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S100A12 and S100A8/9 proteins are biomarkers of articular disease activity in Blau syndrome

S100A12 and S100A8/9 proteins are biomarkers of articular disease activity in Blau syndrome Abstract Objective To identify biomarkers of articular and ocular disease activity in patients with Blau syndrome (BS) Methods Multiplex plasma protein arrays were performed in five BS patients and eight normal healthy volunteers (NHVs). Plasma S100A12 and S100A8/9 were subsequently measured by ELISA at baseline and 1-year follow-up in all patients from a prospective multicentre cohort study. CRP was measured using Meso Scale Discovery immunoassay. Active joint counts, standardization uveitis nomenclature for anterior uveitis cells and vitreous haze by Nussenblatt scale were the clinical parameters. Results Multiplex Luminex arrays identified S100A12 as the most significantly elevated protein in five selected BS vs eight NHVs and this was confirmed by ELISA on additional samples from the same five BS patients. In the patient cohort, S100A12 (n = 39) and S100A8/9 (n = 33) were significantly higher compared with NHVs (n = 44 for S100A12, n = 40 for S100A8/9) (P = 0.0000004 and P = 0.0003, respectively). Positive correlations between active joint counts and S100 levels were significant for S100A12 (P = 0.0008) and S100A8/9 (P = 0.015). CRP levels did not correlate with active joint count. Subgroup analysis showed significant association of S100 proteins with active arthritis (S100A12 P = 0.01, S100A8/9 P = 0.008). Active uveitis was not associated with increased S100 levels. Conclusion S100 proteins are biomarkers of articular disease activity in BS and potential outcome measures in future clinical trials. As secreted neutrophil and macrophage products, S100 proteins may reflect the burden of granulomatous tissue in BS. S100 proteins, Blau syndrome Rheumatology key messages This study identified S100A12 and S100A8/9 as biomarkers for articular disease activity in Blau syndrome. In Blau syndrome, S100 proteins showed a positive correlation with active joint count, whereas CRP did not. Introduction Blau syndrome (BS) is a dominantly inherited autoinflammatory disease resulting from mutations in or near the nucleotide oligomerization domain of the gene encoding nucleotide-binding oligomerization domain-containing protein 2 (NOD2) [1]. A clinical triad of arthritis, dermatitis and uveitis is characteristic, but involvement of various organ systems has become recognized [2–4]. As a symmetrical polyarthritis with uveitis, BS resembles polyarticular JIA, yet the synovitis in BS is more exuberant than destructive and the uveitis affects both compartments of the eye. Moreover, the presence of non-caseating giant cell granulomas in affected tissues reveals its distinct pathogenesis involving activated macrophages as precursors of the characteristic multinucleated cells [5]. To date, no biomarkers of disease activity have been identified in BS. Current management of BS involving corticosteroids, DMARDs and biologic agents is less than satisfactory. Despite multiple therapies, both articular and ocular disease activity persists over time [6]. Specific drugs targeting the NOD2 pathway are being sought and biomarkers are likely to be required. S100A12, S100A8 and S100A9, three phagocyte-specific S100 proteins comprising the group of calgranulins, are secreted by activated neutrophils and macrophages and have been proposed as biomarkers in JIA [7, 8]. S100 proteins are candidates for BS, a disease of activating and proliferating neutrophils and macrophages. One of the aims of our prospective BS cohort study is the search for disease activity biomarkers. We will show here that plasma levels of S100A12 and S100A8/9 proteins are associated with articular disease activity and correlate positively with active joint counts in BS. Methods Patients and control subjects BS patients with sequence-verified NOD2 mutations were enrolled in the on-going BS multicentre prospective cohort study involving 18 centers from 11 countries [6]. The age range for 39 BS patients included in this study was 3–58 years (female/male: 18/21). Patients underwent annual visits for clinical evaluation and sampling. Measurement of active and limited joints was performed by a rheumatologist using the 75-joint count score. Patients underwent an ophthalmological evaluation within a month of study visits. Standardization of Uveitis Nomenclature classification was used to grade anterior uveitis cells (range 0–4+). Vitritis was assessed by the Nussenblatt scale (range 0–8). Blood samples were obtained at baseline and at 1-year follow-up. Participation in the biomarker studies was optional to centers and participants. Normal healthy volunteers (NHVs) were recruited from a pool of adults (age range: 25–63 years; female/male: 17/19) at GlaxoSmithKline (Collegeville, PA, USA) and youth (age range: 5–22 years; female/male: 6/2) from Leuven University Hospital (Leuven, Belgium). This study was conducted in accordance with the ethical principles of the Declaration of Helsinki and was approved by the committee on Medical Ethics of the University Hospitals KU Leuven and Ethics committees and Institutional Review Boards at all clinical sites. Sample collection Blood was collected the same day of the clinical