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: 7682091
• 负责人: Donna K Arnett
• 金额: $ 75.74万
• 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 2012-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7682091
• 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; Disease; Dyslipidemias; Endowment; Environment; Environmental Risk Factor; Exclusion Criteria; Family; Family Study; Family member; Fasting; Fatty acid glycerol esters; Fenofibrate; Fibrates; Funding; Future; Genes; Genetic; Genetic Predisposition to Disease; Genetic Variation; Genome; Genomics; Genotype; Glucose; Guidelines; HDL-triglyceride; Health; Heart Diseases; High Density Lipoprotein Cholesterol; Hour; Human; Hypertriglyceridemia; Incidence; Individual; Inflammatory; Ingestion; Interleukin 6 Receptor; Interleukin-2; Intervention; Intervention Studies; Knowledge; 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; Program Evaluation; Province; Relative (related person); Research; Research Design; Research Personnel; Risk; Role; Secure; Signal Transduction; Spectrometry; Staging; Stratification; Structure; Systems Biology; Technology; Testing; Therapeutic Intervention; Triglycerides; Variant; Very low density lipoprotein; Work; adiponectin; base; clinical practice; cohort; design; effective therapy; falls; follow-up; gene environment interaction; genetic analysis; genetic linkage analysis; genetic variant; genome wide association study; genome-wide; genome-wide linkage; inflammatory marker; interest; lipoprotein triglyceride; meetings; member; multidisciplinary; novel; open label; post intervention; programs; public health relevance; 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发病率的急剧上升，激发了人们对了解影响甘油三酯（tg）升高、低HDL-C和高非HDL-C的干预作用的兴趣。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。遗传变异影响脂质水平及其对环境因素的反应，尽管这种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（GOLDN）的遗传学，GOLDN是NHLBI项目中基因-环境相互作用（PROGENI）合作的4个网络之一。GOLDN是一项基于家庭的干预研究，旨在确定决定脂质（tg、HDL-C、LDL-C、核磁共振测量的颗粒大小）对两种干预反应的基因组区域，一种是提高脂质（摄入83%脂肪，700千卡/平方米的膳食），另一种是降低脂质（非诺贝特治疗160毫克/天，持续3周）。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）。招募和随访于2005年秋季完成（n=1123完成）。高脂膳食干预组在餐后0、3.5和6小时采集空腹脂质和脂蛋白，非诺贝特干预组在第0、1、20和21天采集空腹脂质和脂蛋白。具体来说，我们建议：(i)使用Affymetrix 6.0阵列对所有参与者进行基因分型。（ii）测试遗传变异与干预表型之间的关联（在进食后3.5和6小时测量餐后脂质，以及非诺贝特后的脂质），使用混合模型使用新型结构关联测试控制人群分层。错误发现率方法将控制多重测试。混杂的遗传-脂质关联将被评估为炎症和药物遗传变量。准备在外部队列中复制。我们将确定1500个与脂质和脂蛋白基线或干预表型最显著相关的snp，以及多达1500个变体，通过考虑我们在GOLDN中进化连锁证据和候选基因证据的背景下的发现，以及伴随的NHLBI GWA研究的发现。虽然目前的提案没有要求为复制提供资金，但我们已经从其他三个研究中获得了合作意向的协议。在复制之后，未来的研究将通过检查与基因干预相互作用相关的变异的功能相关性来扩展所提出的工作。对高脂肪饮食反应不良或对非诺贝特反应良好的个体的基因型特征可以使有针对性的干预措施减少血脂异常，并为临床实践确定有效的治疗方法。公共卫生相关性：卫生官员很早就认识到脂肪和胆固醇在肥胖、糖尿病和心脏病等疾病中所起的重要作用。然而，人们的基因是如何与他们的饮食脂肪摄入量或他们用药物来降低血脂的治疗相互作用的，人们知之甚少。拟议中的项目旨在确定影响脂肪和胆固醇对饮食和药物反应的基因变异；这些知识也许有一天会帮助医生根据个人的基因禀赋来定制预防措施和治疗方法。