Research Perspective Volume 13, Issue 18 pp 21814—21837
Development of infrastructure for a systemic multidisciplinary approach to study aging in retired sled dogs
- 1 Vaika, Inc., East Aurora, NY 14052, USA
- 2 Cornell University College of Veterinary Medicine, Ithaca, NY 14853, USA
- 3 Cornell University College of Agriculture and Life Sciences, Ithaca, NY 14853, USA
- 4 North Carolina State University College of Veterinary Medicine, Raleigh, NC 27606, USA
- 5 Tauber Bioinformatic Research Center, University of Haifa, Haifa, Israel
- 6 Roswell Park Comprehensive Cancer Center, Buffalo, NY 14263, USA
Received: August 17, 2021 Accepted: September 25, 2021 Published: September 28, 2021
https://doi.org/10.18632/aging.203600How to Cite
Copyright: © 2021 Fleyshman et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Abstract
Canines represent a valuable model for mammalian aging studies as large animals with short lifespans, allowing longitudinal analyses within a reasonable time frame. Moreover, they develop a spectrum of aging-related diseases resembling that of humans, are exposed to similar environments, and have been reasonably well studied in terms of physiology and genetics. To overcome substantial variables that complicate studies of privately-owned household dogs, we have focused on a more uniform population composed of retired Alaskan sled dogs that shared similar lifestyles, including exposure to natural stresses, and are less prone to breed-specific biases than a pure breed population. To reduce variability even further, we have collected a population of 103 retired (8-11 years-old) sled dogs from multiple North American kennels in a specialized research facility named Vaika. Vaika dogs are maintained under standardized conditions with professional veterinary care and participate in a multidisciplinary program to assess the longitudinal dynamics of aging. The established Vaika infrastructure enables periodic gathering of quantitative data reflecting physical, physiological, immunological, neurological, and cognitive decline, as well as monitoring of aging-associated genetic and epigenetic alterations occurring in somatic cells. In addition, we assess the development of age-related diseases such as arthritis and cancer. In-depth data analysis, including artificial intelligence-based approaches, will build a comprehensive, integrated model of canine aging and potentially identify aging biomarkers that will allow use of this model for future testing of antiaging therapies.