Bread Affects Clinical Parameters and Induces Gut Microbiome-Associated Personal Glycemic Responses

Microbes as medicine

Over the last two decades, advancements in sequencing technologies have significantly deepened our understanding of the human microbiome's complexity, leading to increased concerns about the detrimental effects of antibiotics on these intricate microbial ecosystems. Concurrently, the rise in antimicrobial resistance has intensified the focus on how beneficial microbes can be harnessed to treat diseases and improve health and offer potentially promising alternatives to traditional antibiotic treatments. Here, we provide a comprehensive overview of both established and emerging microbe-centric therapies, from probiotics to advanced microbial ecosystem therapeutics, examine the sophisticated ways in which microbes are used medicinally, and consider their impacts on microbiome homeostasis and health outcomes through a microbial ecology lens. In addition, we explore the concept of rewilding the human microbiome by reintroducing "missing microbes" from nonindustrialized societies and personalizing microbiome modulation to fit individual microbial profiles-highlighting several promising directions for future research. Ultimately, the advancements in sequencing technologies combined with innovative microbial therapies and personalized approaches herald a new era in medicine poised to address antibiotic resistance and improve health outcomes through targeted microbiome management.

Intestinal-level anti-inflammatory bioactivities of whole wheat: Rationale, design, and methods of a randomized, controlled, crossover dietary trial in adults with prediabetes

Randomized controlled trials (RCT) demonstrate that whole wheat consumption improves glycemia. However, substantial inter-individual variation is often observed, highlighting that dietary whole grain recommendations may not support the health of all persons. The objective of this report is to describe the rationale and design of a planned RCT aimed at establishing the gut microbiota and metabolome signatures that predict whole wheat-mediated improvements in glucose tolerance in adults with prediabetes. It is hypothesized that a controlled diet containing wheat bread (WHEAT; 160 g/day) compared with refined bread (WHITE) will improve glucose tolerance in a gut microbiota-mediated manner. Biospecimens will be collected before and after each 2-week study arm. Testing for oral glucose tolerance and gastrointestinal permeability will be performed post-intervention. Assessments will include oral glucose tolerance (primary outcome) and secondary outcomes including gut microbiota, targeted and untargeted metabolomics of fecal and plasma samples, intestinal and host inflammatory responses, and intestinal permeability. WHEAT is predicted to alleviate glucose intolerance by shifting microbiota composition to increase short-chain fatty acid-producing bacteria while reducing populations implicated in intestinal inflammation, barrier dysfunction, and systemic endotoxemia. Further, benefits from WHEAT are anticipated to correlate with gut-level and systemic metabolomic responses that can help to explain the expected inter-individual variability in glucose tolerance. Thus, knowledge gained from integrating multi-omic responses associating with glucose tolerance could help to establish a precision nutrition-based framework that can alleviate cardiometabolic risk. This framework could inform novel dietary whole grain recommendations by enhancing our understanding of inter-individual responsiveness to whole grain consumption.

Pea protein - gum Arabic gel addition as ingredient to increase protein, fiber and decrease lipid content in muffins without impair the texture and intestinal microbiota

This study evaluated the use of a protein-polysaccharide gel (PGEL) as a muffin ingredient, and its effect on the nutritional, textural, and gut microbiome profiles. PGEL was generated by complex coacervation with Pea protein and Gum Arabic. A mixture design was performed with different flour, lipids, and PGEL proportions, where Tx9 (26 % PGEL) showed improved physicochemical characteristics. Optimization was performed using 3 variables, hardness, protein content, and in vitro protein digestibility, to generate an optimal muffin with PGEL (PGEL-Muffin). PGEL-Muffin had a positive effect in its nutritional content and texture (protein: 12.03 %, fiber: 7.90 %, lipids: 9.23 %, and hardness: 4.41 N) compared to a muffin without protein addition (Control) and a muffin with added pea protein powder (Powder-Muffin). PGEL-Muffin did not modify gut microbiome using an ex-vivo system after 4-days of administration. PGEL ingredient could be an opportunity to develop nutritionally improved products without a negative impact on textural properties.

Health benefits and risks of fermented foods-the PIMENTO initiative

Worldwide, fermented foods (FF) are recognized as healthy and safe. Despite the rapid increase of research papers, there is a lack of systematic evaluation of the health benefits and risks of FF. The COST Action CA20128 "Promoting innovation of fermented foods" (PIMENTO) aims to provide a comprehensive assessment on the available evidence by compiling a set of 16 reviews. Seven reviews will cover clinical and biological endpoints associated with major health indicators across several organ systems, including the cardiovascular, gastrointestinal, neurological, immune, and skeletal systems. Nine reviews will address broader biological questions associated with FF including bioactive compounds and vitamin production, nutrient bioavailability and bioaccessibility, the role of FF in healthy diets and personalized nutrition, food safety, regulatory practices, and finally, the health properties of novel and ethnic FF. For each outcome assessed in the reviews, an innovative approach will be adopted based on EFSA's published guidance for health claim submissions. In particular, each review will be composed of three parts: (1) a systematic review of available human studies; (2) a non-systematic review of the mechanism of action related to the clinical endpoints measured by the human studies identified in part 1; and (3) a non-systematic review of the characterization of the FF investigated in the human studies identified in part 1. The evidence and research gaps derived from the reviews will be summarized and published in the form of a strategic road map that will pave the way for future research on FF.

