Abstract
There is growing interest in the use of molecular features as predictors of age, age-related disease risk and mortality. A major shortcoming of this field, however, is the lack of suitable translational research models to identify and understand the underlying mechanisms of these predictive biomarkers in human populations. In particular, we lack a system which, like humans, is genetically variable, lives in diverse environments, and experiences age-related chronic conditions treated in the context of a sophisticated health care system. Here, we present results from our analysis of data from the Dog Aging Project (DAP), a long-term longitudinal study of aging in companion dogs. Using longitudinal survival models on data from 937 dogs of the deeply phenotyped Precision Cohort within the DAP, we present the striking finding of a strong, highly significant positive correlation between the effect of individual metabolites on all-cause mortality in humans, and the association of those same metabolites on all-cause mortality in dogs. We also find that across these independent human studies, the biomarkers identified are also highly correlated, strongly suggesting a general signature of mortality within the plasma metabolome across humans, and now in dogs as well. Given the many similarities between dogs and humans with respect to genetics, environment, disease, and disease treatment, and the fact that dogs are so much shorter lived than humans, we argue that dogs represent an extremely valuable translational model in our ongoing effort to understand the underlying molecular causes and consequences of age-related morbidity and mortality in humans.