Association of autoantibodies with the IFN signature and NETosis in patients with systemic lupus erythematosus

Objective

Systemic lupus erythematosus (SLE) is an autoimmune disease characterized by a variety of disease symptoms and an unpredictable clinical course. To improve treatment outcome, stratification based on immunological manifestations commonly seen in patients with SLE such as autoantibodies, type I interferon (IFN) signature and neutrophil extracellular trap (NET) release may help. It is assumed that there is an association between these immunological phenomena, since NET release induces IFN production and IFN induces autoantibody formation via B-cell activation. Here we studied the association between autoantibodies, the IFN signature, NET release, and clinical manifestations in patients with SLE.

Methods

We performed principal component analysis (PCA) and hierarchical clustering of 57 SLE-related autoantibodies in 25 patients with SLE. We correlated each autoantibody to the IFN signature and NET inducing capacity.

Results

We observed two distinct clusters: one cluster contained mostly patients with a high IFN signature. Patients in this cluster often present with cutaneous lupus, and have higher anti-dsDNA concentrations. Another cluster contained a mix of patients with a high and low IFN signature. Patients with high and low NET inducing capacity were equally distributed between the clusters. Variance between the clusters is mainly driven by antibodies against histones, RibP2, RibP0, EphB2, RibP1, PCNA, dsDNA, and nucleosome. In addition, we found a trend towards increased concentrations of autoantibodies against EphB2, RibP1, and RNP70 in patients with an IFN signature. We found a negative correlation of NET inducing capacity with anti-FcER (r = -0.530; p = 0.007) and anti-PmScl100 (r = -0.445; p = 0.03).

Conclusion

We identified a subgroup of patients with an IFN signature that express increased concentrations of antibodies against DNA and RNA-binding proteins, which can be useful for further patient stratification and a more targeted therapy. We did not find positive associations between autoantibodies and NET inducing capacity. Our study further strengthens the evidence of a correlation between RNA-binding autoantibodies and the IFN signature.

Comprehensive multiplexed autoantibody profiling of patients with advanced urothelial cancer

BACKGROUND

Comprehensive profiling of autoantibodies (AAbs) in metastatic urothelial cancer (mUC) has not been performed to date. This may aid in diagnosis of UC, uncover novel therapeutic targets in this disease as well as identify associations between AAbs and response and toxicity to systemic therapies.

METHODS

We used serum from patients with mUC collected prior to and after systemic therapy (immune checkpoint inhibitor (ICI) or platinum-based chemotherapy (PBC)) at Dana-Farber Cancer Institute. 38 age-matched and sex-matched healthy controls (HCs) from healthy blood donors were also evaluated. The SeroTag immuno-oncology discovery array (Oncimmune) was used, with quantification of the AAb reactivity toward 1132 antigens. Bound AAbs were detected using an anti-immunoglobulin G-specific detection antibody conjugated to the fluorescent reporter dye phycoerythrin. The AAb reactivity was reported as the median fluorescence intensity for each color and sample using a Luminex FlexMAP3D analyzer. Clinical outcomes of interest included radiographic response and development of immune-related adverse events (irAEs). Significance analysis of microarray was used to compare mUC versus HC and radiographic response. Associations with irAE were evaluated using a logistic regression model. P<0.05 was considered statistically significant.

RESULTS

66 patients were included with a median age of 68 years; 54 patients (82%) received ICI and 12 patients (18%) received PBC. Compared with HCs, AAbs against the cancer/testis antigens (CTAG1B, CTAG2, MAGEB18), HSPA1A, TP53, KRAS, and FGFR3 were significantly elevated in patients with mUC. AAbs against BRCA2, TP53, and CTNBB1 were associated with response, and those against BICD2 and UACA were associated with resistance to ICI therapy. AAbs against MITF, CDH3, and KDM4A were associated with development of irAEs in patient who received an ICI. A higher variance in pre-to-post treatment fold change in AAb levels was seen in patients treated with ICI versus PBC and was associated with response to ICI.

CONCLUSIONS

This is the first report of comprehensive AAb profiling of patients with mUC and identified key AAbs that were elevated in patients with mUC versus HCs as well as AAbs associated with therapeutic response to ICI. These findings are hypothesis generating and further mechanistic studies evaluating humoral immunity in UC are required.

