Scientific Results: Rationale and design of the Dog Aging Project precision cohort: a multi-omic resource for longitudinal research in geroscience
July 30, 2025 - 8 minutes readJena Prescott Jena Prescott GeroScience This paper introduces our Precision Cohort, which collects important biological information from dogs in our study group. We collect samples like blood samples, fecal samples, and saliva to look at their genome (DNA sequences), metabolome (how their bodies process substances), microbiome (the community of microbes in their bodies), and epigenome (how their genes are expressed). The goal is to see how these systems change as dogs get older. What we did: Scientific goals: The research platform and protocols are designed to collect high quality biological samples from a large, diverse population of dogs in order to meet the following scientific goals: This paper describes the methods the Dog Aging Project team is using to achieve research goals. Although the team doesn’t have scientific results yet, this paper explains how your participation is helping to build a robust research platform that will make critical discoveries possible. Thus, your involvement is crucial for the following reasons: 1. You and your dog are making scientific history If you’re part of the Precision Cohort or you’ve given samples through the Dog Aging Project, you’re helping researchers gather some of the most detailed information ever collected about companion dogs. This information includes data about metabolism, gut bacteria, and DNA, similar to what scientists use in studies about aging in humans. 2. The goal is better health, not just longer life. This research aims to understand how dogs age, focusing not just on how long they live, but also on how healthy they are as they age. By looking at the data over time, scientists hope to discover early signs of age-related changes and diseases. This could help develop ways to prevent issues, detect them early, and provide personalized care. 3. No changes in your dog’s care are needed right now! This paper is about the study’s design and not about a specific treatment or change in care. While you don’t need to do anything different at the moment, your participation is helping to build knowledge that could one day lead to better veterinary care and a better quality of life for all dogs. A significant challenge in multi-omic geroscience research is the collection of high quality, fit-for-purpose biospecimens from a diverse and well-characterized study population with sufficient sample size to detect age-related changes in physiological biomarkers. The Dog Aging Project designed the precision cohort to study the mechanisms underlying age-related change in the metabolome, microbiome, and epigenome in companion dogs, an emerging model system for translational geroscience research. One thousand dog-owner pairs were recruited into cohort strata based on life stage, sex, size, and geography. We designed and built a novel implementation of the REDCap electronic data capture system to manage study participants, logistics, and biospecimen and survey data collection in a secure online platform. In collaboration with primary care veterinarians, we collected and processed blood, urine, fecal, and hair samples from 976 dogs. The resulting data include complete blood count, chemistry profile, immunophenotyping by flow cytometry, metabolite quantification, fecal microbiome characterization, epigenomic profile, urinalysis, and associated metadata characterizing sample conditions at collection and during lab processing. The project, which has already begun collecting second- and third-year samples from precision cohort dogs, demonstrates that scientifically useful biospecimens can be collected from a geographically dispersed population through collaboration with private veterinary clinics and downstream labs. The data collection infrastructure developed for the precision cohort can be leveraged for future studies. Most important, the Dog Aging Project is an open data project. We encourage researchers around the world to apply for data access and utilize this rich, constantly growing dataset in their own work.Author
Who worked on this research?
Amber J. Keyser
Paul Litwin
Matthew D. Dunbar
Robyn McClelland
Audrey Ruple
Holley Ernst
Brianna L. Butler
Mandy Kauffman
Anne Avery
Benjamin R. Harrison,
Maria Partida-Aguilar
Brianah M. McCoy
Elizabeth Slikas
Ashlee K. Greenier
Efrat Muller
Yadid M. Algavi
Tal Bamberger
Kate E. Creevy
DAP Consortium
Elhanan Borenstein
Noah Snyder-Mackler
Daniel E. L. PromislowWhere was it published?
What is this paper about?
What do these results mean for me and my dog?
Where can I learn more?
Abstract