Search

Obesity is a multifactorial disease associated with low-grade inflammation. The gut is thought to be involved in obesity-related inflammation, as it is continuously exposed to antigens from food, microbiota and metabolites. However, the exact underlying mechanisms are still unknown. Therefore, we examined the relation between gut pathology, microbiota, its metabolites and cytokines in adults with severe obesity. Individuals eligible for bariatric surgery were included. Fecal and plasma samples were collected at surgery timepoint, to assess microbiota and metabolite composition. Jejunal biopsies were collected during surgery and stained for cytotoxic T cells, macrophages, mast cells and tight junction component zonula occludens-1. Based on these stainings, the cohort was divided into four groups: high versus low intestinal inflammation and high versus low intestinal integrity. We found no significant differences in microbiota diversity between groups, nor for individual bacterial species. No significant differences in metabolites were observed between the intestinal inflammatory groups. However, some metabolites and cytokines differed between the intestinal integrity groups. Higher plasma levels of interleukin-8 and tauro-chenodeoxycholic acid were found, whereas isovaleric acid and acetic acid were lower in the high intestinal integrity group. As the results were very subtle, we suggest that our cohort shows very early and minor intestinal pathology. [ABSTRACT FROM AUTHOR]

Nutrition and oral health are closely related, especially in older adults in whom poor nutrition may lead to oral microbial perturbations, exacerbating poor oral health. In a 6-month randomized controlled trial, we evaluated the effects on oral microbiota and on oral health of dietary advice aimed at increasing protein intake to ≥1.2 g/kg adjusted body weight/day (g/kg aBW/d) in community-dwelling older adults with low habitual protein intake (<1.0 g/kg aBW/d). Food intake was measured via 24 h dietary recalls, oral health was measured via questionnaires, and oral microbial composition was assessed via the 16S rRNA sequencing of tongue swabs. Mean baseline protein intake was 0.8 g/kg aBW/day in both groups. In the high protein group (n = 47), participants increased their protein intake to mean 1.2 g/kg aBW/day at the 6-month follow-up. Protein intake in the control group (n = 43) remained at 0.9 g/kg a BW/day. The intervention did not affect self-reported oral health. While it caused moderate shifts in oral microbiota alpha- and beta-diversity measures, abundances of individual bacterial taxa were not affected. In conclusion, our intervention did not affect self-reported oral health within a period of 6 months, nor did it substantially affect the tongue microbiota composition. [ABSTRACT FROM AUTHOR]

The development of microbiome-targeted strategies is limited by individual differences in gut microbiome composition and metabolic responses to interventions. In vitro models that can replicate this variation allow us to conduct pre-clinical studies and assess efficacy. This study describes the exposure of 16 individual fecal microbiota samples to 5 different fibers using an in vitro system for the anaerobic cultivation of bacteria. The individual microbiota differed in composition and metabolite profiles (short-chain fatty acids and branched-chain fatty acids) after incubation with the fibers. Furthermore, microbiota composition after fiber incubation was significantly different between subjects with good intestinal health and subjects with Inflammatory Bowel Disease (IBD). α-diversity was differently affected by dietary fibers; for example, exposure to psyllium resulted in increased diversity in the healthy group and in decreased diversity in the IBD group. Instead, the functional metabolic profile did not differ between the two groups. Finally, the combination of all fibers, tested on the microbiota from IBD subjects, resulted in stronger overall effects on both microbiota composition and metabolite production compared to the single fibers. These results confirm that incubation with dietary fiber results in different compositional and functional effects on individual microbiota and that in vitro models represent successful tools for studying individual fiber effects. [ABSTRACT FROM AUTHOR]

Digital health technologies may support the management and prevention of disease through personalized lifestyle interventions. Wearables and smartphones are increasingly used to continuously monitor health and disease in everyday life, targeting health maintenance. Here, we aim to demonstrate the potential of wearables and smartphones to (1) detect eating moments and (2) predict and explain individual glucose levels in healthy individuals, ultimately supporting health self-management. Twenty-four individuals collected continuous data from interstitial glucose monitoring, food logging, activity, and sleep tracking over 14 days. We demonstrated the use of continuous glucose monitoring and activity tracking in detecting eating moments with a prediction model showing an accuracy of 92.3% (87.2–96%) and 76.8% (74.3–81.2%) in the training and test datasets, respectively. Additionally, we showed the prediction of glucose peaks from food logging, activity tracking, and sleep monitoring with an overall mean absolute error of 0.32 (+/−0.04) mmol/L for the training data and 0.62 (+/−0.15) mmol/L for the test data. With Shapley additive explanations, the personal lifestyle elements important for predicting individual glucose peaks were identified, providing a basis for personalized lifestyle advice. Pending further validation of these digital biomarkers, they show promise in supporting the prevention and management of type 2 diabetes through personalized lifestyle recommendations. [ABSTRACT FROM AUTHOR]

