Indirect modification of animal genomes by interspecific hybridization, cross-breeding, and selection has produced an enormous spectrum of phenotypic diversity over more than 10,000 yr of animal domestication. Using these established technologies, the farming community has successfully increased the yield and efficiency of production in most agricultural species while utilizing land resources that are often unsuitable for other agricultural purposes. Moving forward, animal well-being and agricultural sustainability are moral and economic priorities of consumers and producers alike. Therefore, these considerations will be included in any strategy designed to meet the challenges produced by global climate change and an expanding world population. Improvements in the efficiency and precision of genetic technologies will enable a timely response to meet the multifaceted food requirements of a rapidly increasing world population.

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.