Sherry Thornton

Objective: To evaluate the ability of the Renal Activity Index for Lupus (RAIL) score, a urine biomarker-derived score, to capture and predict the course of active lupus nephritis (LN) in adult patients. Methods: Available serial urine samples collected up to week 52 from a subset of adults with active biopsy-proven proliferative LN participating in the double-blind randomized ALLURE trial of abatacept ( ClinicalTrials.gov : NCT01714817 ) were used to calculate RAIL scores from creatinine-adjusted urine biomarkers (neutrophil gelatinase-associated lipocalin [NGAL], kidney injury molecule 1 [KIM-1], monocyte chemotactic protein 1 [MCP-1], adiponectin, hemopexin, ceruloplasmin). Discriminative performance of RAIL scores alone over time were compared with urine protein/creatinine ratio (UPCR), kidney function (estimated glomerular filtration rate [eGFR]), and mixed model analysis of RAIL score adjusted for baseline UPCR, eGFR, age, weight, sex, and race, with comparisons by renal response states including complete renal response (CRR), partial renal response but not CRR (PRR-only), and nonresponse (NR). Results: The analysis included 240 patients who contributed 599 samples. At weeks 12/24/52, there were 44/22/15 patients with PRR-only, 27/33/18 with CRR, and 127/61/15 NR. RAIL scores, eGFR, and UPCR improved over time irrespective of abatacept use, but were significantly lower with CRR compared to NR. The eGFR alone had poor accuracy (area under the receiver-operating characteristic curve [AUC] < 0.51) to discriminate renal response. Only after correction of baseline UPCR and eGFR, the RAIL score had excellent accuracy to reflect CRR from other renal response states at the current (AUC = 0.83-0.84) and next visit (AUC = 0.84-0.85) and performed better than UPCR; without correction, UPCR and RAIL score had similarly good accuracy. Conclusion: RAIL scores identify active LN and longitudinally predict the course of adult LN. ( ClinicalTrials.gov : NCT01714817 )

Uveitis is an inflammatory ocular disease secondary to disruption of the retinal pigmented epithelium (RPE) and blood retinal barrier (BRB). Known clinical factors do not accurately predict uveitis risk in Juvenile Idiopathic Arthritis (JIA). Tear fluid is easily obtained for biomarker study. We aim to identify tear-based markers associated with the presence of uveitis in children with JIA. In a cross-sectional comparative cohort study, tears were collected by Schirmer strips from children with oligoarticular JIA-associated uveitis (JIA-U) and JIA without uveitis (JIA-no-U). A tandem isotope tagging (iTRAQ and TMT) strategy was used for relative quantitation via nanoLC-MS/MS to quantify proteins in the affected eye. Log transformed relative protein abundance of protein levels was compared between groups using Wilcoxon exact test. We explored the influence of arthritis activity and topical corticosteroids (CS) use on protein levels. STRING analysis was performed. Tear samples of 14 JIA-U and 14 JIA-no-U patients were analyzed. Thirteen proteins were differentially expressed between both groups. Stratified analysis based on arthritis activity (inactive arthritis) and topical CS (off CS) showed that alpha-2-macroglobulin (p = 0.012), apolipoprotein A1 (p = 0.036), S100A9 (p = 0.05), haptoglobin (p = 0.066), and transthyretin (p = 0.066) consistently differentiated between both groups. On STRING analysis, these proteins were associated with the RPE, BRB, and inflammation. Importantly, we identified proteins involved in the RPE, BRB, and immune response that were differentially abundant in the tears of children with JIA-U compared to JIA-no-U, regardless of arthritis activity or topical CS. Candidate tear-based biomarkers may represent a non-invasive means to detect uveitis.