Cytokine and reactivity profiles in SLE patients following anti-CD19 CART therapy

Chimeric antigen receptor (CAR) T cells targeting CD19+ B cells have demonstrated efficacy in refractory systemic lupus erythematosus (SLE). Although initial clinical data suggest that anti-CD19 CAR T cell therapy is well tolerated and highly effective, the immunologic consequences of CAR T cell therapy in SLE patients remain unclear. We profiled serum in six refractory SLE patients prior to and 3 months following CAR T cell infusion. Three months post T cell infusion, the inflammatory cytokines IL-6 and TNFα decreased in patient sera. This was accompanied by elevations in serum IL-7 and BAFF. Furthermore, SLE-associated antibodies dropped profoundly in five of six patients. Last, consistent with other reports of CD19 CAR T therapy in B cell malignancies, we were able to show marginal impact of anti-CD19 CART therapy on pre-existing humoral immune responses in SLE patients. Together, these results provide insights into the mechanisms of efficacy of anti-CD19 CAR T cell therapy in SLE.

Human antibody profiling technologies for autoimmune disease

Autoimmune diseases are caused by the break-down in self-tolerance mechanisms and can result in the generation of autoantibodies specific to human antigens. Human autoantigen profiling technologies such as solid surface arrays and display technologies are powerful high-throughput technologies utilised to discover and map novel autoantigens associated with disease. This review compares human autoantigen profiling technologies including the application of these approaches in chronic and post-infectious autoimmune disease. Each technology has advantages and limitations that should be considered when designing new projects to profile autoantibodies. Recent studies that have utilised these technologies across a range of diseases have highlighted marked heterogeneity in autoantibody specificity between individuals as a frequent feature. This individual heterogeneity suggests that epitope spreading maybe an important mechanism in the pathogenesis of autoimmune disease in general and likely contributes to inflammatory tissue damage and symptoms. Studies focused on identifying autoantibody biomarkers for diagnosis should use targeted data analysis to identify the rarer public epitopes and antigens, common between individuals. Thus, utilisation of human autoantigen profiling technology, combined with different analysis approaches, can illuminate both pathogenesis and biomarker discovery.

Activation of the cGAS-STING innate immune response in cells with deficient mitochondrial topoisomerase TOP1MT

The recognition that cytosolic mitochondrial DNA (mtDNA) activates cyclic GMP-AMP synthase-stimulator of interferon genes (cGAS-STING) innate immune signaling has unlocked novel disease mechanisms. Here, an uncharacterized variant predicted to affect TOP1MT function, P193L, was discovered in a family with multiple early onset autoimmune diseases, including Systemic Lupus Erythematosus (SLE). Although there was no previous genetic association between TOP1MT and autoimmune disease, the role of TOP1MT as a regulator of mtDNA led us to investigate whether TOP1MT could mediate the release of mtDNA to the cytosol, where it could then activate the cGAS-STING innate immune pathway known to be activated in SLE and other autoimmune diseases. Through analysis of cells with reduced TOP1MT expression, we show that loss of TOP1MT results in release of mtDNA to the cytosol, which activates the cGAS-STING pathway. We also characterized the P193L variant for its ability to rescue several TOP1MT functions when expressed in TOP1MT knockout cells. We show that the P193L variant is not fully functional, as its re-expression at high levels was unable to rescue mitochondrial respiration deficits, and only showed partial rescue for other functions, including repletion of mtDNA replication following depletion, nucleoid size, steady state mtDNA transcripts levels and mitochondrial morphology. Additionally, expression of P193L at endogenous levels was unable to rescue mtDNA release-mediated cGAS-STING signaling. Overall, we report a link between TOP1MT and mtDNA release leading to cGAS-STING activation. Moreover, we show that the P193L variant has partial loss of function that may contribute to autoimmune disease susceptibility via cGAS-STING mediated activation of the innate immune system.

Machine learning identifies clusters of longitudinal autoantibody profiles predictive of systemic lupus erythematosus disease outcomes

OBJECTIVES

A novel longitudinal clustering technique was applied to comprehensive autoantibody data from a large, well-characterised, multinational inception systemic lupus erythematosus (SLE) cohort to determine profiles predictive of clinical outcomes.

