Portable Mid-Infrared Spectroscopy Combined with Chemometrics to Diagnose Fibromyalgia and Other Rheumatologic Syndromes Using Rapid Volumetric Absorptive Microsampling
Shreya Madhav Nuguri,
Kevin V. Hackshaw,
Silvia de Lamo Castellvi,
Haona Bao,
Siyu Yao,
Rija Aziz,
Scott Selinger,
Zhanna Mikulik,
Lianbo Yu,
Michelle M. Osuna-Diaz,
Katherine R. Sebastian,
M. Monica Giusti,
Luis Rodriguez-Saona
Affiliations
Shreya Madhav Nuguri
Department of Food Science and Technology, The Ohio State University, Columbus, OH 43210, USA
Kevin V. Hackshaw
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
Department of Food Science and Technology, The Ohio State University, Columbus, OH 43210, USA
Haona Bao
Department of Food Science and Technology, The Ohio State University, Columbus, OH 43210, USA
Siyu Yao
Department of Nutrition and Food Hygiene, School of Public Health, Southeast University, Nanjing 210019, China
Rija Aziz
Department of Internal Medicine, Dell Medical School, The University of Texas, 1601 Trinity St., Austin, TX 78712, USA
Scott Selinger
Department of Internal Medicine, Dell Medical School, The University of Texas, 1601 Trinity St., Austin, TX 78712, USA
Zhanna Mikulik
Department of Internal Medicine, Division of Immunology and Rheumatology, The Ohio State University, 480 Medical Center Dr, Columbus, OH 43210, USA
Lianbo Yu
Center of Biostatistics and Bioinformatics, The Ohio State University, Columbus, OH 43210, USA
Michelle M. Osuna-Diaz
Department of Internal Medicine, Dell Medical School, The University of Texas, 1601 Trinity St., Austin, TX 78712, USA
Katherine R. Sebastian
Department of Internal Medicine, Dell Medical School, The University of Texas, 1601 Trinity St., Austin, TX 78712, USA
M. Monica Giusti
Department of Food Science and Technology, The Ohio State University, Columbus, OH 43210, USA
Luis Rodriguez-Saona
Department of Food Science and Technology, The Ohio State University, Columbus, OH 43210, USA
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.
