Prevalence of preexisting articular bone pathology in patients with osteoarthritis screened for fasinumab clinical trials identified by X-ray or magnetic resonance imaging.

OBJECTIVE: To examine the prevalence of preexisting articular bone pathology in patients with hip or knee pain due to osteoarthritis (OA) screened for fasinumab clinical trials. METHOD: This post-hoc analysis included patients with OA screened for three phase 3 fasinumab studies (NCT02683239, NCT03161093, NCT03304379). During screening, participants who met other clinical inclusion/exclusion criteria underwent radiography of knees, hips, and shoulders. Those with Kellgren-Lawrence grade (KLG) ≥2 for index joint and without an exclusionary finding proceeded to magnetic resonance imaging (MRI) of index, contralateral, and KLG ≥3 joints. Exclusionary findings included bone fragmentation/collapse, bone loss/resorption, osteonecrosis, and fracture, by either X-ray or MRI. Participants with extensive subchondral cysts were also excluded. Prevalence of abnormalities on radiographs and MRIs are reported. RESULTS: Of 27,633 participants screened, 21,997 proceeded to imaging. Of these, 1203 (5.5%) were excluded due to the presence of ≥1 joint with severe articular bone pathology (X-ray or MRI): bone fragmentation/collapse (2.61%), subchondral insufficiency fracture (SIF; 1.67%), osteonecrosis (1.11%), and significant bone loss (0.32%). Additionally, 3.14% screen-failed due to extensive subchondral cysts. More than half of the exclusions due to bone fragmentation/collapse (386/572), osteonecrosis (141/245) and significant bone loss (59/71), and approximately one third of SIF (133/367) and extensive subchondral cysts (229/689) were evident on X-rays. CONCLUSIONS: Approximately one in 20 participants with OA who met the clinical screening criteria for fasinumab phase 3 trials were later excluded due to preexisting severe articular bone pathology findings by X-ray or MRI.

Risk of carpal tunnel syndrome among patients with osteoarthritis: a US population-based study.

BACKGROUND: Carpal tunnel syndrome (CTS), an entrapment neuropathy caused by pressure of the median nerve, is a progressive condition that can lead to a decreased quality of life. Studies suggest an association between CTS and arthritis; however, previous studies examining osteoarthritis (OA) and CTS are limited in number, scope and study design. This study estimated the incidence and risk of CTS among patients with OA, both overall and by specific joints, in a large population-based cohort in the United States. METHODS: Patients from the Optum claims database aged ≥ 45 years and diagnosed with OA between January 1, 2018, and December 31, 2022, were eligible for the OA cohort. The non-OA cohort included those without a diagnosis of OA at the index date and no history of OA for 12 months pre-index. Baseline characteristics were balanced using propensity score matching. The risk of CTS in the OA and non-OA cohort were evaluated using incidence rates and adjusted hazard ratios that were estimated using Cox regression. RESULTS: After applying the inclusion/exclusion criteria, 3,610,240 of the 6,023,384 adults with a diagnosis of OA remained in the OA cohort. After propensity-score matching, each cohort included 1,033,439 individuals. The incidence rates for CTS per 1000 person-years were 7.35 (95% confidence interval [CI] 7.21-7.49) in the OA cohort and 1.44 (95% CI 1.38-1.50) in the non-OA cohort. The risk of developing CTS in patients with OA was ~ 4 times that of patients without (hazard ratio = 3.80; 95% CI 3.54-4.07). This increased risk was found across all OA joint types, with OA of the hand/wrist having the highest risk for CTS. Additionally, multiple OA joints presented a higher risk compared with a single affected joint. CONCLUSIONS: OA increases the risk of CTS, but this is not limited to patients with hand/wrist OA, suggesting a systemic impact of OA on CTS. While the risk appears highest for patients with hand/wrist OA, patients with more distant affected joints like knee or hip also have an increased risk of CTS.

Gene Expression Profiles of Treatment Response and Non-Response in Children With Juvenile Dermatomyositis.

