Protein Intake, Metabolic Status and the Gut Microbiota in Different Ethnicities: Results from Two Independent Cohorts

Association between total, animal, and plant protein intake and type 2 diabetes risk in adults: A systematic review and dose-response meta-analysis of prospective cohort studies

BACKGROUND AND AIMS

While clinical studies indicate that dietary protein may benefit glucose homeostasis in type 2 diabetes (T2D), the impact of dietary protein, including whether the protein is of animal or plant origin, on the risk of T2D is uncertain. We conducted a systematic review and meta-analysis to evaluate the associations of total, animal, and plant protein intakes with the risk of T2D.

METHODS

A systematic search was performed using multiple data sources, including PubMed/Medline, ISI Web of Science, Scopus, and Google Scholar, with the data cut-off in May 2023. Our selection criteria focused on prospective cohort studies that reported risk estimates for the association between protein intake and T2D risk. For data synthesis, we calculated summary relative risks and 95% confidence intervals for the highest versus lowest categories of protein intake using random-effects models. Furthermore, we conducted both linear and non-linear dose-response analyses to assess the dose-response associations between protein intake and T2D risk.

RESULTS

Sixteen prospective cohort studies, involving 615,125 participants and 52,342 T2D cases, were identified, of which eleven studies reported data on intake of both animal and plant protein. Intakes of total (pooled effect size: 1.14, 95% CI: 1.04-1.24) and animal (pooled effect size: 1.18, 95% CI: 1.09-1.27) protein were associated with an increased risk of T2D. These effects were dose-related - each 20-g increase in total or animal protein intake increased the risk of T2D by ∼3% and ∼7%, respectively. In contrast, there was no association between intake of plant protein and T2D risk (pooled effect size: 0.98, 95% CI: 0.89-1.08), while replacing animal with plant protein intake (per each 20 g) was associated with a reduced risk of T2D (pooled effect size: 0.80, 95% CI: 0.76-0.84).

CONCLUSIONS

Our findings indicate that long-term consumption of animal, but not plant, protein is associated with a significant and dose-dependent increase in the risk of T2D, with the implication that replacement of animal with plant protein intake may lower the risk of T2D.

Cross-sectional analyses of metabolites across biological samples mediating dietary acid load and chronic kidney disease

Chronic kidney disease (CKD) is a major public health burden, with dietary acid load (DAL) and gut microbiota playing crucial roles. As DAL can affect the host metabolome, potentially via the gut microbiota, we cross-sectionally investigated the interplay between DAL, host metabolome, gut microbiota, and early-stage CKD (TwinsUK, n = 1,453). DAL was positively associated with CKD stage G1-G2 (Beta (95% confidence interval) = 0.34 (0.007; 0.7), p = 0.046). After adjusting for covariates and multiple testing, we identified 15 serum, 14 urine, 8 stool, and 7 saliva metabolites, primarily lipids and amino acids, associated with both DAL and CKD progression. Of these, 8 serum, 2 urine, and one stool metabolites were found to mediate the DAL-CKD association. Furthermore, the stool metabolite 5-methylhexanoate (i7:0) correlated with 26 gut microbial species. Our findings emphasize the gut microbiota's therapeutic potential in countering DAL's impact on CKD through the host metabolome. Interventional and longitudinal studies are needed to establish causality.

Protein supplementation changes gut microbial diversity and derived metabolites in subjects with type 2 diabetes

High-protein diets are promoted for individuals with type 2 diabetes (T2D). However, effects of dietary protein interventions on (gut-derived) metabolites in T2D remains understudied. We therefore performed a multi-center, randomized-controlled, isocaloric protein intervention with 151 participants following either 12-week high-protein (HP; 30Energy %, N = 78) vs. low-protein (LP; 10 Energy%, N = 73) diet. Primary objectives were dietary effects on glycemic control which were determined via glycemic excursions, continuous glucose monitors and HbA1c. Secondary objectives were impact of diet on gut microbiota composition and -derived metabolites which were determined by shotgun-metagenomics and mass spectrometry. Analyses were performed using delta changes adjusting for center, baseline, and kidney function when appropriate. This study found that a short-term 12-week isocaloric protein modulation does not affect glycemic parameters or weight in metformin-treated T2D. However, the HP diet slightly worsened kidney function, increased alpha-diversity, and production of potentially harmful microbiota-dependent metabolites, which may affect host metabolism upon prolonged exposure.

