Functional Genomics of Cardiac Sodium Channel Variants

随着临床基因检测被广泛用于疑似孟德尔疾病的患者， 在广泛的人群中，一个主要的新挑战是准确预测DNA的致病性 变体。多种特征，包括人群中的等位基因频率、家族史和功能 研究，目前正被用来分配已知的或新的变种，以三大类：良性， 致病性，或（最常见的）不确定意义的变体（VUS）。我们建议在这里测试 假设部署新的表型分析方法将改善变异分类，我们将重点放在这里 在SCN 5A上，编码心脏钠通道。尽管这一渠道发挥着关键作用， 正常的心脏功能，SCN 5A变异是令人惊讶的常见，并已与严重的， 偶尔危及生命的表型，包括1型Brugada综合征（BrS 1）、3型长QT 综合征（LQT 3）、传导系统疾病、心力衰竭和房颤。在目标1中，我们将确定 表型在电子健康记录（EHR）中的效用，结合功能研究，以评估 SCN 5A VUS致病性。电子医疗记录和基因组学（eMERGE）网络， 参与者正在完成25000个孟德尔疾病基因的测序，包括SCN 5A， 受试者EHR。我们将通过分析SCN 5A相关的EHR表型来评估VUS的致病性。 具有和不具有SCN 5A罕见变体的受试者，并建立新检测到的变体的体外功能 使用多路复用半自动电生理学方法。在目标2中，我们将利用 深度突变扫描（DMS）-一种高通量方法，用于诱变靶标中的每个核苷酸 基因组序列，并建立其功能的后果-以确定SCN 5A编码变异与 BrS 1或LQT 3特征。在一个试点实验中，我们开发了一种药物挑战， 在其表面不表达钠电流的细胞（BrS表型）， 增强的持续钠电流（LQT 3）。然后我们生成了所有252个可能的非同义词或 在SCN 5A的12个氨基酸序列上的无义单氨基酸（aa）变体，暴露转染的细胞池， 用一个突变体/细胞进行药物挑战，在药物挑战前和后使用下一代测序， 鉴定具有BrS 1和LQT 3特征的变体，并用常规膜片钳验证预测 方法.我们现在将扩大到扫描更大的区域，从编码跨膜的253个氨基酸开始， 结构域IV，已知含有数十种致病变体。此外，我们将DMS结果映射到 探索功能变体失得的结构基础的渠道。我们将把DMS数据 我们希望将其应用到现有的和新的统计模型中，以建立SCN 5A变异疾病风险的改进模型。结果 这项工作的新方法将建立SCN 5A中罕见变异的功能后果（以及 最终是其他基因），从而使基因组医学成为可能。

As clinical genetic testing is becoming widely deployed for patients with suspected Mendelian diseases as well as in the broad population, a major emerging challenge is the accurate prediction of pathogenicity of DNA variants. Multiple features, including allele frequencies across populations, family history, and functional studies, are currently being used to assign known or new variants to three broad categories: benign, pathogenic, or (most commonly) variant of uncertain significance (VUS). We propose here to test the hypothesis that deploying novel phenotyping methods will improve variant classification, and we will focus here on SCN5A, encoding the cardiac sodium channel. Despite the fact that this channel plays a critical role in normal heart function, SCN5A variants are surprisingly common and have been associated with serious and occasionally life-threatening phenotypes including type 1 Brugada Syndrome (BrS1), type 3 Long QT Syndrome (LQT3), conduction system disease, heart failure, and atrial fibrillation. In aim 1, we will determine the utility of phenotyping in the electronic health record (EHR) coupled to functional studies to assess SCN5A VUS pathogenicity. The Electronic Medical Records and Genomics (eMERGE) network in which we are participants is completing sequencing of 109 Mendelian disease genes, including SCN5A, in 25,000 subjects with EHRs. We will assess VUS pathogenicity by analyzing SCN5A-related EHR phenotypes in subjects with and without SCN5A rare variants and establishing in vitro function for newly-detected variants using multiplexed semi-automated electrophysiologic methods. In aim 2, we will build on preliminary data using deep mutational scanning (DMS) – a high-throughput method to mutagenize each nucleotide in a target genomic sequence and establish its functional consequences – to identify SCN5A coding variants with BrS1 or LQT3 features. In a pilot experiment, we developed a drug challenge that biases survival toward cells that do not express sodium current at their surface (the BrS phenotype) and against cells that display enhanced sustained sodium current (LQT3). We then generated all 252 possible non-synonymous or nonsense single amino acid (aa) variants across a 12aa regon of SCN5A, exposed a pool of cells transfected with one mutant/cell to the drug challenge, used next-generation sequencing pre- and post-drug challenge to identify variants with BrS1 and LQT3 features, and validated predictions with conventional patch clamp methods. We will now scale up to scan larger regions, starting with the 253 aa encoding transmembrane domain IV, known to harbor dozens of pathogenic variants. Further, we will map DMS results onto a model of the channel to probe the structural basis of loss and gain of function variants. We will incorporate DMS data into available and new statistical models to build an improved model of SCN5A variant disease risk. The result of this work will be new approaches to establish functional consequences of rare variants in SCN5A (and ultimately other genes), and thus enable genomic medicine.