Portable Mid-Infrared Spectroscopy Combined with Chemometrics to Diagnose Fibromyalgia and Other Rheumatologic Syndromes Using Rapid Volumetric Absorptive Microsampling.

FT-MIR OPLS-DA central sensitization fibromyalgia point-of-care device rheumatic diseases

Journal

Molecules (Basel, Switzerland)
ISSN: 1420-3049
Titre abrégé: Molecules
Pays: Switzerland
ID NLM: 100964009

Informations de publication

Date de publication:
15 Jan 2024
Historique:
received: 13 12 2023
revised: 04 01 2024
accepted: 10 01 2024
medline: 23 1 2024
pubmed: 23 1 2024
entrez: 23 1 2024
Statut: epublish

Résumé

The diagnostic criteria for fibromyalgia (FM) have relied heavily on subjective reports of experienced symptoms coupled with examination-based evidence of diffuse tenderness due to the lack of reliable biomarkers. Rheumatic disorders that are common causes of chronic pain such as rheumatoid arthritis, systemic lupus erythematosus, osteoarthritis, and chronic low back pain are frequently found to be comorbid with FM. As a result, this can make the diagnosis of FM more challenging. We aim to develop a reliable classification algorithm using unique spectral profiles of portable FT-MIR that can be used as a real-time point-of-care device for the screening of FM. A novel volumetric absorptive microsampling (VAMS) technique ensured sample volume accuracies and minimized the variation introduced due to hematocrit-based bias. Blood samples from 337 subjects with different disorders (179 FM, 158 non-FM) collected with VAMS were analyzed. A semi-permeable membrane filtration approach was used to extract the blood samples, and spectral data were collected using a portable FT-MIR spectrometer. The OPLS-DA algorithm enabled the classification of the spectra into their corresponding classes with 84% accuracy, 83% sensitivity, and 85% specificity. The OPLS-DA regression plot indicated that spectral regions associated with amide bands and amino acids were responsible for discrimination patterns and can be potentially used as spectral biomarkers to differentiate FM and other rheumatic diseases.

Identifiants

pubmed: 38257325
pii: molecules29020413
doi: 10.3390/molecules29020413
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : NIH HHS
ID : R61NS117211, GR122808
Pays : United States

Auteurs

Shreya Madhav Nuguri (SM)

Department of Food Science and Technology, The Ohio State University, Columbus, OH 43210, USA.

Kevin V Hackshaw (KV)

Department of Internal Medicine, Division of Rheumatology, Dell Medical School, The University of Texas, 1601 Trinity St., Austin, TX 78712, USA.

Silvia de Lamo Castellvi (S)

Department of Food Science and Technology, The Ohio State University, Columbus, OH 43210, USA.
Campus Sescelades, Departament d'Enginyeria Química, Universitat Rovira i Virgili, Av. Països Catalans 26, 43007 Tarragona, Spain.

Haona Bao (H)

Department of Food Science and Technology, The Ohio State University, Columbus, OH 43210, USA.

Siyu Yao (S)

Department of Nutrition and Food Hygiene, School of Public Health, Southeast University, Nanjing 210019, China.

Rija Aziz (R)

Department of Internal Medicine, Dell Medical School, The University of Texas, 1601 Trinity St., Austin, TX 78712, USA.

Scott Selinger (S)

Department of Internal Medicine, Dell Medical School, The University of Texas, 1601 Trinity St., Austin, TX 78712, USA.

Zhanna Mikulik (Z)

Department of Internal Medicine, Division of Immunology and Rheumatology, The Ohio State University, 480 Medical Center Dr, Columbus, OH 43210, USA.

Lianbo Yu (L)

Center of Biostatistics and Bioinformatics, The Ohio State University, Columbus, OH 43210, USA.

Michelle M Osuna-Diaz (MM)

Department of Internal Medicine, Dell Medical School, The University of Texas, 1601 Trinity St., Austin, TX 78712, USA.

Katherine R Sebastian (KR)

Department of Internal Medicine, Dell Medical School, The University of Texas, 1601 Trinity St., Austin, TX 78712, USA.

M Monica Giusti (MM)

Department of Food Science and Technology, The Ohio State University, Columbus, OH 43210, USA.

Luis Rodriguez-Saona (L)

Department of Food Science and Technology, The Ohio State University, Columbus, OH 43210, USA.

Classifications MeSH