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Published on: February 23, 2020
Cardiovascular measures from abdominal MRI provide insights into abdominal vessel genetic architecture
Nicolas Basty1, Elena P Sorokin2, Marjola Thanaj1
1Research Centre for Optimal Health, School of Life Sciences, University of Westminster, London, UK.
Insights
Deep learning on abdominal MRI scans identifies novel cardiovascular disease risk factors. This analysis of 44,541 participants reveals genetic links to vascular dimensions and potential screening opportunities for conditions like aortic aneurysms.
Area of Science:
- Cardiovascular Imaging and Genetics
- Deep Learning Applications in Medical Research
Background:
- Cardiovascular disease (CVD) is a leading cause of death, with population imaging studies crucial for understanding disease risk.
- Abdominal magnetic resonance imaging (MRI) offers a potential, non-specific imaging modality for cardiovascular assessment.
Purpose of the Study:
- To segment cardiovascular structures (heart, aorta, vena cava) from abdominal MRI using deep learning.
- To derive and analyze image-derived phenotypes (IDPs) for associations with disease outcomes, genetics, and environmental factors.
- To explore the utility of non-specific abdominal MRI in large cohort studies for cardiovascular risk assessment.
Main Methods:
- Deep learning models were employed to segment the heart, aorta, and vena cava from 44,541 UK Biobank participants' abdominal MRI scans.
- Six key image-derived phenotypes (IDPs) were generated: heart volume and cross-sectional areas (CSA) for the aorta and vena cava.
- Associations between IDPs and disease outcomes, genetic factors (genome-wide association study), and environmental factors were investigated.
Main Results:
- Generated IDPs showed concordance with cardiac MRI standards and replicated known sex and age-related changes.
- Significant associations were found between aortic CSA and abdominal aortic aneurysm, and heart volume and cardiovascular disorders.
- A genome-wide association study identified 72 associations at 59 loci (15 novel). Polygenic risk scores linked to thoracic aneurysm diagnosis.
- Substantial genetic correlation was observed with various cardiovascular traits, and heritability enrichment analysis implicated vascular tissue.
Conclusions:
- Non-specific abdominal MRI is valuable for assessing cardiovascular disease risk in large cohort studies.
- Novel genetic associations with vascular dimensions were identified, highlighting potential for new screening strategies.
- Deep learning segmentation of abdominal MRI provides a scalable method for cardiovascular phenotyping.
Background:
Cardiovascular disease remains a major source of morbidity and mortality, and population imaging studies have yielded insights into disease etiology and risk.
Methods:
In this study, we segment the heart, aorta, and vena cava from abdominal magnetic resonance imaging (MRI) scans using deep learning. We generate six image-derived phenotypes (IDP): heart volume, four aortic and one vena cava cross-sectional areas (CSA), from 44,541 UK Biobank participants, and explore their associations with disease outcomes, as well as genetic and environmental factors.
Results:
Here we show concordance between our IDPs and related IDPs from cardiac magnetic resonance imaging, the current gold standard, and replicate previous findings related to sex differences and age-related changes in heart and vessel dimensions. We identify a significant association between infrarenal descending aorta CSA and incident abdominal aortic aneurysm, and between heart volume and several cardiovascular disorders. In a genome-wide association study, we identify 72 associations at 59 loci (15 novel). We derive a polygenic risk score for each trait and demonstrated an association with thoracic aneurysm diagnosis, pointing to a potential screening opportunity. We demonstrate substantial genetic correlation with cardiovascular traits including aneurysms, varicose veins, dysrhythmia, and cardiac failure. Finally, heritability enrichment analysis implicates vascular tissue in the heritability of these traits.
Conclusions:
This study illustrates the value of non-specific abdominal MRI for exploring cardiovascular disease risk in cohort studies, and identifies novel genetic associations with vascular dimensions.
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