TY - JOUR
T1 - Eigenvector centrality dynamics are related to Alzheimer’s disease pathological changes in non-demented individuals
AU - Lorenzini, Luigi
AU - Ingala, Silvia
AU - Collij, Lyduine E.
AU - Wottschel, Viktor
AU - Haller, Sven
AU - Blennow, Kaj
AU - Frisoni, Giovanni
AU - Chételat, Gaël
AU - Payoux, Pierre
AU - Lage-Martinez, Pablo
AU - Ewers, Michael
AU - Waldman, Adam
AU - Wardlaw, Joanna
AU - Ritchie, Craig
AU - Gispert, Juan Domingo
AU - Mutsaerts, Henk J. M. M.
AU - Visser, Pieter Jelle
AU - Scheltens, Philip
AU - Tijms, Betty
AU - Barkhof, Frederik
AU - Wink, Alle Meije
N1 - Funding Information: EPAD is supported by the European Union/European federation of pharmaceutical industries and associations (EFPIA) Innovative Medicines Initiative (IMI) grant agreement 115736. Funding Information: This work is part of the EPAD LCS (European Prevention of Alzheimer’s Dementia Longitudinal Cohort Study). The authors would like to express their gratitude to the EPAD-LCS participants, without whom this research would have not been possible. EPAD is supported by the European Union/European federation of pharmaceutical industries and associations (EFPIA) Innovative Medicines Initiative (IMI) grant agreement 115736. A.M.W., L.C., H.M., and F.B. are supported by Amyloid Imaging to Prevent Alzheimer’s disease (AMYPAD—IMI 115952). F.B. is supported by the National Institute for health and care research (NIHR) biomedical research center at University college of London hospital (UCLH). L.C. has received research support from GE Healthcare (paid to institution). H.M. is supported by the Dutch Heart Foundation (2020T049), by the Eurostars-2 joint programme with co-funding from the European Union Horizon 2020 research and innovation programme, provided by the Netherlands Enterprise Agency (RvO), and by the EU Joint Program for Neurodegenerative Disease Research, provided by the Netherlands Organisation for health Research and Development and Alzheimer Nederland. K.B. is supported by the Swedish Research Council (#2017-00915), the Alzheimer Drug Discovery Foundation (ADDF), USA (#RDAPB-201809-2016615), the Swedish Alzheimer Foundation (#AF-742881), Hjärnfonden, Sweden (#FO2017-0243), the Swedish state under the agreement between the Swedish government and the County Councils, the ALF-agreement (#ALFGBG-715986), the European Union Joint Program for Neurodegenerative Disorders (JPND2019-466-236), and the National Institute of Health (NIH), USA, (grant #1R01AG068398-01). JMW is supported by the UK Dementia Research Institute (Foundation Chair) which receives its funding from Dementia research institute (DRI) Ltd, funded by the UK Medical Research Council, Alzheimer’s Society and Alzheimer’s Research UK. J.D.G. is supported by the Spanish Ministry of Science and Innovation (RYC-2013-13054) and the Agencia Estatal de Investigación Proyectos de I + D + i RETOS INVESTIGACIÓN (RTI2018-102261-B-I00). Funding Information: H.M. is supported by the Dutch Heart Foundation (2020T049), by the Eurostars-2 joint programme with co-funding from the European Union Horizon 2020 research and innovation programme, provided by the Netherlands Enterprise Agency (RvO), and by the EU Joint Program for Neurodegenerative Disease Research, provided by the Netherlands Organisation for health Research and Development and Alzheimer Nederland. Funding Information: F.B. is supported by the National Institute for health and care research (NIHR) biomedical research center at University college of London hospital (UCLH). Funding Information: J.D.G. is supported by the Spanish Ministry of Science and Innovation (RYC-2013-13054) and the Agencia Estatal de Investigación Proyectos de I + D + i RETOS INVESTIGACIÓN (RTI2018-102261-B-I00). Funding Information: K.B. is supported by the Swedish Research Council (#2017-00915), the Alzheimer Drug Discovery Foundation (ADDF), USA (#RDAPB-201809-2016615), the Swedish Alzheimer Foundation (#AF-742881), Hjärnfonden, Sweden (#FO2017-0243), the Swedish state under the agreement between the Swedish government and the County Councils, the ALF-agreement (#ALFGBG-715986), the European Union Joint Program for Neurodegenerative Disorders (JPND2019-466-236), and the National Institute of Health (NIH), USA, (grant #1R01AG068398-01). JMW is supported by the UK Dementia Research Institute (Foundation Chair) which receives its funding from Dementia research institute (DRI) Ltd, funded by the UK Medical Research Council, Alzheimer’s Society and Alzheimer’s Research UK. Publisher Copyright: © The Author(s) 2023. Published by Oxford University Press on behalf of the Guarantors of Brain.
