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Genetic prediction technology is revolutionizing how we understand disease risk in our pets, yet companion animal medicine lags behind similar advances in humans and production animals. Why? And what does this mean for veterinary medicine?

In this fascinating conversation with Dr. Peter Muir and Dr. Mehdi Momen, we explore the emerging science of polygenic risk scores – statistical tools that can predict an animal's likelihood of developing complex conditions based on their genetic makeup. Using cruciate ligament rupture in dogs as their primary example, our guests explain how conditions often mistaken as simple injuries actually have significant genetic components. With heritability estimated at 40% for this condition in Labrador Retrievers, the potential for accurate genetic prediction is substantial.

The challenges, however, are equally significant. Dog breeds show remarkable genetic diversity, meaning risk factors that predict disease in one breed may not transfer to another. As Dr. Muir notes, Greyhounds – despite being among the most athletic dogs – rarely suffer cruciate ligament ruptures, highlighting the breed-specific nature of genetic risk. Combined with limited funding and smaller datasets compared to human genomics research, these factors have slowed progress.

Yet the future looks promising. Advanced technologies, artificial intelligence, and multi-omics approaches are enhancing prediction accuracy. Unlike diagnostic tests, polygenic risk scores serve as preventive tools, allowing owners to modify their pets' lifestyle before problems develop – "not scary, just caring," as Dr. Momen eloquently puts it. These advances could transform veterinary practice, requiring future veterinarians to become more versed in bioinformatics and computational science.

Want to understand how genetic testing might help your pet live a healthier life? Subscribe to Veterinary Vertex for more cutting-edge discussions at the intersection of clinical practice and scientific discovery.

AJVR article: https://doi.org/10.2460/ajvr.25.01.0018

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