Gene expression and regulation in systemic lupus erythematosus

Background Systemic lupus erythematosus (SLE) is the prototypic systemic autoimmune disease. Genomewide (GW) association studies have identified more than 40 disease-associated loci, together accounting for only 10-20% of disease heritability. Gene expression represents the intermediate phenotype between DNA and disease phenotypic variation, and provides insights regarding genetic and epigenetic effects. We review data on gene expression and regulation in SLE by our group and other investigators. Materials and methods Systematic PubMed search for GW expression studies in SLE published since the year 2000. Results Deregulation of genes involved in type I interferon signaling is a consistent finding in the peripheral blood of active and severe SLE patients. Upregulation of granulocyte-specific transcripts especially in bone marrow mononuclear cells (BMMCs), and of myeloid lineage transcripts in lupus nephritis, provide evidence for pathogenic role of these cells. Gene network analysis in BMMCs identified central gene regulators which could represent therapeutic targets and a high similarity between SLE and non-Hodgkin lymphoma providing a molecular basis for the reported association of the two diseases. Gene expression abnormalities driven by deregulated expression of certain microRNAs in SLE contribute to interferon production, T- and B-cell hyperactivity, DNA hypomethylation, and defective tissue response to injury. Methylation arrays have revealed alterations in white blood cell DNA methylation in SLE suggesting an important role of epigenetics and the environment. Conclusions Gene expression studies have contributed to the characterization of pathogenic processes in SLE. Integrated approaches utilizing genetic variation, transcriptome and epigenome profiling will facilitate efforts towards a molecular-based disease taxonomy. © 2013 Stichting European Society for Clinical Investigation Journal Foundation

Pathogenesis and treatment of CNS lupus

PURPOSE OF REVIEW: Neuropsychiatric manifestations pose diagnostic and therapeutic challenges in systemic lupus erythematosus (SLE). We review recently published studies on the epidemiology, pathogenesis, neuroimaging, and treatment of NPSLE. RECENT FINDINGS: Generalized SLE activity or damage and antiphospholipid antibodies are identified as major risk factors for neuropsychiatric involvement. NPSLE patients have increased genetic burden and novel genomic approaches are expected to elucidate its pathogenesis. Animal data suggest that, in cases of disturbed blood-brain barrier, autoantibodies against the NR2 subunits of the N-methyl-D-aspartate receptor and 16/6 idiotype antibodies may cause diffuse neuropsychiatric manifestations through neuronal apoptosis or brain inflammation; data in humans are still circumstantial. In NPSLE, advanced neuroimaging uncovers structural and metabolic abnormalities in brain regions with normal appearance on conventional MRI. Treatment includes corticosteroids/immunosuppressants for inflammatory manifestations or generalized SLE activity, and antiplatelets/anticoagulation for manifestations related to antiphospholipid antibodies. In refractory cases, uncontrolled studies suggest a beneficial role of rituximab. SUMMARY: We have begun to better understand how brain-reactive autoantibodies, present in a proportion of SLE patients, can cause brain injury and diffuse NPSLE. Further testing will be required to determine the clinical utility of advanced neuroimaging. Controlled trials are needed to guide therapeutic decisions. © 2013 Wolters Kluwer Health / Lippincott Williams & Wilkins

Diagnostic criteria for systemic lupus erythematosus: Has the time come?

Systemic lupus erythematosus (SLE) is a multiorgan disease with protean manifestations. Because SLE is uncommon and heterogeneous, its diagnosis can pose a considerable challenge, especially for clinicians with limited expertise of the disease. This is particularly true at the early stages of SLE, when an inadequate number of features to secure the diagnosis might be present, and for patients presenting with uncommon features, which can nonetheless be severe and require prompt treatment. Furthermore, the suboptimal performance of immunological testing in patients referred for possible SLE has been highlighted. As a result, SLE remains largely a clinical diagnosis that is made after excluding alternative diagnoses. Diagnostic criteria can expedite diagnosis and treatment, but are not available for SLE. Thus, SLE classification criteria are often used, but strict adherence to these criteria could delay diagnosis. Therefore, while eagerly awaiting diagnostic criteria for this disease, we propose interim potential solutions to facilitate its diagnosis. © 2013 Macmillan Publishers Limited. All rights reserved

Sexual dimorphism in SLE: above and beyond sex hormones

Systemic lupus erythematosus (SLE) is characterized by aberrant production of auto-antibodies and a sexual dimorphism both in the phenotypic expression and frequency of the disease between males and females. The striking female predominance was initially attributed primarily to sex hormones. However, recent data challenge this simplistic view and point more towards genetic and epigenetic factors accounting for this difference. More specifically, several SLE-associated single-nucleotide polymorphisms (SNPs) have been found to play an important role in the gender predilection in SLE. Their effect is mediated through their involvement in sex-hormone and immune system signalling and dysregulation of the expression of genes and miRNAs pertinent to the immune system. Additionally, the genetic factors are interchangeably associated with epigenetic modifications such as DNA methylation and histone modification, thus revealing a highly complex network of responsible mechanisms. Of importance, disturbance in the epigenetic process of X chromosome inactivation in females as well as in rare X chromosome abnormalities leads to increased expression of X-linked immune-related genes and miRNAs, which might predispose females to SLE. Microbiota dysbiosis has also been implicated in the sexual dimorphism by the production of oestrogens within the gut and the regulation of oestrogen-responsive immune-related genes. Sexual dimorphism in SLE is an area of active research, and elucidation of its molecular basis may facilitate ongoing efforts towards personalized care. © The Author(s) 2018

