Towards Personalized Treatment in Haemophilia: The Role of Genetic Factors in Iron and Heme Control to Identify Patients at Risk for Haemophilic Arthropathy.

The treatment landscape for haemophilia is changing rapidly, creating opportunities for personalized treatment. As major morbidity is still caused by haemophilic arthropathy, understanding the factors affecting joint damage and joint damage progression might lead to more individualized treatment regimens. We investigated the association of HFE mutations or HMOX1 polymorphisms affecting iron/heme handling with radiographic joint damage in 252 haemophilia patients (severe and moderate). Although iron levels and transferrin saturation were significantly increased in the 95 patients with an HFE mutation, neither carrying this mutation nor the HMOX1 polymorphism was associated with radiographic joint damage, and the same was true after adjustment for well-known factors associated with arthropathy. In conclusion, this study does not support the hypothesis that HFE mutations or HMOX1 polymorphisms can be used to predict the development of haemophilic arthropathy.

Myostatin and CXCL11 promote nervous tissue macrophages to maintain osteoarthritis pain.

Pain is the most debilitating symptom of knee osteoarthritis (OA) that can even persist after total knee replacement. The severity and duration of pain do not correlate well with joint tissue alterations, suggesting other mechanisms may drive pain persistence in OA. Previous work identified that macrophages accumulate in the dorsal root ganglia (DRG) containing the somas of sensory neurons innervating the injured knee joint in a mouse OA model and acquire a M1-like phenotype to maintain pain. Here we aimed to unravel the mechanisms that govern DRG macrophage accumulation and programming. The accumulation of F4/80+iNOS+ (M1-like) DRG macrophages was detectable at day 3 after mono-iodoacetate (MIA)-induced OA in the mouse. Depletion of macrophages prior to induction of OA resolved pain-like behaviors by day 7 without affecting the initial development of pain-like behaviors. Analysis of DRG transcript identified CXCL11 and myostatin. CXCL11 and myostatin were increased at 3 weeks post OA induction, with CXCL11 expression partially localized in satellite glial cells and myostatin in sensory neurons. Blocking CXCL11 or myostatin prevented the persistence of OA pain, without affecting the initiation of pain. CXCL11 neutralization reduced the number of total and F4/80+iNOS+ DRG macrophages, whilst myostatin inhibition diminished the programming of F4/80+iNOS+ DRG macrophages. Intrathecal injection of recombinant CXCL11 did not induce pain-associated behaviors. In contrast, intrathecal myostatin increased the number of F4/80+iNOS+ DRG macrophages concurrent with the development of mechanical hypersensitivity that was prevented by macrophages depletion or CXCL11 blockade. Finally, myostatin inhibition during established OA, resolved pain and F4/80+iNOS+ macrophage accumulation in the DRG. In conclusion, DRG macrophages maintain OA pain, but are not required for the induction of OA pain. Myostatin is a key ligand in neuro-immune communication that drives the persistence of pain in OA through nervous tissue macrophages and represent a novel therapeutic target for the treatment of OA pain.

Subclinical synovial proliferation in patients with severe haemophilia A: The value of ultrasound screening and biochemical markers.

AIM: Subclinical bleeding and inflammation play a role in progression of haemophilic arthropathy. Synovial proliferation is predictive of joint bleeding and its early detection may guide treatment changes and prevent arthropathy progression. This study evaluated the prevalence of active and inactive subclinical synovial proliferation and investigated potential biochemical blood/urine markers to identify patients with active subclinical synovial proliferation. METHODS: This cross-sectional study included patients with severe haemophilia A born 1970-2006 who were evaluated during routine clinic visits. Patients with (a history of) inhibitors or recent joint bleeding were excluded. Elbows, knees and ankles were examined for subclinical synovial proliferation by ultrasound and physical examination. Active synovial proliferation was distinguished from inactive synovial proliferation using predefined criteria. Blood/urine biochemical markers (serum osteopontin, sVCAM-1, Coll2-1, COMP, CS846, TIMP, and urinary CTX-II) were compared individually and as combined indexes between patients with and without active synovial proliferation. RESULTS: This cohort consisted of 79 patients with a median age of 31 years (range 16.5-50.8 years) with 62/79 (78%) of the patients using continuous prophylaxis. The annualized joint bleeding rate over the last 5 years was .6 (.2-1.1). Active (17/79, 22%) and inactive subclinical synovial proliferation (17/79, 22%) were both prevalent in this cohort. Biochemical markers were not correlated with active subclinical synovial proliferation. CONCLUSION: Subclinical synovial proliferation, both active and inactive, was prevalent in patients with severe haemophilia A with access to prophylaxis and would be overlooked without routinely performed ultrasounds. Biochemical markers were unable to identify patients with active subclinical synovial proliferation.