Changes in the Firmicutes to Bacteriodetes ratio in the gut microbiome in individuals with anorexia nervosa following inpatient treatment: A systematic review and a case series

OBJECTIVE

Anorexia nervosa has the highest mortality rate among psychiatric illnesses. Current treatments remain ineffective for a large fraction of patients. This may be due to unclear mechanisms behind its development and maintenance. Studies exploring the role of the gut microbiome have revealed inconsistent evidence of dysbiosis. This article aims to investigate changes in the gut microbiome, particularly, mean differences in the Firmicutes to Bacteroidetes ratio, in adolescent and adult individuals with anorexia nervosa following inpatient treatment.

METHODS

Longitudinal studies investigating gut microbiome composition in inpatient populations of anorexia nervosa before and after treatment were systematically reviewed. Additionally, gut microbiome compositions were characterized in three acute anorexia nervosa inpatients early after admission and after 4-12 weeks of treatment.

RESULTS

Review results indicated an increase in the Firmicutes to Bacteroidetes ratio in individuals with anorexia nervosa after treatment. These however did not match values of their healthy counterparts. In the case-series samples, the reverse occurred with samples taken 4 weeks after treatment. In the patient who provided an extra sample 12 weeks after treatment, similar results to the studies included in the review were observed. Furthermore, Firmicutes to Bacteroidetes ratio values in the case-series samples were notably higher in the two patients who had chronic anorexia nervosa.

DISCUSSION

Differences in methodologies, small sample sizes, and insufficient data limited the generalizability of the outcomes of the reviewed studies. Results suggest a potentially unique microbiome signature in individuals with chronic anorexia nervosa, which may explain different outcomes in this group of patients.

Low-fat yogurt consumption maintains biomarkers of immune function relative to nondairy control food in women with elevated BMI: A randomized controlled crossover trial

Yogurt consumption may help reduce chronic inflammation associated with obesity. However, the underlying mechanism(s) by which yogurt consumption modulates the immune system have not been validated in human intervention studies. We hypothesized that 4-week yogurt consumption (12 oz/day) attenuates systemic inflammation by modulating the proportion of circulating T helper (Th) 17 and regulatory T (Treg) cells in adult women with elevated body mass index (BMI). To test the hypothesis, we conducted a randomized crossover dietary intervention study consisted of a 4-week dietary intervention in which participants consumed 12 oz of either low-fat dairy yogurt or a soy pudding control snack per day, with a 4-week washout between treatments. Thirty-nine healthy adult women with a BMI between 25 and 40 kg/m2 were enrolled and 20 completed the study. Changes in the biometrics, circulating T cells, and markers of systemic and colonic inflammation were assessed between the 2 treatment groups, as well as 24-hour diet recalls were conducted at baseline and following each treatment. The primary study outcome, the change in the proportion of circulating Th17 cells, was unaffected by the treatments. Secondary outcome measures, circulating Treg, Th17, and markers of chronic inflammation, were maintained by yogurt treatment, whereas circulating Treg was increased and interleukin-10 was reduced by control snack treatment. However, circulating Treg changes were not associated with changes to other biomarkers of inflammation, implying other immune cells and/or tissues may mediate circulating biomarkers of chronic inflammation. This study was approved by the University of Wisconsin-Madison institutional review board and registered at ClinicalTrials.gov NCT04149418.

Western diets and chronic diseases

'Westernization', which incorporates industrial, cultural and dietary trends, has paralleled the rise of noncommunicable diseases across the globe. Today, the Western-style diet emerges as a key stimulus for gut microbial vulnerability, chronic inflammation and chronic diseases, affecting mainly the cardiovascular system, systemic metabolism and the gut. Here we review the diet of modern times and evaluate the threat it poses for human health by summarizing recent epidemiological, translational and clinical studies. We discuss the links between diet and disease in the context of obesity and type 2 diabetes, cardiovascular diseases, gut and liver diseases and solid malignancies. We collectively interpret the evidence and its limitations and discuss future challenges and strategies to overcome these. We argue that healthcare professionals and societies must react today to the detrimental effects of the Western diet to bring about sustainable change and improved outcomes in the future.

