Novel Genetic Variants for Cartilage Thickness and Hip Osteoarthritis

Osteoarthritis is one of the most frequent and disabling diseases of the elderly. Only few genetic variants have been identified for osteoarthritis, which is partly due to large phenotype heterogeneity. To reduce heterogeneity, we here examined cartilage thickness, one of the structural components of joint health. We conducted a genome-wide association study of minimal joint space width (mJSW), a proxy for cartilage thickness, in a discovery set of 13,013 participants from five different cohorts and replication in 8,227 individuals from seven independent cohorts. We identified five genome-wide significant (GWS, P≤5·0×10−8) SNPs annotated to four distinct loci. In addition, we found two additional loci that were significantly replicated, but results of combined meta-analysis fell just below the genome wide significance threshold. The four novel associated genetic loci were located in/near TGFA (rs2862851), PIK3R1 (rs10471753), SLBP/FGFR3 (rs2236995), and TREH/DDX6 (rs496547), while the other two (DOT1L and SUPT3H/RUNX2) were previously identified. A systematic prioritization for underlying causal genes was performed using diverse lines of evidence. Exome sequencing data (n = 2,050 individuals) indicated that there were no rare exonic variants that could explain the identified associations. In addition, TGFA, FGFR3 and PIK3R1 were differentially expressed in OA cartilage lesions versus non-lesioned cartilage in the same individuals. In conclusion, we identified four novel loci (TGFA, PIK3R1, FGFR3 and TREH) and confirmed two loci known to be associated with cartilage thickness.The identified associations were not caused by rare exonic variants. This is the first report linking TGFA to human OA, which may serve as a new target for future therapies

Rheumatoid arthritis - clinical aspects: 134. Predictors of Joint Damage in South Africans with Rheumatoid Arthritis

Background: Rheumatoid arthritis (RA) causes progressive joint damage and functional disability. Studies on factors affecting joint damage as clinical outcome are lacking in Africa. The aim of the present study was to identify predictors of joint damage in adult South Africans with established RA. Methods: A cross-sectional study of 100 black patients with RA of >5 years were assessed for joint damage using a validated clinical method, the RA articular damage (RAAD) score. Potential predictors of joint damage that were documented included socio-demographics, smoking, body mass index (BMI), disease duration, delay in disease modifying antirheumatic drug (DMARD) initiation, global disease activity as measured by the disease activity score (DAS28), erythrocyte sedimentation rate (ESR), C reactive protein (CRP), and autoantibody status. The predictive value of variables was assessed by univariate and stepwise multivariate regression analyses. A p value <0.05 was considered significant. Results: The mean (SD) age was 56 (9.8) years, disease duration 17.5 (8.5) years, educational level 7.5 (3.5) years and DMARD lag was 9 (8.8) years. Female to male ratio was 10:1. The mean (SD) DAS28 was 4.9 (1.5) and total RAAD score was 28.3 (12.8). The mean (SD) BMI was 27.2 kg/m2 (6.2) and 93% of patients were rheumatoid factor (RF) positive. More than 90% of patients received between 2 to 3 DMARDs. Significant univariate predictors of a poor RAAD score were increasing age (p = 0.001), lower education level (p = 0.019), longer disease duration (p < 0.001), longer DMARD lag (p = 0.014), lower BMI (p = 0.025), high RF titre (p < 0.001) and high ESR (p = 0.008). The multivariate regression analysis showed that the only independent significant predictors of a higher mean RAAD score were older age at disease onset (p = 0.04), disease duration (p < 0.001) and RF titre (p < 0.001). There was also a negative association between BMI and the mean total RAAD score (p = 0.049). Conclusions: Patients with longstanding established RA have more severe irreversible joint damage as measured by the clinical RAAD score, contrary to other studies in Africa. This is largely reflected by a delay in the initiation of early effective treatment. Independent of disease duration, older age at disease onset and a higher RF titre are strongly associated with more joint damage. The inverse association between BMI and articular damage in RA has been observed in several studies using radiographic damage scores. The mechanisms underlying this paradoxical association are still widely unknown but adipokines have recently been suggested to play a role. Disclosure statement: C.I. has received a research grant from the Connective Tissue Diseases Research Fund, University of the Witwatersrand. All other authors have declared no conflicts of interes