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.

CCR9/CXCR5 Co-Expressing CD4 T Cells Are Increased in Primary Sjögren's Syndrome and Are Enriched in PD-1/ICOS-Expressing Effector T Cells.

Primary Sjögren's syndrome (pSS) is an autoimmune disease characterised by B cell hyperactivity. CXCR5+ follicular helper T cells (Tfh), CXCR5-PD-1hi peripheral helper T cells (Tph) and CCR9+ Tfh-like cells have been implicated in driving B cell hyperactivity in pSS; however, their potential overlap has not been evaluated. Our aim was to study the overlap between the two CXCR5- cell subsets and to study their PD-1/ICOS expression compared to "true" CXCR5/PD-1/ICOS-expressing Tfh cells. CXCR5- Tph and CCR9+ Tfh-like cell populations from peripheral blood mononuclear cells of pSS patients and healthy controls (HC) were compared using flow cytometry. PD-1/ICOS expression from these cell subsets was compared to each other and to CXCR5+ Tfh cells, taking into account their differentiation status. CXCR5- Tph cells and CCR9+ Tfh-like cells, both in pSS patients and HC, showed limited overlap. PD-1/ICOS expression was higher in memory cells expressing CXCR5 or CCR9. However, the highest expression was found in CXCR5/CCR9 co-expressing T cells, which are enriched in the circulation of pSS patients. CXCR5- Tph and CCR9+ Tfh-like cells are two distinct cell populations that both are enriched in pSS patients and can drive B cell hyperactivity in pSS. The known upregulated expression of CCL25 and CXCL13, ligands of CCR9 and CXCR5, at pSS inflammatory sites suggests concerted action to facilitate the migration of CXCR5+CCR9+ T cells, which are characterised by the highest frequencies of PD-1/ICOS-positive cells. Hence, these co-expressing effector T cells may significantly contribute to the ongoing immune responses in pSS.

Identifying multivariate disease trajectories and potential phenotypes of early knee osteoarthritis in the CHECK cohort.

OBJECTIVE: To gain better understanding of osteoarthritis (OA) heterogeneity and its predictors for distinguishing OA phenotypes. This could provide the opportunity to tailor prevention and treatment strategies and thus improve care. DESIGN: Ten year follow-up data from CHECK (1002 early-OA subjects with first general practitioner visit for complaints ≤6 months before inclusion) was used. Data were collected on WOMAC (pain, function, stiffness), quantitative radiographic tibiofemoral (TF) OA characteristics, and semi-quantitative radiographic patellofemoral (PF) OA characteristics. Using functional data analysis, distinctive sets of trajectories were identified for WOMAC, TF and PF characteristics, based on model fit and clinical interpretation. The probabilities of knee membership to each trajectory were used in hierarchical cluster analyses to derive knee OA phenotypes. The number and composition of potential phenotypes was selected again based on model fit (silhouette score) and clinical interpretation. RESULTS: Five trajectories representing different constant levels or changing WOMAC scores were identified. For TF and PF OA, eight and six trajectories respectively were identified based on (changes in) joint space narrowing, osteophytes and sclerosis. Combining the probabilities of knees belonging to these different trajectories resulted in six clusters ('phenotypes') of knees with different degrees of functional (WOMAC) and radiographic (PF) parameters; TF parameters were found not to significantly contribute to clustering. Including baseline characteristics as well resulted in eight clusters of knees, dominated by sex, menopausal status and WOMAC scores, with only limited contribution of PF features. CONCLUSIONS: Several stable and progressive trajectories of OA symptoms and radiographic features were identified, resulting in phenotypes with relatively independent symptomatic and radiographic features. Sex and menopausal status may be especially important when phenotyping knee OA patients, while radiographic features contributed less. Possible phenotypes were identified that, after validation, could aid personalized treatments and patients selection.

