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... Show moreObjectives. 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 (Delta) 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 Delta 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 Delta 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. Show less
Helvoort, E.M. van; Welsing, P.M.J.; Jansen, M.P.; Gielis, W.P.; Loef, M.; Kloppenburg, M.; ... ; Mastbergen, S. 2021
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... Show moreObjectives 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 >= 9 (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. Show less
Background Despite recent advances in the understanding of the genetic architecture of osteoarthritis (OA), only two genetic loci have been identified for OA of the hand, in part explained by the... Show moreBackground Despite recent advances in the understanding of the genetic architecture of osteoarthritis (OA), only two genetic loci have been identified for OA of the hand, in part explained by the complexity of the different hand joints and heterogeneity of OA pathology.Methods We used data from the Rotterdam Study (RSI, RSII and RSIII) to create three hand OA phenotypes based on clustering patterns of radiographic OA severity to increase power in our modest discovery genome-wide association studies in the RS (n=8700), and sought replication in an independent cohort, the Framingham Heart Study (n=1203). We used multiple approaches that leverage different levels of information and functional data to further investigate the underlying biological mechanisms and candidate genes for replicated loci. We also attempted to replicate known OA loci at other joint sites, including the hips and knees.Results We found two novel genome-wide significant loci for OA in the thumb joints. We identified WNT9A as a possible novel causal gene involved in OA pathogenesis. Furthermore, several previously identified genetic loci for OA seem to confer risk for OA across multiple joints: TGFa, RUNX2, COL27A1, ASTN2, IL11 and GDF5 loci.Conclusions We identified a robust novel genetic locus for hand OA on chromosome 1, of which WNT9A is the most likely causal gene. In addition, multiple genetic loci were identified to be associated with OA across multiple joints. Our study confirms the potential for novel insight into the genetic architecture of OA by using biologically meaningful stratified phenotypes. Show less
Helvoort, E.M. van; Spil, W.E. van; Jansen, M.P.; Welsing, P.M.J.; Kloppenburg, M.; Loef, M.; ... ; Lafeber, F.P.J.G. 2020
Purpose The Applied Public-Private Research enabling OsteoArthritis Clinical Headway (APPROACH) consortium intends to prospectively describe in detail, preselected patients with knee osteoarthritis... Show morePurpose 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. Show less
Meulenbelt, I.M.; Bhutani, N.; Hollander, W. den; Gay, S.; Oppermann, U.; Reynard, L.N.; ... ; Loughlin, J. 2017
OBJECTIVE Genetic variation at the type II deiodinase (D2) gene (DIO2) was previously identified as osteoarthritis (OA) risk factor. To investigate mechanisms possibly underlying this association,... Show moreOBJECTIVE Genetic variation at the type II deiodinase (D2) gene (DIO2) was previously identified as osteoarthritis (OA) risk factor. To investigate mechanisms possibly underlying this association, we assessed D2 protein in healthy and OA-affected cartilage and investigated allelic balance of the OA risk polymorphism rs225014 at DIO2 in human OA joints. METHODS Immunohistochemical staining of healthy and OA-affected cartilage was performed for D2. We then assessed allelic balance of DIO2 mRNA within OA-affected cartilage both at and away from the lesion, ligaments and subchondral bone. Allelic balance was measured by the amount of alleles 'C' and 'T' of the intragenic OA risk polymorphism rs225014 in heterozygous carriers. RESULTS A markedly higher amount of D2 positive cells and staining intensity was observed in OA cartilage. A significant, 1.3-fold higher presence was observed for the OA-associated rs225014 'C' allele relative to the 'T' allele of DIO2, which was significant in 28 of 31 donors. CONCLUSION In OA cartilage, D2 protein presence is increased. The allelic imbalance of the DIO2 mRNA transcript, with the OA risk allele 'C' of rs225014 more abundant than the wild-type 'T' allele in heterozygote carriers provides a possible mechanism by which genetic variation at DIO2 confers OA risk. Show less