Pathophysiology of hemophilic arthropathy and potential targets for therapy

Hemophilia is a congenital clotting factor deficiency characterized by spontaneous and trauma-related bleeding. Spontaneous bleeding shows a predilection for joints, and repeated hemarthroses lead to a disabling condition called hemophilic arthropathy. Treatment of this condition consists of preventing joint bleeding on the one hand and orthopedic surgery as a last resort on the other. Up till now, there is no disease modifying therapy available to fill the gap between these extremes. This review provides an overview of the pathogenesis of hemophilic arthropathy in order to identify potential targets for therapy. Joint bleeding induces synovial inflammation, cartilage degeneration and bone damage. These processes interact with each other and result in a vicious circle. Hemarthrosis promotes synovial hypertrophy and neoangiogenesis, increasing the susceptibility to mechanical damage and subsequent bleeding. The inflamed synovium affects the cartilage, while cartilage is also directly affected by blood via the release of cytokines and metalloproteinases, and via hydroxyl radical formation inducing chondrocyte apoptosis. Apart from the inflammatory pathways, iron plays a pivotal role in this process, as does the fibrinolytic system. Considering its pathogenesis, potential targets for disease modifying therapy in hemophilic arthropathy are iron, inflammation, vascular remodeling, hyperfibrinolysis, bone remodeling and cartilage regeneration. So far, iron chelators, anti-inflammatory therapy, anti-fibrinolytics and bone remodeling agents have demonstrated beneficial effects, predominantly in a preclinical setting. There is still a long way to go before these interventions will translate into clinical practice. The most important challenges are: establishing a universal outcome measure to predict efficacy in humans, and determination of the optimal route and timing to administer disease modifying therapy

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

The detrimental effects of iron on the joint : a comparison between haemochromatosis and haemophilia

Joint damage due to (recurrent) joint bleeding in haemophilia causes major morbidity. Although the exact pathogenesis has not been fully elucidated, a central role for iron is hypothesised. Likewise, in hereditary haemochromatosis joint destruction is caused by iron overload. A comparison between these types of arthropathy could provide more insight in the influence of iron in inducing joint damage. A literature review was performed to compare both disorders with respect to their clinical and histological characteristics, and preclinical studies on the influence of iron on different joint components were reviewed. Similarities in the features of arthropathy in haemochromatosis and haemophilia are cartilage degeneration, subchondral bone changes with osteophyte and cyst formation, and osteoporosis. In both disorders synovial inflammation and proliferation are seen, although this is much more explicit in haemophilia. Other substantial differences are the age at onset, the occurrence of chondrocalcinosis radiographically and calcium pyrophosphate dihydrate deposition disease in haemochromatosis, and a rapid progression with joint deformity and neovascularisation in haemophilia. Preclinical studies demonstrate detrimental effects of iron to all components of the joint, resulting in synovial inflammation and hyperplasia, chondrocyte death, and impaired osteoblast function. These effects, particularly the synovial changes, are aggravated in the presence of a pro-inflammatory signal, which is prominent in haemophilic arthropathy and minimal in haemochromatosis. Additional research is needed to further specify the role of iron as a specific target in treating these types of arthropathy

Disease burden of knee osteoarthritis patients with a joint replacement compared to matched controls: a population-based analysis of a Dutch medical claims database

OBJECTIVE: On a population level, the incidence of knee prostheses (KP) has increased, but excess health care costs per patient, compared to matched controls without a KP, in the years surrounding these procedures and their determinants are largely unknown. We therefore aimed to provide estimates of age and sex-specific incidence of KPs, revision KPs, and prosthesis complications in patients with knee osteoarthritis (OA) and to determine excess health care costs in the years surrounding surgery compared with matched controls. METHODS: All KPs in OA patients in the Achmea Health Database were identified as well as up to four controls. Incidence rates of KPs, revisions, and complications from 2006-2013 were determined. Annual health care cost and excess costs (over matched controls) preceding, during, and after surgery were calculated and their determinants were evaluated. RESULTS: The increased incidence of KPs, revisions, and complications was strongest in younger age categories and men. The average costs per patient were relatively stable between 2006-2012. KP patient's annual health care costs increased towards the year of surgery. After surgery, costs decreased, but remained higher as compared to costs prior to surgery. High post-surgery costs were mainly associated with subsequent revisions or additional KPs, but costs were also higher in females, lower age categories, and lower SES. CONCLUSION: These results underscore the increasing burden and medical need associated with end-stage OA, especially in younger age categories. Improvement of guidelines tailored to individual patient groups aimed at avoiding complications and revisions is required to counteract this increasing burden

