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A latent clinical-anatomical dimension relating metabolic syndrome to brain structure and cognition
The link between metabolic syndrome (MetS) and neurodegenerative as well cerebrovascular conditions holds substantial implications for brain health in at-risk populations. This study elucidates the complex relationship between metabolic syndrome (MetS) and brain health by conducting a comprehensive...
Autores principales: | , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cold Spring Harbor Laboratory
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9980040/ https://www.ncbi.nlm.nih.gov/pubmed/36865285 http://dx.doi.org/10.1101/2023.02.22.529531 |
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author | Petersen, Marvin Hoffstaedter, Felix Nägele, Felix L. Mayer, Carola Schell, Maximilian Rimmele, D. Leander Zyriax, Birgit-Christiane Zeller, Tanja Kühn, Simone Gallinat, Jürgen Fiehler, Jens Twerenbold, Raphael Omidvarnia, Amir Patil, Kaustubh R. Eickhoff, Simon B. Thomalla, Götz Cheng, Bastian |
author_facet | Petersen, Marvin Hoffstaedter, Felix Nägele, Felix L. Mayer, Carola Schell, Maximilian Rimmele, D. Leander Zyriax, Birgit-Christiane Zeller, Tanja Kühn, Simone Gallinat, Jürgen Fiehler, Jens Twerenbold, Raphael Omidvarnia, Amir Patil, Kaustubh R. Eickhoff, Simon B. Thomalla, Götz Cheng, Bastian |
author_sort | Petersen, Marvin |
collection | PubMed |
description | The link between metabolic syndrome (MetS) and neurodegenerative as well cerebrovascular conditions holds substantial implications for brain health in at-risk populations. This study elucidates the complex relationship between metabolic syndrome (MetS) and brain health by conducting a comprehensive examination of cardiometabolic risk factors, cortical morphology, and cognitive function in 40,087 individuals. Multivariate, data-driven statistics identified a latent dimension linking more severe MetS to widespread cortical abnormalities and lower cognitive performance, accounting for up to 77% of shared variance in the data. This dimension was replicable across sub-samples. Our results also suggest that MetS-related cortical effects are shaped by the regional cellular composition and macroscopic brain network organization. By leveraging extensive, multi-domain data combined with a dimensional stratification approach, our analysis provides profound insights into the association of MetS and brain health. These findings underscore the necessity for effective risk mitigation strategies aimed at maintaining brain integrity. |
format | Online Article Text |
id | pubmed-9980040 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Cold Spring Harbor Laboratory |
record_format | MEDLINE/PubMed |
spelling | pubmed-99800402023-03-03 A latent clinical-anatomical dimension relating metabolic syndrome to brain structure and cognition Petersen, Marvin Hoffstaedter, Felix Nägele, Felix L. Mayer, Carola Schell, Maximilian Rimmele, D. Leander Zyriax, Birgit-Christiane Zeller, Tanja Kühn, Simone Gallinat, Jürgen Fiehler, Jens Twerenbold, Raphael Omidvarnia, Amir Patil, Kaustubh R. Eickhoff, Simon B. Thomalla, Götz Cheng, Bastian bioRxiv Article The link between metabolic syndrome (MetS) and neurodegenerative as well cerebrovascular conditions holds substantial implications for brain health in at-risk populations. This study elucidates the complex relationship between metabolic syndrome (MetS) and brain health by conducting a comprehensive examination of cardiometabolic risk factors, cortical morphology, and cognitive function in 40,087 individuals. Multivariate, data-driven statistics identified a latent dimension linking more severe MetS to widespread cortical abnormalities and lower cognitive performance, accounting for up to 77% of shared variance in the data. This dimension was replicable across sub-samples. Our results also suggest that MetS-related cortical effects are shaped by the regional cellular composition and macroscopic brain network organization. By leveraging extensive, multi-domain data combined with a dimensional stratification approach, our analysis provides profound insights into the association of MetS and brain health. These findings underscore the necessity for effective risk mitigation strategies aimed at maintaining brain integrity. Cold Spring Harbor Laboratory 2023-10-12 /pmc/articles/PMC9980040/ /pubmed/36865285 http://dx.doi.org/10.1101/2023.02.22.529531 Text en https://creativecommons.org/licenses/by-nc-nd/4.0/This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which allows reusers to copy and distribute the material in any medium or format in unadapted form only, for noncommercial purposes only, and only so long as attribution is given to the creator. |
spellingShingle | Article Petersen, Marvin Hoffstaedter, Felix Nägele, Felix L. Mayer, Carola Schell, Maximilian Rimmele, D. Leander Zyriax, Birgit-Christiane Zeller, Tanja Kühn, Simone Gallinat, Jürgen Fiehler, Jens Twerenbold, Raphael Omidvarnia, Amir Patil, Kaustubh R. Eickhoff, Simon B. Thomalla, Götz Cheng, Bastian A latent clinical-anatomical dimension relating metabolic syndrome to brain structure and cognition |
title | A latent clinical-anatomical dimension relating metabolic syndrome to brain structure and cognition |
title_full | A latent clinical-anatomical dimension relating metabolic syndrome to brain structure and cognition |
title_fullStr | A latent clinical-anatomical dimension relating metabolic syndrome to brain structure and cognition |
title_full_unstemmed | A latent clinical-anatomical dimension relating metabolic syndrome to brain structure and cognition |
title_short | A latent clinical-anatomical dimension relating metabolic syndrome to brain structure and cognition |
title_sort | latent clinical-anatomical dimension relating metabolic syndrome to brain structure and cognition |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9980040/ https://www.ncbi.nlm.nih.gov/pubmed/36865285 http://dx.doi.org/10.1101/2023.02.22.529531 |
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