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ObjectivesThe 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.MethodsThe 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.ResultsNone 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.ConclusionsIdentifying loci conferring susceptibility to osteoarthritis will require large-scale sample sizes and well-defined phenotypes to minimise heterogeneity.

Objective: There is a pressing need to develop reliable molecular biomarkers in osteoarthritis. The aim of the study was to identify novel serum biomarkers for osteoarthritis using a metabolomics approach., Methods: A two-stage study design was utilised. 123 knee osteoarthritis cases and 299 controls were selected from the TwinsUK cohort as a discovery sample. 76 knee osteoarthritis cases and 100 controls from the Chingford Study were used as replication. Knee osteoarthritis was defined as either radiographic, medically diagnosed or total knee joint replacement due to primary osteoarthritis. All the subjects were unrelated white women. Their serum samples were assessed for targeted metabolite profiling by electrospray ionisation tandem mass spectrometry using the AbsoluteIDQ kit. 163 serum metabolites were assessed and their concentrations obtained. The ratios of metabolite concentrations as proxies for enzymatic reaction rates were calculated and tested for the association with knee osteoarthritis. Significance was assessed after adjustment for multiple testing (Bonferroni method) and potential confounders., Results: In the discovery stage, the authors identified 14 ratios significantly associated with knee osteoarthritis with p < or = 1.9 x 10(-6). Two of these 14 ratios were successfully confirmed in the replication stage-the ratios of valine to histidine and xleucine to histidine, with p=0.002. The significance remained after adjustment for age and body mass index., Conclusion: This is the first serum-based metabolomic study of osteoarthritis in humans. The branched-chain amino acids to histidine ratio has potential clinical use as an osteoarthritis biomarker and shows the clinical potential of metabolomics.

Objective: To examine the role of an IGF-I gene promoter polymorphism in the prevalence of radiographic osteoarthritis (ROA), and study its interaction with the COL2A1 gene., Methods: Individuals genotyped for IGF-I (n = 1546) and COL2A1 gene polymorphisms (n = 808) were selected from a random sample (n = 1583) derived from the Rotterdam study. The presence of ROA was defined as a Kellgren score of 2 or more in at least one of four joints (knee, hip, hand, and spine). Genotype specific odds ratios (OR) were adjusted for age, sex, body mass index, and bone mineral density using logistic regression. Interaction with the COL2A1 genotype was tested., Results: Overall, no association was found between the IGF-I polymorphism and ROA. In subjects aged 65 years or younger (n = 971), the prevalence of ROA increased with the absence of the 192 base pair (bp) allele (p for trend = 0.03). Compared with homozygotes for the 192 bp allele, the prevalence of ROA was 1.4 times higher in heterozygotes (95% confidence interval, 1.0 to 1.8) and 1.9 times higher in non-carriers (1.1 to 3.3). There was evidence of interaction between the IGF-I and COL2A1 genes. Individuals with the risk genotype of both genes had an increased prevalence of ROA (OR 3.4 (1.1 to 10.7)). No effect was observed in subjects older than 65 years., Subjects: with genetically determined low IGF-I expression (non-carriers of the 192 bp allele) may be at increased risk of ROA before the age of 65 years. Furthermore, an interaction between the IGF-I and COL2A1 genes is suggested.