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.
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.