Sourdough Bread with Different Fermentation Times: A Randomized Clinical Trial in Subjects with Metabolic Syndrome

The Mediterranean diet, featuring sourdough bread, shows promise in managing metabolic syndrome. This study explored the effects of two sourdough breads, with differing fermentation times but similar nutritional profiles, on inflammation, satiety, and gut microbiota composition in adults with metabolic syndrome. In a double-blind clinical trial, participants were randomized to consume either Elias Boulanger® long-fermentation (48 h) sourdough bread (EBLong) or Elias Boulanger® short-fermentation (2 h) sourdough bread (EBShort) over a two-month period. We assessed clinical parameters, inflammatory biomarkers, satiety-related hormones, and the richness and abundance of gut microbiota at baseline and follow-up. The participants included 31 individuals (mean age, 67, 51.6% female). EBShort was associated with reduced levels of soluble intercellular adhesion molecule (sICAM), and all participants, regardless of the intervention, exhibited a decrease in sICAM and diastolic pressure from baseline (p < 0.017). At follow-up, plasminogen activator inhibitor-1 (PAI-1) levels were lower in EBShort (-744 pg/mL; 95%CI: -282 to -1210 pg/mL) compared to EBLong. No differences in microbiota richness or abundance were observed. EBShort bread was effective in reducing some inflammation markers. The consumption of sourdough bread may offer potential benefits in reducing inflammation markers in individuals with metabolic syndrome; however, longer fermentation times did not show additional benefits.

Prediction of personalised postprandial glycaemic response in type 1 diabetes mellitus

Objectives

Patients with type 1 diabetes (T1D) face unique challenges in glycaemic control due to the complexity and uniqueness of the dietary structure in China, especially in terms of postprandial glycaemic response (PPGR). This study aimed to establish a personalized model for predicting PPGR in patients with T1D.

Materials and methods

Data provided by the First People's Hospital of Yunnan Province, 13 patients with T1D, were recruited and provided with an intervention for at least two weeks. All patients were asked to wear a continuous glucose monitoring (CGM) device under free-living conditions during the study period. To tackle the challenge of incomplete data from wearable devices for CGM measurements, the GAIN method was used in this paper to achieve a more rational interpolation process. In this study, patients' PPGRs were calculated, and a LightGBM prediction model was constructed based on a Bayesian hyperparameter optimisation algorithm and a random search algorithm, which integrated glucose measurement, insulin dose, dietary nutrient content, blood measurement and anthropometry as inputs.

Results

The experimental outcomes revealed that the PPGR prediction model presented in this paper demonstrated superior accuracy (R=0.63) compared to both the carbohydrate content only model (R=0.14) and the baseline model emulating the standard of care for insulin administration (R=0.43). In addition, the interpretation of the model using the SHAP method showed that blood glucose levels at meals and blood glucose trends 30 minutes before meals were the most important features of the model.

Conclusion

The proposed model offers a heightened precision in predicting PPGR in patients with T1D, so it can better guide the diet plan and insulin intake dose of patients with T1D.

Exploring the Nutritional Impact of Sourdough Fermentation: Its Mechanisms and Functional Potential

Sourdough fermentation is one of the oldest traditional methods in food technology and occurs as a result of fermentation of flour prepared from grains. The nutritional role of sourdough is related to the final composition of fermented foods prepared through sourdough fermentation, and recently, sourdough has become an important application to improve nutrition characteristics of bread. Thanks to lactic acid bacteria (LAB) presented in sourdough microflora and metabolites partially produced by yeasts, technological and important nutritional features of the bread improve and an increase in shelf life is achieved. In addition, sourdough bread has a low glycemic index value, high protein digestibility, high mineral and antioxidant content, and improved dietary fiber composition, making it more attractive for human nutrition compared to regular bread. When the sourdough process is applied, the chemical and physical properties of fibers vary according to the degree of fermentation, revealing the physiological importance of dietary fiber and its importance to humans' large intestine microbiota. Therefore, taking these approach frameworks into consideration, this review highlights the benefits of sourdough fermentation in increasing nutrient availability and contributing positively to support human health.

Competitive fungal commensalism mitigates candidiasis pathology

The mycobiota are a critical part of the gut microbiome, but host-fungal interactions and specific functional contributions of commensal fungi to host fitness remain incompletely understood. Here, we report the identification of a new fungal commensal, Kazachstania heterogenica var. weizmannii, isolated from murine intestines. K. weizmannii exposure prevented Candida albicans colonization and significantly reduced the commensal C. albicans burden in colonized animals. Following immunosuppression of C. albicans colonized mice, competitive fungal commensalism thereby mitigated fatal candidiasis. Metagenome analysis revealed K. heterogenica or K. weizmannii presence among human commensals. Our results reveal competitive fungal commensalism within the intestinal microbiota, independent of bacteria and immune responses, that could bear potential therapeutic value for the management of C. albicans-mediated diseases.

Utilization of the microbiome in personalized medicine

Inter-individual human variability, driven by various genetic and environmental factors, complicates the ability to develop effective population-based early disease detection, treatment and prognostic assessment. The microbiome, consisting of diverse microorganism communities including viruses, bacteria, fungi and eukaryotes colonizing human body surfaces, has recently been identified as a contributor to inter-individual variation, through its person-specific signatures. As such, the microbiome may modulate disease manifestations, even among individuals with similar genetic disease susceptibility risks. Information stored within microbiomes may therefore enable early detection and prognostic assessment of disease in at-risk populations, whereas microbiome modulation may constitute an effective and safe treatment tailored to the individual. In this Review, we explore recent advances in the application of microbiome data in precision medicine across a growing number of human diseases. We also discuss the challenges, limitations and prospects of analysing microbiome data for personalized patient care.