METHODS

Demographic, clinical and serological data from 805 patients with SLE obtained within 15 months of diagnosis and at 3-year and 5-year follow-up were included. For each visit, sera were assessed for 29 antinuclear antibodies (ANA) immunofluorescence patterns and 20 autoantibodies. K-means clustering on principal component analysis-transformed longitudinal autoantibody profiles identified discrete phenotypic clusters. One-way analysis of variance compared cluster enrolment demographics and clinical outcomes at 10-year follow-up. Cox proportional hazards model estimated the HR for survival adjusting for age of disease onset.

RESULTS

Cluster 1 (n=137, high frequency of anti-Smith, anti-U1RNP, AC-5 (large nuclear speckled pattern) and high ANA titres) had the highest cumulative disease activity and immunosuppressants/biologics use at year 10. Cluster 2 (n=376, low anti-double stranded DNA (dsDNA) and ANA titres) had the lowest disease activity, frequency of lupus nephritis and immunosuppressants/biologics use. Cluster 3 (n=80, highest frequency of all five antiphospholipid antibodies) had the highest frequency of seizures and hypocomplementaemia. Cluster 4 (n=212) also had high disease activity and was characterised by multiple autoantibody reactivity including to antihistone, anti-dsDNA, antiribosomal P, anti-Sjögren syndrome antigen A or Ro60, anti-Sjögren syndrome antigen B or La, anti-Ro52/Tripartite Motif Protein 21, antiproliferating cell nuclear antigen and anticentromere B). Clusters 1 (adjusted HR 2.60 (95% CI 1.12 to 6.05), p=0.03) and 3 (adjusted HR 2.87 (95% CI 1.22 to 6.74), p=0.02) had lower survival compared with cluster 2.

CONCLUSION

Four discrete SLE patient longitudinal autoantibody clusters were predictive of long-term disease activity, organ involvement, treatment requirements and mortality risk.

Artificial intelligence and high-dimensional technologies in the theragnosis of systemic lupus erythematosus

Systemic lupus erythematosus is a complex, systemic autoimmune disease characterised by immune dysregulation. Pathogenesis is multifactorial, contributing to clinical heterogeneity and posing challenges for diagnosis and treatment. Although strides in treatment options have been made in the past 15 years, with the US Food and Drug Administration approval of belimumab in 2011, there are still many patients who have inadequate responses to therapy. A better understanding of underlying disease mechanisms with a holistic and multiparametric approach is required to improve clinical assessment and treatment. This Review discusses the evolution of genomics, epigenomics, transcriptomics, and proteomics in the study of systemic lupus erythematosus and ways to amalgamate these silos of data with a systems-based approach while also discussing ways to strengthen the overall process. These mechanistic insights will facilitate the discovery of functionally relevant biomarkers to guide rational therapeutic selection to improve patient outcomes.

Machine Learning for Diagnosis of Systemic Lupus Erythematosus: A Systematic Review and Meta-Analysis

Background

Application of machine learning (ML) for identification of systemic lupus erythematosus (SLE) has been recently drawing increasing attention, while there is still lack of evidence-based support.

Methods

Systematic review and meta-analysis are conducted to evaluate its diagnostic accuracy and application prospect. PubMed, Embase, Cochrane Library, and Web of Science libraries are searched, in combination with manual searching and literature retrospection, for studies regarding machine learning for identifying SLE and neuropsychiatric systemic lupus erythematosus (NPSLE). Quality Assessment of Diagnostic Accuracy Studies (QUADA-2) is applied to assess the quality of included studies. Diagnostic accuracy of the SLE model and NPSLE model is assessed using the bivariate fixed-effect model, and the data are pooled. Summary receiver operator characteristic curve (SROC) is plotted, and area under the curve (AUC) is calculated.

Results

Eighteen (18) studies are included, in which ten (10) focused on SLE and eight (8) on NPSLE. The AUC of SLE identification is 0.95, the sensitivity is 0.90, the specificity is 0.89, the PLR is 8.4, the NLR is 0.12, and the DOR is 73. AUC of NPSLE identification is 0.89, the sensitivity is 0.83, the specificity is 0.83, the PLR is 5.0, the NLR is 0.20, and the DOR is 25.

