Genetic epidemiology of rare and regulatory variants for metabolic traits

代谢性状的罕见变异和调控变异的遗传流行病学

• 批准号: 8221707
• 负责人: KAREN L. MOHLKE
• 金额: $ 65.06万
• 依托单位: UNIV OF NORTH CAROLINA CHAPEL HILL
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-09-05 至 2016-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8221707
• 关键词: Adipocytes; Adipose tissue; Adult; Affect; Age; Alcohol consumption; Alleles; Behavior; Behavioral; Biolectric Impedance; Biological Markers; Biopsy; Biopsy Specimen; Blood Pressure; Body Composition; Cardiovascular Diseases; Cardiovascular system; Central obesity; Clinical; Coffee; Complications of Diabetes Mellitus; DNA; Data; Diabetes Mellitus; Diagnosis; Diagnostic; Disease; Disease susceptibility; Dyslipidemias; Environment; Epidemiology; Etiology; Event; Exercise; Fatty acid glycerol esters; Finland; Gene Expression; Gene Frequency; Genes; Genetic; Genetic Determinism; Genome; Genomics; Genotype; Glucose; Goals; Hormones; Individual; Inherited; Insulin; Insulin Resistance; Lead; Lipids; Lipoproteins; Measurement; Meta-Analysis; Metabolic; Metabolic Diseases; Metabolic syndrome; Methods; Minor; Morbidity - disease rate; Nonesterified Fatty Acids; OGTT; Obesity; Participant; Pathway interactions; Pharmaceutical Preparations; Phenotype; Physical activity; Plasma; Population; Proinsulin; RNA; Randomized; Regression Analysis; Relative (related person); Resources; Risk; Risk Factors; Sample Size; Sampling; Site; Smoking; Subgroup; Testing; Tissue Sample; Transcript; United States; Variant; Vegetables; Visit; Work; base; cohort; cost; cytokine; disease characteristic; disease diagnosis; follow-up; gene environment interaction; genetic association; genetic epidemiology; genetic variant; genome sequencing; genome wide association study; improved; in vitro activity; mortality; novel; population based; research clinical testing; subcutaneous; trait

DESCRIPTION (provided by applicant): Diabetes, obesity, metabolic syndrome, and cardiovascular disease are major causes of morbidity and mortality in the USA and worldwide. In the United States, ~34% of adults age e 20 years harbor a set of metabolic risk factors that include abdominal obesity, insulin resistance, atherogenic dyslipidemia, a proinflammatory state, and elevated blood pressure. Substantial evidence exists supporting a genetic component in the etiology of these traits. Our overall goal is to identify genetic variants that are responsible for variability in metabolic traits and risk to the related diseases. In this proposal, we aim to detect both rare variants and regulatory variants to further understand the genes, mechanisms, and pathways that influence obesity, metabolic syndrome, and diabetes. Large population cohorts are needed to identify less common (.005 d MAF < .05) and rare (MAF < .005) genetic determinants, to dissect the genetic contributions to correlated traits, and to evaluate the relative effects of and interactions between genes, environment, and behavior. One of the largest single-site population-based cohorts in which to evaluate genetic determinants of metabolic traits, the METSIM cohort of 10,197 individuals was ascertained in Kuopio, Finland during 2005- 2010. Participants were subjected to extensive clinical exams including oral glucose tolerance tests, body composition analysis, and measurement of plasma biomarkers and metabolites, and behavioral and clinical diagnostic data were collected for diabetes, diabetes complications, and cardiovascular events. In the context of the METSIM study, we will sequence total genomic DNA from 1,000 individuals at >4X coverage and impute genetic variants into 9,197 additional METSIM individuals. We will test variants for association with up to 200 metabolic quantitative traits and follow up association results via imputing variants into >15,000 additional samples. Using subcutaneous adipose samples from a subset of 400 METSIM participants, we will identify allele-specific differences in adipocyte expression and test potentially causal metabolic disease variants for functional regulatory effects. In addition, we will assess evidence for interactions and causal relationships between metabolic traits. Through this work we expect to identify novel genetic determinants of metabolic traits, discover pathogenic regulatory variants, and determine multivariate genetic, regulatory, and environmental relationships that lead to diabetes, obesity, and the metabolic syndrome. Better understanding of these factors and mechanisms may lead to clearer characteristics of disease subgroups and more targeted diagnoses and treatments. PUBLIC HEALTH RELEVANCE: Diabetes, obesity, and the metabolic syndrome are leading causes of morbidity and mortality worldwide. Traits related to these diseases have a strong inherited basis. The proposed work will identify novel variants that influence these traits and mechanisms by which DNA variants influence gene expression and disease. The results may lead to improved disease diagnosis and treatment.

描述（由申请人提供）：糖尿病、肥胖、代谢综合征和心血管疾病是美国和世界范围内发病率和死亡率的主要原因。在美国，大约34%的20岁以上的成年人有一系列代谢危险因素，包括腹部肥胖、胰岛素抵抗、动脉粥样硬化性血脂异常、促炎状态和血压升高。存在大量证据支持这些性状的病因学中的遗传成分。我们的总体目标是确定导致代谢特征变异性和相关疾病风险的遗传变异。在本提案中，我们的目标是检测罕见变异和调节变异，以进一步了解影响肥胖，代谢综合征和糖尿病的基因，机制和途径。需要大量的人口队列来确定不太常见的(。005 d MAF < 0.05)和罕见（MAF < 0.005）遗传决定因素，剖析遗传对相关性状的贡献，并评估基因、环境和行为之间的相对影响和相互作用。2005年至2010年，在芬兰库奥皮奥（Kuopio）确定了10,197人的METSIM队列，这是评估代谢性状遗传决定因素的最大单点人群队列之一。参与者接受了广泛的临床检查，包括口服葡萄糖耐量试验、体成分分析、血浆生物标志物和代谢物的测量，并收集了糖尿病、糖尿病并发症和心血管事件的行为和临床诊断数据。在METSIM研究的背景下，我们将对1000个个体的基因组DNA进行测序，并对另外9197个METSIM个体进行遗传变异推断。我们将测试变异与多达200种代谢数量性状的关联，并通过将变异输入到150 000个额外样本中来跟踪关联结果。使用来自400名METSIM参与者的皮下脂肪样本，我们将确定脂肪细胞表达的等位基因特异性差异，并测试潜在的代谢性疾病变异的功能调节作用。此外，我们将评估代谢性状之间相互作用和因果关系的证据。通过这项工作，我们期望确定代谢特征的新遗传决定因素，发现致病调节变异，并确定导致糖尿病，肥胖和代谢综合征的多变量遗传，调节和环境关系。更好地了解这些因素和机制可能会导致更清晰的疾病亚群特征和更有针对性的诊断和治疗。