Contribution of structural brain phenotypes to the variance in resting energy expenditure in healthy Caucasian subjects

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 PPM, 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-2. 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.