Predictors of Hip Dysplasia

Osteoarthritis Cartilage. 2011 Jan 4. [Epub ahead of print]
Canine Hip Dysplasia is Predictable by Genotyping.
Guo G, Zhou Z, Wang Y, Zhao K, Zhu L, Lust G, Hunter L, Friedenberg S, Li J, Zhang Y, Harris S, Jones P, Sandler J, Krotscheck U, Todhunter R, Zhang Z.
Abstract
OBJECTIVE: To establish a predictive method using whole nome
genotyping for early intervention in canine hip dysplasia (CHD) risk
management, for the prevention of the progression of secondary
osteoarthritis (OA), and for selective breeding.

DESIGN: Two sets of dogs (6 breeds) were genotyped with dense SNPs covering the entire canine genome. The first set contained 359 dogs upon which a predictive formula for genomic breeding value (GBV) was derived by using their estimated breeding value (EBV) of the Norberg angle (a measure of CHD) and their genotypes. To investigate how well the formula would work for an individual dog with genotype only (without using EBV or phenotype), a cross validation was performed by masking the EBV of one dog at a time. The genomic data and the EBV of the remaining dogs were used to predict the GBV for the single dog that was left out. The second set of dogs included 38 new Labrador retriever dogs, which had no pedigree relationship to the dogs in the first set.

RESULTS: The cross validation showed a strong correlation (r>0.7) between the EBV and the GBV. The independent validation showed a strong correlation (r=0.5) between GBV for the Norberg angle and the observed Norberg angle (no EBV was available for the new 38 dogs). Sensitivity, specificity, positive, and negative predictive value of the genomic data were all above 70%.

CONCLUSIONS:
Prediction of CHD from genomic data is feasible, and can be applied for risk management of CHD and early selection for genetic improvement to reduce the prevalence of CHD in breeding programs. The prediction can be implemented before maturity, at which age current radiographic screening programs are traditionally applied, and as soon as DNA is available.