Machine-learning predicted and actual 2-year structural progression in the IMI-APPROACH cohort.

In the Innovative Medicine's Initiative Applied Public-Private Research enabling OsteoArthritis Clinical Headway (IMI-APPROACH) knee osteoarthritis (OA) study, machine learning models were trained to predict the probability of structural progression (s-score), predefined as >0.3 mm/year joint space width (JSW) decrease and used as inclusion criterion. The current objective was to evaluate predicted and observed structural progression over 2 years according to different radiographic and magnetic resonance imaging (MRI)-based structural parameters. Radiographs and MRI scans were acquired at baseline and 2-year follow-up. Radiographic (JSW, subchondral bone density, osteophytes), MRI quantitative (cartilage thickness), and MRI semiquantitative [SQ; cartilage damage, bone marrow lesions (BMLs), osteophytes] measurements were obtained. The number of progressors was calculated based on a change exceeding the smallest detectable change (SDC) for quantitative measures or a full SQ-score increase in any feature. Prediction of structural progression based on baseline s-scores and Kellgren-Lawrence (KL) grades was analyzed using logistic regression. Among 237 participants, around 1 in 6 participants was a structural progressor based on the predefined JSW-threshold. The highest progression rate was seen for radiographic bone density (39%), MRI cartilage thickness (38%), and radiographic osteophyte size (35%). Baseline s-scores could only predict JSW progression parameters (most P>0.05), while KL grades could predict progression of most MRI-based and radiographic parameters (P<0.05). In conclusion, between 1/6 and 1/3 of participants showed structural progression during 2-year follow-up. KL scores were observed to outperform the machine-learning-based s-scores as progression predictor. The large amount of data collected, and the wide range of disease stage, can be used for further development of more sensitive and successful (whole joint) prediction models. Trial Registration: Clinicaltrials.gov number NCT03883568.

Structural changes after ankle joint distraction in haemophilic arthropathy: an explorative study investigating biochemical markers and 3D joint space width.

INTRODUCTION: Ankle joint distraction (AJD) is a promising treatment for patients with severe haemophilic ankle arthropathy (HAA). However, some patients showed no clinical improvement after AJD and these differences may be related to structural differences. AIM: Primarily to quantify the structural changes after AJD in patients with HAA by the use of 3D joint space width (JSW) measurements and biochemical markers and secondarily to correlate these findings with clinical pain/function. METHODS: Patients with haemophilia A/B who underwent AJD were included for this study. Bone contours on MRI (performed before and 12 and 36 months after AJD) were drawn manually and percentage change in JSW was calculated. Blood/urine (before and 6, 12, 24 and 36 months after AJD) was collected for biomarker measurement (COMP, CS846, C10C, CALC2, PRO-C2, CTX-II) and combined indexes of markers were calculated. Mixed effects models were used for analyses on group level. Structural changes were compared with clinical parameters. RESULTS: Eight patients were evaluated. On group level, percentage changes in JSW showed a slight decrease after 12 months followed by a non-statistically significant increase in JSW after 36 months compared to baseline. Biochemical marker collagen/cartilage formation also showed an initial decrease, followed by a trend towards net formation 12, 24 and 36 months after AJD. On individual patient level, no clear correlations between structural changes and clinical parameters were observed. CONCLUSION: Cartilage restoration activity on group level in patients with HAA after AJD was in concordance with clinical improvements. Correlating structural modifications with clinical parameters in the individual patient remains difficult.

Exploring the differences between radiographic joint space width and MRI cartilage thickness changes using data from the IMI-APPROACH cohort.

