ATR-FTIR spectroscopy of plasma supported by multivariate analysis discriminates multiple sclerosis disease

• Published in: Scientific reports Vol. 13; no. 1; pp. 2565 - 11
• Main Authors: Crocco, Maria Caterina, Moyano, María Fernanda Heredia, Annesi, Ferdinanda, Bruno, Rosalinda, Pirritano, Domenico, Del Giudice, Francesco, Petrone, Alfredo, Condino, Francesca, Guzzi, Rita
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 13.02.2023; Nature Publishing Group; Nature Portfolio
• Subjects: 631/57; 692/53; 692/699; Autoimmune diseases; Biomarkers; Biomarkers - blood; Blood; Cognitive ability; Diagnosis; Humanities and Social Sciences; Humans; multidisciplinary; Multiple sclerosis; Multiple Sclerosis - blood; Multiple Sclerosis - diagnosis; Multivariate Analysis; Neurodegenerative diseases; Plasma; Plasma - chemistry; Science; Science (multidisciplinary); Spectroscopy; Spectroscopy, Fourier Transform Infrared - methods; Spectrum analysis
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-023-29617-6

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.