Genomewide Association Study of Lipid Response to Fenofibrate and Dietary Fat

非诺贝特和膳食脂肪的脂质反应的全基因组关联研究

• 批准号: 8129753
• 负责人: Donna K Arnett
• 金额: $ 58.63万
• 依托单位: UNIVERSITY OF ALABAMA AT BIRMINGHAM
• 依托单位国家: 美国
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-09-05 至 2014-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8129753
• 关键词: Affect; Agreement; Biochemical; Bioinformatics; Blood; CCL2 gene; Calories; Candidate Disease Gene; Cholesterol; Chromosomes, Human, Pair 1; Chromosomes, Human, Pair 3; Chromosomes, Human, Pair 4; Chylomicrons; Collaborations; Collection; Consumption; Copy Number Polymorphism; Data; Data Coordinating Center; Development; Diabetes Mellitus; Diet; Dietary Fats; Dietary Intervention; Disease; Dyslipidemias; Endowment; Environment; Environmental Risk Factor; Evaluation; Exclusion Criteria; Family; Family Study; Family member; Fasting; Fatty acid glycerol esters; Fenofibrate; Fibrates; Funding; Genes; Genetic; Genetic Predisposition to Disease; Genetic Variation; Genome; Genomics; Genotype; Glucose; Guidelines; HDL-triglyceride; Health; Heart Diseases; High Density Lipoprotein Cholesterol; High Density Lipoproteins; Hour; Human; Hypertriglyceridemia; Incidence; Individual; Inflammatory; Ingestion; Interleukin-2; Interleukin-6; Intervention; Intervention Studies; Knowledge; LDL Cholesterol Lipoproteins; Letters; Lipids; Lipoproteins; Low-Density Lipoproteins; Measures; Mediating; Meta-Analysis; Metabolic; Metabolic syndrome; Methodology; Methods; Microsatellite Repeats; Modeling; National Heart, Lung, and Blood Institute; Obesity; Parents; Participant; Particle Size; Pharmaceutical Preparations; Pharmacogenetics; Phenotype; Plasma; Play; Population; Population Control; Prevention; Principal Investigator; Province; Relative (related person); Research Design; Research Personnel; Risk; Role; Secure; Signal Transduction; Spectrometry; Staging; Stratification; Structure; Systems Biology; TNF gene; Technology; Testing; Therapeutic Intervention; Triglycerides; Variant; Very low density lipoprotein cholesterol; Work; adiponectin; base; clinical practice; cohort; design; effective therapy; falls; follow-up; gene environment interaction; gene therapy; genetic analysis; genetic linkage analysis; genetic variant; genome wide association study; genome-wide; genome-wide linkage; inclusion criteria; inflammatory marker; interest; lipoprotein triglyceride; meetings; member; multidisciplinary; novel; open label; post intervention; programs; receptor; response; tool; uptake

DESCRIPTION (provided by applicant): The dramatic rise in the incidence of obesity, metabolic syndrome, and diabetes has fueled interest to understand the role of interventions which affect elevated triglycerides (TGs), low HDL-C, and high non- HDL-C. Although LDL-C is a focus of NCEP-ATP-3 guidelines, HDL-C and TGs are also implicated as determinants of risk. Genetic variation influences lipid levels and their response to environmental factors, although the genetic basis of the variable response is not well described. To further characterize the genetic basis of lipids and lipoproteins and their response to environment, we propose a whole-genome association (GWA) study for the Genetics of Lipid Lowering and Diet Network (GOLDN), one of 4 networks in the NHLBI Programs in Gene-Environment Interaction (PROGENI) collaboration. GOLDN is a family-based intervention study designed to identify genomic regions that determine response of lipids (TGs, HDL-C, LDL-C, NMR-measured particle sizes) to 2 interventions, one to raise lipids (ingestion of an 83% fat, 700 kcals/m2 meal) and one to lower lipids (fenofibrate treatment 160 mg qd for 3 weeks). Additional phenotypes include adiponectin, glucose, and inflammatory markers (CRP, TNF1, MCP1, IL-2 soluble receptor, IL-6). Recruitment and follow up were completed in the fall of 2005 (n=1123 completed). During the high-fat meal intervention, fasting lipids and lipoproteins were collected at 0, 3.5 and 6 hours after the meal, and for the fenofibrate intervention, fasting lipid and lipoproteins were collected at days 0, 1, 20 and 21. Specifically, we propose to: (i) Genotype all participants using the Affymetrix 6.0 array. (ii) Test associations between genetic variants and intervention phenotypes (post-prandial lipids measured at 3.5 and 6 hours after ingestion of the meal, and post-fenofibrate lipids) using a mixed model controlling for population stratification using novel structured-association testing. False discovery rate methods will control for multiple testing. Confounding of genetic-lipid associations will be assessed for inflammatory and pharmacogenetic variables. (iii) Prepare for replication in external cohorts. We will identify 1,500 SNPs most significantly associated with lipid and lipoprotein baseline or intervention phenotypes and up to 1500 more variants by considering our findings in the context of evolving linkage evidence and candidate gene evidence within GOLDN, and findings from concomitant NHLBI GWA studies. Although the current proposal does not request funds for replication, we have already secured agreements from three other studies conveying intent to collaborate. Following replication, future research will extend the proposed work by examining the functional relevance of variants associated with gene-by-intervention interactions. Genotypic characterization of individuals who respond poorly to a high-fat diet or favorably to fenofibrate may enable targeted interventions to reduce dyslipidemia and identify effective treatments for clinical practice. PUBLIC HEALTH RELEVANCE: Health officials have long recognized the important role fat and cholesterol play in conditions and diseases such as obesity, diabetes, and heart disease. However, how people's genes interact with their consumption of dietary fat or their treatment with drugs to reduce blood fats is poorly understood. The proposed project aims to identify genetic variants that influence fat and cholesterol's response to diet and drugs; this knowledge may someday help doctors tailor prevention efforts and treatments based on individuals' genetic endowment.