Meulenbelt, I.; Kraus, V.B.; Sandell, L.J.; Loughlin, J. 2011
On November fourth and fifth 2010 a group of more than 100 international investigators gathered in Atlanta for the second Osteoarthritis (OA) Biomarkers Global Initiative workshop titled "Genetics... Show moreOn November fourth and fifth 2010 a group of more than 100 international investigators gathered in Atlanta for the second Osteoarthritis (OA) Biomarkers Global Initiative workshop titled "Genetics and Genomics: New Targets in OA". The first workshop took place in April 2009 and focused on in vitro (soluble) biomarkers whilst the third and final workshop will take place in 2012 and will focus on imaging biomarkers. The OA Research Society International (OARSI) has organized the workshops. In addition to OARSI, the National Institute of Arthritis, Musculoskeletal and Skin Diseases, the Arthritis Foundation, Amgen, Genzyme, the American Orthopaedic Society for Sports Medicine and Pfizer sponsored the second meeting. It was clear from this meeting that experiments in the genetics, epigenetics and genomics of OA, are yielding valuable insights into the etiology of this heterogeneous disease but that much still needs to be learnt. Combining genetic insights with conventional biomarkers and imaging modalities may provide scientists with the enhanced tools to understand this complex disease. With those tools in hand, clinicians and industry can develop protocols to ultimately improve patient care. Show less
Objectives The genetic aetiology of osteoarthritis has not yet been elucidated. To enable a well-powered genome-wide association study (GWAS) for osteoarthritis, the authors have formed the arcOGEN... Show moreObjectives The genetic aetiology of osteoarthritis has not yet been elucidated. To enable a well-powered genome-wide association study (GWAS) for osteoarthritis, the authors have formed the arcOGEN Consortium, a UK-wide collaborative effort aiming to scan genome-wide over 7500 osteoarthritis cases in a two-stage genome-wide association scan. Here the authors report the findings of the stage 1 interim analysis. Methods The authors have performed a genome-wide association scan for knee and hip osteoarthritis in 3177 cases and 4894 population-based controls from the UK. Replication of promising signals was carried out in silico in five further scans (44 449 individuals), and de novo in 14 534 independent samples, all of European descent. Results None of the association signals the authors identified reach genome-wide levels of statistical significance, therefore stressing the need for corroboration in sample sets of a larger size. Application of analytical approaches to examine the allelic architecture of disease to the stage 1 genome-wide association scan data suggests that osteoarthritis is a highly polygenic disease with multiple risk variants conferring small effects. Conclusions Identifying loci conferring susceptibility to osteoarthritis will require large-scale sample sizes and well-defined phenotypes to minimise heterogeneity. Show less
Evangelou, E.; Valdes, A.M.; Kerkhof, H.J.M.; Styrkarsdottir, U.; Zhu, Y.Y.; Meulenbelt, I.; ... ; Translation Res Europe Appl 2011
Objectives Osteoarthritis (OA) is the most prevalent form of arthritis and accounts for substantial morbidity and disability, particularly in older people. It is characterised by changes in joint... Show moreObjectives Osteoarthritis (OA) is the most prevalent form of arthritis and accounts for substantial morbidity and disability, particularly in older people. It is characterised by changes in joint structure, including degeneration of the articular cartilage, and its aetiology is multifactorial with a strong postulated genetic component. Methods A meta-analysis was performed of four genome-wide association (GWA) studies of 2371 cases of knee OA and 35 909 controls in Caucasian populations. Replication of the top hits was attempted with data from 10 additional replication datasets. Results With a cumulative sample size of 6709 