Exploring Specific Metabolic Rates of Major Cell Categories in Adiposity-Diverse

探索肥胖多样性中主要细胞类别的特定代谢率

• 批准号: 7715202
• 负责人: ZIMIAN WANG
• 金额: $ 24.15万
• 依托单位: ST. LUKE'S-ROOSEVELT INST FOR HLTH SCIS
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-07-18 至 2011-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7715202
• 关键词: Address; Adipocytes; Adipose tissue; Adult; Age; Basal metabolic rate; Body Composition; Body measure procedure; Brain; Categories; Cells; Cellularity; Consumption; Data; Data Set; Databases; Dual-Energy X-Ray Absorptiometry; Elderly; Energy Metabolism; Fatty acid glycerol esters; Germany; Goals; Health; Heart; Indirect Calorimetry; Individual; Investigation; Kidney; Knowledge; Left; Linear Regressions; Liver; Magnetic Resonance Imaging; Measures; Metabolic; Methods; Modeling; Molecular; Muscle Fibers; Obesity; Organ; Outcome Study; Potassium; Publishing; Regression Analysis; Residual state; Rest; Sampling; Skeletal Muscle; Subgroup; Testing; Tissues; Underweight; Validation; Weight; Whole-Body Counting; Woman; Work; abstracting; base; experience; improved; in vivo; insight; kidney cell; men; neuronal cell body; public health relevance; quantum; soft tissue; tau Proteins

DESCRIPTION (provided by applicant): Exploring Specific Metabolic Rates of Major Cell Categories in Adiposity-Diverse Adults ABSTRACT Obesity is a significant health problem in the USA. Previous studies observed that obese adults have greater resting energy expenditure (REE), the largest fraction of total energy consumption. Major efforts have been made for predicting REE at the whole-body level (i.e., body mass, BM), molecular level (i.e., fat-free mass, FFM) and organ-tissue level (i.e., major organs/tissues). However, the published REE prediction formulae from normal-weight adults were not valid in obese adults, representing a knowledge gap in energy metabolism investigation. The proposed study aims to deeply understand the REE-body composition relationship at the cellular level. As REE is the collective energy required by all body cells to maintain post-absorptive homeostatic function in the resting condition, we will establish a cellular level REE prediction approach. The new mechanistic model is based on the masses of individual cell categories (Ci) and their specific resting metabolic rates (Ji): REE = #(Ji W Ci). Although various cell categories may have quite different levels of energy consumption, the Ji values have never been quantified in vivo. We will address the Ji values by using multiple linear regression analysis with REE as the dependent variable, and Ci as the independent variables. The REE is measured by indirect calorimetry, and the Ci is quantified from organ/tissue mass by magnetic resonance imaging (MRI), with cellularity measured from body cell mass and lean-soft tissues by whole-body counting and DXA, respectively. The major cell categories include skeletal muscle cells, adipocytes, and organ cells (i.e., liver, brain, heart and kidney cells). In order to predict the Ji values of the six cell categories, this secondary analyses study will combine existing data from two centers in the USA and Germany, and assemble the largest-to-date REE-MRI organ/tissue database (n = 434) with men and women varying in adiposity (BMI 14.4-39.1 kg/m2) and age (18-88 yrs). Our hypothesis is that the derived cellular level approach can accurately predict REE in adiposity- and age-diverse adults. Accordingly, the derived cellular level REE model may fully explain the well-known observation that obese adults have a higher absolute REE, but lower REE/BM and REE/FFM ratios than do normal-weight adults. This study thereby will contribute to our understanding of the inherent relations between REE and body composition and will provide new insights into the energy requirement of obese adults. PUBLIC HEALTH RELEVANCE: Resting energy expenditure (REE) is the largest fraction (65-75%) of total energy consumption. It is known that various cell categories may have quite different levels of energy consumption. However, the specific resting metabolic rates of individual cell categories have never been studied quantitatively. The proposed study aims to establish a new REE prediction model at the cellular level. The potential outcome of this study can be expected to improve our understanding of the inherent relations between REE and cellular level body composition and establishing energy requirement of obese adults.

描述（由申请人提供）：探索肥胖不同成人主要细胞类别的特定代谢率摘要肥胖是美国一个重要的健康问题。先前的研究发现，肥胖的成年人有更多的静息能量消耗（REE），这是总能量消耗的最大比例。在整体水平（即体重，BM）、分子水平（即无脂质量，FFM）和器官组织水平（即主要器官/组织）预测稀土元素方面已经做出了重大努力。然而，已发表的正常体重成年人的REE预测公式对肥胖成年人无效，这代表了能量代谢研究的知识差距。本研究旨在深入了解细胞水平上REE-body composition的关系。由于REE是所有身体细胞在静息状态下维持吸收后稳态功能所需的集体能量，我们将建立细胞水平的REE预测方法。新的机制模型是基于单个细胞种类的质量（Ci）和它们的特定静息代谢率（Ji）： REE = #（Ji W Ci）。虽然不同类型的细胞可能有相当不同的能量消耗水平，但Ji值从未在体内被量化。我们将使用多元线性回归分析，以REE为因变量，Ci为自变量来解决Ji值。REE通过间接量热法测量，Ci通过磁共振成像（MRI）从器官/组织质量中量化，细胞质量分别通过全身计数和DXA从身体细胞质量和瘦软组织中测量。主要的细胞种类包括骨骼肌细胞、脂肪细胞和器官细胞（即肝、脑、心和肾细胞）。为了预测六种细胞类别的Ji值，这项二级分析研究将结合美国和德国两个中心的现有数据，并汇集迄今为止最大的REE-MRI器官/组织数据库（n = 434），其中男性和女性的肥胖程度（BMI 14.4-39.1 kg/m2）和年龄（18-88岁）不同。我们的假设是，衍生细胞水平的方法可以准确地预测肥胖和年龄不同的成年人的REE。因此，导出的细胞水平REE模型可以充分解释众所周知的观察结果，即肥胖成年人的绝对REE较高，但REE/BM和REE/FFM比正常体重的成年人低。因此，这项研究将有助于我们了解REE与身体成分之间的内在关系，并将为肥胖成年人的能量需求提供新的见解。公共卫生相关性：静息能量消耗（REE）是总能量消耗的最大部分（65-75%）。众所周知，不同类型的细胞可能有相当不同的能量消耗水平。然而，个别细胞类别的特定静息代谢率从未被定量研究过。本研究旨在建立一个新的细胞水平REE预测模型。本研究的潜在结果有望提高我们对REE与细胞水平体成分之间的内在关系的理解，并建立肥胖成人的能量需求。