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New tool searches gut microbiome for clues to Alzheimer's disease

New tool searches gut microbiome for clues to Alzheimer's disease


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

Previous research has shown that people with Alzheimer's disease have changes in their gut bacteria as the disease progresses. The newly published cell report This study outlines a computational method to determine how bacterial byproducts, called metabolites, interact with receptors on cells and contribute to Alzheimer's disease.

Dr. Feixion Chen, the founding director of the Cleveland Clinic Genome Center, worked closely with the Luo-Rubo Center for Brain Health and the Center for Microbiome and Human Health (CMHH). The study ranks metabolites and receptors by their likelihood of interacting and how likely the pair is to impact Alzheimer's disease. This data provides one of the most comprehensive roadmaps for metabolite-related disease research to date.

When bacteria break down the food we consume for energy, they release metabolites into our system. Metabolites then interact with and influence cells, promoting cellular processes that can be beneficial or harmful to health. In addition to Alzheimer's disease, researchers have linked metabolites to heart disease, infertility, cancer, autoimmune diseases and allergies.

Preventing harmful interactions between metabolites and our cells can help fight disease. Researchers are working to develop drugs that activate or block metabolites from binding to cell surface receptors. Progress in this approach has been slow due to the vast amount of information required to identify target receptors.

Intestinal metabolites are the key to many physiological processes in our bodies, and all have keys to human health and disease. The problem is that there are tens of thousands of receptors and thousands of metabolites in our system, so manually determining which key goes into which lock is time-consuming and expensive. That's why we decided to use AI. ”

Dr. Feixion Chen, Founding Director of the Genome Center, Cleveland Clinic

Dr. Chen's team believes that known gut metabolites in the human body with existing safety profiles, if widely applied, could provide effective prevention or even intervention approaches for Alzheimer's disease and other complex diseases. I tested whether.

Dr. Yunguang Qiu, the study's lead author and a Cheng Lab postdoctoral fellow, led a team that included CMMH Research Director Dr. J. Mark Brown. James Leverenz, MD, Director of the Cleveland Clinic Luo Lubo Brain Health Center and Director of the Cleveland Alzheimer's Disease Research Center. and neuropsychologist Jessica Caldwell, Ph.D., ABPP/CN. Director of the Women's Alzheimer's Movement Prevention Center at the Cleveland Clinic in Nevada.

Using a type of AI called machine learning, the research team analyzed more than 1.09 million potential metabolite-receptor pairs and predicted how likely each interaction was to contribute to Alzheimer's disease. .

Integrated analysis:

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

The research team investigated the metabolite and receptor pairs most likely to influence Alzheimer's disease in brain cells from Alzheimer's patients.

One of the molecules they focused on is a protective metabolite called agmatine, which is thought to protect brain cells from inflammation and the damage that comes with it. The study found that agmatine most likely interacts with a receptor called CA3R in Alzheimer's disease.

Treatment of neurons affected by Alzheimer's disease with agmatine directly reduced CA3R levels, indicating that the metabolite and receptor interact. Neurons treated with agmatine also had reduced levels of phosphorylated tau protein, a marker of Alzheimer's disease.

Dr. Chen says these experiments demonstrate how his team's AI algorithms can open up new research avenues for many diseases other than Alzheimer's disease.

“Although we focused specifically on Alzheimer's disease, metabolite-receptor interactions are involved in almost all diseases that involve the gut microbiome,” he said. “We hope that our method can provide a framework for advancing the entire field of metabolite-related diseases and human health.” Dr. Chen and his team are currently working on research in human health and Alzheimer's disease. We are further developing and applying these AI technologies to study the interactions between genetic and environmental factors (including food and intestinal metabolites) in diseases, including other complex diseases .


Reference magazines:

Yu Chiu other. (2024). Systematic characterization of the multi-omic landscape between gut microbial metabolites and GPCRomes in Alzheimer's disease. cell report.




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