Four Systemic Lupus Erythematosus Subgroups, Defined by Autoantibodies Status, Differ Regarding HLA-DRB1 Genotype Associations and Immunological and Clinical Manifestations

Histone-Specific CD4+ T Cell Plasticity in Active and Quiescent Systemic Lupus Erythematosus

OBJECTIVE

The aim of this study was to assess whether circulating histone-specific T cells represent tools for precision medicine in systemic lupus erythematosus (SLE).

METHODS

Seroprevalence of autoantibodies and HLA-DR beta (DRB) 1 profile were assessed among 185 patients with SLE and combined with bioinformatics and literature evidence to identify HLA-peptide autoepitope couples for ex vivo detection of antigen-specific T cells through flow cytometry. T cell differentiation and polarization was investigated in patients with SLE, patients with Takayasu arteritis, and healthy controls carrying HLA-DRB1*03:01 and/or HLA-DRB1*11:01. SLE Disease Activity Index 2000 and Lupus Low Disease Activity State were used to estimate disease activity and remission.

RESULTS

Histone-specific CD4+ T cells were selectively detected in patients with SLE. Among patients with a history of anti-DNA antibodies, 77% had detectable histone-specific T cells, whereas 50% had lymphocytes releasing cytokines or upregulating activation markers after in vitro challenge with histone peptide antigens. Histone-specific regulatory and effector T helper (Th) 1-, Th2-, and atypical Th1/Th17 (Th1*)-polarized cells were significantly more abundant in patients with SLE with quiescent disease. In contrast, total Th1-, Th2-, and Th1*-polarized and regulatory T cells were similarly represented between patients and controls or patients with SLE with active versus quiescent disease. Histone-specific effector memory T cells accumulated in the blood of patients with quiescent SLE, whereas total effector memory T cell counts did not change. Immunosuppressants were associated with expanded CD4+ histone-specific naive T (TN) and terminally differentiated T cells.

CONCLUSION

Histone-specific T cells are selectively detected in patients with SLE, and their concentration in the blood varies with disease activity, suggesting that they represent innovative tools for patient stratification and therapy.

Low CD4 + T cell count is related to specific anti-nuclear antibodies, IFNα protein positivity and disease activity in systemic lupus erythematosus pregnancy

BACKGROUND

Lymphopenia, autoantibodies and activation of the type I interferon (IFN) system are common features in systemic lupus erythematosus (SLE). We speculate whether lymphocyte subset counts are affected by pregnancy and if they relate to autoantibody profiles and/or IFNα protein in SLE pregnancy.

METHODS

Repeated blood samples were collected during pregnancy from 80 women with SLE and 51 healthy controls (HC). Late postpartum samples were obtained from 19 of the women with SLE. Counts of CD4 + and CD8 + T cells, B cells and NK cells were measured by flow cytometry. Positivity for anti-nuclear antibodies (ANA) fine specificities (double-stranded DNA [dsDNA], Smith [Sm], ribonucleoprotein [RNP], chromatin, Sjögren's syndrome antigen A [SSA] and B [SSB]) and anti-phospholipid antibodies (cardiolipin [CL] and β2 glycoprotein I [β2GPI]) was assessed with multiplexed bead assay. IFNα protein concentration was quantified with Single molecule array (Simoa) immune assay. Clinical data were retrieved from medical records.

RESULTS

Women with SLE had lower counts of all lymphocyte subsets compared to HC throughout pregnancy, but counts did not differ during pregnancy compared to postpartum. Principal component analysis revealed that low lymphocyte subset counts differentially related to autoantibody profiles, cluster one (anti-dsDNA/anti-Sm/anti-RNP/anti-Sm/RNP/anti-chromatin), cluster two (anti-SSA/anti-SSB) and cluster three (anti-CL/anti-β2GPI), IFNα protein levels and disease activity. CD4 + T cell counts were lower in women positive to all ANA fine specificities in cluster one compared to those who were negative, and B cell numbers were lower in women positive for anti-dsDNA and anti-Sm compared to negative women. Moreover, CD4 + T cell and B cell counts were lower in women with moderate/high compared to no/low disease activity, and CD4 + T cell count was lower in IFNα protein positive relative to negative women. Finally, CD4 + T cell count was unrelated to treatment.

CONCLUSION

Lymphocyte subset counts are lower in SLE compared to healthy pregnancies, which seems to be a feature of the disease per se and not affected by pregnancy. Our results also indicate that low lymphocyte subset counts relate differentially to autoantibody profiles, IFNα protein levels and disease activity, which could be due to divergent disease pathways.

