4.3 Article

Aging Research 2011: Exploring the Pet Dog Paradigm

期刊

ILAR JOURNAL
卷 52, 期 1, 页码 97-105

出版社

OXFORD UNIV PRESS
DOI: 10.1093/ilar.52.1.97

关键词

animal model; cognitive aging; disease resistance; dog; gene-environment interaction; healthspan; life course; longevity; sex difference

资金

  1. PG Pet Care
  2. Rottweiler Health Foundation
  3. Brookdale National Fellowship

向作者/读者索取更多资源

Researchers are counting on comparative biologists to find alternative animal models of human aging that will foster experimental approaches to study disability-free longevity, not just the addition of years. This article presents one such alternative: the use of pet dogs living in the same environment as people to study the determinants of healthy longevity. There are both theoretical and practical reasons for this research model beyond the well-documented physiologic similarities between dogs and humans. First, a wealth of medical data-based on clinical and biochemical evaluation, medical imaging, and pathology-is available for pet dogs. Second, a vast array of phenotypic domains can be accurately assessed in dogs, ranging from cardiac contractility and glomerular integrity to the ability to climb stairs and interact with people. Moreover, studying pet dogs obviates the purchase and per diem costs typically associated with large animal research. Pet dogs may be particularly well suited for exploring (1) mechanisms of sex differences in longevity; (2) interventions to compress morbidity and enhance healthspan; (3) genomic correlates of successful aging phenotypes and endophenotypes; (4) heterogeneity in resistance to aging-related diseases, such as cancer; and (5) noninvasive biomarkers of particular target organs. Finally, between-breed differences in senescence trajectories and longevity may expand hypotheses of key genetic factors that contribute to sustained organ function and the postponement of disease. Yet the pet dog paradigm in aging research is nascent; tapping into the potential of this model will add to the existing strengths of conventional model systems.

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