Insights into [ME/CFS] Phenotypes through Comprehensive Metabolomics

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A recent study in the journal Scientific Reports from Dr. W. Ian Lipkin, who is the Principal Investigator for the Columbia ME/CFS Center, has new metabolic and microbiome findings that could lead to the development of a diagnostic biomarker for ME/CFS. The article, titled “Insights into myalgic encephalomyelitis/chronic fatigue syndrome phenotypes through comprehensive metabolomics,” details the analysis of plasma metabolomic, fecal bacterial metagenomic, and clinical data from 50 ME/CFS patients and 50 healthy controls. Metabolomics, which is the study of metabolites, or the end products of cellular processes, can give insight about the physiological state of the body, and how it is functioning.

The group analyzed 562 different molecules of the metabolome in subject blood samples using mass spectrometry, and then linked that data to fecal metagenomic data and clinical data. When all of the data was combined, the group was able to develop a predictive model for ME/CFS diagnosis with a 0.836 score, or an accuracy rate of 84 percent. In an article by Medical News Today about the study, first author Dr. Dorottya Nagy-Szakal is quoted, saying, “this is a strong predictive model that suggests we’re getting close to the point where we’ll have lab tests that will allow us to say with a high level of certainty who has this disorder.”

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