Korean J Vet Res > Volume 56(4); 2016 > Article
Korean Journal of Veterinary Research 2016;56(4):205-208.
DOI: https://doi.org/10.14405/kjvr.2016.56.4.205    Published online February 27, 2017.
Serum serotonin concentration in lean and obese dogs with myxomatous mitral valve disease
Kyu-Tae Kim1, Hee-Myung Park2, Changbaig Hyun3, Kyoung-Won Seo1, Kun-Ho Song1
1College of Veterinary Medicine, Chungnam National University
2College of Veterinary Medicine, Konkuk University
3College of Veterinary Medicine, Kangwon National University
Abstract
The aim of the present study is to investigate the potential influence of obesity as a factor in 5-hydroxytryptamine (5-HT) concentration in myxomatous mitral valve disease (MMVD) dogs. Fifty-five client-owned dogs were enrolled in a randomized trial. Dogs were classified by echocardiography into healthy (control), mild, and moderate to severe MMVD groups. Each group was subclassified by using a 9-point body condition score (BCS); lean (BCS 5-6/9) and obese groups (BCS 7.5-9/9). Dogs with moderate to severe MMVD had lower serotonin (5-HT) concentrations than the control group (p = 0.03). Dogs with moderate to severe MMVD (p = 0.017) had lower serum 5-HT concentrations than the control group in the obese group (BCS 7.5-9/9). Significant difference was found between the lean and obese groups (p = 0.015) which are not consider severe in the MMVD group. These results suggested that 5-HT concentration was decreased with the increasing severity of MMVD, and obesity might be taken into consideration when interpreting the serotonin concentration in MMVD dogs.
Key Words: 5-HT concentration, body condition score, dogs, myxomatous mitral valve disease, obesity


About
Browse articles
For contributors
Policy
Editorial Office
#401-1, 85 Bldg., College of Veterinary Medicine, Seoul National University
1 Gwanak-ro, Gwanak-gu, Seoul 08826, Korea
Tel: +82-2-880-1229    Fax: +82-2-878-9762    E-mail: jvs@ksvs.or.kr                

Copyright © 2024 by The Korean Society of Veterinary Science.

Developed in M2PI

Close layer
prev next