Objective: We examine levels of candidate blood‐based biomarkers (CBBs) in patients with juvenile idiopathic arthritis (JIA) treated with tofacitinib.Methods: Patients with JIA who participated in clinical trial NCT02592434 received tofacitinib from baseline to week 18. Serial serum samples were assayed for CBBs (S100A8/9, S100A12, interleukin‐18 [IL‐18], serum amyloid A, resistin, vascular endothelial growth factor, angiopoietin‐1, angiopoietin‐2, matrix metalloproteinase 8 [MMP8], MMP2, tissue inhibitor of metalloproteinases 1, leptin, chemokine [C‐X‐C motif] ligand 9, soluble IL‐2 receptor, intercellular adhesion molecule 1, soluble tumor necrosis factor receptor, IL‐6, IL‐23, monocyte chemotactic protein 1, chemokine [C‐C motif] ligand 18 [CCL18], and CCL20). Association of CBBs with JIA response to treatment from baseline to week 18 were assessed.Results: This study included 166 patients with polyarticular‐course JIA. Paired serum samples from 143 patients were available at both baseline and week 18. Thirty‐five percent (50 of 143) of patients had a JIA‐American College of Rheumatology 90 (JIA‐ACR90) level improvement, whereas 90, 121, and 137 (63%, 85%, and 96%) achieved JIA‐ACR70, 50, and 30 improvement at week 18. Despite small numerical differences by JIA category, there were no baseline CBB values that independently predicted a decrease in Juvenile Arthritis Disease Activity Score (JADAS‐27) or JIA‐ACR90 response by week 18. Decrease in resistin level (baseline to week 18) was significantly associated with week 18 improvement in JADAS‐27 and JIA‐ACR90 response after adjusting for age, sex, JIA disease duration, and baseline resistin (r² 0.79, SE 0.070, P < 0.01, and odds ratio [95% confidence interval] 1.134 [1.018–1.264]). HLA‐B27 positivity was significantly associated with not achieving a JIA‐ACR90 response at week 18 (P = 0.0097).Conclusion: Among the CBBs included, only resistin was significantly associated with treatment response, and no CBB was identified that forecasts JIA improvement after initiation of tofacitinib. The association of HLA‐B27 positivity with lower response to tofacitinib in JIA is intriguing and merits further study.

A biosafety plan is essential to establish appropriate practices for biosafety in a shared resource laboratory (SRL). A biosafety plan will contain the essential information for the use of biological samples on specific instrumentation, their apparent risks, and the steps that should be taken to mitigate these risks. Establishment of a biosafety plan can be a daunting task as the variety of pathogens that come through the SRL is highly diverse and may change over time; however, having a plan that can adapt to this variety will provide a framework for addressing concerns and educating personnel and users on biosafety practices. Using resources available at your institution and developing a robust relationship with health and safety personnel at your institution is key to generating an effective biosafety plan. Here we provide a basic underlying structure for a biosafety plan to aid SRL personnel in generating or maintaining their biosafety procedures, and provide guidance for establishing a dynamic, living biosafety plan.

Macrophage activation syndrome (MAS) is a life-threatening cytokine storm complicating systemic juvenile idiopathic arthritis (SJIA) driven by IFN-γ. SJIA and MAS are also associated with an unexplained emerging inflammatory lung disease (SJIA-LD), with our recent work supporting pulmonary activation of IFN-γ pathways pathologically linking SJIA-LD and MAS. Our objective was to mechanistically define the potentially novel observation of pulmonary inflammation in the TLR9 mouse model of MAS. In acute MAS, lungs exhibit mild but diffuse CD4-predominant, perivascular interstitial inflammation with elevated IFN-γ, IFN-induced chemokines, and alveolar macrophage (AMϕ) expression of IFN-γ–induced genes. Single-cell RNA sequencing confirmed IFN-driven transcriptional changes across lung cell types with myeloid expansion and detection of MAS-specific macrophage populations. Systemic MAS resolution was associated with increased AMϕ and interstitial lymphocytic infiltration. AMϕ transcriptomic analysis confirmed IFN-γ–induced proinflammatory polarization during acute MAS, which switches toward an antiinflammatory phenotype after systemic MAS resolution. Interestingly, recurrent MAS led to increased alveolar inflammation and lung injury, and it reset AMϕ polarization toward a proinflammatory state. Furthermore, in mice bearing macrophages insensitive to IFN-γ, both systemic features of MAS and pulmonary inflammation were attenuated. These findings demonstrate that experimental MAS induces IFN-γ–driven pulmonary inflammation replicating key features of SJIA-LD and provides a model system for testing potentially novel treatments directed toward SJIA-LD.