PY - 2023
Y1 - 2023
N2 - Amyloid-β accumulation starts in highly connected brain regions and is associated with functional connectivity alterations in the early stages of Alzheimer’s disease. This regional vulnerability is related to the high neuronal activity and strong fluctuations typical of these regions. Recently, dynamic functional connectivity was introduced to investigate changes in functional network organization over time. High dynamic functional connectivity variations indicate increased regional flexibility to participate in multiple subnetworks, promoting functional integration. Currently, only a limited number of studies have explored the temporal dynamics of functional connectivity in the pre-dementia stages of Alzheimer’s disease. We study the associations between abnormal cerebrospinal fluid amyloid and both static and dynamic properties of functional hubs, using eigenvector centrality, and their relationship with cognitive performance, in 701 non-demented participants from the European Prevention of Alzheimer’s Dementia cohort. Voxel-wise eigenvector centrality was computed for the whole functional magnetic resonance imaging time series (static), and within a sliding window (dynamic). Differences in static eigenvector centrality between amyloid positive (A+) and negative (A-) participants and amyloid-tau groups were found in a general linear model. Dynamic eigenvector centrality standard deviation and range were compared between groups within clusters of significant static eigenvector centrality differences, and within 10 canonical resting-state networks. The effect of the interaction between amyloid status and cognitive performance on dynamic eigenvector centrality variability was also evaluated with linear models. Models were corrected for age, sex, and education level. Lower static centrality was found in A+ participants in posterior brain areas including a parietal and an occipital cluster; higher static centrality was found in a medio-frontal cluster. Lower eigenvector centrality variability (standard deviation) occurred in A+ participants in the frontal cluster. The default mode network and the dorsal visual networks of A+ participants had lower dynamic eigenvector centrality variability. Centrality variability in the default mode network and dorsal visual networks were associated with cognitive performance in the A- and A+ groups, with lower variability being observed in A+ participants with good cognitive scores. Our results support the role and timing of eigenvector centrality alterations in very early stages of Alzheimer’s disease and show that centrality variability over time adds relevant information on the dynamic patterns that cause static eigenvector centrality alterations. We propose that dynamic eigenvector centrality is an early biomarker of the interplay between early Alzheimer’s disease pathology and cognitive decline.
AB - Amyloid-β accumulation starts in highly connected brain regions and is associated with functional connectivity alterations in the early stages of Alzheimer’s disease. This regional vulnerability is related to the high neuronal activity and strong fluctuations typical of these regions. Recently, dynamic functional connectivity was introduced to investigate changes in functional network organization over time. High dynamic functional connectivity variations indicate increased regional flexibility to participate in multiple subnetworks, promoting functional integration. Currently, only a limited number of studies have explored the temporal dynamics of functional connectivity in the pre-dementia stages of Alzheimer’s disease. We study the associations between abnormal cerebrospinal fluid amyloid and both static and dynamic properties of functional hubs, using eigenvector centrality, and their relationship with cognitive performance, in 701 non-demented participants from the European Prevention of Alzheimer’s Dementia cohort. Voxel-wise eigenvector centrality was computed for the whole functional magnetic resonance imaging time series (static), and within a sliding window (dynamic). Differences in static eigenvector centrality between amyloid positive (A+) and negative (A-) participants and amyloid-tau groups were found in a general linear model. Dynamic eigenvector centrality standard deviation and range were compared between groups within clusters of significant static eigenvector centrality differences, and within 10 canonical resting-state networks. The effect of the interaction between amyloid status and cognitive performance on dynamic eigenvector centrality variability was also evaluated with linear models. Models were corrected for age, sex, and education level. Lower static centrality was found in A+ participants in posterior brain areas including a parietal and an occipital cluster; higher static centrality was found in a medio-frontal cluster. Lower eigenvector centrality variability (standard deviation) occurred in A+ participants in the frontal cluster. The default mode network and the dorsal visual networks of A+ participants had lower dynamic eigenvector centrality variability. Centrality variability in the default mode network and dorsal visual networks were associated with cognitive performance in the A- and A+ groups, with lower variability being observed in A+ participants with good cognitive scores. Our results support the role and timing of eigenvector centrality alterations in very early stages of Alzheimer’s disease and show that centrality variability over time adds relevant information on the dynamic patterns that cause static eigenvector centrality alterations. We propose that dynamic eigenvector centrality is an early biomarker of the interplay between early Alzheimer’s disease pathology and cognitive decline.
KW - amyloid
KW - eigenvector centrality
KW - functional connectivity
KW - preclinical Alzheimer’s disease
UR - http://www.scopus.com/inward/record.url?scp=85161049545&partnerID=8YFLogxK
U2 - https://doi.org/10.1093/braincomms/fcad088
DO - https://doi.org/10.1093/braincomms/fcad088
M3 - Article
C2 - 37151225
SN - 2632-1297
VL - 5
JO - Brain Communications
JF - Brain Communications
IS - 3
M1 - fcad088
ER -