OBJECTIVE: The study objective was to identify differences in gene expression between treatment responders (TRs) and treatment non-responders (TNRs) diagnosed with juvenile dermatomyositis (JDM). METHODS: Gene expression analyses were performed using whole blood messenger RNA sequencing in patients with JDM (n = 17) and healthy controls (HCs; n = 10). Four analyses were performed (A1-4) comparing differential gene expression and pathways analysis exploiting the timing of sample acquisition and the treatments received to perform these comparative analyses. Analyses were done at diagnosis and follow-up, which averaged 7 months later in the cohort. RESULTS: At diagnosis, the expression of 10 genes differed between TRs and TNRs. Hallmark and canonical pathway analysis revealed 11 and 60 pathways enriched in TRs and 3 and 21 pathways enriched in TNRs, respectively. Pathway enrichment at diagnosis in TRs was strongest in pathways involved in metabolism, complement activation, and cell signaling as mediated by IL-8, p38/microtubule associated protein kinases (MAPK)/extracellular signal-regulated kinases (ERK), Phosphatidylinositol 3 Kinase Gamma (PI3Kγ), and the B cell receptor. Follow-up hallmark and canonical pathway analysis showed that 2 and 14 pathways were enriched in TRs, whereas 24 and 123 pathways were enriched in treatment TNRs, respectively. Prior treatment with glucocorticoids significantly altered expression of 13 genes in the analysis of subjects at diagnosis with JDM as compared with HCs. CONCLUSION: Numerous genes and pathways differ between TRs and TNRs at diagnosis and follow-up. Prior treatment with glucocorticoids prior to specimen acquisition had a small effect on the performed analyses.

A Comparison of International League of Associations for Rheumatology and Pediatric Rheumatology International Trials Organization Classification Systems for Juvenile Idiopathic Arthritis Among Children in a Canadian Arthritis Cohort.

OBJECTIVE: The aim of the Paediatric Rheumatology International Trials Organisation (PRINTO) juvenile idiopathic arthritis (JIA) classification criteria, which is still in development, is to identify homogeneous groups of JIA patients. This study was undertaken to compare International League of Associations for Rheumatology (ILAR) JIA classification criteria and PRINTO JIA classification criteria using data from the ReACCh-Out (Research in Arthritis in Canadian Children, Emphasizing Outcomes) cohort. METHODS: We used clinicobiologic data recorded within 7 months of diagnosis to assign a diagnosis of JIA and identify subcategories of JIA among 1,228 patients according to the 2 JIA classification systems. We compared the proportions of patients classified and the alignment of classification categories with clinicobiologic subtypes and adult arthritis types. RESULTS: The PRINTO criteria classified 244 patients (19.9%) as having early-onset antinuclear antibody-positive JIA, 157 (12.8%) as having enthesitis/spondylitis-related JIA, 38 (3.1%) as having systemic JIA, and 10 (0.8%) as having rheumatoid factor-positive JIA. A total of 12% of patients were unclassifiable using the ILAR criteria, while 63.3% were unclassifiable using the PRINTO criteria (777 with other JIA and 2 with unclassified JIA). In sensitivity analyses, >50% of patients remained unclassifiable using the PRINTO criteria. Compared to the PRINTO criteria, ILAR JIA categories aligned better with clinicobiologic subtypes in 131 patients (χ2 = 44, P = 0.005, versus χ2 = 15, P = 0.07 for PRINTO), and ILAR categories aligned better with adult types of arthritis in 389 evaluable patients. CONCLUSION: Currently identified PRINTO disorders can only be used to classify a minority of JIA patients, leaving a large proportion of JIA patients with other disorders requiring further characterization. Current PRINTO JIA classification criteria do not align better with clinicobiologic subtypes or adult forms of arthritis compared with the older ILAR classification system.

Human Monoclonal Antibody Cocktail for the Treatment or Prophylaxis of Middle East Respiratory Syndrome Coronavirus.

