Splicing-based biomarkers define a robust multigene classifier for relapsing-remitting multiple sclerosis

Federica Airi, Department of Biomedical Sciences, Humanitas University, Via Rita Levi Montalcini 4, Pieve Emanuele, 20072, Milan, Italy.
Valeria Rimoldi, Department of Biomedical Sciences, Humanitas University, Via Rita Levi Montalcini 4, Pieve Emanuele, 20072, Milan, Italy.
Elvezia Maria Paraboschi, Department of Biomedical Sciences, Humanitas University, Via Rita Levi Montalcini 4, Pieve Emanuele, 20072, Milan, Italy.
Valentina Pellicanò, Department of Biomedical Sciences, Humanitas University, Via Rita Levi Montalcini 4, Pieve Emanuele, 20072, Milan, Italy.
Damiano Verda, Rulex Innovation Labs, Via Felice Romani 9, 16122 Genova, Italy.
Giuseppe Liberatore, Neuromuscular and Neuroimmunology Service, IRCCS Humanitas Research Hospital, Italy.
Claudia Cantoni, Department of Translational Neuroscience, Barrow Neurological Institute, Phoenix, USA.
Laura Piccio, Neuroscience theme, School of Medical Sciences, Faculty of Medicine and Health, The University of Sydney, Camperdown, NSW, Australia.
Alvino Bisecco, Department of Advanced Medical and Surgical Sciences - University of Campania "Luigi Vanvitelli", Naples, Italy.
Anita Capalbo, Department of Biomedical Sciences, Humanitas University, Via Rita Levi Montalcini 4, Pieve Emanuele, 20072, Milan, Italy.
Giulia Cardamone, Department of Biomedical Sciences, Humanitas University, Via Rita Levi Montalcini 4, Pieve Emanuele, 20072, Milan, Italy.
Eduardo Nobile-Orazio, Neuromuscular and Neuroimmunology Service, IRCCS Humanitas Research Hospital And Milan University, Italy.
Giulia Soldà, Department of Biomedical Sciences, Humanitas University, Via Rita Levi Montalcini 4, Pieve Emanuele, 20072, Milan, Italy.
Rosanna Asselta, Department of Biomedical Sciences, Humanitas University, Via Rita Levi Montalcini 4, Pieve Emanuele, 20072, Milan, Italy.

Document Type

Article

Abstract

BACKGROUND: Alternative splicing (AS) is recognized as a key mechanism in multiple sclerosis (MS). We aimed to construct and validate a multivariate AS-based classifier (MS-Splicing Score, MS-SS) for the discrimination of relapsing-remitting MS (RRMS) patients from healthy controls. METHODS: Three AS events (IFNAR2 exon-8 skipping, NFAT5 exon-2 skipping, PRKCA exon-3∗ inclusion) were selected based on functional and literature evidence. Isoforms were quantified via fluorescent-competitive RT-PCR in peripheral blood RNA from two independent cohorts (Italy: 37 RRMS, 50 controls; USA: 29 RRMS, 20 controls). A logistic regression model was trained to derive the MS-SS, followed by ROC analysis. RESULTS: The MS-SS distinguished RRMS patients from controls in both cohorts (Italy: p = 0.00083, AUC = 0.71, 95 %CI = 0.59-0.82; USA: p = 0.00074, AUC = 0.77, 95 %CI = 0.63-0.90). In the pooled dataset, the score remained significantly elevated in MS (p = 5.9 × 10, AUC = 0.72, 95 %CI = 0.64-0.81), and a PCA-based refinement improved classification accuracy, yielding an AUC = 0.87 (95 %CI = 0.81-0.94). At the optimal cutoff (Youden's index), the score achieved a sensitivity of 80 % and specificity of 86 %. Supervised rule-based modeling using a logic-learning machine algorithm identified interpretable splicing thresholds and enabled clinical classification at the individual level. CONCLUSION: Our study introduces a novel, robust AS-based classifier for RRMS and proposes a strategy for transcriptome-based biomarker development in neuroimmunology. However, the relatively small sample sizes within each cohort may limit the generalizability of these findings, warranting larger validation studies to confirm the clinical utility of this biomarker.

Keywords

Alternative splicing, Biomarkers, Multiple sclerosis, Peripheral blood, Splicing score

Publication Date

12-1-2025

Publication Title

Journal of translational autoimmunity

E-ISSN

2589-9090

Volume

11

First Page

100312

PubMed ID

40978497

Digital Object Identifier (DOI)

10.1016/j.jtauto.2025.100312

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