Maternal dietary intervention during lactation impacts the maternal faecal and human milk microbiota

AIMS

To determine the effect of a two-week reduced fat and sugar and increased fibre maternal dietary intervention on the maternal faecal and human milk (HM) microbiomes.

METHODS AND RESULTS

Faecal swabs and HM samples were collected from mothers (n = 11) immediately pre-intervention, immediately post-intervention, and 4 and 8 weeks post-intervention, and were analysed using full-length 16S rRNA gene sequencing. Maternal macronutrient intake was assessed at baseline and during the intervention. Maternal fat and sugar intake during the intervention were significantly lower than pre-intervention (P = <0.001, 0.005, respectively). Significant changes in the bacterial composition of maternal faeces were detected after the dietary intervention, with decreases in the relative abundance of Bacteroides caccae (P = <0.001) and increases in the relative abundance of Faecalibacillus intestinalis (P = 0.006). In HM, the diet resulted in a significant increase in Cutibacterium acnes (P = 0.001) and a decrease in Haemophilus parainfluenzae (P = <0.001). The effect of the diet continued after the intervention, with faecal swabs and HM samples taken 4 and 8 weeks after the diet showing significant differences compared to baseline.

CONCLUSION

This pilot study demonstrates that short-term changes in maternal diet during lactation can alter the bacterial composition of the maternal faeces and HM.

Transforming the cardiometabolic disease landscape: Multimodal AI-powered approaches in prevention and management

The rise of artificial intelligence (AI) has revolutionized various scientific fields, particularly in medicine, where it has enabled the modeling of complex relationships from massive datasets. Initially, AI algorithms focused on improved interpretation of diagnostic studies such as chest X-rays and electrocardiograms in addition to predicting patient outcomes and future disease onset. However, AI has evolved with the introduction of transformer models, allowing analysis of the diverse, multimodal data sources existing in medicine today. Multimodal AI holds great promise in more accurate disease risk assessment and stratification as well as optimizing the key driving factors in cardiometabolic disease: blood pressure, sleep, stress, glucose control, weight, nutrition, and physical activity. In this article we outline the current state of medical AI in cardiometabolic disease, highlighting the potential of multimodal AI to augment personalized prevention and treatment strategies in cardiometabolic disease.

Moderate variations in the human diet impact the gut microbiota in humanized mice

AIM

Drastic diet interventions have been shown to promote rapid and significant compositional changes of the gut microbiota, but the impact of moderate diet variations is less clear. Here, we aimed to clarify the impact of moderate diet variations that remain within the spectrum of the habitual human diet on gut microbiota composition.

METHODS

We performed a pilot diet intervention where five healthy volunteers consumed a vegetarian ready-made meal for three days to standardize dietary intake before switching to a meat-based ready-made western-style meal and high sugar drink for two days. We performed 16S rRNA sequencing from daily fecal sampling to assess gut microbiota changes caused by the intervention diet. Furthermore, we used the volunteers' fecal samples to colonize germ-free mice that were fed the same sterilized diets to study the effect of a moderate diet intervention on the gut microbiota in a setting of reduced interindividual variation.

RESULTS

In the human intervention, we found that fecal microbiota composition varied between and within individuals regardless of diet. However, when we fed the same diets to mice colonized with the study participants' feces, we observed significant, often donor-specific, changes in the mouse microbiota following this moderate diet intervention.

CONCLUSION

Moderate variations in the habitual human diet have the potential to alter the gut microbiota. Feeding humanized mice human diets may facilitate our understanding of individual human gut microbiota responses to moderate dietary changes and help improve individualized interventions.

Potential Mechanisms of Precision Nutrition-Based Interventions for Managing Obesity

Precision nutrition (PN) considers multiple individual-level and environmental characteristics or variables to better inform dietary strategies and interventions for optimizing health, including managing obesity and metabolic disorders. Here, we review the evidence on potential mechanisms-including ones to identify individuals most likely to respond-that can be leveraged in the development of PN interventions addressing obesity. We conducted a review of the literature and included laboratory, animal, and human studies evaluating biochemical and genetic data, completed and ongoing clinical trials, and public programs in this review. Our analysis describes the potential mechanisms related to 6 domains including genetic predisposition, circadian rhythms, physical activity and sedentary behavior, metabolomics, the gut microbiome, and behavioral and socioeconomic characteristics, i.e., the factors that can be leveraged to design PN-based interventions to prevent and treat obesity-related outcomes such as weight loss or metabolic health as laid out by the NIH 2030 Strategic Plan for Nutrition Research. For example, single nucleotide polymorphisms can modify responses to certain dietary interventions, and epigenetic modulation of obesity risk via physical activity patterns and macronutrient intake have also been demonstrated. Additionally, we identified limitations including questions of equitable implementation across a limited number of clinical trials. These include the limited ability of current PN interventions to address systemic influences such as supply chains and food distribution, healthcare systems, racial or cultural inequities, and economic disparities, particularly when designing and implementing PN interventions in low- and middle-income communities. PN has the potential to help manage obesity by addressing intra- and inter-individual variation as well as context, as opposed to "one-size fits all" approaches though there is limited clinical trial evidence to date.