evaluation. Corticosteroids were withheld for up to 24 h prior to sampling when medically feasible. Additionally, all samples were collected as close to the nadir of any biologic therapies as feasible. Peripheral blood was collected following each study site’s approved venipuncture procedure using standard methods for plasma isolation. Plasma was stored in 1.5 ml protein LoBind tubes (Eppendorf) at −80°C until further analysis. SF samples were collected from both knees of a patient requiring therapeutic arthrocentesis. Plasma protein profiling and cytokine measurement Plasma protein profiling was performed at Myriad RBM (Austin, TX, USA) using the Human DiscoveryMAP 250+ multiplex Luminex array. The assay version used in these studies measured 261 different cytokines and circulating proteins. Plasma IL-8, IL-16 and CRP were measured using Singleplex kits from Meso Scale Discovery (Rockville, MD, USA). Plasma S100A12 was measured using the CircuLex S100A12/EN-RAGE ELISA kit (CycLex Co. Nagano, Japan). Plasma S100A8/9 heterodimer was measured using Quantikine ELISA kit (R&D Systems, Minneapolis, MN, USA). Bioinformatic analysis Plasma protein profiles were analysed using a partial least squares discriminant analysis. Data was analysed using JMP 11.0.0 software (SAS Institute, Cary, NC, USA). Unpaired data endpoints that appeared to be approximately normal with similar variances were analysed using a two-sample, two-sided t test to compare group means, assuming unequal variances. Endpoints that violated the assumptions of normality and/or equal variance were analysed using the non-parametric Wilcoxon rank-sum test to compare groups. Clinical assessment and analysis Spearman’s rank test was used for correlations between S100 proteins and CRP levels with joint counts. Subgroups were stratified by articular and ocular disease. Briefly a joint count = 0 was required for inactive arthritis, a standardization uveitis nomenclature grade of 0 for inactive anterior uveitis and a Nussenblatt scale of 0 for inactive vitritis; the worse eye was considered when involvement was asymmetrical. Inactive eye disease required both inactive anterior uveitis and vitritis. Kruskal–Wallis and Mann–Whitney U tests were used for comparisons of S100 and CRP levels between activity groups. Results Significantly increased plasma S100A12 and S100A8/9 in BS To search for biomarkers of disease activity, we profiled an agnostic set of 261 cytokines and circulating plasma proteins from five BS patients and eight NHVs using multiplex Luminex technology. Six proteins, S100A12, IGFBP-3, IL-16, IL-8, PLGF and S100B, were more abundant in BS with false discovery rate P < 0.1. Of those, three proteins, IL-8, IL-16 and S100A12, represented significant differences between BS and NHVs with false discovery rate P < 0.015 (Fig. 1A). To confirm these results, independent blood samples from these five BS patients were collected 6 weeks after the initial blood sampling and analysed using different immunoassays (Singleplex kits from Meso Scale Discovery for IL-8 and IL-16, ELISA for S100A12). The average levels of IL-8, IL-16 and S100A12 were significantly increased in BS by 2.5-, 1.8- and 4.4-fold, respectively, relative to NHVs, consistent with the initial Luminex results. Since S100A12 showed the highest increase in the five selected BS patients vs eight NHVs, it became the focus of further analysis. Fig. 1 View largeDownload slide S100A12 and S100A8/9 plasma levels in Blau syndrome (A) Two hundred and sixty-one circulating proteins were examined in plasma from BS (n = 5) and NHV (n = 8) subjects using multiplex Luminex arrays (left). Six differentially expressed plasma proteins with FDR P < 0.10; of those, IL-8, IL-16 and S100A12 were significantly increased in BS relative to NHVs with FDR P < 0.015 (right). (B) Plasma levels of S100A12 in 39 BS [50.08 (34.01) ng/ml] were significantly increased vs 44 NHVs [20.08 (11.65) ng/ml] with P = 0.0000004. (C) Plasma levels of S100A8/9 heterodimer in 33 BS [1315 (886) ng/ml] were significantly increased vs 40 NHVs [730 (364) ng/ml] with P = 0.0003. The data are shown as means (s.d.). BS: Blau syndrome; FDR: false discovery rate; NHV: normal healthy volunteer. Fig. 1 View largeDownload slide S100A12 and S100A8/9 plasma levels in Blau syndrome (A) Two hundred and sixty-one circulating proteins were examined in plasma from BS (n = 5) and NHV (n = 8) subjects using multiplex Luminex arrays (left). Six differentially expressed plasma proteins with FDR P < 0.10; of those, IL-8, IL-16 and S100A12 were significantly increased in BS relative to NHVs with FDR P < 0.015 (right). (B) Plasma levels of S100A12 in 39 BS [50.08 (34.01) ng/ml] were significantly increased vs 44 NHVs [20.08 (11.65) ng/ml] with P = 0.0000004. (C) Plasma levels of S100A8/9 heterodimer in 33 BS [1315 (886) ng/ml] were significantly increased vs 40 NHVs [730 (364) ng/ml] with P = 0.0003. The data are shown as means (s.d.). BS: Blau syndrome; FDR: false discovery rate; NHV: normal healthy volunteer. Next, we measured plasma S100A12 in the whole cohort of BS patients at baseline. The mean values of S100A12 [50.08 (34.01) ng/ml vs 20.08 (11.65) ng/ml, P = 0.0000004] were significantly increased in BS (n = 39) compared with NHVs (n = 44) (Fig. 1B). Subsequently, we measured plasma S100A8/9 heterocomplexes in the