Antibodies Isolated from Rheumatoid Arthritis Patients against Lysine-Containing Proteus mirabilis O3 (S1959) Lipopolysaccharide May React with Collagen Type I

Proteomics Landscape Mapping of Organ-Resolved Behçet's Disease Using In-Depth Plasma Proteomics for Identifying Hyaluronic Binding Protein 2 Expression Associated With Vascular Involvement

OBJECTIVE

This study was undertaken to elucidate the pathogenesis and heterogeneity of Behçet's disease (BD) involving different organs using in-depth proteomics to identify the biomarkers for clinical assessment and treatment of patients with BD.

METHODS

We measured the expression levels of proteins in plasma samples from 98 patients with BD and from 31 healthy controls using our in-depth proteomics platform with a data-independent acquisition mass spectrometer and antibody microarray. We performed bioinformatics analyses of the biologic processes and signaling pathways that were changed in the BD group and constructed a proteomics landscape of organ-resolved BD pathogenesis. We then validated the biomarkers of disease severity and the vascular subset in an independent cohort of 108 BD patients and 29 healthy controls using an enzyme-linked immunosorbent assay.

RESULTS

The BD group had 220 differentially expressed proteins, which discriminated between BD patients (88.6%) and healthy controls (95.5%). The bioinformatics analyses revealed different biologic processes associated with BD pathogeneses, including complement activation, wound healing, angiogenesis, and leukocyte-mediated immunity. Furthermore, the constructed proteomics landscape of organ-resolved BD identified proteomics features of BD associated with different organs and protein targets that could be used for the development of therapeutic treatment. Hyaluronic binding protein 2, tenascin, and serpin A3 were validated as potential biomarkers for the clinical assessment of vascular BD and treatment targets.

CONCLUSION

Our results provide valuable insight into the pathogenesis of organ-resolved BD in terms of proteomics characteristics and potential biomarkers for clinical assessment and potential therapies for vascular BD.

Prevalence of anti-SARS-CoV-2 IgG antibodies in a group of patients, a control group, and healthcare workers of Thrace area in Greece, by the use of two distinct methods

Introduction

The aim of this study was to assess the clinical performance of different automated immunoassays available in Europe to detect anti-SARS-CoV-2 antibodies; an ELISA assay and a CLIA. The second goal was to estimate the seroprevalence of SARS-CoV-2 antibodies among healthcare workers in Evros area during the first pandemic wave of COVID-19.

Methods

The study included serum samples from 101 patients with confirmed COVID-19 by RT-PCR and 208 negative patients. Furthermore, it included 1036 healthcare workers (HWs) of the Evros Region, Northern Greece. The measurement of anti-SARS-CoV-2 antibodies was performed using the Abbott SARS-CoV-2 IgG and anti-SARS-CoV-2 ELISA IgG assay (Epitope Diagnostics, USA).

Results

Of 101 confirmed COVID-19 patients, 82 were hospitalized and 19 were outpatients. Hospitalized patients had higher IgG levels in comparison to outpatients (6.46±2.2 vs. 3.52±1.52, p<0.001). Of 208 non-COVID-19 patients only 1 was positive in both ELISA and CLIA assay. SARS-CoV-2-IgG antibodies were detected in 6 HWs out of 1036 (0.58%) with mean S/CO-value of anti-SARS-CoV-2 IgG 3.12±1.3 (confidence interval 0.95), which was lower than in COVID-19 patients (3.12 vs. 5.9; p=0.016). The clinical evaluation of two immunoassays showed remarkably high true positivity rates in the confirmed COVID-19 patients. Sensitivities obtained with CLIA and ELISA methods were 99.02% vs. 97.09% and specificities 99.52% vs 99.05% respectively.

Conclusions

We found an acceptable accordance between CLIA and ELISA assays in the confirmed COVID-19 patients. In all subjects included in this study in the past medical history, the information that was obtained included details about the presence of autoimmune diseases.

