium MethylationEPIC array from whole blood samples in 31 patients diagnosed with MCTD and 255 healthy subjects. We observed a pervasive hypomethylation involving 170 genes enriched for immune-related function such as those involved in type I interferon signaling pathways or in negative regulation of viral genome replication. We mostly identified epigenetic signals at genes previously implicated in other SADs, for example MX1, PARP9, DDX60 , or IFI44L , for which we also observed that MCTD patients exhibit higher DNA methylation variability compared with controls, suggesting that these sites might be involved in plastic immune responses that are relevant to the disease. Through methylation quantitative trait locus (meQTL) analysis we identified widespread local genetic effects influencing DNA methylation variability at MCTD-associated sites. Interestingly, for IRF7, IFI44 genes, and the HLA region we have evidence that they could be exerting a genetic risk on MCTD mediated through DNA methylation changes. Comparison of MCTD-associated epigenome with patients diagnosed with SLE, or Sjögren's Syndrome, reveals a common interferon-related epigenetic signature, however we find substantial epigenetic differences when compared with patients diagnosed with rheumatoid arthritis and systemic sclerosis. Furthermore, we show that MCTD-associated CpGs are potential epigenetic biomarkers with high diagnostic value. Our study serves to reveal new genes and pathways involved in MCTD, to illustrate the important role of epigenetic modifications in MCTD pathology, in mediating the interaction between different genetic and environmental MCTD risk factors, and as potential biomarkers of SADs. [ABSTRACT FROM AUTHOR]

Objective: Immune-mediated inflammatory diseases (IMIDs) are heterogeneous and complex conditions with overlapping clinical symptoms and elevated familial aggregation, which suggests the existence of a shared genetic component. In order to identify this genetic background in a systematic fashion, we performed the first cross-disease genome-wide meta-analysis in systemic seropositive rheumatic diseases, namely, systemic sclerosis, systemic lupus erythematosus, rheumatoid arthritis and idiopathic inflammatory myopathies.Methods: We meta-analysed ~6.5 million single nucleotide polymorphisms in 11 678 cases and 19 704 non-affected controls of European descent populations. The functional roles of the associated variants were interrogated using publicly available databases.Results: Our analysis revealed five shared genome-wide significant independent loci that had not been previously associated with these diseases: NAB1, KPNA4-ARL14, DGQK, LIMK1 and PRR12. All of these loci are related with immune processes such as interferon and epidermal growth factor signalling, response to methotrexate, cytoskeleton dynamics and coagulation cascade. Remarkably, several of the associated loci are known key players in autoimmunity, which supports the validity of our results. All the associated variants showed significant functional enrichment in DNase hypersensitivity sites, chromatin states and histone marks in relevant immune cells, including shared expression quantitative trait loci. Additionally, our results were significantly enriched in drugs that are being tested for the treatment of the diseases under study.Conclusions: We have identified shared new risk loci with functional value across diseases and pinpoint new potential candidate loci that could be further investigated. Our results highlight the potential of drug repositioning among related systemic seropositive rheumatic IMIDs. [ABSTRACT FROM AUTHOR]

Abstract Epigenetics is known to be an important mechanism in the pathogenesis of autoimmune diseases. Epigenetic variations can act as integrators of environmental and genetic exposures and propagate activated states in immune cells. Studying epigenetic alterations by means of genome-wide approaches promises to unravel novel molecular mechanisms related to disease etiology, disease progression, clinical manifestations and treatment responses. This paper reviews what we have learned in the last five years from epigenome-wide studies for three systemic autoimmune diseases, namely systemic lupus erythematosus, primary Sjögren's syndrome, and rheumatoid arthritis. We examine the degree of epigenetic sharing between different diseases and the possible mediating role of epigenetic associations in genetic and environmental risks. Finally, we also shed light into the use of epigenetic markers towards a better precision medicine regarding disease prediction, prevention and personalized treatment in systemic autoimmunity. [ABSTRACT FROM AUTHOR]

