Author: Dr. Audrey Ruple, Associate Professor of One Health Epidemiology and Comparative/Translational Medicine, Department of Public Health, Purdue University
“By studying aging in dogs, we hope to learn how to better match human health span to life span so that we can all live longer, healthier lives,” Ruple said.
Photo: Researchers seek a helping paw for dog aging study (2020). Retrieved from https://www.purdue.edu/newsroom/releases/2020/Q1/researchers-seek-a-helping-paw-for-dog-aging-study.htmlMany opportunities exist in the field of veterinary medical big data where information collected from companion animals, especially dogs, can be used to inform healthcare decisions in humans. Dogs provide an ideal model for translational medicine as they have the most phenotypic diversity and known naturally occurring diseases of all land mammals other than humans. Dogs share a tremendous amount of ancestral genetic sequence with humans, as well as our physical and chemical environments. The level of sophistication of the healthcare system for dogs in the United States is second only to that of humans. Thus, data related to dog health presents many opportunities to discover insights into health and disease outcomes in both dog and human populations.
Many veterinary datasets offer advantages over data sources collected in human populations. As we are all well aware now with ongoing COVID-19 era conversations in nearly every aspect of society, the HIPPA Privacy Act declared medical information, including electronic medical records, protected information. Veterinary patient records are, in contrast, not considered protected health information. Yet our animal companions, especially dogs, share disease outcomes from cancer, eye disorders and infections, including antimicrobial resistant ones, that can be informative for human health research. In fact, naturally occurring diseases in companion animals are often similar — and sometimes identical — to human diseases in relation to the disease etiology, progression and how that disease responds to medical intervention or treatment.
The largest open access dataset in the United States is part of the Dog Aging Project and includes detailed information about individual dog participant’s physical and chemical environments, diet, exercise, behavior and comprehensive health history. In a recent open-access journal article, Veterinary Big Data: When Data Goes to the Dogs, published in Animals as part of the Special Issue Data-Driven Decision Making in Animal Industries, several veterinary medical datasets well suited for use in translational medicine were described in detail, alongside the advantages and disadvantages of each data source.
Datasets from pet hospitals, especially those with hundreds or thousands of clinics that are able to collect data over a geographically diverse area to which other data, such as that on disease spread, can be married offers the opportunity for unique insights. The Veterinary Medical Database (VMDB) is the oldest companion animal health database providing low cost or free access to researchers. There are also a variety of opportunities for datasets from pet insuring companies, individual research projects and other ongoing efforts with interest in a wide variety of questions in translational and human medicine.
No data source is without faults, but veterinary medical big data represents an underutilized resource in translational medicine. Furthermore, employing data from companion animals brought by owners for medical attention may have lesser ethical concerns than research in which diseases are induced to facilitate their study. The use of medical data collected in dog populations will continue to be a rich source of information that can be used to inform our understanding of both dog and human health, longevity and disease outcomes. This means that what treatments and medical interventions we as consumers of human medicine have available may very well be influenced by data which comes from none other than the human’s long-standing best friend — the dog.
ConsumerCorner.2021.Letter.25
