Is There a Contribution of Structural Brain Phenotypes to the Variance in Resting Energy Expenditure before and after Weight Loss in Overweight Females?

Abstract

Brain gray (GM) and white matter (WM) are associated with resting energy expenditure (REE). The impact of weight loss on GM and WM masses, as well as on their associations with REE and the ratio between body and brain metabolism, i.e., encephalic measure (EM)), are unknown. Longitudinal data of 69 female Caucasian subjects (age range 19–69 years) with detailed information on fat mass (FM), fat free mas (FFM), GM, WM and REE. Mean weight loss was 14.5 ± 11.9 kg with changes in FM (−12.9 ± 9.8 kg), FFM (−1.7 ± 4.8 kg) and REE (−159 ± 191 kcal/24 h) (all p < 0.05). With weight loss, there were no changes in GM and WM. Before and after weight loss, FFM was the main determinant of REE (r2 = 0.483 and 0.413; p < 0.05). After weight loss, GM added to the variances in REE (3.6%), REEadjFFM (6.1%) and the REE on FFM residuals (6.6%). In addition, before and after weight loss GM explained 25.0% and 10.0% of the variances in EM (p < 0.05). Weight loss had no effect on volumes of GM and WM. After weight loss, both, GM added to the variances of REE, REE on FFM residuals and EM.

Advances in body composition: a 100-year journey

“…An important advance over recent decades is that body composition measurements can now be extended far past assessments of whole component volume and mass to chemical and cellular compositions. Examples include brown adipose tissue within the total body adipose tissue component [19], intermuscular adipose tissue and intramyocellular lipids within skeletal muscles [20,21], intrahepatic lipid in liver [22], white and gray matter in the brain [23], muscle microarchitecture [24], and vast numbers of metabolites [21]. These kinds of capabilities extend traditional body composition analysis to estimation of an organ or tissues "quality" in vivo.…”