Background: The calcium-binding proteins S100A8/A9 (calprotectin) and S100A12 (extracellular newly identified receptor for advanced glycation end-products binding protein [EN-RAGE]) are involved in multiple signalling pathways to mediate inflammation, can be secreted by activated monocytes/macrophages and exhibit cytokine-like extracellular functions. Circulating levels of these proteins have been associated with disease and clinical responses in systemic juvenile idiopathic arthritis (sJIA), including treatment response.¹ Studies suggest that serum S100A8/A9 and S100A12, which are released at inflammation sites, are more specific biomarkers of local inflammation (e.g. in the synovium) than systemic biomarkers such as CRP and ESR.^2,3 Objectives: To investigate if baseline S100A8/A9 and S100A12 predict clinical response to abatacept treatment in polyarticular JIA (pJIA), and to assess whether changes from baseline in S100A8/A9 or S100A12 can be better prognostic markers for response to abatacept treatment than CRP in pJIA. Methods: Data are from a phase III trial of SC abatacept for the treatment of pJIA (NCT01844518).⁴ This 24-month, single-arm, open-label, international, multicentre, two-part study included male and female patients with pJIA aged 2–17 years. This analysis examined the correlation between biomarkers (S100A8/A9, S100A12 and high-sensitivity CRP [hsCRP]) and disease activity (measured using Juvenile Arthritis Disease Activity Score [JADAS]) at baseline, baseline biomarker values as predictors of future treatment response (ACR and JADAS endpoints), and the correlation between change from baseline in biomarker values and treatment response at Day 113. Results: Of 219 total patients, 158 (72%) had S100A8/A9 values and 155 (71%) had S100A12 values at baseline. Median S100A8/A9 and S100A12 values were 3295 ng/mL (normal range, 716–3004 ng/mL) and 176 ng/mL (normal range, 32–385 ng/mL), respectively. S100A8/A9, S100A12 and hsCRP (median 0.20 mg/dL; normal ≤0.6 mg/dL) had a low-to-moderate but significant association with disease activity at baseline; coefficients for associations between JADAS71-CRP low disease activity (LDA) and the biomarkers S100A8/A9, S100A12 and hsCRP were 0.23 (p=0.0038), 0.16 (p=0.0448) and 0.26 (p=0.0001), respectively. Baseline S100A8/A9 level above the median was associated with lower odds of ACR100 at Day 113 (p=0.0052). Figure 1 shows the associations of baseline biomarker values with Day 113 ACR and JADAS scores in the overall population. Baseline S100A8/A9 or S100A12 did not significantly influence ACR50 or ACR70 responses at Day 113, but high baseline values were associated with reduced odds of ACR90 (p=0.01), ACR100 (p=0.005), ACR-inactive disease (ID) (p=0.0001), and JADAS71-CRP (LDA) (p=0.02). By Day 477, elevated baseline S100A12 was still significantly associated with lower odds of ACR100 overall (0.467; p=0.0248) but baseline S100A8/A9 was not; at Day 645, neither was significantly associated with ACR100 response. At Day 113, changes from baseline in S100A8/A9 and S100A12 were correlated with ACR100 (coefficients of 0.22 [p=0.0082] and 0.26 [p=0.0015], respectively) and