The impact of intermittent fasting on gut microbiota: a systematic review of human studies

Background

Intermittent fasting (IF) has gained popularity in interventions targeting overweight, obesity and metabolic syndrome. IF may affect the gut microbiome composition and therefore have various effects on gut microbiome mediated functions in humans. Research on the effects of IF on human gut microbiome is limited. Therefore, the objective of this systematic review was to determine how different types of IF affect the human gut microbiome.

Methods

A literature search was conducted for studies investigating the association of different types of IF and gut microbiota richness, alpha and beta diversity, and composition in human subjects. Databases included Cochrane Library (RRID:SCR_013000), PubMed (RRID:SCR_004846), Scopus (RRID:SCR_022559) and Web of Science (RRID:SCR_022706). A total of 1,332 studies were retrieved, of which 940 remained after removing duplicates. Ultimately, a total of 8 studies were included in the review. The included studies were randomized controlled trials, quasi-experimental studies and pilot studies implementing an IF intervention (time-restricted eating, alternate day fasting or 5:2 diet) in healthy subjects or subjects with any disease.

Results

Most studies found an association between IF and gut microbiota richness, diversity and compositional changes. There was heterogeneity in the results, and bacteria which were found to be statistically significantly affected by IF varied widely depending on the study.

Conclusion

The findings in this systematic review suggest that IF influences gut microbiota. It seems possible that IF can improve richness and alpha diversity. Due to the substantial heterogeneity of the results, more research is required to validate these findings and clarify whether the compositional changes might be beneficial to human health.

Systematic Review Registration

https://www.crd.york.ac.uk/prospero/, identifier CRD42021241619.

Fermented foods, their microbiome and its potential in boosting human health

Fermented foods (FFs) are part of the cultural heritage of several populations, and their production dates back 8000 years. Over the last ~150 years, the microbial consortia of many of the most widespread FFs have been characterised, leading in some instances to the standardisation of their production. Nevertheless, limited knowledge exists about the microbial communities of local and traditional FFs and their possible effects on human health. Recent findings suggest they might be a valuable source of novel probiotic strains, enriched in nutrients and highly sustainable for the environment. Despite the increasing number of observational studies and randomised controlled trials, it still remains unclear whether and how regular FF consumption is linked with health outcomes and enrichment of the gut microbiome in health-associated species. This review aims to sum up the knowledge about traditional FFs and their associated microbiomes, outlining the role of fermentation with respect to boosting nutritional profiles and attempting to establish a link between FF consumption and health-beneficial outcomes.

Are postprandial glucose responses sufficiently person-specific to use in personalized dietary advice? Design of the RepEAT study: a fully controlled dietary intervention to determine the variation in glucose responses

Introduction

An elevated postprandial glucose response is associated with an increased risk of cardiometabolic diseases. Existing research suggests large heterogeneity in the postprandial glucose responses to identical meals and food products between individuals, but the effect of other consumed meals during the day and the order of meals during the day on the heterogeneity in postprandial glucose responses still needs to be investigated. In addition, the robustness of the glucose responses to meals or foods is still unknown.

Objectives

The overall aim of the project is to assess whether the glucose response to a meal is sufficiently person-specific to use in personalized dietary advice. We aim to answer the question: "How replicable are glucose responses to meals within individuals and how consistent is the variation in glucose responses between individuals?"

Methods

The question will be assessed under standardized conditions of a 9-week fully controlled dietary intervention in which all meals are the same between individuals and consumed in a fixed order at a fixed time. 63 apparently healthy men and women with a BMI of 25-40 kg/m2 and aged 45-75 years were enrolled in the RepEAT study (NCT05456815), of whom 53 participants completed the study. The RepEAT study comprised a fully controlled dietary intervention of nine weeks, consisting of three repetitive periods of three weeks. Within each three-week period, a variety of meals and food products were offered during breakfast, lunch, dinner and in between meal snacks. Throughout the dietary intervention, glucose was continuously monitored using Freestyle Libre Pro IQ monitors. Physical activity was monitored using the ActiGraph and ActivPAL. To measure the association between glucose responses and an individual's phenotype, various measurements were performed before the start of the dietary intervention including an oral glucose tolerance test, a high-fat mixed meal challenge, assessment of body fat distribution including liver fat (MRI/MRS), and cardiometabolic markers.

Discussion

The repetitive and fully controlled nature of the dietary study allows detailed assessment of the replicability of the glucose responses to meals and food products within individuals. Furthermore, the consistency of the variation between individuals independent of insulin resistance will be determined.

