Phenome-wide association study of cardiac and aortic structure and function

Differences in cardiac and aortic structure and function are associated with cardiovascular diseases and a wide range of other types of disease. Here we analyzed cardiovascular magnetic resonance images (MRI) from a population-based study, the UK Biobank, using an automated machine-learning-based analysis pipeline. Quantitative phenotypes derived from cardiovascular MRI enable us to assess cardiac and aortic structure and function in a non-invasive way, and provide important biomarkers for the determination of pathological states in cardiovascular diseases.

The downstream phenome-wide association study (PheWAS) tested for correlations of a wide range of non-imaging phenotypes of the participants with imaging phenotypes. Researchers may explore the associations between imaging phenotypes and non-imaging phenotypes using the data visualization website. Associations were identified for cardiac and aortic phenotypes with a wide range of non-imaging phenotypes, including birth weight, mental health and cognitive-performance measures. Mendelian randomization analysis provided further evidence for the potential causal relationship between birth weight and cardiac and aortic structures even in mid-later ages.

This study illustrates how population-based cardiac and aortic imaging phenotypes can be used to better define cardiovascular disease risks as well as heart-brain health interactions, highlighting new opportunities for studying disease mechanisms and developing image-based biomarkers.

For more details, see Bai W, Suzuki H, Huang J, et al. A population-based phenome-wide association study of cardiac and aortic structure and function. Nature Medicine. 2020.