with ACR-ID (0.22 [p=0.0067] and 0.26 [p=0.0014], respectively); change in hsCRP was not significantly correlated with disease response. Conclusion: S100A8/A9 and S100A12 may serve as prognostic biomarkers to predict response to abatacept treatment at Day 113. Changes from baseline S100A8/A9 and S100A12 levels were more highly correlated with efficacy outcomes including ACR100 and ACR-ID at Day 113 compared with hsCRP. References: [1]Aljaberi N, et al. Pediatr Rheumatol Online J 2020;18:7. [2]Hammer H, et al. Arthritis Res Ther 2011;13:R178. [3]Nordal HH, et al. BMC Musculoskelet Disord 2014;15:335. [4]Brunner H, et al. Arthritis Rheumatol 2018;70:1144–1154. Acknowledgements: Professional medical writing and editorial assistance was provided by Rob Coover, MPH, at Caudex and was funded by Bristol Myers Squibb. Disclosure of Interests: Nicolino Ruperto Speakers bureau: NR has received honoraria for consultancies or speaker bureaus (< 10.000 USD each) from the following pharmaceutical companies in the past 3 years: Ablynx, Astrazeneca-Medimmune, Bayer, Biogen, Boehringer, Bristol Myers Squibb, Celgene, Eli Lilly, EMD Serono, GlaxoSmithKline, Hoffmann-La Roche, Janssen, Merck, Novartis, Pfizer, R-Pharma, Sinergie, Sobi and UCB, Consultant of: NR has received honoraria for consultancies or speaker bureaus (< 10.000 USD each) from the following pharmaceutical companies in the past 3 years: Ablynx, Astrazeneca-Medimmune, Bayer, Biogen, Boehringer, Bristol Myers Squibb, Celgene, Eli Lilly, EMD Serono, GlaxoSmithKline, Hoffmann-La Roche, Janssen, Merck, Novartis, Pfizer, R-Pharma, Sinergie, Sobi and UCB, Grant/research support from: The IRCCS Istituto Giannina Gaslini (IGG), where NR works as full-time public employee has received contributions (>10.000 USD each) from the following industries in the last 3 years: Bristol Myers Squibb, Eli Lilly, F Hoffmann-La Roche, GlaxoSmithKline, Janssen, Novartis, Pfizer, Sobi. This funding has been reinvested for the research activities of the hospital in a fully independent manner, without any commitment with third parties., Grant Schulert Speakers bureau: Novartis, Consultant of: SOBI, Alyssa Sproles: None declared, Sherry Thornton: None declared, Gabriel Vega Cornejo Speakers bureau: AbbVie, Grant/research support from: Bristol Myers Squibb, Eli Lilly, Janssen, Parexel, Sanofi, Jordi Anton Speakers bureau: AbbVie, Gebro, GlaxoSmithKline, Novartis, Pfizer, Roche, Sobi, Consultant of: AbbVie, Gebro, GlaxoSmithKline, Novartis, Pfizer, Roche, Sobi, Grant/research support from: AbbVie, Amgen, Gebro, GlaxoSmithKline, Lilly, Novartis, Novimmune, Pfizer, Roche, Sanofi, Sobi, Ruben Cuttica Speakers bureau: AbbVie, Bristol Myers Squibb, GlaxoSmithKline, Lilly, Novartis, Pfizer, Roche, UCB, Paid instructor for: AbbVie, Novartis, Pfizer, Roche, Consultant of: AbbVie, Bristol Myers Squibb, GlaxoSmithKline, Lilly, Novartis, Pfizer, Roche, UCB, Michael Henrickson: None declared, Ivan Foeldvari Consultant of: Bristol Myers Squibb, Gilead, Hexal, MEDAC, Novartis, Pfizer, Sanofi, Daniel Kingsbury Consultant of: Pfizer, Margarita Askelson Consultant of: Currently working for Syneos