Impaired innate and adaptive immune responses to BNT162b2 SARS-CoV-2 vaccination in systemic lupus erythematosus

Understanding the immune responses to SARS-CoV-2 vaccination is critical to optimizing vaccination strategies for individuals with autoimmune diseases, such as systemic lupus erythematosus (SLE). Here, we comprehensively analyzed innate and adaptive immune responses in 19 patients with SLE receiving a complete 2-dose Pfizer-BioNTech mRNA vaccine (BNT162b2) regimen compared with a control cohort of 56 healthy control (HC) volunteers. Patients with SLE exhibited impaired neutralizing antibody production and antigen-specific CD4+ and CD8+ T cell responses relative to HC. Interestingly, antibody responses were only altered in patients with SLE treated with immunosuppressive therapies, whereas impairment of antigen-specific CD4+ and CD8+ T cell numbers was independent of medication. Patients with SLE also displayed reduced levels of circulating CXC motif chemokine ligands, CXCL9, CXCL10, CXCL11, and IFN-γ after secondary vaccination as well as downregulation of gene expression pathways indicative of compromised innate immune responses. Single-cell RNA-Seq analysis reveals that patients with SLE showed reduced levels of a vaccine-inducible monocyte population characterized by overexpression of IFN-response transcription factors. Thus, although 2 doses of BNT162b2 induced relatively robust immune responses in patients with SLE, our data demonstrate impairment of both innate and adaptive immune responses relative to HC, highlighting a need for population-specific vaccination studies.

Epstein-Barr virus reactivation and disease flare of systemic lupus erythematosus

SLE affects females rather than males with a ratio of about 9:1. Owing to the high morbidity with multiple organ involvement, SLE flare-up remains a challenge for women's health. In an accumulation of the past 70 years of studies globally, EBV has been found to be strongly associated with SLE. In the past two decades, EBV reactivation has been proven as prevalent in SLE patients as well as being strongly associated with higher SLE activity and higher prevalence of SLE flare. Hence, strategies to control EBV reactivation in SLE including pharmacological (such as Tenofovir prodrugs TDF and TAF) and non-pharmacological approaches are being developed. The heterogeneity of SLE constitutes clinical challenges, suggesting a stratification of SLE into subgroups based on EBV reactivation or non-reactivation is reasonable. Future-wise, adding anti-EBV reactivation medication to current immunosuppressants for the subgroup of SLE patients with EBV reactivation could be beneficial to achieve long-term remission of SLE.

A survey of ficolin-3 activity in Systemic Lupus Erythematosus reveals a link to hematological disease manifestations and autoantibody profile

The complement system plays a central role in the pathogenesis of Systemic Lupus Erythematosus (SLE), but most studies have focused on the classical pathway. Ficolin-3 is the main initiator of the lectin pathway of complement in humans, but its role in systemic autoimmune disease has not been conclusively determined. Here, we combined biochemical and genetic approaches to assess the contribution of ficolin-3 to SLE risk and disease manifestations. Ficolin-3 activity was measured by a functional assay in serum or plasma samples from Swedish SLE patients (n = 786) and controls matched for age and sex (n = 566). Genetic variants in an extended 300 kb genomic region spanning the FCN3 locus were analyzed for their association with ficolin-3 activity and SLE manifestations in a Swedish multicenter cohort (n = 985). Patients with ficolin-3 activity in the highest tertile showed a strong enrichment in an SLE cluster defined by anti-Sm/DNA/nucleosome antibodies (OR 3.0, p < 0.001) and had increased rates of hematological disease (OR 1.4, p = 0.078) and lymphopenia (OR = 1.6, p = 0.039). Genetic variants associated with low ficolin-3 activity mapped to an extended haplotype in high linkage disequilibrium upstream of the FCN3 gene. Patients carrying the lead genetic variant associated with low ficolin-3 activity had a lower frequency of hematological disease (OR 0.67, p = 0.018) and lymphopenia (OR 0.63, p = 0.031) and fewer autoantibodies (p = 0.0019). Loss-of-function variants in the FCN3 gene were not associated with SLE, but four (0.5 %) SLE patients developed acquired ficolin-3 deficiency where ficolin-3 activity in serum was depleted following diagnosis of SLE. Taken together, our results provide genetic and biochemical evidence that implicate the lectin pathway in hematological SLE manifestations. We also identify lectin pathway activation through ficolin-3 as a factor that contributes to the autoantibody response in SLE.

