Michael Harrop
Well-known member
https://medicalxpress.com/news/2025-07-previously-undetectable-biomarkers-gut-microbiome.html#google_vignette
https://www.nature.com/articles/s41591-025-03788-3
https://www.nature.com/articles/s41591-025-03788-3
The findings—potentially relevant to long COVID due to its similarity with ME/CFS—come from data on 249 individuals analyzed using a new artificial intelligence (AI) platform that identifies disease biomarkers from stool, blood, and other routine lab tests.
"Our study achieved 90% accuracy in distinguishing individuals with chronic fatigue syndrome, which is significant because doctors currently lack reliable biomarkers for diagnosis,"
"Some physicians doubt it as a real disease due to the absence of clear laboratory markers, sometimes attributing it to psychological factors."
"Our data indicate these biological disruptions become more entrenched over time," Unutmaz said. "That doesn't mean longer-duration ME/CFS can't be reversed, but it may be more challenging."
Abstract
Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a chronic illness with a multifactorial etiology and heterogeneous symptomatology, posing major challenges for diagnosis and treatment.
Here we present BioMapAI, a supervised deep neural network trained on a 4-year, longitudinal, multi-omics dataset from 249 participants, which integrates gut metagenomics, plasma metabolomics, immune cell profiling, blood laboratory data and detailed clinical symptoms. By simultaneously modeling these diverse data types to predict clinical severity, BioMapAI identifies disease- and symptom-specific biomarkers and classifies ME/CFS in both held-out and independent external cohorts. Using an explainable AI approach, we construct a unique connectivity map spanning the microbiome, immune system and plasma metabolome in health and ME/CFS adjusted for age, gender and additional clinical factors.
This map uncovers altered associations between microbial metabolism (for example, short-chain fatty acids, branched-chain amino acids, tryptophan, benzoate), plasma lipids and bile acids, and heightened inflammatory responses in mucosal and inflammatory T cell subsets (MAIT, γδT) secreting IFN-γ and GzA.
Overall, BioMapAI provides unprecedented systems-level insights into ME/CFS, refining existing hypotheses and hypothesizing unique mechanisms—specifically, how multi-omics dynamics are associated to the disease’s heterogeneous symptoms.
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