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Abstract
Multiple sclerosis (MS) is one of the most common neurodegenerative diseases showing various symptoms both of physical and cognitive type. In this work, we used attenuated total reflection Fourier transformed infrared (ATR-FTIR) spectroscopy to analyze plasma samples for discriminating MS patients from healthy control individuals, and identifying potential spectral biomarkers helping the diagnosis through a quick non-invasive blood test. The cohort of the study consists of 85 subjects, including 45 MS patients and 40 healthy controls. The differences in the spectral features both in the fingerprint region (1800–900 cm−1) and in the high region (3050–2800 cm−1) of the infrared spectra were highlighted also with the support of different chemometric methods, to capture the most significant wavenumbers for the differentiation. The results show an increase in the lipid/protein ratio in MS patients, indicating changes in the level (metabolism) of these molecular components in the plasma. Moreover, the multivariate tools provided a promising rate of success in the diagnosis, with 78% sensitivity and 83% specificity obtained through the random forest model in the fingerprint region. The MS diagnostic tools based on biomarkers identification on blood (and blood component, like plasma or serum) are very challenging and the specificity and sensitivity values obtained in this work are very encouraging. Overall, the results obtained suggest that ATR-FTIR spectroscopy on plasma samples, requiring minimal or no manipulation, coupled with statistical multivariate approaches, is a promising analytical tool to support MS diagnosis through the identification of spectral biomarkers.
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1 University of Calabria, Molecular Biophysics Laboratory, Department of Physics, Rende, Italy (GRID:grid.7778.f) (ISNI:0000 0004 1937 0319); University of Calabria, STAR Research Infrastructure, Rende, Italy (GRID:grid.7778.f) (ISNI:0000 0004 1937 0319)
2 University of Calabria, Molecular Biophysics Laboratory, Department of Physics, Rende, Italy (GRID:grid.7778.f) (ISNI:0000 0004 1937 0319)
3 CNR-Nanotec Rende, Rende, Italy (GRID:grid.7778.f)
4 University of Calabria, Department of Pharmacy, Health and Nutritional Sciences, Rende, Italy (GRID:grid.7778.f) (ISNI:0000 0004 1937 0319)
5 Multiple Sclerosis Clinic, Annunziata Hospital, Neurological and Stroke Unit, Cosenza, Italy (GRID:grid.413811.e); SOC Neurologia-Azienda Ospedaliera Pugliese-Ciaccio, Catanzaro, Italy (GRID:grid.459358.6) (ISNI:0000 0004 1768 6328)
6 Multiple Sclerosis Clinic, Annunziata Hospital, Neurological and Stroke Unit, Cosenza, Italy (GRID:grid.413811.e); SOC Neurologia-Ospedale Jazzolino, Azienda Ospedaliera Provinciale, Vibo Valentia, Italy (GRID:grid.413811.e)
7 Multiple Sclerosis Clinic, Annunziata Hospital, Neurological and Stroke Unit, Cosenza, Italy (GRID:grid.413811.e)
8 University of Calabria, Department of Economics, Statistics and Finance “Giovanni Anania”, Arcavacata di Rende, Italy (GRID:grid.7778.f) (ISNI:0000 0004 1937 0319)
9 University of Calabria, Molecular Biophysics Laboratory, Department of Physics, Rende, Italy (GRID:grid.7778.f) (ISNI:0000 0004 1937 0319); CNR-Nanotec Rende, Rende, Italy (GRID:grid.7778.f)