Conclusion

Machine learning presented remarkable performance in identification of SLE and NPSLE. Based on the convenience for inclusion factor collection and non-invasiveness of detection, machine learning is expected to be widely applied in clinical practice to assist medical decision making.

Detecting Autoantibodies by Multiparametric Assays: Impact on Prevention, Diagnosis, Monitoring, and Personalized Therapy in Autoimmune Diseases

BACKGROUND

The introduction of multiparametric autoantibody tests has been proposed to improve the accuracy of the immunological diagnosis of autoimmune diseases (AID) and to accelerate time for completing the diagnostic process. Multiplex tests are capable of detecting many autoantibodies in a single run whereas a traditional immunoassay uses a single antigen to detect only a single specificity of autoantibodies. The reasons why multiplex tests could replace conventional immunoassays lie in the evidence that they allow for more efficient handling of large numbers of samples by the laboratory, while ensuring greater diagnostic sensitivity in AID screening.

CONTENT

This review aims to highlight the important role that multiparametric tests could assume when designed for defined profiles they are used not only for diagnostic purposes but also to predict the onset of AID to identify clinical phenotypes and to define prognosis. Furthermore, differences in the antibody profile could identify which subjects will be responsive or not to a specific pharmacological treatment.

SUMMARY

The use of autoantibody profiles, when specifically requested and performed with clinically validated technologies, can represent a significant step toward personalized medicine in autoimmunology.

Paradoxical sex-specific patterns of autoantibody response to SARS-CoV-2 infection

Background

Pronounced sex differences in the susceptibility and response to SARS-CoV-2 infection remain poorly understood. Emerging evidence has highlighted the potential importance of autoimmune activation in modulating the acute response and recovery trajectories following SARS-CoV-2 exposure. Given that immune-inflammatory activity can be sex-biased in the setting of severe COVID-19 illness, the aim of the study was to examine sex-specific autoimmune reactivity to SARS-CoV-2 in the absence of extreme clinical disease.

Methods

In this study, we assessed autoantibody (AAB) reactivity to 91 autoantigens previously linked to a range of classic autoimmune diseases in a cohort of 177 participants (65% women, 35% men, mean age of 35) with confirmed evidence of prior SARS-CoV-2 infection based on presence of antibody to the nucleocapsid protein of SARS-CoV-2. Data were compared to 53 pre-pandemic healthy controls (49% women, 51% men). For each participant, socio-demographic data, serological analyses, SARS-CoV-2 infection status and COVID-19 related symptoms were collected by  an electronic survey of questions. The symptoms burden score was constructed based on the total number of reported symptoms (N = 21) experienced within 6 months prior to the blood draw, wherein a greater number of symptoms corresponded to a higher score and assigned as more severe burden.

Results

In multivariable analyses, we observed sex-specific patterns of autoreactivity associated with the presence or absence (as well as timing and clustering of symptoms) associated with prior COVID-19 illness. Whereas the overall AAB response was more prominent in women following asymptomatic infection, the breadth and extent of AAB reactivity was more prominent in men following at least mildly symptomatic infection. Notably, the observed reactivity included distinct antigens with molecular homology with SARS-CoV-2.

Conclusion

Our results reveal that prior SARS-CoV-2 infection, even in the absence of severe clinical disease, can lead to a broad AAB response that exhibits sex-specific patterns of prevalence and antigen selectivity. Further understanding of the nature of triggered AAB activation among men and women exposed to SARS-CoV-2 will be essential for developing effective interventions against immune-mediated sequelae of COVID-19.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-021-03184-8.

Blocking FcγRIIB in Smooth Muscle Cells Reduces Hypertension

[Figure: see text].

