A latent clinical-anatomical dimension relating metabolic syndrome to brain structure and cognition
Loading...
Citations
Scopus:
Altmetric:
Altmetric::
Download
Associated Records
Authors
File Licence
Editors
Date
2024-03-21
Source Title
eLife
Journal Title
Journal ISSN
Volume Title
Publisher
eLIFE SCIENCES PUBL LTD
Melbourne Authors
Affiliation
Florey Department of Neuroscience and Mental Health
Document Type
Journal Article
Subject Code
Citation
Petersen, M., Hoffstaedter, F., Nägele, F. L., Mayer, C., Schell, M., Rimmele, D. L., Zyriax, B. C., Zeller, T., Kühn, S., Gallinat, J., Fiehler, J., Twerenbold, R., Omidvarnia, A., Patil, K. R., Eickhoff, S. B., Thomalla, G. & Cheng, B. (2024). A latent clinical-anatomical dimension relating metabolic syndrome to brain structure and cognition. eLife, 12, https://doi.org/10.7554/eLife.93246.
Access Status
Open Access
Access URL
Open Access URL
published version
Open Access at PMC
Linked Resource URL
NHMRC Grant Code
ARC Grant Code
Description
Abstract
The link between metabolic syndrome (MetS) and neurodegenerative as well as cerebrovascular conditions holds substantial implications for brain health in at-risk populations. This study elucidates the complex relationship between MetS and brain health by conducting a comprehensive examination of cardiometabolic risk factors, brain morphology, and cognitive function in 40,087 individuals. Multivariate, data-driven statistics identified a latent dimension linking more severe MetS to widespread brain morphological abnormalities, accounting for up to 71% of shared variance in the data. This dimension was replicable across sub-samples. In a mediation analysis, we could demonstrate that MetS-related brain morphological abnormalities mediated the link between MetS severity and cognitive performance in multiple domains. Employing imaging transcriptomics and connectomics, our results also suggest that MetS-related morphological abnormalities are linked to 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 can inform effective therapeutic and risk mitigation strategies aimed at maintaining brain integrity.