Objective: African Americans, East Asians, and Hispanics with systemic lupus erythematous (SLE) are more likely to develop lupus nephritis (LN) than are SLE patients of European descent. The etiology of this difference is not clear, and this study was undertaken to investigate how genetic variants might explain this effect. Methods: In this cross-sectional study, 1244 SLE patients from multiethnic case collections were genotyped for 817,810 single-nucleotide polymorphisms (SNPs) across the genome. Continental genetic ancestry was estimated utilizing the program ADMIXTURE. Gene-based testing and pathway analysis was performed within each ethnic group and meta-analyzed across ethnicities. We also performed candidate SNP association tests with SNPs previously established as risk alleles for SLE, LN, and chronic kidney disease (CKD). Association testing and logistic regression models were performed with LN as the outcome, adjusted for continental ancestries, sex, disease duration, and age. Results: We studied 255 North European, 263 South European, 238 Hispanic, 224 African American and 264 East Asian SLE patients, of whom 606 had LN (48.7%). In genome-wide gene-based and candidate SNP analyses, we found distinct genes, pathways and established risk SNPs associated with LN for each ethnic group. Gene-based analyses showed significant associations between variation in ZNF546 (p = 1.0E-06), TRIM15 (p = 1.0E-06), and TRIMI0 (p = 1.0E-06) and LN among South Europeans, and TTC34 (p = 8.0E-06) was significantly associated with LN among Hispanics. The SNP rs8091180 in NFATC1 was associated with LN (OR 1.43, p = 3.3E-04) in the candidate SNP meta-analysis with the highest OR among African-Americans (OR 2.17, p = 0.0035). Conclusion: Distinct genetic factors are associated with the risk of LN in SLE patients of different ethnicities. CKD risk alleles may play a role in the development of LN in addition to SLE-associated risk variants. These findings may further explain the clinical heterogeneity of LN risk and response to therapy observed between different ethnic groups. [ABSTRACT FROM AUTHOR]

Abstract: Intestinal microbiota has been associated with systemic autoimmune diseases, yet the functional consequences of these associations are elusive. We characterized the fecal microbiota (16S rRNA gene amplification and sequencing) and the plasma metabolome (high‐performance liquid chromatography coupled to mass spectrometry) in 59 patients with systemic sclerosis (SSc) and 28 healthy controls (HCs). Microbial and metabolic data were cross‐correlated to find meaningful associations after extensive data mining analysis and internal validation. Our data show that a reduced model of nine bacteria is capable of differentiating HCs from SSc patients. SSc gut microbiota is characterized by a reduction in protective butyrate‐producing bacteria and by an increase in proinflammatory noxious genera, especially Desulfovibrio. From the metabolic point of view, a multivariate model with 17 metabolite intermediates well distinguished cases from controls. The most interesting peaks we found were identified as glycerophospholipid metabolites and benzene derivatives. The microbial and metabolic data showed significant interactions between Desulfovibrio and alpha‐N‐phenylacetyl‐ l‐glutamine and 2,4‐dinitrobenzenesulfonic acid. Our data suggest that in SSc, intestinal microbiota is characterized by proinflammatory alterations subtly entwined with the metabolic state. Desulfovibrio is a relevant actor in gut dysbiosis that may promote intestinal damage and influence amino acid metabolism. [ABSTRACT FROM AUTHOR]

