Serum ARGS-aggrecan in a phase 2 clinical trial targeting osteoarthritis.

OBJECTIVE: To monitor serum concentrations of the aggrecan ARGS neoepitope in a clinical trial of ADAMTS-5 inhibition as disease-modifying therapy of knee osteoarthritis, and to investigate relationships between reduction in ARGS and change in cartilage thickness, knee related pain and function. DESIGN: ROCCELLA trial participants received once-daily oral S201086 75, 150 or 300 mg, or placebo, for 52 weeks. Serum was collected at baseline, 4, 12, 28 and 52 weeks, and 2 weeks post treatment with ARGS measured by an in-house immunoassay. Change from baseline to week 52 in central medial femorotibial compartment cartilage thickness was measured by MRI, function and pain by WOMAC subscores. Associations between cumulative change in ARGS and change in cartilage thickness or WOMAC subscores were evaluated by linear regression. RESULTS: S201086 reduced serum levels of ARGS in a dose-dependent manner throughout the treatment period. Maximal reduction was at 4 weeks with a 58.5% [95% CI 60.8%, 56.2%] reduction of ARGS compared to baseline for 300 mg S201086. Two weeks post treatment, ARGS concentrations rebounded with a dose-dependent overshoot compared to baseline levels. Cumulative change of ARGS concentration from baseline to week 52 had no effect on change in cartilage thickness (slope -0.8x10-6 [-2.9x10-6, 1.3x10-6]) or change in WOMAC pain and function (slopes -30x10-6 [-64x10-6, 5.2x10-6] and -97x10-6 [-214x10-6, 20x10-6], respectively) at week 52. CONCLUSION: Systemic inhibition of ADAMTS-5 resulted in markedly reduced serum ARGS, but change in serum ARGS concentrations showed no association with the progression of cartilage thinning, or patient reported pain and function. CLINICALTRIALS: GOV: NCT03595618.

Development and validation of a machine learning-supported strategy of patient selection for osteoarthritis clinical trials: the IMI-APPROACH study.

Objectives: To efficiently assess the disease-modifying potential of new osteoarthritis treatments, clinical trials need progression-enriched patient populations. To assess whether the application of machine learning results in patient selection enrichment, we developed a machine learning recruitment strategy targeting progressive patients and validated it in the IMI-APPROACH knee osteoarthritis prospective study. Design: We designed a two-stage recruitment process supported by machine learning models trained to rank candidates by the likelihood of progression. First stage models used data from pre-existing cohorts to select patients for a screening visit. The second stage model used screening data to inform the final inclusion. The effectiveness of this process was evaluated using the actual 24-month progression. Results: From 3500 candidate patients, 433 with knee osteoarthritis were screened, 297 were enrolled, and 247 completed the 2-year follow-up visit. We observed progression related to pain (P, 30%), structure (S, 13%), and combined pain and structure (P â€‹+ â€‹S, 5%), and a proportion of non-progressors (N, 52%) ∼15% lower vs an unenriched population. Our model predicted these outcomes with AUC of 0.86 [95% CI, 0.81-0.90] for pain-related progression and AUC of 0.61 [95% CI, 0.52-0.70] for structure-related progression. Progressors were ranked higher than non-progressors for P â€‹+ â€‹S (median rank 65 vs 143, AUC = 0.75), P (median rank 77 vs 143, AUC = 0.71), and S patients (median rank 107 vs 143, AUC = 0.57). Conclusions: The machine learning-supported recruitment resulted in enriched selection of progressive patients. Further research is needed to improve structural progression prediction and assess this strategy in an interventional trial.

Quantitative CT of the knee in the IMI-APPROACH osteoarthritis cohort: Association of bone mineral density with radiographic disease severity, meniscal coverage and meniscal extrusion.