OBJECTIVE: Longitudinal weight-bearing radiographic joint space width (JSW) and non-weight-bearing MRI-based cartilage thickness changes often show weak correlations. The current objective was to investigate these correlations, and to explore the influence of different factors that could contribute to longitudinal differences between the two methods. METHODS: The current study included 178 participants with medial osteoarthritis (OA) out of the 297 knee OA participants enrolled in the IMI-APPROACH cohort. Changes over 2 years in medial JSW (ΔJSWmed), minimum JSW (ΔJSWmin), and medial femorotibial cartilage thickness (ΔMFTC) were assessed using linear regression, using measurements from radiographs and MRI acquired at baseline, 6 months, and 1 and 2 years. Pearson R correlations were calculated. The influence of cartilage quality (T2 mapping), meniscal extrusion (MOAKS scoring), potential pain-induced unloading (difference in knee-specific pain scores), and increased loading (BMI) on the correlations was analyzed by dividing participants in groups based on each factor separately, and comparing correlations (slope and strength) between groups using linear regression models. RESULT: Correlations between ΔMFTC and ΔJSWmed and ΔJSWmin were statistically significant (p < 0.004) but weak (R < 0.35). Correlations were significantly different between groups based on cartilage quality and on meniscal extrusion: only patients with the lowest T2 values and with meniscal extrusion showed significant moderate correlations. Pain-induced unloading or BMI-induced loading did not influence correlations. CONCLUSIONS: While the amount of loading does not seem to make a difference, weight-bearing radiographic JSW changes are a better reflection of non-weight-bearing MRI cartilage thickness changes in knees with higher quality cartilage and with meniscal extrusion.

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.

TOFA-PREDICT study protocol: a stratification trial to determine key immunological factors predicting tofacitinib efficacy and drug-free remission in psoriatic arthritis (PsA).

INTRODUCTION: Psoriatic arthritis (PsA) is a chronic, inflammatory, musculoskeletal disease that affects up to 30% of patients with psoriasis. Current challenges in clinical care and research include personalised treatment, understanding the divergence of therapy response and unravelling the multifactorial pathophysiology of this complex disease. Moreover, there is an urgent clinical need to predict, assess and understand the cellular and molecular pathways underlying the response to disease-modifying antirheumatic drugs (DMARDs). The TOFA-PREDICT clinical trial addresses this need. Our primary objective is to determine key immunological factors predicting tofacitinib efficacy and drug-free remission in PsA. METHODS AND ANALYSIS: In this investigator-initiated, phase III, multicentre, open-label, four-arm randomised controlled trial, we plan to integrate clinical, molecular and imaging parameters of 160 patients with PsA. DMARD-naïve patients are randomised to methotrexate or tofacitinib. Additionally, patients who are non-responsive to conventional synthetic (cs)DMARDs continue their current csDMARD and are randomised to etanercept or tofacitinib. This results in four arms each with 40 patients. Patients are followed for 1 year. Treatment response is defined as minimal disease activity at week 16. Clinical data, biosamples and images are collected at baseline, 4 weeks and 16 weeks; at treatment failure (treatment switch) and 52 weeks. For the first 80 patients, we will use a systems medicine approach to assess multiomics biomarkers and develop a prediction model for treatment response. Subsequently, data from the second 80 patients will be used for validation. ETHICS AND DISSEMINATION: The study was approved by the Medical Research Ethics Committee in Utrecht, Netherlands, is registered in the European Clinical Trials Database and is carried out in accordance with the Declaration of Helsinki. The study's progress is monitored by Julius Clinical, a science-driven contract research organisation. TRIAL REGISTRATION NUMBER: EudraCT: 2017-003900-28.

Ankle joint distraction is a promising alternative treatment for patients with severe haemophilic ankle arthropathy.

INTRODUCTION: Haemophilic ankle arthropathy (HAA) causes major morbidity. When conservative treatment fails, major surgical interventions are indicated. An alternative treatment to maintain joint mobility and postpone these interventions is desired. AIM: To gather prospective data on clinical/structural changes after ankle joint distraction (AJD) in HAA. METHODS: This study includes patients with severe HAA insufficiently responding to conservative treatment. AJD was performed during 8-10 weeks by use of an external frame. Questionnaires, physical examination and radiology were used to evaluate pain, function and structural changes before and 6, 12, 24 and 36 months after distraction. Mixed effect models were used for analysis. RESULTS: This study includes eight cases (21-53 years). The fixed effects estimates of the visual analogue score (0-10) improved from 7.5 at baseline to 3.4 (p = .023) 3 years after distraction. The Haemophilia Activities List (HAL, 0-100) for basic/complex lower extremities functions improved from respectively 29.6 and 31.5 to 54.3 (p = .015) and 50.7 (p = .031). Joint mobility was maintained. Magnetic resonance imaging (MRI) showed thickened cartilage and reduced bone marrow oedema and subchondral cysts. Pin tract infections (n = 6) were effectively treated and no adverse bleeding events occurred. At 3-year follow-up, in none of the patients the originally indicated arthrodesis was performed. CONCLUSION: This first prospective study showed that AJD in HAA results in decreased pain, improved function and decreased arthropathy-related MRI findings in the majority of patients for prolonged time. Although the study population is small and follow-up is relatively short, AJD may be promising to postpone invalidating interventions and might be a breakthrough treatment.

