CANDIDATE GENE STUDIES OF OBESITY GUIDED BY WHOLE GENOME ASSOCIATION DATA

描述(申请人提供)：肥胖症在美国的流行有增无减，并伴随着严重的并发症，包括糖尿病、癌症、心血管疾病和死亡。尽管最近肥胖率的上升是由于生活方式的改变，但易感性 或者，对肥胖的抵抗力很大程度上受到遗传因素的影响。由研究人员领导的全基因组关联(GWA)研究已经确定了人类基因组中数十个常见的DNA序列变异与体重指数(BMI)和其他肥胖衡量标准相关的位置(位置)。尽管GWA研究取得了成功，但这些研究只能评估常见的变异，而且这些变异大多是非编码的，这使得人们很难确定每个相关基因座的多个基因中的哪些是相关的。尽管从GWA研究中发现的基因座仍然可以突出相关的生物学途径，但相关基因的不确定性是完成功能和计算后续研究的关键障碍，这些后续研究将详细揭示GWA研究所暗示的生物学。因此，我们将致力于研究罕见的变异，特别是罕见的编码变异，这些变异可以更准确地定位影响肥胖的基因。我们还将重新分析现有的大型(N~200,000)GWA数据集，使用包含更罕见的遗传变异的新“参照板”，以便能够测试更罕见的遗传变异 与BMI和其他肥胖指标的关系。我们将在复制样本中测试和跟踪编码和非编码变异；我们将把非编码变异与基因组注释联系起来，以提供对机制的进一步洞察(目标1)。此外，我们将从GWA研究确定的基因座中选择600个基因，并在表型良好的样本和从BMI分布的尾部提取的样本中对这些基因的编码区进行重点、有针对性的测序(目标2)。为了测试更低频率的编码变异，因此超出了GWA研究的范围，我们将对从BMI分布尾部提取的样本进行更全面的基因分型研究，使用一种“外显子芯片”，全面调查频率为0.5%的非同义变异。我们将把这些数据与其他可用的完整外显子基因和序列数据结合起来，以识别与BMI和其他肥胖衡量标准相关的个体变异(因此也包括基因)(目标3)。最后，我们将把基因分型和测序数据与其他数据集(基因表达、蛋白质相互作用)相结合，以确定另外600个基因，以便进一步进行有针对性的测序，以确定具有影响BMI和其他肥胖衡量标准的稀有变异集合的基因，并将这些研究扩展到非欧洲祖先的样本(目标4)。成功地定位与肥胖相关的基因将是发现影响人类肥胖的关键途径的关键下一步，这反过来又可以指导治疗和预防的努力。

DESCRIPTION (provided by applicant): The obesity epidemic in the U.S. continues unabated, and is accompanied by substantial complications, including diabetes, cancer, cardiovascular disease, and death. Although the recent rise in obesity is due to lifestyle changes, susceptibility or resistance to obesity is strongly influenced by genetic factors. Genome-wide association (GWA) studies, led by the investigators, have identified dozens of places (loci) in the human genome where common DNA sequence variation is associated with body mass index (BMI), and other measures of obesity. Although successful, these GWA studies have only been able to assess common variation, and most of these variants are noncoding, making it difficult to be confident about which of the multiple genes in each of the associated loci are relevant. Although loci identified from GWA studies can still highlight relevant biological pathways, the uncertainty about the relevant genes represents a key obstacle to completing the functional and computational follow-up studies that would reveal in detail the biology that has been hinted at by the GWA studies. Accordingly, we will focus our efforts on studying rare variation, and particularly rare coding variation, which can more precisely pinpoint genes that influence obesity. We will also reanalyze existing large (N~200,000) GWA data sets, using new "reference panels" containing rarer genetic variants to be able to test rarer genetic variation for association with BMI and other measures of obesity. We will test and follow-up in replication samples both coding and noncoding variation; we will correlate noncoding variation with genomic annotations that could provide further insight into mechanism (Aim 1). In addition, we will select 600 genes from within the loci identified by GWA studies and perform focused, targeted sequencing of the coding regions of these genes in well-phenotyped samples and samples drawn from the tails of the BMI distribution (Aim 2). To test coding variants that are of even lower frequency and therefore beyond the reach of GWA studies, we will perform more comprehensive genotyping studies in samples drawn from the tails of the BMI distribution, using an "exome chip" that comprehensively surveys nonsynonymous variation with frequency >0.5%. We will combine these data with additional available whole exome genotype and sequence data to identify individual variants (and hence genes) that show association with BMI and other measures of obesity (Aim 3). Finally, we will integrate the genotyping and sequencing data with other data sets (gene expression, protein-protein interaction) to identify an additional 600 genes for further targeted sequencing to identify genes with collections of rare variants that influence BMI and other measures of obesity, and extend these studies into samples of non-European ancestries (Aim 4). Successfully pinpointing genes that are associated with obesity would be a critical next step in uncovering key pathways that influence obesity in humans, which in turn could guide efforts at therapy and prevention.