OBJECTIVE: Osteoarthritis (OA) is a highly prevalent chronic condition. The subchondral bone plays an important role in onset and progression of OA making it a potential treatment target for disease-modifying therapeutic approaches. However, little is known about changes of periarticular bone mineral density (BMD) in OA and its relation to meniscal coverage and meniscal extrusion at the knee. Thus, the aim of this study was to describe periarticular BMD in the Applied Public-Private Research enabling OsteoArthritis Clinical Headway (APPROACH) cohort at the knee and to analyze the association with structural disease severity, meniscal coverage and meniscal extrusion. DESIGN: Quantitative CT (QCT), MRI and radiographic examinations were acquired in 275 patients with knee osteoarthritis (OA). QCT was used to assess BMD at the femur and tibia, at the cortical bone plate (Cort) and at the epiphysis at three locations: subchondral (Sub), mid-epiphysis (Mid) and adjacent to the physis (Juxta). BMD was evaluated for the medial and lateral compartment separately and for subregions covered and not covered by the meniscus. Radiographs were used to determine the femorotibial angle and were evaluated according to the Kellgren and Lawrence (KL) system. Meniscal extrusion was assessed from 0 to 3. RESULTS: Mean BMD differed significantly between each anatomic location at both the femur and tibia (p < 0.001) in patients with KL0. Tibial regions assumed to be covered with meniscus in patients with KL0 showed lower BMD at Sub (p < 0.001), equivalent BMD at Mid (p = 0.07) and higher BMD at Juxta (p < 0.001) subregions compared to regions not covered with meniscus. Knees with KL2-4 showed lower Sub (p = 0.03), Mid (p = 0.01) and Juxta (p < 0.05) BMD at the medial femur compared to KL0/1. Meniscal extrusion grade 2 and 3 was associated with greater BMD at the tibial Cort (p < 0.001, p = 0.007). Varus malalignment is associated with significant greater BMD at the medial femur and at the medial tibia at all anatomic locations. CONCLUSION: BMD within the epiphyses of the tibia and femur decreases with increasing distance from the articular surface. Knees with structural OA (KL2-4) exhibit greater cortical BMD values at the tibia and lower BMD at the femur at the subchondral level and levels beneath compared to KL0/1. BMD at the tibial cortical bone plate is greater in patients with meniscal extrusion grade 2/3.

Structural tissue damage and 24-month progression of semi-quantitative MRI biomarkers of knee osteoarthritis in the IMI-APPROACH cohort.

BACKGROUND: The IMI-APPROACH cohort is an exploratory, 5-centre, 2-year prospective follow-up study of knee osteoarthritis (OA). Aim was to describe baseline multi-tissue semiquantitative MRI evaluation of index knees and to describe change for different MRI features based on number of subregion-approaches and change in maximum grades over a 24-month period. METHODS: MRIs were acquired using 1.5 T or 3 T MRI systems and assessed using the semi-quantitative MRI OA Knee Scoring (MOAKS) system. MRIs were read at baseline and 24-months for cartilage damage, bone marrow lesions (BML), osteophytes, meniscal damage and extrusion, and Hoffa- and effusion-synovitis. In descriptive fashion, the frequencies of MRI features at baseline and change in these imaging biomarkers over time are presented for the entire sample in a subregional and maximum score approach for most features. Differences between knees without and with structural radiographic (R) OA are analyzed in addition. RESULTS: Two hundred eighty-nine participants had readable baseline MRI examinations. Mean age was 66.6 ± 7.1 years and participants had a mean BMI of 28.1 ± 5.3 kg/m2. The majority (55.3%) of included knees had radiographic OA. Any change in total cartilage MOAKS score was observed in 53.1% considering full-grade changes only, and in 73.9% including full-grade and within-grade changes. Any medial cartilage progression was seen in 23.9% and any lateral progression on 22.1%. While for the medial and lateral compartments numbers of subregions with improvement and worsening of BMLs were very similar, for the PFJ more improvement was observed compared to worsening (15.5% vs. 9.0%). Including within grade changes, the number of knees showing BML worsening increased from 42.2% to 55.6%. While for some features 24-months change was rare, frequency of change was much more common in knees with vs. without ROA (e.g. worsening of total MOAKS score cartilage in 68.4% of ROA knees vs. 36.7% of no-ROA knees, and 60.7% vs. 21.8% for an increase in maximum BML score per knee). CONCLUSIONS: A wide range of MRI-detected structural pathologies was present in the IMI-APPROACH cohort. Baseline prevalence and change of features was substantially more common in the ROA subgroup compared to the knees without ROA. TRIAL REGISTRATION: Clinicaltrials.gov identification: NCT03883568.

Predicted and actual 2-year structural and pain progression in the IMI-APPROACH knee osteoarthritis cohort.

