High-throughput discovery of disease-associated ion channel variants

高通量发现疾病相关离子通道变异

• 批准号: 10712437
• 负责人: Andrew M. Glazer
• 金额: $ 43.75万
• 依托单位: VANDERBILT UNIVERSITY MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-07-15 至 2028-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10712437
• 关键词: 3-Dimensional; Affect; American; Biology; Cell surface; Cells; Charge; Classification; Clinical; Data; Data Set; Disease; Effectiveness; Environment; Epilepsy; Genes; Genomic medicine; Health; High-Throughput Nucleotide Sequencing; Homeostasis; Homologous Gene; Human; In Vitro; Ion Channel; Ion Channel Gating; Ions; Learning; Libraries; Ligands; Link; Measures; Medical Genetics; Membrane Lipids; Mendelian disorder; Mutagenesis; Mutation; Mutation Analysis; Pathogenicity; Patients; Phenotype; Play; Proteins; Reaction; Role; Tissues; Variant; Work; biobank; body system; cohort; disease phenotype; experimental study; gamma-Aminobutyric Acid; genetic analysis; genetic testing; genetic variant; genome sequencing; medical schools; mutation screening; novel; patch clamp; phenotypic data; protein function; protein structure; receptor; trafficking; variant of unknown significance

PROJECT SUMMARY Ion channels pass charged ions through lipid membranes in a regulated manner. Ion channels play major roles in regulating electrically excitable tissues, sensing and responding to the environment, and maintaining cell homeostasis. Over 70 ion channels have been linked to Mendelian “channelopathy” disorders, affecting a diverse set of organ systems. As genetic testing and genomic medicine become prominent, an important challenge is to understand the spectrum of which mutations in ion channel genes cause disease. Unfortunately, a large fraction of variants are currently annotated as “Variants of Uncertain Significance,” which limits the effectiveness and potential of genomic medicine. This proposal seeks to decipher which variants in channelopathy genes cause disease. We will first use large biobank datasets with linked genome sequencing and phenotype data. We will examine associations between genetic variants in 76 channelopathy genes and relevant disease phenotypes. Using control pathogenic variants, we will first determine which gene-phenotype pairs are associated in biobank datasets, then discover novel candidate disease-associated variants that are present in carriers with relevant disease phenotypes. Next, we will use high-throughput automated patch clamping to study hundreds of variants in ion channel genes. Our initial focus will be 5 key ion channel genes that span a range of ion types and organ systems, as well as selected variants from the biobank genetic analyses. Next, we will perform deep mutational scans (a comprehensive mutational study) of every mutation in selected ion channel genes, starting with GABRA1, a ligand- gated ion channel gene (receptor) involved in GABA sensing and linked to seizure disorders. We will generate all possible mutations with degenerate mutagenesis reactions, integrate the mutation library into cells, then measure each mutation's impact on cell surface trafficking and channel function using high-throughput sequencing. Finally, we will integrate these patient and in vitro functional datasets to learn fundamental features of ion channel biology and disease. Through an analysis of the 2D and 3D protein structures, we will decipher protein mutational hotspots. From an analysis of mutational impacts from homologous genes I will determine whether mutation information can be ported to homologous genes. Finally, we will integrate variant data into the American College of Medical Genetics classification framework to clinically reclassify variants. Overall, these experiments have great potential to help resolve the VUS problem for ion channels and decipher novel ion channel biology.

项目摘要 离子通道以受调节的方式使带电离子通过脂质膜。离子通道 在调节电兴奋组织，感知和响应 环境和维持细胞稳态。超过70种离子通道与孟德尔式 “通道病”疾病，影响不同的器官系统。作为基因检测和基因组 医学变得突出，一个重要的挑战是要了解光谱， 离子通道基因的突变导致疾病。不幸的是，目前有很大一部分变体 注释为“意义不确定的变体”，这限制了 基因组医学 这项提议试图破译通道病基因中的哪些变体导致疾病。我们将 首先使用具有关联基因组测序和表型数据的大型生物库数据集。我们将研究 76个通道病基因的遗传变异与相关疾病表型之间的关联。 使用对照致病性变异，我们将首先确定哪些基因-表型对与 在生物库数据集中，然后发现新的候选疾病相关变异， 相关疾病表型的携带者。接下来，我们将使用高吞吐量的自动修补程序 研究离子通道基因的数百种变异。我们最初的重点将是5个关键离子 通道基因，跨越一系列离子类型和器官系统，以及选择的变体， 生物库的基因分析接下来，我们将执行深度突变扫描（全面的 突变研究）的每一个突变，在选定的离子通道基因，开始与GABRA 1，配体- 门控离子通道基因（受体），参与GABA感应并与癫痫发作有关。我们将 用简并诱变反应产生所有可能的突变， 然后测量每个突变对细胞表面运输和通道功能的影响， 高通量测序。最后，我们将整合这些患者和体外功能数据集， 学习离子通道生物学和疾病的基本特征。通过对2D和3D的分析 蛋白质结构，我们将破译蛋白质突变热点。从突变的分析 同源基因的影响，我将确定突变信息是否可以移植到 同源基因最后，我们将把变异数据整合到美国医学院 遗传学分类框架，用于临床重新分类变异。总的来说，这些实验 很有可能帮助解决离子通道的VUS问题并破译新的离子通道 生物学