Aberrant B cell receptor signaling in circulating naïve and IgA+ memory B cells from newly-diagnosed autoantibody-positive rheumatoid arthritis patients.

OBJECTIVE: Altered B cell receptor (BCR) signaling has been implicated in the pathogenesis of rheumatoid arthritis (RA). Here we aimed to identify signaling aberrations in autoantibody-positive and autoantibody-negative RA patients by performing a comprehensive analysis of the BCR signaling cascade in different B cell subsets. METHODS: We first optimized phosphoflow cytometry for an in-depth analysis of BCR signaling across immunoglobulin isotypes in healthy donors. Subsequently, we compared BCR signaling in circulating B cell subsets from treatment-naïve, newly-diagnosed autoantibody-positive RA and autoantibody-negative RA patients and healthy controls (HCs). RESULTS: We observed subset-specific phosphorylation patterns of the BCR signalosome in circulating B cells from healthy donors. Compared with HCs, autoantibody-positive RA patients displayed enhanced responses to BCR stimulation for multiple signaling proteins, specifically in naïve and IgA+ memory B cells. Whereas in unstimulated healthy donor B cells, the phosphorylation status of individual signaling proteins showed only limited correlation, BCR stimulation enhanced the interconnectivity in phosphorylation within the BCR signalosome. However, this strong interconnectivity within the BCR signalosome in stimulated B cells from HCs was lost in RA, especially in autoantibody-positive RA patients. Finally, we observed strong correlations between SYK and BTK protein expression, and IgA and IgG anti-citrullinated protein antibody concentrations in serum from autoantibody-positive RA patients. CONCLUSION: Collectively, the isotype-specific analysis of multiple key components of the BCR signalosome identified aberrant BCR signaling responses in treatment-naïve autoantibody-positive RA patients, particularly in naïve B cells and IgA+ memory B cells. Our findings support differential involvement of dysregulated BCR signaling in the pathogenesis of autoantibody-positive and autoantibody-negative RA.

The course of cytokine and chemokine gene expression in clinically suspect arthralgia patients during progression to inflammatory arthritis.

OBJECTIVES: Autoantibody responses increase years before the onset of inflammatory arthritis (IA) and are stable during transitioning from clinically suspect arthralgia (CSA) to IA. Cytokine and chemokine levels also increase years before IA onset. However, the course in the at-risk stage of CSA during progression to disease or non-progression is unknown. To increase the understanding of processes mediating disease development, we studied the course of cytokine, chemokine and related receptors gene expression in CSA patients during progression to IA and in CSA patients who ultimately did not develop IA. METHODS: Whole-blood RNA expression of 37 inflammatory cytokines, chemokines and related receptors was determined by dual-colour reverse transcription multiplex ligation-dependent probe amplification in paired samples of CSA patients at CSA onset and either at IA development or after 24 months without IA development. ACPA-positive and ACPA-negative CSA patients developing IA were compared at CSA onset and during progression to IA. Generalised estimating equations tested changes over time. A false discovery rate approach was applied. RESULTS: None of the cytokine/chemokine genes significantly changed in expression between CSA onset and IA development. In CSA patients without IA development, G-CSF expression decreased (P = 0.001), whereas CCR6 and TNIP1 expression increased (P < 0.001 and P = 0.002, respectively) over a 2 year period. Expression levels in ACPA-positive and ACPA-negative CSA patients who developed IA were similar. CONCLUSION: Whole-blood gene expression of assessed cytokines, chemokines and related receptors did not change significantly from CSA to IA development. This suggests that changes in expression of these molecules may not be related to the final process of developing chronicity and may have occurred preceding CSA onset. Changes in gene expression in CSA patients without IA development may provide clues for processes related to resolution.

Machine learning identifies a profile of inadequate responder to methotrexate in rheumatoid arthritis.

OBJECTIVES: Around 30% of patients with RA have an inadequate response to MTX. We aimed to use routine clinical and biological data to build machine learning models predicting EULAR inadequate response to MTX and to identify simple predictive biomarkers. METHODS: Models were trained on RA patients fulfilling the 2010 ACR/EULAR criteria from the ESPOIR and Leiden EAC cohorts to predict the EULAR response at 9 months (± 6 months). Several models were compared on the training set using the AUROC. The best model was evaluated on an external validation cohort (tREACH). The model's predictions were explained using Shapley values to extract a biomarker of inadequate response. RESULTS: We included 493 therapeutic sequences from ESPOIR, 239 from EAC and 138 from tREACH. The model selected DAS28, Lymphocytes, Creatininemia, Leucocytes, AST, ALT, swollen joint count and corticosteroid co-treatment as predictors. The model reached an AUROC of 0.72 [95% CI (0.63, 0.80)] on the external validation set, where 70% of patients were responders to MTX. Patients predicted as inadequate responders had only 38% [95% CI (20%, 58%)] chance to respond and using the algorithm to decide to initiate MTX would decrease inadequate-response rate from 30% to 23% [95% CI: (17%, 29%)]. A biomarker was identified in patients with moderate or high activity (DAS28 > 3.2): patients with a lymphocyte count superior to 2000 cells/mm3 are significantly less likely to respond. CONCLUSION: Our study highlights the usefulness of machine learning in unveiling subgroups of inadequate responders to MTX to guide new therapeutic strategies. Further work is needed to validate this approach.

A semi-supervised decision support system to facilitate antibiotic stewardship for urinary tract infections.

Urinary Tract Infections (UTIs) are among the most frequently occurring infections in the hospital. Urinalysis and urine culture are the main tools used for diagnosis. Whereas urinalysis is sufficiently sensitive for detecting UTI, it has a relatively low specificity, leading to unnecessary treatment with antibiotics and the risk of increasing antibiotic resistance. We performed an evaluation of the current diagnostic process with an expert-based label for UTI as outcome, retrospectively established using data from the Electronic Health Records. We found that the combination of urinalysis results with the Gram stain and other readily available parameters can be used effectively for predicting UTI. Based on the obtained information, we engineered a clinical decision support system (CDSS) using the reliable semi-supervised ensemble learning (RESSEL) method, and found it to be more accurate than urinalysis or the urine culture for prediction of UTI. The CDSS provides clinicians with this prediction within hours of ordering a culture and thereby enables them to hold off on prematurely prescribing antibiotics for UTI while awaiting the culture results.

Basic FGF and PDGF-BB synergistically stimulate hyaluronan and IL-6 production by orbital fibroblasts.

Orbital fibroblast activation is a central pathologic feature of Graves' Ophthalmopathy (GO). Basic fibroblast growth factor (bFGF) and vascular endothelial growth factor (VEGF) have been proposed to contribute to GO, but their effects on orbital fibroblasts are largely unknown. We found that bFGF stimulated proliferation and hyaluronan production, but not IL-6 production by orbital fibroblasts, while VEGF hardly affected orbital fibroblast activity. Remarkably, co-stimulation of orbital fibroblasts with bFGF and PDGF-BB synergistically enhanced IL-6 and hyaluronan production and displayed an additive effect on proliferation compared to either bFGF or PDGF-BB stimulation. Nintedanib, a FGF- and PDGF-receptor targeting drug, more efficiently blocked bFGF + PDGF-BB-induced IL-6 and hyaluronan production than dasatinib that only targets PDGF-receptor. In conclusion, bFGF may contribute to orbital inflammation and tissue remodeling in GO, especially through synergistic interaction with PDGF-BB. Multi-target therapy directed at the bFGF and PDGF pathways may potentially be of interest for the treatment of GO.