"Precision Medicine in Autoimmune Diseases: Fact or Fiction"

Much is said about precision medicine, but its real significance and the possibility of making it a real possibility is far from certain. Several studies in each of the autoimmune diseases have provided important insight into molecular pathways but the use of molecular studies, particularly those looking into transcriptome pathways, have seldom approached the possibility of using the data for disease stratification and then for prediction, or diagnosis. Only the type I interferon signature has been considered in the use of this signature for therapeutic purposes, particularly in the case of systemic lupus erythematosus. Here, the authors provide an update on precision medicine, what can be translated into clinical practice, and what do single-cell molecular studies provide to our knowledge in autoimmune diseases, focusing on a few examples. The main message being that we should try to move from precision medicine of established disease to preventive medicine in order to predict the development of disease.

miRNA-Mediated Control of B Cell Responses in Immunity and SLE

Loss of B cell tolerance is central to autoimmune diseases such as systemic lupus erythematosus (SLE). As such, the mechanisms involved in B cell development, maturation, activation, and function that are aberrantly regulated in SLE are of interest in the design of targeted therapeutics. While many factors are involved in the generation and regulation of B cell responses, miRNAs have emerged as critical regulators of these responses within the last decade. To date, miRNA involvement in B cell responses has largely been studied in non-autoimmune, immunization-based systems. However, miRNA profiles have also been strongly associated with SLE in human patients and these molecules have proven critical in both the promotion and regulation of disease in mouse models and in the formation of autoreactive B cell responses. Functionally, miRNAs are small non-coding RNAs that bind to complementary sequences located in target mRNA transcripts to mediate transcript degradation or translational repression, invoking a post-transcriptional level of genetic regulation. Due to their capacity to target a diverse range of transcripts and pathways in different immune cell types and throughout the various stages of development and response, targeting miRNAs is an interesting potential therapeutic avenue. Herein, we focus on what is currently known about miRNA function in both normal and SLE B cell responses, primarily highlighting miRNAs with confirmed functions in mouse models. We also discuss areas that should be addressed in future studies and whether the development of miRNA-centric therapeutics may be a viable alternative for the treatment of SLE.

[New antibodies in diagnostics]

Rheumatologists were pivotal in the development of using autoantibodies to diagnose chronic inflammatory diseases. Rheumatoid factors were already discovered in 1940 and antinuclear antibodies and their target structures in the 1950s and 1960s. Even though now a vast array of autoantibodies can be routinely measured, we still need more diagnostic markers for chronic inflammatory diseases. Nowadays novel autoantibodies can be easily discovered using new technologies which are described in this article, Therefore we can expect, that new diagnostic autoantibodies will be available soon.

Systemic lupus erythematosus with hypothyroidism as the initial clinical manifestation: A case report

Systemic lupus erythematosus (SLE) is a multisystem autoimmune disease and hypothyroidism is an organ-specific autoimmune disease. The two diseases may occur successively or simultaneously. The majority of previous studies observed that thyroid disease was more frequent in patients with SLE than in the general population, particularly those who had a higher incidence of anti-thyroid antibodies. However, there are no reported cases of SLE with hypothyroidism as the initial clinical manifestation, to the best of our knowledge. The present study reported on a case of SLE with this unusual initial clinical manifestation and reviewed the literature to estimate the prevalence of clinical hypothyroidism in patients with SLE (range, 3.0-21.4%). The case of the present study had no obvious facial erythema, photosensitivity or recurrent oral ulcers, and only had hypothyroidism as the initial clinical symptom, but the laboratory examination supported the diagnosis of SLE. The present study suggested that in the clinical diagnosis, attention should be paid to screening for connective tissue diseases when diagnosing hypothyroidism, and the importance of thyroid dysfunction should also be recognized in the treatment of SLE.

Profiling of IgG antibodies targeting unmodified and corresponding citrullinated autoantigens in a multicenter national cohort of early arthritis in Germany

OBJECTIVE

To assess the diagnostic potential of IgG antibodies to citrullinated and corresponding native autoantigens in early arthritis.

METHODS

IgG autoantibodies to 390 distinct unmodified and corresponding in vitro citrullinated recombinant proteins were measured by a multiplex assay in baseline blood samples from a German multicenter national cohort of 411 early arthritis patients (56.5 ± 14.6 years, 62.8% female). The cohort was randomly split into a training cohort (n = 329, 28.6% ACPA positive) and a validation cohort (n = 82, 32.9% ACPA pos.). The diagnostic properties of candidate antibodies to predict a subsequent diagnosis of rheumatoid arthritis (RA) as opposed to a non-RA diagnosis were assessed by receiver operating characteristics analysis and generalized linear modeling (GLM) with Bonferroni correction in comparison to clinically determined IgM rheumatoid factor (RF) and citrullinated peptide antibody (ACPA) status.

