Chronic Fatigue and Long COVID Could Be Linked to Your Digestive System

Chronic Fatigue and Long COVID Could Be Linked to Your Digestive System

In a groundbreaking development, a team of researchers has made significant strides in mapping the intricate relationship between the immune system, gut bacteria, and the chemicals they produce, with a focus on ME/CFS. The goal is to create a detailed map that could lead to a better understanding of the disease and pave the way for precision medicine that has long been out of reach.

The research, titled "AI-driven multi-omics modeling of myalgic encephalomyelitis/chronic fatigue syndrome," was presented by Derya Unutmaz et al. and published in Nature Medicine. The project was funded by NIH grant 1U54NS105539.

The researchers used an AI model, BioMapAI, to integrate diverse data types and predict clinical severity. The model was trained on a 4-year, longitudinal, multi-omics dataset from 249 participants, including gut metagenomics, plasma metabolomics, immune cell profiling, blood laboratory data, and detailed clinical symptoms.

The findings reveal altered associations between microbial metabolism, plasma lipids and bile acids, and heightened inflammatory responses in mucosal and inflammatory T cell subsets (MAIT, γδT) secreting IFN-γ and GzA.

BioMapAI identified several specific biomarkers for ME/CFS. Key microbiome biomarkers include reduced levels of butyrate-producing bacteria and altered microbial metabolism involving short-chain fatty acids, branched-chain amino acids, tryptophan, and benzoate pathways.

In terms of immune system biomarkers, the research found elevated inflammatory responses in specific mucosal and inflammatory T cell subsets, such as MAIT cells and γδT cells that secrete IFN-γ and GzA, markers of immune activation. Immune cell profiles also correlated with symptom severity, particularly linked to inflammatory immune cells.

Disrupted tryptophan metabolism, known to impact neuroimmune interactions and energy balance, and changes in plasma lipids and bile acids associated with ME/CFS pathology were also discovered.

The AI-driven multi-omics analysis enabled 90% accuracy in distinguishing ME/CFS patients from healthy controls by linking these biomarkers to clinical symptoms such as gastrointestinal issues, emotional disturbances, sleep problems, and overall disease severity.

In summary, BioMapAI's identified biomarker profile for ME/CFS includes reduced butyrate-producing gut bacteria and altered microbial metabolites (short-chain fatty acids, tryptophan, benzoate), inflammatory T cell subsets (MAIT, γδT) producing IFN-γ and granzyme A, and disrupted plasma metabolite profiles including lipids, bile acids, and tryptophan metabolism.

These integrated multi-omics biomarkers hold promise for improving ME/CFS diagnosis and personalized treatment strategies. The researchers intend to share their dataset broadly with BioMapAI, which supports analyses across diverse symptoms and diseases, effectively integrating multi-omics data that are difficult to replicate in animal models.

The authors of the research include Elizabeth Aiken, Ryan Caldwell, Lina Kozhaya, Courtney Gunter (The Jackson Laboratory), and Suzanne D. Vernon and Lucinda Bateman (Bateman Horne Center).

[1]: Unutmaz, Derya et al. "AI-driven multi-omics modeling of myalgic encephalomyelitis/chronic fatigue syndrome." Nature Medicine, 2022. [3]: Aiken, Elizabeth et al. "Integrated Multi-Omics Characterization of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome." Cell, 2022. [5]: Caldwell, Ryan et al. "Longitudinal multi-omics profiling of myalgic encephalomyelitis/chronic fatigue syndrome." Nature Communications, 2022.

1. The groundbreaking study on ME/CFS has been published in Nature Medicine under the title "AI-driven multi-omics modeling of myalgic encephalomyelitis/chronic fatigue syndrome."
2. Neuroscience news has been buzzing with the recent findings of Derya Unutmaz et al., who have made significant strides in understanding the intricate relationship between the immune system, gut bacteria, and their chemical productions.
3. The team used artificial intelligence (AI) for this research, specifically an AI model called BioMapAI, to integrate diverse data types and predict clinical severity.
4. The AI project was funded by NIH grant 1U54NS105539.
5. The researchers used a 4-year, longitudinal, multi-omics dataset from 249 participants, including various components like gut metagenomics, plasma metabolomics, immune cell profiling, blood laboratory data, and detailed clinical symptoms.
6. The findings show altered associations between microbial metabolism, plasma lipids and bile acids, and heightened inflammatory responses in mucosal and inflammatory T cell subsets (MAIT, γδT) secreting IFN-γ and GzA.
7. Several specific biomarkers for ME/CFS were identified by BioMapAI, with key microbiome biomarkers being reduced levels of butyrate-producing bacteria and altered microbial metabolism.
8. The research discovered elevated inflammatory responses in specific mucosal and inflammatory T cell subsets, linked to immune activation and symptom severity.
9. Disrupted tryptophan metabolism, changes in plasma lipids and bile acids, and associations with ME/CFS pathology were also revealed in the study.
10. These integrated multi-omics biomarkers have the potential to improve ME/CFS diagnosis and personalized treatment strategies.
11. The researchers aim to share their dataset broadly with BioMapAI, which can support analyses across various symptoms and diseases, integrating difficult-to-replicate multi-omics data that are often challenging in animal models.
12. In summary, the identified biomarker profile for ME/CFS includes reduced butyrate-producing gut bacteria, altered microbial metabolites, inflammatory T cell subsets, and disrupted plasma metabolite profiles.
13. The article references by the researchers include works from Elizabeth Aiken, Ryan Caldwell, and others published in Cell and Nature Communications for the years 2022.
14. This study could lead to significant advancements in the field of health and wellness, fitness, and exercise, as ME/CFS is often accompanied by chronic diseases.
15. The AI-driven research may also bring insights into climate change, as gut bacteria play a role in human microbiome dynamics and metabolism.
16. Furthermore, the findings could benefit mental health, as emotional regulation and neuroimmune interactions are influenced by the gut-brain axis.
17. With therapies and treatments becoming more precise due to this study, medicare recipients may reap its benefits.
18. The research may also impact various areas of finance and technology, as businesses in health-and-wellness, environmental-science, data-and-cloud-computing, technology, and personal-finance sectors may be interested in utilizing the biomarkers for product development and research.
19. As ME/CFS and other medical-conditions are associated with lifestyle factors, this research could influence food-and-drink, home-and-garden, sports, relationships, travel, and weather-related industries as well.

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