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The link between static and dynamic brain functional network connectivity and genetic risk of Alzheimer's disease

Apolipoprotein E (APOE) polymorphic alleles are genetic factors associated with Alzheimer’s disease (AD) risk. Although previous studies have explored the link between AD genetic risk and static functional network connectivity (sFNC), to the best of our knowledge, no previous studies have evaluated...

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Autores principales: Sendi, Mohammad S.E., Zendehrouh, Elaheh, Ellis, Charles A., Fu, Zening, Chen, Jiayu, Miller, Robyn L., Mormino, Elizabeth C., Salat, David H., Calhoun, Vince D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9999198/
https://www.ncbi.nlm.nih.gov/pubmed/36871405
http://dx.doi.org/10.1016/j.nicl.2023.103363
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author Sendi, Mohammad S.E.
Zendehrouh, Elaheh
Ellis, Charles A.
Fu, Zening
Chen, Jiayu
Miller, Robyn L.
Mormino, Elizabeth C.
Salat, David H.
Calhoun, Vince D.
author_facet Sendi, Mohammad S.E.
Zendehrouh, Elaheh
Ellis, Charles A.
Fu, Zening
Chen, Jiayu
Miller, Robyn L.
Mormino, Elizabeth C.
Salat, David H.
Calhoun, Vince D.
author_sort Sendi, Mohammad S.E.
collection PubMed
description Apolipoprotein E (APOE) polymorphic alleles are genetic factors associated with Alzheimer’s disease (AD) risk. Although previous studies have explored the link between AD genetic risk and static functional network connectivity (sFNC), to the best of our knowledge, no previous studies have evaluated the association between dynamic FNC (dFNC) and AD genetic risk. Here, we examined the link between sFNC, dFNC, and AD genetic risk with a data-driven approach. We used rs-fMRI, demographic, and APOE data from cognitively normal individuals (N = 886) between 42 and 95 years of age (mean = 70 years). We separated individuals into low, moderate, and high-risk groups. Using Pearson correlation, we calculated sFNC across seven brain networks. We also calculated dFNC with a sliding window and Pearson correlation. The dFNC windows were partitioned into three distinct states with k-means clustering. Next, we calculated the proportion of time each subject spent in each state, called occupancy rate or OCR and frequency of visits. We compared both sFNC and dFNC features across individuals with different genetic risks and found that both sFNC and dFNC are related to AD genetic risk. We found that higher AD risk reduces within-visual sensory network (VSN) sFNC and that individuals with higher AD risk spend more time in a state with lower within-VSN dFNC. We also found that AD genetic risk affects whole-brain sFNC and dFNC in women but not men. In conclusion, we presented novel insights into the links between sFNC, dFNC, and AD genetic risk.
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spelling pubmed-99991982023-03-11 The link between static and dynamic brain functional network connectivity and genetic risk of Alzheimer's disease Sendi, Mohammad S.E. Zendehrouh, Elaheh Ellis, Charles A. Fu, Zening Chen, Jiayu Miller, Robyn L. Mormino, Elizabeth C. Salat, David H. Calhoun, Vince D. Neuroimage Clin Regular Article Apolipoprotein E (APOE) polymorphic alleles are genetic factors associated with Alzheimer’s disease (AD) risk. Although previous studies have explored the link between AD genetic risk and static functional network connectivity (sFNC), to the best of our knowledge, no previous studies have evaluated the association between dynamic FNC (dFNC) and AD genetic risk. Here, we examined the link between sFNC, dFNC, and AD genetic risk with a data-driven approach. We used rs-fMRI, demographic, and APOE data from cognitively normal individuals (N = 886) between 42 and 95 years of age (mean = 70 years). We separated individuals into low, moderate, and high-risk groups. Using Pearson correlation, we calculated sFNC across seven brain networks. We also calculated dFNC with a sliding window and Pearson correlation. The dFNC windows were partitioned into three distinct states with k-means clustering. Next, we calculated the proportion of time each subject spent in each state, called occupancy rate or OCR and frequency of visits. We compared both sFNC and dFNC features across individuals with different genetic risks and found that both sFNC and dFNC are related to AD genetic risk. We found that higher AD risk reduces within-visual sensory network (VSN) sFNC and that individuals with higher AD risk spend more time in a state with lower within-VSN dFNC. We also found that AD genetic risk affects whole-brain sFNC and dFNC in women but not men. In conclusion, we presented novel insights into the links between sFNC, dFNC, and AD genetic risk. Elsevier 2023-02-27 /pmc/articles/PMC9999198/ /pubmed/36871405 http://dx.doi.org/10.1016/j.nicl.2023.103363 Text en © 2023 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Regular Article
Sendi, Mohammad S.E.
Zendehrouh, Elaheh
Ellis, Charles A.
Fu, Zening
Chen, Jiayu
Miller, Robyn L.
Mormino, Elizabeth C.
Salat, David H.
Calhoun, Vince D.
The link between static and dynamic brain functional network connectivity and genetic risk of Alzheimer's disease
title The link between static and dynamic brain functional network connectivity and genetic risk of Alzheimer's disease
title_full The link between static and dynamic brain functional network connectivity and genetic risk of Alzheimer's disease
title_fullStr The link between static and dynamic brain functional network connectivity and genetic risk of Alzheimer's disease
title_full_unstemmed The link between static and dynamic brain functional network connectivity and genetic risk of Alzheimer's disease
title_short The link between static and dynamic brain functional network connectivity and genetic risk of Alzheimer's disease
title_sort link between static and dynamic brain functional network connectivity and genetic risk of alzheimer's disease
topic Regular Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9999198/
https://www.ncbi.nlm.nih.gov/pubmed/36871405
http://dx.doi.org/10.1016/j.nicl.2023.103363
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