Nutri-microbiome epidemiology, an emerging field to disentangle the interplay between nutrition and microbiome for human health

Diet and nutrition have a substantial impact on the human microbiome, and interact with the microbiome, especially gut microbiome, to modulate various diseases and health status. Microbiome research has also guided the nutrition field to a more integrative direction, becoming an essential component of the rising area of precision nutrition. In this review, we provide a broad insight into the interplay among diet, nutrition, microbiome, and microbial metabolites for their roles in the human health. Among the microbiome epidemiological studies regarding the associations of diet and nutrition with microbiome and its derived metabolites, we summarize those most reliable findings and highlight evidence for the relationships between diet and disease-associated microbiome and its functional readout. Then, the latest advances of the microbiome-based precision nutrition research and multidisciplinary integration are described. Finally, we discuss several outstanding challenges and opportunities in the field of nutri-microbiome epidemiology.

Probiotic responder identification in cross-over trials for constipation using a Bayesian statistical model considering lags between intake and effect periods

Recent advances in microbiome research have led to the further development of microbial interventions, such as probiotics and prebiotics, which are potential treatments for constipation. However, the effects of probiotics vary from person to person; therefore, the effectiveness of probiotics needs to be verified for each individual. Individuals showing significant effects of the target probiotic are called responders. A statistical model for the evaluation of responders was proposed in a previous study. However, the previous model does not consider the lag between intake and effect periods of the probiotic. It is expected that the lag exists when probiotics are administered and when they are effective. In this study, we propose a Bayesian statistical model to estimate the probability that a subject is a responder, by considering the lag between intake and effect periods. In synthetic dataset experiments, the proposed model was found to outperform the base model, which did not factor in the lag. Further, we found that the proposed model could distinguish responders showing large uncertainty in terms of the lag between intake and effect periods.

Uncovering personalized glucose responses and circadian rhythms from multiple wearable biosensors with Bayesian dynamical modeling

Wearable biosensors and smartphone applications can measure physiological variables over multiple days in free-living conditions. We measure food and drink ingestion, glucose dynamics, physical activity, heart rate (HR), and heart rate variability (HRV) in 25 healthy participants over 14 days. We develop a Bayesian inference framework to learn personal parameters that quantify circadian rhythms and physiological responses to external stressors. Modeling the effects of ingestion events on glucose levels reveals that slower glucose decay kinetics elicit larger postprandial glucose spikes, and we uncover a circadian baseline rhythm for glucose with high amplitudes in some individuals. Physical activity and circadian rhythms explain as much as 40%-65% of the HR variance, whereas the variance explained for HRV is more heterogeneous across individuals. A more complex model incorporating activity, HR, and HRV explains up to 15% of additional glucose variability, highlighting the relevance of integrating multiple biosensors to better predict glucose dynamics.

Nourishing the brain on deep space missions: nutritional psychiatry in promoting resilience

The grueling psychological demands of a journey into deep space coupled with ever-increasing distances away from home pose a unique problem: how can we best take advantage of the benefits of fresh foods in a place that has none? Here, we consider the biggest challenges associated with our current spaceflight food system, highlight the importance of supporting optimal brain health on missions into deep space, and discuss evidence about food components that impact brain health. We propose a future food system that leverages the gut microbiota that can be individually tailored to best support the brain and mental health of crews on deep space long-duration missions. Working toward this goal, we will also be making investments in sustainable means to nourish the crew that remains here on spaceship Earth.

Role of the Gut Microbiota and Its Metabolites in Tumorigenesis or Development of Colorectal Cancer

Colorectal cancer (CRC) is the most common cancer of the digestive system with high mortality and morbidity rates. Gut microbiota is found in the intestines, especially the colorectum, and has structured crosstalk interactions with the host that affect several physiological processes. The gut microbiota include CRC-promoting bacterial species, such as Fusobacterium nucleatum, Escherichia coli, and Bacteroides fragilis, and CRC-protecting bacterial species, such as Clostridium butyricum, Streptococcus thermophilus, and Lacticaseibacillus paracasei, which along with other microorganisms, such as viruses and fungi, play critical roles in the development of CRC. Different bacterial features are identified in patients with early-onset CRC, combined with different patterns between fecal and intratumoral microbiota. The gut microbiota may be beneficial in the diagnosis and treatment of CRC; some bacteria may serve as biomarkers while others as regulators of chemotherapy and immunotherapy. Furthermore, metabolites produced by the gut microbiota play essential roles in the crosstalk with CRC cells. Harmful metabolites include some primary bile acids and short-chain fatty acids, whereas others, including ursodeoxycholic acid and butyrate, are beneficial and impede tumor development and progression. This review focuses on the gut microbiota and its metabolites, and their potential roles in the development, diagnosis, and treatment of CRC.

Does sourdough bread provide clinically relevant health benefits?

