Genetics of myocardial interstitial fibrosis in the human heart and association with disease

• Published in: Nature genetics Vol. 55; no. 5; pp. 777 - 786
• Main Authors: Nauffal, Victor, Di Achille, Paolo, Klarqvist, Marcus D. R., Cunningham, Jonathan W., Hill, Matthew C., Pirruccello, James P., Weng, Lu-Chen, Morrill, Valerie N., Choi, Seung Hoan, Khurshid, Shaan, Friedman, Samuel F., Nekoui, Mahan, Roselli, Carolina, Ng, Kenney, Philippakis, Anthony A., Batra, Puneet, Ellinor, Patrick T., Lubitz, Steven A.
• Format: Journal Article
• Language: English
• Published: New York Nature Publishing Group US 01.05.2023; Nature Publishing Group
• Subjects: 38; 38/91; 45; 45/43; 631/208/205/2138; 631/208/457; 692/699/75/230; 692/699/75/29/1309; 692/699/75/74; Agriculture; Animal Genetics and Genomics; Aorta; Aortic stenosis; Association analysis; Biobanks; Biomarkers; Biomedical and Life Sciences; Biomedicine; Body mass index; Calcium signalling; Cancer Research; Cardiac arrhythmia; Cardiomyopathies - genetics; Cardiomyopathies - pathology; Cardiomyopathy; Cardiovascular disease; Cardiovascular diseases; Chromatin; Clinical outcomes; Conformation; Congestive heart failure; Coronary artery disease; Diabetes; Diabetes mellitus; Ejection fraction; Electrocardiography; Failure analysis; Fibrosis; Gene Function; Genes; Genetics; Genome-Wide Association Study; Genomes; Glucose transport; Growth factors; Heart; Heart diseases; Heart failure; Homeostasis; Human Genetics; Humans; Hypertension; Hypertrophy; Inflammatory diseases; Learning algorithms; Machine learning; Magnetic resonance imaging; Medical imaging; Metabolic disorders; Myocardium - pathology; Oxidative stress; Rheumatoid arthritis; United Kingdom > UK
• ISSN: 1061-4036; 1546-1718; 1546-1718
• DOI: 10.1038/s41588-023-01371-5

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. Genome-wide association analyses identify 11 loci associated with native myocardial T1 time, a marker of interstitial fibrosis, providing insights into the pathways involved in myocardial fibrosis and myofibroblast cell state acquisition.