Literature DB >> 30586653

The expression profile of genes involved in osteoclastogenesis detected in whole blood of Arabian horses during 3 years of competing at race track.

Monika Stefaniuk-Szmukier1, Katarzyna Ropka-Molik2, Katarzyna Piórkowska2, Monika Bugno-Poniewierska3.   

Abstract

One of the most significant reason of economic loss on race track performance is lame in performed horses. Primarily, due to the failure within proper bone maintenance during conditioning in young horses. The training overload causes bone turnover disturbances in homeostasis between bone resorption and bone formation which promote the bone loss. Within our study we investigated training induced changes in transcript abundance of genes (NFATc1, CTSK, DAP12, CLEC5A, IL6ST, VAV3) involved in osteoclastogenesis hence bone resorption, in whole blood of Arabian horses. The expression pattern of all analysed genes varied depend of exercise intense activity. All training stages generate similar response to training whatever season was. The initial training had greater effect on expression pattern than increased, prolonged, established conditioning. Notwithstanding, the significant increase of transcript abundance of all investigated genes was observed during period of starts with racing competition. There is no biomarker known with highly significant accuracy according to degree of articular cartilage or bone disease in a single joint. Thus, the markers presented in our report, poses the potential to be further investigate as useful tool for bone turnover.
Copyright © 2018 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Arabian horses; Bone remodelling; Gene expression; Osteoclastogensis; Racing training

Mesh:

Year:  2018        PMID: 30586653     DOI: 10.1016/j.rvsc.2018.12.013

Source DB:  PubMed          Journal:  Res Vet Sci        ISSN: 0034-5288            Impact factor:   2.534


  2 in total

Review 1.  The Genetics of Racing Performance in Arabian Horses.

Authors:  K Ropka-Molik; M Stefaniuk-Szmukier; A D Musiał; B D Velie
Journal:  Int J Genomics       Date:  2019-09-02       Impact factor: 2.326

Review 2.  Use of Omics Data in Fracture Prediction; a Scoping and Systematic Review in Horses and Humans.

Authors:  Seungmee Lee; Melissa E Baker; Michael Clinton; Sarah E Taylor
Journal:  Animals (Basel)       Date:  2021-03-30       Impact factor: 2.752

  2 in total

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