Prediction model for knee osteoarthritis incidence, including clinical, genetic and biochemical risk factors.

OBJECTIVE: To develop and validate a prognostic model for incident knee osteoarthritis (KOA) in a general population and determine the value of different risk factor groups to prediction. METHODS: The prognostic model was developed in 2628 individuals from the Rotterdam Study-I (RS-I). Univariate and multivariate analyses were performed for questionnaire/easily obtainable variables, imaging variables, genetic and biochemical markers. The extended multivariate model was tested on discrimination (receiver operating characteristic curve and area under the curve (AUC)) in two other population-based cohorts: Rotterdam Study-II and Chingford Study. RESULTS: In RS-I, there was moderate predictive value for incident KOA based on the genetic score alone in subjects aged <65 years (AUC 0.65), while it was only 0.55 for subjects aged ≥65 years. The AUC for gender, age and body mass index (BMI) in prediction for KOA was 0.66. Addition of the questionnaire variables, genetic score or biochemical marker urinary C-terminal cross-linked telopeptide of type II collagen to the model did not change the AUC. However, when adding the knee baseline KL score to the model the AUC increased to 0.79. Applying external validation, similar results were observed in the Rotterdam Study-II and the Chingford Study. CONCLUSIONS: Easy obtainable 'Questionnaire' variables, genetic markers, OA at other joint sites and biochemical markers add only modestly to the prediction of KOA incidence using age, gender and BMI in an elderly population. Doubtful minor radiographic degenerative features in the knee, however, are a very strong predictor of future KOA. This is an important finding, as many radiologists do not report minor degenerative changes in the knee.

Statin use is associated with reduced incidence and progression of knee osteoarthritis in the Rotterdam study.

BACKGROUND: Osteoarthritis is the most frequent chronic joint disease causing pain and disability. Besides biomechanical mechanisms, the pathogenesis of osteoarthritis may involve inflammation, vascular alterations and dysregulation of lipid metabolism. As statins are able to modulate many of these processes, this study examines whether statin use is associated with a decreased incidence and/or progression of osteoarthritis. METHODS: Participants in a prospective population-based cohort study aged 55 years and older (n=2921) were included. x-Rays of the knee/hip were obtained at baseline and after on average 6.5 years, and scored using the Kellgren and Lawrence score for osteoarthritis. Any increase in score was defined as overall progression (incidence and progression). Data on covariables were collected at baseline. Information on statin use during follow-up was obtained from computerised pharmacy databases. The overall progression of osteoarthritis was compared between users and non-users of statins. Using a multivariate logistic regression model with generalised estimating equation, OR and 95% CI were calculated after adjusting for confounding variables. RESULTS: Overall progression of knee and hip osteoarthritis occurred in 6.9% and 4.7% of cases, respectively. The adjusted OR for overall progression of knee osteoarthritis in statin users was 0.43 (95% CI 0.25 to 0.77, p=0.01). The use of statins was not associated with overall progression of hip osteoarthritis. CONCLUSIONS: Statin use is associated with more than a 50% reduction in overall progression of osteoarthritis of the knee, but not of the hip.

Impact of different descriptions of the Kellgren and Lawrence classification criteria on the diagnosis of knee osteoarthritis.

OBJECTIVES: Although the Kellgren and Lawrence (K&L) criteria for defining radiological osteoarthritis are widely used in epidemiological and clinical studies, the authors previously documented the existence of five different versions of these criteria. This study identifies the impact of the use of alternative versions of the K&L criteria and evaluates which description has the highest association with knee complaints. METHODS: Two readers scored most radiographs of the knees of participants of the Rotterdam Study with the original K&L description (90%). In addition, each alternative description was used in a random part (20%) of the radiographs. The authors calculated reproducibility of all descriptions, and compared sensitivity and specificity of the alternative descriptions for three cut-off points with the original description as reference standard (K&L≥1, K&L≥2 and K&L≥3). The authors calculated κ statistics to compare agreement between the original and alternative descriptions, and evaluated the association with knee complaints. RESULTS: The dataset comprises radiographs of knees of 3071 people. For cut-off K&L≥1 all four alternatives classified more people as having osteoarthritis than the original description; κ was low, and sensitivity and specificity were moderate to good. For cut-offs K&L≥2 and K&L≥3 there was little difference in the number of cases and κ, sensitivity and specificity were good to perfect. The original description and alternative 3 showed the strongest association with knee complaints. CONCLUSIONS: The different descriptions of the K&L criteria have impact on the classification of osteoarthritis in the lowest grade (K&L≥1). All descriptions have strengths and weaknesses. It depends on the purpose which is the best description.

