We are very excited to announce that in collaboration with the lab of Julia Oh at The Jackson Laboratory, which studies the microbiome in ME/CFS for the JAX CRC, we have just posted the full preprint of our new ME/CFS microbiome paper on BioRxiv, which will continue to be updated following reviewer comment and peer-review. In this detailed study led by Ruoyun Xiong, we did deep multi-omics, where we performed shotgun metagenomics of the gut microbiota and plasma metabolomics in 79 healthy controls and two cohorts of ME/CFS patients: 75 with short-term disease (<4 years), and 79 patients with long-term disease (>10 years). We also correlated these data to clinical information collected from subject questionnaires, and built multiple state-of-the-art classifiers that were able to differentiate short or long-term ME/CFS from each other, or ME/CFS from healthy controls.
The gut microbiome has been recently studied as a potential contributor to ME/CFS, and previous groups have shown that ME/CFS patients have frequent gastrointestinal (GI) disturbances, and changes in their gut microbiota compared to healthy controls. A few of the major differences that we found are that ME/CFS subjects had reduced gut microbiome diversity (fewer members) and richness. High diversity is associated with ecosystem health, and less diverse ecosystems are associated with decreased resilience and a susceptibility to colonization by pathogenic microbes. We also noticed a change in the ratio of the overall amounts of Firmicutes to Bacteroidetes phyla. Changes in this ratio have previously been noted in some chronic disorders and inflammatory diseases, such as inflammatory bowel disease (IBD). When looking at short-term vs. long-term ME/CFS, we found that subjects with a disease duration of <4 years had more microbial dysbiosis, but ME/CFS subjects with a disease duration of <10 years had more severe phenotypic and metabolic abnormalities.
One of the major problems that ME/CFS patients face is that there is no standard diagnostic test for ME/CFS. Our use of multiple ‘omics data greatly increased classification accuracy between ME/CFS subjects and healthy controls, and identified microbial and metabolic features that could be interesting to investigate further to find therapeutic strategies.