Clusters based on demography, disease phenotype, and autoantibody status predicts mortality in lupus: data from Indian lupus cohort (INSPIRE)

OBJECTIVES

SLE is associated with significant mortality, and data from South Asia is limited. Thus, we analysed the causes and predictors of mortality and hierarchical cluster-based survival in the Indian SLE Inception cohort for Research (INSPIRE).

METHODS

Data for patients with SLE was extracted from the INSPIRE database. Univariate analyses of associations between mortality and a number of disease variables were conducted. Agglomerative unsupervised hierarchical cluster analysis was undertaken using 25 variables defining the SLE phenotype. Survival rates across clusters were assessed using non-adjusted and adjusted Cox proportional-hazards models.

RESULTS

Among 2072 patients (with a median follow-up of 18 months), there were 170 deaths (49.2 deaths per 1000 patient-years) of which cause could be determined in 155 patients. 47.1% occurred in the first 6 months. Most of the mortality (n = 87) were due to SLE disease activity followed by coexisting disease activity and infection (n = 24), infections (n = 23), and 21 to other causes. Among the deaths in which infection played a role, 24 had pneumonia. Clustering identified four clusters, and the mean survival estimates were 39.26, 39.78, 37.69 and 35.86 months in clusters 1, 2, 3 and 4, respectively (P < 0.001). The adjusted hazard ratios (HRs) (95% CI) were significant for cluster 4 [2.19 (1.44, 3.31)], low socio-economic-status [1.69 (1.22, 2.35)], number of BILAG-A [1.5 (1.29, 1.73)] and BILAG-B [1.15 (1.01, 1.3)], and need for haemodialysis [4.63 (1.87,11.48)].

CONCLUSION

SLE in India has high early mortality, and the majority of deaths occur outside the health-care setting. Clustering using the clinically relevant variables at baseline may help identify individuals at high risk of mortality in SLE, even after adjusting for high disease activity.

HLA-DR genotypes in patients with systemic lupus erythematosus in Taiwan

BACKGROUND

Different human leukocyte antigen (HLA)-DR genotypes have been known to be associated with the risk of development of systemic lupus erythematosus (SLE) in different populations, although Lu et al. have reported previously that no correlation exists between the HLA-DR genotype and disease manifestation in SLE patients in Taiwan. We investigated the effects different HLA-DR genotypes had on SLE incidence in Taiwanese patients as to whether risk alleles were associated with different clinical manifestations, and the effects risk alleles had on the age of disease onset.

METHODS

Two hundred thirty-four SLE patients and 346 healthy controls were enrolled. HLA-DR genotyping was performed with the HLA FluoGene DRDQ kit for each subject. Chi-square tests and t tests were performed for statistical analysis.

RESULTS

HLA-DR2 was significantly more frequently found in SLE patients than in controls (odds ratio [OR] = 2.05, 95% CI, 1.44-2.92, p < 0.001). Notably, HLA-DR6 appeared to trend toward negative correlation with SLE, whereas HLA-DR8 appeared to trend toward positive correlation. HLA-DR2 patients had an earlier onset of disease as well as a higher prevalence of oral ulcer, avascular necrosis of bone, and renal involvement (lupus nephritis).

CONCLUSION

HLA-DR2 was associated with SLE susceptibility in this Taiwanese population as well as lower age of disease onset and more severe clinical manifestations.

Analysis of transcriptomic features reveals molecular endotypes of SLE with clinical implications

BACKGROUND

Systemic lupus erythematosus (SLE) is known to be clinically heterogeneous. Previous efforts to characterize subsets of SLE patients based on gene expression analysis have not been reproduced because of small sample sizes or technical problems. The aim of this study was to develop a robust patient stratification system using gene expression profiling to characterize individual lupus patients.

METHODS

We employed gene set variation analysis (GSVA) of informative gene modules to identify molecular endotypes of SLE patients, machine learning (ML) to classify individual patients into molecular subsets, and logistic regression to develop a composite metric estimating the scope of immunologic perturbations. SHapley Additive ExPlanations (SHAP) revealed the impact of specific features on patient sub-setting.

RESULTS

Using five datasets comprising 2183 patients, eight SLE endotypes were identified. Expanded analysis of 3166 samples in 17 datasets revealed that each endotype had unique gene enrichment patterns, but not all endotypes were observed in all datasets. ML algorithms trained on 2183 patients and tested on 983 patients not used to develop the model demonstrated effective classification into one of eight endotypes. SHAP indicated a unique array of features influential in sorting individual samples into each of the endotypes. A composite molecular score was calculated for each patient and significantly correlated with standard laboratory measures. Significant differences in clinical characteristics were associated with different endotypes, with those with the least perturbed transcriptional profile manifesting lower disease severity. The more abnormal endotypes were significantly more likely to experience a severe flare over the subsequent 52 weeks while on standard-of-care medication and specific endotypes were more likely to be clinical responders to the investigational product tested in one clinical trial analyzed (tabalumab).

