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In Alzheimer-prone brain regions, metabolism and risk-gene expression are strongly correlated

Neuroimaging in the preclinical phase of Alzheimer’s disease provides information crucial to early intervention, particularly in people with a high genetic risk. Metabolic network modularity, recently applied to the study of dementia, is increased in Alzheimer’s disease patients compared with contro...

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Autores principales: Ye, Fengdan, Funk, Quentin, Rockers, Elijah, Shulman, Joshua M, Masdeu, Joseph C, Pascual, Belen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9453434/
https://www.ncbi.nlm.nih.gov/pubmed/36092303
http://dx.doi.org/10.1093/braincomms/fcac216
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author Ye, Fengdan
Funk, Quentin
Rockers, Elijah
Shulman, Joshua M
Masdeu, Joseph C
Pascual, Belen
author_facet Ye, Fengdan
Funk, Quentin
Rockers, Elijah
Shulman, Joshua M
Masdeu, Joseph C
Pascual, Belen
author_sort Ye, Fengdan
collection PubMed
description Neuroimaging in the preclinical phase of Alzheimer’s disease provides information crucial to early intervention, particularly in people with a high genetic risk. Metabolic network modularity, recently applied to the study of dementia, is increased in Alzheimer’s disease patients compared with controls, but network modularity in cognitively unimpaired elderly with various risks of developing Alzheimer’s disease needs to be determined. Based on their 5-year cognitive progression, we stratified 117 cognitively normal participants (78.3 ± 4.0 years of age, 52 women) into three age-matched groups, each with a different level of risk for Alzheimer’s disease. From their fluorodeoxyglucose PET we constructed metabolic networks, evaluated their modular structures using the Louvain algorithm, and compared them between risk groups. As the risk for Alzheimer’s disease increased, the metabolic connections among brain regions weakened and became more modular, indicating network fragmentation and functional impairment of the brain. We then set out to determine the correlation between regional brain metabolism, particularly in the modules derived from the previous analysis, and the regional expression of Alzheimer-risk genes in the brain, obtained from the Allen Human Brain Atlas. In all risk groups of this elderly population, the regional brain expression of most Alzheimer-risk genes showed a strong correlation with brain metabolism, particularly in the module that corresponded to regions of the brain that are affected earliest and most severely in Alzheimer’s disease. Among the genes, APOE and CD33 showed the strongest negative correlation and SORL1 showed the strongest positive correlation with brain metabolism. The Pearson correlation coefficients remained significant when contrasted against a null-hypothesis distribution of correlation coefficients across the whole transcriptome of 20 736 genes (SORL1: P = 0.0130; CD33, P = 0.0136; APOE: P = 0.0093). The strong regional correlation between Alzheimer-related gene expression in the brain and brain metabolism in older adults highlights the role of brain metabolism in the genesis of dementia.
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spelling pubmed-94534342022-09-09 In Alzheimer-prone brain regions, metabolism and risk-gene expression are strongly correlated Ye, Fengdan Funk, Quentin Rockers, Elijah Shulman, Joshua M Masdeu, Joseph C Pascual, Belen Brain Commun Original Article Neuroimaging in the preclinical phase of Alzheimer’s disease provides information crucial to early intervention, particularly in people with a high genetic risk. Metabolic network modularity, recently applied to the study of dementia, is increased in Alzheimer’s disease patients compared with controls, but network modularity in cognitively unimpaired elderly with various risks of developing Alzheimer’s disease needs to be determined. Based on their 5-year cognitive progression, we stratified 117 cognitively normal participants (78.3 ± 4.0 years of age, 52 women) into three age-matched groups, each with a different level of risk for Alzheimer’s disease. From their fluorodeoxyglucose PET we constructed metabolic networks, evaluated their modular structures using the Louvain algorithm, and compared them between risk groups. As the risk for Alzheimer’s disease increased, the metabolic connections among brain regions weakened and became more modular, indicating network fragmentation and functional impairment of the brain. We then set out to determine the correlation between regional brain metabolism, particularly in the modules derived from the previous analysis, and the regional expression of Alzheimer-risk genes in the brain, obtained from the Allen Human Brain Atlas. In all risk groups of this elderly population, the regional brain expression of most Alzheimer-risk genes showed a strong correlation with brain metabolism, particularly in the module that corresponded to regions of the brain that are affected earliest and most severely in Alzheimer’s disease. Among the genes, APOE and CD33 showed the strongest negative correlation and SORL1 showed the strongest positive correlation with brain metabolism. The Pearson correlation coefficients remained significant when contrasted against a null-hypothesis distribution of correlation coefficients across the whole transcriptome of 20 736 genes (SORL1: P = 0.0130; CD33, P = 0.0136; APOE: P = 0.0093). The strong regional correlation between Alzheimer-related gene expression in the brain and brain metabolism in older adults highlights the role of brain metabolism in the genesis of dementia. Oxford University Press 2022-08-25 /pmc/articles/PMC9453434/ /pubmed/36092303 http://dx.doi.org/10.1093/braincomms/fcac216 Text en © The Author(s) 2022. Published by Oxford University Press on behalf of the Guarantors of Brain. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Ye, Fengdan
Funk, Quentin
Rockers, Elijah
Shulman, Joshua M
Masdeu, Joseph C
Pascual, Belen
In Alzheimer-prone brain regions, metabolism and risk-gene expression are strongly correlated
title In Alzheimer-prone brain regions, metabolism and risk-gene expression are strongly correlated
title_full In Alzheimer-prone brain regions, metabolism and risk-gene expression are strongly correlated
title_fullStr In Alzheimer-prone brain regions, metabolism and risk-gene expression are strongly correlated
title_full_unstemmed In Alzheimer-prone brain regions, metabolism and risk-gene expression are strongly correlated
title_short In Alzheimer-prone brain regions, metabolism and risk-gene expression are strongly correlated
title_sort in alzheimer-prone brain regions, metabolism and risk-gene expression are strongly correlated
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9453434/
https://www.ncbi.nlm.nih.gov/pubmed/36092303
http://dx.doi.org/10.1093/braincomms/fcac216
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