Determining the lowest optimally effective methotrexate dose for individual RA patients using their dose response relation in a tight control treatment approach

Objective: To determine the optimal methotrexate dose in individual patients and to explore whether this optimal dose and the level of disease activity at that dose could be predicted. Methods: Data from CAMERA II trial comparing MTX and MTX with 10 mg of prednisone both in a tight control treatment strategy in early RA was used. For each patient a curve for disease activity over time was fitted and the MTX dose after which further step-up did not result in relevant improvement in disease activity anymore was determined the 'lowest optimally effective MTX dose (LOED)'. The association of demographic and clinical characteristics at baseline with this LOED and with the level of disease activity reached at LOED was studied. Results: In 204 (100 MTX and 104 MTX with prednisone) out of 236 patients LOED could be defined. 10 mg/wk was the most prevalent LOED in patients treated with MTX and prednisone and 10 mg/wk, 20 mg/wk and 30 mg/wk in the MTX strategy. Although the specific LOED could not reliably be predicted, higher baseline disease activity, height and lower weight were associated with higher LOEDs (i.e at least 15 mg/wk). A score was presented to decide on a starting dose of 10 mg/wk or (at least) 15 mg/wk. The level of disease activity at LOED could not be reliably predicted. Conclusion: A starting dose of 10 mg/wk might be a good choice for most patients and is frequently already the optimal dose. However, a subgroup of patient can be determined who would require higher MTX doses

Complex machine-learning algorithms and multivariable logistic regression on par in the prediction of insufficient clinical response to methotrexate in rheumatoid arthritis

The goals of this study were to examine whether machine-learning algorithms outper-form multivariable logistic regression in the prediction of insufficient response to methotrexate (MTX); secondly, to examine which features are essential for correct prediction; and finally, to in-vestigate whether the best performing model specifically identifies insufficient responders to MTX (combination) therapy. The prediction of insufficient response (3-month Disease Activity Score 28-Erythrocyte-sedimentation rate (DAS28-ESR) > 3.2) was assessed using logistic regression, least absolute shrinkage and selection operator (LASSO), random forest, and extreme gradient boosting (XGBoost). The baseline features of 355 rheumatoid arthritis (RA) patients from the “treatment in the Rotterdam Early Arthritis CoHort” (tREACH) and the U-Act-Early trial were combined for analyses. The model performances were compared using area under the curve (AUC) of receiver operating characteristic (ROC) curves, 95% confidence intervals (95% CI), and sensitivity and specificity. Fi-nally, the best performing model following feature selection was tested on 101 RA patients starting tocilizumab (TCZ)-monotherapy. Logistic regression (AUC = 0.77 95% CI: 0.68–0.86) performed as well as LASSO (AUC = 0.76, 95% CI: 0.67–0.85), random forest (AUC = 0.71, 95% CI: 0.61 = 0.81), and XGBoost (AUC = 0.70, 95% CI: 0.61–0.81), yet logistic regression reached the highest sensitivity (81%). The most important features were baseline DAS28 (components). For all algorithms, models with six features performed similarly to those with 16. When applied to the TCZ-monotherapy group, logistic regression’s sensitivity significantly dropped from 83% to 69% (p = 0.03). In the current dataset, logistic regression performed equally well compared to machine-learning algorithms in the prediction of insufficient response to MTX. Models could be reduced to six features, which are more conducive for clinical implementation. Interestingly, the prediction model was specific to MTX (combination) therapy response

Lowest optimally effective MTX dose (LOED) reached per strategy arm.

<p>Lowest optimally effective MTX dose (LOED) reached per strategy arm.</p