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.

GaitSmart motion analysis compared to commonly used function outcome measures in the IMI-APPROACH knee osteoarthritis cohort.

BACKGROUND: There are multiple measures for assessment of physical function in knee osteoarthritis (OA), but each has its strengths and limitations. The GaitSmart® system, which uses inertial measurement units (IMUs), might be a user-friendly and objective method to assess function. This study evaluates the validity and responsiveness of GaitSmart® motion analysis as a function measurement in knee OA and compares this to Knee Injury and Osteoarthritis Outcome Score (KOOS), Short Form 36 Health Survey (SF-36), 30s chair stand test, and 40m self-paced walk test. METHODS: The 2-year Innovative Medicines Initiative-Applied Public-Private Research enabling OsteoArthritis Clinical Headway (IMI-APPROACH) knee OA cohort was conducted between January 2018 and April 2021. For this study, available baseline and 6 months follow-up data (n = 262) was used. Principal component analysis was used to investigate whether above mentioned function instruments could represent one or more function domains. Subsequently, linear regression was used to explore the association between GaitSmart® parameters and those function domains. In addition, standardized response means, effect sizes and t-tests were calculated to evaluate the ability of GaitSmart® to differentiate between good and poor general health (based on SF-36). Lastly, the responsiveness of GaitSmart® to detect changes in function was determined. RESULTS: KOOS, SF-36, 30s chair test and 40m self-paced walk test were first combined into one function domain (total function). Thereafter, two function domains were substracted related to either performance based (objective function) or self-reported (subjective function) function. Linear regression resulted in the highest R2 for the total function domain: 0.314 (R2 for objective and subjective function were 0.252 and 0.142, respectively.). Furthermore, GaitSmart® was able to distinguish a difference in general health status, and is responsive to changes in the different aspects of objective function (Standardized response mean (SRMs) up to 0.74). CONCLUSION: GaitSmart® analysis can reflect performance based and self-reported function and may be of value in the evaluation of function in knee OA. Future studies are warranted to validate whether GaitSmart® can be used as clinical outcome measure in OA research and clinical practice.

Classification of rheumatoid arthritis into active or inactive with a modified Disease Activity score, for future use as a treat-to-target tool, with a HandScan score replacing joint counts.

OBJECTIVES: To establish the value of a modified Disease Activity score with Optical Spectral Transmission score (DAS-OST) without joint counts but with a HandScan score, versus that of DAS28, to classify rheumatoid arthritis (RA) as active versus inactive, with as reference standard the rheumatologist's clinical classification. METHODS: RA patients with at least one HandScan and DAS28 measurement performed at the same visit were included. Data was extracted from medical records, as was the clinical interpretation as active or inactive RA by the rheumatologist. Logistic regression analyses were performed to calculate areas under the receiver operating characteristics (AU-ROC) curves. The clinical interpretation was used as reference standard in all analyses, and disease activity measures were used as predictor variables. The performance of predictor variables (AU-ROCs) was compared. RESULTS: The data of 1505 RA patients were used for analyses. The highest AU-ROC of 0.88 (95%CI 0.85-0.90) was shown for DAS28; AU-ROC of DAS-OST was 0.78 (95%CI 0.75-0.81), difference 0.10, p<0.01. CONCLUSIONS: Compared to DAS28, DAS-OST classified RA statistically significantly less well as active versus inactive, when using the clinical classification as reference standard. However, a DAS-modification without joint scores might have a place in strategies limiting routine outpatients' visits to the rheumatologist.

Development and Validation of Rheumatoid Arthritis Disease Activity Indices Including HandScan (Optical Spectral Transmission) Scores.

