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Adipose Metabolic Profiling for Obesity Drug Targeting

Adipose Metabolic Profiling for Obesity Drug Targeting
用于肥胖药物靶向的脂肪代谢分析
批准号:
6759565
负责人:
KYONGBUM LEE
金额:
$15.5万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2004
资助国家:
美国
项目状态:
已结题
起止时间:
2004-05-01 至 2006-04-30

项目摘要

项目成果

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中文摘要
翻译
描述(由申请人提供):本研究计划的长期目标是确定作用于WAT以减少体脂的肥胖药物的潜在靶点。在发达国家,尤其是美国,肥胖正日益成为主要的健康问题。流行病学数据指出,增加的体脂(白色脂肪组织,WAT)质量是肥胖的主要原因,肥胖是通过脂肪细胞大小和数量的增加而发生的。目前饮食疗法的效果大多是可逆的,只有不到10%的减肥者能够维持减肥效果。最近的证据描绘了脂肪组织内代谢调节的日益复杂的画面,其分泌调节脂肪细胞和全身能量代谢的自分泌、旁分泌和内分泌因子。鉴于这一情况,减少食物摄入或抑制消化脂肪吸收的一个有希望的替代方案是通过直接影响脂肪细胞代谢来减少WAT质量。认识到细胞代谢调控的复杂性,本研究采取了一种新颖的,面向系统的方法。为了解决基因和蛋白质表达谱研究留下的知识空白,该提案侧重于获得关于肥胖和非肥胖脂肪细胞生长的全面代谢信息。该项目的发展:1)开发用于肥胖和正常脂肪细胞生长的组织工程化模型系统,2)分析胞外代谢物浓度和胞内代谢通量的相关变化,和3)鉴定脂肪细胞生长的各个阶段(前脂肪细胞与成熟脂肪细胞)和/或类型(肥胖与正常)的区别性标志物特征。a)首先在静态培养物中,然后在生物反应器培养物中,比较肥胖(Ob 17)和非肥胖(3 T3-L1)脂肪细胞前体细胞的分化和生长。除其他外,将根据形态学、生化功能(包括胰岛素敏感性)和生长速率进行比较。微流体生物反应器实验将进行共培养中的Ob 17和3 T3-L1细胞的比较。B)产生代谢谱文库,其包括培养基中所有主要碳水化合物、氨基酸和脂质代谢物的浓度变化。主要分析方法将是液相色谱法,c)使用已建立的建模方法生成平行代谢通量库,d)对代谢物和通量库进行多变量判别分析,以鉴定每种生长条件的显著标志物。这些程序的预期结果是一个全面的代谢谱和标志物库,这些代谢谱和标志物捕获肥胖和正常脂肪生长的广泛和独特的特征。这一知识输出标志着在脂肪能量代谢的全球研究中,在功能水平上迈出了重要的第一步,并应作为进一步研究的必要信息平台,研究脂肪生长中的主要驱动反应作为肥胖药物靶点。
英文摘要
DESCRIPTION (provided by applicant): The long-term objective of this research program is to identify potential targets for obesity drugs that act on WAT to reduce body fat. Obesity is increasingly becoming a leading health problem in developed countries, especially the U.S. Epidemiological data point to increased body fat (white adipose tissue, WAT) mass as a chief contributor to obesity, which occurs both by increases in fat cell size and number. The effects of current dietary therapies are mostly reversible, and less than 10 % of those who lose weight are able to maintain the weight loss. Recent evidence paints an increasingly complex picture of metabolic regulation within the adipose tissue, which secretes autocrine, paracrine, and endocrine factors that regulate adipose cellular and whole body energy metabolism. In light of this picture, a promising alternative to reducing food intake or inhibiting digestive fat absorption is to reduce WAT mass by directly influencing adipose cellular metabolism. Recognizing the complexity of cellular metabolic regulation, this research takes a novel, systems oriented approach. Addressing the knowledge gap left by gene and protein expression profiling studies, this proposal focuses on obtaining comprehensive metabolic information on obese and non-obese adipose cellular growth. The project develops by: 1) developing tissue-engineered model systems for obese and normal adipose cellular growth, 2) profiling associated changes to extracellular metabolite concentrations and intracellular metabolic fluxes, and 3) identifying discriminatory markers characteristic of the various stages (pre- vs. mature adipocyte) and/or types (obese vs. normal) of adipose cellular growth. These specific aims will be achieved by performing the following tasks: a) Compare the differentiation and growth of obese (Ob17) and non-obese (3T3-L1) adipocyte precursor cells, first in static, then bioreactor cultures. Comparisons will be made, among others, on the basis of morphology, biochemical function (including insulin sensitivity), and growth rate. Micro-fluidic bioreactor experiments will perform comparisons of Ob17 and 3T3-L1 cells in co-culture, b) Generate metabolic profile libraries encompassing concentration changes for all major primary carbohydrate, amino acid, and lipid metabolites in culture media. The primary analytical method will be liquid chromatography, c) Generate parallel metabolic flux libraries using established modeling methodologies, d) Perform multivariate discriminant analysis on the metabolite and flux libraries to identify significant markers for each of the growth conditions. The expected outcome of these procedures is a comprehensive library of metabolic profiles and markers that capture both broad and unique features of obese and normal adipose growth. This knowledge output marks a significant first step, at the functional level, in the global study of adipose energy metabolism, and should serve as a necessary information platform for further studies that investigate major driving reactions in adipose growth as obesity drug targets.
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A Machine-Learning Based Software Widget for Resolving Metabolite Identities
  • 批准号:
    9223450
  • 项目类别:
  • 资助金额:
    $14.76万
  • 财政年份:
    2016
  • 负责人:
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  • 依托单位:
Computational Metabolomics of Gut Microbiota Metabolites
  • 批准号:
    8794445
  • 项目类别:
  • 资助金额:
    $21.32万
  • 财政年份:
    2014
  • 负责人:
    KYONGBUM LEE
  • 依托单位:
Computational Metabolomics of Gut Microbiota Metabolites
  • 批准号:
    8638680
  • 项目类别:
  • 资助金额:
    $19.1万
  • 财政年份:
    2014
  • 负责人:
    KYONGBUM LEE
  • 依托单位:
Engineering an in vitro model of adipose tissue formation and metabolism
  • 批准号:
    8038517
  • 项目类别:
  • 资助金额:
    $20.53万
  • 财政年份:
    2010
  • 负责人:
    KYONGBUM LEE
  • 依托单位:
海外基金