Disrupted Core Periphery of Brain Networks in Multiple Sclerosis
Author Information
Author(s): Pontillo Giuseppe, Prados Ferran, Wink Alle Meije, Kanber Baris, Bisecco Alvino, Broeders Tommy A. A., Brunetti Arturo, Cagol Alessandro, Calabrese Massimiliano, Castellaro Marco, Cocozza Sirio, Colato Elisa, Collorone Sara, Cortese Rosa, De Stefano Nicola, Douw Linda, Enzinger Christian, Filippi Massimo, Foster Michael A., Gallo Antonio, Gonzalez‐Escamilla Gabriel, Granziera Cristina, Groppa Sergiu, Harbo Hanne F., Høgestøl Einar A., Llufriu Sara, Lorenzini Luigi, Martinez‐Heras Eloy, Messina Silvia, Moccia Marcello, Nygaard Gro O., Palace Jacqueline, Petracca Maria, Pinter Daniela, Rocca Maria A., Strijbis Eva, Toosy Ahmed, Valsasina Paola, Vrenken Hugo, Ciccarelli Olga, Cole James H., Schoonheim Menno M., Barkhof Frederik
Primary Institution: UCL Queen Square Institute of Neurology, University College London
Hypothesis
Joint brain network changes across structural and functional levels would manifest in a disrupted multilayer core-periphery structure compared to healthy individuals.
Conclusion
The study shows that multilayer networks represent a meaningful framework to model multimodal MRI data, with disruption of the core-periphery structure emerging as a potential biomarker for disease severity and cognitive impairment in multiple sclerosis.
Supporting Evidence
- PwMS showed significant disruption of the multiplex core-periphery organization (κ = −0.14, Hedges' g = 0.49, p < 0.001).
- Disruption of the core-periphery structure was associated with clinical phenotype and levels of physical disability.
- Multiplex κ was the only connectomic measure adding to conventional MRI in predicting disease status and cognitive impairment.
Takeaway
People with multiple sclerosis have a weaker connection in their brain networks compared to healthy people, which can help doctors understand how severe the disease is and how it affects thinking.
Methodology
The study used a multilayer network approach integrating structural, diffusion, and resting-state functional MRI data from 1048 people with multiple sclerosis and 436 healthy controls to analyze brain connectivity.
Potential Biases
The retrospective nature and multi-center design may introduce variability in data quality and participant characteristics.
Limitations
The study is cross-sectional, limiting causal inference, and clinical evaluations were restricted to EDSS and SDMT, which may not fully capture disability.
Participant Demographics
1048 people with multiple sclerosis (695 females, mean age 43.3 years) and 436 healthy controls (250 females, mean age 38.3 years).
Statistical Information
P-Value
p<0.001
Statistical Significance
p<0.001
Digital Object Identifier (DOI)
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