Artificial intelligence links gut bacteria to the development of Alzheimer's disease

 

one In a new study published in Cell Reports, scientists developed a complex systems biology approach combining artificial intelligence (AI), genetics, and multi-omics analysis to investigate how gut metabolites produced by bacteria influence Alzheimer's disease.

This study identifies specific receptors that interact with metabolites in humans and may open new avenues for therapy. This important discovery could lead to the development of new drugs that target these interactions, offering hope for treating or preventing Alzheimer's disease.

Alzheimer's disease is a type of neurodegenerative disease that mostly affects the elderly and is characterized by a decline in cognitive abilities such as memory and thinking. It is characterized by the accumulation of beta-amyloid plaques and tau protein tangles in the brain, which interfere with brain functioning and cause cell death.

The exact cause of Alzheimer's disease is not fully understood, but it is believed that a combination of genetics, lifestyle, and environment affect the brain over time. As the disease progresses, it can affect daily life and independence, making it one of the most common causes of dementia in the elderly.

Previous research has shown that the intestinal flora of people with Alzheimer's disease changes as the disease progresses. The metabolites produced by these bacteria can affect brain health and cause diseases. However, the specific ways in which these metabolites exert their effects are still unknown.

This difference in understanding led to this new study, which aims to define the interaction between metabolites and the human receptors they affect. The study was conducted by Feixiong Cheng and his team, led by experts from the Cleveland Clinic Genome Center, Roruvo Center for Brain Health, and the Center for Microbiome and Human Health.

Researchers used machine learning algorithms to analyze more than a million potential metabolite-receptor pairs to predict the interactions most relevant to diseases. Genetic information, including Mendelian randomization, complements these predictions by identifying cause and receptor involvement.

-Gut metabolites are the key to many physiological functions in our body, and each key holds a lock relevant to human health and disease,” said Cheng. - The problem is that there are tens of thousands of receptors and thousands of metabolites in our body, so finding which key fits the lock is slow and expensive. So we decided to use intelligence.

This study also included experiments using neurons from Alzheimer's patients to test the effects of specific metabolites of the protein tau, an important biomarker of the disease. This versatility allows researchers to identify key disruptions in the gut-brain axis, thereby uncovering treatment targets for Alzheimer's disease.

One of the most interesting results of this study is the identification of G protein-coupled receptors (GPCRs) that interact with metabolites produced by intestinal bacteria. The researchers focused on orphan GPCRs, receptors whose natural operators are unknown, and found that certain metabolites can activate these receptors. This discovery is of particular interest because it opens new avenues for the development of drugs that target these receptors in order to alter their activity to achieve or reduce an anti-inflammatory effect.

Among the metabolites examined, phenethylamine and agmatine stand out for their effects on the tau protein, which is involved in the neurodegenerative features of Alzheimer's disease. Studies have shown that these metabolites can change the level of phosphorylated tau protein in neurons of Alzheimer's patients. In particular, agmatine exhibits protection against the reduction of harmful tau phosphorylation, indicating that it may be a candidate for treatment.

Application of machine learning models is required to predict interactions between more than a million metabolite-receptor pairs. This high level of competition not only facilitates the identification of relevant interventions, but also improves understanding of the complex mechanisms by which the gut microbiota influences the healthy nutrition of the brain. By combining genetic analysis and experimental data, scientists tested these predictions and improved their understanding of the gut-brain axis in the context of Alzheimer's disease.

Although academic writers are committed, they are aware of some limitations. The complexity of the stomach-brain axis means that these findings are preliminary and need further confirmation through experiments and clinical studies. Future studies should be conducted to confirm these interactions in these diseases and to investigate the therapeutic potential of altering this pathway.

Additionally, studies have focused on biochemical interactions at the molecular level without considering the broader physical and environmental factors that may influence these processes in living systems.

However, this study provides an important foundation for understanding how metabolites from gut bacteria influence brain health and disease. The implications of these findings are not limited to Alzheimer's disease, as these models and information can also be used for other diseases of the brain and diseases affected by the gut microbiota.

- We focus on Alzheimer's disease, but metabolite-receptor interactions play a role in nearly all diseases associated with gut microbes," he said. "We hope our method will provide a foundation to support all diseases related to metabolism and human health."

"Systematic characterization of the multi-omics landscape of gut microbial metabolites and GPCRome in Alzheimer's disease", authors of this study are Yunguang Qiu, Yuan Hou, Dhruv Gohel, Yadi Zhou, Jielin Xu, Marina Bykova, Yang Yuxin, James B. Leverenz, Andrew Pieper, Ruth Nusinov, Jessica Z.K. Caldwell, J. Mark Brown and Feixiong Cheng.

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Alzheimer's Disease