Health providing services to Bristol Myers Squibb, Jinqi Liu Shareholder of: Bristol Myers Squibb, Employee of: Bristol Myers Squibb, Sumanta Mukherjee Shareholder of: Bristol Myers Squibb, GlaxoSmithKline, Employee of: Bristol Myers Squibb, GlaxoSmithKline, Robert Wong Shareholder of: Bristol Myers Squibb, Employee of: Bristol Myers Squibb, Daniel J Lovell Speakers bureau: Genentech, Wyeth Pharm, Consultant of: Abbott, Amgen, AstraZeneca, Boehringer Ingelheim, Celgene, GlaxoSmithKline, Hoffman-La Roche, Novartis, Pfizer, Regeneron, Takeda, UBC, Wyeth Pharma, Xoma, Alberto Martini Speakers bureau: AbbVie, Novartis, Consultant of: AbbVie, Eli Lilly, EMD Serono, Idorsia, Janssen, Novartis, Pfizer, Alexei Grom Consultant of: AB2Bio, Novartis, Sobi (NovImmune), Grant/research support from: AB2Bio, Novartis, Sobi (NovImmune), Hermine Brunner Speakers bureau: GlaxoSmithKline, Novartis, Pfizer, Roche, Paid instructor for: Novartis, Pfizer (funds go to CCHMC/employer), Consultant of: Boehringer Ingelheim, Bristol Myers Squibb, GlaxoSmithKline, Janssen, Merck, Novartis, Pfizer, Roche, UCB (funds go to CCHMC/employer), Grant/research support from: Bristol Myers Squibb, Pfizer (funds go to CCHMC/employer).

Improved, noninvasive biomarkers are needed to accurately detect lupus nephritis (LN) activity. The purpose of this study was to evaluate five S100 proteins (S100A4, S100A6, S100A8/9, and S100A12) in both serum and urine as potential biomarkers of global and renal system-specific disease activity in childhood-onset systemic lupus erythematosus (cSLE). In this multicenter study, S100 proteins were measured in the serum and urine of four cSLE cohorts and healthy control subjects using commercial enzyme-linked immunosorbent assays. Patients were divided into cohorts on the basis of biospecimen availability: (1) longitudinal serum, (2) longitudinal urine, (3) cross-sectional serum, and (4) cross-sectional urine. Global and renal disease activity were defined using the Systemic Lupus Erythematosus Disease Activity Index 2000 (SLEDAI-2K) and the SLEDAI-2K renal domain score. Nonparametric testing was used for statistical analysis, including the Wilcoxon signed-rank test, Kruskal-Wallis test, Mann-Whitney U test, and Spearman’s rank correlation coefficient. All urine S100 proteins were elevated in patients with active LN compared with patients with active extrarenal disease and healthy control subjects. All urine S100 protein levels decreased with LN improvement, with S100A4 demonstrating the most significant decrease. Urine S100A4 levels were also higher with proliferative LN than with membranous LN. S100A4 staining in the kidney localized to mononuclear cells, podocytes, and distal tubular epithelial cells. Regardless of the S100 protein tested, serum levels did not change with cSLE improvement. Higher urine S100 levels are associated with increased LN activity in cSLE, whereas serum S100 levels do not correlate with disease activity. Urine S100A4 shows the most promise as an LN activity biomarker, given its pronounced decrease with LN improvement, isolated elevation in urine, and positive staining in resident renal cells.

