Protein-based classifier to predict conversion from clinically isolated syndrome to multiple sclerosis

Eva Borràs, Ester Cantó, Meena Choi, Luisa Maria Villar, José Carlos Álvarez-Cermeño, Cristina Chiva, Xavier Montalban, Olga Vitek, Manuel Comabella, Eduard Sabidó

Research output: Contribution to journalArticleResearchpeer-review

26 Citations (Scopus)


© 2016 by The American Society for Biochemistry and Molecular Biology, Inc. Multiple sclerosis is an inflammatory, demyelinating, and neurodegenerative disease of the central nervous system. In most patients, the disease initiates with an episode of neurological disturbance referred to as clinically isolated syndrome, but not all patients with this syndrome develop multiple sclerosis over time, and currently, there is no clinical test that can conclusively establish whether a patient with a clinically isolated syndrome will eventually develop clinically defined multiple sclerosis. Here, we took advantage of the capabilities of targeted mass spectrometry to establish a diagnostic molecular classifier with high sensitivity and specificity able to differentiate between clinically isolated syndrome patients with a high and a low risk of developing multiple sclerosis. Based on the combination of abundances of proteins chitinase 3-like 1 and ala-β-his-dipeptidase in cerebrospinal fluid, we built a statistical model able to assign to each patient a precise probability of conversion to clinically defined multiple sclerosis. Our results are of special relevance for patients affected by multiple sclerosis as early treatment can prevent brain damage and slow down the disease progression.
Original languageEnglish
Pages (from-to)318-328
JournalMolecular and Cellular Proteomics
Issue number1
Publication statusPublished - 1 Jan 2016


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