BACKGROUND: REGN3048 and REGN3051 are human monoclonal antibodies (mAb) targeting the spike glycoprotein on the Middle East respiratory syndrome coronavirus (MERS-CoV), which binds to the receptor dipeptidyl peptidase-4 (DPP4) and is necessary for infection of susceptible cells. METHODS: Preclinical study: REGN3048, REGN3051 and isotype immunoglobulin G (IgG) were administered to humanized DPP4 (huDPP4) mice 1 day prior to and 1 day after infection with MERS-CoV (Jordan strain). Virus titers and lung pathology were assessed. Phase 1 study: healthy adults received the combined mAb (n = 36) or placebo (n = 12) and followed for 121 days. Six dose levels were studied. Strict safety criteria were met prior to dose escalation. RESULTS: Preclinical study: REGN3048 plus REGN3051, prophylactically or therapeutically, was substantially more effective for reducing viral titer, lung inflammation, and pathology in huDPP4 mice compared with control antibodies and to each antibody monotherapy. Phase 1 study: REGN3048 plus REGN3051 was well tolerated with no dose-limiting adverse events, deaths, serious adverse events, or infusion reactions. Each mAb displayed pharmacokinetics expected of human IgG1 antibodies; it was not immunogenic. CONCLUSIONS: REGN3048 and REGN3051 in combination were well tolerated. The clinical and preclinical data support further development for the treatment or prophylaxis of MERS-CoV infection.

Associations of clinical and inflammatory biomarker clusters with juvenile idiopathic arthritis categories.

OBJECTIVE: To identify discrete clusters comprising clinical features and inflammatory biomarkers in children with JIA and to determine cluster alignment with JIA categories. METHODS: A Canadian prospective inception cohort comprising 150 children with JIA was evaluated at baseline (visit 1) and after six months (visit 2). Data included clinical manifestations and inflammation-related biomarkers. Probabilistic principal component analysis identified sets of composite variables, or principal components, from 191 original variables. To discern new clinical-biomarker clusters (clusters), Gaussian mixture models were fit to the data. Newly-defined clusters and JIA categories were compared. Agreement between the two was assessed using Kruskal-Wallis analyses and contingency plots. RESULTS: Three principal components recovered 35% (three clusters) and 40% (five clusters) of the variance in patient profiles in visits 1 and 2, respectively. None of the clusters aligned precisely with any of the seven JIA categories but rather spanned multiple categories. Results demonstrated that the newly defined clinical-biomarker lustres are more homogeneous than JIA categories. CONCLUSION: Applying unsupervised data mining to clinical and inflammatory biomarker data discerns discrete clusters that intersect multiple JIA categories. Results suggest that certain groups of patients within different JIA categories are more aligned pathobiologically than their separate clinical categorizations suggest. Applying data mining analyses to complex datasets can generate insights into JIA pathogenesis and could contribute to biologically based refinements in JIA classification.

A Clinically and Biologically Based Subclassification of the Idiopathic Inflammatory Myopathies Using Machine Learning.

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.

Patterns of joint involvement in juvenile idiopathic arthritis and prediction of disease course: A prospective study with multilayer non-negative matrix factorization.

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 (<60%; 157). Localized patients more often maintained their baseline patterns (P < 0.05 for five groups by permutation test) than nonlocalized patients (P < 0.05 for three groups by permutation test) over a five-year follow-up period. We modelled time to zero joints in the discovery cohort using a multivariate Cox proportional hazards model considering joint pattern, degree of localization, and ILAR subtype. Despite receiving more intense treatment, 50% of nonlocalized patients had zero joints at one year compared to six months for localized patients. Overall, localized patients required less time to reach zero joints (partial: P = 0.0018 versus localized by log-rank test; extended: P = 0.0057). Potential limitations include the requirement for patients to be treatment naïve (except NSAIDs), which may skew the patient cohorts towards milder disease, and the validation cohort size precluded multivariate analyses of disease trajectories. CONCLUSIONS: Multilayer NMF identified patterns of joint involvement that predicted disease trajectory in children with arthritis. Our hierarchical unsupervised approach identified a new clinical feature, degree of localization, which predicted outcomes in both cohorts. Detailed assessment of every joint is already part of every musculoskeletal exam for children with arthritis. Our study supports both the continued collection of detailed joint involvement and the inclusion of patterns and degrees of localization to stratify patients and inform treatment decisions. This will advance pediatric rheumatology from counting joints to realizing the potential of using data available from uncovering patterns of joint involvement.

