For those dealing with chronic fatigue syndrome, it may take years for them to receive a conclusive diagnosis. Not to mention, there are only a few of them that actually get diagnosed. Now, a novel blood test could help with this.
What Is Chronic Fatigue Syndrome?
Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS), is a long-term and serious condition that affects many systems in the body. Individuals battling ME/CFS are incapable of performing their typical activities. In certain instances, the condition could even leave them confined to the bed. People with the condition often experience severe sleep and fatigue problems.
A report suggests that roughly 836,000 to 2.5 million Americans are dealing with the condition. However, the majority of them has not been conclusively diagnosed. Experts also think that roughly 91% of them across the US are undiagnosed and do not have the necessary medical support.
However, these statistics and demographics could improve with the help of a novel diagnostic tool.
Blood Test For Detecting Chronic Fatigue Syndrome
The preliminary results of a scientific team that the University of Oxford led has released their preliminary results. This pertains to a blood cell-based test that is capable of distinguishing people with ME/CFs and people without the condition. The test was able to reach an accuracy of 91%.
Jiabao Xu and colleagues explain in the study that the simple test development of MEC/CFS' early diagnosis is a crucial goal. Early diagnosis would aid the effective management of the condition and could potentially enable more discoveries regarding the pathways and treatment of the condition. This would be especially true if the blood test is capable of revealing changes that take place as time passes.
The novel blood test is capable of distinguishing properties of peripheral blood mononuclear cells (PBMCs) among people who are dealing with and are not dealing with ME/CFS. It does so through the Raman spectroscopy technique as well as an artificial intelligence tool.
Earlier studies have shown that the PMBCs of those with ME/CFS have lower energy functions. Such findings align with the growing theory that the condition is one pertaining to impaired energy production.
The researchers of the recent study then tried out their diagnostic method among almost 100 individuals. These included 61 people with ME/CFS, 21 with multiple sclerosis (which has several symptoms that are similar to ME/CFS), and 16 healthy individuals who served as the control group.
They examined 2,000 cells from 98 samples from patients and examined the single cells' molecular vibrations. The spectra results show alterations in intracellular metabolite levels that were produced during the cells' metabolization of fuel.
The researchers were able to observe distinct differences between the ME/CFS group and the two others.
With the AI algorithm, 91% of the patients got accurately classified. The tool was also capable of differentiating mild, moderate, and severe cases of ME/CFS with an accuracy of 84%.
It will take more time to validate the findings in a larger sample. The researchers are hopeful that their approach will bypass the challenges that other research teams have experienced when it comes to sample processing. However, Raman spectroscopy that is single-celled is not fully available in certified diagnostic labs.
Nevertheless, they are still hopeful for positive changes that studies like this aim for as they point to identifiable biomarkers in the condition.
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