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.

心肌间质纤维化与心血管疾病和不良预后有关。在这里，为了研究人类心脏纤维化的生物学途径，我们开发了一个机器学习模型来测量 41,505 名接受心脏磁共振成像的英国生物库参与者的天然心肌 T1 时间，这是心肌纤维化的标志。较长的 T1 时间与糖尿病、肾脏疾病、主动脉瓣狭窄、心肌病、心力衰竭、房颤、传导疾病和类风湿性关节炎有关。全基因组关联分析确定了 11 个与 T1 时间相关的独立位点。鉴定的基因座涉及葡萄糖转运 ( SLC2A12 )、铁稳态 ( HFE、TMPRSS6 ))、组织修复 ( ADAMTSL1、VEGFC )、氧化应激 ( SOD2 )、心脏肥大 ( MYH7B ) 和钙信号 ( CAMK2D )。使用转化生长因子 β1 介导的心脏成纤维细胞活化测定，我们发现 11 个位点中的 9 个由表现出表达时间变化或开放染色质构象的基因组成，支持它们与肌成纤维细胞状态获取的生物学相关性。通过利用机器学习使用心脏成像对心肌间质纤维化进行大规模量化，我们验证了心脏纤维化与疾病之间的关联，并确定了纤维化的新生物学相关途径。