The Mayo Clinic research team has developed a revolutionary computational tool that can analyze the gut microbiome, a diverse community of trillions of microorganisms in the digestive system, providing valuable insights into overall health.
In a recent publication in Nature Communications, the tool displayed an impressive accuracy of at least 80% in distinguishing between healthy individuals and those with various diseases. The researchers achieved this by studying stool gut microbiome profiles from over 8,000 samples representing a wide range of diseases, geographical locations, and demographic groups.
The tool, Gut Microbiome Wellness Index 2, can detect even subtle changes in gut health, providing crucial insights into a person’s potential progression or recovery from disease. By harnessing bioinformatics and machine learning methods, researchers analyzed gut microbiome profiles from 54 studies across 26 countries and six continents, resulting in a comprehensive and diverse dataset.
This advancement overcomes longstanding challenges in human microbiome research, offering a pivotal opportunity to define what signifies a “healthy” microbiome and pinpoint early indicators of potential health issues. The Gut Microbiome Wellness Index 2 fills a significant void in existing health and wellness measurement tools.
The significance of the gut microbiome in digestion, metabolism, and immune function cannot be overstated. Researchers are increasingly recognizing the link between an imbalanced gut microbiome and various chronic diseases. This tool holds the potential to transform the landscape of healthcare by providing invaluable insights into individual gut health for proactive disease management and overall well-being.
“Finally, we have a standardized index to quantitatively measure how ‘healthy’ a person’s gut microbiome is,” says Jaeyun Sung, Ph.D., the senior author and computational biologist at Mayo Clinic Center for Individualized Medicine’s Microbiomics Program.
“Our tool is not intended to diagnose specific diseases but rather to serve as a proactive health indicator,” he adds. “By identifying adverse changes in gut health before serious symptoms arise, the tool could potentially inform dietary or lifestyle modifications to prevent mild issues from escalating into more severe health conditions or prompt further diagnostic testing. By being able to answer whether a person’s gut is healthy or trending toward a diseased state, we ultimately aim to empower individuals to take proactive steps in managing their own health.”
The tool development process was a meticulously crafted journey, involving the identification of microbial species, the careful selection of the most relevant features, and the optimization of the machine learning model.
The end result is nothing short of groundbreaking—an index that screens a gut microbiome sample and quantifies how closely it resembles that of a healthy (disease-free) or non-healthy (diseased) individual.
To prove its capability, the study team subjected the index to rigorous testing. It was first trialed on a training set of over 8,000 microbiome samples before being validated on a new cohort of 1,140 samples.
Furthermore, the team tested its tool in various clinical scenarios, including post-fecal microbiota transplantation, changes in dietary fiber intake, and antibiotic exposure, showcasing its ability to detect shifts in gut health.
The enhanced Gut Microbiome Wellness Index 2 represents a significant leap forward, incorporating a broader range of data and utilizing advanced computational methods to provide a more precise assessment of gut health and changes in the gut microbiome.
Dr. Sung and his team are committed to further advancing the Gut Microbiome Health Index 2 by expanding its dataset to encompass diverse microbiome samples from a variety of populations. Additionally, they aim to integrate cutting-edge artificial intelligence techniques to significantly improve the tool’s predictive accuracy and adaptability.
Journal reference:
- Daniel Chang, Vinod K. Gupta, Benjamin Hur, Sergio Cobo-López, Kevin Y. Cunningham, Nam Soo Han, Insuk Lee, Vanessa L. Kronzer, Levi M. Teigen, Lioudmila V. Karnatovskaia, Erin E. Longbrake, John M. Davis III, Heidi Nelson & Jaeyun Sung. Gut Microbiome Wellness Index 2 enhances health status prediction from gut microbiome taxonomic profiles. Nature Communications, 2024; DOI: 10.1038/s41467-024-51651-9