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During the past two decades, the treatment of popliteal artery aneurysms (PAAs) has undergone a transformation. Although open surgical repair (OR) has remained the reference standard for treatment, endovascular repair (ER) has become an attractive alternative for select patient populations. The objective of the present study was to compare the outcomes of OR vs ER of PAAs at a single institution.We performed a retrospective review of the medical records for all patients who had undergone repair for PAAs from 1998 to 2017. The baseline patient, anatomic, and operative characteristics and outcomes were compared between the OR and ER cohorts. Intervention and treatment were at the discretion of the surgeon.From 1998 to 2017, 64 patients had undergone repair of 73 PAAs at our tertiary care center. Of the 69 patients (73 PAAs), 29 (33 PAAs) had undergone OR and 35 (40 PAAs) had undergone ER. When comparing the two cohorts, no statistically significant differences were found in the demographic characteristics such as age, gender, or number of runoff vessels. Significantly more patients in the ER group (n = 21; 53%) than in the OR group (n = 7; 21%) had had hyperlipidemia (P = .008) and a previous carotid intervention (6% vs 0%; P = .029). Overall, the presence of symptoms was similar between the two groups. However, the OR group had a significantly higher number of patients who had presented with acute ischemia (P = .01). The length of stay was significantly shorter for the ER cohort (mean, 1.8 days; range, 1-11 days) than for the OR group (mean, 5.4 days; range, 2-13 days; P .0001). No significant difference was found in the primary or secondary patency rates between the two groups. In the ER group, good runoff (two or more vessels) was a positive predictor for primary patency at 1 year (odds ratio, 3.36; 95% confidence interval, 1.0-11.25). However, it was not in the OR group. Postoperative single and/or dual antiplatelet therapy did not affect primary patency in either cohort.The results of our study have demonstrated that ER of PAAs is a safe and durable option with patency rates comparable to those with OR and a decreased length of stay, with good runoff a positive predictor for primary patency in the ER cohort.

We studied children enrolled within 90 days of juvenile idiopathic arthritis diagnosis in the Research in Arthritis in Canadian Children Emphasizing Outcomes (ReACCh-Out) prospective inception cohort to identify longitudinal trajectories of pain severity and features that may predict pain trajectory at diagnosis. A total of 1062 participants were followed a median of 24.3 months (interquartile range = 16.0-37.1 months). Latent trajectory analysis of pain severity, measured in a 100-mm visual analogue scale, identified 5 distinct trajectories: (1) mild-decreasing pain (56.2% of the cohort); (2) moderate-decreasing pain (28.6%); (3) chronically moderate pain (7.4%); (4) minimal pain (4.0%); and (5) mild-increasing pain (3.7%). Mean disability and quality of life scores roughly paralleled the pain severity trajectories. At baseline, children with chronically moderate pain, compared to those with moderate-decreasing pain, were older (mean 10.0 vs 8.5 years, P = 0.01) and had higher active joint counts (mean 10.0 vs 7.2 joints, P = 0.06). Children with mild-increasing pain had lower joint counts than children with mild-decreasing pain (2.3 vs 5.2 joints, P < 0.001). Although most children with juvenile idiopathic arthritis in this cohort had mild or moderate initial levels of pain that decreased quickly, about 1 in 10 children had concerning pain trajectories (chronically moderate pain and mild-increasing pain). Systematic periodic assessment of pain severity in the months after diagnosis may help identify these concerning pain trajectories early and lay out appropriate pain management plans. Focused research into the factors leading to these concerning trajectories may help prevent them.

