Genotype-Phenotype Taxonomy of Hypertrophic Cardiomyopathy.
Genotype-Phenotype Taxonomy of Hypertrophic Cardiomyopathy.
复制标题
DOI：
10.1161/circgen.123.004200
复制
发表时间：
2023-12
影响因子：
7.4
通讯作者：
O'Regan, Declan P.
中科院分区：
文献类型：
--
作者：
Curran, Lara;de Marvao, Antonio;Inglese, Paolo;McGurk, Kathryn A.;Schiratti, Pierre-Raphael;Clement, Adam;Zheng, Sean L.;Li, Surui;Pua, Chee Jian;Shah, Mit;Jafari, Mina;Theotokis, Pantazis;Buchan, Rachel J.;Jurgens, Sean J.;Raphael, Claire E.;Baksi, Arun John;Pantazis, Antonis;Halliday, Brian P.;Pennell, Dudley J.;Bai, Wenjia;Chin, Calvin W. L.;Tadros, Rafik;Bezzina, Connie R.;Watkins, Hugh;Cook, Stuart A.;Prasad, Sanjay K.;Ware, James S.;O'Regan, Declan P.
肥厚型心肌病（HCM）是与异质表型相关的心源性猝死的重要原因，但尚无系统的框架来对形态进行分类或评估相关风险。在这里，我们定量调查 HCM 中的基因型-表型关联，以得出数据驱动的疾病表达分类法。我们招募了 436 名 HCM 患者（中位年龄 60 岁；28.8% 为女性），并提供临床、遗传和影像数据。还招募了来自新加坡的 60 名 HCM 患者（中位年龄 59 岁；11% 女性）和来自英国生物银行的参考人群（n=16 691；平均年龄 55 岁；52.5% 女性）组成的独立队列。我们使用机器学习通过心脏磁共振成像分析左心室的 3 维结构，并构建基于树的 HCM 表型分类。基因型和死亡风险分布被预测在树上。与基因型阴性个体相比，HCM 致病性或可能致病性变异的携带者左心室质量较低，但基底间隔肥厚程度较高，寿命较短（平均随访时间为 9.9 年）（风险比，2.66 [95% CI，1.42-4.96]；P<0.002）。使用 3 维形状的无监督学习确定了四个主要表型分支：（1）非肌瘤肥大伴高血压； (2) 与流出道梗阻相关的弥漫性和基底不对称肥大； (3)孤立性基底肥大； (4) 家族性肌节 HCM 富集的轻度非梗阻性肥大（致病性或可能致病性变异的比值比，2.18 [95% CI，1.93–2.28]；P=0.0001）。 HCM 的多基因风险也与不同的疾病表达模式和程度相关。该模型可推广到独立队列（可信度，M1：0.86-0.88）。我们报告了一种数据驱动的 HCM 分类法，用于识别具有相似形态的患者群体，同时保持疾病严重程度、遗传风险和结果的连续性。这种方法对于理解疾病多样性的原因和后果具有重要价值。
Hypertrophic cardiomyopathy (HCM) is an important cause of sudden cardiac death associated with heterogeneous phenotypes, but there is no systematic framework for classifying morphology or assessing associated risks. Here, we quantitatively survey genotype-phenotype associations in HCM to derive a data-driven taxonomy of disease expression. We enrolled 436 patients with HCM (median age, 60 years; 28.8% women) with clinical, genetic, and imaging data. An independent cohort of 60 patients with HCM from Singapore (median age, 59 years; 11% women) and a reference population from the UK Biobank (n=16 691; mean age, 55 years; 52.5% women) were also recruited. We used machine learning to analyze the 3-dimensional structure of the left ventricle from cardiac magnetic resonance imaging and build a tree-based classification of HCM phenotypes. Genotype and mortality risk distributions were projected on the tree. Carriers of pathogenic or likely pathogenic variants for HCM had lower left ventricular mass, but greater basal septal hypertrophy, with reduced life span (mean follow-up, 9.9 years) compared with genotype negative individuals (hazard ratio, 2.66 [95% CI, 1.42–4.96]; P<0.002). Four main phenotypic branches were identified using unsupervised learning of 3-dimensional shape: (1) nonsarcomeric hypertrophy with coexisting hypertension; (2) diffuse and basal asymmetrical hypertrophy associated with outflow tract obstruction; (3) isolated basal hypertrophy; and (4) milder nonobstructive hypertrophy enriched for familial sarcomeric HCM (odds ratio for pathogenic or likely pathogenic variants, 2.18 [95% CI, 1.93–2.28]; P=0.0001). Polygenic risk for HCM was also associated with different patterns and degrees of disease expression. The model was generalizable to an independent cohort (trustworthiness, M1: 0.86–0.88). We report a data-driven taxonomy of HCM for identifying groups of patients with similar morphology while preserving a continuum of disease severity, genetic risk, and outcomes. This approach will be of value in understanding the causes and consequences of disease diversity.