Informatics for your Gut: at the Interface of Nutrition, the Microbiome, and Technology

BACKGROUND

A significant portion of individuals in the United States and worldwide experience diseases related to or driven by diet. As research surrounding user-centered design and the microbiome grows, movement of the spectrum of translational science from bench to bedside for improvement of human health through nutrition becomes more accessible. In this literature survey, we examined recent literature examining informatics research at the interface of nutrition and the microbiome.

OBJECTIVES

The objective of this survey was to synthesize recent literature describing how technology is being applied to understand health at the interface of nutrition and the microbiome focusing on the perspective of the consumer.

METHODS

A survey of the literature published between January 1, 2021 and October 10, 2022 was performed using the PubMed database and resulting literature was evaluated against inclusion and exclusion criteria.

RESULTS

A total of 139 papers were retrieved and evaluated against inclusion and exclusion criteria. After evaluation, 45 papers were reviewed in depth revealing four major themes: (1) microbiome and diet, (2) usability,(3) reproducibility and rigor, and (4) precision medicine and precision nutrition.

CONCLUSIONS

A review of the relationships between current literature on technology, nutrition and the microbiome, and self-management of dietary patterns was performed. Major themes that emerged from this survey revealed exciting new horizons for consumer management of diet and disease, as well as progress towards elucidating the relationship between diet, the microbiome, and health outcomes. The survey revealed continuing interest in the study of diet-related disease and the microbiome and acknowledgement of needs for data re-use, sharing, and unbiased and rigorous measurement of the microbiome. The literature also showed trends toward enhancing the usability of digital interventions to support consumer health and home management, and consensus building around how precision medicine and precision nutrition may be applied in the future to improve human health outcomes and prevent diet-related disease.

Impacts of Dietary Protein and Niacin Deficiency on Reproduction Performance, Body Growth, and Gut Microbiota of Female Hamsters (Tscherskia triton) and Their Offspring

Food resources are vital for animals to survive, and gut microbiota play an essential role in transferring nutritional materials into functional metabolites for hosts. Although the fact that diet affects host microbiota is well known, its impacts on offspring remain unclear. In this study, we assessed the effects of low-protein and niacin-deficient diets on reproduction performance, body growth, and gut microbiota of greater long-tailed hamsters (Tscherskia triton) under laboratory conditions. We found that maternal low-protein diet (not niacin deficiency) had a significant negative effect on reproduction performance of female hamsters (longer mating latency with males and smaller litter size) and body growth (lower body weight) of both female hamsters and their offspring. Both protein- and niacin-deficient diets showed significant maternal effects on the microbial community in the offspring. A maternal low-protein diet (not niacin deficiency) significantly reduced the abundance of major bacterial taxa producing short-chain fatty acids, increased the abundance of probiotic taxa, and altered microbial function in the offspring. The negative effects of maternal nutritional deficiency on gut microbiota are more pronounced in the protein group than the niacin group and in offspring more than in female hamsters. Our results suggest that a low-protein diet could alter gut microbiota in animals, which may result in negative impacts on their fitness. It is necessary to conduct further analysis to reveal the roles of nutrition, as well as its interaction with gut microbes, in affecting fitness of greater long-tailed hamsters under field conditions. IMPORTANCE Gut microbes are known to be essential for hosts to digest food and absorb nutrients. Currently, it is still unclear how maternal nutrient deficiency affects the fitness of animals by its effect on gut microbes. Here, we evaluated the effects of protein- and niacin-deficient diets on mating behavior, reproduction, body growth, and gut microbiota of both mothers and offspring of the greater long-tailed hamster (Tscherskia triton) under laboratory conditions. We found that a low-protein diet significantly reduced maternal reproduction performance and body growth of both mothers and their offspring. Both protein and niacin deficiencies showed significant maternal effects on the microbial community of the offspring. Our results hint that nutritional deficiency may be a potential factor in causing the observed sustained population decline of the greater long-tailed hamsters due to intensified monoculture in the North China Plain, and this needs further field investigation.