During the last decade, scientific interest in and consumer attention to sourdough fermentation in bread making has increased. On the one hand, this technology may favorably impact product quality, including flavor and shelf-life of bakery products; on the other hand, some cereal components, especially in wheat and rye, which are known to cause adverse reactions in a small subset of the population, can be partially modified or degraded. The latter potentially reduces their harmful effects, but depends strongly on the composition of sourdough microbiota, processing conditions and the resulting acidification. Tolerability, nutritional composition, potential health effects and consumer acceptance of sourdough bread are often suggested to be superior compared to yeast-leavened bread. However, the advantages of sourdough fermentation claimed in many publications rely mostly on data from chemical and in vitro analyzes, which raises questions about the actual impact on human nutrition. This review focuses on grain components, which may cause adverse effects in humans and the effect of sourdough microbiota on their structure, quantity and biological properties. Furthermore, presumed benefits of secondary metabolites and reduction of contaminants are discussed. The benefits claimed deriving from in vitro and in vivo experiments will be evaluated across a broader spectrum in terms of clinically relevant effects on human health. Accordingly, this critical review aims to contribute to a better understanding of the extent to which sourdough bread may result in measurable health benefits in humans.

AI4FoodDB: a database for personalized e-Health nutrition and lifestyle through wearable devices and artificial intelligence

The increasing prevalence of diet-related diseases calls for an improvement in nutritional advice. Personalized nutrition aims to solve this problem by adapting dietary and lifestyle guidelines to the unique circumstances of each individual. With the latest advances in technology and data science, researchers can now automatically collect and analyze large amounts of data from a variety of sources, including wearable and smart devices. By combining these diverse data, more comprehensive insights of the human body and its diseases can be achieved. However, there are still major challenges to overcome, including the need for more robust data and standardization of methodologies for better subject monitoring and assessment. Here, we present the AI4Food database (AI4FoodDB), which gathers data from a nutritional weight loss intervention monitoring 100 overweight and obese participants during 1 month. Data acquisition involved manual traditional approaches, novel digital methods and the collection of biological samples, obtaining: (i) biological samples at the beginning and the end of the intervention, (ii) anthropometric measurements every 2 weeks, (iii) lifestyle and nutritional questionnaires at two different time points and (iv) continuous digital measurements for 2 weeks. To the best of our knowledge, AI4FoodDB is the first public database that centralizes food images, wearable sensors, validated questionnaires and biological samples from the same intervention. AI4FoodDB thus has immense potential for fostering the advancement of automatic and novel artificial intelligence techniques in the field of personalized care. Moreover, the collected information will yield valuable insights into the relationships between different variables and health outcomes, allowing researchers to generate and test new hypotheses, identify novel biomarkers and digital endpoints, and explore how different lifestyle, biological and digital factors impact health. The aim of this article is to describe the datasets included in AI4FoodDB and to outline the potential that they hold for precision health research. Database URL https://github.com/AI4Food/AI4FoodDB.

Maternal microbiota and gestational diabetes: impact on infant health

Gestational diabetes mellitus (GDM) is a common complication of pregnancy that has been associated with an increased risk of obesity and diabetes in the offspring. Pregnancy is accompanied by tightly regulated changes in the endocrine, metabolic, immune, and microbial systems, and deviations from these changes can alter the mother's metabolism resulting in adverse pregnancy outcomes and a negative impact on the health of her infant. Maternal microbiomes are significant drivers of mother and child health outcomes, and many microbial metabolites are likely to influence the host health. This review discusses the current understanding of how the microbiota and microbial metabolites may contribute to the development of GDM and how GDM-associated changes in the maternal microbiome can affect infant's health. We also describe microbiota-based interventions that aim to improve metabolic health and outline future directions for precision medicine research in this emerging field.

Investigating Gene-Diet Interactions Impacting the Association Between Macronutrient Intake and Glycemic Traits

Few studies have demonstrated reproducible gene-diet interactions (GDIs) impacting metabolic disease risk factors, likely due in part to measurement error in dietary intake estimation and insufficient capture of rare genetic variation. We aimed to identify GDIs across the genetic frequency spectrum impacting the macronutrient-glycemia relationship in genetically and culturally diverse cohorts. We analyzed 33,187 participants free of diabetes from 10 National Heart, Lung, and Blood Institute Trans-Omics for Precision Medicine program cohorts with whole-genome sequencing, self-reported diet, and glycemic trait data. We fit cohort-specific, multivariable-adjusted linear mixed models for the effect of diet, modeled as an isocaloric substitution of carbohydrate for fat, and its interactions with common and rare variants genome-wide. In main effect meta-analyses, participants consuming more carbohydrate had modestly lower glycemic trait values (e.g., for glycated hemoglobin [HbA1c], -0.013% HbA1c/250 kcal substitution). In GDI meta-analyses, a common African ancestry-enriched variant (rs79762542) reached study-wide significance and replicated in the UK Biobank cohort, indicating a negative carbohydrate-HbA1c association among major allele homozygotes only. Simulations revealed that >150,000 samples may be necessary to identify similar macronutrient GDIs under realistic assumptions about effect size and measurement error. These results generate hypotheses for further exploration of modifiable metabolic disease risk in additional cohorts with African ancestry.

