A Cornell research team is on the verge of transforming how veterinarians detect and manage inflammation in dairy cattle—potentially improving both animal welfare and farm profitability.

Dr. Sabine Mann, a veterinarian and associate professor at Cornell University’s College of Veterinary Medicine, has long seen the need for a practical, cost-effective way to identify inflammation in cows before it progresses into more serious illnesses like mastitis or metritis. Traditional approaches often detect these diseases only after they’ve already begun to cause pain, health decline, and financial loss.

“Cows with excessive, chronic inflammation produce less milk; they may not be able to reproduce as quickly, or they may be more susceptible to disease,” Mann said. “So this kind of undiagnosed inflammation can lead to less efficient and less sustainable dairy farms and less milk in our food supply. We want to be able to detect inflammation before we even have a disease diagnosis—that’s the time where we think we have the most potential for improvement, at a herd level.”

Mann teamed up with immunology specialists Dr. Bettina Wagner and Dr. Anja Sipka to pioneer a new diagnostic tool. The result is a promising blood test that targets specific immune proteins called cytokines, which are elevated in cows experiencing inflammation.

Over the past seven years, the team has developed and refined an assay capable of detecting three distinct cytokines—early signals that the body’s immune system is responding to injury or infection. Now, they are working to broaden the scope of the test by adding chemokines, another group of immune-related proteins that help guide white blood cells to areas of damage or infection.

Dr. Wagner, a veteran in veterinary immunology and a professor in the same department, brings years of experience building diagnostic panels—including those used to detect Lyme disease in dogs and horses. Dr. Sipka, a researcher with expertise in bovine immune responses, is focused on defining the thresholds between beneficial inflammation and harmful immune overreactions in dairy herds.

Although this new test is not yet available for widespread veterinary use, it is currently offered through Cornell’s Animal Health Diagnostic Center to support clinical research. The team is using this phase to collect data and refine the tool, identifying which biomarkers most strongly correlate with key farm outcomes like reduced milk output, increased illness, and reproductive challenges.

The ultimate goal, according to Mann, is to give veterinarians a clearer picture of herd health and equip them with the data needed to make proactive changes.

Understanding the balance of immune function is a major focus of the research. While inflammation is a normal and necessary defense mechanism, some animals have an exaggerated response that can do more harm than good. Pinpointing which cows are prone to this overreaction—and why—is a key question the team hopes to answer through ongoing studies.

Chemokines, for example, act like directional signals in the immune system, telling defensive cells where to go. By tracking their presence, researchers may better understand how the immune system orchestrates its response—and how that might go awry in certain animals.

This work is being made possible through support from multiple funding sources, including the U.S. Department of Agriculture’s National Institute of Food and Agriculture and the Cornell University Agricultural Experiment Station. The latter distributes federal funds designated for agricultural research through the Hatch Act, a system that has supported land-grant universities in protecting the food supply for nearly 140 years.

Additional resources and infrastructure from the state-funded Animal Health Diagnostic Center have also played a crucial role in moving the research forward, Wagner said.

With further development, the team hopes this diagnostic tool will soon become a standard part of herd health management—offering early insight into problems that were once hidden until it was too late to act.