High-Density Proximity Mapping Reveals the Subcellular Organization of mRNA-Associated Granules and Bodies.

mRNA processing, transport, translation, and ultimately degradation involve a series of dedicated protein complexes that often assemble into large membraneless structures such as stress granules (SGs) and processing bodies (PBs). Here, systematic in vivo proximity-dependent biotinylation (BioID) analysis of 119 human proteins associated with different aspects of mRNA biology uncovers 7424 unique proximity interactions with 1,792 proteins. Classical bait-prey analysis reveals connections of hundreds of proteins to distinct mRNA-associated processes or complexes, including the splicing and transcriptional elongation machineries (protein phosphatase 4) and the CCR4-NOT deadenylase complex (CEP85, RNF219, and KIAA0355). Analysis of correlated patterns between endogenous preys uncovers the spatial organization of RNA regulatory structures and enables the definition of 144 core components of SGs and PBs. We report preexisting contacts between most core SG proteins under normal growth conditions and demonstrate that several core SG proteins (UBAP2L, CSDE1, and PRRC2C) are critical for the formation of microscopically visible SGs.

Childhood Takayasu arteritis: disease course and response to therapy.

BACKGROUND: Takayasu arteritis (TAK) is a large vessel vasculitis that rarely affects children. Data on childhood TAK are scarce. The aim of this study was to analyze the presenting features, course and outcome of children with TAK, compare efficacy of treatment regimens and identify high-risk factors for adverse outcome. METHODS: A single-center cohort study of consecutive children fulfilling the EULAR/PRINTO/PReS criteria for childhood TAK between 1986 and 2015 was performed. Clinical phenotypes, laboratory markers, imaging features, disease course and treatment were documented. Disease activity was assessed using the Pediatric Vasculitis Disease Activity Score at each visit. OUTCOME: disease flare defined as new symptoms and/or increased inflammatory markers necessitating therapy escalation and/or new angiographic lesions, or death. ANALYSIS: logistic regression tested relevant variables for flare. Kaplan-Meier analyses compared treatment regimens. RESULTS: Twenty-seven children were included; 74% were female, median age at diagnosis was 12.4 years. Twenty-two (81%) children presented with active disease at diagnosis. Treatment regimens included corticosteroids alone (15%), corticosteroids plus methotrexate (37%), cyclophosphamide (19%), or a biologic agent (11%). Adverse outcomes were documented in 14/27 (52%) children: two (7%) died within 6 months of diagnosis, and 13 (48%) experienced disease flares. The 2-year flare-free survival was 80% with biologic treatments compared to 43% in non-biologic therapies (p = 0.03); at last follow-up, biologic therapies resulted in significantly higher rates of inactive disease (p = 0.02). No additional outcome predictor was identified. CONCLUSIONS: Childhood TAK carries a high disease burden; half of the children experienced flares and 7% died. Biologic therapies were associated with better control of disease activity.

Ritonavir-boosted danoprevir-based regimens in treatment-naive and prior null responders with HCV genotype 1 or 4 and compensated cirrhosis.

BACKGROUND AND AIM: Effective and safe antiviral treatment regimens are needed for patients with chronic hepatitis C (CHC) and cirrhosis. METHODS: An international open-label trial was conducted in CHC patients with genotype (G)1/4 infection, compensated cirrhosis, HCV RNA ≥ 50,000 IU/mL and body mass index 18-35 kg/m(2). Treatment-naive patients (Cohort 1) received a triple therapy regimen [danoprevir/r 100/100 mg twice daily (bid), ribavirin 1000/1200 mg/day and peginterferon alfa-2a 180 µg/week] for 24 weeks. Prior null responders (Cohort 2) received a quadruple therapy regimen (danoprevir/r 100/100 mg bid, mericitabine 1000 mg bid and peginterferon alfa-2a/ribavirin). The primary efficacy outcome was sustained virological response (HCV RNA < limit of quantification, target not detected) at end of the 24-week follow-up period (SVR24). RESULTS: In Cohort 1 (n = 23), 73.9 and 65.2 % of patients had a virological response at Weeks 4 and 24, respectively; 39.1 % achieved SVR24 (G1a = 1/13; G1b = 8/9; G4 = 0/1). In Cohort 2 (n = 20), 100 % achieved virological response at Weeks 4 and 24; 65 % achieved SVR24 (G1a = 4/8; G1b = 7/10; G4 = 2/2). Treatment failure was more common in G1a than G1b-infected patients and less common in patients receiving quadruple therapy. Treatment failure was associated with emergence of resistance to danoprevir, but not mericitabine. The safety profile was typical of that associated with peginterferon alfa-2a/ribavirin. No deaths/episodes of hepatic decompensation occurred. CONCLUSIONS: Treatment with danoprevir/r-based regimens for 24 weeks is safe and well tolerated in CHC patients with compensated cirrhosis. A quadruple therapy regimen (danoprevir/r, mericitabine, peginterferon alfa/ribavirin) produced high SVR24 rates in prior null responders, particularly among G1b patients.

