High-throughput screening and stem cell modeling of causal eQTL variants

描述（由申请人提供）：人类心血管疾病（CVD）新的有效治疗方法的发现需要识别和验证新的疾病机制。近年来，基因组变异的研究进入了一个新的阶段，无偏全基因组关联研究（GWAS）可以发现与常见疾病相关的新的遗传位点。我们最近描述了95个与血脂水平相关的基因座，LDL胆固醇（LDL-C），HDL胆固醇（HDL-C）或甘油三酯（TG）与CVD的风险密切相关。将新的关联转化为功能性见解，并最终降低CVD风险的疗法，需要做很多工作。关键的一步是确定这些基因位点如何影响与脂质代谢相关的人类组织类型（主要是肝脏和脂肪）的表型。我们对患者手术肝脏和脂肪组织样本中的基因型与基因表达进行了表达数量性状位点（eQTL）分析;从这项工作中，我们发现了许多脂质相关标签单核苷酸多态性（SNP）与附近基因的肝脏或脂肪表达之间的强相关性。这些观察结果表明，与标签SNP连锁不平衡（LD）的因果SNP直接影响导致人类血脂水平变化的因果基因的表达。识别这些致病SNP和致病基因将有助于深入了解DNA变异驱动肝脏和脂肪表型变化的分子机制，并最终影响疾病风险。我们的总体策略是将联合收割机几种创新方法结合起来以鉴定偶然的SNP。我们将：（1）使用新的大规模平行报告基因测定（MPRA）对eQTL基因座中的候选SNP进行高通量筛选，以改变适当组织类型中报告基因表达，从而优先考虑SNP用于进一步研究;（2）使用人类基因组编辑和尖端TAL效应核酸酶（TALEN）技术来改变人类多能干细胞（hPSC）中的每个高优先级SNP，以便产生仅在SNP处不同的等基因细胞系;（3）将等基因hPSC分化成适当的组织类型;和（4）测量附近的基因表达以确认SNP确实是eQTL的原因。我们建议对人类肝脏和脂肪中具有eQTL的57个脂质相关基因座实施这一总体策略。成功完成该项目不仅将为脂质代谢生物学提供新的见解，而且还将建立一种新的方法学范式，研究人员可以通过该范式确定下一代人类遗传研究中确定的DNA序列变异是复杂表型的遗传基础。

DESCRIPTION (provided by applicant): The discovery of new and effective treatments for human cardiovascular disease (CVD) requires the identification and validation of novel disease mechanisms. Recently, studies of genomic variation entered a new phase, in which unbiased genome-wide association studies (GWAS) can identify novel genetic loci associated with common diseases. We have recently described 95 loci associated with blood lipid levels LDL cholesterol (LDL-C), HDL cholesterol (HDL-C), or triglycerides (TG), which are strongly associated with risk for CVD. Much work will be needed to convert the novel associations into functional insights and, ultimately, therapies to reduce the risk of CVD. A key step is to determine how these genetic loci affect phenotypes in human tissue types relevant to lipid metabolism, principally liver and adipose. We have performed expression quantitative trait locus (eQTL) analyses of genotype vs. gene expression in surgical liver and adipose tissue samples from patients; from this work, we found strong associations between a number of lipid-associated tag single nucleotide polymorphisms (SNPs) and either hepatic or adipose expression of nearby genes. These observations suggest that causal SNPs in linkage disequilibrium (LD) with the tag SNPs directly influence the expression of causal genes that are responsible for changes in blood lipid levels in humans. Identifying these causal SNPs and causal genes would lead to insights into the molecular mechanisms by which the DNA variants drive phenotypic changes in liver and adipose and, ultimately, affect the risk of disease. Our general strategy is to combine several innovations to identify casual SNPs. We will: (1) perform high- throughput screening of candidate SNPs in eQTL loci for alteration of reporter gene expression in the appropriate tissue type, using a novel massively parallel reporter assay (MPRA), to prioritize SNPs for further study; (2) use human genome editing with cutting-edge TAL effector nuclease (TALEN) technology to alter each high-priority SNP in human pluripotent stem cells (hPSCs), so as to generate isogenic cell lines that differ only at the SNP; (3) differentiate the isogenic hPSCs into the appropriate tissue type; and (4) measure nearby gene expression to confirm that the SNP is truly causal for the eQTL. We propose to implement this general strategy for 57 lipid-associated loci with eQTLs in human liver and adipose. Success in completing this project will not only provide fresh new insights into the biology of lipid metabolism, but will also establish a new methodological paradigm by which investigators can determine which DNA sequence variants identified in next-generation human genetic studies underlie the genetic basis of complex phenotypes.