Objective To characterize the early disease course in childhood-onset antineutrophil cytoplasmic antibody (ANCA)–associated vasculitis (AAV) and the 12-month outcomes in children with AAV. Methods Eligible subjects were children entered into the Pediatric Vasculitis Initiative study who were diagnosed before their eighteenth birthday as having granulomatosis with polyangiitis (Wegener's), microscopic polyangiitis, eosinophilic granulomatosis with polyangiitis (Churg-Strauss), or ANCA-positive pauci-immune glomerulonephritis. The primary outcome measure was achievement of disease remission (Pediatric Vasculitis Activity Score [PVAS] of 0) at 12 months with a corticosteroid dosage of

Pulmonary renal syndrome refers to an association of pulmonary and glomerular disease and includes disorders, such as the ANCA-associated vasculitides, anti-glomerular basement membrane antibody disease, systemic lupus erythematosus, and IgA vasculitis (Henoch-Schönlein purpura). We present the medical history of a 26-month-old boy with an extensive purpuric rash, involving the limbs, trunk, and face, who developed clinically significant pulmonary hemorrhage and renal involvement. Rapid recognition of this rare but potentially life-threatening condition is crucial. In this report, we discuss the differential diagnosis, diagnostic studies, and treatment options to consider when facing a young child presenting with a pulmonary renal syndrome.

Our in vivo studies on a rat model established safety of transfusing liposome-treated red blood cells (RBCs) but identified the potential for immune modulation as related to transfusion efficacy of liposome-treated RBCs. The aim of this study was at assessing the impact of liposome-induced membrane changes on the immune profile of liposome-treated RBCs by (a) evaluating their interaction with endothelial cells and monocytes; and (b) the resulting immune response derived from this interaction, in the form of cytokine release, adhesion molecules expression and phagocytosis. Unilamellar liposomes were synthesized to contain unsaturated phospholipids (1,2-dioleoyl-sn-glycero-3-phosphocholine [DOPC]:CHOL, 7:3 mol%). The human RBCs immune profile was assessed by incubating control and DOPC-treated RBCs with human umbilical vein endothelial cells (HUVECs) and monocytes. Cytokine release measured by Luminex technology, vascular cell adhesion molecule (VCAM)-1 and E-selectin on HUVECs measured by flow cytometry, and the erythrophagocytic activity of monocytes by monocyte monolayer assay (MMA) were determined. Fibroblast growth factor [FGF]-2 was the only cytokine released by HUVECs that remained increased after incubation with DOPC-treated RBCs compared to control throughout storage. The expression of both VCAM-1 (15.3 ± 5.6% versus 6.3 ± 0.9%, p = 0.008) and E-selectin (18.0 ± 6.3% versus 6.6 ± 0.7%, p = 0.004) by HUVECs were significantly increased after incubation with DOPC-treated RBCs at day 2 of storage. The MMA resulted in phagocytic indexes of zero for both control and DOPC-treated RBCs at day 2 and 42 of storage. The liposome treatment did not result in significant changes to the immune profile of stored DOPC-treated RBCs. These findings combined with previous in vivo results, make liposome treatment a potential candidate for application in RBC preservation and open the possibility for clinical use with other cell types.

Numerous studies point to the utility of blood cytokine measurements in the diagnosis and treatment of human disease. Advances in detection allow robust multiplex analysis. However, cytokines are present at low levels and are produced and act in complex networks which can remain active in stored blood. A major barrier to the routine use of cytokines as clinical biomarkers is sample management prior to analysis. Studies on cytokine stability under storage frequently use ‘spiked’ normal control plasma or serum to generate detectable levels of the cytokines of interest. These conditions may oversimplify the reality of clinically complex samples and provide limited information regarding optimal management of whole blood samples prior to plasma separation. Cytokine stability has also been addressed previously using plasma from normal individuals under different conditions of anticoagulant use, storage time and temperature of storage. No studies have as yet been undertaken to address cytokine stability in critically ill patients which may differ from normal, healthy individuals due to underlying cofounders such as inflammation. To address these issues, we subjected samples from five patients exhibiting an inflammatory disease state to three storage extremes which might be encountered in a clinical setting, prior to analysis of 40 cytokines. Blood drawn into EDTA or ACD anticoagulant was immediately separated and plasma stored at −80 °C. Matched samples were stored as follows; whole blood overnight at room temperature, or whole blood or plasma stored 10 days at 4 °C. We used equivalence testing to determine the similarity of stored cytokine values to baseline values. In ACD plasma, Eotaxin, IL-6, IL-11, IL-15, IP10, MDC, MCP-1 met equivalence to baseline in all storage conditions while for EDTA plasma stored 10 days at 4 °C EGF, FGF2, Fractalkine, G-CSF, IL-1β, IL-5, IL-6, IL-7, IL-11, IP-10, TGFα and TNFα showed equivalence to baseline measurements. Intraclass Correlation Coefficients (ICC) were calculated and the following cytokines showed good to excellent agreement across all 4 storage conditions: Eotaxin, IL-5, IL-6, IL-11, IL-13, IP-10, MCP-1 and TNFα when collected in EDTA, and Eotaxin, IL-5, IL-6, IL-11, IL12-p40, IL-15, IP-10 and MCP-1 when collected in ACD. Five plasma cytokines were identified as being the least stable in both ACD and EDTA: IL-7, IL-9, IL12p70, RANTES, sCD40L, while IL-1β was identified as unstable stored in ACD plasma. This study identified several clinically important cytokines that are remarkably stable in blood and plasma, and some that stored poorly. To our knowledge, this is the first cytokine storage study to use medically unwell patient samples and equivalence testing to evaluate the stability of measured cytokine values after storage.

