Characterizing Brain–Cardiovascular Aging Using Multiorgan Imaging and Machine Learning

The structure and function of the brain and cardiovascular system change over the lifespan. In this study, we aim to establish the extent to which age-related changes in these two vital organs are linked. Utilizing normative models and data from the UK Biobank, we estimate biological ages for the brain and heart for 2,904 middle-aged and older healthy adults, including both males and females. Biological ages were based on multiple structural, morphological, and functional features derived from brain and cardiovascular imaging modalities. We find that cardiovascular aging, particularly aging of its functional capacity and physiology, is selectively associated with the aging of specific brain networks, including the salience, default mode, and somatomotor networks as well as the subcortex. Our work provides unique insight into brain-heart relationships and may facilitate an improved understanding of the increased co-occurrence of brain and heart diseases in aging.

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Publication Details

Journal
Journal of Neuroscience
Published
2024-12-30
DOI
https://doi.org/10.1523/jneurosci.1440-24.2024
Citations
3
Primary Topic
Functional Brain Connectivity Studies
Type
article
Field-Weighted Citation Impact
1.03
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article

Characterizing Brain–Cardiovascular Aging Using Multiorgan Imaging and Machine Learning

Caio Seguin, Yalda Amirmoezzi, Andrew Zalesky, Sina Mansour L. et al.
3 citations
Journal of Neuroscience
Functional Brain Connectivity Studies
1.03
article

Characterizing Brain–Cardiovascular Aging Using Multiorgan Imaging and Machine Learning

Caio Seguin, Yalda Amirmoezzi, Andrew Zalesky, Sina Mansour L., Ye Tian, Vanessa Cropley
article en
3 citations

Abstract

The structure and function of the brain and cardiovascular system change over the lifespan. In this study, we aim to establish the extent to which age-related changes in these two vital organs are linked. Utilizing normative models and data from the UK Biobank, we estimate biological ages for the brain and heart for 2,904 middle-aged and older healthy adults, including both males and females. Biological ages were based on multiple structural, morphological, and functional features derived from brain and cardiovascular imaging modalities. We find that cardiovascular aging, particularly aging of its functional capacity and physiology, is selectively associated with the aging of specific brain networks, including the salience, default mode, and somatomotor networks as well as the subcortex. Our work provides unique insight into brain-heart relationships and may facilitate an improved understanding of the increased co-occurrence of brain and heart diseases in aging.

Journal of NeuroscienceVol. 45(8)
The University of Melbourne (AU), National University of Singapore (SG), Orygen (AU), Indiana University Bloomington (US), Indiana University (US)
Openalex Percentile: Top 23%
Functional Brain Connectivity Studies
1.03
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Characterizing Brain–Cardiovascular Aging Using Multiorgan Imaging and Machine Learning — Caio Seguin, Yalda Amirmoezzi, et al. · Journal of Neuroscience (2024) | TGRS Research Map | TGRS