Effect of AMY1 copy number variation and various doses of starch intake on glucose homeostasis: data from a cross-sectional observational study and a crossover meal study

The global human gut microbiome: genes, lifestyles, and diet

A growing number of human gut microbiome studies consistently describe differences between human populations. Here, we review how factors related to host genetics, ethnicity, lifestyle, and geographic location help explain this variation. Studies from contrasting environmental scenarios point to diet and lifestyle as the most influential. The effect of human migration and displacement demonstrates how the microbiome adapts to newly adopted lifestyles and contributes to the profound biological and health consequences attributed to migration. This information strongly suggests against a universal scale for healthy or dysbiotic gut microbiomes, and prompts for additional microbiome population surveys, particularly from less industrialized nations. Considering these important differences will be critical for designing strategies to diagnose and restore dysbiosis in various human populations.

Prevotella abundance and salivary amylase gene copy number predict fat loss in response to wholegrain diets

Background

Salivary amylase (AMY1) gene copy number (CN) and Prevotella abundance in the gut are involved in carbohydrate digestion in the upper and lower gastrointestinal tract, respectively; and have been suggested as prognostic biomarkers for weight loss among overweight individuals consuming diets rich in fiber and wholegrains.

Objective

We hypothesized that Prevotella abundance would be linked to greater loss of body fat after wholegrain consumption among individuals with low AMY1 CN, but not in those with high AMY1 CN.

Methods

We reanalyzed data from two independent randomized ad libitum wholegrain interventions (fiber intake ∼33 g/d for 6–8 weeks), to investigate the relationship between baseline Prevotella abundance and body fat loss among healthy, overweight participants stratified into two groups by median AMY1 CN. Individuals with no detected Prevotella spp. were excluded from the main analysis.

Results

In both studies, individuals with low AMY1 CN exhibited a positive correlation between baseline Prevotella abundance and fat loss after consuming the wholegrain diet (r > 0.5, P < 0.05), but no correlation among participants with high AMY1 CN (P ≥ 0.6). Following consumption of the refined wheat control diets, there were no associations between baseline Prevotella abundance and changes in body fat in any of the AMY1 groups.

Conclusion

These results suggest that Prevotella abundance together with AMY1 CN can help predict fat loss in response to ad libitum wholegrain diets, highlighting the potential of these biomarkers in personalized obesity management.

Genetic and epigenetic nutritional interactions influencing obesity risk and adiposity outcomes

PURPOSE OF REVIEW

This article aims to critically overview the current interplay of genetic/epigenetic factors and several nutritional aspects influencing obesity susceptibility and adiposity outcomes for obesity management and weight status monitoring.

RECENT FINDINGS

Single nucleotide polymorphisms located in or near genes participating in energy homeostasis, fatty acid metabolism, appetite control, brain regulation, and thermogenesis have been associated with body composition measures (body weight, body mass index, waist circumference, body fat percentage, and visceral adipose tissue) depending on nutrient intakes, dietary patterns, and eating behaviors. Moreover, studies analyzing interactions between the epigenome and dietary intakes in relation to adiposity outcomes are reported. The main epigenetic mechanisms include methylation levels of promoter sequences, telomere length, and micro-ribonucleic acid expression profiles, whereas covalent histone modifications remain less studied.

SUMMARY

Exploring potential interactions between the genetic/epigenetic background and nutritional features is improving the current understanding of the obesity physiopathogenesis and the usefulness of translating this precision information in the clinical setting for weight gain prediction, the design of personalized nutrition therapies as well as individual responsiveness estimation to dietary advice. The analysis of further relationships between the genotype, the epigenotype and other precision markers including the gut microbiota and the metabolome is warranted.