CONCLUSIONS

Transcriptomic profiling and ML reproducibly separated lupus patients into molecular endotypes with significant differences in clinical features, outcomes, and responsiveness to therapy. Our classification approach using a composite scoring system based on underlying molecular abnormalities has both staging and prognostic relevance.

Distinct HLA associations with autoantibody-defined subgroups in idiopathic inflammatory myopathies

BACKGROUND

In patients with idiopathic inflammatory myopathies (IIM), autoantibodies are associated with specific clinical phenotypes suggesting a pathogenic role of adaptive immunity. We explored if autoantibody profiles are associated with specific HLA genetic variants and clinical manifestations in IIM.

METHODS

We included 1348 IIM patients and determined the occurrence of 14 myositis-specific or -associated autoantibodies. We used unsupervised cluster analysis to identify autoantibody-defined subgroups and logistic regression to estimate associations with clinical manifestations, HLA-DRB1, HLA-DQA1, HLA-DQB1 alleles, and amino acids imputed from genetic information of HLA class II and I molecules.

FINDINGS

We identified eight subgroups with the following dominant autoantibodies: anti-Ro52, -U1RNP, -PM/Scl, -Mi2, -Jo1, -Jo1/Ro52, -TIF1γ or negative for all analysed autoantibodies. Associations with HLA-DRB1∗11, HLA-DRB1∗15, HLA-DQA1∗03, and HLA-DQB1∗03 were present in the anti-U1RNP-dominated subgroup. HLA-DRB1∗03, HLA-DQA1∗05, and HLA-DQB1∗02 alleles were overrepresented in the anti-PM/Scl and anti-Jo1/Ro52-dominated subgroups. HLA-DRB1∗16, HLA-DRB1∗07 alleles were most frequent in anti-Mi2 and HLA-DRB1∗01 and HLA-DRB1∗07 alleles in the anti-TIF1γ subgroup. The HLA-DRB1∗13, HLA-DQA1∗01 and HLA-DQB1∗06 alleles were overrepresented in the negative subgroup. Significant signals from variations in class I molecules were detected in the subgroups dominated by anti-Mi2, anti-Jo1/Ro52, anti-TIF1γ, and the negative subgroup.

INTERPRETATION

Distinct HLA class II and I associations were observed for almost all autoantibody-defined subgroups. The associations support autoantibody profiles use for classifying IIM which would likely reflect underlying pathogenic mechanisms better than classifications based on clinical symptoms and/or histopathological features.

FUNDING

See a detailed list of funding bodies in the Acknowledgements section at the end of the manuscript.

Machine learning: Predicting hospital length of stay in patients admitted for lupus flares

BACKGROUND

Although rare, severe systemic lupus erythematosus (SLE) flares requiring hospitalization account for most of the direct costs of SLE care. New machine learning (ML) methods may optimize lupus care by predicting which patients will have a prolonged hospital length of stay (LOS). Our study uses a machine learning approach to predict the LOS in patients admitted for lupus flares and assesses which features prolong LOS.

METHODS

Our study sampled 5831 patients admitted for lupus flares from the National Inpatient Sample Database 2016-2018 and collected 90 demographics and comorbidity features. Four machine learning (ML) models were built (XGBoost, Linear Support Vector Machines, K Nearest Neighbors, and Logistic Regression) to predict LOS, and their performance was evaluated using multiple metrics, including accuracy, receiver operator area under the curve (ROC-AUC), precision-recall area under the curve (PR- AUC), and F1-score. Using the highest-performing model (XGBoost), we assessed the feature importance of our input features using Shapley value explanations (SHAP) to rank their impact on LOS.

RESULTS

Our XGB model performed the best with a ROC-AUC of 0.87, PR-AUC of 0.61, an F1 score of 0.56, and an accuracy of 95%. The features with the most significant impact on the model were "the need for a central line," "acute dialysis," and "acute renal failure." Other top features include those related to renal and infectious comorbidities.

CONCLUSION

Our results were consistent with the established literature and showed promise in ML over traditional methods of predictive analyses, even with rare rheumatic events such as lupus flare hospitalizations.