RESULTS

Of 411 patients, 309 (75.2%) were classified as RA. Detection rates of antibody responses to citrullinated and uncitrullinated forms of the proteins were weakly correlated (Spearman's r = 0.13 (95% CI 0.029-0.22), p = 0.01). The concentration of 34 autoantibodies (32 to citrullinated and 2 to uncitrullinated antigens) was increased at least 2-fold in RA patients and further assessed. In the training cohort, a significant association of citrullinated "transformer 2 beta homolog" (cTRA2B)-IgG with RA was observed (OR 5.3 × 103, 95% CI 0.8 × 103-3.0 × 106, p = 0.047). Sensitivity and specificity of cTRA2B-IgG (51.0%/82.9%) were comparable to RF (30.8%/91.6%) or ACPA (32.1%/94.7%). Similar results were obtained in the validation cohort. The addition of cTRA2B-IgG to ACPA improved the diagnostic performance over ACPA alone (p = 0.026 by likelihood ratio test).

CONCLUSIONS

cTRA2B-IgG has the potential to improve RA diagnosis in conjunction with RF and ACPA in early arthritis.

Proteomic analysis to define predictors of treatment response to adalimumab or methotrexate in rheumatoid arthritis patients

Seropositivity for anti-citrullinated peptide antibodies (ACPA) in patients with rheumatoid arthritis (RA), a chronic autoimmune arthritis, is associated with worse long-term disease outcomes. ACPA is ubiquitously tested in RA patients, but other autoantibodies exist (in both citrullinated and non-citrullinated form) which may provide additional information on RA subtypes and/or treatment response. We used a multiplex bead-based assay of 376 autoantibodies to test associations between these autoantibodies and treatment response in RA patients. Clusters of patients with similar autoantibody expression were defined and cluster membership was associated with treatment response. Thirty-four autoantibodies were differentially expressed in RA patients compared with healthy controls; citrullinated vimentin was associated with treatment response. A selection of citrullinated autoantibodies was found to be associated with treatment response in a subanalysis of ACPA-negative RA patients. Finer ACPA specificities in ACPA-negative RA patients may be predictive of treatment response and could represent a rich vein of future study.

High diagnostic accuracy of histone H4-IgG autoantibodies in systemic lupus erythematosus

Objective

Diagnosis of SLE relies on the detection of autoantibodies. We aimed to assess the diagnostic potential of histone H4 and H2A variant antibodies in SLE.

Methods

IgG-autoantibodies to histones H4 (HIST1H4A), H2A type 2-A (HIST2H2AA3) and H2A type 2-C (HIST2H2AC) were measured along with a standard antibody (SA) set including SSA, SSB, Sm, U1-RNP and RPLP2 in a multiplex magnetic microsphere-based assay in 153 SLE patients [85% female, 41 (13.5) years] and 81 healthy controls [77% female, 43.3 (12.4) years]. Receiver operating characteristic analysis was performed to assess diagnostic performance of individual markers. Logistic regression analysis was performed on a random split of samples to determine the additional value of histone antibodies in comparison with SA by likelihood ratio test and determination of diagnostic accuracy in the remaining validation samples.

Results

Microsphere-based assay showed good interclass correlation (mean 0.85, range 0.73-0.99) and diagnostic performance in receiver operating characteristic analysis (area under the curve (AUC) range 84.8-93.2) compared with routine assay for SA parameters. HIST1H4A-IgG was the marker with the best individual diagnostic performance for SLE vs healthy (AUC 0.97, sensitivity 95% at 90% specificity). HIST1H4A-IgG was an independent significant predictor for the diagnosis of SLE in multivariate modelling (P < 0.0001), and significantly improved prediction of SLE over SA parameters alone (residual deviance 45.9 vs 97.1, P = 4.3 × 10-11). Diagnostic accuracy in the training and validation samples was 89 and 86% for SA, and 95 and 89% with the addition of HIST1H4A-IgG.

Conclusion

HIST1H4A-IgG antibodies improve diagnostic accuracy for SLE vs healthy.

