Background: Atrial cardiopathy often precedes atrial fibrillation (AF) and has emerged as an independent risk factor for cardiovascular outcomes. However, previous studies have been limited in size and have overlooked the right atrium.
Methods: In 51 693 UK Biobank participants without prevalent AF, we assessed biatrial volumes and emptying fraction from cardiac magnetic resonance imaging using deep learning segmentation. We evaluated associations with new-onset AF, ischemic stroke, heart failure, and dementia, conducted a genome-wide association study, and evaluated causal associations using Mendelian randomization.
Results: Among 51 693 adults, the mean (SD) age was 65 (7.7) years, and 24 584 (48%) were male. During the 4-year follow-up, 964 (1.9%) developed AF, 266 (0.5%) developed ischemic stroke, 365 (0.7%) developed heart failure, and 72 (0.1%) developed dementia. After adjustment for clinical risk factors, both left and right atrial measures were associated with new-onset AF (left atrial minimal volume; hazard ratio, 1.55 [95% CI, 1.48-1.62]), ischemic stroke, and heart failure, with stronger associations in women. Left atrial minimal volume was also associated with dementia. Our genome-wide association study identified 51 (27 novel) genetic associations with atrial measures, many of which do not overlap with established AF loci. Genetic correlations revealed that each atrium had varying correlations with cardiometabolic risk factors, and Mendelian randomization demonstrated that left atrial measures had direct causal effects on AF and stroke risk. However, the stroke associations were attenuated after accounting for AF variants.
Conclusions: In this largest assessment of biatrial structure and function to date, both left and right atrial cardiopathies were independently associated with increased risk of adverse cardiovascular events. We identified several novel genetic loci for atrial traits and observed unique genetic correlations between left and right atrial traits and cardiovascular phenotypes, providing insight into chamber-specific remodeling. Several of these measures are likely to be causal determinants of cardiovascular complications previously attributed to AF.
Keywords: atrial fibrillation; atrial function; cardiovascular diseases; deep learning; heart atria; heart failure.