B cell polygenic risk scores associate with anti-dsDNA antibodies and nephritis in systemic lupus erythematosus

OBJECTIVE

B cell function and autoantibodies are important in SLE pathogenesis. In this work, we aimed to investigate the impact of cumulative SLE B cell genetics on SLE subphenotype and autoantibody profile.

METHODS

Female patients with SLE (n=1248) and healthy controls (n=400) were genotyped using Illumina's Global Screening Array. Two polygenic risk scores (PRSs), one representing B cell genes and the other B cell activation genes, were calculated for each individual using risk loci for SLE in genes assigned to B cell-related pathways according to the Kyoto Encyclopedia of Genes and Genomes, Gene Ontology and Reactome Databases.

RESULTS

Double-stranded DNA (dsDNA) antibodies were more prevalent among patients with a high compared with a low SLE B cell PRS (OR 1.47 (1.07 to 2.01), p=0.018), and effect sizes were augmented in patients with human leucocyte antigen (HLA) risk haplotypes HLA-DRB1*03:01 and HLA-DRB1*15:01 (DRB1*03/15 -/- (OR 0.99 (0.56 to 1.77), p=0.98; DRB1*03/15 +/- or -/+ (OR 1.64 (1.06 to 2.54), p=0.028; and DRB1*03/15 +/+ (OR 4.47 (1.21 to 16.47), p=0.024). Further, a high compared with a low B cell PRS was associated with low complement levels in DRB1*03/15 +/+ patients (OR 3.92 (1.22 to 12.64), p=0.022). The prevalence of lupus nephritis (LN) was higher in patients with a B cell activation PRS above the third quartile compared with patients below (OR 1.32 (1.00 to 1.74), p=0.048).

CONCLUSIONS

High genetic burden related to B cell function is associated with dsDNA antibody development and LN. Assessing B cell PRSs may be important in order to determine immunological pathways influencing SLE and to predict clinical phenotype.

Acute and post-acute sequelae of SARS-CoV-2 infection: a review of risk factors and social determinants

SARS-CoV-2 infection leading to Coronavirus Disease 2019 (COVID-19) has caused more than 762 million infections worldwide, with 10-30% of patients suffering from post-acute sequelae of SARS-CoV-2 infections (PASC). Initially thought to primarily affect the respiratory system, it is now known that SARS-CoV-2 infection and PASC can cause dysfunction in multiple organs, both during the acute and chronic stages of infection. There are also multiple risk factors that may predispose patients to worse outcomes from acute SARS-CoV-2 infection and contribute to PASC, including genetics, sex differences, age, reactivation of chronic viruses such as Epstein Barr Virus (EBV), gut microbiome dysbiosis, and behavioral and lifestyle factors, including patients' diet, alcohol use, smoking, exercise, and sleep patterns. In addition, there are important social determinants of health, such as race and ethnicity, barriers to health equity, differential cultural perspectives and biases that influence patients' access to health services and disease outcomes from acute COVID-19 and PASC. Here, we review risk factors in acute SARS-CoV-2 infection and PASC and highlight social determinants of health and their impact on patients affected with acute and chronic sequelae of COVID-19.

Disentangling the Pathogenesis of Systemic Lupus Erythematosus: Close Ties between Immunological, Genetic and Environmental Factors

Systemic Lupus Erythematosus (SLE) is a systemic autoimmune disease that attacks various organ systems with a variety of clinical implications, ranging from mild skin and mucosal manifestations to severe central nervous system manifestations and death. Cases of SLE have been documented nearly two centuries ago when scholars used the terms 'erythema centrifugum' and 'seborrhea congestiva' to describe the discoid skin lesions and the butterfly or malar rash in SLE. Since then, knowledge about this disease has developed rapidly, especially knowledge related to the underlying pathogenesis of SLE. To date, it is known that immune system dysregulation, supported by genetic and environmental predisposition, can trigger the occurrence of SLE in a group of susceptible individuals. Various inflammatory mediators, cytokines and chemokines, as well as intra- and intercellular signaling pathways, are involved in the pathogenesis of SLE. In this review, we will discuss the molecular and cellular aspects of SLE pathogenesis, with a focus on how the immune system, genetics and the environment interact and trigger the various clinical manifestations of SLE.

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.

Autoantibody-based subgroups and longitudinal seroconversion in juvenile-onset systemic lupus erythematosus

OBJECTIVE

To explore the clinical value of autoantibody-based subgroup framework and the trend of autoantibody fluctuation in juvenile-onset SLE (JSLE).

