A population-based phenome-wide association study of cardiac and aortic structure and function

Area of Science:

• Cardiovascular imaging and genetics
• Biomarker discovery
• Population health studies

Background:

• Cardiac and aortic structure and function are linked to various diseases.
• Population-based imaging studies are crucial for understanding disease risk.
• The UK Biobank provides a rich dataset for large-scale health research.

Purpose of the Study:

• To comprehensively phenotype cardiac and aortic structure and function using cardiovascular magnetic resonance imaging.
• To explore variations in these phenotypes based on sex, age, and cardiovascular risk factors.
• To investigate associations between imaging phenotypes and non-imaging traits, including early-life factors, mental health, and cognitive function.

Main Methods:

• Analysis of cardiovascular magnetic resonance images from 26,893 UK Biobank participants.
• Application of an automated machine-learning-based analysis pipeline.
• Phenome-wide association study (PheWAS) and Mendelian randomization analyses.

Main Results:

• Detailed characterization of cardiac and aortic structural and functional phenotypes across a large population.
• Identification of variations in phenotypes by sex, age, and cardiovascular risk factors.
• Discovery of correlations between imaging phenotypes and a wide range of non-imaging health and cognitive traits.

Conclusions:

• Population-based cardiac and aortic imaging phenotypes offer valuable insights into cardiovascular disease risk.
• These phenotypes can elucidate heart-brain health interactions and disease mechanisms.
• The study highlights potential for developing novel image-based biomarkers for health and disease.