Systemic lupus erythematosus (SLE, MIM152700) is an autoimmune disease characterized by self-reactive antibodies resulting in systemic inflammation and organ failure. TNFAIP3, encoding the ubiquitin-modifying enzyme A20, is an established susceptibility locus for SLE. By fine mapping and genomic re-sequencing in ethnically diverse populations, we fully characterized the TNFAIP3 risk haplotype and identified a TT>A polymorphic dinucleotide (deletion T followed by a T to A transversion) associated with SLE in subjects of European (P = 1.58 × 10−8, odds ratio = 1.70) and Korean (P = 8.33 × 10−10, odds ratio = 2.54) ancestry. This variant, located in a region of high conservation and regulatory potential, bound a nuclear protein complex composed of NF-κB subunits with reduced avidity. Further, compared with the non-risk haplotype, the haplotype carrying this variant resulted in reduced TNFAIP3 mRNA and A20 protein expression. These results establish this TT>A variant as the most likely functional polymorphism responsible for the association between TNFAIP3 and SLE. [ABSTRACT FROM AUTHOR]

The article focuses on a study which assessed programmed death 1 (PD-1) receptor expression in patients with systemic lupus erythematosus (SLE) compared with relatives and unrelated healthy controls and identified the correlations of lower expression levels of PD-1 receptor with the PD-1.3A genotype. The researchers stimulated the peripheral blood mononuclear cells with anti-CD3/anti-CD28 and analyzed PD-1 expression by flow cytometry. Study findings demonstrated significantly lower PD-1 receptor expression in SLE patients.

The article discusses a study on autoimmune diseases and autoantibodies in families with systemic lupus erythematosus (SLE) in Iceland. The association of SLE susceptibility factors and low levels of mannan-binding lectin with autoimmune disease is also determined. The results indicate a high frequency of autoimmune diseases and autoantibodies in SLE families.

Systemic lupus erythematosus (SLE) is a predominantly female autoimmune disease that affects multiple organ systems. Herein, we report on an X-chromosome gene association with SLE. Methyl-CpG-binding protein 2 (MECP2) is located on chromosome Xq28 and encodes for a protein that plays a critical role in epigenetic transcriptional regulation of methylation-sensitive genes. Utilizing a candidate gene association approach, we genotyped 21 SNPs within and around MECP2 in SLE patients and controls. We identify and replicate association between SLE and the genomic element containing MECP2 in two independent SLE cohorts from two ethnically divergent populations. These findings are potentially related to the overexpression of methylation-sensitive genes in SLE. [ABSTRACT FROM AUTHOR]

This article discusses findings of a study, which determined whether specific isoforms of IRF5 are transcribed in patients with systemic lupus erythematosus who have risk genotypes in the exon 1B donor splice site at single-nucleotide polymorphism. A key component of the type I interferon pathway, IRF5 has a genetic association with systemic lupus erythematosus (SLE) and is involved in the transcriptional activation of various proinflammatory cytokines and interferon-α.

The identification of genes for autoimmune diseases is just the first step towards our understanding of disease pathogenesis. In investigating how mutations, deletions or other types of polymorphic defects occur, it is important to determine the pathways and the mechanisms through which susceptibility leads to disease. In this review I touch on three examples of studies that have attempted to understand the mechanisms of genetic susceptibility in three genes identified recently for systemic lupus erythematosus: PDCD1, PTPN22 and IRF5. We are just beginning to comprehend and much needs to be done. [ABSTRACT FROM AUTHOR]

Systemic lupus erythematosus (SLE) is a complex autoimmune disease characterized by activation of the type I interferon (IFN) pathway. Here we convincingly replicate association of the IFN regulatory factor 5 (IRF5) rs2004640 T allele with SLE in four independent case-control cohorts (P = 4.4 × 10−16) and by family-based transmission disequilibrium test analysis (P = 0.0006). The rs2004640 T allele creates a 5′ donor splice site in an alternate exon 1 of IRF5, allowing expression of several unique IRF5 isoforms. We also identify an independent cis-acting variant associated with elevated expression of IRF5 and linked to the exon 1B splice site. Haplotypes carrying the variant associated with elevated expression and lacking the exon 1B donor site do not confer risk of SLE. Thus, a common IRF5 haplotype driving elevated expression of multiple unique isoforms of IRF5 is an important genetic risk factor for SLE, establishing a causal role for type I IFN pathway genes in human autoimmunity. [ABSTRACT FROM AUTHOR]