cohort of patients at baseline because S100A8 and S100A9 have already been shown to be biomarkers in JIA. The results showed significantly higher levels of S100A8/9 [1315 (886) ng/ml vs 730 (364) ng/ml, P = 0.0003] in BS (n = 33) compared with NHVs (n = 40) (Fig. 1C). An additional observation was a robust elevation of S100A12 and S100A8/9 in SF (patient 4, supplementary Table S1, available at Rheumatology online). S100A12 and S100A8/9 concentrations in SF were 154- and 27-fold, respectively, higher than plasma concentrations obtained the same day. A collection of SF from the right knee of the same patient 2 year later confirmed the findings. Elevated S100A12 and S100A8/9 concentrations in SF may reflect local release from synovium into the joint space. S100A12 and S100A8/9 correlate with articular disease activity in BS Clinical activity scores and NOD2 mutation data on 39 BS patients are shown in supplementary Table S1, available at Rheumatology online. Thirty-nine BS samples from the baseline visit were available for S100A12 and CRP, and thirty-three for S100A8/9 measurements. S100A12 and S100A8/9 values exhibited a positive correlation with active joint count at baseline (R = 0.48/P = 0.0008, R = 0.42/P = 0.015, respectively) (Fig. 2A and B). At year 1, a positive correlation between S100A12 values and active joint count was confirmed (R = 0.39/P = 0.03). Plasma levels of CRP did not significantly correlate with active joint count, although the mean values of CRP [8.92 (13.52) μg/ml vs 2.73 (4.52) μg/ml] were higher in BS (n = 39) when compared with NHVs (n = 40). Fig. 2 View largeDownload slide The correlation of plasma S100A12 and S100A8/9 levels with active joint counts in Blau syndrome (A) Correlations between S100A12 (n = 39) and S100A8/9 (n = 33) levels with active joint counts at baseline in BS (Spearman’s rank test). (B) S100A12 and S100A8/9 levels in BS with vs without active arthritis irrespective of uveitis activity (Mann–Whitney U-test). All data are shown as medians and interquartile ranges. BS: Blau syndrome; A: arthritis; U: uveitis; +: with active disease; −: without active disease. Fig. 2 View largeDownload slide The correlation of plasma S100A12 and S100A8/9 levels with active joint counts in Blau syndrome (A) Correlations between S100A12 (n = 39) and S100A8/9 (n = 33) levels with active joint counts at baseline in BS (Spearman’s rank test). (B) S100A12 and S100A8/9 levels in BS with vs without active arthritis irrespective of uveitis activity (Mann–Whitney U-test). All data are shown as medians and interquartile ranges. BS: Blau syndrome; A: arthritis; U: uveitis; +: with active disease; −: without active disease. Higher S100A12 and S100A8/9 values in subgroups of BS patients with active arthritis Patients were then stratified in subgroups according to presence or absence of active arthritis (A+, A−) and active uveitis (U+, U−) based on the definitions described in the methods both at baseline and at 1-year follow-up. Four subgroups were identified at baseline: A+U+ (n = 17), A+U− (n = 10), A−U+ (n = 5) and A−U− (n = 7). The median (range) values for S100A12 in each group were 66 (21–166), 38 (9–104), 25 (15–73) and 24 (9–50) ng/ml, respectively. The Kruskal–Wallis test showed a significant difference among the four groups (P = 0.02). Subgroup analysis showed higher S100A12 values in patients with active arthritis vs patients without, independent of uveitis activity (P = 0.01; Fig. 2C). S100A12 values in patients who had both active arthritis and uveitis were not significantly higher compared with values in patients with arthritis but no uveitis, suggesting a predominant effect of articular inflammation on S100A12 levels. For S100A8/9, median (range) values in nanogram per millilitre were 1361 (595–3611) for A+U+ patients (n = 11), 1355 (810–4434) for A+U− (n = 9), 970 (427–1686) for A−U+ (n = 6) and 731 (334–1292) for A−U− (n = 7). Subgroup analysis revealed higher S100A8/9 values in patients with active arthritis vs patients without, independent of uveitis activity (P = 0.008; Fig. 2D). Discussion We showed that S100A12 and S100A8/9 are associated with active arthritis in BS. Further, plasma levels of S100A12 and S100A8/9 correlate positively with the number of active joints. Conversely, S100 protein levels were not associated with active uveitis. These findings suggest that the synovium is the major contributor to circulating S100 protein levels in BS, which is further supported by the prominently increased S100 levels in SF. The absence of association with uveitis activity is different from what has been reported in JIA and idiopathic uveitis [8]. This could be a consequence of the few patients without arthritis in our cohort, hampering our ability to isolate the effect of uveitis. CRP levels did not show association with articular disease activity, a fact that matches the absence of overt systemic inflammatory features in BS. The S100A8/9 dimer (also known as calprotectin) and S100A12 proteins are multifunctional secreted proteins involved in cell–cell signalling that promote myeloid proliferation and modulation of the inflammatory response. S100A12 and S100A8/9 are produced by activated neutrophils and macrophages, and are chemotactic for both [9]. Although the evidence in support of gain function mutations of the NOD2 gene in BS is considerable [10], ex vivo stimulation of NOD2 mutated peripheral blood cells with muramyl dipeptide, its selective ligand, shows an attenuated nuclear factor κB (NFκB)-dependent cytokine response in supernatant [11, 12]. Correspondingly, the phenotype of the majority of BS patients is characterized by inflammatory granulomatous organ involvement, rather than overt systemic inflammation. Since S100A12 and S100A8/9 reflect the proliferation of activated neutrophils and macrophages in the inflamed hypertrophic synovium, it was not surprising to find a strong correlation with articular disease activity but not for CRP, a hepatic product secreted upon systemic stimulation by NFκB-dependent circulating cytokines. We recognize a number of weaknesses in our study. The fewer samples available at the year 1 visit may have impaired our ability to confirm the differences between clinical subgroups in S100 levels. At this stage, S100 proteins may not be suitable for monitoring disease activity in individual patients. Our correlation analysis showed a lower performance of S100 proteins at the extreme values of joint counts. At present, no composite clinical activity scores have been validated for BS, and accordingly we used the active and limited joint counts as clinical measures. This is the first prospective study focused on biomarker discovery for disease activity in BS. The design of our study allowed us to obtain reliable clinical evaluations at the time of blood sampling on a substantial number of patients for this rare disease. To conclude, we have successfully identified S100A12 and S100A8/9 as biomarkers for articular disease activity in BS. Future efforts will include the search for an appropriate marker for uveitis activity as well as the collection of more longitudinal data to confirm the efficiency of the S100 biomarkers over time. Acknowledgements The authors wish to express their gratitude to Friederike Mackensen MD from the University of Heidelberg, collaborator of the Blau project since its inception, who tragically passed away prematurely on 19 April 2016 before she had the chance to review the contents of this submission. Funding: The study was supported under a research collaboration agreement with GlaxoSmithKline pharmaceuticals. Disclosure statement: L.W. is an employee and shareholder of GlaxoSmithKline. C.D.R. was awarded a Grant to study Blau syndrome from the University of Leuven. K.P.F. was an employee and shareholder of GlaxoSmithKline. B.J.V. is an employee and shareholder of GlaxoSmithKline. J.B. is an employee and shareholder of GlaxoSmithKline. C.H.W. received an unrestricted grant from GlaxoSmithKline to carry out the work described here. F.M. has received lecture honoraria from Heidelberg Eng, Meso Scale Discovery; has provided consultancy services for Merck Serono and Abbvie; and has received grants/research support from Allergan, Santen, Servier and AbbVie. All other authors have declared no conflicts of interest. Supplementary data Supplementary data are available at Rheumatology online. References 1 Miceli-Richard C , Lesage S , Rybojad M et al. CARD15 mutations in Blau syndrome . Nat Genet 2001 ; 29 : 19 – 20 . Google Scholar CrossRef Search ADS PubMed 2 Blau EB. Familial granulomatous arthritis, iritis, and rash . J Pediatr 1985 ; 107 : 689 – 93 . Google Scholar CrossRef Search ADS PubMed 3 Rose CD , Arostegui JI , Martin TM et al. NOD-2 associated Pediatric Granulomatous Arthritis (PGA) an expanding phenotype . Arthritis Rheum 2009 ; 60 : 1797 – 803 . Google Scholar CrossRef Search ADS PubMed 4 Arostegui J , Arnal C , Merino R et al. NOD2 gene-associated pediatric granulomatous arthritis: Clinical diversity, novel and recurrent mutations, and evidence of clinical improvement with interleukin‐1 blockade in a Spanish cohort . Arthritis Rheum 2007 ; 56 : 3805 – 13 . Google Scholar CrossRef Search ADS PubMed 5 Janssen CE , Rose CD , De Hertogh G et al. Morphologic and immunohistochemical characterization of granulomas in the nucleotide oligomerization domain 2-related disorders Blau syndrome and Crohn disease . J Allergy Clin Immunol 2012 ; 129 : 1076 – 84 . Google Scholar CrossRef Search ADS PubMed 6 Rosé CD , Pans S , Casteels I et al. Blau syndrome: cross-sectional data from a multicenter study of clinical, radiological and functional outcomes . Rheumatology 2015 ; 54 : 1008 – 16 . Google Scholar CrossRef Search ADS PubMed 7 Gerss J , Roth J , Holzinger D et al. Phagocyte-specific S100 proteins and high sensitivity C reactive protein as biomarkers for a risk-adapted treatment to maintain remission in juvenile idiopathic arthritis: a comparative study . Ann Rheum Dis 2012 ; 71 : 1991 – 7 . Google Scholar CrossRef Search ADS PubMed 8 Walscheid K , Heiligenhaus A , Holzinger D et al. Elevated S100A8/A9 and S100A12 serum levels reflect intraocular inflammation in juvenile idiopathic arthritis-associated uveitis: results from a pilot study . Invest Ophthalmol Vis Sci 2016 ; 56 : 7653 – 60 . Google Scholar CrossRef Search ADS 9 Donato R , Cannon BR , Sorci G et al. Functions of S100 proteins . Curr Mol Med 2013 ; 13 : 24 – 57 . Google Scholar CrossRef Search ADS PubMed 10 Kanazawa N , Okafuji I , Kamble N et al. Early-onset sarcoidosis and CARD15 mutations with constitutive nuclear factor κB activation: common genetic etiology with Blau syndrome . Blood 2005 ; 105 : 1195 – 7 . Google Scholar CrossRef Search ADS PubMed 11 Martin TM , Zhang Z , Kurz P et al. The NOD2 defect in Blau syndrome does not result in excess interleukin 1 activity . Arthritis Rheum 2009 ; 60 : 611 – 8 . Google Scholar CrossRef Search ADS PubMed 12 Dugan J , Griffith E , Snow P et al. A Blau syndrome-associated Nod2 mutation alters expression of full length NOD2 and limits responses to muramyl dipeptide in knock-in mice . J Immunology 2015 ; 194 : 349 – 57 . Google Scholar CrossRef Search ADS © The Author(s) 2018. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved. For permissions, please email: journals.permissions@oup.com This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices) http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Rheumatology Oxford University Press

S100A12 and S100A8/9 proteins are biomarkers of articular disease activity in Blau syndrome

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© The Author(s) 2018. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved. For permissions, please email: journals.permissions@oup.com
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Abstract

Abstract Objective To identify biomarkers of articular and ocular disease activity in patients with Blau syndrome (BS) Methods Multiplex plasma protein arrays were performed in five BS patients and eight normal healthy volunteers (NHVs). Plasma S100A12 and S100A8/9 were subsequently measured by ELISA at baseline and 1-year follow-up in all patients from a prospective multicentre cohort study. CRP was measured using Meso Scale Discovery immunoassay. Active joint counts, standardization uveitis nomenclature for anterior uveitis cells and vitreous haze by Nussenblatt scale were the clinical parameters. Results Multiplex Luminex arrays identified S100A12 as the most significantly elevated protein in five selected BS vs eight NHVs and this was confirmed by ELISA on additional samples from the same five BS patients. In the patient cohort, S100A12 (n = 39) and S100A8/9 (n = 33) were significantly higher compared with NHVs (n = 44 for S100A12, n = 40 for S100A8/9) (P = 0.0000004 and P = 0.0003, respectively). Positive correlations between active joint counts and S100 levels were significant for S100A12 (P = 0.0008) and S100A8/9 (P = 0.015). CRP levels did not correlate with active joint count. Subgroup analysis showed significant association of S100 proteins with active arthritis (S100A12 P = 0.01, S100A8/9 P = 0.008). Active uveitis was not associated with increased S100 levels. Conclusion S100 proteins are biomarkers of articular disease activity in BS and potential outcome measures in future clinical trials. As secreted neutrophil and macrophage products, S100 proteins may reflect the burden of granulomatous tissue in BS. S100 proteins, Blau syndrome Rheumatology key messages This study identified S100A12 and S100A8/9 as biomarkers for articular disease activity in Blau syndrome. In Blau syndrome, S100 proteins showed a positive correlation with active joint count, whereas CRP did not. Introduction Blau syndrome (BS) is a dominantly inherited autoinflammatory disease resulting from mutations in or near the nucleotide oligomerization domain of the gene encoding nucleotide-binding oligomerization domain-containing protein 2 (NOD2) [1]. A clinical triad of arthritis, dermatitis and uveitis is characteristic, but involvement of various organ systems has become recognized [2–4]. As a symmetrical polyarthritis with uveitis, BS resembles polyarticular JIA, yet the synovitis in BS is more exuberant than destructive and the uveitis affects both compartments of the eye. Moreover, the presence of non-caseating giant cell granulomas in affected tissues reveals its distinct pathogenesis involving activated macrophages as precursors of the characteristic multinucleated cells [5]. To date, no biomarkers of disease activity have been identified in BS. Current management of BS involving corticosteroids, DMARDs and biologic agents is less than satisfactory. Despite multiple therapies, both articular and ocular disease activity persists over time [6]. Specific drugs targeting the NOD2 pathway are being sought and biomarkers are likely to be required. S100A12, S100A8 and S100A9, three phagocyte-specific S100 proteins comprising the group of calgranulins, are secreted by activated neutrophils and macrophages and have been proposed as biomarkers in JIA [7, 8]. S100 proteins are candidates for BS, a disease of activating and proliferating neutrophils and macrophages. One of the aims of our prospective BS cohort study is the search for disease activity biomarkers. We will show here that plasma levels of S100A12 and S100A8/9 proteins are associated with articular disease activity and correlate positively with active joint counts in BS. Methods Patients and control subjects BS patients with sequence-verified NOD2 mutations were enrolled in the on-going BS multicentre prospective cohort study involving 18 centers from 11 countries [6]. The age range for 39 BS patients included in this study was 3–58 years (female/male: 18/21). Patients underwent annual visits for clinical evaluation and sampling. Measurement of active and limited joints was performed by a rheumatologist using the 75-joint count score. Patients underwent an ophthalmological evaluation within a month of