A roadmap towards personalized immunology

Big data generation and computational processing will enable medicine to evolve from a "one-size-fits-all" approach to precise patient stratification and treatment. Significant achievements using "Omics" data have been made especially in personalized oncology. However, immune cells relative to tumor cells show a much higher degree of complexity in heterogeneity, dynamics, memory-capability, plasticity and "social" interactions. There is still a long way ahead on translating our capability to identify potentially targetable personalized biomarkers into effective personalized therapy in immune-centralized diseases. Here, we discuss the recent advances and successful applications in "Omics" data utilization and network analysis on patients' samples of clinical trials and studies, as well as the major challenges and strategies towards personalized stratification and treatment for infectious or non-communicable inflammatory diseases such as autoimmune diseases or allergies. We provide a roadmap and highlight experimental, clinical, computational analysis, data management, ethical and regulatory issues to accelerate the implementation of personalized immunology.

SLE redefined on the basis of molecular pathways

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.

Emerging technologies in autoantibody testing for rheumatic diseases

Testing for the presence of antinuclear antibodies (ANAs) is a key step in the diagnosis of systemic lupus erythematosus (SLE) and other systemic autoimmune rheumatic diseases (SARD). The standard slide-based indirect immunofluorescence (IIF) test is widely used, but is limited by a relative lack of specificity for SLE and not all SARD-ANAs are detected. Alternative immunoassays that might offer enhanced diagnostic and prognostic information have evolved, and some of these have entered clinical practice. This review summarizes the current state of ANA testing and multiplex techniques for detecting other autoantibodies, the possibility of point-of-care testing, and approaches for applications in early disease stages.

From mechanism to therapies in systemic lupus erythematosus

PURPOSE OF REVIEW

Systemic lupus erythematosus (SLE) is a disabling and deadly disease. Development of novel therapies for SLE has historically been limited by incomplete understanding of immune dysregulation. Recent advances in lupus pathogenesis, however, have led to the adoption or development of new therapeutics, including the first Food and Drug Administration-approved drug in 50 years.

RECENT FINDINGS

Multiple cytokines (interferon, B lymphocyte stimulator, IL-6, and IL-17), signaling pathways (Bruton's Tyrosine Kinase, Janus kinase/signal transducer and activator of transcription), and immune cells are dysregulated in SLE. In this review, we cover seminal discoveries that demonstrate how this dysregulation is integral to SLE pathogenesis and the novel therapeutics currently under development or in clinical trials. In addition, early work suggests metabolic derangements are another target for disease modification. Finally, molecular profiling has led to improved patient stratification in the heterogeneous SLE population, which may improve clinical trial outcomes and therapeutic selection.

SUMMARY

Recent advances in the treatment of SLE have directly resulted from improved understanding of this complicated disease. Rheumatologists may have a variety of novel agents and more precise targeting of select lupus populations in the coming years.

From autoantibody research to standardized diagnostic assays in the management of human diseases – report of the 12th Dresden Symposium on Autoantibodies

Testing for autoantibodies (AABs) is becoming more and more relevant, not only for diagnosing autoimmune diseases (AIDs) but also for the differentiation of defined AID subtypes with different clinical manifestations, course and prognosis as well as the very early diagnosis for adequate management in the context of personalized medicine. A major challenge to improve diagnostic accuracy is to harmonize or even standardize AAB analyses. This review presents the results of the 12th Dresden Symposium on Autoantibodies that focused on several aspects of improving autoimmune diagnostics. Topics that are addressed include the International Consensus on ANA Patterns (ICAP) and the International Autoantibody Standardization (IAS) initiatives, the optimization of diagnostic algorithms, the description and evaluation of novel disease-specific AABs as well as the development and introduction of novel assays into routine diagnostics. This review also highlights important developments of recent years, most notably the improvement in diagnosing and predicting the course of rheumatoid arthritis, systemic sclerosis, idiopathic inflammatory myopathies, and of autoimmune neurological, gastrointestinal and liver diseases; the potential diagnostic role of anti-DFS70 antibodies and tumor-associated AABs. Furthermore, some hot topics in autoimmunity regarding disease pathogenesis and management are described.