Blood Test Differentiates Fibromyalgia Syndrome

A finger-stick blood sample test has been developed to detect fibromyalgia syndrome, a painful disorder that is difficult to diagnose.

A high-powered and specialized microscope can detect the presence of small molecules in blood-spot samples from patients known to have fibromyalgia and differentiating between the syndrome and two types of arthritis that share some of the same symptoms.

Scientists at the Ohio State University (Columbus, OH, USA) used infrared microspectroscopy (IRMS), which identifies the biochemical content of a blood sample based on where peaks of molecules appear in the infrared spectrum. The technology offers hints at the molecules present in the samples based on how molecular bonds vibrate when they are struck by light. The investigators first obtained blood samples from 14 patients diagnosed with fibromyalgia, 15 with rheumatoid arthritis (RA), and 12 with osteoarthritis (OS). These other conditions were chosen for comparison because they produce similar symptoms as fibromyalgia, but are easier to diagnose.

The blood collected was applied to blood spot cards and processed. Aliquots were placed on a SuperMask 192-well microarray slide (Arrayit Corporation; Sunnyvale, CA, USA) and dried under vacuum to produce dried serum films (DSF). Attenuated total reflectance (ATR) infrared (IR) spectra were recorded using infinity corrected Fourier transform infrared spectroscopy (FT-IR) microscope. The UMA 600 series IR microscope was connected to an Excalibur 3100GX FTIR spectrometer (Varian; Walnut Creek, CA, USA) equipped with a dynamically aligned Michelson interferometer. Samples also were extracted from dried blood spots and analyzed by nontargeted global metabolomic profiling. In this study, 166 compounds of known biochemical identity were detected.

While both methods were able to obtain informative results using blood spot samples, the IRMS approach differentiated fibromyalgia subjects from the RA and OA groups with zero misclassifications, providing a 100% accuracy rate, whereas the accuracy of the metabolomics approach was 75%. The cost of the IRMS analysis was lower than that of the metabolomics approach. Kevin V. Hackshaw, MD, rheumatologist and the lead author said, “The importance of producing a faster diagnosis cannot be overstated, because patients experience tremendous stress during the diagnostic process. Just getting the diagnosis actually makes patients feel better and lowers costs because of reductions in anxiety.” The study was published on August 21, 2013, in the journal Analyst.

Related Links:

Ohio State University
Arrayit Corporation
Varian