2026 American Academy of Neurology Abstract Website

Maria Rocca¹, Paola Valsasina⁴, Paolo Preziosa¹, Nicolò Tedone², Menno Schoonheim⁵, Antonio Gallo⁶, Patrizia Pantano⁷, Christian Enzinger⁸, Sara Llufriu⁹, Massimiliano Calabrese¹⁰, Giuseppe Pontillo¹¹, Einar A. Hogestol¹², Sergiu Groppa¹³, Nicola De Stefano¹⁴, Sara Collorone¹⁵, Massimo Filippi³
¹Neuroimaging Research Unit, Division of Neuroscience, and Neurology Unit, ²Neuroimaging Research Unit, Division of Neuroscience, ³Neuroimaging Research Unit, Division of Neuroscience, Neurology Unit, Neurorehabilitation Unit, and Neurophysiology Service, IRCCS San Raffaele Scientific Institute, and Vita-Salute San Raffaele University, ⁴Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, ⁵Multiple Sclerosis Center Amsterdam, Anatomy and Neuroscience, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam University Medical College VUMC, ⁶Department of Advanced Medical and Surgical Sciences, University of Campania Luigi Vanvitelli, ⁷Department of Human Neuroscience, Sapienza University of Rome, Rome, and IRCCS Neuromed, Pozzilli, ⁸Department of Neurology, Medical University of Graz, ⁹Neuroimmunology and Multiple Sclerosis Unit, and Laboratory of Advanced Imaging in Neuroimmunological Diseases (ImaginEM), Hospital Clinic and Institut d’Investigacions Biomediques August Pi I Sunyer (IDIPABS), University of Barcelona, ¹⁰Multiple Sclerosis Center, Department of Neurosciences and Biomedicine and Movement, University Hospital of Verona, ¹¹Departments of Advanced Biomedical Sciences and Electrical Engineering and Information Technology, University of Naples “Federico II”, ¹²Institute of Clinical Medicine, and Department of Psychology, University of Oslo, ¹³Clinic of Neurology and Department of Neurology, Neurostimulation and Neuroimaging, University of Saarland, ¹⁴Department of Medicine, Surgery and Neuroscience, University of Siena, ¹⁵Queen Square MS Center, Department of Neuroinflammation, UCL Institute of Neurology

Objective:

To perform a multimodal analysis of grey matter (GM) structural and functional networks in a multicenter cohort (12 European sites) to evaluate the contribution of structural/functional MRI GM damage in depicting multiple sclerosis (MS) clinical features.

Background:

MS is characterized by significant variability in clinical manifestations, likely because of the wide heterogeneity in the distribution of structural brain damage and the varying efficiency of brain plasticity across patients.

Design/Methods:

3D T1-weighted, resting state (RS) functional MRI and clinical evaluations were obtained from 1754 MS patients (65 clinically isolated syndromes [CIS], 1338 relapsing-remitting [RR] and 351 progressive [P] MS) and 597 healthy controls (HC). Parallel independent component analysis (P-ICA) on GM volume and degree centrality maps produced structural/functional network components and corresponding Z-scores.

Results:

P-ICA identified six structural GM networks with significant atrophy in MS patients vs HC (p range <0.001-0.03). CIS patients showed atrophy in the default-mode network (DMN) (p<0.001), RRMS had additional atrophy in occipital, deep GM, and fronto-parietal networks (all p<0.001), while PMS exhibited further atrophy in DMN (p=0.002) and occipital network (p=0.01). P-ICA also identified three sensorimotor networks showing increased functional connectivity (FC) in MS patients vs HC (p=range 0.007/<0.001), while the DMN, fronto-parietal and salience networks showed decreased FC (all p<0.001). CIS patients presented limited FC abnormalities, while more pronounced decrease FC in PMS vs RRMS was found in the DMN (p=0.004) and fronto-parietal (p=0.005) networks. In MS, most of networks showed decreased structural-functional association (interaction p range=0.04 to <0.001), correlating with more severe clinical disability.

Conclusions:

Multimodal analysis of structural/functional brain network helped to unravel complex changes of human network organization associated with MS disease.