Evaluation of the metabotype concept after intervention with oral glucose tolerance test and dietary fiber-enriched food: An enable study

Differential association of dietary scores with the risk of type 2 diabetes by metabotype

PURPOSE

We aimed to examine the association between dietary patterns and type 2 diabetes mellitus (T2DM) while considering the potential effect modification by metabolic phenotypes (metabotypes). Additionally, we aimed to explore the association between dietary scores and prediabetes.

METHODS

A total of 1460 participants (11.8% with T2DM) from the cross-sectional population-based KORA FF4 study were included. Participants, classified into three metabotype subgroups, had both their FSAm-NPS dietary index (underpinning the Nutri-Score) and ultra-processed foods (UPF) intake (using NOVA classification) calculated. Glucose tolerance status was assessed via oral glucose tolerance tests (OGTT) in non-diabetic participants and was classified according to the American Diabetes Association criteria. Logistic regression models were used for both the overall and metabotype-stratified analyses of dietary scores' association with T2DM, and multinomial probit models for their association with prediabetes.

RESULTS

Participants who had a diet with a higher FSAm-NPS dietary index (i.e., a lower diet quality) or a greater percentage of UPF consumption showed a positive association with T2DM. Stratified analyses demonstrated a strengthened association between UPF consumption and T2DM specifically in the metabolically most unfavorable metabotype (Odds Ratio, OR 1.92; 95% Confidence Interval, CI 1.35, 2.73). A diet with a higher FSAm-NPS dietary index was also positively associated with prediabetes (OR 1.19; 95% CI 1.04, 1.35).

CONCLUSION

Our study suggests different associations between poorer diet quality and T2DM across individuals exhibiting diverse metabotypes, pointing to the option for stratified dietary interventions in diabetes prevention.

Inoculation of Newborn Lambs with Ruminal Solids Derived from Adult Goats Reprograms the Development of Gut Microbiota and Serum Metabolome and Favors Growth Performance

Microbial transplantation in early life was a strategy to optimize the health and performance of livestock animals. This study aimed to investigate the effect of active ruminal solids microorganism supplementation on newborn lamb gut microbiota and serum metabolism. Twenty-four Youzhou dark newborn lambs were randomly divided into three groups: (1) newborn lambs fed with sterilized goat milk inoculated with sterilized normal saline (CON), supernatant from ruminal solids (SRS), or autoclaved supernatant from ruminal solids (ASRS). Results showed that SRS increased gut bacterial richness and community, downregulating the Firmicutes/Bacteroidetes ratio, and increased the abundance of some probiotics (Bacteroidetes, Spirochaetota, and Fibrobacterota), while reducing the abundance of Fusobacteriota, compared to the CON group. SRS also improved the plasma metabolic function, such as arachidonic acid metabolism, primary bile acid biosynthesis, and tryptophan metabolism and then actively promoted the levels of ALP and HLD. Our study indicated that inoculation with active ruminal solids significantly affected the intestinal microbial communities and metabolic characteristics, and these changes can improve the growing health of the newborn lamb. These findings provided an experimental and theoretical basis for the application of ruminal solid-attached microorganisms in the nutritional management of lambs reared for human consumption.

Distinct patterns of personalised dietary advice delivered by a metabotype framework similarly improve dietary quality and metabolic health parameters: secondary analysis of a randomised controlled trial

Background

In a 12-week randomised controlled trial, personalised nutrition delivered using a metabotype framework improved dietary intake, metabolic health parameters and the metabolomic profile compared to population-level dietary advice. The objective of the present work was to investigate the patterns of dietary advice delivered during the intervention and the alterations in dietary intake and metabolic and metabolomic profiles to obtain further insights into the effectiveness of the metabotype framework.

Methods

Forty-nine individuals were randomised into the intervention group and subsequently classified into metabotypes using four biomarkers (triacylglycerol, HDL-C, total cholesterol, glucose). These individuals received personalised dietary advice from decision tree algorithms containing metabotypes and individual characteristics. In a secondary analysis of the data, patterns of dietary advice were identified by clustering individuals according to the dietary messages received and clusters were compared for changes in dietary intake and metabolic health parameters. Correlations between changes in blood clinical chemistry and changes in metabolite levels were investigated.