cases and 44 439 controls, one genome-wide significant locus was identified on chromosome 7q22 for knee OA (rs4730250, p = 9.2 x 10(-9)), thereby confirming its role as a susceptibility locus for OA. Conclusion The associated signal is located within a large (500 kb) linkage disequilibrium block that contains six genes: PRKAR2B (protein kinase, cAMP-dependent, regulatory, type II, beta), HPB1 (HMG-box transcription factor 1), COG5 (component of oligomeric golgi complex 5), GPR22 (G protein-coupled receptor 22), DUS4L (dihydrouridine synthase 4-like) and BCAP29 (B cell receptor-associated protein 29). Gene expression analyses of the (six) genes in primary cells derived from different joint tissues confirmed expression of all the genes in the joint environment. Show less
Meulenbelt, I.; Bos, S.D.; Chapman, K.; Breggen, R. van der; Houwing-Duistermaat, J.J.; Kremer, D.; ... ; Slagboom, E. 2011
Objective To study whether common genetic variants of the genes involved in the complex regulatory mechanism determining the intracellular bio-availability of T3 influence osteoarthritis onset.... Show moreObjective To study whether common genetic variants of the genes involved in the complex regulatory mechanism determining the intracellular bio-availability of T3 influence osteoarthritis onset. Methods In total 17 genetic variants within the genes encoding WD40-repeat/SOCS-box protein 1, ubiquitin specific protease 33, thyroid hormone receptor alpha, deiodinase, iodothyronine, type III (DIO3) and Indian hedgehog were measured and associated with osteoarthritis in a meta-analyses in European populations from the UK, The Netherlands, Greece and Spain containing a total of 3252 osteoarthritis cases and 2132 controls. Results The minor allele of the DIO3 variant rs945006 showed suggestive evidence for protective association in the overall meta-analyses, which was supported by individual osteoarthritis studies and osteoarthritis subtypes. The association appeared most significant in cases with knee and/or hip with an allelic OR of 0.81 (95% CI 0.70 to 0.930) with a nominal p value of 0.004 and a permutation-based corrected p value for multiple testing of 0.039. Conclusion The findings suggest that the DIO3 gene modulates osteoarthritis disease risk; however, additional studies are necessary to replicate our findings. To elucidate the molecular mechanisms focus should be on the local adaptation to T3 availability either during the endochondral ossification process or during ageing of the articular cartilage. Show less
Background: The objective of this study was to examine the relationship between common genetic variation of the ESR2 gene and osteoarthritis. Methods: In the discovery study, the Rotterdam Study-I,... Show moreBackground: The objective of this study was to examine the relationship between common genetic variation of the ESR2 gene and osteoarthritis. Methods: In the discovery study, the Rotterdam Study-I, 7 single nucleotide polymorphisms (SNPs) were genotyped and tested for association with hip (284 cases, 2772 controls), knee (665 cases, 2075 controls), and hand OA (874 cases, 2184 controls) using an additive model. In the replication stage one SNP (rs1256031) was tested in an additional 2080 hip, 1318 knee and 557 hand OA cases and 4001, 2631 and 1699 controls respectively. Fixed- and random-effects meta-analyses were performed over the complete dataset including 2364 hip, 1983 knee and 1431 hand OA cases and approximately 6000 controls. Results: The C allele of rs1256031 was associated with a 36% increased odds of hip OA in women of the Rotterdam Study-I (OR 1.36, 95% CI 1.08-1.70, p = 0.009). Haplotype analysis and analysis of knee-and hand OA did not give additional information. With the replication studies, the meta-analysis did not show a significant effect of this SNP on hip OA in the total population (OR 1.06, 95% CI 0.99-1.15, p = 0.10). Stratification according to gender did not change the results. In this study, we had 80% power to detect an odds ratio of at least 1.14 for hip OA (alpha = 0.05). Conclusion: This study showed that common genetic variation in the ESR2 gene is not likely to influence the risk of osteoarthritis with effects smaller than a 13% increase. Show less