METHODS

Eighty-seven patients with JSLE were retrospectively collected and divided into subgroups via a two-step cluster based on the status of nine autoantibodies (double-stranded-DNA (dsDNA), nucleosome, histone, ribosomal P protein, Smith (Sm), u1-ribonucleoprotein (RNP), Sjögren's syndrome antigen A (SSA)/Ro52, SSA/Ro60, Sjögren's syndrome antigen B (SSB)/La). The final model selected in this study was based on adequate goodness of fit of the Silhouette coefficient and clinical interpretability. Clinical manifestations, organ involvements and disease activity were compared among the subgroups. Fluctuation in autoantibody status was also collected and analysed. Flare-free survival rates of the patients with positive/negative seroconversion and patients without seroconversion were studied by the Kaplan-Meier method and compared using a log-rank test.

RESULTS

Two clusters were identified: subgroup 1 (positive anti-Sm/RNP group) and subgroup 2 (negative anti-Sm/RNP group). There were more lupus nephritis (LN) and neuropsychiatric SLE (NPSLE) cases in subgroup 1 than in subgroup 2. Patients in subgroup 1 exhibited higher SLE Disease Activity Index scores compared with those in subgroup 2. Furthermore, anti-ribosomal P protein (61.1%), anti-nucleosome (58.3%) and anti-dsDNA (54%) were most commonly positive autoantibodies. A progressive decrease in the frequency of patients with positive results was demonstrated during the follow-up years. The decrease was notable for anti-dsDNA, anti-nucleosome and anti-ribosomal P protein (remaining 27.27%, 38.89% and 45.00% positive in the fifth year, respectively). While for those negative at baseline diagnosis, the decrease in the frequency of negative results was progressive but modest. Kaplan-Meier curve showed that the flare-free survival of patients with positive seroconversion was significantly lower than those without seroconversion and those with negative seroconversion (p<0.001).

CONCLUSIONS

In children with SLE, subgroups based on autoantibody profile can be applied to differentiate phenotypes and disease activity. Two important organ involvements, LN and NPSLE, are more common in patients with positive anti-Sm/RNP autoantibodies. Positive seroconversion may provide a valuable perspective for assessing flare, and it is worthwhile to retest the array of autoantibodies during follow-up.

Genetic variations in low-to-medium-affinity Fcγ receptors and autoimmune neutropenia in early childhood in a Danish cohort

Autoimmune neutropenia (AIN) in early childhood is caused by autoantibodies directed against antigens on the neutrophil membrane and is a frequent cause of neutropenia in children. Association of AIN with Fcγ receptor (FCGR) 3B variants is well described. In this study, we investigate genetic variations in the FCGR locus and copy number variation of FCGR3B. A total of 130 antibody-positive AIN patients, 64 with specific anti-HNA-1a antibodies and 66 with broad-reacting anti-FcγRIIIb antibodies, were genotyped with a multiplex ligation probe assay and compared with healthy controls. Positive findings were confirmed with real-time q-PCR. We determined copy numbers of the FCGR2 and FCGR3 genes and the following SNPs: FCGR2A Q62W (rs201218628), FCGR2A H166R (rs1801274), FCGR2B I232T (rs1050501), FCGR3A V176F (rs396991), haplotypes for FCGR2B/C promoters (rs3219018/rs780467580), FCGR2C STOP/ORF and HNA-1 genotypes in FCGR3B (rs447536, rs448740, rs52820103, rs428888 and rs2290834). Generally, associations were antibody specific, with all associations being representative of the anti-HNA-1a-positive group, while the only association found in the anti-FcγRIIIb group was with the HNA-1 genotype. An increased risk of AIN was observed for patients with one copy of FCGR3B; the HNA genotypes HNA-1a, HNA-1aa or HNA-1aac; the FCGR2A 166H and FCGR2B 232I variations; and no copies of FCGR2B 2B.4. A decreased risk was observed for HNA genotype HNA-1bb; FCGR2A 166R; FCGR2B 232T; and one copy of FCGR2B promoter 2B.4. We conclude that in our Danish cohort, there was a strong association between variation in the FCGR locus and AIN. The findings of different genetic associations between autoantibody groups could indicate the presence of two different disease entities and disease heterogeneity.

