TY - JOUR
T1 - Functional brain network organization measured with magnetoencephalography predicts cognitive decline in multiple sclerosis
AU - Nauta, Ilse M.
AU - Kulik, Shanna D.
AU - Breedt, Lucas C.
AU - Eijlers, Anand J.C.
AU - Strijbis, Eva M.M.
AU - Bertens, Dirk
AU - Tewarie, Prejaas
AU - Hillebrand, Arjan
AU - Stam, Cornelis J.
AU - Uitdehaag, Bernard M.J.
AU - Geurts, Jeroen J.G.
AU - Douw, Linda
AU - de Jong, Brigit A.
AU - Schoonheim, Menno M.
N1 - Funding Information:
The authors would like to thank the Dutch MS Research Foundation for supporting this study. We would like to thank W.N. van Wieringen of the Amsterdam UMC, Department of Epidemiology and Biostatistics, for statistical consultation regarding the bootstrap analyses. We would also like to thank the research assistants of the Amsterdam UMC, Department of Neurology, MS Center Amsterdam, and the laboratory technicians of the Amsterdam UMC, Department of Clinical Neurophysiology and MEG Center, for the data acquisition. We thank L. Bürmann of the Amsterdam UMC, Department of Anatomy and Neurosciences, MS Center Amsterdam, for her help with the MEG processing steps. We also thank all patients and healthy controls for their participation. The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was supported by the Dutch MS Research Foundation, grant numbers 15-911 and 14-358e.
Funding Information:
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was supported by the Dutch MS Research Foundation, grant numbers 15-911 and 14-358e.
Funding Information:
The authors would like to thank the Dutch MS Research Foundation for supporting this study. We would like to thank W.N. van Wieringen of the Amsterdam UMC, Department of Epidemiology and Biostatistics, for statistical consultation regarding the bootstrap analyses. We would also like to thank the research assistants of the Amsterdam UMC, Department of Neurology, MS Center Amsterdam, and the laboratory technicians of the Amsterdam UMC, Department of Clinical Neurophysiology and MEG Center, for the data acquisition. We thank L. Bürmann of the Amsterdam UMC, Department of Anatomy and Neurosciences, MS Center Amsterdam, for her help with the MEG processing steps. We also thank all patients and healthy controls for their participation.
Publisher Copyright:
© The Author(s), 2020.
PY - 2021/10
Y1 - 2021/10
N2 - 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 ((Formula presented.)), 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.
AB - 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 ((Formula presented.)), 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.
KW - cognitive functioning
KW - longitudinal
KW - magnetic resonance imaging
KW - magnetoencephalography
KW - Multiple sclerosis
KW - network organization
UR - http://www.scopus.com/inward/record.url?scp=85097492738&partnerID=8YFLogxK
U2 - 10.1177/1352458520977160
DO - 10.1177/1352458520977160
M3 - Article
C2 - 33295249
AN - SCOPUS:85097492738
SN - 1352-4585
VL - 27
SP - 1727
EP - 1737
JO - Multiple Sclerosis Journal
JF - Multiple Sclerosis Journal
IS - 11
ER -