Objective To identify early predictors of disease activity at 18 months in JIA using clinical and biomarker profiling. Methods Clinical and biomarker data were collected at JIA diagnosis in a prospective longitudinal inception cohort of 82 children with non-systemic JIA, and their ability to predict an active joint count of 0, a physician global assessment of disease activity of ≤1 cm, and inactive disease by Wallace 2004 criteria 18 months later was assessed. Correlation-based feature selection and ReliefF were used to shortlist predictors and random forest models were trained to predict outcomes. Results From the original 112 features, 13 effectively predicted 18-month outcomes. They included age, number of active/effused joints, wrist, ankle and/or knee involvement, ESR, ANA positivity and plasma levels of five inflammatory biomarkers (IL-10, IL-17, IL-12p70, soluble low-density lipoprotein receptor-related protein 1 and vitamin D), at enrolment. The clinical plus biomarker panel predicted active joint count = 0, physician global assessment ≤ 1, and inactive disease after 18 months with 0.79, 0.80 and 0.83 accuracy and 0.84, 0.83, 0.88 area under the curve, respectively. Using clinical features alone resulted in 0.75, 0.72 and 0.80 accuracy, and area under the curve values of 0.81, 0.78 and 0.83, respectively. Conclusion A panel of five plasma biomarkers combined with clinical features at the time of diagnosis more accurately predicted short-term disease activity in JIA than clinical characteristics alone. If validated in external cohorts, such a panel may guide more rationally conceived, biologically based, personalized treatment strategies in early JIA.

Additional file 5. Final set of KPIs: descriptions and reporting. Full descriptions and reporting details for the final set of KPIs. Is an extension of Table 4 in manuscript.

Additional file 3. Summary of proposed Key Performance Indicators (KPIs), modifications and rationale. Summary of modifications to KPIs and rationale by the working group or Delphi panel.

Additional file 2. Select guidelines or standards of care or recommendations endorsed by various medical societies. Sources and links/references for guidelines, standards of care and recommendations endorsed by various medical societies.

Additional file 1. Select websites searched for grey literature review. Sources and website links for sites searched for grey literature review.

Background The evaluation of quality of care in juvenile idiopathic arthritis (JIA) is critical for advancing patient outcomes but is not currently part of routine care across all centers in Canada. The study objective is to review the current landscape of JIA quality measures and use expert panel consensus to define key performance indicators (KPIs) that are important and feasible to collect for routine monitoring in JIA care in Canada. Methods Thirty-seven candidate KPIs identified from a systematic review were reviewed for inclusion by a working group including 3 pediatric rheumatologists. A shortlist of 14 KPIs was then assessed using a 3-round modified Delphi panel based on the RAND/UCLA Appropriateness Method. Ten panelists across Canada participated based on their expertise in JIA, quality measurement, or lived experience as a parent of a child with JIA. During rounds 1 and 3, panelists rated each KPI on a 1–9 Likert scale on themes of importance, feasibility, and priority. In round 2, panelists participated in a moderated in-person discussion that resulted in minor modifications to some KPIs. KPIs with median scores of ≥ 7 on all 3 questions without disagreement were included in the framework. Results Ten KPIs met the criteria for inclusion after round 3. Five KPIs addressed patient assessments: pain, joint count, functional status, global assessment of disease activity, and the clinical Juvenile Arthritis Disease Activity Score (cJADAS). Three KPIs examined access to care: wait times for consultation, access to pediatric rheumatologists within 1 year of diagnosis, and frequency of clinical follow-up. Safety was addressed through KPIs on tuberculous screening and laboratory monitoring. KPIs examining functional status using the Childhood Health Assessment Questionnaire (CHAQ), quality of life, uveitis, and patient satisfaction were excluded due to concerns about feasibility of measurement. Conclusions The proposed KPIs build upon existing KPIs and address important processes of care that should be measured to improve the quality of JIA care. The feasibility of capturing these measures will be tested in various data sources including the Understanding Childhood Arthritis Network (UCAN) studies. Subsequent work should focus on development of meaningful outcome KPIs to drive JIA quality improvement in Canada and beyond.

