Chronic intestinal inflammation has increased in horses and humans in recent years. Inflammatory bowel disease is becoming increasingly common, particularly in horses, and can cause serious health problems. But the diagnosis is currently still complex and stressful for horses.
The diagnosis of Inflammatory Bowel Disease (IBD) in horses is usually made by first observing typical symptoms in affected horses. These include weight loss, loss of performance and pain. This is followed by an endoscopy and a biopsy of the intestinal wall. Diagnosis of IBD is therefore expensive for the horse owner and stressful for the horse as it requires fasting, endoscopy and usually transport to an equine clinic. Another factor that makes diagnosis difficult is the horse’s long gastrointestinal tract. Veterinarians can only examine part of it during endoscopy.
The role of the microbiome in the diagnosis of inflammatory bowel disease
Because current diagnostics are so complex, researchers at the Finnish University of Jyväskylä have developed an innovative approach: They use the composition of the bacterial community (microbiota) in horse feces. Previous studies in other species, including humans, have already shown that microbiota composition can be used to detect chronic intestinal inflammation and monitor disease progression.
In their study „Gut Microbiota Profiling as a Promising Tool to Detect Equine Inflammatory Bowel Disease (IBD)“ The researchers examined the bacterial diversity and composition of fecal samples. These included samples from 27 healthy horses and 49 horses diagnosed with inflammatory bowel disease (IBD). The scientists discovered differences in the composition of the microbiota. They identified certain groups of bacteria that were either more common or less common in horses with inflammatory bowel disease than in healthy horses.
AI as a key technology for chronic intestinal inflammation in horses
The researchers then developed a machine learning model to predict inflammatory bowel disease in horses based on the microbiota composition in fecal samples. Despite the relatively small sample size, this made it possible to diagnose the problem much better than the methods currently used to detect chronic intestinal inflammation, the scientists concluded. “This AI-based neural network model predicted IBD in the test samples with 100 percent accuracy,” Tiina Sävilä, a postdoctoral researcher at the University of Jyväskylä, tells ScienceDaily. This creates the basis for future research and the development of a reliable diagnostic tool. The next step is to further test the model with a larger number of samples and improve its performance.
Kerstin WackermannEditor
The editor behind the big advice topics. Expert in equine medicine, from respiratory to cysts. Well connected with veterinarians, universities, colleges, experts and experts, she is a specialist journalist who has also intensively dealt with and researched horse keeping issues at St.GEORG for more than 20 years.
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