Toggle Main Menu Toggle Search

Open Access padlockePrints

Preliminary genetic analyses of important musculoskeletal conditions of Thoroughbred racehorses in Hong Kong

Lookup NU author(s): Dr Claire WelshORCiD



This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


A retrospective cohort study of important musculoskeletal conditions of Thoroughbred racehorses was conducted using health records generated over a 15. year period (n=5062, 1296 sires). The prevalence of each condition in the study population was: fracture, 13%; osteoarthritis, 10%; suspensory ligament injury, 10%; and tendon injury, 19%. Linear and logistic sire and animal regression models were built to describe the binary occurrence of these musculoskeletal conditions, and to evaluate the significance of possible environmental risk factors. The heritability of each condition was estimated using residual maximum likelihood (REML). Bivariate mixed models were used to generate estimates of genetic correlations between each pair of conditions.Heritability estimates of fracture, osteoarthritis, suspensory ligament and tendon injury were small to moderate (range: 0.01-0.20). Fracture was found to be positively genetically correlated with both osteoarthritis and suspensory ligament injury. These results suggest that there is a significant genetic component involved in the risk of the studied conditions. Due to positive genetic correlations, a reduction in prevalence of one of the correlated conditions may effect a reduction in risk of the other condition. © 2013 The Authors.

Publication metadata

Author(s): Welsh CE, Lewis TW, Blott SC, Mellor DJ, Lam KH, Stewart BD, Parkin TDH

Publication type: Article

Publication status: Published

Journal: Veterinary Journal

Year: 2013

Volume: 198

Issue: 3

Pages: 611-615

Print publication date: 01/12/2013

Online publication date: 05/06/2013

Date deposited: 17/10/2019

ISSN (print): 1090-0233

ISSN (electronic): 1532-2971

Publisher: Elsevier Ltd


DOI: 10.1016/j.tvjl.2013.05.002

PubMed id: 23746478


Altmetrics provided by Altmetric


Funder referenceFunder name