Fibromyalgia is a long-term condition that causes body-wide pain. Other symptoms of fibromyalgia include increase sensitivity to pain, fatigue, stiff muscles, disturbed sleep, irritable bowel syndrome, and cognitive disturbances such as problems with memory and concentration. There is currently no cure for fibromyalgia, so treatment consists of medication, talking therapies, and lifestyle changes to help relieve and manage symptoms of the condition.
Diagnosing fibromyalgia relies on a wide range of symptoms reported by the patients themselves. Diagnosis also sometimes includes a physical evaluation of a patient’s pain by applying light pressure to specific tender points where pain is often felt. But diagnostic tools are lacking quick and accessible options to definitively diagnose fibromyalgia.
Carried out by The Ohio State University, the objective of the study was to develop a “rapid biomarker-based method for diagnosing fibrmyalgia by using vibrational spectroscopy to differentiate patients with fibromyalgia from those with rheumatoid arthritis, osteoarthritis, or systemic lupus erythematosus”. The research also aimed to identify metabolites “associated with these differences.”
The discoveries coming from the study could significantly improve patient care. Lead researcher Kevin Hackshaw, who is a professor in Ohio State’s College of Medicine and a rheumatologist at the Wexner Medical Center, described how patients are often left without proper care or advice on how to manage the chronic pain and fatigue caused by FM.
But, a “metabolic fingerprint”, or biomarkers of the disease like the ones found in this study, could be identified and used to create targeted treatment for patients. Hackshaw said:
“We found clear, reproducible metabolic patterns in the blood of dozens of patients with fibromyalgia. This brings us much closer to a blood test than we have ever been.”
Co-author of the study Luis Rodriguez-Saona said:
“We can look back into some of these fingerprints and potentially identify some of the chemicals associated with the differences we are seeing.”
“This could lead to better, more directed treatment for patients,” Hackshaw said.
In time, a particular protein, acid, or combination of molecules could be identified that is associated with fibromyalgia. Additionally, metabolic fingerprinting could even assess the severity of the condition in each patient.
With patients sometimes waiting an average of five years between the development of symptoms and final diagnosis, fast, accurate diagnosis is desperately needed, and has a number of clear benefits for patients and doctors alike. Patients can be assured that their symptoms are real and not imagined, and doctors can make faster and more confident diagnoses and can curate appropriate and informed treatment plans.
Patients that are left undiagnosed are often given strong and addictive opioid painkillers that have not produced evidence of being an effective treatment for those with fibromyalgia.
Hackshaw states, “When you look at chronic pain clinics, about 40 percent of patients on opioids meet the diagnostic criteria for fibromyalgia. Fibromyalgia often gets worse, and certainly doesn’t get better, with opioids.”
Unfortunately, some medical professionals are also in doubt about the validity of fibromyalgia as a disease. “Most physicians nowadays don’t question whether fibromyalgia is real, but there are still skeptics out there,” Hackshaw explains.
To build on the findings of the study, Hackshaw and Rodriguez-Saona aim to carry out larger-scale clinical trials to see if the results produced by this study can be reliably replicated.
This study included 50 participants with a fibromyalgia diagnosis. Also included in the study were 29 people with rheumatoid arthritis, 23 people with lupus, and 19 people with osteoarthritis.
Blood samples from each participant were analyzed using vibrational spectroscopy, a technique used to measure the energy level of molecules. This technique showed up definite patterns that distinguished the blood samples of fibromyalgia patients from the samples of the other participants living with different, but symptomatically similar, conditions.
Baseline patterns were generated from samples taken from patients whose disease status they were aware of before using two types of spectroscopy to evaluate the remaining samples. Although the researchers did not know the participants’ diagnoses for the remaining samples, they were able to accurately group every sample into disease categories based on the sample’s molecular signature.
Rodriguez-Saona is an expert in the testing methods used in the study. His lab utilizes metabolic fingerprinting for research in food, investigating issues including the adulteration of milk and cooking oils, and works to help agricultural organizations to identify plants that are well suited to combat disease.
Rodriguez-Saona said on the impact of this new study’s discovery:
“These initial results are remarkable. If we can help speed diagnosis for these patients, their treatment will be better and they’ll likely have better outlooks. There’s nothing worse than being in a gray area where you don’t know what disease you have.”
The study concludes that vibrational spectroscopy “may provide a reliable diagnostic test” for differentiating fibromyalgia from other conditions, and Hackshaw hopes that there will be a test available for broad clinical use within five years.
reference:Researchers hope blood test that accurately diagnoses fibromyalgia could be available within five years