Abstract
Cerebrovascular support is critical for healthy cognitive aging—arterial stiffness (arteriosclerosis) has been linked to heightened risks for cognitive decline, and ultimately for Alzheimer’s disease and other forms of dementia. Conversely, neurovascular health is supported by lifestyle factors, including cardiorespiratory fitness. Here, capitalizing on a relatively large sample of participants with neuroimaging and behavioral data (N = 173, age range = 18-87 years), we aimed to provide support for a hierarchical model of neurocognitive aging, which links age-related declines in cerebrovascular health to the rate of cognitive decline via a series of intervening variables, such as cardiorespiratory fitness and white matter integrity. By applying a novel piecewise regression approach to our cross-sectional sample to support Granger-like causality inferences, we show that, on average, a precipitous decline in cerebral arterial elasticity (measured with diffuse optical imaging of the cerebral arterial pulse; pulse-DOT) temporally precedes an acceleration in the development of white matter lesions (T1-weighted MRI white matter hypointensities) by nearly a decade. And by employing serial mediation analyses, we show that age may impair cognition via the sequential indirect effect of arteriosclerosis and demyelination on fluid, but not crystallized, abilities. Importantly, we replicate these results using pulse pressure, an independent index of arterial health, thereby providing converging evidence for the central role of arteriosclerosis as an accelerating factor in normal and pathological aging. Enhanced cardiorespiratory fitness may also confer neuroprotective benefits by slowing the rate of arteriosclerosis.
Competing Interest Statement
The authors have declared no competing interest.
Footnotes
Statement of conflict interests: None of the authors of this article has any financial or other conflicts of interest regarding this work.
Data/code availability statement: Code for analyses will be made publicly available via GitHub upon publication. Data will be made available at the end of the overarching project.
