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Cleveland Clinic researchers are using artificial intelligence to uncover the link between the gut microbiome and Alzheimer's disease.

Previous studies showed that people with Alzheimer's disease experience changes in their gut bacteria as the disease develops. The Cell Reports study outlines a computational method to determine how bacterial byproducts called metabolites interact with receptors on our cells and contribute to Alzheimer's disease.

Feixiong Cheng, PhD, inaugural director of the Cleveland Clinic Genome Center, worked closely with the Luo Ruvo Center for Brain Health and the Center for Microbiome and Human Health (CMHH). The study ranks metabolites and receptors by the likelihood they will interact with each other, and the likelihood that the pair will influence Alzheimer's disease. The data provides researchers with one of the most comprehensive roadmaps to studying metabolite-associated diseases to date.

What is a gut metabolite?

Bacteria release metabolites into our systems as they break down the food we eat for energy. The metabolites then interact with and influence cells, fueling cellular processes that can be helpful or harmful to our health. In addition to Alzheimer's disease, researchers have connected metabolites to heart disease, infertility, cancers and autoimmune disorders and allergies.

Preventing harmful interactions between metabolites and our cells could help fight disease. Researchers are working to develop drugs to activate or block metabolites from connecting with receptors on the cell surface. Progress with this approach is slow because of the vast amount of information needed to identify a target receptor.

"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," says Dr. Cheng, staff in Genomic Medicine. "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." The team used AI to test whether well-known gut metabolites with existing safety profiles offer effective prevention or even intervention approaches for Alzheimer's disease or other complex diseases.

Using AI to unlock the gut-brain connection

Study first author and Cheng Lab postdoctoral fellow Yunguang Qiu, PhD, spearheaded a team that included J. Mark Brown, PhD, Director of Research, CMMH; James Leverenz, MD, Director of Cleveland Clinic's Luo Ruvo Center for Brain Health and the Director of the Cleveland Alzheimer's Disease Research Center; and neuropsychologist Jessica Caldwell, PhD, ABPP/CN, Director of the Women's Alzheimer's Movement Prevention Center at Cleveland Clinic Nevada.

The team used a form of AI called machine learning to analyze over 1.09 million potential metabolite-receptor pairs and predict the likelihood that each interaction contributed to Alzheimer's disease.

The analyses integrated:

• Genetic and proteomic data from human and preclinical Alzheimer's disease studies
• Different receptor protein structures and metabolite shapes
• How different metabolites affect patient-derived brain cells

Checking the math in brain cells

The team investigated the metabolite-receptor pairs with the highest likelihood of influencing Alzheimer's disease in brain cells derived from patients with Alzheimer's disease.

One molecule they focused on is a protective metabolite called agmatine, thought to shield brain cells from inflammation and associated damage. The study found agmatine was most likely to interact with a receptor called CA3R in Alzheimer's disease.

Treating Alzheimer's-affected neurons with agmatine directly reduced CA3R levels, indicating the metabolite and receptor influence each other. Neurons treated with agmatine also had lower levels of phosphorylated tau proteins, a marker for Alzheimer's disease.

Dr. Cheng says these experiments demonstrate how his team's AI algorithms can pave the way for new research avenues into many diseases beyond Alzheimer's.

"We specifically focused on Alzheimer's disease, but metabolite-receptor interactions play a role in almost every disease that involves gut microbes," he says. "We hope that our methods can provide a framework to progress the entire field of metabolite-associated diseases and human health." Now, Dr. 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.

About this study

Yunguang Qiu, PhD, a postdoctoral fellow at the Cheng Lab, is the first author of this study, which was supported by the National Institute of Neurological Disorders and Stroke (RF1NS133812) and the National Institute on Aging (U01AG073323, R01AG066707. R01AG076448, R01AG082118, RF1AG082211, R01AG084250, and R21AG83003) under the National Institutes of Health (NIH).