Genetics of myocardial interstitial fibrosis in the human heart and association with disease.
Victor NauffalPaolo Di AchilleMarcus D R KlarqvistJonathan W CunninghamMatthew C HillJames Paul PirruccelloLu-Chen WangValerie N MorrillSeung Hoan ChoiShaan KhurshidSamuel Freesun FriedmanMahan NekouiCarolina RoselliKenney NgAnthony A PhilippakisPuneet BatraPatrick T EllinorSteven A LubitzPublished in: Nature genetics (2023)
Myocardial interstitial fibrosis is associated with cardiovascular disease and adverse prognosis. Here, to investigate the biological pathways that underlie fibrosis in the human heart, we developed a machine learning model to measure native myocardial T1 time, a marker of myocardial fibrosis, in 41,505 UK Biobank participants who underwent cardiac magnetic resonance imaging. Greater T1 time was associated with diabetes mellitus, renal disease, aortic stenosis, cardiomyopathy, heart failure, atrial fibrillation, conduction disease and rheumatoid arthritis. Genome-wide association analysis identified 11 independent loci associated with T1 time. The identified loci implicated genes involved in glucose transport (SLC2A12), iron homeostasis (HFE, TMPRSS6), tissue repair (ADAMTSL1, VEGFC), oxidative stress (SOD2), cardiac hypertrophy (MYH7B) and calcium signaling (CAMK2D). Using a transforming growth factor β1-mediated cardiac fibroblast activation assay, we found that 9 of the 11 loci consisted of genes that exhibited temporal changes in expression or open chromatin conformation supporting their biological relevance to myofibroblast cell state acquisition. By harnessing machine learning to perform large-scale quantification of myocardial interstitial fibrosis using cardiac imaging, we validate associations between cardiac fibrosis and disease, and identify new biologically relevant pathways underlying fibrosis.
Keyphrases
- left ventricular
- heart failure
- aortic stenosis
- machine learning
- transforming growth factor
- atrial fibrillation
- genome wide
- genome wide association
- hypertrophic cardiomyopathy
- cardiovascular disease
- magnetic resonance imaging
- endothelial cells
- oxidative stress
- rheumatoid arthritis
- left atrial
- dna damage
- liver fibrosis
- cardiac resynchronization therapy
- mitral valve
- high resolution
- epithelial mesenchymal transition
- transcatheter aortic valve replacement
- dna methylation
- computed tomography
- high throughput
- aortic valve replacement
- gene expression
- artificial intelligence
- stem cells
- ejection fraction
- magnetic resonance
- type diabetes
- deep learning
- cardiovascular events
- poor prognosis
- idiopathic pulmonary fibrosis
- adipose tissue
- oral anticoagulants
- endoplasmic reticulum stress
- weight loss
- left atrial appendage
- direct oral anticoagulants
- insulin resistance