Cardiovascular Disease Pathogenicity Predictor (CVD-PP): A Tissue-Specific In Silico Tool for Discriminating Pathogenicity of Variants of Unknown Significance in Cardiovascular Disease Genes.

IF 6 2区 医学 Q1 CARDIAC & CARDIOVASCULAR SYSTEMS Circulation: Genomic and Precision Medicine Pub Date : 2024-10-29 DOI:10.1161/CIRCGEN.123.004464
Megan E Ramaker, Jawan W Abdulrahim, Kristin M Corey, Ryne C Ramaker, Lydia Coulter Kwee, William E Kraus, Svati H Shah
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引用次数: 0

Abstract

Background: Interpretation of variants of uncertain significance (VUSs) remains a challenge in the care of patients with inherited cardiovascular diseases (CVDs); 56% of variants within CVD risk genes are VUS, and machine learning algorithms trained upon large data resources can stratify VUS into higher versus lower probability of contributing to a CVD phenotype.

Methods: We used ClinVar pathogenic/likely pathogenic and benign/likely benign variants from 47 CVD genes to build a predictive model of variant pathogenicity utilizing measures of evolutionary constraint, deleteriousness, splicogenicity, local pathogenicity, cardiac-specific expression, and population allele frequency. Performance was validated using variants for which the ClinVar pathogenicity assignment changed. Functional validation was assessed using prior studies in >900 identified VUS. The model utility was demonstrated using the Catheterization Genetics cohort.

Results: We identified a top-ranked model that accurately prioritized variants for which ClinVar clinical significance had changed (n=663; precision-recall area under the curve, 0.97) and performed well compared with conventional in silico methods. This model (CVD pathogenicity predictor) also had high accuracy in prioritizing VUS with functional effects in vivo (precision-recall area under the curve, 0.58). In Catheterization Genetics, there was a greater burden of higher CVD pathogenicity predictor scored VUS in individuals with dilated cardiomyopathy compared with controls (P=8.2×10-15). Of individuals in Catheterization Genetics who harbored highly ranked CVD pathogenicity predictor VUS meeting clinical pathogenicity criteria, 27.6% had clinical evidence of disease. Variant prioritization using this model increased genetic diagnosis in Catheterization Genetics participants with a known clinical diagnosis of hypertrophic cardiomyopathy (7.8%-27.2%).

Conclusions: We present a cardiac-specific model for prioritizing variants underlying CVD syndromes with high performance in discriminating the pathogenicity of VUS in CVD genes. Variant review and phenotyping of individuals carrying VUS of pathogenic interest support the clinical utility of this model. This model could also have utility in filtering variants as part of large-scale genomic sequencing studies.

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心血管疾病致病性预测因子(CVD-PP):一种组织特异性硅学工具,用于判别心血管疾病基因中意义不明变异的致病性。
背景:在治疗遗传性心血管疾病(CVDs)患者的过程中,对意义不确定的变异体(VUSs)的解释仍然是一项挑战;CVD风险基因中56%的变异体是VUS,而根据大量数据资源训练的机器学习算法可以将VUS分层,将其分为导致CVD表型的概率较高和较低的变异体:我们利用来自 47 个心血管疾病基因的 ClinVar 致病/可能致病变异和良性/可能良性变异建立了一个变异致病性预测模型,该模型利用了进化约束、缺失性、剪接致病性、局部致病性、心脏特异性表达和群体等位基因频率等指标。使用 ClinVar 致病性分配发生变化的变异体对其性能进行了验证。对超过 900 个已识别 VUS 的先前研究进行了功能验证评估。结果:结果:我们发现了一个排名靠前的模型,它能准确地优先处理 ClinVar 临床意义已发生变化的变异(n=663;精确度-召回曲线下面积,0.97),与传统的硅学方法相比表现良好。该模型(心血管疾病致病性预测因子)在优先选择具有体内功能效应的 VUS 方面也具有很高的准确性(曲线下的精确度-召回面积,0.58)。在心导管遗传学中,与对照组相比,扩张型心肌病患者中CVD致病性预测因子得分较高的VUS负担更大(P=8.2×10-15)。在导管遗传学中携带符合临床致病性标准的心血管疾病致病性预测因子高分VUS的个体中,27.6%有临床疾病证据。使用该模型进行的变异优先排序增加了导管遗传学参与者中已知肥厚型心肌病临床诊断的基因诊断率(7.8%-27.2%):我们提出了一种心脏特异性模型,用于优先排查心血管疾病综合征的基础变异,该模型在判别心血管疾病基因中 VUS 的致病性方面表现出色。对携带致病性 VUS 的个体进行的变异审查和表型分析支持了该模型的临床实用性。该模型还可用于筛选变异,作为大规模基因组测序研究的一部分。
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来源期刊
Circulation: Genomic and Precision Medicine
Circulation: Genomic and Precision Medicine Biochemistry, Genetics and Molecular Biology-Genetics
CiteScore
9.20
自引率
5.40%
发文量
144
期刊介绍: Circulation: Genomic and Precision Medicine is a distinguished journal dedicated to advancing the frontiers of cardiovascular genomics and precision medicine. It publishes a diverse array of original research articles that delve into the genetic and molecular underpinnings of cardiovascular diseases. The journal's scope is broad, encompassing studies from human subjects to laboratory models, and from in vitro experiments to computational simulations. Circulation: Genomic and Precision Medicine is committed to publishing studies that have direct relevance to human cardiovascular biology and disease, with the ultimate goal of improving patient care and outcomes. The journal serves as a platform for researchers to share their groundbreaking work, fostering collaboration and innovation in the field of cardiovascular genomics and precision medicine.
期刊最新文献
Cardiovascular Disease Pathogenicity Predictor (CVD-PP): A Tissue-Specific In Silico Tool for Discriminating Pathogenicity of Variants of Unknown Significance in Cardiovascular Disease Genes. Yield of Genetic Testing for Long-QT Syndrome in Elderly Patients With Torsades de Pointes. How Normal Is Low-Normal Left Ventricular Ejection Fraction in Familial Dilated Cardiomyopathy? Polygenic Risk and Coronary Artery Disease Severity. Clinical Utility of Protein Language Models in Resolution of Variants of Uncertain Significance in KCNQ1, KCNH2, and SCN5A Compared With Patch-Clamp Functional Characterization.
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