Identification and functional impact of NAFLD associated genetic variants

 描述（由申请人提供）：非酒精性脂肪性肝病（NAFLD）是由肝脏脂肪变性（脂质积聚）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原因。有一些有效的方法来预防或治疗这种疾病。因此，需要更好地了解其病因，以提高诊断和治疗。我们之前发现NAFLD是可遗传的（遗传影响），并在5个基因座上发现了常见的（次要等位基因频率（MAF）>5%）单核苷酸多态性（SNP），这些基因座首先在约7，000名欧洲血统的个体中与肝脂肪变性相关，然后跨越血统。5个位点的变异共同解释了约20%的遗传力，表明其他有影响力的变异仍有待发现。我们和其他人现在已经发现，携带功能编码（影响蛋白质序列）的基因通常具有小的影响，但也可能具有大的影响。在五个相关位点中的三个，我们现在已经确定了跨祖先的推定功能编码变体。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体，但许多是低频率（MAF 1-5%）或罕见（MAF < 1%）和中性的，而不是破坏性的。由于插补和小样本量的限制，这些低频率和罕见的变异在全基因组关联研究中未被充分探索。现在可以使用新的Illumina Human Exome BeadChip在大量样品中对这些变体进行经济实惠的分析。此外，我们可以在我们创建的基于细胞的肝脂肪变性新模型中测试特定基因和变体是否影响肝脂质积聚。我们假设存在对肝脂肪变性有影响的低频率（MAF 1-5%）和罕见（MAF <1%）编码变体，并且如果在肝脏中表达，则影响肝脏脂质积聚。为了鉴定和表征对NAFLD影响的低频率和罕见频率变体，我们现在已经收集了最大的、最具祖先多样性的基于人群的个体集合（来自8个队列的> 16，000），测量了肝脂肪变性，并用外显子组珠芯片对其进行基因分型。我们将在我们的队列中协调肝脂肪变性表型和基因型，并在各组中进行单变异、基于基因和条件性Meta分析，以确定推定的因果变异。我们将在> 4，000例组织学证实的NAFLD病例和~ 3，000例对照中随访来自肝脂肪变性分析的顶级相关变体和基因，以复制我们的发现。使用我们的肝脂肪变性细胞模型，我们将在人肝细胞系中过表达和敲低肝脏表达的携带编码变体的基因，并表征其遗传和脂质组学作用机制。我们将从我们已经确定的三个基因开始，这些基因含有与NAFLD相关的编码变体，然后从拟议的外显子组分析中确定和复制新的基因。这项工作将开始，以确定导致NAFLD的遗传和代谢机制，为开发新的生物标志物以及这种疾病的潜在治疗方法提供信息。

 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.