Obesity promotes a chronic inflammatory and hypercoagulable state that drives cardiovascular disease, type 2 diabetes, fatty liver disease, and several cancers. Elevated thrombin activity underlies obesity-linked thromboembolic events, but the mechanistic links between the thrombin/fibrin(ogen) axis and obesity-associated pathologies are incompletely understood. In this work, immunohistochemical studies identified extravascular fibrin deposits within white adipose tissue and liver as distinct features of mice fed a high-fat diet (HFD) as well as obese patients. Fibγ^390–396A mice carrying a mutant form of fibrinogen incapable of binding leukocyte α_Mβ₂-integrin were protected from HFD-induced weight gain and elevated adiposity. Fibγ^390–396A mice had markedly diminished systemic, adipose, and hepatic inflammation with reduced macrophage counts within white adipose tissue, as well as near-complete protection from development of fatty liver disease and glucose dysmetabolism. Homozygous thrombomodulin-mutant Thbd^Pro mice, which have elevated thrombin procoagulant function, gained more weight and developed exacerbated fatty liver disease when fed a HFD compared with WT mice. In contrast, treatment with dabigatran, a direct thrombin inhibitor, limited HFD-induced obesity development and suppressed progression of sequelae in mice with established obesity. Collectively, these data provide proof of concept that targeting thrombin or fibrin(ogen) may limit pathologies in obese patients.

Background CD163 is a hemoglobin scavenger receptor and serves as a marker of activated monocytes and macrophages. It is also expressed on monocytes from children with active systemic juvenile idiopathic arthritis, and highly enriched on hemophagocytic macrophages that characterize the emergence of macrophage activation syndrome. However, the regulation of CD163 expression during monocyte and macrophage polarization is poorly understood. MicroRNA are small non-coding RNA that post-transcriptionally regulate gene expression, often serving as feedback loops to “fine tune” gene expression programs. Objectives Determine microRNA regulation of CD163 at the protein and mRNA levels using novel flow cytometry techniques. Methods Human THP-1 monocytic cells and primary monocytes and monocyte-derived macrophages (MDMs) from healthy donors were polarized with activating conditions including M1 (LPS and IFNg), M2a (IL-4), M2b (LPS and immune complexes) and M2c (TGFb or IL-10). CD163 expression was determined by quantitative RT-PCR or on a single-cell level using RNA flow cytometry. Transcripts were detected using the PrimeFlow kit, with probes specific for CD163 mRNA and other cell surface markers. Cells were also transfected with specific microRNA mimics. Results Significantly increased CD163 mRNA levels were detected only in monocytes and macrophages polarized towards M2c by IL-10 treatment. Similarly, single-cell RNA analysis showed markedly increased CD163 mRNA upon IL-10 treatment, with more modest increases in protein expression. Several candidate microRNA may regulate CD163. As such, our studies indicate that overexpression of miR-125a and miR-181c significantly reduced CD163 mRNA expression in IL-10 polarized macrophages. Notably, both of these microRNAs were significantly increased in monocytes from children with active systemic JIA. In vitro, miR-125a and miR-181c were both elevated in polarizing conditions that restrict CD163 expression. Interestingly, these microRNAs regulated CD163 expression through distinct mechanisms. Computationally, miR-181 is predicted to bind directly to CD163 mRNA. Indeed, using RNA immunoprecipitation (RIP) we found that overexpression of miR-181c significantly increased delivery of CD163 mRNA to the RNA-induced silencing complex. In contrast, CD163 does not have a predicted miR-125a binding site. Using whole transcriptome analysis of macrophages overexpressing miR-125a-5p, significantly reduced levels of mRNA encoding several macrophage receptors, including IL10RA and TGFbR2, was observed. This suggests that miR-125a-5p exerts more global effects to restrict M2c polarization. Conclusions These data show that microRNAs regulate the IL-10-induced expression of CD163 in human macrophages through distinct mechanisms, directly targeting of CD163 mRNA and indirectly inhibiting cytokine receptor expression. These findings illustrate how microRNA “fine-tune” innate immune activation during inflammatory responses, and expand the understanding of the phenotype of activated monocytes and macrophages in systemic JIA. Disclosure of Interest S. Thornton: None declared, T. Do: None declared, R. Tan: None declared, A. Sproles: None declared, M. Bennett: None declared, M. Medvedovic: None declared, M. DeLay: None declared, N. Shen: None declared, A. Grom Grant/research support from: Novartis, Novimmune, Consultant for: Novartis, Novimmune, G. Schulert: None declared