OBJECTIVES: The IMI-APPROACH knee osteoarthritis study used machine learning (ML) to predict structural and/or pain progression, expressed by a structural (S) and pain (P) predicted-progression score, to select patients from existing cohorts. This study evaluates the actual 2-year progression within the IMI-APPROACH, in relation to the predicted-progression scores. METHODS: Actual structural progression was measured using minimum joint space width (minJSW). Actual pain (progression) was evaluated using the Knee injury and Osteoarthritis Outcomes Score (KOOS) pain questionnaire. Progression was presented as actual change (Δ) after 2 years, and as progression over 2 years based on a per patient fitted regression line using 0, 0.5, 1 and 2-year values. Differences in predicted-progression scores between actual progressors and non-progressors were evaluated. Receiver operating characteristic (ROC) curves were constructed and corresponding area under the curve (AUC) reported. Using Youden's index, optimal cut-offs were chosen to enable evaluation of both predicted-progression scores to identify actual progressors. RESULTS: Actual structural progressors were initially assigned higher S predicted-progression scores compared with structural non-progressors. Likewise, actual pain progressors were assigned higher P predicted-progression scores compared with pain non-progressors. The AUC-ROC for the S predicted-progression score to identify actual structural progressors was poor (0.612 and 0.599 for Δ and regression minJSW, respectively). The AUC-ROC for the P predicted-progression score to identify actual pain progressors were good (0.817 and 0.830 for Δ and regression KOOS pain, respectively). CONCLUSION: The S and P predicted-progression scores as provided by the ML models developed and used for the selection of IMI-APPROACH patients were to some degree able to distinguish between actual progressors and non-progressors. TRIAL REGISTRATION: ClinicalTrials.gov, https://clinicaltrials.gov, NCT03883568.

Safety, Pharmacokinetics, and Pharmacodynamics of the ADAMTS-5 Inhibitor GLPG1972/S201086 in Healthy Volunteers and Participants With Osteoarthritis of the Knee or Hip.

GLPG1972/S201086 is a disintegrin and metalloproteinase with thrombospondin motif-5 (ADAMTS-5) inhibitor in development as an osteoarthritis disease-modifying therapy. We report the safety, tolerability, pharmacokinetics, and pharmacodynamics (turnover of plasma/serum ARGS-aggrecan neoepitope fragments [ARGS]) of GLPG1972 in 3 randomized, double-blind, placebo-controlled phase 1 trials. Study A, a first-in-human trial of single (≤2100 mg [fasted] and 300 mg [fed]) and multiple (≤1050 mg once daily [fed]; 14 days) ascending oral (solution) doses, investigated GLPG1972 in healthy men (N = 41; NCT02612246). Study B investigated multiple ascending oral (tablet) doses of GLPG1972 (≤300 mg once daily [fed]; 4 weeks) in male and female participants with osteoarthritis (N = 30; NCT03311009). Study C investigated single (Japanese: ≤1500 mg; White: 300 mg [fasted]) and multiple (Japanese, ≤1050 mg once daily; White, 300 mg once daily [fed]; 14 days) ascending oral (tablet) doses of GLPG1972 in healthy Japanese and White men (N = 88). The pharmacokinetic profile of GLPG1972 was similar between healthy participants and participants with osteoarthritis, with low to moderate interindividual variability. GLPG1972 was rapidly absorbed (median time to maximum concentration, 4 hours), and eliminated with a mean apparent terminal elimination half-life of ≈10 hours. Steady state was achieved within 2 days of dosing, with minimal accumulation. Steady-state plasma exposure after 300 mg of GLPG1972 showed no or minor differences between populations. Area under the plasma concentration-time curve (56.8-67.6 µg · h/mL) and time to maximum concentration (4 hours) were similar between studies. Urinary excretion of GLPG1972 (24 hours) was low (<11%). Multiple dosing significantly reduced ARGS levels vs baseline at all time points for all doses vs placebo. GLPG1972 was generally well tolerated at all doses.

Neuropathic pain in the IMI-APPROACH knee osteoarthritis cohort: prevalence and phenotyping.

