课题基金 / 基金详情

Osteocalcin and Metabolic Risk Factors. The Framingham Study

Osteocalcin and Metabolic Risk Factors. The Framingham Study
骨钙素和代谢风险因素。
批准号:
7990841
负责人:
Yi-Hsiang Hsu
金额:
$20.93万
依托单位国家:
美国
项目类别:
财政年份:
2010
资助国家:
美国
项目状态:
已结题
起止时间:
2010-08-09 至 2012-06-30

项目摘要

项目成果

Yi-Hsiang Hsu的其他基金

相似基金

相关文献

中文摘要
翻译
描述(申请人提供):基于最近在啮齿动物身上的发现,骨钙素(OC)是成骨细胞特有的一种主要骨形成蛋白,作为瘦素调节成骨细胞的反馈环,它可能通过促进b细胞增殖、胰岛素产生、胰岛素敏感性和脂联素表达,在能量代谢的内分泌调节中发挥关键作用。这一新证据表明,骨细胞不仅在骨骼上发挥局部功能,还可能参与胰岛素抵抗和代谢综合征的发病机制。然而,OC如何与脂肪细胞、胰腺2细胞和其他参与葡萄糖稳态的功能分子相互作用的潜在机制仍不清楚。生物学证据的存在往往与截然不同的疾病的“内部表型”联系在一起,这提出了另一种可能性,即疾病之间可能并不像人们通常认为的那样相互独立。我们的研究试图将两个系统联系起来:骨骼和能量代谢。因此,这一建议的基本假设是,存在共同的遗传变量来调节血清OC和代谢风险因素(代谢综合征风险因素聚集:包括中心性肥胖、高血糖、血脂异常和高血压在内的风险因素的组合)。在这项应用中,我们在Framingham心脏研究中提出了一种全基因组关联(GWA)方法,以确定(1)血清OC的新遗传变异和(2)对血清OC和代谢风险因素(包括腰围、收缩压、空腹甘油三酯、空腹高密度脂蛋白、空腹血糖、空腹血浆胰岛素、脂联素浓度和胰岛素抵抗指数,如HOMA-IR和QUICI)具有直接多效性影响的共同基因决定因素。将使用最先进的GWA分析方法,包括使用最近开发的遗传力方法原理的多表型GWA分析,基于先验信息的加权假设,以及新开发的结构建模来推断直接多效性效应。还将应用生物信息学方法,如路径网络分析、基因集浓缩测试和ESNP分析。我们将使用已经收集的表型数据和可用的高密度550K Affymetrix基因分型数据。拟议的工作将利用弗雷明翰心脏研究丰富的可用数据和大样本量。这将是第一个使用GWA方法试图翻译动物OC发现的人类研究,这将提供机会产生新的假说来理解串扰背后的信号通路和潜在的生物学机制,因为人们还不完全了解这种骨蛋白如何调节葡萄糖代谢、胰岛素分泌和胰岛素敏感性。在人类身上证实这些发现也可能对女性具有重要的意义,她们通常患有骨质疏松症和心血管疾病风险因素聚集的病态、有时甚至是致命的并发症,即代谢综合征。 公共卫生相关性:最近的动物研究表明,骨钙素是一种重要的骨骼蛋白,参与能量代谢的内分泌调节。然而,骨钙素如何与脂肪细胞和胰腺2细胞相互作用的潜在机制仍然不清楚。我们的研究将是第一次使用最先进的全基因组关联方法来尝试识别骨钙素和代谢风险因素共享的新的遗传变异,这将提供对潜在分子靶点的有价值的见解,这将有助于进一步了解骨骼和能量代谢之间的潜在通信机制。
英文摘要
DESCRIPTION (provided by applicant): Based on a recent discovery in rodents, for the first time, osteocalcin (OC), a major bone formation protein uniquely secreted by osteoblasts, may play a crucial role in endocrine regulation of energy metabolism by enhancing b-cell proliferation, insulin production, insulin sensitivity and adiponectin expression as a feedback loop of Leptin's regulation of osteoblasts. This new evidence suggests that bone cells not only function locally on the skeleton, but may also be involved in the pathogenesis of insulin resistance and the metabolic syndrome. However, the underlying mechanisms for how OC interacting with adipocytes, pancreatic 2 cells and other molecules functionally involved in glucose homeostasis are still unclear. The existence of biological evidence linking "endo-phenotypes" of often quite distinct diseases raises another possibility that diseases may not be as independent of each other as is often assumed. Our study attempts to link two systems: bone and energy metabolisms. Thus the underlying hypothesis of this proposal is that there are shared genetic variants that regulate both serum OC and metabolic risk factors (metabolic syndrome risk factor clustering: a combination of risk factors including central obesity, hyperglycemia, dyslipidemia, and hypertension). In this application we are proposing a genome-wide association (GWA) approach in the Framingham Heart Study to identify (1) novel genetic variants for serum OC and (2) shared genetic determinants with directly pleiotropic effects on both serum OC and metabolic risk factors (including waist circumference, systolic blood pressure, fasting triglycerides, fasting HDL cholesterol, fasting plasma glucose, fasting plasma insulin, adiponectin concentrations and insulin resistance indices such as HOMA-IR and QUICKI). The state-of-the-art GWA analytical approaches will be used including the multipe-phenotyping GWA analysis using a recent developed Principle of Heritability method, weighted hypotheses based on prior information, and a newly developed structure modeling to infer the directly pleotropic effects. Bioinformatics approaches, such as pathway network analyses, gene- set enrichment test, and eSNP analyses will also be applied. We will use already collected phenotype data and available high-density 550K Affymetrix genotyping data. The proposed work will take advantage of the rich available data and large sample size of the Framingham Heart Study. This will be the first human study using GWA approach to attempt to translate the OC findings from animals, which will afford the opportunity to generate new hypotheses to understand the signaling pathways and underlying biological mechanisms behind the crosstalk, as it is not fully understood how this bone protein regulates glucose metabolism, insulin secretion and insulin sensitivity. Confirmation of these findings in humans could also have important implications for women who commonly suffer from the morbid and sometimes mortal complications of both osteoporosis and cardiovascular disease risk factor clustering, metabolic syndrome. PUBLIC HEALTH RELEVANCE: Recent animal studies have showed that osteocalcin, an important bone protein, involves in the endocrine regulation of energy metabolism. However, the underlying mechanisms for how osteocalcin interacting with adipocytes and pancreatic 2 cells are still unclear. Our study will be the first human study using state-of-the-art genome-wide association approaches to attempt to identify novel genetic variants shared by both osteocalcin and metabolic risk factors, which will provide valuable insight into potential molecular targets that will help further understanding the underlying mechanisms of communication between skeleton and energy metabolism.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
Bioinformatics Core
  • 批准号:
    10404414
  • 项目类别:
  • 资助金额:
    $9.07万
  • 财政年份:
    2023
  • 负责人:
    Yi-Hsiang Hsu
  • 依托单位:
Identifying Osteoporosis Genes by Whole Genome Sequencing and Functional Validation in Zebra Fish
Identifying Osteoporosis Genes by Whole Genome Sequencing and Functional Validation in Zebra Fish
Identifying Osteoporosis Genes by Whole Genome Sequencing and Functional Validation in Zebra Fish
海外基金