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，是心肌梗死（MI）的因果遗传危险因素，心肌梗死是世界范围内死亡的主要原因。需要新的策略来降低载脂蛋白和心肌梗死风险，研究人类遗传变异可以找到降低心肌梗死风险的治疗靶点。通过基于人群的测序和基因分型研究，我们和其他人得到了存在于成千上万个体中以血浆LDL-C、TG和心肌梗死状态为特征的所有蛋白质编码DNA变异的系统目录。然而，通过这些方法发现的大多数蛋白质编码变异是“中性的”，即它们对基因编码的蛋白质的功能影响很小或没有影响。因此，试图将蛋白质编码变异体与LDL-C、TG或MI联系起来面临着巨大的信号噪声问题，即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性变异。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)建立基于细胞的检测方法来测量载脂蛋白生物学；2)测试特定基因和变异对细胞分析的影响；3)根据这些细胞分析中等位基因的功能重要性，分析其与脂质或心肌梗死风险的关系。我们

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).