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Cleveland Clinic researchers are using artificial intelligence to confirm the link between the gut microbiome and Alzheimer’s disease.
Using a variant of AI called machine learning, the team scrutinized nearly 1.1 million potential metabolite-receptor pairs to forecast the probability of each interaction influencing Alzheimer’s disease. The data provides one of the most comprehensive roadmaps to studying metabolite-associated diseases to date, the authors claim.
“Our findings provide further weight to re-purposing this existing FDA-approved drug as a novel treatment for Alzheimer’s, which is in great need of new therapies,” said Feixong Cheng, PhD, who led the research.
“Gut metabolites are the key to many physiological processes in our bodies, and for every key there is a lock for human health and disease,” Cheng said. “The problem is that we have tens of thousands of receptors and thousands of metabolites in our system, so manually figuring out which key goes into which lock has been slow and costly. That’s why we decided to use AI.”
Cheng’s team tested whether well-known gut metabolites in the human body with existing safety profiles may offer effective prevention or even intervention approaches for Alzheimer’s disease or other complex diseases if broadly applied.
“We specifically focused on Alzheimer’s disease, but metabolite-receptor interactions play a role in almost every disease that involves gut microbes,” he said. “We hope that our methods can provide a framework to progress the entire field of metabolite-associated diseases and human health.” Now, Cheng and his team are further developing and applying these AI technologies to study interactions between genetic and environmental factors (including food and gut metabolites) on human health and diseases, including Alzheimer’s disease and other complex diseases.
Alzheimer’s disease currently affects more than six million Americans, and the total is projected to triple by 2050, underscoring the need for rapid development of new prevention and treatment strategies.