Reflecting the two main prevailing and opposing views on the nature of emotions, emotional responses to food and beverages are typically measured using either (a) a categorical (lexicon-based) approach where users select or rate the terms that best express their food-related feelings or (b) a dimensional approach where they rate perceived food items along the dimensions of valence and arousal. Relating these two approaches is problematic since a response in terms of valence and arousal is not easily expressed in terms of emotions (like happy or disgusted). In this study, we linked the dimensional approach to a categorical approach by establishing mapping between a set of 25 emotion terms (EsSense25) and the valence–arousal space (via the EmojiGrid graphical response tool), using a set of 20 food images. In two 'matching' tasks, the participants first imagined how the food shown in a given image would make them feel and then reported either the emotional terms or the combination of valence and arousal that best described their feelings. In two labeling tasks, the participants first imagined experiencing a given emotion term and then they selected either the foods (images) that appeared capable to elicit that feeling or reported the combination of valence and arousal that best reflected that feeling. By combining (1) the mapping between the emotion terms and the food images with (2) the mapping of the food images to the valence–arousal space, we established (3) an indirect (via the images) mapping of the emotion terms to the valence–arousal space. The results show that the mapping between terms and images was reliable and that the linkages have straightforward and meaningful interpretations. The valence and arousal values that were assigned to the emotion terms through indirect mapping to the valence–arousal space were typically less extreme than those that were assigned through direct mapping. [ABSTRACT FROM AUTHOR]

Oxidative stress aggravates the progression of lifestyle-related chronic diseases. However, knowledge and practices that enable quantifying oxidative stress are still lacking. Here, we performed a proof-of-concept study to predict the oxidative stress status in a healthy population using retrospective cohort data from Boramae medical center in Korea (n = 1328). To obtain binary performance measures, we selected healthy controls versus oxidative disease cases based on the "health space" statistical methodology. We then developed a machine learning algorithm for discrimination of oxidative stress status using least absolute shrinkage and selection operator (LASSO)/elastic net regression with 10-fold cross-validation. A proposed fine-tune model included 16 features out of the full spectrum of diverse and complex data. The predictive performance was externally evaluated by generating receiver operating characteristic curves with area under the curve of 0.949 (CI 0.925 to 0.974), sensitivity of 0.923 (CI 0.879 to 0.967), and specificity of 0.855 (CI 0.795 to 0.915). Moreover, the discrimination power was confirmed by applying the proposed diagnostic model to the full dataset consisting of subjects with various degrees of oxidative stress. The results provide a feasible approach for stratifying the oxidative stress risks in the healthy population and selecting appropriate strategies for individual subjects toward implementing data-driven precision nutrition. [ABSTRACT FROM AUTHOR]

Personalized nutrition may be more effective in changing lifestyle behaviors compared to population-based guidelines. This single-arm exploratory study evaluated the impact of a 10-week personalized systems nutrition (PSN) program on lifestyle behavior and health outcomes. Healthy men and women (n = 82) completed the trial. Individuals were grouped into seven diet types, for which phenotypic, genotypic and behavioral data were used to generate personalized recommendations. Behavior change guidance was also provided. The intervention reduced the intake of calories (−256.2 kcal; p < 0.0001), carbohydrates (−22.1 g; p < 0.0039), sugar (−13.0 g; p < 0.0001), total fat (−17.3 g; p < 0.0001), saturated fat (−5.9 g; p = 0.0003) and PUFA (−2.5 g; p = 0.0065). Additionally, BMI (−0.6 kg/m2; p < 0.0001), body fat (−1.2%; p = 0.0192) and hip circumference (−5.8 cm; p < 0.0001) were decreased after the intervention. In the subgroup with the lowest phenotypic flexibility, a measure of the body's ability to adapt to environmental stressors, LDL (−0.44 mmol/L; p = 0.002) and total cholesterol (−0.49 mmol/L; p < 0.0001) were reduced after the intervention. This study shows that a PSN program in a workforce improves lifestyle habits and reduces body weight, BMI and other health-related outcomes. Health improvement was most pronounced in the compromised phenotypic flexibility subgroup, which indicates that a PSN program may be effective in targeting behavior change in health-compromised target groups. [ABSTRACT FROM AUTHOR]

