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Biological heart and brain ageing in subjects with cardiovascular diseases
Elizabeth Mcavoy1,2,3, Matthias Wilms1,2,4,5,6, Nils D Forkert1,2,4,7
1Department of Radiology, University of Calgary, Calgary, AB, Canada.
Insights
Cardiovascular diseases impact brain and heart aging differently, challenging the heart-brain axis theory. Quantifying brain age gap and heart age gap revealed varied effects across conditions and sexes.
Area of Science:
- Neuroscience
- Cardiology
- Gerontology
Background:
- The heart-brain axis hypothesis posits bidirectional communication between the heart and brain.
- Cardiovascular diseases are linked to increased neurological disease risk.
- Quantitative effects of cardiovascular diseases on brain aging remain unclear.
Purpose of the Study:
- To explore how cardiovascular diseases affect biological brain and heart aging.
- To quantify the brain age gap (BAG) and heart age gap (HAG).
- To investigate the relationship between BAG and HAG in cardiovascular disease.
Main Methods:
- Utilized UK Biobank data including brain and cardiac MRI, and pulse wave analysis.
- Trained machine learning models (CNN for BAG, CatBoost for HAG) on healthy subjects.
- Calculated BAG and HAG for individuals with cardiovascular diseases, categorized by Phecodes and sex.
Main Results:
- Significant differences in BAG and HAG distributions were found in 24 of 36 cardiovascular disease groups compared to healthy subjects.
- No strong correlations were observed between BAG and HAG within disease groups.
- Sex-specific differences in BAG and HAG were noted for conditions like hypotension and cardiac conduction disorders.
Conclusions:
- Combined BAG and HAG offer insights into cardiovascular and neurological aging interplay.
- The lack of strong BAG-HAG correlation questions the heart-brain axis theory's generalizability for age gap biomarkers.
- Heterogeneous aging processes in the heart and brain warrant further investigation.
Introduction:
The heart-brain axis hypothesis suggests a bidirectional connection between the brain and the heart with relevant implications in health and disease. Cardiovascular diseases have been empirically linked to an increased risk of neurological diseases. However, it remains unclear to what extent different cardiovascular diseases affect brain health quantitatively across subjects and if that is associated with the extent the heart is affected by a disease. Therefore, this study aims to explore how cardiovascular diseases affect biological ageing of the brain and heart by quantifying the brain age gap (BAG) and the heart age gap (HAG) and relating the two to each other.
Methods:
This study used data from UK Biobank participants with available T1-weighted brain magnetic resonance imaging (MRI) scans, cardiac MRI-derived features, as well as pulse wave analysis cardiac measurements. This dataset included 7,500 healthy females and 6,684 healthy males. The data from healthy subjects was used to train biological brain age prediction machine learning models. For BAG computation, a convolutional neural network was trained based on the MRI data, while a CatBoost model was trained for HAG analyses based on the tabulated cardiac features. Individuals with cardiovascular diseases (F = 2,304, M = 2,925) in the UK Biobank were categorized using Phecodes and split based on sex and used to calculate the HAG and BAG for further analyses.
Results:
In 36 sex-specific cardiovascular disease groups, 24 showed significant differences from healthy subjects in the BAG and HAG distributions, whereas no strong correlations between the BAG and HAG distributions within disease groups were found. However, some diseases, such as hypotension and cardiac conduction disorders, showed sex-specific differences.
Discussion:
This study demonstrates that the combined use of HAG and BAG biomarkers provides a more comprehensive understanding of the interplay between cardiovascular and neurological ageing. The significant differences observed in disease groups, while lacking a strong correlation between the BAG and HAG, questions the generalizability of the heart-brain axis theory with respect to age gap biomarkers, suggesting potentially heterogeneous aging processes of the two systems that warrant further investigation in future work.
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