Machine-learning-derived heart and brain age are independently associated with cognition
Publication date
2023-09
Authors
Iakunchykova, Olena
Schirmer, Henrik
Vangberg, Torgil
Wang, Yunpeng
Diez Benavente, Ernest
van Es, René
van de Leur, Rutger
Lindekleiv, Haakon
Attia, Zachi I.
Lopez-Jimenez, Francisco
Editors
Advisors
Supervisors
Document Type
Article
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License
cc_by_nc_nd
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.
Keywords
cognitive tests, deep neural networks, dementia, ECG, MRI, Neurology, Clinical Neurology
Citation
Iakunchykova, O, Schirmer, H, Vangberg, T, Wang, Y, Benavente, E D, van Es, R, van de Leur, R R, Lindekleiv, H, Attia, Z I, Lopez-Jimenez, F, Leon, D A & Wilsgaard, T 2023, 'Machine-learning-derived heart and brain age are independently associated with cognition', European Journal of Neurology, vol. 30, no. 9, pp. 2611-2619. https://doi.org/10.1111/ene.15902