Systematic cell-based functional screening for LDL and triglyceride genes

描述(由申请人提供)：载脂蛋白B(ApoB)含有脂蛋白，以血浆低密度脂蛋白胆固醇(LDL-C)和甘油三酯(TG)为标志，是导致心肌梗死(MI)的因果、可遗传的危险因素，心肌梗死是全球主要的死亡原因。需要新的策略来降低含载脂蛋白的脂蛋白和心肌梗死风险，研究人类遗传变异可以导致降低心肌梗死风险的治疗目标。通过基于人群的测序和基因分型研究，我们和其他人正在得出存在于数万个具有血浆低密度脂蛋白-C、甘油三酯和心肌梗死状态的个体中存在的所有蛋白质编码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都是“中性的”，即它们对基因编码的蛋白质的功能几乎没有影响。因此，试图将蛋白质编码变体与低密度脂蛋白、甘油三酯或心肌梗死联系起来，面临着巨大的信噪比问题，来自功能等位基因的信号被来自中性等位基因的噪声所淹没。因此，人类遗传学研究面临的关键障碍是区分导致疾病的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)建立基于细胞的分析方法来测量apoB生物学；2)测试特定基因和变体对细胞分析的影响；以及3)根据等位基因在这些细胞分析中的功能重要性对等位基因进行加权后，分析与血脂或心肌梗死风险的关联。我们 假设遗传学与系统获得的细胞功能数据相结合，可以准确定位不仅导致低密度脂蛋白或甘油三酯改变，而且导致心肌梗死风险的新基因。为了验证这一假设，我们提出了以下目标：目标1--强有力地建立系统的过度表达、敲除和互补，用于同时测试细胞中apoB相关功能的多个基因和变体；目标2-扩大我们技术的应用，以测试120个基因，目的是识别更多新的低密度脂蛋白-C和甘油三酯基因；以及目标3-利用我们的技术破译哪些低密度脂蛋白-C和甘油三酯基因也会增加心肌梗死的风险。这一建议解决了现代遗传学的一个根本挑战(区分个人基因组中功能相关的和中性的变体)，方法是将新技术(基于细胞的系统基因和基因变体的功能表征)应用于重大的未得到满足的健康需求(改善的心肌梗塞治疗)。

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).