Effect of 6-month caloric restriction on Cu bound to ceruloplasmin in adult overweight subjects

Abstract

In a randomized clinical trial of calorie restriction (CR), we demonstrated that important cardiovascular disease (CVD) biomarkers were favorably influenced by CR alone and in conjunction with physical exercise. The aim of this study was to examine the effects of CR with or without exercise on copper bound to ceruloplasmin (CuCp), a well-known biomarker for CVD, in overweight men and women enrolled in the CALERIE phase 1 study. Forty-six individuals were randomized to one of four groups for 6 months: control, healthy weight maintenance; CR, 25% CR from baseline energy requirements; CR+exercise, 12.5% CR and 12.5% through aerobic exercise; and low-calorie diet, low-calorie diet until 15% reduction in body weight followed by weight maintenance diet. CuCp was determined in fasting blood samples by a high-performance liquid chromatography-inductively coupled plasma mass spectrometry methodology and compared with changes in body composition and markers of CVD. After 6 months, CR combined with exercise induced a decrease in plasma concentration of CuCp. CuCp was inversely correlated with insulin sensitivity at baseline and after 6 months of intervention. A cluster analysis showed that the percent change of weight after 6 months of intervention was the most important variable that could discriminate the intervention groups. The percent change of CuCp was the only other variable selected by the analysis. Decreased CuCp in overweight subjects by CR combined with exercise suggests a positive effect of this intervention on metabolic health. Further studies to explain the relationship between weight loss and CuCp and its relevance for cardiovascular health are needed.

Keywords: Caloric restriction (CR); Cardiovascular disease (CVD); Copper bound to ceruloplasmin (CuCp); Insulin sensitivity (Si); Physical exercise (EX).

Figure 1

Classification tree by CHAID algorithm of the 4 experimental groups (CTRL= control group, CR = calorie restriction group, CR+EX = calorie restriction plus exercise group, LCD = low calorie diet group). To establish the best variable which percent change can be used to characterize the interventions, a decision tree analysis was performed by “Chi-squared Automatic Interaction Detector” (CHAID) algorithm. The variables considered in the decision tree analysis included sex, and the changes (% at M6) of CuCp, Weight; BMI; FM, FFM, and percent fat (from DXA); insulin sensitivity (Si) from IVGTT; TATMass, VATMass and SATmass (from CT) and, Chol, LDL, HDL, Trig (from fasting blood samples). To determine the best split at any node the CHAID algorithm choose the predictor variable with the smallest adjusted p-value, i.e., the predictor variable that will yield the most significant split. In growing the tree it was used the following stopping rules: minimum terminal parental node size of 10 cases, minimum terminal child nodes size of 5 cases and alpha = 0.05 for splitting nodes. The convergence criteria for the CHAID were: Epsilon = 0.001 and 100 as the maximum number of iterations before stopping the process.