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2 min read Grant Period: January 1, 2026 - December 31, 2027 Active Grant

03424: Genetic Investigation of Acquired Urinary Incontinence in Dogs

Urethral sphincter mechanism incompetence (USMI) is the most common acquired urinary incontinence (UI) in female dogs. The loss of hormones after a female dog is neutered (a.k.a. spayed) is considered a major contributing factor to USMI. USMI is much more common in certain breeds, indicating that it also has a genetic basis. We want to understand which genes contribute to risk of developing USMI, and how this genetic risk combines with hormonal factors to influence development of incontinence. To prepare for the proposed project, we used genomic data from the Golden Retriever Lifetime Study (GRLS) and the Dog Aging Project (DAP) to identify genetic associations with USMI. Our results highlighted genes connected to extracellular matrix function and a non-coding RNA molecule of unknown function. Extracellular matrix is the support structure that holds all of our cells together, and is critically important for the function of connective tissue body-wide, not just within the urethra. If USMI is a disorder of ECM dysfunction, it suggests that dogs with USMI may be at risk for other disorders affecting connective tissue, like ligament rupture or osteoarthritis. Validation of these findings in an independent cohort is critical. In this project, we aim to validate the associations we discovered in GRLS and DAP data in a dog breed at high risk for USMI, the Doberman Pinscher. Because we have no information about the non-coding RNA that is also strongly associated with this condition, our second aim is to demonstrate its presence in bladder or urethra of affected and unaffected dogs, plausibly linking it to USMI. The rationale for this work stems from concerns by owners and veterinarians that neutering increases risk of various disorders, including incontinence, and should be delayed or avoided in certain breeds. This work will begin to provide a much-needed mechanistic explanation for observed variations in disease risk that can be used to make evidence-based healthcare decisions.