study visits. Standardization of Uveitis Nomenclature classification was used to grade anterior uveitis cells (range 0–4+). Vitritis was assessed by the Nussenblatt scale (range 0–8). Blood samples were obtained at baseline and at 1-year follow-up. Participation in the biomarker studies was optional to centers and participants. Normal healthy volunteers (NHVs) were recruited from a pool of adults (age range: 25–63 years; female/male: 17/19) at GlaxoSmithKline (Collegeville, PA, USA) and youth (age range: 5–22 years; female/male: 6/2) from Leuven University Hospital (Leuven, Belgium). This study was conducted in accordance with the ethical principles of the Declaration of Helsinki and was approved by the committee on Medical Ethics of the University Hospitals KU Leuven and Ethics committees and Institutional Review Boards at all clinical sites. Sample collection Blood was collected the same day of the clinical evaluation. Corticosteroids were withheld for up to 24 h prior to sampling when medically feasible. Additionally, all samples were collected as close to the nadir of any biologic therapies as feasible. Peripheral blood was collected following each study site’s approved venipuncture procedure using standard methods for plasma isolation. Plasma was stored in 1.5 ml protein LoBind tubes (Eppendorf) at −80°C until further analysis. SF samples were collected from both knees of a patient requiring therapeutic arthrocentesis. Plasma protein profiling and cytokine measurement Plasma protein profiling was performed at Myriad RBM (Austin, TX, USA) using the Human DiscoveryMAP 250+ multiplex Luminex array. The assay version used in these studies measured 261 different cytokines and circulating proteins. Plasma IL-8, IL-16 and CRP were measured using Singleplex kits from Meso Scale Discovery (Rockville, MD, USA). Plasma S100A12 was measured using the CircuLex S100A12/EN-RAGE ELISA kit (CycLex Co. Nagano, Japan). Plasma S100A8/9 heterodimer was measured using Quantikine ELISA kit (R&D Systems, Minneapolis, MN, USA). Bioinformatic analysis Plasma protein profiles were analysed using a partial least squares discriminant analysis. Data was analysed using JMP 11.0.0 software (SAS Institute, Cary, NC, USA). Unpaired data endpoints that appeared to be approximately normal with similar variances were analysed using a two-sample, two-sided t test to compare group means, assuming unequal variances. Endpoints that violated the assumptions of normality and/or equal variance were analysed using the non-parametric Wilcoxon rank-sum test to compare groups. Clinical assessment and analysis Spearman’s rank test was used for correlations between S100 proteins and CRP levels with joint counts. Subgroups were stratified by articular and ocular disease. Briefly a joint count = 0 was required for inactive arthritis, a standardization uveitis nomenclature grade of 0 for inactive anterior uveitis and a Nussenblatt scale of 0 for inactive vitritis; the worse eye was considered when involvement was asymmetrical. Inactive eye disease required both inactive anterior uveitis and vitritis. Kruskal–Wallis and Mann–Whitney U tests were used for comparisons of S100 and CRP levels between activity groups. Results Significantly increased plasma S100A12 and S100A8/9 in BS To search for biomarkers of disease activity, we profiled an agnostic set of 261 cytokines and circulating plasma proteins from five BS patients and eight NHVs using multiplex Luminex technology. Six proteins, S100A12, IGFBP-3, IL-16, IL-8, PLGF and S100B, were more abundant in BS with false discovery rate P < 0.1. Of those, three proteins, IL-8, IL-16 and S100A12, represented significant differences between BS and NHVs with false discovery rate P < 0.015 (Fig. 1A). To confirm these results, independent blood samples from these five BS patients were collected 6 weeks after the initial blood sampling and analysed using different immunoassays (Singleplex kits from Meso Scale Discovery for IL-8 and IL-16, ELISA for S100A12). The average levels of IL-8, IL-16 and S100A12 were significantly increased in BS by 2.5-, 1.8- and 4.4-fold, respectively, relative to NHVs, consistent with the initial Luminex results. Since S100A12 showed the highest increase in the five selected BS patients vs eight NHVs, it became the focus of further analysis. Fig. 1 View largeDownload slide S100A12 and S100A8/9 plasma levels in Blau syndrome (A) Two hundred and sixty-one circulating proteins were examined in plasma from BS (n = 5) and NHV (n = 8) subjects using multiplex Luminex arrays (left). Six differentially expressed plasma proteins with FDR P < 0.10; of those, IL-8, IL-16 and S100A12 were significantly increased in BS relative to NHVs with FDR P < 0.015 (right). (B) Plasma levels of S100A12 in 39 BS [50.08 (34.01) ng/ml] were significantly increased vs 44 NHVs [20.08 (11.65) ng/ml] with P = 0.0000004. (C) Plasma levels of S100A8/9 heterodimer in 33 BS [1315 (886) ng/ml] were significantly increased vs 40 NHVs [730 (364) ng/ml] with P = 0.0003. The data are shown as means (s.d.). BS: Blau syndrome; FDR: false discovery rate; NHV: normal healthy volunteer. Fig. 1 View largeDownload slide S100A12 and S100A8/9 plasma levels in Blau syndrome (A) Two hundred and sixty-one circulating proteins were examined in plasma from BS (n = 5) and NHV (n = 8) subjects using multiplex