Objective Published predictive models of disease outcomes in idiopathic inflammatory myopathies (IIMs) are sparse and of limited accuracy due to disease heterogeneity. Computational methods may address this heterogeneity by partitioning patients based on clinical and biological phenotype. Methods To identify new patient groups, we applied similarity network fusion (SNF) to clinical and biological data from 168 patients with myositis (64 adult polymyositis [PM], 65 adult dermatomyositis [DM], and 39 juvenile DM [JDM]) in the Rituximab in Myositis trial. We generated a sparse proof-of-concept bedside classifier using multinomial regression and identified characteristics that distinguished these groups. We conducted χ2 tests to link new patient groups with the myositis subtypes. Results SNF identified five patient groups in the discovery cohort that subdivided the myositis subtypes. The sparse multinomial regressor to predict patient group assignments (areas under the receiver operating characteristic curve = [0.78, 0.97]; areas under the precision-recall curve = [0.55, 0.96]) found that autoantibody enrichment defined four of these groups: anti-Mi-2, anti-signal recognition peptide (SRP), anti-nuclear matrix protein 2 (NXP2), and anti-synthetase (Syn). Depletion of immunoglobulin M (IgM) defined the fifth group. Each group was associated with one subtype, with adult DM being associated with anti-Mi-2 and anti-Syn autoantibodies, JDM being associated with anti-NXP2 autoantibodies, and adult PM being associated with IgM depletion and anti-SRP autoantibodies. These associations enabled us to further resolve the current myositis subtypes. Conclusion Using unsupervised machine learning, we identified clinically and biologically homogeneous groups of patients with IIMs, forming the basis of an integrated disease classification based on both clinical and biological phenotype, thus validating other approaches and what has been previously described.

Anti-neutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) refers to a complex group of systemic vasculitides that are characterized by primary small-to-medium sized blood vessel inflammation with the presence of autoantibodies known as ANCA. AAV diseases include Granulomatosis with Polyangiitis (GPA), Eosinophilic Granulomatosis with Polyangiitis (EGPA), and Microscopic Polyangiitis (MPA). AAVs are challenging conditions associated with high cumulative disease and treatment related morbidity and mortality. Given its rarity and the resulting paucity of pediatric-specific clinical trial evidence, pediatric rheumatologists have had to often extrapolate from adult literature for management and therapeutic decisions. The aim of this review is to provide a comprehensive overview of the important findings and overall conclusions of critical landmark clinical trials in the induction and maintenance treatments in adult AAV for the pediatric rheumatologist. This review also highlights the outcomes of recent pediatric AAV observational studies and discusses the future research priorities in pediatric AAV management.

