Research Article: The companion dog as a model for human aging and mortality

Date Published: February 19, 2018

Publisher: John Wiley and Sons Inc.

Author(s): Jessica M. Hoffman, Kate E. Creevy, Alexander Franks, Dan G. O’Neill, Daniel E. L. Promislow.

http://doi.org/10.1111/acel.12737

Abstract

Around the world, human populations have experienced large increases in average lifespan over the last 150 years, and while individuals are living longer, they are spending more years of life with multiple chronic morbidities. Researchers have used numerous laboratory animal models to understand the biological and environmental factors that influence aging, morbidity, and longevity. However, the most commonly studied animal species, laboratory mice and rats, do not experience environmental conditions similar to those to which humans are exposed, nor do we often diagnose them with many of the naturally occurring pathologies seen in humans. Recently, the companion dog has been proposed as a powerful model to better understand the genetic and environmental determinants of morbidity and mortality in humans. However, it is not known to what extent the age‐related dynamics of morbidity, comorbidity, and mortality are shared between humans and dogs. Here, we present the first large‐scale comparison of human and canine patterns of age‐specific morbidity and mortality. We find that many chronic conditions that commonly occur in human populations (obesity, arthritis, hypothyroidism, and diabetes), and which are associated with comorbidities, are also associated with similarly high levels of comorbidity in companion dogs. We also find significant similarities in the effect of age on disease risk in humans and dogs, with neoplastic, congenital, and metabolic causes of death showing similar age trajectories between the two species. Overall, our study suggests that the companion dog may be an ideal translational model to study the many complex facets of human morbidity and mortality.

Partial Text

Age is the greatest risk factor not only for the probability of death, but also for the majority of morbidities associated with mortality (Finkel, 2005; Kaeberlein, Rabinovitch & Martin, 2015; Kennedy et al., 2014). However, studies to identify factors that alter patterns of aging using animal models have focused on lifespan and age‐specific mortality, rather than the underlying patterns of morbidity that lead to death. This gap is due in part to the difficulty of measuring causes of mortality in the standard animal models in aging studies. For example, age‐related morbidity and causes of mortality in the commonly studied models of aging range from the not well understood (and often not studied) in mice (Simms & Berg, 1957; Snyder, Ward & Treuting, 2016), to the poorly understood in flies and worms (but see Herndon et al., 2002; Rera, Clark & Walker, 2012), to nonexistent in yeast. In addition, many diseases important to human aging (e.g., cardiovascular disease and dementia) do not develop spontaneously in our commonly studied model organisms. To this end, we need a model organism that allows us to understand not only age‐related mortality, but also age‐related morbidity and causes of death. The companion dog (i.e., dogs that reside under their owner’s care) has the potential to fill this gap and to enable us to better understand the genetic and environmental factors that affect lifespan, and the underlying forces that shape age‐specific morbidity and mortality.

We obtained morbidity and mortality data from 112,375 humans from the U.S. Census Bureau’s National Longitudinal Mortality Study, 73,835 dogs in the Veterinary Medical Database (VMDB, 37,480 of which remained after removal of individuals with “unclassified” pathophysiological process [PP] or organ system [OS] and were used for comorbidity PP/OS analysis, see Methods), and 5,095 dogs in the VetCompass Programme database in the United Kingdom. Using the Census human data and VMDB canine data, we were able to compare eight PP and nine OS categories between the two species. There were a total of 106 different possible causes of death for the Census dataset, and these were assigned to a total of 38 of 72 possible PP×OS combinations. For the VMDB, 5563 different diagnoses were recorded representing 93 PP×OS combinations. The VetCompass dataset had 56 diagnoses that were not able to be placed into PP and OS cause of death, and which had no information on comorbidity, and as such were only used for longevity analysis.

Many authors have pointed out that age is the single greatest risk factor for a variety of causes of death (Finkel, 2005; Kaeberlein et al., 2015; Kennedy et al., 2014). However, with few exceptions, we know relatively little about the factors that determine how age shapes disease risk, why rates of aging (i.e., age‐specific rates of increase) differ among diseases, and why some diseases show relatively few signs of aging at all. In some cases, most notably cancer, we have been able to develop mathematical models that are consistent with age trajectories (Armitage & Doll, 1954; Frank, 2007).

Here, we have presented a large‐scale comparison of human and companion dog mortality. The study findings suggest the dog could be an excellent model to study diverse causes of morbidity and mortality that also affect humans. However, many data are still lacking. A long‐term longitudinal study of aging in domestic dogs, representing a diversity of genotypes and environments, would allow for a more accurate understanding of the promises and pitfalls of the companion dog as a model of human morbidity and mortality.

JMH and DELP designed the experiment. JMH and AF completed the data analysis and made the figures. KEC divided causes of death in the human dataset. DGO provided and assisted with the VetCompass data. JMH wrote the first draft of the manuscript, and all authors commented and revised the manuscript.

The authors declare no conflict of interests.

 

Source:

http://doi.org/10.1111/acel.12737

 

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