OBJECTIVE: To develop and validate a composite rheumatoid arthritis (RA) disease activity index using optical spectral transmission (OST) scores obtained with the HandScan, replacing tender and swollen joint counts. METHODS: RA patients from a single center routinely undergoing HandScan measurements with at least 1 concurrent OST score and Disease Activity Score in 28 joints (DAS28) were included. Data were extracted from medical records. Linear regression analyses with the DAS28 as the outcome were performed to create a disease activity index (DAS-OST). OST score, erythrocyte sedimentation rate (ESR), and patient global assessment (PtGA) visual analog scale (VAS), sex, age, disease duration, and rheumatoid factor status were evaluated as independent variables. Final models were derived based on the statistical significance of coefficients and model fit. Of the data, two-thirds were used for development and one-third for validation; external validation was performed in a cohort from another center. Agreement between DAS-OST and DAS28 was assessed using the Bland-Altman plot method and intraclass correlation coefficient (ICC). Diagnostic value of the DAS-OST was determined for established definitions of remission, low disease activity (LDA), and high disease activity (HDA). RESULTS: Data of 3,358 observations from 1,505 unique RA patients were extracted. DAS-OST was defined as: -0.44 + OST × 0.03 + male × -0.11 + LN(ESR) × 0.77 + PtGA VAS × 0.03. The ICCs between DAS-OST and DAS28 were 0.88 (95% confidence interval [95% CI] 0.87-0.90) and 0.82 (95% CI 0.75-0.86) and measurement errors were 0.58 and 0.87 in internal and external validation, respectively. Sensitivity for remission, LDA, and HDA was 79%, 91%, and 43%, respectively, and specificity was 92%, 80%, and 96% in external validation. CONCLUSION: Using the HandScan, RA disease activity can be accurately estimated if combined with ESR, PtGA VAS, and sex into a disease activity index (DAS-OST).

Comparison between 2D radiographic weight-bearing joint space width and 3D MRI non-weight-bearing cartilage thickness measures in the knee using non-weight-bearing 2D and 3D CT as an intermediary.

BACKGROUND: In knee osteoarthritis, radiographic joint space width (JSW) is frequently used as a surrogate marker for cartilage thickness; however, longitudinal changes in radiographic JSW have shown poor correlations with those of magnetic resonance imaging (MRI) cartilage thickness. There are fundamental differences between the techniques: radiographic JSW represents two-dimensional (2D), weight-bearing, bone-to-bone distance, while on MRI three-dimensional (3D) non-weight-bearing cartilage thickness is measured. In this exploratory study, computed tomography (CT) was included as a third technique, as it can measure bone-to-bone under non-weight-bearing conditions. The objective was to use CT to compare the impact of weight-bearing versus non-weight-bearing, as well as bone-to-bone JSW versus actual cartilage thickness, in the knee. METHODS: Osteoarthritis patients (n = 20) who were treated with knee joint distraction were included. Weight-bearing radiographs, non-weight-bearing MRIs and CTs were acquired before and 2 years after treatment. The mean radiographic JSW and cartilage thickness of the most affected compartment were measured. From CT, the 3D median JSW was calculated and a 2D projectional image was rendered, positioned similarly and measured identically to the radiograph. Pearson correlations between the techniques were derived, both cross-sectionally and longitudinally. RESULTS: Fourteen patients could be analyzed. Cross-sectionally, all comparisons showed moderate to strong significant correlations (R = 0.43-0.81; all p < 0.05). Longitudinal changes over time were small; only the correlations between 2D CT and 3D CT (R = 0.65; p = 0.01) and 3D CT and MRI (R = 0.62; p = 0.02) were statistically significant. CONCLUSION: The poor correlation between changes in radiographic JSW and MRI cartilage thickness appears primarily to result from the difference in weight-bearing, and less so from measuring bone-to-bone distance versus cartilage thickness.

Dorsal Root Ganglia Macrophages Maintain Osteoarthritis Pain.