Background: Heterogeneity in response to biological medication is a major challenge in the management of Juvenile Idiopathic Arthritis (JIA) (1). Biomarkers such as cytokines or whole blood RNA expression profiles that predict therapy efficacy prior to treatment pose a solution and could enable precision medicine. It was previously demonstrated that whole blood gene expression profiles can predict response to anti-TNF-α therapy in patients with JIA (2). These findings currently await validation in a multicenter prospective cohort study. Harmonization of data from different cohorts, however, is often hampered by site-dependent differences in biological sample collection and processing (3). For instance, the biological material that is retrospectively available from biobanks depends on what is stored exactly, e.g. whole blood versus peripheral blood mononuclear cells (PBMC). Furthermore, different blood collection tubes containing different additives can affect sample quality at an early stage and make interchangeability or comparability of data impossible. Objectives: We evaluated the comparability of gene expression profiles when whole blood from patients with JIA is collected in different RNA collection tubes and processed accordingly. Next, we will investigate the predictive capacity for therapy response of RNA expression profiles from frozen PBMC of 63 JIA patients. Methods: Peripheral blood from 11 children with non-systemic JIA with active disease was collected in PAXgene (PreAnalytiX) and Tempus (Applied Biosystems) tubes. All tubes were subsequently stored in the freezer at -80 °C. After thawing, RNA from the PAXgene tubes was extracted with use of the PAXgene Blood RNA Kit and RNA from the Tempus tubes was isolated by using the Tempus Preserved Blood RNA Purification Kit I. Gene expression of CSNK1D, C1D, ASAP2, SRRD, PPP1R3B, HLA-DQA1, PDZK1IP1 and MZB1 was determined with qPCR. For our next experiment, frozen PBMC derived from patients with non-systemic JIA who are included in our longitudinal Pharmachild registry biobank will be used. Of the 63 patients, 28 (44.4%) children were diagnosed with oligo articular JIA, 19 (30.2%) with poly articular JIA, 9 (14.3%) with enthesitis-related JIA, 4 (6.3%) with psoriatic JIA and 3 (4.8%) with undifferentiated JIA. The average age at sampling was 11.5 years ± 4.0 and 65% of the patients was female. These samples will be run on a 96-analyte NanoString panel and associated with clinical response at time points 3 and 6 months after start of TNF-α blockade. Results: Both RNA blood collection systems yielded high-quality RNA, with overall higher RNA concentrations for blood collected in Tempus tubes in comparison to PAXgene tubes. qPCR data showed that gene expression of all measured genes is affected by the method of blood collection and processing. However, the inter-individual variation was similar between both collection tubes, indicating that similar RNA profiles were observed. Conclusion: Gene expression profiles derived from whole blood collected in PAXgene or Tempus tubes are comparable, but are not interchangeable. References: [1] Swart JF, de Roock S, & Prakken BJ. Understanding inflammation in juvenile idiopathic arthritis: How immune biomarkers guide clinical strategies in the systemic onset subtype. Eur J Immunol 2016;46(9):2068-2077. [2] Cui A, Quon G, Rosenberg AM et al. Gene Expression Deconvolution for Uncovering Molecular Signatures in Response to Therapy in Juvenile Idiopathic Arthritis. PloS one 2016;11(5):1-17. [3] Yeung RS, Albani S, Feldman BM et al. Enhancing translational research in paediatric rheumatology through standardization. Nature Reviews Rheumatology 2016;12(11):684. Disclosure of Interests: None declared

Annals of the rheumatic diseases 76(5), 906-913 (2017). doi:10.1136/annrheumdis-2016-210324, Published by BMJ Publ. Group, London

Con A hepatitis is regarded as a T cell–mediated model of acute liver injury. Mincle is a C-type lectin receptor that is critical in the immune response to mycobacteria and fungi but does not have a well-defined role in preclinical models of non-pathogen–mediated inflammation. Because Mincle can ligate the cell death ligand SAP130, we postulated that Mincle signaling drives intrahepatic inflammation and liver injury in Con A hepatitis. Acute liver injury was assessed in the murine Con A hepatitis model using C57BL/6, Mincle−/−, and Dectin-1−/− mice. The role of C/EBPβ and hypoxia-inducible factor-1α (HIF-1α) signaling was assessed using selective inhibitors. We found that Mincle was highly expressed in hepatic innate inflammatory cells and endothelial cells in both mice and humans. Furthermore, sterile Mincle ligands and Mincle signaling intermediates were increased in the murine liver in Con A hepatitis. Most significantly, Mincle deletion or blockade protected against Con A hepatitis, whereas Mincle ligation exacerbated disease. Bone marrow chimeric and adoptive transfer experiments suggested that Mincle signaling in infiltrating myeloid cells dictates disease phenotype. Conversely, signaling via other C-type lectin receptors did not alter disease course. Mechanistically, we found that Mincle blockade decreased the NF-κβ–related signaling intermediates C/EBPβ and HIF-1α, both of which are necessary in macrophage-mediated inflammatory responses. Accordingly, Mincle deletion lowered production of nitrites in Con A hepatitis and inhibition of both C/EBPβ and HIF-1α reduced the severity of liver disease. Our work implicates a novel innate immune driver of Con A hepatitis and, more broadly, suggests a potential role for Mincle in diseases governed by sterile inflammation.