Application of Machine Learning Models in Systemic Lupus Erythematosus

Systemic Lupus Erythematosus (SLE) is a systemic autoimmune disease and is extremely heterogeneous in terms of immunological features and clinical manifestations. This complexity could result in a delay in the diagnosis and treatment introduction, with impacts on long-term outcomes. In this view, the application of innovative tools, such as machine learning models (MLMs), could be useful. Thus, the purpose of the present review is to provide the reader with information about the possible application of artificial intelligence in SLE patients from a medical perspective. To summarize, several studies have applied MLMs in large cohorts in different disease-related fields. In particular, the majority of studies focused on diagnosis and pathogenesis, disease-related manifestations, in particular Lupus Nephritis, outcomes and treatment. Nonetheless, some studies focused on peculiar features, such as pregnancy and quality of life. The review of published data demonstrated the proposal of several models with good performance, suggesting the possible application of MLMs in the SLE scenario.

Anti-phosphatidylserine/prothrombin antibodies and thrombosis associate positively with HLA-DRB1*13 and negatively with HLA-DRB1*03 in SLE

OBJECTIVES

Emerging evidence demonstrates that aPS-PT associate with thrombotic events. Genetic predisposition, including HLA-DRB1 alleles, is known to contribute to the occurrence of conventional aPL [anti-β2glycoprotein-I (anti-β2GPI) and aCL]. We investigated associations between aPS-PT and HLA-DRB1* alleles and thrombosis in SLE. Conventional aPL were included for comparison.

METHODS

We included 341 consecutive SLE patients, with information on general cardiovascular risk factors, including blood lipids, LA and thrombotic events. aPS/PT, anti-β2GPI and aCL of IgA/G/M isotypes and LA were quantified.

RESULTS

aPS/PT antibodies associated positively with HLA-DRB1*13 [odds ratio (OR) 2.7, P = 0.002], whereas anti-β2GPI and aCL antibodies associated primarily with HLA-DRB1*04 (OR 2.5, P = 0.0005). These associations remained after adjustment for age, gender and other HLA-DRB1* alleles. HLA-DRB1*13, but not DRB1*04, remained as an independent risk factor for thrombosis and APS after adjustment for aPL and cardiovascular risk factors. The association between DRB1*13 and thrombosis was mediated by aPS-PT positivity. HLA-DRB1*03, on the other hand, associated negatively with thrombotic events as well as all aPL using both uni- and multivariate analyses. HLA-DRB1*03 had a thrombo-protective effect in aPL-positive patients. Additionally, HLA-DRB1*03 was associated with a favourable lipid profile regarding high-density lipoprotein and triglycerides.

CONCLUSIONS

HLA-DRB1*13 confers risk for both aPS-PT and thrombotic events in lupus. The association between HLA-DRB1*13 and thrombosis is largely, but not totally, mediated through aPS-PT. HLA-DRB1*03 was negatively associated with aPL and positively with favourable lipid levels. Thus, HLA-DRB1*03 seems to identify a subgroup of SLE patients with reduced vascular risk.

Complement C4 Copy Number Variation is Linked to SSA/Ro and SSB/La Autoantibodies in Systemic Inflammatory Autoimmune Diseases

OBJECTIVE

Copy number variation of the C4 complement components, C4A and C4B, has been associated with systemic inflammatory autoimmune diseases. This study was undertaken to investigate whether C4 copy number variation is connected to the autoimmune repertoire in systemic lupus erythematosus (SLE), primary Sjögren's syndrome (SS), or myositis.

METHODS

Using targeted DNA sequencing, we determined the copy number and genetic variants of C4 in 2,290 well-characterized Scandinavian patients with SLE, primary SS, or myositis and 1,251 healthy controls.

RESULTS

A prominent relationship was observed between C4A copy number and the presence of SSA/SSB autoantibodies, which was shared between the 3 diseases. The strongest association was detected in patients with autoantibodies against both SSA and SSB and 0 C4A copies when compared to healthy controls (odds ratio [OR] 18.0 [95% confidence interval (95% CI) 10.2-33.3]), whereas a weaker association was seen in patients without SSA/SSB autoantibodies (OR 3.1 [95% CI 1.7-5.5]). The copy number of C4 correlated positively with C4 plasma levels. Further, a common loss-of-function variant in C4A leading to reduced plasma C4 was more prevalent in SLE patients with a low copy number of C4A. Functionally, we showed that absence of C4A reduced the individuals' capacity to deposit C4b on immune complexes.

CONCLUSION

We show that a low C4A copy number is more strongly associated with the autoantibody repertoire than with the clinically defined disease entities. These findings may have implications for understanding the etiopathogenetic mechanisms of systemic inflammatory autoimmune diseases and for patient stratification when taking the genetic profile into account.