Insights into the genetic architecture of osteoarthritis from stage 1 of the arcOGEN study.

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 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.

Large-scale meta-analysis of interleukin-1 beta and interleukin-1 receptor antagonist polymorphisms on risk of radiographic hip and knee osteoarthritis and severity of knee osteoarthritis.

OBJECTIVE: To clarify the role of common genetic variation in the Interleukin-1ß (IL1B) and Interleukin-1R antagonist (IL1RN) genes on risk of knee and hip osteoarthritis (OA) and severity of knee OA by means of large-scale meta-analyses. METHODS: We searched PubMed for articles assessing the role of IL1B and IL1RN polymorphisms/haplotypes on the risk of hip and/or knee OA. Novel data were included from eight unpublished studies. Meta-analyses were performed using fixed- and random-effects models with a total of 3595 hip OA and 5013 knee OA cases, and 6559 and 9132 controls respectively. The role of ILRN haplotypes on radiographic severity of knee OA was tested in 1918 cases with Kellgren-Lawrence (K/L) 1 or 2 compared to 199 cases with K/L 3 or 4. RESULTS: The meta-analysis of six published studies retrieved from the literature search and eight unpublished studies showed no evidence of association between common genetic variation in the IL1B or IL1RN genes and risk of hip OA or knee OA (P>0.05 for rs16944, rs1143634, rs419598 and haplotype C-G-C (rs1143634, rs16944 and rs419598) previously implicated in risk of hip OA). The C-T-A haplotype formed by rs419598, rs315952 and rs9005, previously implicated in radiographic severity of knee OA, was associated with reduced severity of knee OA (odds ratio (OR)=0.71 95%CI 0.56-0.91; P=0.006, I(2)=74%), and achieved borderline statistical significance in a random-effects model (OR=0.61 95%CI 0.35-1.06 P=0.08). CONCLUSION: Common genetic variation in the Interleukin-1 region is not associated with prevalence of hip or knee OA but our data suggest that IL1RN might have a role in severity of knee OA.

Recommendations for standardization and phenotype definitions in genetic studies of osteoarthritis: the TREAT-OA consortium.

OBJECTIVE: To address the need for standardization of osteoarthritis (OA) phenotypes by examining the effect of heterogeneity among symptomatic (SOA) and radiographic osteoarthritis (ROA) phenotypes. METHODS: Descriptions of OA phenotypes of the 28 studies involved in the TREAT-OA consortium were collected. We investigated whether different OA definitions result in different association results by creating various hip OA definitions in one large population based cohort (the Rotterdam Study I (RSI)) and testing those for association with gender, age and body mass index using one-way ANOVA. For ROA, we standardized the hip-, knee- and hand ROA definitions and calculated prevalence's of ROA before and after standardization in nine cohort studies. This procedure could only be performed in cohort studies and standardization of SOA definitions was not feasible at this moment. RESULTS: In this consortium, all studies with SOA phenotypes (knee, hip and hand) used a different definition and/or assessment of OA status. For knee-, hip- and hand ROA five, four and seven different definitions were used, respectively. Different hip ROA definitions do lead to different association results. For example, we showed in the RSI that hip OA defined as "at least definite joint space narrowing (JSN) and one definite osteophyte" was not associated with gender (P =0.22), but defined as "at least one definite osteophyte" was significantly associated with gender (P=3×10(-9)). Therefore, a standardization process was undertaken for ROA definitions. Before standardization a wide range of ROA prevalence's was observed in the nine cohorts studied. After standardization the range in prevalence of knee- and hip ROA was small. CONCLUSION: Phenotype definitions influence the prevalence of OA and association with clinical variables. ROA phenotypes within the TREAT-OA consortium were standardized to reduce heterogeneity and improve power in future genetics studies.