结构和变异效应预测因子在RyR1临床解释中的互补作用

IF 3.7 2区 医学 Q2 GENETICS & HEREDITY
Rolando Hernández Trapero, Mihaly Badonyi, Lukas Gerasimavicius, Joseph A. Marsh
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引用次数: 0

摘要

RYR1相关疾病,由编码骨骼肌红嘌呤受体的RYR1基因变异引起,包括广泛的显性和隐性表型。RyR1的广泛长度和疾病变异的多种机制为临床解释带来了重大挑战,当前变异效应预测因子(vep)的有限性能和偏差加剧了这一挑战。本研究评估了70种VEPs区分致病性RyR1错义变异和来自人群数据库的推定良性变异的功效。现有的副总裁表现各异。那些在已知临床标签上训练的人表现出更好的分类性能,但这可能被数据循环夸大了。相比之下,使用避免或最小化训练偏差的方法的副总裁表现有限,可能反映了识别功能增益变量的困难。利用蛋白质结构信息,我们引入了疾病变异的空间接近度(SPDV),这是一种仅基于致病突变的三维聚类的新度量。我们为我们的方法和表现最好的vep确定了ACMG/AMP PP3/BP4分类阈值,使我们能够将PP3/BP4证据水平分配给所有不确定意义的RyR1错义变体。因此,我们认为我们基于蛋白质结构的方法代表了一种正交策略,超过了现有的计算工具,可以帮助诊断ryr1相关疾病。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Complementary Roles of Structure and Variant Effect Predictors in RyR1 Clinical Interpretation

Complementary Roles of Structure and Variant Effect Predictors in RyR1 Clinical Interpretation

RyR1-related disorders, arising from variants in the RYR1 gene encoding the skeletal muscle ryanodine receptor, encompass a wide range of dominant and recessive phenotypes. The extensive length of RyR1 and diverse mechanisms underlying disease variants pose significant challenges for clinical interpretation, exacerbated by the limited performance and biases of current variant effect predictors (VEPs). This study evaluates the efficacy of 70 VEPs for distinguishing pathogenic RyR1 missense variants from putatively benign variants derived from population databases. Existing VEPs show variable performance. Those trained on known clinical labels show greater classification performance, but this is likely inflated by data circularity. In contrast, VEPs using methodologies that avoid or minimise training bias show limited performance, likely reflecting difficulty in identifying gain-of-function variants. Leveraging protein structural information, we introduce Spatial Proximity to Disease Variants (SPDV), a novel metric based solely on three-dimensional clustering of pathogenic mutations. We determine ACMG/AMP PP3/BP4 classification thresholds for our method and top-performing VEPs, allowing us to assign PP3/BP4 evidence levels to all RyR1 missense variants of uncertain significance. Thus, we suggest that our protein structure–based approach represents an orthogonal strategy over existing computational tools for aiding in the diagnosis of RyR1-related diseases.

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来源期刊
Human Mutation
Human Mutation 医学-遗传学
CiteScore
8.40
自引率
5.10%
发文量
190
审稿时长
2 months
期刊介绍: Human Mutation is a peer-reviewed journal that offers publication of original Research Articles, Methods, Mutation Updates, Reviews, Database Articles, Rapid Communications, and Letters on broad aspects of mutation research in humans. Reports of novel DNA variations and their phenotypic consequences, reports of SNPs demonstrated as valuable for genomic analysis, descriptions of new molecular detection methods, and novel approaches to clinical diagnosis are welcomed. Novel reports of gene organization at the genomic level, reported in the context of mutation investigation, may be considered. The journal provides a unique forum for the exchange of ideas, methods, and applications of interest to molecular, human, and medical geneticists in academic, industrial, and clinical research settings worldwide.
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