The impact of oligofructose on stimulation of gut hormones, appetite regulation and adiposity

Objective: To investigate the effect of nutrient stimulation of gut hormones by oligofructose supplementation on appetite, energy intake (EI), body weight (BW) and adiposity in overweight and obese volunteers. Methods: In a parallel, single-blind and placebo-controlled study, 22 healthy overweight and obese volunteers were randomly allocated to receive 30 g day−1 oligofructose or cellulose for 6 weeks following a 2-week run-in. Subjective appetite and side effect scores, breath hydrogen, serum short chain fatty acids (SCFAs), plasma gut hormones, glucose and insulin concentrations, EI, BW and adiposity were quantified at baseline and post-supplementation. Results: Oligofructose increased breath hydrogen (P < 0.0001), late acetate concentrations (P = 0.024), tended to increase total area under the curve (tAUC)420mins peptide YY (PYY) (P = 0.056) and reduced tAUC450mins hunger (P = 0.034) and motivation to eat (P = 0.013) when compared with cellulose. However, there was no significant difference between the groups in other parameters although within group analyses showed an increase in glucagon-like peptide 1 (GLP-1) (P = 0.006) in the cellulose group and a decrease in EI during ad libitum meal in both groups. Conclusions: Oligofructose increased plasma PYY concentrations and suppressed appetite, while cellulose increased GLP-1 concentrations. EI decreased in both groups. However, these positive effects did not translate into changes in BW or adiposity.

Circulating pancreatic polypeptide concentrations predict visceral and liver fat content

CONTEXT AND OBJECTIVE: No current biomarker can reliably predict visceral and liver fat content, both of which are risk factors for cardiovascular disease. Vagal tone has been suggested to influence regional fat deposition. Pancreatic polypeptide (PP) is secreted from the endocrine pancreas under vagal control. We investigated the utility of PP in predicting visceral and liver fat. PATIENTS AND METHODS: Fasting plasma PP concentrations were measured in 104 overweight and obese subjects (46 men and 58 women). In the same subjects, total and regional adipose tissue, including total visceral adipose tissue (VAT) and total subcutaneous adipose tissue (TSAT), were measured using whole-body magnetic resonance imaging. Intrahepatocellular lipid content (IHCL) was quantified by proton magnetic resonance spectroscopy. RESULTS: Fasting plasma PP concentrations positively and significantly correlated with both VAT (r = 0.57, P < .001) and IHCL (r = 0.51, P < .001), but not with TSAT (r = 0.02, P = .88). Fasting PP concentrations independently predicted VAT after controlling for age and sex. Fasting PP concentrations independently predicted IHCL after controlling for age, sex, body mass index (BMI), waist-to-hip ratio, homeostatic model assessment 2-insulin resistance, (HOMA2-IR) and serum concentrations of triglyceride (TG), total cholesterol (TC), and alanine aminotransferase (ALT). Fasting PP concentrations were associated with serum ALT, TG, TC, low- and high-density lipoprotein cholesterol, and blood pressure (P < .05). These associations were mediated by IHCL and/or VAT. Fasting PP and HOMA2-IR were independently significantly associated with hepatic steatosis (P < .01). CONCLUSIONS: Pancreatic polypeptide is a novel predictor of visceral and liver fat content, and thus a potential biomarker for cardiovascular risk stratification and targeted treatment of patients with ectopic fat deposition.

Akkermansia muciniphila and improved metabolic health during a dietary intervention in obesity: relationship with gut microbiome richness and ecology

Objective: Individuals with obesity and type 2 diabetes differ from lean and healthy individuals in their abundance of certain gut microbial species and microbial gene richness. Abundance of Akkermansia muciniphila, a mucin-degrading bacterium, has been inversely associated with bodyfat mass and glucose intolerance in mice, but more evidence is needed in humans. The impact of diet and weight loss on this bacterial species is unknown. Our objective was to evaluate the association between fecal A. muciniphila abundance, fecal microbiome gene richness, diet, host characteristics, and their changes after calorie restriction (CR). Design: The intervention consisted of a 6-week CR period followed by a 6-week weight stabilization (WS) diet in overweight and obese adults (N=49, including 41 women). Fecal A. muciniphila abundance, fecal microbial gene richness, diet and bioclinical parameters were measured at baseline and after CR and WS. Results: At baseline A. muciniphila was inversely related to fasting glucose, waist-to-hip ratio, and subcutaneous adipocyte diameter. Subjects with higher gene richness and A. muciniphila abundance exhibited the healthiest metabolic status, particularly in fasting plasma glucose, plasma triglycerides and body fat distribution. Individuals with higher baseline A. muciniphila displayed greater improvement in insulin sensitivity markers and other clinical parameters after CR. A. muciniphila was associated with microbial species known to be related to health. Conclusion: A. muciniphila is associated with a healthier metabolic status and better clinicaloutcomes after CR in overweight/obese adults, however the interaction between gut microbiota ecology and A. muciniphila has to be taken into account.

Quantifying diet-induced metabolic changes of the human gut microbiome

The human gut microbiome is known to be associated with various human disorders, but a major challenge is to go beyond association studies and elucidate causalities. Mathematical modeling of the human gut microbiome at a genome scale is a useful tool to decipher microbe-microbe, diet-microbe and microbe-host interactions. Here, we describe the CASINO (Community And Systems-level INteractive Optimization) toolbox, a comprehensive computational platform for analysis of microbial communities through metabolic modeling. We first validated the toolbox by simulating and testing the performance of single bacteria and whole communities in vitro. Focusing on metabolic interactions between the diet, gut microbiota, and host metabolism, we demonstrated the predictive power of the toolbox in a diet-intervention study of 45 obese and overweight individuals and validated our predictions by fecal and blood metabolomics data. Thus, modeling could quantitatively describe altered fecal and serum amino acid levels in response to diet intervention.