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Fibromyalgia Blood Test Progress, But Control Group Lacking

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News

Fibromyalgia Blood Test Progress, But Control Group Lacking

Image credit: The Ohio State University Wexner Center
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A blood test for fibromyalgia would be a relief for millions of people living with the poorly-understood condition, which is characterized by many symptoms including chronic widespread pain, sleep problems, and fatigue.

The test is the result of a unique collaboration between rheumatologists and the Ohio State food science and technology department, and relies on a technique called vibrational spectroscopy.

Vibrational spectroscopy is used in the food science industry to characterize different components in food, and measures the energy in compounds at a specific vibration.

By characterizing the unique energy of different metabolites, unique “fingerprints” can be compared. There are two types of vibrational spectroscopy, which differ in the types of vibrations that are used to excite the chemical bonds.


Video credit: Ohio State Wexner Medical Center

Luis Rodriguez-Saona, co-author and professor of food science and technology at Ohio State University commented:

“Each person’s blood is unique, like a fingerprint, and this test can show us the intricate details of that fingerprint. Now, we can see that certain patterns in those fingerprints indicate fibromyalgia, while different ones signal other conditions.”

To assess the biomarker-based diagnostic test, blood samples were collected from people with fibromyalgia (FM, n = 50), rheumatoid arthritis (n = 29), osteoarthritis (n = 19) and systemic lupus erythematosus (n = 23).

The aim of the study was to differentiate people with fibromyalgia from those with the other rheumatologic conditions, and the findings were published in The Journal of Biological Chemistry by a team from The Ohio State University Wexner Medical Center.

Blood samples were collected with portable FT-IR and FT-Raman microspectroscopy, and subjected to metabolomics analysis by ultra-HPLC coupled to a photodiode array and tandem mass spectrometry.

Pattern recognition analysis identified the different metabolomic fingerprints and clustered all study participants into the correct groups (FM, rheumatoid arthritis and systemic lupus erythematosus) with no misclassification.

The authors concluded that the technique may prove to be a reliable diagnostic test for differentiating fibromyalgia from other disorders and for establishing blood biomarkers of fibromyalgia-associated pain.

In a press release, Kevin Hackshaw, lead author of the study and associate professor of rheumatology at Ohio State commented on the significance of the findings:

“Being able to see the biological differences in the blood of those with fibromyalgia compared to those with other conditions like lupus, osteoarthritis and rheumatoid arthritis finally gives patients validation of their symptoms.”

“Not only does this help us direct treatment, but also prevents the use of unnecessary medications, like opiates, that don’t alleviate fibromyalgia pain and can lead to addiction.”   

The authors did note that the effect of medications on these analyses was beyond the scope of the study. However, all medications that patients were on at the time were recorded and there was no obvious effect of medication on the recorded signals.

To validate the test, further studies must include medication-free control groups, to determine whether the fibromyalgia group in fact can be distinguished from the general healthy population.

Currently, there is no gold standard for fibromyalgia diagnosis, which makes clinical diagnosis extremely difficult.

The authors concluded that with advancements in the methods described in the paper, the techniques may be of great importance in biomarker identification and in the hunt for therapeutic targets.  

Reference:

Hackshaw, K. V. et al. (2019). Metabolic fingerprinting for diagnosis of fibromyalgia and other rheumatologic disorders. The Journal of Biological Chemistry. 294: 2555-2568

Meet The Author
Michele Trott, PhD
Michele Trott, PhD
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