Randomized study of danoprevir/ritonavir-based therapy for HCV genotype 1 patients with prior partial or null responses to peginterferon/ribavirin.

BACKGROUND & AIMS: Chronic hepatitis C treatment for prior non-responders to peginterferon (PegIFN)/ribavirin remains suboptimal. The MATTERHORN study evaluated regimens containing ritonavir-boosted danoprevir (danoprevir/r) in prior PegIFN alfa/ribavirin non-responders. METHODS: Prior partial responders (N=152) were randomized to 24 weeks of twice-daily danoprevir/r 100/100mg, mericitabine 1000 mg and ribavirin 1000/1200 mg (IFN-free); danoprevir/r plus PegIFN alfa-2a/ribavirin (triple); or danoprevir/r, mericitabine and PegIFN alfa-2a/ribavirin (Quad). Prior null responders (N=229) were randomized to 24 weeks of IFN-free therapy, or quad alone (Quad 24) or quad plus 24-weeks of PegIFN alfa-2a/ribavirin (Quad 48). The primary endpoint was sustained virological response (HCV RNA <25 IU/ml) 24 weeks after end-of-treatment (SVR24). Due to high relapse rates, genotype (G) 1a patients in IFN-free arms were offered additional PegIFN alfa-2a/ribavirin. RESULTS: Among prior partial responders, SVR24 rates were 46.2%, 51.0%, and 86.0%, in the IFN-free, Triple and Quad arms, respectively; among prior null responders, SVR24 rates were 45.5%, 80.5%, and 83.8% respectively. Relapse rates were lower and SVR24 rates higher in G1b-infected than G1a-infected patients. SVR24 rates in G1a and G1b patients randomized to Quad were 75.0% and 96.2%, respectively, in the partial Quad arm, and 68.1% and 100%, respectively, in the null Quad 24 arm. Treatment failure was associated with resistance to danoprevir, but not to mericitabine, and was more common in G1a infected patients. Treatment was well-tolerated. CONCLUSIONS: Danoprevir/r, mericitabine plus PegIFN alfa-2a/ribavirin was well-tolerated and produced high overall SVR24 rates in prior partial and null responders to PegIFN alfa/ribavirin. In contrast, IFN-free regimens were associated with unacceptably high relapse rates.

The biologic basis of clinical heterogeneity in juvenile idiopathic arthritis.

OBJECTIVE: Childhood arthritis encompasses a heterogeneous family of diseases. Significant variation in clinical presentation remains despite consensus-driven diagnostic classifications. Developments in data analysis provide powerful tools for interrogating large heterogeneous data sets. We report a novel approach to integrating biologic and clinical data toward a new classification for childhood arthritis, using computational biology for data-driven pattern recognition. METHODS: Probabilistic principal components analysis was used to transform a large set of data into 4 interpretable indicators or composite variables on which patients were grouped by cluster analysis. Sensitivity analysis was conducted to determine key variables in determining indicators and cluster assignment. Results were validated against an independent validation cohort. RESULTS: Meaningful biologic and clinical characteristics, including levels of proinflammatory cytokines and measures of disease activity, defined axes/indicators that identified homogeneous patient subgroups by cluster analysis. The new patient classifications resolved major differences between patient subpopulations better than International League of Associations for Rheumatology subtypes. Fourteen variables were identified by sensitivity analysis to crucially determine indicators and clusters. This new schema was conserved in an independent validation cohort. CONCLUSION: Data-driven unsupervised machine learning is a powerful approach for interrogating clinical and biologic data toward disease classification, providing insight into the biology underlying clinical heterogeneity in childhood arthritis. Our analytical framework enabled the recovery of unique patterns from small cohorts and addresses a major challenge, patient numbers, in studying rare diseases.