Although it is a non-specific procedure that does not identify specific health conditions, it could lead to new biomarkers that clinical laboratories could use for predictive healthcare
Researchers from the Mayo Clinic recently used artificial intelligence (AI) to develop a predictive computational tool that analyzes an individual’s gut microbiome to identify how a person may experience improvement or deterioration in health.
Dubbed the Gut Microbiome Wellness Index 2 (GMWI2), Mayo’s new tool does not identify the presence of specific health conditions but can detect even minor changes in overall gut health.
Built on an earlier prototype, GMWI2 “demonstrated at least 80% accuracy in differentiating healthy individuals from those with any disease,” according to a Mayo news release. “The researchers used bioinformatics and machine learning methods to analyze gut microbiome profiles in stool samples gathered from 54 published studies spanning 26 countries and six continents. This approach produced a diverse and comprehensive dataset.”
The Mayo researchers published their findings in the journal Nature Communications titled, “Gut Microbiome Wellness Index 2 Enhances Health Status Prediction from Gut Microbiome Taxonomic Profiles.”
“Finally, we have a standardized index to quantitatively measure how ‘healthy’ a person’s gut microbiome is,” said Jaeyun Sung, PhD, a computational biologist at the Mayo Clinic Center for Individualized Medicine: Microbiomics Program and senior author of the study in the news release.
“Our tool is not intended to diagnose specific diseases but rather to serve as a proactive health indicator,” said senior study author Jaeyun Sung, PhD (above), a computational biologist at the Mayo Clinic Center for Individualized Medicine: Microbiomics Program in the news release ease. “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.” For microbiologists and clinical laboratory managers, this area of new knowledge about the human microbiome may lead to multiplex diagnostic assays. (Photo copyright: Mayo Clinic.)
Connecting Specific Diseases with Gut Microbiome
Gut bacteria that resides in the gastrointestinal tract consists of trillions of microbes that help regulate various bodily functions and may provide insights regarding the overall health of an individual. An imbalance in the gut microbiome is associated with an assortment of illnesses and chronic diseases, including cardiovascular issues, digestive problems, and some cancers and autoimmune diseases.
To develop GMWI2, the Mayo scientists provided the machine-learning algorithm with data on microbes found in stool samples from approximately 8,000 people collected from 54 published studies. They looked for the presence of 11 diseases, including colorectal cancer and inflammatory bowel disease (IBS). About 5,500 of the subjects had been previously diagnosed with one of the 11 diseases, and the remaining people did not have a diagnosis of the conditions.
The scientists then tested the efficacy of GMWI2 on an additional 1,140 stool samples from individuals who were diagnosed with conditions such as pancreatic cancer and Parkinson’s disease, compared with those who did not have those illnesses.
The algorithm gives subjects a score between -6 and +6. People with a higher GMWI2 score have a healthier microbiome that more closely resembles individuals who do not have certain diseases.
Likewise, a low GMWI2 score suggests the individual has a gut microbiome that is similar to those who have specific illnesses.
Highly Accurate Results
According to their study, the researchers determined that “GMWI2 achieves a cross-validation balanced accuracy of 80% in distinguishing healthy (no disease) from non-healthy (diseased) individuals and surpasses 90% accuracy for samples with higher confidence,” they wrote in Nature Communications.
Launched in 2020, the original GMWI (Gut Microbiome Wellness Index) was trained on a much smaller number of samples but still showed similar results.
The researchers tested the enhanced GMWI2 algorithm across various clinical schemes to determine if the results were similar. These scenarios included individuals who had previous fecal microbiota transplants and people who had made dietary changes or who had exposure to antibiotics. They found that their improved tool detected changes in gut health in those scenarios as well.
“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,” Sung said in the news release.
The Mayo Clinic team is developing the next version of their tool, which will be known as the Gut Microbiome Wellness Index 3. They plan to train it on at least 12,000 stool samples and use more sophisticated algorithms to decipher the data.
More research and studies are needed to determine the overall usefulness of Mayo’s Gut Microbiome Wellness Index and its marketability. Here is a world-class health institution disclosing a pathway/tool that analyzes the human microbiome to identify how an individual may be experiencing either an improvement in health or a deterioration in health.
The developers believe it will eventually help physicians determine how patients’ conditions are improving or worsening by comparing the patients’ microbiomes to the profiles of other healthy and unhealthy microbiomes. As this happens, it would create a new opportunity for clinical laboratories to perform the studies on the microbiomes of patients being assayed in this way by their physicians.
—JP Schlingman
Related Information:
Mayo Researchers Develop Tool That Measures Health of a Person’s Gut Microbiome
Stanford University Scientists Discover New Lifeform Residing in Human Microbiome
Researchers from Stanford University Develop First Synthetic Human Microbiome from Scratch