Objective Several research groups have examined osteoarthritis (OA) association with Interleukin-1 (IL-1) region markers and haplotypes The results have been suggestive for hand OA, negative for... Show moreObjective Several research groups have examined osteoarthritis (OA) association with Interleukin-1 (IL-1) region markers and haplotypes The results have been suggestive for hand OA, negative for knee OA, and conflicting for hip OA Design Our aim was to address conflicts employing meta-analytical methods on data from 1238 European-descent cases with various OA phenotypes and 1269 European-descent controls from four study centers We imputed some missing genotype data and reconstructed IL-1 region extended haplotypes A previously reported 7-marker IL1A-IL1B-IL1RN extended risk haplotype was tested for association with each specific index phenotype Results. For hip OA, data from three centers showed heterogeneity of extended-risk-haplotype effect, two panels showing trend toward risk and another showing protection, with overall odds ratio (OR) 1 24 (95% Confidence interval (CI) 0 45-3 41, P 0 67) The heterogeneity fell partly along control ascertainment lines, chiefly between controls ascertained as spouses of arthroplasty patients and controls identified through population radiographic survey For knee OA, the results showed no heterogeneity and no significant extended-risk-haplotype effect For hand OA, the results showed little heterogeneity and a modest trend toward positive association (summary OR 1 34, 95% CI 0 83-2 17 P 023) Using a Bayesian partition modeling approach, the 7-marker extended haplotypes showed no significant effect on any OA phenotype examined A 3-single-nucleotide polymorphism (SNP) IL1B-IL1RN haplotype rs1143627-rs16944-rs419598 showed a trend toward hand OA association (posterior probability of association 0 72) with the most prominent feature being protection from a specific haplotype representing a partial mirror image of the extended risk haplotype (OR estimated at 0 46) Conclusions The meta-analysis data do not confirm but only suggest that some hand and hip OA risk could be associated with the IL-1 region, particularly centered in IL1B and possibly also IL1RN (C) 2009 Published by Elsevier Ltd on behalf of Osteoarthritis Research Society International Show less
Objective. To identify novel genes involved in osteoarthritis (OA), by means of a genome-wide association study. Methods. We tested 500,510 single-nucleotide polymorphisms (SNPs) in 1,341 Dutch... Show moreObjective. To identify novel genes involved in osteoarthritis (OA), by means of a genome-wide association study. Methods. We tested 500,510 single-nucleotide polymorphisms (SNPs) in 1,341 Dutch Caucasian OA cases and 3,496 Dutch Caucasian controls. SNPs associated with at least 2 OA phenotypes were analyzed in 14,938 OA cases and similar to 39,000 controls. Meta-analyses were performed using the program Comprehensive Meta-analysis, with P values <1 x 10(-7) considered genome-wide significant. Results. The C allele of rs3815148 on chromosome 7q22 (minor allele frequency 23%; intron 12 of the COG5 gene) was associated with a 1.14-fold increased risk (95% confidence interval 1.09-1.19) of knee and/or hand OA (P = 8 x 10(-8)) and also with a 30% increased risk of knee OA progression (95% confidence interval 1.03-1.64) (P = 0.03). This SNP is in almost complete linkage disequilibrium with rs3757713 (68 kb upstream of GPR22), which is associated with GPR22 expression levels in lymphoblast cell lines (P = 4 x 10(-12)). Immunohistochemistry experiments revealed that G protein coupled receptor protein 22 (GPR22) was absent in normal mouse articular cartilage or synovium. However, GPR22-positive chondrocytes were found in the upper layers of the articular cartilage of mouse knee joints that were challenged with in vivo papain treatment or methylated bovine serum albumin treatment. GPR22-positive chondrocyte-like cells were also found in osteophytes in instability-induced OA. Conclusion. Our findings identify a novel common variant on chromosome 7q22 that influences susceptibility to prevalence and progression of OA. Since the GPR22 gene encodes a G protein-coupled receptor, this is potentially an interesting therapeutic target. Show less
