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How old is your dog, really? Predicting age through methylation

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Loyal team
by Loyal team

We know biological samples can tell us about our dog’s health and breed ancestry, but is the saliva in your dog’s mouth enough to tell us your dog’s age and birthday? The answer is, in some ways, yes.

In Loyal’s X-Thousand Dogs study—XTD for short—we collected saliva samples from roughly 1,600 dogs of 187 different breeds in 48 US states and health information from their science-loving humans, including a dog named Mazel and his pet parent Abigail. One aspect of this project was measuring DNA methylation and determining a methylation age—a measure of the impact of lifestyle, diet and environment on a dog’s health and longevity.

This is important in several ways. For dogs that were adopted as adults and who have unknown birthdays, determining methylation age might give us a more accurate estimate of chronological age, and help us make choices about preventative healthcare. And someday, with further research, methylation age might help us not only measure the impact of lifestyle and environment of healthspan and lifespan but guide us in making healthier lifestyle and nutritional choices for our dogs. For all dogs, using information directly from a dog’s biology allows you to use snippets of insights over time to evaluate the impact of your dog’s lifestyle and environment on their health and aging.

Mazel is a study participant with an unknown age

Who is Mazel? Mazel is a brilliant and energetic 10 lb. mixed breed dog with a long back, who resembles a terrier. He was adopted from a shelter in July 2010 as a young adult, but his true age and birthday is unknown. Mazel loves hiking in the hills and exploring, but he’s slowing down and not chasing rabbits anymore. 

Abigail, Mazel’s pet parent, describes him at his current age as “sometimes a little arthritic.” She says, “He’s one of those dogs who is longer than he is tall, and he will throw out his back sometimes. That limits him.”

He seemed pretty young, but no one knew his age for certain. Like most dogs with unknown backgrounds, guesses from friends and family—and even from the vet—might all be different. Since the risk of health problems in dogs grows with age, it would be helpful to have a more accurate way to estimate how old dogs like Mazel really are.

X-Thousand Dogs builds our understanding of aging through epigenetics and methylation

One possible way of doing this is through epigenetics. The passage of time and environmental factors change the structure of our dogs’ DNA in ways that influence how their genes work. One such change is methylation, the process where methyl groups are added to DNA (as in the animation below). 

An animation captioned: DNA Methylation. DNA methylation changes when a methyl group is added or removed to CpG sites. These changes allow us to observe the impact of lifestyle and the environment on dogs as they age. Below the caption is an illustration of a dark blue DNA strand with one nucleotide highlighting red. A box shows a zoomed in version of the nucleotide as a cytosine that is adding and taking away a methyl group. Below this animation is the DNA sequence -AAATACACACCCGAGAA-
DNA methylation changes when a methyl group is added or removed to CpG sites. These changes allow us to observe the impact of lifestyle and the environment on dogs as they age

Methylation age is closely related to chronological age,and both increase steadily with time. Unlike chronological age, which depends only on time, methylation age reflects the impact of environment, diet, and many other factors on a dog’s DNA. This is why the methylation age and chronological age are usually different for any individual dog. In our XTD study results, we call methylation age the estimated age.

The XTD study was able to show that methylation age can predict chronological age in dogs. Using the largest methylation dataset in dogs to date, we built on previous research to confirm that changes in DNA over time can tell us the chronological age of dogs when we don’t know their date of birth.

How does age prediction work?

Based on information from the shelter, Abigail estimates that Mazel was born in August 2009, but she’d always suspected he was older. When she swabbed Mazel earlier this year for XTD, Mazel’s methylation age was 9 months younger than his reported age. The model suggests Mazel’s age is closer to 12 years and 3 months. Rather than older, Mazel was actually younger than the shelter and Abigail expected.

Mazel's age prediction results on a graph, showing a linear dark blue line for all dogs (represented by smaller, lighter blue dots). The graph shows that Mazel's Predicted age through methylation was slightly below 12 years old (closer to 11 years old), and his Reported age was a little over 12 years old.
Mazel’s age prediction results from X-Thousand Dogs—you can see his estimated methylation age on the vertical axis and reported age from his pet parent Abigail on the horizontal axis

While it’s useful to know how old a dog is more precisely than just a guess based on how he or she looks, chronological age isn’t a perfect predictor of health status. Age affects every dog differently. Just as there are people running marathons in their 80s while others experience serious age-related health problems much younger, some dogs are healthier and stronger than others at the same age.

Beyond chronological age, it would be useful for vets and dog owners to have a reliable measure of age, how much age has affected a particular dog, and what their risk of age-related health problems truly is.

What does methylation age prediction mean for my dog’s health?

It’s possible that methylation age may reflect environmental factors and their impact on health status better than the length of time a dog has lived. Because methylation age is influenced by environmental and lifestyle factors, not just time, it could tell us more about the health status of individual dogs than their chronological age does. This measure of age through methylation could guide us in decisions about medical tests and treatments, diet, activity levels, and other factors that might extend healthspan and lifespan for our dogs. 

Methylation will likely be an important component of measuring aging, and in adding to our understanding of this process in dogs, the XTD study has opened up more avenues of research for exploration into early cancer detection and environmental factors that impact DNA methylation and aging.

In addition to looking at methylation, the saliva samples we collected in the XTD study allowed us to analyze the oral microbiome of participants—the population of bacteria that live in the mouth. These bacteria can perform important roles in promoting health, but imbalances in the oral ecosystem can also increase the risk of disease. For example, Desulfomicrobium orale (D. orale) is linked to lower quality oral health (Oba 2021). 

The population of bacteria in the mouth can also reflect and influence the systemic health of an individual. Understanding this ecology in dogs may help us to better identify and manage, or even prevent, both oral and systemic disease.

Study participant contributions have a huge impact on advancing aging research

Abigail was very excited to be a part of this research study and to learn a little more about her dog. Mazel didn’t have much to say about the results, but he did enjoy the treat that came with the test kit. Both Abigail and Mazel, along with all the other XTD participants, have made a significant contribution to our understanding of dog aging and our efforts to find better ways to measure aging and to predict and prevent age-related health problems.

At Loyal, we’re continuing to find ways to understand the connection between your dog’s health and aging and its impact on lifespan. We look forward to continuing to share our research that contributes to the future of health and longevity in dogs.

Mazel at the beach

Sources

Oba, P.M., Carroll, M.Q., Alexander, C. et al. Microbiota populations in supragingival plaque, subgingival plaque, and saliva habitats of adult dogs. anim microbiome 3, 38 (2021). https://doi.org/10.1186/s42523-021-00100-9

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