In public health initiatives, generic nutrition advice (GNA) from national guidelines has a limited effect on food-intake improvement. Personalized nutrition advice (PNA) may enable dietary behavior change. A monocentric, randomized, parallel, controlled clinical trial was performed in males (n = 55) and females (n = 100) aged 25 to 70 years. Participants were allocated to control, GNA or PNA groups. The PNA group consisted of automatically generated dietary advice based on personal metabolic health parameters, dietary intake, anthropometric and hemodynamic measures, gender and age. Participants who received PNA (n = 51) improved their nutritional intake status for fruits P (p < 0.0001), whole grains (p = 0.008), unsalted nuts (p < 0.0001), fish (p = 0.0003), sugar-sweetened beverages (p = 0.005), added salt (p = 0.003) and less unhealthy choices (p = 0.002), whereas no improvements were observed in the control and GNA group. PNA participants were encouraged to set a goal for one or multiple food categories. Goal-setting led to greater improvement of food categories within the PNA group including; unsalted nuts (p < 0.0001), fruits (p = 0.0001), whole grains (p = 0.005), fish (p = 0.0001), dairy (p = 0.007), vegetables (p = 0.01) and unhealthy choices (p = 0.02). In a healthy population, participants receiving PNA changed their food-intake behavior more favorably than participants receiving GNA or no advice. When personal goals were set, nutritional behavior was more prone to change. [ABSTRACT FROM AUTHOR]

Chronic exposure of children in sub-Saharan Africa to aflatoxins has been associated with low birth weight, stunted growth, immune suppression, and liver function damage. Lactobacillus species have been shown to reduce aflatoxin contamination during the process of food fermentation. Twenty-three Lactobacillus strains were isolated from fecal samples obtained from a cohort of rural Ugandan children at the age of 54 to 60 months, typed by 16S rRNA gene sequencing, and characterized in terms of their ability to bind aflatoxin B1 in vitro. Evidence for chronic exposure of these children to aflatoxin B1 in the study area was obtained by analysis of local foods (maize flour and peanuts), followed by the identification of the breakdown product aflatoxin M1 in their urine samples. Surprisingly, Lactobacillus in the gut microbiota of 140 children from the same cohort at 24 and 36 months showed the highest positive correlation coefficient with stunting among all bacterial genera identified in the stool samples. This correlation was interpreted to be associated with dietary changes from breastfeeding to plant-based solid foods that pose an additional risk for aflatoxin contamination, on one hand, and lead to increased intake of Lactobacillus species on the other. [ABSTRACT FROM AUTHOR]

Recently, the concept of prebiotics has been revisited to expand beyond non-digestible oligosaccharides, and the requirements for selective stimulation were extended to include microbial groups other than, and additional to, bifidobacteria and lactobacilli. Here, the gut microbiota-modulating effects of well-known and novel prebiotics were studied. An in vitro fermentation screening platform (i-screen) was inoculated with adult fecal microbiota, exposed to different dietary fibers that had a range of concentrations (inulin, alpha-linked galacto-oligosaccharides (alpha-GOS), beta-linked GOS, xylo-oligosaccharides (XOS) from corn cobs and high-fiber sugar cane, and beta-glucan from oats), and compared to a positive fructo-oligosaccharide (FOS) control and a negative control (no fiber addition). All dietary fibers displayed prebiotic activity, with beta-glucan showing more distinct effects on the microbial composition and metabolism compared to the other fibers. Beta-glucan induced the growth of Prevotella and Roseburia with a concomitant increase in propionate production. Inulin and both forms of GOS and XOS had a strong bifidogenic effect on the microbial composition. A dose-response effect was observed for butyrate when exposed to beta-glucan and inulin. The findings of this study support the potential for alpha-GOS, XOS, and oat beta-glucan to serve as novel prebiotics, due to their association with the positive shifts in microbiome composition and short-chain fatty acid production that point to potential health benefits. [ABSTRACT FROM AUTHOR]