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Cardiometabolic risk factors associated with brain age and accelerate brain ageing
The structure and integrity of the ageing brain is interchangeably linked to physical health, and cardiometabolic risk factors (CMRs) are associated with dementia and other brain disorders. In this mixed cross‐sectional and longitudinal study (interval mean = 19.7 months), including 790 healthy indi...
Autores principales: | , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley & Sons, Inc.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8720200/ https://www.ncbi.nlm.nih.gov/pubmed/34626047 http://dx.doi.org/10.1002/hbm.25680 |
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author | Beck, Dani de Lange, Ann‐Marie G. Pedersen, Mads L. Alnæs, Dag Maximov, Ivan I. Voldsbekk, Irene Richard, Geneviève Sanders, Anne‐Marthe Ulrichsen, Kristine M. Dørum, Erlend S. Kolskår, Knut K. Høgestøl, Einar A. Steen, Nils Eiel Djurovic, Srdjan Andreassen, Ole A. Nordvik, Jan E. Kaufmann, Tobias Westlye, Lars T. |
author_facet | Beck, Dani de Lange, Ann‐Marie G. Pedersen, Mads L. Alnæs, Dag Maximov, Ivan I. Voldsbekk, Irene Richard, Geneviève Sanders, Anne‐Marthe Ulrichsen, Kristine M. Dørum, Erlend S. Kolskår, Knut K. Høgestøl, Einar A. Steen, Nils Eiel Djurovic, Srdjan Andreassen, Ole A. Nordvik, Jan E. Kaufmann, Tobias Westlye, Lars T. |
author_sort | Beck, Dani |
collection | PubMed |
description | The structure and integrity of the ageing brain is interchangeably linked to physical health, and cardiometabolic risk factors (CMRs) are associated with dementia and other brain disorders. In this mixed cross‐sectional and longitudinal study (interval mean = 19.7 months), including 790 healthy individuals (mean age = 46.7 years, 53% women), we investigated CMRs and health indicators including anthropometric measures, lifestyle factors, and blood biomarkers in relation to brain structure using MRI‐based morphometry and diffusion tensor imaging (DTI). We performed tissue specific brain age prediction using machine learning and performed Bayesian multilevel modeling to assess changes in each CMR over time, their respective association with brain age gap (BAG), and their interaction effects with time and age on the tissue‐specific BAGs. The results showed credible associations between DTI‐based BAG and blood levels of phosphate and mean cell volume (MCV), and between T1‐based BAG and systolic blood pressure, smoking, pulse, and C‐reactive protein (CRP), indicating older‐appearing brains in people with higher cardiometabolic risk (smoking, higher blood pressure and pulse, low‐grade inflammation). Longitudinal evidence supported interactions between both BAGs and waist‐to‐hip ratio (WHR), and between DTI‐based BAG and systolic blood pressure and smoking, indicating accelerated ageing in people with higher cardiometabolic risk (smoking, higher blood pressure, and WHR). The results demonstrate that cardiometabolic risk factors are associated with brain ageing. While randomized controlled trials are needed to establish causality, our results indicate that public health initiatives and treatment strategies targeting modifiable cardiometabolic risk factors may also improve risk trajectories and delay brain ageing. |
format | Online Article Text |
id | pubmed-8720200 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | John Wiley & Sons, Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-87202002022-01-07 Cardiometabolic risk factors associated with brain age and accelerate brain ageing Beck, Dani de Lange, Ann‐Marie G. Pedersen, Mads L. Alnæs, Dag Maximov, Ivan I. Voldsbekk, Irene Richard, Geneviève Sanders, Anne‐Marthe Ulrichsen, Kristine M. Dørum, Erlend S. Kolskår, Knut K. Høgestøl, Einar A. Steen, Nils Eiel Djurovic, Srdjan Andreassen, Ole A. Nordvik, Jan E. Kaufmann, Tobias Westlye, Lars T. Hum Brain Mapp Research Articles The structure and integrity of the ageing brain is interchangeably linked to physical health, and cardiometabolic risk factors (CMRs) are associated with dementia and other brain disorders. In this mixed cross‐sectional and longitudinal study (interval mean = 19.7 months), including 790 healthy individuals (mean age = 46.7 years, 53% women), we investigated CMRs and health indicators including anthropometric measures, lifestyle factors, and blood biomarkers in relation to brain structure using MRI‐based morphometry and diffusion tensor imaging (DTI). We performed tissue specific brain age prediction using machine learning and performed Bayesian multilevel modeling to assess changes in each CMR over time, their respective association with brain age gap (BAG), and their interaction effects with time and age on the tissue‐specific BAGs. The results showed credible associations between DTI‐based BAG and blood levels of phosphate and mean cell volume (MCV), and between T1‐based BAG and systolic blood pressure, smoking, pulse, and C‐reactive protein (CRP), indicating older‐appearing brains in people with higher cardiometabolic risk (smoking, higher blood pressure and pulse, low‐grade inflammation). Longitudinal evidence supported interactions between both BAGs and waist‐to‐hip ratio (WHR), and between DTI‐based BAG and systolic blood pressure and smoking, indicating accelerated ageing in people with higher cardiometabolic risk (smoking, higher blood pressure, and WHR). The results demonstrate that cardiometabolic risk factors are associated with brain ageing. While randomized controlled trials are needed to establish causality, our results indicate that public health initiatives and treatment strategies targeting modifiable cardiometabolic risk factors may also improve risk trajectories and delay brain ageing. John Wiley & Sons, Inc. 2021-10-09 /pmc/articles/PMC8720200/ /pubmed/34626047 http://dx.doi.org/10.1002/hbm.25680 Text en © 2021 The Authors. Human Brain Mapping published by Wiley Periodicals LLC. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made. |
spellingShingle | Research Articles Beck, Dani de Lange, Ann‐Marie G. Pedersen, Mads L. Alnæs, Dag Maximov, Ivan I. Voldsbekk, Irene Richard, Geneviève Sanders, Anne‐Marthe Ulrichsen, Kristine M. Dørum, Erlend S. Kolskår, Knut K. Høgestøl, Einar A. Steen, Nils Eiel Djurovic, Srdjan Andreassen, Ole A. Nordvik, Jan E. Kaufmann, Tobias Westlye, Lars T. Cardiometabolic risk factors associated with brain age and accelerate brain ageing |
title | Cardiometabolic risk factors associated with brain age and accelerate brain ageing |
title_full | Cardiometabolic risk factors associated with brain age and accelerate brain ageing |
title_fullStr | Cardiometabolic risk factors associated with brain age and accelerate brain ageing |
title_full_unstemmed | Cardiometabolic risk factors associated with brain age and accelerate brain ageing |
title_short | Cardiometabolic risk factors associated with brain age and accelerate brain ageing |
title_sort | cardiometabolic risk factors associated with brain age and accelerate brain ageing |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8720200/ https://www.ncbi.nlm.nih.gov/pubmed/34626047 http://dx.doi.org/10.1002/hbm.25680 |
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