描述（由申请人提供）：肥胖，代谢综合征和糖尿病的发生率的急剧上升引起了人们的兴趣，以了解影响甘油三酸酯（TGS），低HDL-C和高HDL-C的干预措施的作用。尽管LDL-C是NCEP-ATP-3指南的重点，但HDL-C和TG也被认为是风险的决定因素。遗传变异会影响脂质水平及其对环境因素的反应，尽管可变反应的遗传基础尚未得到很好的描述。为了进一步表征脂质和脂蛋白的遗传基础及其对环境的反应，我们提出了一项全基因组关联（GWA）研究脂质降低和饮食网络遗传学（GOLDN）的全基因组关联研究（GOLDN），这是NHLBI程序中基因环境相互作用（GroceNi）协作中NHLBI程序中的4个网络之一。 GOLDN是一项基于家庭的干预研究，旨在识别基因组区域，以确定脂质的反应（TGS，HDL-C，LDL-C，NMR粒度尺寸）至2种干预措施，一种是为了增加脂质（摄入83％的脂肪，700 kcals/m2餐）和下脂化处理160粒涂层160000000000000000岁。其他表型包括脂联素，葡萄糖和炎症标志物（CRP，TNF1，MCP1，IL-2可溶性受体，IL-6）。招聘和随访于2005年秋季完成（n = 1123完成）。在高脂餐干预期间，餐后0、3.5和6小时收集空腹脂质和脂蛋白，以及用于非诺贝特干预，禁食脂质和脂蛋白在第0、1、20和21天收集。 （ii）使用新型的结构化协助测试，使用混合模型控制种群分层的混合模型。错误的发现率方法将控制多次测试。将评估遗传脂质关联的混淆，以评估炎症和药物遗传学变量。 （iii）准备在外部人群中复制。我们将通过在Goldn中不断发展的连锁证据证据和候选基因证据的背景下考虑我们的发现，以及从一致的NHLBI GWA研究中考虑我们的发现，从而确定与脂质和脂蛋白基线或干预表型最显着相关的1,500个SNP以及多达1500种变体。尽管当前的提案并不要求资金复制，但我们已经从其他三项研究中获得了指定的协议，这些协议传达了与之合作的意图。复制后，未来的研究将通过研究与基因划分相互作用相关的变体的功能相关性来扩展所提出的工作。对高脂饮食反应较差或对非诺贝特的有益反应不佳的个体的基因型表征可以使靶向干预措施减少血脂异常并确定有效的临床实践治疗方法。公共卫生相关性：长期以来，卫生官员已经认识到脂肪和胆固醇在肥胖，糖尿病和心脏病等疾病中的重要作用。但是，人们的基因如何与饮食脂肪的消费或用药物治疗以减少血液脂肪相互作用。拟议的项目旨在确定影响脂肪和胆固醇对饮食和药物的反应的遗传变异。有一天，这些知识可能会帮助医生根据个人的遗传捐赠来量身定制预防和治疗。