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Functional brain network organization measured with magnetoencephalography predicts cognitive decline in multiple sclerosis.
Nauta, Ilse M; Kulik, Shanna D; Breedt, Lucas C; Eijlers, Anand Jc; Strijbis, Eva Mm; Bertens, Dirk; Tewarie, Prejaas; Hillebrand, Arjan; Stam, Cornelis J; Uitdehaag, Bernard Mj; Geurts, Jeroen Jg; Douw, Linda; de Jong, Brigit A; Schoonheim, Menno M.
Affiliation
  • Nauta IM; Department of Neurology, Amsterdam UMC, Vrije Universiteit Amsterdam, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands.
  • Kulik SD; Department of Anatomy & Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands.
  • Breedt LC; Department of Anatomy & Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands.
  • Eijlers AJ; Department of Anatomy & Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands.
  • Strijbis EM; Department of Neurology, Amsterdam UMC, Vrije Universiteit Amsterdam, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands/Department of Clinical Neurophysiology and MEG Center, Amsterdam UMC, Vrije Universiteit Amsterdam, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, Th
  • Bertens D; Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands; Klimmendaal Rehabilitation Center, Arnhem, The Netherlands.
  • Tewarie P; Department of Neurology, Amsterdam UMC, Vrije Universiteit Amsterdam, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands.
  • Hillebrand A; Department of Clinical Neurophysiology and MEG Center, Amsterdam UMC, Vrije Universiteit Amsterdam, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands.
  • Stam CJ; Department of Neurology, Amsterdam UMC, Vrije Universiteit Amsterdam, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands/Department of Clinical Neurophysiology and MEG Center, Amsterdam UMC, Vrije Universiteit Amsterdam, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, Th
  • Uitdehaag BM; Department of Neurology, Amsterdam UMC, Vrije Universiteit Amsterdam, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands.
  • Geurts JJ; Department of Anatomy & Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands.
  • Douw L; Department of Anatomy & Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands.
  • de Jong BA; Department of Neurology, Amsterdam UMC, Vrije Universiteit Amsterdam, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands.
  • Schoonheim MM; Department of Anatomy & Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands.
Mult Scler ; 27(11): 1727-1737, 2021 10.
Article in En | MEDLINE | ID: mdl-33295249
ABSTRACT

BACKGROUND:

Cognitive decline remains difficult to predict as structural brain damage cannot fully explain the extensive heterogeneity found between MS patients.

OBJECTIVE:

To investigate whether functional brain network organization measured with magnetoencephalography (MEG) predicts cognitive decline in MS patients after 5 years and to explore its value beyond structural pathology.

METHODS:

Resting-state MEG recordings, structural MRI, and neuropsychological assessments were analyzed of 146 MS patients, and 100 patients had a 5-year follow-up neuropsychological assessment. Network properties of the minimum spanning tree (i.e. backbone of the functional brain network) indicating network integration and overload were related to baseline and longitudinal cognition, correcting for structural damage.

RESULTS:

A more integrated beta band network (i.e. smaller diameter) and a less integrated delta band network (i.e. lower leaf fraction) predicted cognitive decline after 5 years (Radj2=15%), independent of structural damage. Cross-sectional analyses showed that a less integrated network (e.g. lower tree hierarchy) related to worse cognition, independent of frequency band.

CONCLUSIONS:

The level of functional brain network integration was an independent predictive marker of cognitive decline, in addition to the severity of structural damage. This work thereby indicates the promise of MEG-derived network measures in predicting disease progression in MS.
Subject(s)
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Cognitive Dysfunction / Multiple Sclerosis Type of study: Diagnostic_studies / Etiology_studies / Observational_studies / Prevalence_studies / Prognostic_studies / Risk_factors_studies Limits: Humans Language: En Journal: Mult Scler Journal subject: NEUROLOGIA Year: 2021 Document type: Article Affiliation country: Netherlands Publication country: ENGLAND / ESCOCIA / GB / GREAT BRITAIN / INGLATERRA / REINO UNIDO / SCOTLAND / UK / UNITED KINGDOM

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Cognitive Dysfunction / Multiple Sclerosis Type of study: Diagnostic_studies / Etiology_studies / Observational_studies / Prevalence_studies / Prognostic_studies / Risk_factors_studies Limits: Humans Language: En Journal: Mult Scler Journal subject: NEUROLOGIA Year: 2021 Document type: Article Affiliation country: Netherlands Publication country: ENGLAND / ESCOCIA / GB / GREAT BRITAIN / INGLATERRA / REINO UNIDO / SCOTLAND / UK / UNITED KINGDOM