Pain is the major debilitating symptom of osteoarthritis (OA), which is difficult to treat. In OA patients joint tissue damage only poorly associates with pain, indicating other mechanisms contribute to OA pain. Immune cells regulate the sensory system, but little is known about the involvement of immune cells in OA pain. Here, we report that macrophages accumulate in the dorsal root ganglia (DRG) distant from the site of injury in two rodent models of OA. DRG macrophages acquired an M1-like phenotype, and depletion of DRG macrophages resolved OA pain in male and female mice. Sensory neurons innervating the damaged knee joint shape DRG macrophages into an M1-like phenotype. Persisting OA pain, accumulation of DRG macrophages, and programming of DRG macrophages into an M1-like phenotype were independent of Nav1.8 nociceptors. Inhibition of M1-like macrophages in the DRG by intrathecal injection of an IL4-IL10 fusion protein or M2-like macrophages resolved persistent OA pain. In conclusion, these findings reveal a crucial role for macrophages in maintaining OA pain independent of the joint damage and suggest a new direction to treat OA pain.SIGNIFICANCE STATEMENT In OA patients pain poorly correlates with joint tissue changes indicating mechanisms other than only tissue damage that cause pain in OA. We identified that DRG containing the somata of sensory neurons innervating the damaged knee are infiltrated with macrophages that are shaped into an M1-like phenotype by sensory neurons. We show that these DRG macrophages actively maintain OA pain remotely and independent of joint damage. The phenotype of these macrophages is crucial for a pain-promoting role. Targeting the phenotype of DRG macrophages with either M2-like macrophages or a cytokine fusion protein that skews macrophages into an M2-like phenotype resolves OA pain. Our work reveals a mechanism that contributes to the maintenance of OA pain distant from the affected knee joint and suggests that dorsal root ganglia macrophages are a target to treat osteoarthritis chronic pain.

On-demand treatment with the iron chelator deferasirox is ineffective in preventing blood-induced joint damage in haemophilic mice.

INTRODUCTION: Early intervention in the devastating process of haemophilic arthropathy (HA) is highly desirable, but no disease-modifying therapy is currently available. Considering the pivotal role of iron in the development of HA, iron chelation is considered a promising therapeutic approach. A previous study in haemophilic mice demonstrated that treatment with the iron chelator deferasirox (DFX) 8 weeks before joint bleed induction, attenuated cartilage damage upon blood exposure. However, in haemophilia patients this approach is not opportune given the unpredictable occurrence of hemarthroses. AIM: To evaluate the effectiveness of on-demand DFX treatment, initiated immediately after joint bleed induction. METHODS: A joint bleed was induced in 66 factor VIII-deficient mice by infra-patellar needle puncture. Mice were randomly assigned to treatment with either placebo (drinking water) or DFX (dissolved in drinking water) throughout the study. Five weeks after joint bleed induction, inflammation and cartilage damage were assessed histologically. Joints of ten bleed naive haemophilic mice served as controls. RESULTS: A joint bleed resulted in significant inflammation and cartilage damage in the blood-exposed joint compared with those of control animals, in both the placebo and DFX group (all p = <.05). No differences in tibiofemoral or patellar inflammation (p = .305 and p = .787, respectively) nor cartilage damage (p = .265 and p = .802, respectively) were found between the blood-exposed joints of both treatment groups. CONCLUSION: On-demand treatment with DFX does not prevent joint damage following blood exposure in haemophilic mice. DFX seems unable to reach the joint in time to exert its effect before the irreversible harmful process is initiated.

Enhanced Extracellular Matrix Breakdown Characterizes the Early Distraction Phase of Canine Knee Joint Distraction.

OBJECTIVE: Joint distraction triggers intrinsic cartilage repair in animal models of osteoarthritis (OA), corroborating observations in human OA patients treated with joint distraction. The present study explores the still largely elusive mechanism initiating this repair process. DESIGN: Unilateral OA was induced in the knee joint of 8 dogs using the groove model; the contralateral joint served as a control. After 10 weeks, 4 animals received joint distraction, the other 4 serving as OA controls. Halfway the distraction period (after 4 weeks of a standard 8-week distraction treatment), all animals were euthanized, and joint tissues were collected. A targeted quantitative reverse transcription polymerase chain reaction (qRT-PCR) analysis was performed of commonly involved processes including matrix catabolism/anabolism, inflammation, and known signaling pathways in OA. In addition, cartilage changes were determined on tissue sections using the canine OARSI (Osteoarthritis Research Society International) histopathology score and collagen type II (COL2A1) immunostaining. RESULTS: Midway distraction, the distracted OA joint showed an upregulation of proteolytic genes, for example, ADAMTS5, MMP9, MMP13, compared to OA alone and the healthy joints, which correlated with an increased OARSI score. Additionally, genes of the transforming growth factor (TGF)-ß and Notch pathway, and markers associated with progenitor cells were increased. CONCLUSIONS: Joint distraction initiates both catabolic and anabolic transcriptional responses. The enhanced turnover, and thereby renewal of the matrix, could be the key to the cartilage repair observed in the months after joint distraction.