Luminex arrays (left). Six differentially expressed plasma proteins with FDR P < 0.10; of those, IL-8, IL-16 and S100A12 were significantly increased in BS relative to NHVs with FDR P < 0.015 (right). (B) Plasma levels of S100A12 in 39 BS [50.08 (34.01) ng/ml] were significantly increased vs 44 NHVs [20.08 (11.65) ng/ml] with P = 0.0000004. (C) Plasma levels of S100A8/9 heterodimer in 33 BS [1315 (886) ng/ml] were significantly increased vs 40 NHVs [730 (364) ng/ml] with P = 0.0003. The data are shown as means (s.d.). BS: Blau syndrome; FDR: false discovery rate; NHV: normal healthy volunteer. Next, we measured plasma S100A12 in the whole cohort of BS patients at baseline. The mean values of S100A12 [50.08 (34.01) ng/ml vs 20.08 (11.65) ng/ml, P = 0.0000004] were significantly increased in BS (n = 39) compared with NHVs (n = 44) (Fig. 1B). Subsequently, we measured plasma S100A8/9 heterocomplexes in the cohort of patients at baseline because S100A8 and S100A9 have already been shown to be biomarkers in JIA. The results showed significantly higher levels of S100A8/9 [1315 (886) ng/ml vs 730 (364) ng/ml, P = 0.0003] in BS (n = 33) compared with NHVs (n = 40) (Fig. 1C). An additional observation was a robust elevation of S100A12 and S100A8/9 in SF (patient 4, supplementary Table S1, available at Rheumatology online). S100A12 and S100A8/9 concentrations in SF were 154- and 27-fold, respectively, higher than plasma concentrations obtained the same day. A collection of SF from the right knee of the same patient 2 year later confirmed the findings. Elevated S100A12 and S100A8/9 concentrations in SF may reflect local release from synovium into the joint space. S100A12 and S100A8/9 correlate with articular disease activity in BS Clinical activity scores and NOD2 mutation data on 39 BS patients are shown in supplementary Table S1, available at Rheumatology online. Thirty-nine BS samples from the baseline visit were available for S100A12 and CRP, and thirty-three for S100A8/9 measurements. S100A12 and S100A8/9 values exhibited a positive correlation with active joint count at baseline (R = 0.48/P = 0.0008, R = 0.42/P = 0.015, respectively) (Fig. 2A and B). At year 1, a positive correlation between S100A12 values and active joint count was confirmed (R = 0.39/P = 0.03). Plasma levels of CRP did not significantly correlate with active joint count, although the mean values of CRP [8.92 (13.52) μg/ml vs 2.73 (4.52) μg/ml] were higher in BS (n = 39) when compared with NHVs (n = 40). Fig. 2 View largeDownload slide The correlation of plasma S100A12 and S100A8/9 levels with active joint counts in Blau syndrome (A) Correlations between S100A12 (n = 39) and S100A8/9 (n = 33) levels with active joint counts at baseline in BS (Spearman’s rank test). (B) S100A12 and S100A8/9 levels in BS with vs without active arthritis irrespective of uveitis activity (Mann–Whitney U-test). All data are shown as medians and interquartile ranges. BS: Blau syndrome; A: arthritis; U: uveitis; +: with active disease; −: without active disease. Fig. 2 View largeDownload slide The correlation of plasma S100A12 and S100A8/9 levels with active joint counts in Blau syndrome (A) Correlations between S100A12 (n = 39) and S100A8/9 (n = 33) levels with active joint counts at baseline in BS (Spearman’s rank test). (B) S100A12 and S100A8/9 levels in BS with vs without active arthritis irrespective of uveitis activity (Mann–Whitney U-test). All data are shown as medians and interquartile ranges. BS: Blau syndrome; A: arthritis; U: uveitis; +: with active disease; −: without active disease. Higher S100A12 and S100A8/9 values in subgroups of BS patients with active arthritis Patients were then stratified in subgroups according to presence or absence of active arthritis (A+, A−) and active uveitis (U+, U−) based on the definitions described in the methods both at baseline and at 1-year follow-up. Four subgroups were identified at baseline: A+U+ (n = 17), A+U− (n = 10), A−U+ (n = 5) and A−U− (n = 7). The median (range) values for S100A12 in each group were 66 (21–166), 38 (9–104), 25 (15–73) and 24 (9–50) ng/ml, respectively. The Kruskal–Wallis test showed a significant difference among the four groups (P = 0.02). Subgroup analysis showed higher S100A12 values in patients with active arthritis vs patients without, independent of uveitis activity (P = 0.01; Fig. 2C). S100A12 values in patients who had both active arthritis and uveitis were not significantly higher compared with values in patients with arthritis but no uveitis, suggesting a predominant effect of articular inflammation on S100A12 levels. For S100A8/9, median (range) values in nanogram per millilitre were 1361 (595–3611) for A+U+ patients (n = 11), 1355 (810–4434) for A+U− (n = 9), 970 (427–1686) for A−U+ (n = 6) and 731 (334–1292) for A−U− (n = 7). Subgroup analysis revealed higher S100A8/9 values in patients with active arthritis vs patients without, independent of uveitis activity (P = 0.008; Fig. 2D). Discussion We showed that S100A12 and S100A8/9 are associated with active arthritis in BS. Further, plasma levels of S100A12 and S100A8/9 correlate positively with the number of active joints. Conversely, S100 protein levels were not associated with active uveitis. These findings suggest that the synovium is the major contributor to circulating S100 protein levels in