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A team of scientists led by the University of Oxford has just published their preliminary results of a blood cell-based test that can distinguish between unaffected individuals and those with chronic fatigue syndrome (also known as myalgic encephalomyelitis or ME/CFS) with 91 percent accuracy.

“ME/CFS is still viewed with skepticism by many [medical professionals] with no effective treatment options or clear pathology,” Xu and colleagues note.

Let’s hope that soon changes, with studies like this pointing to detectable biological changes in the energy-limiting, life-altering condition.

The study was published in Advanced Science.

Building on their pilot study, and the research suggesting PBMCs are perturbed in ME/CFS, Xu and colleagues tested their diagnostic approach in nearly 100 people: including 61 individuals with ME/CFS, 16 healthy controls, and 21 people with multiple sclerosis, an autoimmune disorder that has many similar symptoms to ME/CFS.

If the blood test could distinguish between people with ME/CFS and those with MS, as well as healthy folks, then it might bode well for its use in differentiating ME/CFS from other illnesses, such as fibromyalgiachronic Lyme disease, and long COVID.

The team profiled more than 2,000 cells across 98 patient samples, analyzing the molecular vibrations of single cells. The resulting spectra, much like those astronomers use to look at the chemical composition of stars, reflect changes in levels of intracellular metabolites produced when cells metabolize fuel.

Xu and colleagues observed clear metabolic differences between ME/CFS patients and the two control groups.

Applying the AI algorithm, the test could accurately classify 91 percent of patients, and could even differentiate between mild, moderate, and severe ME/CFS patients with 84 percent accuracy.


The full article and research can be found here:



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