Results

Two clusters of individuals with distinct patterns of dietary advice were identified. Cluster 1 had the highest percentage of messages delivered to increase the intake of beans and pulses and milk and dairy products. Cluster 2 had the highest percentage of messages delivered to limit the intake of foods high in added sugar, high-fat foods and alcohol. Following the intervention, both patterns improved dietary quality assessed by the Alternate Mediterranean Diet Score and the Alternative Healthy Eating Index, nutrient intakes, blood pressure, triacylglycerol and LDL-C (p ≤ 0.05). Several correlations were identified between changes in total cholesterol, LDL-C, triacylglycerol, insulin and HOMA-IR and changes in metabolites levels, including mostly lipids (sphingomyelins, lysophosphatidylcholines, glycerophosphocholines and fatty acid carnitines).

Conclusion

The findings indicate that the metabotype framework effectively personalises and delivers dietary advice to improve dietary quality and metabolic health.

Clinical trial registration

isrctn.com, identifier ISRCTN15305840.

Berberine regulates glucose metabolism in largemouth bass by modulating intestinal microbiota

This study examined the role of intestinal microbiota in berberine (BBR)-mediated glucose (GLU) metabolism regulation in largemouth bass. Four groups of largemouth bass (133.7 ± 1.43 g) were fed with control diet, BBR (1 g/kg feed) supplemented diet, antibiotic (ATB, 0.9 g/kg feed) supplemented diet and BBR + ATB (1g/kg feed +0.9 g/kg feed) supplemented diet for 50 days. BBR improved growth, decreased the hepatosomatic and visceral weight indices, significantly downregulated the serum total cholesterol and GLU levels, and significantly upregulated the serum total bile acid (TBA) levels. The hepatic hexokinase, pyruvate kinase, GLU-6-phosphatase and glutamic oxalacetic transaminase activities in the largemouth bass were significantly upregulated when compared with those in the control group. The ATB group exhibited significantly decreased final bodyweight, weight gain, specific growth rates and serum TBA levels, and significantly increased hepatosomatic and viscera weight indices, hepatic phosphoenolpyruvate carboxykinase, phosphofructokinase, and pyruvate carboxylase activities, and serum GLU levels. Meanwhile, the BBR + ATB group exhibited significantly decreased final weight, weight gain and specific growth rates, and TBA levels and significantly increased hepatosomatic and viscera weight indices and GLU levels. High-throughput sequencing revealed that compared with those in the control group, the Chao one index and Bacteroidota contents were significantly upregulated and the Firmicutes contents were downregulated in the BBR group. Additionally, the Shannon and Simpson indices and Bacteroidota levels were significantly downregulated, whereas the Firmicutes levels were significantly upregulated in ATB and BBR + ATB groups. The results of in-vitro culture of intestinal microbiota revealed that BBR significantly increased the number of culturable bacteria. The characteristic bacterium in the BBR group was Enterobacter cloacae. Biochemical identification analysis revealed that E. cloacae metabolizes carbohydrates. The size and degree of vacuolation of the hepatocytes in the control, ATB, and ATB + BBR groups were higher than those in the BBR group. Additionally, BBR decreased the number of nuclei at the edges and the distribution of lipids in the liver tissue. Collectively, BBR reduced the blood GLU level and improved GLU metabolism in largemouth bass. Comparative analysis of experiments with ATB and BBR supplementation revealed that BBR regulated GLU metabolism in largemouth bass by modulating intestinal microbiota.

Metabotyping: a tool for identifying subgroups for tailored nutrition advice

Diet-related diseases are the leading cause of death globally and strategies to tailor effective nutrition advice are required. Personalised nutrition advice is increasingly recognised as more effective than population-level advice to improve dietary intake and health outcomes. A potential tool to deliver personalised nutrition advice is metabotyping which groups individuals into homogeneous subgroups (metabotypes) using metabolic profiles. In summary, metabotyping has been successfully employed in human nutrition research to identify subgroups of individuals with differential responses to dietary challenges and interventions and diet–disease associations. The suitability of metabotyping to identify clinically relevant subgroups is corroborated by other fields such as diabetes research where metabolic profiling has been intensely used to identify subgroups of patients that display patterns of disease progression and complications. However, there is a paucity of studies examining the efficacy of the approach to improve dietary intake and health parameters. While the application of metabotypes to tailor and deliver nutrition advice is very promising, further evidence from randomised controlled trials is necessary for further development and acceptance of the approach.

