Missense variants causing Wiedemann-Steiner syndrome preferentially occur in the KMT2A-CXXC domain and are accurately classified using AlphaFold2.
Missense variants causing Wiedemann-Steiner syndrome preferentially occur in the KMT2A-CXXC domain and are accurately classified using AlphaFold2.
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DOI：
10.1371/journal.pgen.1010278
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发表时间：
2022-06
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影响因子：
4.5
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中科院分区：
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--
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Wiedemann-Steiner综合征(WDSTS)是一种由KMT2a基因从头变异引起的神经发育障碍，它编码一个多结构域的组蛋白甲基转移酶。为了深入了解WDSTS目前未知的发病机制，我们研究了可能导致WDSTS的变异在KMT2A15个不同区域的空间分布。与健康对照中的变体相比，WDSTS变体在CXXC结构域中的过度表达是61.9倍，CXXC结构域介导与未甲基化的CPGS的结合，这表明该结构域在调节表型方面发挥了重要作用。相反，我们在催化集结构域内没有发现明显的过度表示。证实了这些结果，我们发现Kmt2a缺陷小鼠的海马神经元优先在CpG富含区域显示组蛋白甲基化(H3K4me1和H3K4me3)被破坏，但这对基因表达没有系统影响。受这些结果的启发，我们将AlphaFold2对CXXC结构域结构的准确预测与先前的生物学知识相结合，开发了一种CXXC结构域中错义变体的分类方案。我们的分类器在坚持测试集上获得了92.6%的阳性预测值和92.9%的阴性预测值。这种分类性能使我们能够随后进行硅饱和突变，并根据它们的功能效应对总共445个变体进行分类。我们的结果为WDSTS的机制基础提供了一个新的见解，并提供了一个例子，说明AlphaFold2如何能够以非常高的精度对各种效应的计算机表征做出贡献，这表明一种可能适用于许多其他孟德尔疾病的范式。Wiedemann-Steiner综合征(WDSTS)是一种由组蛋白甲基转移酶KMT2a基因突变引起的儿童神经发育障碍。由于KMT2A有许多不同的结构域，执行不同的功能，我们推测，通过识别WDSTS导致的遗传变异最丰富的结构域，我们将对WDSTS的分子发病机制有更深入的了解。我们发现，到目前为止，与未甲基化的CPGS结合的CXXC结构域表现出最大的富集性，这表明KMT2A的CpG结合能力的丧失在WDSTS中起着核心作用。接下来，为了了解CXXC结构域遗传破坏的具体规则，我们将该结构域的功能/结构的先验知识与AlphaFold2的3D结构预测相结合，开发了一个针对CXXC错义变体的效果分类器。我们发现这个分类器表现出准确的性能，因此我们应用它来为可能出现的任何这样的变体提供分类，以帮助在临床上解释这些变体。我们的工作为WDSTS提供了新的见解，并建议了一种错误变异分类的策略，该策略可能适用于许多其他儿科遗传疾病。
Wiedemann-Steiner syndrome (WDSTS) is a neurodevelopmental disorder caused by de novo variants in KMT2A, which encodes a multi-domain histone methyltransferase. To gain insight into the currently unknown pathogenesis of WDSTS, we examined the spatial distribution of likely WDSTS-causing variants across the 15 different domains of KMT2A. Compared to variants in healthy controls, WDSTS variants exhibit a 61.9-fold overrepresentation within the CXXC domain–which mediates binding to unmethylated CpGs–suggesting a major role for this domain in mediating the phenotype. In contrast, we find no significant overrepresentation within the catalytic SET domain. Corroborating these results, we find that hippocampal neurons from Kmt2a-deficient mice demonstrate disrupted histone methylation (H3K4me1 and H3K4me3) preferentially at CpG-rich regions, but this has no systematic impact on gene expression. Motivated by these results, we combine accurate prediction of the CXXC domain structure by AlphaFold2 with prior biological knowledge to develop a classification scheme for missense variants in the CXXC domain. Our classifier achieved 92.6% positive and 92.9% negative predictive value on a hold-out test set. This classification performance enabled us to subsequently perform an in silico saturation mutagenesis and classify a total of 445 variants according to their functional effects. Our results yield a novel insight into the mechanistic basis of WDSTS and provide an example of how AlphaFold2 can contribute to the in silico characterization of variant effects with very high accuracy, suggesting a paradigm potentially applicable to many other Mendelian disorders. Wiedemann-Steiner syndrome (WDSTS) is a neurodevelopmental pediatric disorder caused by the genetic disruption of the histone methyltransferase KMT2A. Since KMT2A has many different domains that perform different functions, we reasoned that by identifying the domains most enriched for WDSTS-causing genetic variants we would gain insights into the incompletely understood molecular pathogenesis of WDSTS. We discovered that the CXXC domain—which binds unmethylated CpGs—shows by far the greatest enrichment, suggesting that loss of the CpG-binding ability of KMT2A plays a central role in WDSTS. Next, to understand specific rules underlying the genetic disruption of the CXXC domain, we combined prior knowledge about the function/structure of the domain with 3D structure prediction by AlphaFold2 to develop an effect classifier for CXXC missense variants. We found that this classifier exhibits accurate performance, and we therefore applied it to provide classifications for any such variant that can possibly arise, in order to aid in the interpretation of such variants in the clinic. Our work provides novel insights into WDSTS and suggests a strategy for missense variant classification that can potentially be applied to many other pediatric genetic disorders.
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