OBJECTIVES: Osteoarthritis (OA) patients with a neuropathic pain (NP) component may represent a specific phenotype. This study compares joint damage, pain and functional disability between knee OA patients with a likely NP component, and those without a likely NP component. METHODS: Baseline data from the Innovative Medicines Initiative Applied Public-Private Research enabling OsteoArthritis Clinical Headway knee OA cohort study were used. Patients with a painDETECT score ≥19 (with likely NP component, n=24) were matched on a 1:2 ratio to patients with a painDETECT score ≤12 (without likely NP component), and similar knee and general pain (Knee Injury and Osteoarthritis Outcome Score pain and Short Form 36 pain). Pain, physical function and radiographic joint damage of multiple joints were determined and compared between OA patients with and without a likely NP component. RESULTS: OA patients with painDETECT scores ≥19 had statistically significant less radiographic joint damage (p≤0.04 for Knee Images Digital Analysis parameters and Kellgren and Lawrence grade), but an impaired physical function (p<0.003 for all tests) compared with patients with a painDETECT score ≤12. In addition, more severe pain was found in joints other than the index knee (p≤0.001 for hips and hands), while joint damage throughout the body was not different. CONCLUSIONS: OA patients with a likely NP component, as determined with the painDETECT questionnaire, may represent a specific OA phenotype, where local and overall joint damage is not the main cause of pain and disability. Patients with this NP component will likely not benefit from general pain medication and/or disease-modifying OA drug (DMOAD) therapy. Reserved inclusion of these patients in DMOAD trials is advised in the quest for successful OA treatments.Trial registration numberThe study is registered under clinicaltrials.gov nr: NCT03883568.

A deep learning method for predicting knee osteoarthritis radiographic progression from MRI.

BACKGROUND: The identification of patients with knee osteoarthritis (OA) likely to progress rapidly in terms of structure is critical to facilitate the development of disease-modifying drugs. METHODS: Using 9280 knee magnetic resonance (MR) images (3268 patients) from the Osteoarthritis Initiative (OAI) database , we implemented a deep learning method to predict, from MR images and clinical variables including body mass index (BMI), further cartilage degradation measured by joint space narrowing at 12 months. RESULTS: Using COR IW TSE images, our classification model achieved a ROC AUC score of 65%. On a similar task, trained radiologists obtained a ROC AUC score of 58.7% highlighting the difficulty of the classification task. Additional analyses conducted in parallel to predict pain grade evaluated by the WOMAC pain index achieved a ROC AUC score of 72%. Attention maps provided evidence for distinct specific areas as being relevant in those two predictive models, including the medial joint space for JSN progression and the intra-articular space for pain prediction. CONCLUSIONS: This feasibility study demonstrates the interest of deep learning applied to OA, with a potential to support even trained radiologists in the challenging task of identifying patients with a high-risk of disease progression.

Applications of transcriptomics in support of drug development for osteoarthritis.

Objective: Understanding the heterogeneity and pathophysiology of osteoarthritis (OA) is critical to support the development of tailored disease-modifying treatments. To this aim, transcriptomics tools are highly relevant to delineate dysregulated molecular pathways and identify new therapeutic targets. Methods: We review the methodology and outcomes of transcriptomics studies conducted in OA, based on a comprehensive literature search of the PubMed and Google Scholar databases using the terms "osteoarthritis", "OA", "knee OA", "hip OA", "genes", "RNA-seq", "microarray", "transcriptomic" and "PCR" as key words. Beyond target-focused RT-qPCR, more comprehensive techniques include microarrays, RNA sequencing (RNA-seq) and single cell RNA-seq analyses. Results: The standardization of those methods to ensure the quality of both RNA extraction and sequencing is critical to get meaningful insights. Transcriptomics studies have been conducted in various tissues involved in the pathogenesis of OA, including articular cartilage, subchondral bone and synovium, as well as in the blood of patients. Molecular pathways dysregulated in OA relate to cartilage degradation, matrix and bone remodeling, neurogenic pain, inflammation, apoptosis and angiogenesis. This knowledge has direct application to patient stratification and further, to the identification of candidate therapeutic targets and biomarkers intended to monitor OA progression. Conclusion: In light of its high-throughput capabilities and ability to provide comprehensive information on major biological processes, transcriptomics represents a powerful method to support the development of new disease-modifying drugs in OA.

A simple inclusion criteria combination increases the rate of cartilage loss in patients with knee osteoarthritis.

Objectives: Selection of patients with KL radiographic grade 2 and 3 is widely used in clinical trials, but this approach could have some limitations. The purpose of this study performed on OsteoArthritis Initiative (OAI) data is to assess whether adding OARSI-JSN to KL grading could select a population with increased rate of cartilage loss. Indeed, KL is not compartment-specific and not uniformly graded amongst expert readers. OARSI-JSN is another established, compartment-specific grading scale that specifically captures the joint space narrowing from radiographs. Design: 1019 knee radiographs data from the progression cohort of the OAI public database were used. Cartilage loss measured with magnetic resonance imaging was evaluated using change over 1 year from baseline in cartilage thickness in the central Medial Tibio-Femoral Compartment (cMTFC) in the KL2-3 and KL2-3+JSN1-2 populations. Results: The mean cMTFC cartilage loss over one year was -0.135 â€‹± â€‹0.29 â€‹mm (median â€‹= â€‹-0.095 â€‹mm) in the KL2-3 population and -0.176 â€‹± â€‹0.29 â€‹mm (median â€‹= â€‹-0.140 â€‹mm) in the KL2-3 +JSN1-2 population. Conclusions: OARSI-JSN appears to be an effective inclusion criterion to be considered in combination with the KL grade in future clinical trials testing the structural efficacy of DMOADs in a time window of 1-year as it contributes to identify knees in whom the disease progresses rapidly.