Antioxidant Dietary Fiber Sourced from Agroindustrial Byproducts and Its Applications

Agroindustrial activities generate various residues or byproducts which are inefficiently utilized, impacting the environment and increasing production costs. These byproducts contain significant amounts of bioactive compounds, including dietary fiber with associated phenolic compounds, known as antioxidant dietary fiber (ADF). Phenolic compounds are related to the prevention of diseases related to oxidative stress, such as neurodegenerative and cardiovascular diseases. The mechanism of ADF depends on its chemical structure and the interactions between the dietary fiber and associated phenolic compounds. This work describes ADF, the main byproducts considered sources of ADF, its mechanisms of action, and its potential use in the formulation of foods destined for human consumption. ADF responds to the demand for low-cost, functional ingredients with great health benefits. A higher intake of antioxidant dietary fiber contributes to reducing the risk of diseases such as type II diabetes, colon cancer, obesity, and kidney stones, and has bile-acid retention-excretion, gastrointestinal laxative, hypoglycemic, hypocholesterolemic, prebiotic, and cardioprotective effects. ADF is a functional, sustainable, and profitable ingredient with different applications in agroindustry; its use can improve the technofunctional and nutritional properties of food, helping to close the cycle following the premise of the circular economy.

Optimized Metabotype Definition Based on a Limited Number of Standard Clinical Parameters in the Population-Based KORA Study

The aim of metabotyping is to categorize individuals into metabolically similar groups. Earlier studies that explored metabotyping used numerous parameters, which made it less transferable to apply. Therefore, this study aimed to identify metabotypes based on a set of standard laboratory parameters that are regularly determined in clinical practice. K-means cluster analysis was used to group 3001 adults from the KORA F4 cohort into three clusters. We identified the clustering parameters through variable importance methods, without including any specific disease endpoint. Several unique combinations of selected parameters were used to create different metabotype models. Metabotype models were then described and evaluated, based on various metabolic parameters and on the incidence of cardiometabolic diseases. As a result, two optimal models were identified: a model composed of five parameters, which were fasting glucose, HDLc, non-HDLc, uric acid, and BMI (the metabolic disease model) for clustering; and a model that included four parameters, which were fasting glucose, HDLc, non-HDLc, and triglycerides (the cardiovascular disease model). These identified metabotypes are based on a few common parameters that are measured in everyday clinical practice. These metabotypes are cost-effective, and can be easily applied on a large scale in order to identify specific risk groups that can benefit most from measures to prevent cardiometabolic diseases, such as dietary recommendations and lifestyle interventions.

Association between Usual Dietary Intake of Food Groups and DNA Methylation and Effect Modification by Metabotype in the KORA FF4 Cohort

Associations between diet and DNA methylation may vary among subjects with different metabolic states, which can be captured by clustering populations in metabolically homogenous subgroups, called metabotypes. Our aim was to examine the relationship between habitual consumption of various food groups and DNA methylation as well as to test for effect modification by metabotype. A cross-sectional analysis of participants (median age 58 years) of the population-based prospective KORA FF4 study, habitual dietary intake was modeled based on repeated 24-h diet recalls and a food frequency questionnaire. DNA methylation was measured using the Infinium MethylationEPIC BeadChip providing data on >850,000 sites in this epigenome-wide association study (EWAS). Three metabotype clusters were identified using four standard clinical parameters and BMI. Regression models were used to associate diet and DNA methylation, and to test for effect modification. Few significant signals were identified in the basic analysis while many significant signals were observed in models including food group-metabotype interaction terms. Most findings refer to interactions of food intake with metabotype 3, which is the metabotype with the most unfavorable metabolic profile. This research highlights the importance of the metabolic characteristics of subjects when identifying associations between diet and white blood cell DNA methylation in EWAS.