BS, which is further supported by the prominently increased S100 levels in SF. The absence of association with uveitis activity is different from what has been reported in JIA and idiopathic uveitis [8]. This could be a consequence of the few patients without arthritis in our cohort, hampering our ability to isolate the effect of uveitis. CRP levels did not show association with articular disease activity, a fact that matches the absence of overt systemic inflammatory features in BS. The S100A8/9 dimer (also known as calprotectin) and S100A12 proteins are multifunctional secreted proteins involved in cell–cell signalling that promote myeloid proliferation and modulation of the inflammatory response. S100A12 and S100A8/9 are produced by activated neutrophils and macrophages, and are chemotactic for both [9]. Although the evidence in support of gain function mutations of the NOD2 gene in BS is considerable [10], ex vivo stimulation of NOD2 mutated peripheral blood cells with muramyl dipeptide, its selective ligand, shows an attenuated nuclear factor κB (NFκB)-dependent cytokine response in supernatant [11, 12]. Correspondingly, the phenotype of the majority of BS patients is characterized by inflammatory granulomatous organ involvement, rather than overt systemic inflammation. Since S100A12 and S100A8/9 reflect the proliferation of activated neutrophils and macrophages in the inflamed hypertrophic synovium, it was not surprising to find a strong correlation with articular disease activity but not for CRP, a hepatic product secreted upon systemic stimulation by NFκB-dependent circulating cytokines. We recognize a number of weaknesses in our study. The fewer samples available at the year 1 visit may have impaired our ability to confirm the differences between clinical subgroups in S100 levels. At this stage, S100 proteins may not be suitable for monitoring disease activity in individual patients. Our correlation analysis showed a lower performance of S100 proteins at the extreme values of joint counts. At present, no composite clinical activity scores have been validated for BS, and accordingly we used the active and limited joint counts as clinical measures. This is the first prospective study focused on biomarker discovery for disease activity in BS. The design of our study allowed us to obtain reliable clinical evaluations at the time of blood sampling on a substantial number of patients for this rare disease. To conclude, we have successfully identified S100A12 and S100A8/9 as biomarkers for articular disease activity in BS. Future efforts will include the search for an appropriate marker for uveitis activity as well as the collection of more longitudinal data to confirm the efficiency of the S100 biomarkers over time. Acknowledgements The authors wish to express their gratitude to Friederike Mackensen MD from the University of Heidelberg, collaborator of the Blau project since its inception, who tragically passed away prematurely on 19 April 2016 before she had the chance to review the contents of this submission. Funding: The study was supported under a research collaboration agreement with GlaxoSmithKline pharmaceuticals. Disclosure statement: L.W. is an employee and shareholder of GlaxoSmithKline. C.D.R. was awarded a Grant to study Blau syndrome from the University of Leuven. K.P.F. was an employee and shareholder of GlaxoSmithKline. B.J.V. is an employee and shareholder of GlaxoSmithKline. J.B. is an employee and shareholder of GlaxoSmithKline. C.H.W. received an unrestricted grant from GlaxoSmithKline to carry out the work described here. F.M. has received lecture honoraria from Heidelberg Eng, Meso Scale Discovery; has provided consultancy services for Merck Serono and Abbvie; and has received grants/research support from Allergan, Santen, Servier and AbbVie. All other authors have declared no conflicts of interest. Supplementary data Supplementary data are available at Rheumatology online. References 1 Miceli-Richard C , Lesage S , Rybojad M et al. CARD15 mutations in Blau syndrome . Nat Genet 2001 ; 29 : 19 – 20 . Google Scholar CrossRef Search ADS PubMed 2 Blau EB. Familial granulomatous arthritis, iritis, and rash . J Pediatr 1985 ; 107 : 689 – 93 . Google Scholar CrossRef Search ADS PubMed 3 Rose CD , Arostegui JI , Martin TM et al. NOD-2 associated Pediatric Granulomatous Arthritis (PGA) an expanding phenotype . Arthritis Rheum 2009 ; 60 : 1797 – 803 . 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Google Scholar CrossRef Search ADS PubMed 11 Martin TM , Zhang Z , Kurz P et al. The NOD2 defect in Blau syndrome does not result in excess interleukin 1 activity . Arthritis Rheum 2009 ; 60 : 611 – 8 . Google Scholar CrossRef Search ADS PubMed 12 Dugan J , Griffith E , Snow P et al. A Blau syndrome-associated Nod2 mutation alters expression of full length NOD2 and limits responses to muramyl dipeptide in knock-in mice . J Immunology 2015 ; 194 : 349 – 57 . Google Scholar CrossRef Search ADS © The Author(s) 2018. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved. For permissions, please email: journals.permissions@oup.com This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices)

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Rheumatology – Oxford University Press

Published: Apr 7, 2018

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