summary: Researchers are pioneering the use of artificial intelligence to investigate how the gut microbiome influences Alzheimer’s disease. Their latest research uses AI to analyze how metabolites produced by gut bacteria interact with cell receptors and may contribute to the development of Alzheimer’s disease. Masu.
In this study, we identified key metabolite-receptor pairs, tested their effects on neurons affected by Alzheimer’s disease, and demonstrated the protective effects of certain metabolites, such as agmatine. This discovery opens new avenues for understanding and potentially treating Alzheimer’s disease and other diseases influenced by gut microbiome interactions.
Important facts:
- This study utilized AI to evaluate more than 1.09 million potential interactions between metabolites and cellular receptors and identify those most likely to impact Alzheimer’s disease.
- Key findings include the identification of agmatine, a metabolite that interacts with CA3R receptors and exhibits potential protective effects against brain inflammation and damage associated with Alzheimer’s disease.
- This study highlights the broader implications of metabolite-receptor interactions and suggests that they play a role in a variety of diseases and may lead to new therapeutic approaches.
sauce: cleveland clinic
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.
“Gut metabolites are the key to many physiological processes in our bodies, and all have keys to human health and disease,” said Dr. Chen, a genomic medicine staff member.
“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. 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 postdoctoral fellow at Cheng Lab, 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 receptors (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 associated damage. 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 field of metabolite-related diseases and human health as a whole.”
Currently, Dr. Chen and his team are studying the interactions between genetic and environmental factors (including food and gut metabolites) on human health and disease, including Alzheimer’s disease and other complex diseases. We are further developing and applying these AI technologies to achieve this goal.
Funding: Dr. Yunguang Qiu, a postdoctoral fellow in the Cheng lab, is the study’s first author and was supported by the National Institute of Neurological Disorders and Stroke (RF1NS133812) and the National Institute on Aging (U01AG073323, R01AG066707. R01AG076448, R01AG082118). Masu. , RF1AG082211, R01AG084250, and R21AG83003) are under the jurisdiction of the National Institutes of Health (NIH).
About this AI and Alzheimer’s disease research news
author: alicia reale
sauce: cleveland clinic
contact: Alicia Reale – Cleveland Clinic
image: Image credited to Neuroscience News
Original research: Open access.
“Systematic characterization of the multiomic landscape between gut microbial metabolites and GPCRomes in Alzheimer’s disease” by Feixiong Cheng et al. cell report
abstract
Systematic characterization of the multiomic landscape between gut microbial metabolites and GPCRomes in Alzheimer’s disease
highlight
- Machine learning model predicts 1.09 million gut metabolite-GPCR pairs
- Multi-omics analysis identifies GPCRs and intestinal metabolites associated with Alzheimer’s disease
- Agmatine reduces C3AR and p-tau levels in patient iPSC-derived neurons
- Phenethylamine reduces p-tau in iPSC-derived neurons of Alzheimer’s disease patients
summary
Changes in the size and properties of gut microbial metabolites are thought to be involved in Alzheimer’s disease (AD), but the host receptors that sense and respond to these metabolites are poorly understood.
Here, we develop a systems biology framework that integrates machine learning and multi-omics to identify molecular relationships between gut microbial metabolites and non-olfactory G protein-coupled receptors (referred to as ‘GPCRomes’). .
We evaluate 1.09 million metabolite-protein pairs connecting 408 human GPCRs and 335 gut microbial metabolites.
Using genetics-derived Mendelian randomization and integrated analysis of human brain transcriptome and proteome profiles, we demonstrate that an orphan GPCR (i.e. GPR84) is a potential drug target for Alzheimer’s disease and that triacanthin has been experimentally It was identified that it activates GPR84.
We demonstrate that phenethylamine and agmatine significantly reduce tau hyperphosphorylation (p-tau181 and p-tau205) in Alzheimer’s disease patient-induced pluripotent stem cell-derived neurons.
This study demonstrates a systems biology framework for uncovering GPCR targets of the human gut microbiota in Alzheimer’s disease and other complex diseases when broadly applied.
