Machine-learning-derived heart and brain age are independently associated with cognition

10Citations
Citations of this article
8Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

Background and purpose: A heart age biomarker has been developed using deep neural networks applied to electrocardiograms. Whether this biomarker is associated with cognitive function was investigated. Methods: Using 12-lead electrocardiograms, heart age was estimated for a population-based sample (N = 7779, age 40–85 years, 45.3% men). Associations between heart delta age (HDA) and cognitive test scores were studied adjusted for cardiovascular risk factors. In addition, the relationship between HDA, brain delta age (BDA) and cognitive test scores was investigated in mediation analysis. Results: Significant associations between HDA and the Word test, Digit Symbol Coding Test and tapping test scores were found. HDA was correlated with BDA (Pearson's r = 0.12, p = 0.0001). Moreover, 13% (95% confidence interval 3–36) of the HDA effect on the tapping test score was mediated through BDA. Discussion: Heart delta age, representing the cumulative effects of life-long exposures, was associated with brain age. HDA was associated with cognitive function that was minimally explained through BDA.

Cite

CITATION STYLE

APA

Iakunchykova, O., Schirmer, H., Vangberg, T., Wang, Y., Benavente, E. D., van Es, R., … Wilsgaard, T. (2023). Machine-learning-derived heart and brain age are independently associated with cognition. European Journal of Neurology, 30(9), 2611–2619. https://doi.org/10.1111/ene.15902

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free