Identification and functional impact of NAFLD associated genetic variants

 描述(申请人提供)：非酒精性脂肪性肝病(NAFLD)是由肝脏脂肪变性(脂肪堆积)引起的，是一种常见疾病，在美国影响多达2900万成年人，到2020年将成为全球肝病的头号病因。预防或治疗这种疾病的有效方法很少。需要更好地了解其病因，以提高诊断和治疗水平。我们以前发现NAFLD是可遗传的(受遗传影响)，并在5个与肝脏脂肪变性相关的基因座上发现了共同的单核苷酸多态(SNPs)(次要等位基因频率(MAF)和GT；5%)，首先在约7000名欧洲血统的个体中，然后在不同的祖先中。这5个基因座上的变异共同解释了约20%的遗传力，这表明其他有影响力的变异仍有待发现。我们和其他人现在发现，含有功能编码(影响蛋白质序列)的基因通常也会含有影响较小的常见变体，也可能含有影响较大的罕见变体。在五个相关基因座中的三个，我们现在已经确定了假定的跨祖先的功能编码变体。最近的全基因组和外显子组测序研究发现了许多新的编码变异，但许多是低频率(MAF 1-5%)或罕见(MAF&lt；1%)的，并且是中性的，而不是破坏性的。由于归因和小样本数量的限制，这些低频率和罕见的变异在全基因组关联研究中一直没有得到充分的探索。这些变种现在可以使用新的Illumina人类外显子组珠芯片在大量样本中进行检测。此外，在我们建立的一种新的基于细胞的肝脏脂肪变性模型中，我们可以测试特定的基因和变体是否影响肝脏脂肪堆积。我们假设低频率(MAF 1-5%)和罕见(MAF&lt；1%)的编码变异对肝脏脂肪变性有影响，如果在肝脏中表达，会影响肝脏的脂肪堆积。为了识别和表征对NAFLD有影响的低频和稀有频率变异，我们现在已经收集了最大、最具祖先多样性的基于群体的个体集合(来自8个队列的16,000个个体)，测量肝脏脂肪变性，并使用Exome BeadChip对它们进行基因分型。我们将在我们的队列中协调肝脏脂肪变性的表型和基因类型，并进行跨组的单一变异、基于基因和条件荟萃分析，以确定可能的因果变异。我们将在4,000例经组织学证实的NAFLD病例和约3,000名对照中追踪来自肝脏脂肪变性分析的顶级相关变异和基因，以复制我们的发现。利用我们的肝脏脂肪变性的细胞模型，我们将在人类肝细胞系中过度表达和敲除含有编码变体的肝脏表达基因，并表征它们的遗传和脂质学作用机制。我们将从我们已经识别的包含与NAFLD相关的编码变体的三个基因开始，然后继续从拟议的外显子组分析中识别和复制新的基因。这项工作将开始定义导致NAFLD的遗传和代谢机制，从而为开发新的生物标记物和潜在的治疗这种疾病提供信息。

 DESCRIPTION (provided by applicant): Nonalcoholic fatty liver disease (NAFLD) is caused by hepatic steatosis (lipid accumulation), is a common disease that affects up to 29 million adults in the U.S., and will become the number one cause of liver disease worldwide by 2020. There are few effective ways to prevent or treat this disease. A better understanding of its etiology is needed to improve diagnosis and treatment. We previously found that NAFLD is heritable (genetically influenced) and identified common (minor allele frequency (MAF) >5%) single nucleotide polymorphisms (SNPs) at 5 loci that associate with hepatic steatosis first in ~7,000 individuals of European ancestry and then across ancestries. Variants at the 5 loci together explain ~20% of heritability suggesting that other influential variants remain to be discovered. We and others have now found that genes harboring functional coding (affecting protein sequence) common variants of small effect often can also harbor rare variants with large effects. At three of the five associated loci we have now identified putative functional coding variants across ancestries. Recent whole genome and exome sequencing studies identified many new coding variants but many are low frequency (MAF 1-5%) or rare (MAF < 1%) and neutral as opposed to damaging. These low frequency and rare variants have been underexplored in genome-wide association studies due to the limitations of imputation and small sample sizes. These variants can now be affordably assayed in large numbers of samples using the new Illumina Human Exome BeadChip. Further, we can test whether particular genes and variants affect hepatic lipid accumulation in a new cell based model of hepatic steatosis we have created. We hypothesize that low frequency (MAF 1-5%) and rare (MAF <1%) coding variants with effects on hepatic steatosis exist and if expressed in liver, affect liver lipid accumulation. To identify and characterize low and rare frequency variants for effects on NAFLD, we have now assembled the largest, most ancestrally diverse population based collection of individuals (>16,000 from 8 cohorts) with measures of hepatic steatosis and genotyped them with the Exome BeadChip. We will harmonize the hepatic steatosis phenotype and genotypes in our cohorts and carry out single variant, gene based, and conditional meta analyses across groups to identify putative causal variants. We will follow up top associating variants and genes from hepatic steatosis analyses in >4,000 histologically confirmed NAFLD cases and ~3,000 controls to replicate our findings. Using our cellular model of hepatic steatosis, we will overexpress and knockdown liver expressed genes harboring coding variants in human liver cell lines and characterize their genetic and lipidomic mechanisms of action. We will start with the three genes we have already identified that harbor coding variants that associate with NAFLD and then proceed to new genes identified and replicated from the proposed exome analyses. This work will begin to define the genetic and metabolic mechanisms which cause NAFLD to inform development of new biomarkers as well as potential therapeutics for this condition.