Extensive fragmentation and re-organization of transcription in Systemic Lupus Erythematosus

Systemic Lupus Erythematosus (SLE) is the prototype of autoimmune diseases, characterized by extensive gene expression perturbations in peripheral blood immune cells. Circumstantial evidence suggests that these perturbations may be due to altered epigenetic profiles and chromatin accessibility but the relationship between transcriptional deregulation and genome organization remains largely unstudied. In this work we propose a genomic approach that leverages patterns of gene coexpression from genome-wide transcriptome profiles in order to identify statistically robust Domains of Co-ordinated gene Expression (DCEs). Application of this method on a large transcriptome profiling dataset of 148 SLE patients and 52 healthy individuals enabled the identification of significant disease-associated alterations in gene co-regulation patterns, which also correlate with SLE activity status. Low disease activity patient genomes are characterized by extensive fragmentation leading to overall fewer DCEs of smaller size. High disease activity genomes display extensive redistribution of co-expression domains with expanded and newly-appearing (emerged) DCEs. The dynamics of domain fragmentation and redistribution are associated with SLE clinical endophenotypes, with genes of the interferon pathway being highly enriched in DCEs that become disrupted and with functions associated to more generalized symptoms, being located in domains that emerge anew in high disease activity genomes. Our results suggest strong links between the SLE phenotype and the underlying genome structure and underline an important role for genome organization in shaping gene expression in SLE. © 2020, The Author(s)

Lupus or not? SLE Risk Probability Index (SLERPI): A simple, clinician-friendly machine learning-based model to assist the diagnosis of systemic lupus erythematosus

Objectives: Diagnostic reasoning in systemic lupus erythematosus (SLE) is a complex process reflecting the probability of disease at a given timepoint against competing diagnoses. We applied machine learning in well-characterised patient data sets to develop an algorithm that can aid SLE diagnosis. Methods: From a discovery cohort of randomly selected 802 adults with SLE or control rheumatologic diseases, clinically selected panels of deconvoluted classification criteria and non-criteria features were analysed. Feature selection and model construction were done with Random Forests and Least Absolute Shrinkage and Selection Operator-logistic regression (LASSO-LR). The best model in 10-fold cross-validation was tested in a validation cohort (512 SLE, 143 disease controls). Results: A novel LASSO-LR model had the best performance and included 14 variably weighed features with thrombocytopenia/haemolytic anaemia, malar/maculopapular rash, proteinuria, low C3 and C4, antinuclear antibodies (ANA) and immunologic disorder being the strongest SLE predictors. Our model produced SLE risk probabilities (depending on the combination of features) correlating positively with disease severity and organ damage, and allowing the unbiased classification of a validation cohort into diagnostic certainty levels (unlikely, possible, likely, definitive SLE) based on the likelihood of SLE against other diagnoses. Operating the model as binary (lupus/not-lupus), we noted excellent accuracy (94.8%) for identifying SLE, and high sensitivity for early disease (93.8%), nephritis (97.9%), neuropsychiatric (91.8%) and severe lupus requiring immunosuppressives/biologics (96.4%). This was converted into a scoring system, whereby a score >7 has 94.2% accuracy. Conclusions: We have developed and validated an accurate, clinician-friendly algorithm based on classical disease features for early SLE diagnosis and treatment to improve patient outcomes. © Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ

In an early SLE cohort the ACR-1997, SLICC-2012 and EULAR/ACR-2019 criteria classify non-overlapping groups of patients: use of all three criteria ensures optimal capture for clinical studies while their modification earlier classification and treatment

OBJECTIVES: Classification criteria are biased towards classifying long-standing disease. We compared the European League Against Rheumatism (EULAR)/American College of Rheumatology (ACR)-2019, Systemic Lupus International Collaborating Clinics (SLICC)-2012 and ACR-1997 criteria in an early (median 48 months) systemic lupus erythematosus (SLE) cohort. METHODS: Patients diagnosed with SLE (n=690) or control diseases (n=401). Sensitivity, specificity of the criteria and time-to-classification were calculated. Modified classification algorithms were derived from a random 80% and validated in the remaining 20% of the dataset running multiple iterations. RESULTS: At last assessment, sensitivities of ACR-1997, SLICC-2012 and EULAR/ACR-2019 criteria were 85.7%, 91.3% and 88.6%, with specificities 93.0%, 93.8% and 97.3%, respectively. Both SLICC and EULAR/ACR enabled earlier classification. Only 76.7% of patients with SLE met all three criteria suggesting non-overlapping groups. Notably, unclassified patients had high prevalence of British Isles Lupus Assessment Group moderate/severe manifestations (43.3%-60%) and SLICC/ACR organ damage (30%-50%). At diagnosis, criteria missed 25.6%-30.5% of patients. Modification of EULAR/ACR and SLICC algorithms to include hypocomplementaemia and/or positive anti-phospholipid antibodies as alternative entry criterion, and/or allow classification with fewer clinical criteria from multiple organs, increased their sensitivity at diagnosis (median 82.0% and 86.2%) and overall (93.7% and 97.1%) with modest decreases in specificity. Importantly, patients who were still missed by the modified criteria had lower incidence of major organ involvement, use of immunosuppressive/biological therapies and organ damage. CONCLUSIONS: The SLICC and EULAR/ACR are more sensitive than the ACR and the EULAR/ACR criteria have superior specificity in early SLE, although patients with significant disease can be missed. Combination and/or modification of the classification algorithms may enhance their sensitivity, allowing earlier classification and treatment of more patients with high disease burden. © Author(s) (or their employer(s)) 2020. No commercial re-use. See rights and permissions. Published by BMJ