Institute of Human Nutrition and Food Science, Christian-Albrechts-Universität zu Kiel, Kiel , Germany.
Department of Neurology, Christian-Albrechts-Universität zu Kiel, Kiel , Germany.
J Appl Physiol (1985). 2018 Aug 1;125(2):320-327. doi: 10.1152/japplphysiol.00690.2017. Epub 2017 Sep 21.
Brain gray (GM) and white matter (WM) volumes are related to weight changes. The impact of structural variations in GM and WM on the variance in resting energy expenditure (REE) and the REE-on-fat-free mass (FFM) association is unknown. The aim of this study was to address this in healthy Caucasian subjects. Cross-sectional data analysis of 493 healthy Caucasian subjects (age range 6-80 years; 3 age groups) was conducted with comprehensive information on FFM, organ and tissue masses, and detailed brain composition as assessed by whole body magnetic resonance imaging and REE (assessed by indirect calorimetry). REE was calculated (REEc) using organ and tissue masses times their specific metabolic rates. FFM was the major determinant of REE (70.6%); individual masses of liver, total brain, and heart explained a further 2.1% of the variance in REE. Replacing total brain with GM and WM did not change the total R. Nevertheless, GM added more to the variance in REE (5.6%) and corresponding residuals (12.5%) than did total brain. Additionally, up to 12% was explained by age and sex (<2%). There was a systematic bias between REE and REEc with positive values in younger subjects but negative values in older ones. This bias remained after substituting the specific metabolic rate of brain with the specific metabolic rates of GM and WM. In healthy Caucasian subjects, GM and WM contributed to the variance in REE. Detailed brain structures do not explain the bias between REE and REEc. NEW & NOTEWORTHY Detailed brain composition (gray and white matter) contributed to the variances of resting energy expenditure (REE) and REE-on-fat-free mass residuals. Gray matter explained most of the variances, and for future studies on energy expenditure, brain compartments should be analyzed separately with regard to their different energy needs.
脑灰质(GM)和白质(WM)体积与体重变化有关。GM 和 WM 的结构变化对静息能量消耗(REE)的方差以及 REE 与去脂体重(FFM)的关联的影响尚不清楚。本研究旨在探讨这一问题在健康的白种人群体中。对 493 名健康白种人(年龄范围 6-80 岁;3 个年龄组)进行了横断面数据分析,这些人群的信息包括 FFM、器官和组织质量以及全身磁共振成像和 REE(间接热量法评估)评估的详细脑成分。REE 是使用器官和组织质量乘以其特定代谢率来计算的(REEc)。FFM 是 REE 的主要决定因素(70.6%);肝脏、总脑和心脏的个体质量进一步解释了 REE 方差的 2.1%。用 GM 和 WM 代替总脑并不能改变总 R。然而,GM 对 REE(5.6%)和相应残差(12.5%)的方差增加超过了总脑。此外,年龄和性别可解释高达 12%(<2%)。REE 与 REEc 之间存在系统偏差,年轻受试者的数值为正,而年长受试者的数值为负。在用 GM 和 WM 的特定代谢率代替脑的特定代谢率后,这种偏差仍然存在。在健康的白种人群体中,GM 和 WM 对 REE 的方差有贡献。详细的脑结构并不能解释 REE 和 REEc 之间的偏差。本研究的重要发现为,在健康的白种人群体中,GM 和 WM 对 REE 的方差有贡献。详细的脑结构并不能解释 REE 和 REEc 之间的偏差。对于未来的能量消耗研究,应根据其不同的能量需求,分别分析脑区。