Correlations between autoantibodies and the ATR-FTIR spectra of sera from rheumatoid arthritis patients

Rheumatoid arthritis (RA) is one of the most common autoimmune diseases worldwide. Due to high heterogeneity in disease manifestation, accurate and fast diagnosis of RA is difficult. This study analyzed the potential relationship between the infrared (IR) spectra obtained by attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR) and the presence of autoantibodies and antibodies against urease in sera. Additionally, the wave number of the IR spectrum that enabled the best differentiation between patients and healthy blood donors was investigated. Using a mathematical model involving principal component analysis and discriminant analysis, it was shown that the presence of anti-citrullinated protein antibody, rheumatoid factor, anti-neutrophil cytoplasmic antibodies, and anti-nuclear antibodies correlated significantly with the wave numbers in the IR spectra of the tested sera. The most interesting findings derived from determination of the best predictors for distinguishing RA. Characteristic features included an increased reaction with urease mimicking peptides and a correspondence with particular nucleic acid bands. Taken together, the results demonstrated the potential application of ATR-FTIR in the study of RA and identified potential novel markers of the disease.

Haemophilus parasuis (Glaesserella parasuis) as a Potential Driver of Molecular Mimicry and Inflammation in Rheumatoid Arthritis

Background:Haemophilus parasuis (Hps; now Glaesserella parasuis) is an infectious agent that causes severe arthritis in swines and shares sequence similarity with residues 261–273 of collagen type 2 (Coll_261−273), a possible autoantigen in rheumatoid arthritis (RA).

Objectives/methods: We tested the presence of Hps sequencing 16S ribosomal RNA in crevicular fluid, synovial fluids, and tissues in patients with arthritis (RA and other peripheral arthritides) and in healthy controls. Moreover, we examined the cross-recognition of Hps by Coll_261−273-specific T cells in HLA-DRB1^*04^pos RA patients, by T-cell receptor (TCR) beta chain spectratyping and T-cell phenotyping.

Results:Hps DNA was present in 57.4% of the tooth crevicular fluids of RA patients and in 31.6% of controls. Anti-Hps IgM and IgG titers were detectable and correlated with disease duration and the age of the patients. Peripheral blood mononuclear cells (PBMCs) were stimulated with Hps virulence-associated trimeric autotransporter peptide (VtaA10_755−766), homologous to human Coll_261−273 or co-cultured with live Hps. In both conditions, the expanded TCR repertoire overlapped with Coll_261−273 and led to the production of IL-17.

Discussion: We show that the DNA of an infectious agent (Hps), not previously described as pathogen in humans, is present in most patients with RA and that an Hps peptide is able to activate T cells specific for Coll_261−273, likely inducing or maintaining a molecular mimicry mechanism.

Conclusion: The cross-reactivity between VtaA10_755−766 of a non-human infectious agent and human Coll_261−273 suggests an involvement in the pathogenesis of RA. This mechanism appears emphasized in predisposed individuals, such as patients with shared epitope.

Mining the capacity of human-associated microorganisms to trigger rheumatoid arthritis-A systematic immunoinformatics analysis of T cell epitopes

Autoimmune diseases, often triggered by infection, affect ~5% of the worldwide population. Rheumatoid Arthritis (RA)–a painful condition characterized by the chronic inflammation of joints—comprises up to 20% of known autoimmune pathologies, with the tendency of increasing prevalence. Molecular mimicry is recognized as the leading mechanism underlying infection-mediated autoimmunity, which assumes sequence similarity between microbial and self-peptides driving the activation of autoreactive lymphocytes. T lymphocytes are leading immune cells in the RA-development. Therefore, deeper understanding of the capacity of microorganisms (both pathogens and commensals) to trigger autoreactive T cells is needed, calling for more systematic approaches. In the present study, we address this problem through a comprehensive immunoinformatics analysis of experimentally determined RA-related T cell epitopes against the proteomes of Bacteria, Fungi, and Viruses, to identify the scope of organisms providing homologous antigenic peptide determinants. By this, initial homology screening was complemented with de novo T cell epitope prediction and another round of homology search, to enable: i) the confirmation of homologous microbial peptides as T cell epitopes based on the predicted binding affinity to RA-related HLA polymorphisms; ii) sequence similarity inference for top de novo T cell epitope predictions to the RA-related autoantigens to reveal the robustness of RA-triggering capacity for identified (micro/myco)organisms. Our study reveals a much larger repertoire of candidate RA-triggering organisms, than previously recognized, providing insights into the underestimated role of Fungi in autoimmunity and the possibility of a more direct involvement of bacterial commensals in RA-pathology. Finally, our study pinpoints Endoplasmic reticulum chaperone BiP as the most potent (most likely mimicked) RA-related autoantigen, opening an avenue for identifying the most potent autoantigens in a variety of different autoimmune pathologies, with possible implications in the design of next-generation therapeutics aiming to induce self-tolerance by affecting highly reactive autoantigens.