PLEIOTROPIC EFFECTS ON OBESITY AND LIPOPROTEINS

这个子项目是许多研究子项目中的一个 由NIH/NCRR资助的中心赠款提供的资源。子项目和 研究者（PI）可能从另一个NIH来源获得了主要资金， 因此可以在其他CRISP条目中表示。所列机构为 研究中心，而研究中心不一定是研究者所在的机构。 这是灵长类动物动脉粥样硬化的饮食和基因型研究计划的第三个项目。" 该项目的总体目标是绘制、表征和鉴定多态性基因，这些基因有助于肥胖易感性的变化及其与心血管疾病（CVD）的关系。 本项目在当前和以前的资助期间的研究已经导致了许多数量性状基因座（QTL）的染色体定位，这些基因座有助于狒狒肥胖的风险。 目前提出的工作的主要目标是鉴定和表征特定基因，这些基因是先前鉴定的QTL的基础，并且与反映脂肪组织积累或功能的肥胖相关表型的变异相关。其次，我们将研究长期暴露于高胆固醇高脂肪（HCHF）饮食对重要的肥胖相关蛋白表达水平的影响，这些蛋白被认为在介导胰岛素抵抗中发挥作用，并最终增加动脉粥样硬化的发展风险。 最后，我们将试图加强以前检测到的肥胖相关的QTL，并发现新的QTL，包括额外的协变量和调查各种相互作用模型。

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.