Researchers at the University of Jyväskylä, Finland, are developing a promising method to support the diagnosis of inflammatory bowel diseases (IBD) in horses. Awareness of the prevalence of IBD in both humans and animals has increased in recent decades, and the need for effective and affordable diagnostic methods has become increasingly urgent. This study, published in Animals, is the first to show an association between the gut microbiota composition and chronic types of IBD in horses.
Inflammatory bowel diseases (IBD) have become more common in both humans and animals. IBD is now a fairly common disease also in horses, causing serious welfare challenges such as weight loss, decreased performance, and pain-related behaviors. Symptoms can lead to premature retirement and even euthanasia of the horse. IBD is usually diagnosed by observing general symptoms and ultimately by endoscopy and examining a biopsy taken from the intestinal wall.
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”Diagnosing IBD is also expensive for the owner and stressful for the horse, as it requires fasting, endoscopy and usually transportation to a horse hospital,” explains Academy Research Fellow Silva Uusi-Heikkilä from the University of Jyväskylä. Furthermore, endoscopy is challenging because an adult horse has a long gastrointestinal tract and most of it remains unexplored during endoscopy for practical reasons.
Microbiota composition
Researchers at the University of Jyväskylä explored the opportunities to use the composition of the bacterial community, or microbiota, in horse fecal samples as a non-invasive diagnostic tool for IBD. Studies in other species, such as humans, have shown that the gut microbiota composition can be used to detect IBD and the progression of the disease. Based on this knowledge, researchers analyzed the microbiota composition of horse fecal samples to determine if that can indicate the presence of IBD.
”We observed differences in the composition of the gut microbiota between horses with IBD and healthy horses,” explains Uusi-Heikkilä. The relative abundances of certain bacterial groups were found to either increase or decrease in horses with IBD, she adds.
Artificial intelligence
Using microbiota composition assessments, the researchers developed a machine learning model to predict IBD based on the microbiota species composition in fecal samples.
”This AI-based neural network model predicted IBD in the test samples with 100% accuracy,” says Postdoctoral Researcher Tiina Sävilammi from the University of Jyväskylä. The next step is to further test the model and to improve its performance with more samples, she adds.
The researchers’ promising results suggest that in the future, analyzing the species composition of microbiota in fecal samples could become an accurate, cost-effective, and non-invasive method to support screening IBD in horses. This advancement could reduce the stress and financial burden associated with current diagnostic methods, benefiting both horses and their owners.
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