How Useful is Genetic Testing?

Hello, Summarians!

It is possible to run a lot of high-tech tests. The question can be “Is it worth it?” Studies like these can help us sort through the hype.

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Genetic Testing in Pets.

The commercial genetic testing market for companion animals has grown significantly since the sequencing of domestic dog and cat genomes in the early 2000s, with the market value projected to rise from $322 million in 2022 to $640 million by 2030. This growth is fueled by advances in genetic technology, increasing affordability, and higher pet adoption rates, which often leave owners with limited knowledge of their pets' histories. Direct-to-consumer (D2C) genetic testing kits are easily accessible online and through third-party platforms like Amazon and Chewy, offering pet owners information about their pets’ breed composition and health-related genetic risks. 

Health-related tests are particularly emphasized, potentially influencing veterinary medicine as owners might make care decisions without consulting a veterinarian. Although concerns have been raised about the implications for animal welfare, research indicates that owners tend to focus more on breed information than health data. Companies are also integrating services into veterinary care, promoting personalized medicine, and collaborating with veterinary practices to improve the standard of care. Genetic testing has demonstrated clinical utility by identifying risks such as specific heart conditions in certain breeds, enabling informed care decisions and proactive health measures. 

However, challenges remain in the industry's transparency, regulatory oversight, and veterinarians’ confidence in interpreting genetic results. Some tests report genetic variants with limited scientific backing, raising credibility issues. Standards have been proposed to address these concerns, but their adoption is uncertain. Veterinary care providers (VCPs) report variability in confidence when interpreting results, particularly between species and test types, reflecting gaps in knowledge and training. These gaps are more pronounced in cat-related genetic testing due to its relatively recent introduction compared to dog testing. 

A study investigating VCP perspectives found that veterinarians often assist clients in understanding genetic test results, even when not directly involved in ordering the tests. This highlights the need for integrating D2C genetic testing knowledge into veterinary education and practice. While the study underscores the potential of genetic testing to enhance veterinary care, it also reveals limitations, such as reliance on self-reported data and a cross-sectional design that limits longitudinal insights. Future research should focus on improving veterinarians' genetic counseling skills, addressing species-specific challenges, and establishing regulatory and quality assurance standards. 

Overall, bridging the gap between genetic companies, veterinarians, and pet owners is essential for realizing the full benefits of genetic testing. Clearer communication, targeted training, and standardized guidelines could ensure that genetic testing becomes a valuable tool in advancing veterinary care. 

Bennett, N. E., Johnson, E. A., & Gray, P. B. (2024). Veterinary care providers recognize clinical utility of genetic testing but report limited confidence in interpreting direct-to-consumer results. American Journal of Veterinary Research https://doi.org/10.2460/ajvr.24.09.0265 

Bottom line — Can be useful but has limitations

Vet Techs and Moral Distress

The study aimed to document veterinary technicians' (VTs') experiences with medical futility and its impact on moral distress and attrition. A 56-question anonymous survey was distributed among members of the National Association of Veterinary Technicians in America in early 2023, yielding 1,944 responses (22% response rate). Nearly all respondents reported encountering futile treatments during their careers, with most having provided such treatments, often against their conscience. This experience caused moderate to severe stress in a majority of respondents, leading nearly half to consider leaving their positions due to moral distress, while over half knew someone who left the profession for similar reasons. 

The study highlights the widespread occurrence of medical futility in veterinary medicine, the moral distress it causes, and its role in contributing to burnout and attrition among VTs. Burnout, characterized by emotional exhaustion, depersonalization, and diminished personal accomplishment, was prevalent, with many VTs reporting adverse emotional and physical effects, including self-medication and suicidal ideation. The constrained sense of agency, lack of professional autonomy, and pressure to provide futile treatments despite personal reservations emerged as significant contributors to moral distress. 

Differences in how veterinarians and technicians define futility were noted, reflecting their respective roles and value structures. While veterinarians emphasized physiological outcomes, VTs focused on patient suffering and quality of life. The lack of training in addressing the emotional and ethical challenges associated with medical futility exacerbates the issue. Strategies to address these challenges include fostering psychological safety, improving communication, and integrating VTs into decision-making processes. 

The study underscores the need for structural changes in veterinary practices to better support VTs, enhance their autonomy, and address moral distress to improve retention. Limitations of the study include its cross-sectional design, potential selection bias, and reliance on self-reported data. Future research should explore the evolving values of veterinary professionals, cultural and socioeconomic influences, and ways to strengthen VT autonomy and shared decision-making roles. Addressing these issues is vital to mitigating burnout and ensuring the sustainability of the veterinary profession amidst a growing workforce shortage. 

Peterson, N. W., Foltz, K., Moses, L., & Boyd, J. W. (2025). Veterinary technicians report in a survey how futile veterinary treatments contribute to their moral distress and impact their professional and personal lives. Journal of the American Veterinary Medical Association https://doi.org/10.2460/javma.24.10.0659 

Bottom line — This needs to be addressed or we may have even greater issues.

AI — Helpful or Not?

Artificial intelligence (AI) is an emerging technology with the potential to transform small animal veterinary medicine by addressing key challenges in the field. Four primary use cases—diagnostic imaging, early disease detection, administrative support, and disease surveillance—illustrate varying levels of progress and practical value creation. 

In diagnostic imaging, AI has advanced significantly, with applications in radiomics providing support for radiologists by identifying critical features in images and improving workflow efficiency. These tools enhance diagnostic capabilities while allowing specialists to validate outputs, reducing explainability concerns. This use case is already delivering tangible value and is well beyond the hype stage. 

For early disease detection, AI models aim to predict disease risk at an individual level based on demographics and clinical data, enabling earlier diagnosis and intervention. However, progress is hindered by limited and biased data, as well as the "black box" nature of many algorithms, which erodes trust. While promising, this area is still in its infancy in terms of practical implementation. 

Administrative workload reduction through AI has shown substantial promise, with tools automating tasks like note-taking, scheduling, and inventory tracking. Speech recognition and natural language processing technologies are mature and widely adopted, providing immediate value to veterinary practices. AI-powered chatbots for client communication further enhance efficiency, though concerns about accuracy and privacy persist. 

Disease surveillance benefits from AI’s ability to process large, complex datasets, enabling the monitoring of outbreaks and trends at scale. Despite notable examples of success, such as tracking acute vomiting in dogs, this use case faces challenges in data availability and quality, which limit its broader application. 

Overall, AI’s impact varies across these use cases, with diagnostic imaging and administrative tasks showing maturity, while early disease detection and disease surveillance remain in earlier stages of development. The main barrier to broader AI adoption in small animal medicine is the lack of high-quality, coherent data. Addressing this will require collaborative efforts to improve electronic health data collection and sharing, paving the way for AI-driven advancements in veterinary medicine. 

Albergante, L., O’Flynn, C., & De Meyer, G. (2025). Artificial intelligence is beginning to create value for selected small animal veterinary applications while remaining immature for others. Journal of the American Veterinary Medical Association https://doi.org/10.2460/javma.24.09.0617 

Bottom line — Potentially useful for diagnostic imaging.

Just putting things in perspective …