Cardiovascular and metabolic health is associated with functional brain connectivity in middle-aged and older adults: Results from the Human Connectome Project-Aging study

Several cardiovascular and metabolic indicators, such as cholesterol and blood pressure have been associated with altered neural and cognitive health as well as increased risk of dementia and Alzheimer's disease in later life. In this cross-sectional study, we examined how an aggregate index of...

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Veröffentlicht in:NeuroImage (Orlando, Fla.) Fla.), 2023-08, Vol.276, p.120192-120192, Article 120192
Hauptverfasser: Rashid, Barnaly, Glasser, Matthew F., Nichols, Thomas, Van Essen, David, Juttukonda, Meher R., Schwab, Nadine A., Greve, Douglas N, Yacoub, Essa, Lovely, Allison, Terpstra, Melissa, Harms, Michael P., Bookheimer, Susan Y., Ances, Beau M., Salat, David H., Arnold, Steven E.
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Sprache:eng
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Zusammenfassung:Several cardiovascular and metabolic indicators, such as cholesterol and blood pressure have been associated with altered neural and cognitive health as well as increased risk of dementia and Alzheimer's disease in later life. In this cross-sectional study, we examined how an aggregate index of cardiovascular and metabolic risk factor measures was associated with correlation-based estimates of resting-state functional connectivity (FC) across a broad adult age-span (36–90+ years) from 930 volunteers in the Human Connectome Project Aging (HCP-A). Increased (i.e., worse) aggregate cardiometabolic scores were associated with reduced FC globally, with especially strong effects in insular, medial frontal, medial parietal, and superior temporal regions. Additionally, at the network-level, FC between core brain networks, such as default-mode and cingulo-opercular, as well as dorsal attention networks, showed strong effects of cardiometabolic risk. These findings highlight the lifespan impact of cardiovascular and metabolic health on whole-brain functional integrity and how these conditions may disrupt higher-order network integrity.
ISSN:1053-8119
1095-9572
DOI:10.1016/j.neuroimage.2023.120192