Genetic epidemiology of rare and regulatory variants for metabolic traits

描述（由申请人提供）：糖尿病、肥胖症、代谢综合征和心血管疾病是美国和全球发病率和死亡率的主要原因。在美国，约34%的20岁以上的成年人存在一系列代谢风险因素，包括腹部肥胖、胰岛素抵抗、致动脉粥样硬化性血脂异常、促炎状态和血压升高。大量证据支持这些特征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和相关疾病风险的遗传变异。在这项提案中，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。需要大规模的人群队列来识别不太常见（0.005 d MAF <0.05）和罕见（MAF <0.005）的遗传决定因素，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。其中一个最大的单点人口为基础的队列，以评估代谢性状的遗传决定因素，METSIM队列的10,197人确定在芬兰库奥皮奥在2005年至2010年。参与者接受了广泛的临床检查，包括口服葡萄糖耐量试验，身体成分分析，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，我们将以>4X覆盖率对1，000个个体的总基因组DNA进行测序，并将遗传变异归因于另外9，197个METSIM个体。我们将测试变异与多达200种代谢数量性状的关联，并通过将变异插补到超过15，000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，并测试潜在的因果代谢疾病变体的功能调节作用。此外，我们将评估代谢特征之间的相互作用和因果关系的证据。通过这项工作，我们希望确定新的代谢性状的遗传决定因素，发现致病性调节变异，并确定多元的遗传，调节和环境的关系，导致糖尿病，肥胖和代谢综合征。更好地了解这些因素和机制可能会导致更清晰的疾病亚组特征和更有针对性的诊断和治疗。 公共卫生相关性：糖尿病、肥胖和代谢综合征是全球发病率和死亡率的主要原因。与这些疾病相关的特征具有很强的遗传基础。拟议的工作将确定影响这些特征的新变体，以及DNA变体影响基因表达和疾病的机制。这些结果可能会改善疾病的诊断和治疗。

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.