Researchers have long suspected that genetic susceptibility is shared among autoimmune diseases. With the increased understanding of genetic risks and disease etiology, we are beginning to comprehend the nature of shared autoimmunity. This article briefly describes the most recent advances in the genetics of autoimmunity and the novel genes discovered. [ABSTRACT FROM AUTHOR]

We identified and replicated an association between ITGAM (CD11b) at 16p11.2 and risk of systemic lupus erythematosus (SLE) in 3,818 individuals of European descent. The strongest association was at a nonsynonymous SNP, rs1143679 (P = 1.7 × 10−17, odds ratio = 1.78). We further replicated this association in two independent samples of individuals of African descent (P = 0.0002 and 0.003; overall meta-analysis P = 6.9 × 10−22). The genetic association between ITGAM and SLE implicates the αMβ2-integrin adhesion pathway in disease development. [ABSTRACT FROM AUTHOR]

Systemic lupus erythematosus (SLE) is a heterogeneous disease with unpredictable patterns of activity. Patients with similar activity levels may have different prognosis and molecular abnormalities. In this study, we aimed to measure the main differences in drug-induced gene expression signatures across SLE patients and to evaluate the potential for clinical data to build a machine learning classifier able to predict the SLE subset for individual patients. SLE transcriptomic data from two cohorts were compared with drug-induced gene signatures from the CLUE database to compute a connectivity score that reflects the capability of a drug to revert the patient signatures. Patient stratification based on drug connectivity scores revealed robust clusters of SLE patients identical to the clusters previously obtained through longitudinal gene expression data, implying that differential treatment depends on the cluster to which patients belongs. The best drug candidates found, mTOR inhibitors or those reducing oxidative stress, showed stronger cluster specificity. We report that drug patterns for reverting disease gene expression follow the cell-specificity of the disease clusters. We used 2 cohorts to train and test a logistic regression model that we employed to classify patients from 3 independent cohorts into the SLE subsets and provide a clinically useful model to predict subset assignment and drug efficacy. [ABSTRACT FROM AUTHOR]

Abstract: For years the identification of candidate genes has been approached in various ways. The latest technology allows for whole genome SNP analysis in genetic association studies. These studies pose new challenges but also new possibilities. I hereby review what is known to date on lupus genetics and what challenges we are to overcome with the new available methods. [Copyright &y& Elsevier]

Dysbiosis has been described in systemic autoimmune diseases (SADs), including systemic lupus erythematosus (SLE), Sjögren's syndrome (SjS), and primary anti-phosholipid syndrome (PAPS), however the biological implications of these associations are often elusive. Stool and plasma samples from 114 subjects, including in SLE (n = 27), SjS (n = 23), PAPs (n = 11) and undifferentiated connective tissue (UCTD, n = 26) patients, and geographically-matched healthy controls (HCs, n = 27), were collected for microbiome (16s rRNA gene sequencing) and metabolome (high-performance liquid chromatography coupled to mass spectrometry) analysis to identify shared characteristics across diseases. Out of 130 identified microbial genera, a subset of 29 bacteria was able to differentiate study groups (area under receiver operating characteristics (AUROC) = 0.730 ± 0.025). A fair classification was obtained with a subset of 41 metabolic peaks out of 254 (AUROC = 0.748 ± 0.021). In both models, HCs were well separated from SADs, while UCTD largely overlapped with the other diseases. In all of the SADs pro-tolerogenic bacteria were reduced, while pathobiont genera were increased. Metabolic alterations included two clusters comprised of: (a) members of the acylcarnitine family, positively correlating with a Prevotella-enriched cluster and negatively correlating with a butyrate-producing bacteria-enriched cluster; and (b) phospholipids, negatively correlating with butyrate-producing bacteria. These findings demonstrate a strong interaction between intestinal microbiota and metabolic function in patients with SADs. [ABSTRACT FROM AUTHOR]