A new study published in Nature Medicine has identified previously undetectable biomarkers in the gut microbiome that may predict chronic fatigue syndrome (ME/CFS) and long COVID. The research, conducted by a team of scientists led by Dr. Julia Oh, used an artificial intelligence platform to analyze data from 249 individuals with ME/CFS.
The study found that patients with ME/CFS had disrupted interactions between their immune system, metabolism, and gut microbiome. These disruptions were linked to symptoms such as fatigue, sleep abnormalities, dizziness, and chronic pain. The researchers also found that patients with ME/CFS had lower levels of beneficial fatty acids produced in the gut, along with other nutrients essential for metabolism, inflammation control, and energy.
The study used a deep neural network model called BioMapAI to analyze data from stool, blood, and other routine lab tests. The model achieved 90% accuracy in distinguishing individuals with ME/CFS from those without the condition. The researchers also found that patients who were ill for longer periods of time had more entrenched biological disruptions.
The study’s findings provide new insights into the mechanisms underlying ME/CFS and long COVID. They suggest that targeting the gut microbiome and metabolism may be a promising approach to developing personalized treatments for these conditions. The research team plans to share their dataset broadly with BioMapAI, which supports analyses across diverse symptoms and diseases.
The discovery of biomarkers for ME/CFS is significant because it provides a new tool for diagnosis and treatment. However, the study’s findings also highlight the complexity of ME/CFS and long COVID, and the need for further research to fully understand these conditions.
Source: https://medicalxpress.com/news/2025-07-previously-undetectable-biomarkers-gut-microbiome.html