Urinary markers differentially associate with kidney inflammatory activity and chronicity measures in patients with lupus nephritis

Objective Lupus nephritis (LN) is diagnosed by biopsy, but longitudinal monitoring assessment methods are needed. Here, in this preliminary and hypothesis-generating study, we evaluate the potential for using urine proteomics as a non-invasive method to monitor disease activity and damage. Urinary biomarkers were identified and used to develop two novel algorithms that were used to predict LN activity and chronicity.Methods Baseline urine samples were collected for four cohorts (healthy donors (HDs, n=18), LN (n=42), SLE (n=17) or non-LN kidney disease biopsy control (n=9)), and over 1 year for patients with LN (n=42). Baseline kidney biopsies were available for the LN (n=46) and biopsy control groups (n=9). High-throughput proteomics platforms were used to identify urinary analytes ≥1.5 SD from HD means, which were subjected to stepwise, univariate and multivariate logistic regression modelling to develop predictive algorithms for National Institutes of Health Activity Index (NIH-AI)/National Institutes of Health Chronicity Index (NIH-CI) scores. Kidney biopsies were analysed for macrophage and neutrophil markers using immunohistochemistry (IHC).Results In total, 112 urine analytes were identified from LN, SLE and biopsy control patients as both quantifiable and overexpressed compared with HDs. Regression analysis identified proteins associated with the NIH-AI (n=30) and NIH-CI (n=26), with four analytes common to both groups, demonstrating a difference in the mechanisms associated with NIH-AI and NIH-CI. Pathway analysis of the NIH-AI and NIH-CI analytes identified granulocyte-associated and macrophage-associated pathways, and the presence of these cells was confirmed by IHC in kidney biopsies. Four markers each for the NIH-AI and NIH-CI were identified and used in the predictive algorithms. The NIH-AI algorithm sensitivity and specificity were both 93% with a false-positive rate (FPR) of 7%. The NIH-CI algorithm sensitivity was 88%, specificity 96% and FPR 4%. The accuracy for both models was 93%.Conclusions Longitudinal predictions suggested that patients with baseline NIH-AI scores of ≥8 were most sensitive to improvement over 6–12 months. Viable approaches such as this may enable the use of urine samples to monitor LN over time

Using the circulating proteome to assess type I interferon activity in systemic lupus erythematosus.

Type I interferon (IFN) drives pathology in systemic lupus erythematosus (SLE) and can be tracked via IFN-inducible transcripts in blood. Here, we examined whether measurement of circulating proteins, which enter the bloodstream from inflamed tissues, also offers insight into global IFN activity. Using a novel protocol we generated 1,132 aptamer-based protein measurements from anti-dsDN

A randomised phase IIb study of mavrilimumab, a novel GM-CSF receptor alpha monoclonal antibody, in the treatment of rheumatoid arthritis

Objectives: Despite the therapeutic value of current rheumatoid arthritis (RA) treatments, agents with alternative modes of action are required. Mavrilimumab, a fully human monoclonal antibody targeting the granulocyte-macrophage colony-stimulating factor receptor-α, was evaluated in patients with moderate-to-severe RA. Methods: In a phase IIb study (NCT01706926), patients with inadequate response to ≥1 synthetic disease-modifying antirheumatic drug(s), Disease Activity Score 28 (DAS28)-C reactive protein (CRP)/erythrocyte sedimentation rate ≥3.2, ≥4 swollen joints despite methotrexate (MTX) were randomised 1:1:1:1 to subcutaneous mavrilimumab (150, 100, 30 mg), or placebo every other week (eow), plus MTX for 24 weeks. Coprimary outcomes were DAS28-CRP change from baseline to week 12 and American College of Rheumatology (ACR) 20 response rate (week 24). Results: 326 patients were randomised (150 mg, n=79; 100 mg, n=85; 30 mg, n=81; placebo, n=81); 305 completed the study (September 20