AUTHOR=Neupokoeva Anna , Bratchenko Ivan , Bratchenko Lyudmila , Khivintseva Elena , Shirolapov Igor , Shusharina Natalia , Khoimov Matvei , Zakharov Valery , Zakharov Alexander 

TITLE=Raman liquid biopsy: a new approach to the multiple sclerosis diagnostics

JOURNAL=Frontiers in Neurology

VOLUME=Volume 16 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/neurology/articles/10.3389/fneur.2025.1516712

DOI=10.3389/fneur.2025.1516712

ISSN=1664-2295

ABSTRACT=Background/objectivesDespite the prevalence of multiple sclerosis, there is currently no biomarker by which this disease can be reliably identified. Existing diagnostic methods are either expensive or have low specificity. Therefore, the search for a diagnostic method with high specificity and sensitivity, and at the same time not requiring complex sample processing or expensive equipment, is urgent.MethodsThe article discusses the use of blood serum surface enhanced Raman spectroscopy in combination with machine learning analysis to separate persons with multiple sclerosis and healthy individuals. As a machine learning method for Raman spectra processing the projection on latent structures-discriminant analysis was used.ResultsUsing the above methods, we have obtained possibility to separate persons with multiple sclerosis and healthy ones with an average specificity of 0.96 and an average sensitivity of 0.89. The main Raman bands for discrimination against multiple sclerosis and healthy individuals are 632, 721–735, 1,048–1,076 cm−1. In general, the study of the spectral properties of blood serum using surface enhanced Raman spectroscopy is a promising method for diagnosing multiple sclerosis, however, further detailed studies in this area are required.