Spectrochemical analysis in blood plasma combined with subsequent chemometrics for fibromyalgia detection

Abstract

Fibromyalgia is a rheumatologic condition characterized by multiple and chronic body pain, and other typical symptoms such as intense fatigue, anxiety and depression. It is a very complex disease where treatment is often made by non-medicated alternatives in order to alleviate symptoms and improve the patient’s quality of life. Herein, we propose a method to detect patients with fibromyalgia ( n = 252, 126 controls and 126 patients with fibromyalgia) through the analysis of their blood plasma using attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy in conjunction with chemometric techniques, hence, providing a low-cost, fast and accurate diagnostic approach. Different chemometric algorithms were tested to classify the spectral data; genetic algorithm with linear discriminant analysis (GA-LDA) achieved the best diagnostic results with a sensitivity of 89.5% in an external test set. The GA-LDA model identified 24 spectral wavenumbers responsible for class separation; amongst these, the Amide II (1,545 cm −1 ) and proteins (1,425 cm −1 ) were identified to be discriminant features. These results reinforce the potential of ATR-FTIR spectroscopy with multivariate analysis as a new tool to screen and detect patients with fibromyalgia in a fast, low-cost, non-destructive and minimally invasive fashion.

The Search for Biomarkers in Fibromyalgia

“…Amide II (1545 cm) and proteins 1425 cm were identified to be discriminant features. Their results reinforce the prior results of Hackshaw in showing the potential of vibrational spectroscopy with multivariate analysis as a tool to screen and detect patients with FM in a rapid, low-cost, and minimally invasive manner [91].…”

Multivariate classification techniques and mass spectrometry as a tool in the screening of patients with fibromyalgia

“…Studies carried out by the American College of Rheumatology offer good results for differentiating between groups of patients with and without fibromyalgia, taking into account the occurrence of 11 of the 18 sensitive pain points for FM symptoms 33 , the accuracy obtained in this classification was 84.9% with a sensitivity of 88.4%. In a more recent study using blood plasma samples from groups with and without FM and readings in mid-infrared spectroscopy coupled with multivariate classification 2 , the accuracy results reached values of 84.2% and sensitivity of 89.5% using the GA-LDA model. For this paper, using paper spray ionization mass spectrometry, the best results provided 100% accuracy for SPA-LDA, in addition to classification with PCA that also recognized all case group (FG) samples as patients with fibromyalgia.…”

“…Fibromyalgia (FM) is a rheumatologic disorder that causes chronic pain and other symptomatic conditions such as depression, anxiety and sleep and memory disorders 1 , 2 . This disorder is common in clinical rheumatology routine, with a worldwide prevalence between 0.5 and 5%, affecting women approximately seven times more than men 3 .…”

“…Some reports on the investigation of biological and metabolomic markers in biofluids from patients with FM are also located in the literature 23 , 25 , 26 , but without the occurrence of application of chemometric tools for group classification. In a recent study 2 the blood plasma of control and fibromyalgia patients is used, in which it was possible to reach good results of discrimination of these groups from infrared (IR) spectroscopic analysis coupled with chemometric techniques. In this case, despite the good results in IR, the spectra obtained are difficult to interpret and have low resolution for elucidating molecules of clinical interest, and consequent detection of FM in blood smear.…”

ATR-FTIR spectroscopy in blood plasma combined with multivariate analysis to detect HIV infection in pregnant women

“…Since, we worked with the bio-fingerprint region (900–1,800 cm −1 ) only, these main water bands were removed. However, water has an absorbance band within the bio-fingerprint region at 1646 cm −1 , which broadens the Amide I band and creates a shoulder 23 . In addition, absorbances < 1,000 cm −1 tend to greatly increase in a liquid environment, hence, compressing the bands between 1,200–1,500 cm −1 23 .…”