Obesity Brain Expression

描述（由申请人提供）：神经内分泌因素已令人信服地与肥胖的病因学有关。虽然全基因组关联研究（GWAS）已经确定了与肥胖相关的基因和位点的分数，但缺乏对这些基因的功能作用的了解，特别是在人类大脑中。许多脑库没有单一的体重指数（BMI）指标。然而，纵向队列研究中的脑捐赠计划代表了一种独特的脑样本资源，具有长达六十年的生前数据，包括BMI。这项提案是三个纵向队列研究之间的合作：1）心脏病研究（FHS），2）宗教秩序研究（ROS）和3）记忆和衰老项目（MAP）。从这些研究中已经捐赠的1,300多个死后大脑样本中筛选出75个来自持续肥胖个体的样本和75个来自BMI持续正常（18.5<BMI<25）个体的样本。这些精心挑选的样本为研究特定脑区基因表达与BMI的关系提供了前所未有的机会，为BMI的神经内分泌控制提供了关键见解。本申请提出在来自FHS、ROS和MAP脑库的高度表征的选定样品中应用下一代RNA测序和microRNA测序技术以及最先进的统计方法，以进一步理解肥胖的遗传基础。通过创建一个广泛的脑源性基因组数据的公共资源，可以最大限度地提高产生这些数据的投资回报，这些数据对研究各种疾病和临床措施都有价值。在目标1中，我们提出了2个大脑区域的RNA和microRNA测序：下丘脑外侧和纹状体，以确定来自持续肥胖个体的75个样本和75个对照（BMI始终正常）的区域特异性基因表达模式。RNA测序将识别编码序列变体，新的基因转录本和剪接点，并估计基因单个外显子的大脑区域特异性RNA表达水平。MicroRNA测序将鉴定与基因表达调控有关的短RNA序列。我们将使用这些数据来表征以前在全基因组关联研究中鉴定的基因，并鉴定肥胖和非肥胖个体脑组织之间差异表达的新基因。在目标2中，我们将整合全基因组SNP和转录组数据，进行eSNP，eQTL和途径分析，以确定潜在的生物学机制。这些研究将提供深入了解基因在肥胖的启动和病理生理学中的作用，并创建一个有价值的公共数据库，其中包含一组综合表型特征的参与者中大脑中综合特征的区域基因表达。

DESCRIPTION (provided by applicant): Neuroendocrine factors have been convincingly implicated in the etiology of obesity. Although genome-wide association studies (GWAS), have identified scores of genes and loci associated with obesity, insight into the functional roles for these genes, particularly within the human brain, is lacking. Many brain banks do not have a single body mass index (BMI) measure. However, brain donation programs within longitudinal, cohort studies represent a unique resource of brain samples with up to six decades of ante-mortem data including BMI. This proposal is a collaboration among three such longitudinal cohort studies: 1) The Framingham Heart Study (FHS) 2) The Religious Order Study (ROS) and 3) the Memory and Aging Project (MAP). Selection from over 1,300 post mortem brain samples already donated via these studies enabled identification of 75 samples from consistently obese individuals and 75 samples from individuals with consistently normal BMI (18.5<BMI<25). These carefully selected samples provide an unprecedented opportunity to study the relationship of gene expression in specific brain regions to BMI providing key insight into the neuroendocrine control of BMI. This application proposes to apply next generation RNA sequencing and microRNA sequencing technology and state of the art statistical approaches in highly characterized, selected samples from the FHS, ROS and MAP brain banks to further the understanding of the genetic basis of obesity. The return on investment in generating these data will be maximized by creating a publicly available resource of extensive brain derived genomic data of value for studying a wide range of diseases and clinical measures. In Aim 1 we propose RNA and microRNA sequencing in 2 brain regions: lateral hypothalamus and striatum to determine region specific gene expression patterns in 75 samples from consistently obese individuals and 75 controls (consistently normal BMI). RNA-sequencing will identify coding sequence variants, novel gene transcripts, & splice junctions and estimate brain region specific RNA expression levels for individual exons of genes. MicroRNA sequencing will identify short RNA sequences implicated in regulation of gene expression. We will use these data to characterize genes previously identified in genomewide association studies and to identify novel genes differentially expressed between brain tissue from obese and non-obese individuals. In Aim 2 we will integrate the genome-wide SNP and transcriptome data to perform eSNP, eQTL, and pathway analyses to identify underlying biological mechanisms. These studies will provide insight into the role of genes in the initiation and pathophysiology of obesity and create a valuable public database containing comprehensively characterized regional gene expression in brain in a cohort of comprehensively phenotypically characterized participants.