Objective To uniquely classify children with microscopic polyangiitis (MPA), to describe their demographic characteristics, presenting clinical features, and initial treatments in comparison to patients with granulomatosis with polyangiitis (Wegener's) (GPA). Methods The European Medicines Agency (EMA) classification algorithm was applied by computation to categorical data from patients recruited to the ARChiVe (A Registry for Childhood Vasculitis: e-entry) cohort, with the data censored to November 2015. The EMA algorithm was used to uniquely distinguish children with MPA from children with GPA, whose diagnoses had been classified according to both adult- and pediatric-specific criteria. Descriptive statistics were used for comparisons. Results In total, 231 of 440 patients (64% female) fulfilled the classification criteria for either MPA (n = 48) or GPA (n = 183). The median time to diagnosis was 1.6 months in the MPA group and 2.1 months in the GPA group (ranging to 39 and 73 months, respectively). Patients with MPA were significantly younger than those with GPA (median age 11 years versus 14 years). Constitutional features were equally common between the groups. In patients with MPA compared to those with GPA, pulmonary manifestations were less frequent (44% versus 74%) and less severe (primarily, hemorrhage, requirement for supplemental oxygen, and pulmonary failure). Renal pathologic features were frequently found in both groups (75% of patients with MPA versus 83% of patients with GPA) but tended toward greater severity in those with MPA (primarily, nephrotic-range proteinuria, requirement for dialysis, and end-stage renal disease). Airway/eye involvement was absent among patients with MPA, because these GPA-defining features preclude a diagnosis of MPA within the EMA algorithm. Similar proportions of patients with MPA and those with GPA received combination therapy with corticosteroids plus cyclophosphamide (69% and 78%, respectively) or both drugs in combination with plasmapheresis (19% and 22%, respectively). Other treatments administered, ranging in decreasing frequency from 13% to 3%, were rituximab, methotrexate, azathioprine, and mycophenolate mofetil. Conclusion Younger age at disease onset and, perhaps, both gastrointestinal manifestations and more severe kidney disease seem to characterize the clinical profile in children with MPA compared to those with GPA. Delay in diagnosis suggests that recognition of these systemic vasculitides is suboptimal. Compared with adults, initial treatment regimens in children were comparable, but the complete reversal of female-to-male disease prevalence ratios is a provocative finding.

The past decade has seen many successes in translational rheumatology, from dramatic improvements in outcomes brought about by novel biologic therapies, to the discovery of new monogenic inflammatory disorders. Advances in molecular medicine, combined with progress towards precision care, provide an excellent opportunity to accelerate the translation of biological understanding to the bedside. However, although the field of rheumatology is a leader in the standardization of data collection and measures of disease activity, it lags behind in standardization of biological sample collection and assay performance. Uniform approaches are necessary for robust collaborative research, particularly in rare diseases. Standardization is also critical to increase reproducibility between centres, a prerequisite for clinical implementation of translational research. This Perspectives article emphasizes the need for standardization and implementation of best practices, presented in the context of lessons learned from international biorepository networks.