The long and winding road: From mouse linkage studies to a novel human therapeutic pathway in type 1 diabetes

Autoimmunity involves a loss of immune tolerance to self-proteins due to a combination of genetic susceptibility and environmental provocation, which generates autoreactive T and B cells. Genetic susceptibility affects lymphocyte autoreactivity at the level of central tolerance (e.g., defective, or incomplete MHC-mediated negative selection of self-reactive T cells) and peripheral tolerance (e.g., failure of mechanisms to control circulating self-reactive T cells). T regulatory cell (Treg) mediated suppression is essential for controlling peripheral autoreactive T cells. Understanding the genetic control of Treg development and function and Treg interaction with T effector and other immune cells is thus a key goal of autoimmunity research. Herein, we will review immunogenetic control of tolerance in one of the classic models of autoimmunity, the non-obese diabetic (NOD) mouse model of autoimmune Type 1 diabetes (T1D). We review the long (and still evolving) elucidation of how one susceptibility gene, Cd137, (identified originally via linkage studies) affects both the immune response and its regulation in a highly complex fashion. The CD137 (present in both membrane and soluble forms) and the CD137 ligand (CD137L) both signal into a variety of immune cells (bi-directional signaling). The overall outcome of these multitudinous effects (either tolerance or autoimmunity) depends upon the balance between the regulatory signals (predominantly mediated by soluble CD137 via the CD137L pathway) and the effector signals (mediated by both membrane-bound CD137 and CD137L). This immune balance/homeostasis can be decisively affected by genetic (susceptibility vs. resistant alleles) and environmental factors (stimulation of soluble CD137 production). The discovery of the homeostatic immune effect of soluble CD137 on the CD137-CD137L system makes it a promising candidate for immunotherapy to restore tolerance in autoimmune diseases.

The Interaction of Anti-DNA Antibodies with DNA: Evidence for Unconventional Binding Mechanisms

Antibodies to DNA (anti-DNA) are the serological hallmark of systemic lupus erythematosus, a prototypic autoimmune disease. These antibodies bind to conserved sites on single-stranded and double-stranded DNA and display variable region somatic mutations consistent with antigen selection. Nevertheless, the interaction of anti-DNA with DNA has unconventional features. Anti-DNA antibodies bind by a mechanism called monogamous bivalency, in which stable interaction requires contact of both Fab sites with determinants on the same extended DNA molecule; the size of this DNA can be hundreds to thousands of bases, especially in solid phase assays. This binding also requires the presence of the Fc portion of IgG, a binding mechanism known as Fc-dependent monogamous bivalency. As shown by the effects of ionic strength in association and dissociation assays, anti-DNA binding is primarily electrostatic. Like anti-DNA autoantibodies, anti-DNA antibodies that bind specifically to non-conserved sites on bacterial DNA, a type of anti-DNA found in otherwise healthy individuals, also interact by monogamous bivalency. The unconventional features of anti-DNA antibodies may reflect the highly charged and polymeric nature of DNA and the need for molecular rearrangements to facilitate monogamous bivalency; the Fc portion contributes to binding in an as yet unknown way.

Antibodies to Porphyromonas gingivalis Are Increased in Patients with Severe Periodontitis, and Associate with Presence of Specific Autoantibodies and Myocardial Infarction

There is accumulating data suggesting that periodontitis is associated with increased risk of systemic and autoimmune diseases, including cardiovascular disease, rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE), and there is an unmet need to identify these individuals early. With the periodontal bacteria Porphyromonas gingivalis (Pg) as one of the key drivers of periodontitis, we set out to investigate whether antibodies to Pg virulence factor arginine gingipain (Rgp) could serve as a biomarker for periodontitis patients at increased risk of autoimmunity and systemic disease. We measured serum anti-Rgp IgG in three study populations: PAROKRANK (779 individuals with myocardial infarction (MI); 719 controls), where 557 had periodontitis, and 312 were positive for autoantibodies associated with RA/SLE; the PerioGene North pilot (41 periodontitis; 39 controls); and an SLE case/control study (101 SLE; 100 controls). Anti-Rgp IgG levels were increased in severe periodontitis compared to controls (p < 0.0001), in individuals positive for anti-citrullinated protein antibodies (p = 0.04) and anti-dsDNA antibodies (p = 0.035), compared to autoantibody-negative individuals; and in MI patients versus matched controls (p = 0.035). Our data support longitudinal studies addressing the role of anti-Rgp antibodies as biomarkers for periodontitis patients at increased risk of developing autoimmunity linked to RA and SLE, and mechanisms underpinning these associations.