Systematic cell-based functional screening for LDL and triglyceride genes

描述（由申请方提供）：以血浆低密度脂蛋白胆固醇（LDL-C）和甘油三酯（TG）为标志的含载脂蛋白-B（apoB）的脂蛋白是心肌梗死（MI）的因果性、可遗传的风险因素，心肌梗死是全球主要死亡原因。需要新的策略来降低含载脂蛋白B的脂蛋白和MI风险，并且研究遗传的人类遗传变异可以导致降低MI风险的治疗靶点。通过基于人群的测序和基因分型研究，我们和其他人正在推导出数万名血浆LDL-C、TG和MI状态个体中存在的所有蛋白编码DNA变体的系统目录。然而，通过这些方法发现的大多数蛋白质编码变体是“中性的”，即，它们对由该基因编码的蛋白质的功能几乎没有或没有影响。因此，将蛋白质编码变体与LDL-C、TG或MI相关联的尝试面临巨大的信噪比问题，其中来自功能等位基因的信号被来自中性等位基因的噪声淹没。因此，人类遗传学研究面临的关键巴里是区分致病等位基因和非致病变异。为了克服这一挑战，我们提出了一种系统的基于细胞的功能基因组学方法：1）建立基于细胞的测定来测量apoB生物学; 2）测试特定基因和变体对细胞测定的影响; 3）在基于等位基因在这些细胞测定中的功能意义对其进行加权后，分析与脂质或MI风险的关联。我们 假设遗传学与细胞中系统获得的功能数据相结合，可以精确定位新的基因，这些基因不仅可以改变LDL- C或TG，还可以改变MI风险。为了验证这一假设，我们提出了以下目标：目标1 -稳健地建立系统性过表达、敲低和互补，用于平行测试细胞中apoB相关功能的多个基因和变体;目标2 -扩大我们的技术的应用，以测试120个基因，目的是鉴定额外的新LDL-C和TG基因;目的3 -利用我们的技术来破译哪些LDL-C和TG基因也赋予MI风险。该提案通过将新技术（基因和遗传变体的系统性基于细胞的功能表征）应用于显著未满足的健康需求（改善MI治疗）来解决现代遗传学的根本挑战（区分个体基因组中的功能相关变体和中性变体）。

DESCRIPTION (provided by applicant): Apolipoprotein-B (apoB) containing lipoproteins, as marked by plasma low-density lipoprotein cholesterol (LDL-C) and triglycerides (TG), are causal, heritable risk factors for myocardial infarction (MI), the leading cause of death worldwide. New strategies to lower apoB- containing lipoproteins and MI risk are needed and studying inherited human genetic variation can lead to therapeutic targets that reduce MI risk. Through population-based sequencing and genotyping studies we and others are deriving systematic catalogues of all protein-coding DNA variants present in tens of thousands of individuals characterized for plasma LDL-C, TG, and MI status. However, most protein-coding variants discovered through these approaches are "neutral", i.e., they have little or no effect on the function of the protein encoded by the gene. As such, attempts to associate protein-coding variants with LDL-C, TG, or MI face a tremendous signal to noise problem where the signal from functional alleles is overwhelmed by the noise from neutral alleles. Therefore, the critical barrie facing human genetic studies is distinguishing alleles causal for disease from nonpathogenic variants. To overcome this challenge, we propose a systematic cell-based functional genomics approach that: 1) establishes cell-based assays to measure apoB biology; 2) tests the effect of specific genes and variants on cellular assays; and 3) analyzes association with either lipids or MI risk after weighting alleles based on their functional significance in these cellular assays. We hypothesize that the combination of genetics with systematically- acquired functional data in cells can pinpoint new genes responsible for not only altered LDL- C or TG but also MI risk. To test this hypothesis, we propose the following aims: Aim 1 - To robustly establish systematic overexpression, knockdown and complementation for testing multiple genes and variants in parallel for apoB-relevant functions in cells; Aim 2 - To scale up the application of our technology to test 120 genes with the goal of identifying additional novel LDL-C and TG genes; and Aim 3 - To exploit our technology to decipher which LDL-C and TG genes also confer risk for MI. This proposal addresses a fundamental challenge to modern genetics (to distinguish functionally-relevant from neutral variants in an individual's genome) by applying novel technology (systematic cell-based functional characterization of genes and genetic variants) to a significant unmet health need (improved treatments for MI).