Gut Microbiota in Nutrition and Health with a Special Focus on Specific Bacterial Clusters

Health is influenced by how the gut microbiome develops as a result of external and internal factors, such as nutrition, the environment, medication use, age, sex, and genetics. Alpha and beta diversity metrics and (enterotype) clustering methods are commonly employed to perform population studies and to analyse the effects of various treatments, yet, with the continuous development of (new) sequencing technologies, and as various omics fields as a result become more accessible for investigation, increasingly sophisticated methodologies are needed and indeed being developed in order to disentangle the complex ways in which the gut microbiome and health are intertwined. Diseases of affluence, such as type 2 diabetes (T2D) and cardiovascular diseases (CVD), are commonly linked to species associated with the Bacteroides enterotype(s) and a decline of various (beneficial) complex microbial trophic networks, which are in turn linked to the aforementioned factors. In this review, we (1) explore the effects that some of the most common internal and external factors have on the gut microbiome composition and how these in turn relate to T2D and CVD, and (2) discuss research opportunities enabled by and the limitations of some of the latest technical developments in the microbiome sector, including the use of artificial intelligence (AI), strain tracking, and peak to trough ratios.

Characterization of the Gut Microbiota in Individuals with Overweight or Obesity during a Real-World Weight Loss Dietary Program: A Focus on the Bacteroides 2 Enterotype

Background: Dietary intervention is a cornerstone of weight loss therapies. In obesity, a dysbiotic gut microbiota (GM) is characterized by high levels of Bacteroides lineages and low diversity. We examined the GM composition changes, including the Bacteroides 2 enterotype (Bact2), in a real-world weight loss study in subjects following a high-protein hypocaloric diet with or without a live microorganisms (LMP) supplement. Method: 263 volunteers were part of this real-world weight loss program. The first phase was a high-protein low-carbohydrate calorie restriction diet with or without LMP supplements. Fecal samples were obtained at baseline and after 10% weight loss for 163 subjects. Metagenomic profiling was obtained by shotgun sequencing. Results: At baseline, the Bact2 enterotype was more prevalent in subjects with aggravated obesity and metabolic alterations. After weight loss, diversity increased and Bact2 prevalence decreased in subjects with lower GM diversity at baseline, notably in LMP consumers. Significant increases in Akkermansia muciniphila and Parabacteroides distasonis and significant decreases of Eubacterium rectale, Streptococcus thermophilus and Bifidobacterial lineages were observed after weight loss. Conclusions: Baseline microbiome composition is associated with differential changes in GM diversity and Bact2 enterotype prevalence after weight loss. Examining these signatures could drive future personalized nutrition efforts towards more favorable microbiome compositions.

Physical Activity and Dietary Composition Relate to Differences in Gut Microbial Patterns in a Multi-Ethnic Cohort-The HELIUS Study

Physical activity (PA) at recommended levels contributes to the prevention of non-communicable diseases, such as atherosclerotic cardiovascular disease (asCVD) and type 2 diabetes mellitus (T2DM). Since the composition of the gut microbiota is strongly intertwined with dietary intake, the specific effect of exercise on the gut microbiota is not known. Moreover, multiple other factors, such as ethnicity, influence the composition of the gut microbiota, and this may be derived by distinct diet as well as PA patterns. Here we aim to untangle the associations between PA and the gut microbiota in a sample (n = 1334) from the Healthy Life In an Urban Setting (HELIUS) multi-ethnic cohort. The associations of different food groups and gut microbiota were also analyzed. PA was monitored using subjective (n = 1309) and objective (n = 162) methods, and dietary intake was assessed with ethnic-specific food frequency questionnaire (FFQ). The gut microbiota was profiled using 16S rRNA gene amplicon sequencing, and the functional composition was generated with the Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt2). Associations were assessed using multivariable and machine learning models. In this cohort, a distinct gut microbiota composition was associated with meeting the Dutch PA norm as well as with dietary intake, e.g., grains. PA related parameters such as muscle strength and calf circumference correlated with gut microbiota diversity. Furthermore, gut microbial functionality differed between active and sedentary groups. Differential representation of ethnicities in active and sedentary groups in both monitor methods hampered the detection of ethnic-specific effects. In conclusion, both PA and dietary intake were associated with gut microbiota composition in our multi-ethnic cohort. Future studies should further elucidate the role of ethnicity and diet in this association.