Cohort profile: The Applied Public-Private Research enabling OsteoArthritis Clinical Headway (IMI-APPROACH) study: a 2-year, European, cohort study to describe, validate and predict phenotypes of osteoarthritis using clinical, imaging and biochemical markers.

PURPOSE: The Applied Public-Private Research enabling OsteoArthritis Clinical Headway (APPROACH) consortium intends to prospectively describe in detail, preselected patients with knee osteoarthritis (OA), using conventional and novel clinical, imaging, and biochemical markers, to support OA drug development. PARTICIPANTS: APPROACH is a prospective cohort study including 297 patients with tibiofemoral OA, according to the American College of Rheumatology classification criteria. Patients were (pre)selected from existing cohorts using machine learning models, developed on data from the CHECK cohort, to display a high likelihood of radiographic joint space width (JSW) loss and/or knee pain progression. FINDINGS TO DATE: Selection appeared logistically feasible and baseline characteristics of the cohort demonstrated an OA population with more severe disease: age 66.5 (SD 7.1) vs 68.1 (7.7) years, min-JSW 2.5 (1.3) vs 2.1 (1.0) mm and Knee injury and Osteoarthritis Outcome Score pain 31.3 (19.7) vs 17.7 (14.6), except for age, all: p<0.001, for selected versus excluded patients, respectively. Based on the selection model, this cohort has a predicted higher chance of progression. FUTURE PLANS: Patients will visit the hospital again at 6, 12 and 24 months for physical examination, pain and general health questionnaires, collection of blood and urine, MRI scans, radiographs of knees and hands, CT scan of the knee, low radiation whole-body CT, HandScan, motion analysis and performance-based tests.After two years, data will show whether those patients with the highest probabilities for progression experienced disease progression as compared to those wit lower probabilities (model validation) and whether phenotypes/endotypes can be identified and predicted to facilitate targeted drug therapy. TRIAL REGISTRATION NUMBER: NCT03883568.

Long-term strontium ranelate administration in monkeys preserves characteristics of bone mineral crystals and degree of mineralization of bone.

UNLABELLED: In monkeys, long-term strontium ranelate administration results in a dose-dependent bone strontium uptake (mainly into newly formed bone) that preserves the degree of mineralization of bone and the bone mineral at the crystal level, showing its safety at bone mineral level. INTRODUCTION: Strontium ranelate simultaneously increases bone formation and decreases bone resorption, leading to prevention of bone loss and increase in bone mass and bone strength in normal and ovariectomized rats. This study investigated the interactions of stable strontium (Sr) with bone mineral in monkeys after long-term strontium ranelate treatment and after a period of treatment withdrawal. MATERIALS AND METHODS: Iliac bone was obtained from untreated monkeys, monkeys at the end of a 52-week strontium ranelate administration (200, 500, 1250 mg/kg/day orally), and in parallel groups 10 weeks after the end of strontium ranelate administration (same three doses; n = 3-7). Sr uptake and distribution in bone mineral were quantified by X-ray microanalysis, changes at the crystal level by X-ray diffraction, and the degree of mineralization of bone (DMB) by quantitative microradiography. RESULTS: After strontium ranelate administration, dose-dependent Sr uptake occurred into cortical and cancellous bone, with higher content (1.6 times) in new than in old bone. This Sr uptake decreased (50%) 10 weeks after treatment withdrawal; the decrease occurred almost exclusively in new bone. At the end of strontium ranelate treatment and after its withdrawal, a preservation of crystal characteristics was observed, suggesting that Sr was only faintly linked to crystals by ionic substitution and of DMB. CONCLUSIONS: These results show the absence of a deleterious effect of long-term strontium ranelate treatment on bone mineralization, confirming the histomorphometric observations made in postmenopausal osteoporotic women treated with strontium ranelate.