Pharmacogenetics of obesity and endocannabinergic modulation (POEM)

肥胖和内源性大麻素能调节的药物遗传学（POEM）

• 批准号: 7650677
• 负责人: Russell A. Wilke
• 金额: $ 22.71万
• 依托单位: MEDICAL COLLEGE OF WISCONSIN
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-08-01 至 2009-12-21
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7650677
• 关键词: Acute; Adipose tissue; Adult; Age; Alleles; Amidohydrolases; Anatomic Sites; Animals; Behavioral; Behavioral Genetics; Body Composition; Body fat; Body mass index; CNR1 gene; Candidate Disease Gene; Cannabis; Canned Foods; Centers for Disease Control and Prevention (U.S.); Central obesity; Cholesterol; Clinic; Clinical; Code; Cohort Studies; Communities; Comorbidity; Complex; DEXA; DNA; DNA Resequencing; Data; Databases; Density Gradient Centrifugation; Development; Disease; Dyslipidemias; Eating; Effectiveness; Endocannabinoids; Environmental Risk Factor; Enzymes; Epidemic; Etiology; European; Extended Family; Family; Fasting; Fatty acid glycerol esters; Food; Frequencies; Future; Gender; Genes; Genetic; Genetic Polymorphism; Genetic Variation; Genomics; Genotype; Glucose; Goals; Haplotypes; Health; Healthcare; High Density Lipoprotein Cholesterol; Hip region structure; Homeostasis; Human; Hydrolase Gene; Hypertriglyceridemia; Hypothalamic structure; Individual; Insulin; Insulin Resistance; International; Intravenous; Islets of Langerhans; Kinetics; LDL Cholesterol Lipoproteins; Laboratories; Leptin; Life; Ligands; Lipids; Lipoproteins; Liver; Maps; Measures; Medical; Medicine; Metabolic; Metabolic Diseases; Metabolic syndrome; Metabolism; Methods; Midbrain structure; Modeling; Monoacylglycerol Lipases; Mutation; Names; Nucleotides; Obesity; Overweight; Particle Size; Pathway interactions; Patients; Peripheral; Pharmacogenetics; Phenotype; Population; Prevalence; Probability; Property; Receptor Gene; Receptor Signaling; Regulation; Research; Research Infrastructure; Research Project Grants; Rewards; Risk; Risk Factors; Role; Satiation; Scanning; Series; Serine; Signal Pathway; Signal Transduction; Signaling Pathway Gene; Single Nucleotide Polymorphism; Site; Skeletal Muscle; Skinfold Thickness; Statistical Methods; Stimulus; Stratification; Study Subject; System; Testing; Transacylase; Triglycerides; United States; Validation; Variant; Visceral; Waist-Hip Ratio; Weight Gain; Wisconsin; X-Ray Computed Tomography; Yang; amidase; anandamide; base; biobank; blood glucose regulation; cannabinoid receptor; cohort; design; experience; fasting glucose; fatty acid amide hydrolase; food consumption; genetic analysis; glycemic control; human data; improved; in vivo; increased appetite; indexing; insulin sensitivity; interest; lipid disorder; obesity prevention; pleiotropism; population based; preclinical study; programs; public health relevance; response; subcutaneous; therapy design; trait; waist circumference

DESCRIPTION (provided by applicant): One of the most interesting cellular signaling pathways involved in the development of obesity and obesity-related comorbidity has been the endocannabinoid (eCB) system. It has been known for thousands of years that cannabis extracts increase appetite, particularly for highly palatable foods and can result in weight gain. The eCB system consists of two endogenous cannabinoid receptors, CB1 and CB2. Emerging animal and human data support the hypotheses that obesity and obesity-related metabolic disorders are associated with overactive signaling specifically at the level of the CB1 receptor (gene name CNR1). The CB1 receptor has two endogenous ligands: N-arachidonylethanolamine (AEA) and 2-arachdionylglycerol (2-AG). Synthesis of these ligands is regulated by a series of transacylases and phopholipases. Degradation of AEA is catalyzed by a serine amidase, fatty acid amide hydrolase (gene name FAAH). While 2-AG is degraded by multiple enzymes, recent evidence suggests a primary role for monoacylglycerol lipase (gene name MGLL). eCB/CB1 receptor signaling is involved in the regulation of food consumption and metabolism via multiple mechanisms: it regulates the rewarding properties of food via effects on central mesolimbic pathways; it also regulates food intake at the hypothalamus; and it modulates peripheral metabolism through effects on adipose tissue, the liver, skeletal muscle and the endocrine pancreas. Over-activity of eCB/CB1 