Trial Report Early Diagnosis of Fibromyalgia Using Surface-Enhanced Raman Spectroscopy Combined with Chemometrics, 2024, Bao

https://www.mdpi.com/2227-9059/12/1/133

Early Diagnosis of Fibromyalgia Using Surface-Enhanced Raman Spectroscopy Combined with Chemometrics
by
Haona Bao
1,
Kevin V. Hackshaw
2,*,
Silvia de Lamo Castellvi
1,3,
Yalan Wu
1,
Celeste Matos Gonzalez
1,
Shreya Madhav Nuguri
1,
Siyu Yao
1,4,
Chelsea M. Goetzman
5,6,
Zachary D. Schultz
5,
Lianbo Yu
7,
Rija Aziz
8,
Michelle M. Osuna-Diaz
8,
Katherine R. Sebastian
8,
Monica M. Giusti
1and
Luis Rodriguez-Saona
1


1
Department of Food Science and Technology, The Ohio State University, Columbus, OH 43210, USA
2
Department of Internal Medicine, Division of Rheumatology, Dell Medical School, The University of Texas, 1601 Trinity St., Austin, TX 78712, USA
3
Departament d’Enginyeria Química, Universitat Rovira i Virgili, Av. Països Catalans 26, 43007 Tarragona, Spain
4
Department of Nutrition and Food Hygiene, School of Public Health, Southeast University, Nanjing 210009, China
5
Department of Chemistry and Biochemistry, The Ohio State University, Columbus, OH 43210, USA
6
Savannah River National Laboratory, Jackson, SC 29831, USA
7
Center of Biostatistics and Bioinformatics, The Ohio State University, Columbus, OH 43210, USA
8
Department of Internal Medicine, Dell Medical School, The University of Texas, 1601 Trinity St., Austin, TX 78712, USA
*
Author to whom correspondence should be addressed.

Biomedicines 2024, 12(1), 133; https://doi.org/10.3390/biomedicines12010133
Submission received: 21 December 2023 / Revised: 28 December 2023 / Accepted: 4 January 2024 / Published: 9 January 2024

(This article belongs to the Special Issue Neuropathic Pain: From Mechanisms to Therapeutic Approaches)

Abstract

Fibromyalgia (FM) is a chronic muscle pain disorder that shares several clinical features with other related rheumatologic disorders.

This study investigates the feasibility of using surface-enhanced Raman spectroscopy (SERS) with gold nanoparticles (AuNPs) as a fingerprinting approach to diagnose FM and other rheumatic diseases such as rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), osteoarthritis (OA), and chronic low back pain (CLBP).

Blood samples were obtained on protein saver cards from FM (n = 83), non-FM (n = 54), and healthy (NC, n = 9) subjects.

A semi-permeable membrane filtration method was used to obtain low-molecular-weight fraction (LMF) serum of the blood samples.

SERS measurement conditions were standardized to enhance the LMF signal. An OPLS-DA algorithm created using the spectral region 750 to 1720 cm−1 enabled the classification of the spectra into their corresponding FM and non-FM classes (Rcv > 0.99) with 100% accuracy, sensitivity, and specificity.

The OPLS-DA regression plot indicated that spectral regions associated with amino acids were responsible for discrimination patterns and can be potentially used as spectral biomarkers to differentiate FM and other rheumatic diseases.

This exploratory work suggests that the AuNP SERS method in combination with OPLS-DA analysis has great potential for the label-free diagnosis of FM.

Keywords:
fibromyalgia; surface-enhanced Raman spectroscopy; central sensitization syndrome; metabolic fingerprinting; in-clinic disease diagnostics; chemometrics; blood

 

Press release:
"A blood test will diagnose #fibromyalgia more reliably: A pioneering technique that a URV researcher has helped to develop enables this chronic disease to be identified more quickly and precisely"

https://www.eurekalert.org/news-releases/1036432