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.

项目概要 离子通道以受调节的方式使带电离子穿过脂质膜。 在调节电兴奋组织、感知和响应方面发挥着重要作用 超过 70 个离子通道与孟德尔相关。 “通道病”疾病，影响多种器官系统，如基因检测和基因组。 医学变得越来越突出，一个重要的挑战是了解其范围 不幸的是，目前大部分变异都是离子通道基因突变引起的。 注释为“不确定意义的变体”，这限制了 基因组医学。 该提案旨在破译通道病基因的哪些变异会导致疾病。 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。 76 个通道病基因的遗传变异与相关疾病表型之间的关联。 使用对照致病变异，我们将首先确定哪些基因-表型对相关 在生物库数据集中，然后发现新的候选疾病相关变异 接下来，我们将使用高通量自动化补丁。 我们最初的重点是 5 个关键离子。 跨越一系列离子类型和器官系统的通道基因，以及从中选择的变体 接下来，我们将进行深度突变扫描（全面的突变扫描）。 突变研究）对所选离子通道基因中的每个突变进行研究，从 GABRA1（一种配体）开始 门控离子通道基因（受体）参与 GABA 传感并与癫痫症相关。 通过简并诱变反应生成所有可能的突变，整合突变库 进入细胞，然后使用以下方法测量每个突变对细胞表面运输和通道功能的影响 最后，我们将整合这些患者和体外功能数据集。 通过 2D 和 3D 分析了解离子通道生物学和疾病的基本特征。 蛋白质结构，我们将从突变分析中破译蛋白质突变热点。 同源基因的影响我将确定是否可以将突变信息移植到 最后，我们将把变异数据整合到美国医学院。 临床上对变异进行重新分类的遗传学分类框架总体而言，这些实验已经完成。 帮助解决离子通道的 VUS 问题和破译新型离子通道的巨大潜力 生物学。