signaling at any or all of these sites can result in increased food intake and/or altered metabolism, thus promoting obesity. The goal of the studies outlined in this application will be to define the degree to which eCB/CB1 signaling pathway gene variability contributes to human obesity. We propose to test this hypothesis in two independent study cohorts. Using haplotype tagging SNPs (tagSNPs) selected from the International Human Haplotype Map (HapMap), we have begun genotyping three critical eCB/CB1 signaling genes, and testing for association between variation in these candidate genes and obesity and obesity-related metabolic disorders (changes in insulin responsiveness and derangements in lipid homeostasis) in 2209 study subjects from 507 families participating in the Take Off Pounds Sensibly (TOPS) obesity research program. We plan to test tagSNPs in each of these candidate eCB/CB1 signaling genes for association with 12 quantitative traits: body mass index (BMI), waist circumference, hip circumference, waist/hip ratio (WHR), fasting glucose, insulin, insulin/glucose ratio, homeostasis model assessment of insulin resistance (HOMA-IR), fasting triglyceride levels, total cholesterol, LDL cholesterol, and HDL cholesterol. Any tagSNPs found to be associated with BMI (as a global measure of obesity) or WHR (as a measure of abdominal obesity) will be further tested for association with total body fat by DEXA scan (as a confirmatory measure of global obesity) and the ratio of visceral fat / subcutaneous fat by CT scan (as a confirmatory measure of abdominal obesity) in 504 rigorously phenotyped individuals from the 50 TOPS families that have proven most informative in prior genetic analyses. These 504 rigorously phenotyped individuals are nested within the original cohort. Any tagSNPs found to be associated with glucose homeostasis in the original cohort will also be tested for a relationship with insulin sensitivity in these 504 more rigorously phenotyped individuals using the minimal model (MinMod), which compensates for subject-to-subject variability in insulin and glucose kinetics. The MinMod provides four well characterized glycemic control parameters: insulin sensitivity (SI), acute insulin response to intravenous glucose (AIRG), glucose effectiveness (SG), and disposition index (DI). TagSNPs found to be associated with lipid levels in the original cohort will also be tested for association with lipoprotein particle size distribution in these 504 subjects. All three candidate genes (FAAH, MGLL, and CNR1) will then be resequenced in 96 obese study subjects with insulin resistance and dyslipidemia identified from within the original TOPS cohort. All common and rare variants will be re-genotyped in the entire cohort (n = 2209), and Bayesian statistical methods will be employed to identify potentially causative alleles. For each gene, causative polymorphisms will be prioritized using a quantitative trait nucleotide (QTN) approach, and all variants with greater than 80% posterior probability of effect (based upon Bayesian information criterion) will be genotyped in a second population, the Marshfield Clinic Personalized Medicine Research Project (PMRP). The PMRP database represents one of the largest population-based Biobanks in the U.S (n = 19,573). This cohort will allow us to test the generalizability of our initial findings a population of similar ethnic composition. Each variant from the original family-based cohort will be prioritized according to pleiotropy (i.e., association with more than one obesity-related phenotypic trait). We will then use the PMRP population to test the most informative obesity alleles for association with BMI, and the most informative metabolic alleles for association with fasting glucose and routine clinical lipid data. PUBLIC HEALTH RELEVANCE: The current obesity epidemic represents a major international health crisis. The prevalence of obesity-related medical problems is continuing to increase, placing an unprecedented burden on health care infrastructure. We plan to quantify the role of three candidate genes in the development of obesity and obesity-related medical problems. In the future, individual patients with variation in these genes may benefit from targeted behavioral and/or pharmacological interventions designed to improve their health.