Background Joint inflammation is the common feature underlying juvenile idiopathic arthritis (JIA). Clinicians recognize patterns of joint involvement currently not part of the International League of Associations for Rheumatology (ILAR) classification. Using unsupervised machine learning, we sought to uncover data-driven joint patterns that predict clinical phenotype and disease trajectories. Methods and findings We analyzed prospectively collected clinical data, including joint involvement using a standard 71-joint homunculus, for 640 discovery patients with newly diagnosed JIA enrolled in a Canada-wide study who were followed serially for five years, treatment-naïve except for nonsteroidal anti-inflammatory drugs (NSAIDs) and diagnosed within one year of symptom onset. Twenty-one patients had systemic arthritis, 300 oligoarthritis, 125 rheumatoid factor (RF)-negative polyarthritis, 16 RF-positive polyarthritis, 37 psoriatic arthritis, 78 enthesitis-related arthritis (ERA), and 63 undifferentiated arthritis. At diagnosis, we observed global hierarchical groups of co-involved joints. To characterize these patterns, we developed sparse multilayer non-negative matrix factorization (NMF). Model selection by internal bi-cross-validation identified seven joint patterns at presentation, to which all 640 discovery patients were assigned: pelvic girdle (57 patients), fingers (25), wrists (114), toes (48), ankles (106), knees (283), and indistinct (7). Patterns were distinct from clinical subtypes (P < 0.001 by χ2 test) and reproducible through external data set validation on a 119-patient, prospectively collected independent validation cohort (reconstruction accuracy Q2 = 0.55 for patterns; 0.35 for groups). Some patients matched multiple patterns. To determine whether their disease outcomes differed, we further subdivided the 640 discovery patients into three subgroups by degree of localization—the percentage of their active joints aligning with their assigned pattern: localized (≥90%; 359 patients), partially localized (60%–90%; 124), or extended (, Using unsupervised machine learning, Rae Yeung and colleagues uncover data-driven joint patterns that predict clinical phenotype and disease trajectories in JIA., Author summary Why was this study done? Juvenile idiopathic arthritis (JIA) is a heterogeneous childhood disease for which joint inflammation is the common denominator. The current classification system, the International League of Associations for Rheumatology (ILAR) subtypes, categorize patients according to the number of active joints (four or fewer versus five or more affected joints in the first six months of disease) with little evidence to support this cut-off. Grouping frequently co-involved joints into joint patterns may help to better classify patients and predict disease course. What did the researchers do and find? We analyzed baseline joint involvement data from 640 treatment-naïve patients from 16 Canadian centers participating in the Research in Arthritis in Canadian Children, Emphasizing Outcomes (ReACCh-Out) study between 2005 and 2010. We identified seven joint patterns that grouped frequently co-involved joints using multilayer non-negative matrix factorization (NMF), an unsupervised pattern recognition technique. We named these patterns as follows: pelvic girdle, fingers, wrists, toes, knees, ankles, and indistinct. These seven patterns described more homogenous groupings of joints than the ILAR subtypes and further stratified them. Throughout disease course, we found that patients with joint involvements largely overlapping their baseline patterns, i.e., those having localized involvement, continued to have the same active joints, whereas patients with nonlocalized involvement did not. Patients with localized joint involvement reached zero joint involvement faster than those with nonlocalized involvement. What do these findings mean? Patterns of joint involvement represent prognostic features that should be incorporated into a comprehensive JIA disease classification. Patients with nonlocalized joint involvement are at high risk of poor outcome. Grouping patients by joint pattern and degree of localization may help clinicians tailor treatments based on predicted disease trajectories.

The human Fc-gamma receptors (FcγRs) link adaptive and innate immunity by binding immunoglobulin G (IgG). All human low-affinity FcγRs are encoded by the FCGR2/3 locus containing functional single nucleotide polymorphisms (SNPs) and gene copy number variants. This locus is notoriously difficult to genotype and high-throughput methods commonly used focus on only a few SNPs. We performed multiplex ligation-dependent probe amplification for all relevant genetic variations at the FCGR2/3 locus in >4,000 individuals to define linkage disequilibrium (LD) and allele frequencies in different populations. Strong LD and extensive ethnic variation in allele frequencies was found across the locus. LD was strongest for the FCGR2C-ORF haplotype (rs759550223+rs76277413), which leads to expression of FcγRIIc. In Europeans, the FCGR2C-ORF haplotype showed strong LD with, among others, rs201218628 (FCGR2A-Q27W, r2 = 0.63). LD between these two variants was weaker (r2 = 0.17) in Africans, whereas the FCGR2C-ORF haplotype was nearly absent in Asians (minor allele frequency