People with chronic fatigue syndrome are a select group who sometimes take years to get a formal diagnosis. According to experts, up to 91 percent of Americans are living without a diagnosis for a sickness that saps their vitality, intelligence, and ability to live carefree lives. However, if a recently created diagnostic test passes inspection, those figures may eventually improve.
The preliminary findings of a blood test that may reliably discriminate between healthy people and those with chronic fatigue syndrome (commonly known as myalgic encephalomyelitis or ME/CFS) have just been published by a team of researchers lead by the University of Oxford.
“The development of a simple blood test with the potential for early diagnosis [of ME/CFS] is] a critical goal,” write Jiabao Xu and colleagues in their open-access, peer-reviewed study.
They assert that “early diagnosis would enable patients to manage their conditions more effectively, potentially leading to new discoveries in disease pathways and treatment development”, particularly if such a blood test can detect changes over time.
Using a technology called Raman spectroscopy and an artificial intelligence (AI) tool, the blood test distinguishes between the characteristics of a kind of blood cell called peripheral blood mononuclear cells (PBMCs) in persons with and without ME/CFS.
An emerging idea that the illness is one of impaired energy production is consistent with previous research’ findings that PMBCs from persons with ME/CFS have diminished energetic function.
Based on their pilot study and the evidence suggesting that PBMCs are disturbed in ME/CFS, Xu and colleagues tested their diagnostic methodology in nearly 100 individuals, including 61 people with ME/CFS, 16 healthy controls, and 21 people with multiple sclerosis, an autoimmune disease that shares many symptoms with ME/CFS.
Blood tests may be useful in separating ME/CFS from other illnesses such fibromyalgia, chronic Lyme disease, and extended COVID if they can tell apart between those with ME/CFS, MS patients, and healthy people.
The team examined the molecular vibrations of individual cells while profiling over 2,000 cells from 98 patient samples. The resulting spectra show changes in amounts of intracellular metabolites created as cells metabolise fuel, similar to those used by astronomers to examine the chemical makeup of stars.
ME/CFS patients and the two control groups showed distinct metabolic abnormalities, according to Xu and colleagues.
The test could correctly identify 91 percent of patients after applying the AI algorithm, and it could even distinguish between individuals with mild, moderate, and severe ME/CFS with 84 percent accuracy.
It will take some time for additional research to confirm the findings in larger cohorts. Xu and colleagues are hoping that their approach can solve sample processing issues that other teams have run through. Single-cell Raman spectroscopy is not frequently used in accredited diagnostic laboratories, nevertheless.
Similar blood cell-based assays utilising other analytical methods have previously showed promise. There hasn’t been any development since Stanford University researchers reported the results of a pilot study of a test that analyses PBMCs in 2019. (Team members from Stanford are still researching ME/CFS.)
Untold thousands of ME/CFS sufferers are still desperate for a diagnosis and effective, evidence-based treatment choices.
“Many [medical professionals] still view ME/CFS with scepticism due to the lack of clear pathology or effective treatment options,” write Xu and colleagues.
With research like this suggesting discernible biochemical changes in the energy-restricting, life-altering illness, let’s hope that soon changes. Advanced Science published the study.
