麻豆淫院

A network analysis of more than 26,000 dogs and their health conditions helps reveal which diseases tend to go together, providing data that veterinarians and researchers can use to help treat the problems that dogs face, according to a study in the open-access journal PLOS Computational Biology by Antoinette Fang from the Fred Hutchinson Cancer Center in Seattle, Washington, U.S., and colleagues.

As both humans and their pups age, conditions and diseases accumulate, but some are more likely to be comorbid鈥攐r occur together鈥攖han others. To better understand which conditions might co-occur in dogs as they age, the authors of this study used owner-reported data from dogs in the nationwide Dog Aging Project, a long-term study that tracks the health of dogs as they age.

The scientists collected data on 160 health conditions from 26,614 dogs, and created comorbidity networks that showed which diseases tended to pop up together in pups and in what order.

The new networks showed some expected comorbidities. Diabetes tends to co-occur with blindness, for example, and dogs with kidney disease also tend to have hypertension. But the networks also revealed new connections, such as the association between low iron in the blood and an excess of protein in the urine.

Analyzing when the diseases occurred showed that dogs tend to suffer hip dysplasia before osteoarthritis, have dry eye syndrome before eye ulcers, and diabetes before cataracts. While the study relied on dog owner reports, the authors hope that such networks and associations could help guide veterinary practice and give aging researchers new ideas for improving the lives of our canine companions.

The authors note, "Mining owner-reported data from the Dog Aging Project, we built the first large-scale canine comorbidity network, confirming that diabetes often occurs before cataracts and revealing that health problems tend to cluster around a few key diseases as dogs age."

The authors say, "Because pet dogs share our homes, environments and many of our age-related diseases, mapping how their illnesses cluster and cascade offers a powerful window into the same multimorbidity processes that erode human health and points to earlier detection and prevention strategies for people too."