Genetic versus environmental determinants of cardiac structure and function: twin-based CMR evidence for modifiable myocardial remodelling
J Attaluri, L S Canas, M Modat, J O Cleary, R E Thornley, P Bridgen, L Billimoria, V Bowyer, S L Giles, A N Price, J V Hajnal, S Ourselin, A Chiribiri, C J Steves, P G MasciAbstract
Background
Understanding the genetic versus environmental determinants of cardiovascular structure and function is fundamental to unraveling the mechanisms underlying cardiovascular disease, identifying modifiable and potentially druggable pathways, and improving interpretation of imaging-derived phenotypes (IDPs) for clinical decision-making and prevention. Cardiovascular magnetic resonance (CMR) provides highly accurate and reproducible quantitative IDPs of cardiac geometry and performance; however, the relative contributions of inherited and environmental influences to these traits remain incompletely defined. Twin designs offer a powerful quasi-experimental framework to disentangle genetic effects from environmental contributions, enabling deeper mechanistic insight into cardiovascular remodelling.
Purpose
We leveraged the TwinsUK cohort combined with convolutional neural network (CNN)–based segmentation of 0.55T CMR imaging to quantify the relative contributions of genetic and environmental factors to cardiac geometry, and function.
Methods
We analyzed 734 twins (age: 67±9 years; 84% female; 69% monozygotic) from the TwinsUK MR imaging sub-study who underwent 0.55T CMR. Automated, quality-controlled 2D nnU-Net CNN models were used to segment left and right cardiac chambers and the thoracic aorta to derive CMR-based IDPs (Figure-1). Heritability was estimated using structural equation ACE models, partitioning phenotypic variance into additive genetic (A), shared environmental (C), and unique environmental (E) components. Within monozygotic twin pairs, mixed-effects discordant twin models decomposed exposure–phenotype associations into within-pair effects (βW; reflecting non-shared environmental influence) and between-family effects (βB; reflecting genetic and shared environmental contributions).
Results
Ascending aortic dimension exhibited the highest heritability (h²=0.64), while ventricular volumes and LV mass showed moderate-to-high genetic contribution (h²=0.55–0.57). Left ventricular performance indices were predominantly determined by unique environmental factors (LV-EF e²=0.53; LV diastolic function [peak-filling-rate] e²=0.51), (Figure-2). Within monozygotic pairs, higher BMI increased LV mass (βW=0.38, P<10⁻¹4) and mass-to-volume ratio (βW=0.006, P<10⁻⁵); hypertension showed parallel structural associations (LV mass t=4.24, P<0.001) with minimal effects on LV performance.
Conclusions
Cardiac geometry is largely genetically determined, whereas LV function is predominantly environmentally influenced. Adiposity and hypertension drive genome-independent LV remodelling, underscoring the central role of early preventive strategies in cardiovascular disease. Of importance, ascending aorta size variability is largely explained by genetic factors, challenging the assumption that aortic dilatation primarily reflects long-standing environmental risk exposure, such as uncontrolled hypertension or obesity.nnU-Net SegmentationsACE Variance Decomposition of CMR Phenotypes