描述(申请人提供)：在肥胖和肥胖相关共病的发展过程中，最有趣的细胞信号通路之一是内源性大麻(ECB)系统。几千年来，人们都知道大麻提取物会增加食欲，特别是对美味的食物，并会导致体重增加。欧洲央行系统由两个内源性大麻素受体CB1和CB2组成。新兴的动物和人类数据支持这样的假设，即肥胖和肥胖相关的代谢紊乱与过度活跃的信号有关，特别是在CB1受体(基因名称CNR1)的水平上。CB1受体有两个内源性配体：N-花生四烯基乙醇胺(AEA)和2-花生二烯基甘油(2-AG)。这些配体的合成受一系列转酰基酶和磷脂酶的调节。AEA的降解是由一种丝氨酸酰胺酶，脂肪酸酰胺水解酶(基因名称FAAH)催化的。虽然2-AG被多种酶降解，但最近的证据表明单酰基甘油脂肪酶(基因名称MGLL)起主要作用。ECB/CB1受体信号通过多种机制参与食物消耗和代谢的调节：它通过影响中央中脑边缘通路来调节食物的奖赏特性；它还调节下丘脑的食物摄入量；它通过对脂肪组织、肝脏、骨骼肌和内分泌胰腺的作用来调节外周代谢。ECB/CB1信号在任何或所有这些部位的过度活动都会导致食物摄入量增加和/或代谢改变，从而促进肥胖。本申请概述的研究目标将是确定ECB/CB1信号通路基因变异性对人类肥胖的影响程度。我们建议在两个独立的研究队列中检验这一假设。使用从国际人类单倍型图谱(HapMap)中选择的单倍型标签SNPs(Tag SNPs)，我们已经开始对三个关键的ECB/CB1信号基因进行基因分型，并测试这些候选基因的变异与肥胖和肥胖相关代谢紊乱(胰岛素反应性变化和脂代谢紊乱)之间的关联，该研究来自507个家庭，来自507个家庭，参与了敏感地减轻体重(TOPS)肥胖研究计划。我们计划测试这些候选ECB/CB1信号基因中的每个标签SNPs与12个数量性状的关联：体重指数(BMI)、腰围、臀围、腰臀比(WHR)、空腹血糖、胰岛素、胰岛素/血糖比、胰岛素抵抗稳态模型评估(HOMA-IR)、空腹甘油三酯水平、总胆固醇、低密度脂蛋白胆固醇和高密度脂蛋白胆固醇。任何被发现与BMI(作为全球肥胖衡量标准)或腰围比(作为腹部肥胖衡量标准)相关的标签SNPs，将通过DEXA扫描(作为全球肥胖症的确认性衡量标准)和CT扫描(作为腹部肥胖症的确认性衡量标准)对来自50个TOP家庭的504个严格表型的个体进行进一步测试，以确定其与全身脂肪的相关性(作为全球肥胖症的确认性衡量标准)和内脏脂肪/皮下脂肪的比率(作为腹型肥胖症的确认性衡量标准)。这504个严格表型的个体嵌套在原始队列中。在最初的队列中被发现与葡萄糖稳态相关的任何标签SNPs也将使用最小模型(MinMod)在这504个更严格的表型个体中测试与胰岛素敏感性的关系，该最小模型(MinMod)补偿了受试者之间的胰岛素和葡萄糖动力学的变异性。MinMod提供了四个特征明确的血糖控制参数：胰岛素敏感性(SI)、静脉注射葡萄糖的急性胰岛素反应(AIRG)、葡萄糖有效性(SG)和处置指数(DI)。在最初的队列中被发现与血脂水平相关的TagSNPs也将被测试与这504名受试者中脂蛋白颗粒大小分布的相关性。所有三个候选基因(FAAH、MGLL和CNR1)将在96名肥胖研究受试者中重新测序，这些受试者从最初的TOP队列中识别出胰岛素抵抗和血脂异常。所有常见和罕见的变异都将在整个队列中重新进行基因分型(n=2209)，并将使用贝叶斯统计方法来识别潜在的致病等位基因。对于每个基因，原因多态将使用数量性状核苷酸(QTN)方法进行优先排序，所有后验效应概率大于80%的变异(基于贝叶斯信息标准)将在第二个群体-马什菲尔德临床个性化医学研究项目(PMRP)中进行基因分型。PMRP数据库代表了美国最大的基于种群的生物库之一(n=19573)。这一队列将使我们能够测试我们最初发现的概括性，即具有相似种族构成的人口。最初以家庭为基础的队列中的每个变异将根据多效性(即与一个以上与肥胖相关的表型特征的关联)进行优先排序。然后，我们将使用PMRP人群来测试与BMI相关的最有信息的肥胖等位基因，以及与空腹血糖和常规临床血脂数据相关的最有信息的代谢等位基因。与公共卫生相关：当前的肥胖症流行是一场重大的国际健康危机。与肥胖相关的医疗问题的流行正在继续增加，给卫生保健基础设施带来了前所未有的负担。我们计划量化三个候选基因在肥胖和肥胖相关医学问题发展中的作用。未来，具有这些基因变异的个体患者可能会受益于旨在改善他们健康的有针对性的行为和/或药物干预。