PLEIOTROPIC EFFECTS ON OBESITY AND LIPOPROTEINS

这个子项目是许多研究子项目中利用 资源由NIH/NCRR资助的中心拨款提供。子项目和 调查员(PI)可能从NIH的另一个来源获得了主要资金， 并因此可以在其他清晰的条目中表示。列出的机构是 该中心不一定是调查人员的机构。 这是项目项目“灵长类动脉粥样硬化中的饮食和基因类型”的项目3。 该项目的总体目标是定位、表征和识别导致肥胖易感性变异的多态基因及其与心血管疾病(CVD)的关系。在当前和之前的赠款期间，这一项目的研究导致了许多数量性状基因座(QTL)的染色体定位，这些QTL导致了狒狒肥胖的风险。目前提出的工作的主要目标是识别和表征特定的基因(S)，这些基因低于先前识别的QTL，并且与反映脂肪组织积累或功能的肥胖相关表型的变化有关。其次，我们将研究长期暴露在高胆固醇高脂肪(HCHF)饮食中对肥胖相关重要蛋白表达水平的影响，这些蛋白被认为在调节胰岛素抵抗方面发挥作用，并最终增加发生动脉粥样硬化的风险。最后，我们将试图加强先前检测到的与肥胖相关的QTL，并通过包括更多的协变量和调查各种交互作用模型来发现新的QTL。

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. This is Project 3 of Program Project "Diet and Genotype in Primate Atherosclerosis." The overarching objective of this project is to map, characterize and identify polymorphic genes that contribute to variation in susceptibility to obesity and their relationship to cardiovascular disease (CVD). Research in this project during the current and previous grant periods has led to the chromosomal localization of numerous quantitative trait loci (QTLs) contributing to the risk for obesity in baboons. The primary goal of the currently proposed work is the identification and characterization of specific gene(s) that underly QTLs previously identified, and that are associated with variation in obesity-related phenotypes reflecting adipose tissue accumulation or function. Secondly, we will examine the effects of chronic exposure to a high cholesterol high fat (HCHF) diet on the expression levels of important obesity-related proteins that are thought to play a role in mediating insulin resistance, and ultimately to increased risk for the development of atherosclerosis. Finally, we will attempt to strengthen previously detected obesity-related QTLs and to discover new QTLs by including additional covariates and by investigating a variety of interaction models.