ARTICLE HIGHLIGHTS

We aimed to identify genetic modifiers of the dietary macronutrient-glycemia relationship using whole-genome sequence data from 10 Trans-Omics for Precision Medicine program cohorts. Substitution models indicated a modest reduction in glycemia associated with an increase in dietary carbohydrate at the expense of fat. Genome-wide interaction analysis identified one African ancestry-enriched variant near the FRAS1 gene that may interact with macronutrient intake to influence hemoglobin A1c. Simulation-based power calculations accounting for measurement error suggested that substantially larger sample sizes may be necessary to discover further gene-macronutrient interactions.

Omics biomarkers and an approach for their practical implementation to delineate health status for personalized nutrition strategies

Personalized nutrition (PN) has gained much attention as a tool for empowerment of consumers to promote changes in dietary behavior, optimizing health status and preventing diet related diseases. Generalized implementation of PN faces different obstacles, one of the most relevant being metabolic characterization of the individual. Although omics technologies allow for assessment the dynamics of metabolism with unprecedented detail, its translatability as affordable and simple PN protocols is still difficult due to the complexity of metabolic regulation and to different technical and economical constrains. In this work, we propose a conceptual framework that considers the dysregulation of a few overarching processes, namely Carbohydrate metabolism, lipid metabolism, inflammation, oxidative stress and microbiota-derived metabolites, as the basis of the onset of several non-communicable diseases. These processes can be assessed and characterized by specific sets of proteomic, metabolomic and genetic markers that minimize operational constrains and maximize the information obtained at the individual level. Current machine learning and data analysis methodologies allow the development of algorithms to integrate omics and genetic markers. Reduction of dimensionality of variables facilitates the implementation of omics and genetic information in digital tools. This framework is exemplified by presenting the EU-Funded project PREVENTOMICS as a use case.

Identification of a Novel Score for Adherence to the Mediterranean Diet That Is Inversely Associated with Visceral Adiposity and Cardiovascular Risk: The Chrono Med Diet Score (CMDS)

Adherence to the Mediterranean diet (MedDiet) leads to reduction of mortality from all causes, especially in subjects with cardiovascular disease, obesity, and diabetes. Numerous scores have been proposed to evaluate the adherence to MedDiet, mainly focused on eating habits. In this study, we verified whether existing validated MedDiet scores, namely, MEDI-LITE and the Mediterranean Diet Score (MDS), could be associated with visceral adiposity. Failing to find a significant association with adiposity, we proposed the validation of a new, easy-to-use adherence questionnaire, the Chrono Med-Diet score (CMDS). CMDS contains eleven food categories, including chronobiology of dietary habits and physical activity. Compared to the MEDI-LITE score and MDS, low values of CMDS are linked to increased waist circumference (WC) and dysmetabolic conditions. CMDS was also inversely correlated with cardiovascular risk (CVR), as well as Fatty Liver Index (FLI). In conclusion, the CMDS is a novel questionnaire to study the adherence to the MedDiet that, focusing on type and timing of carbohydrates intake, has the peculiar capability of capturing subjects with abdominal obesity, thus being an easy-to-use instrument of personalized medicine.

A New Approach to Personalized Nutrition: Postprandial Glycemic Response and its Relationship to Gut Microbiota

A prolonged and elevated postprandial glucose response (PPGR) is now considered a main factor contributing for the development of metabolic syndrome and type 2 diabetes, which could be prevented by dietary interventions. However, dietary recommendations to prevent alterations in PPGR have not always been successful. New evidence has supported that PPGR is not only dependent of dietary factors like the content of carbohydrates, or the glycemic index of the foods, but is also dependent on genetics, body composition, gut microbiota, among others. In recent years, continuous glucose monitoring has made it possible to establish predictions on the effect of different dietary foods on PPGRs through machine learning methods, which use algorithms that integrate genetic, biochemical, physiological and gut microbiota variables for identifying associations between them and clinical variables with aim of personalize dietary recommendations. This has allowed to improve the concept of personalized nutrition, since it is now possible to recommend through these predictions specific dietary foods to prevent elevated PPGRs that are highly variable among individuals. Additional components that can enrich the predictive algorithms are findings of nutrigenomics, nutrigenetics and metabolomics. Thus, this review aims to summarize the evidence of the components that integrate personalized nutrition focused on the prevention of PPGRs, and to show the future of personalized nutrition by laying the groundwork for the development of individualized dietary management and its impact on the improvement of metabolic diseases.

Rationale, Design and Participants Baseline Characteristics of a Crossover Randomized Controlled Trial of the Effect of Replacing SSBs with NSBs versus Water on Glucose Tolerance, Gut Microbiome and Cardiometabolic Risk in Overweight or Obese Adult SSB Consumer: Strategies to Oppose SUGARS with Non-Nutritive Sweeteners or Water (STOP Sugars NOW) Trial and Ectopic Fat Sub-Study

BACKGROUND

Health authorities are near universal in their recommendation to replace sugar-sweetened beverages (SSBs) with water. Non-nutritive sweetened beverages (NSBs) are not as widely recommended as a replacement strategy due to a lack of established benefits and concerns they may induce glucose intolerance through changes in the gut microbiome. The STOP Sugars NOW trial aims to assess the effect of the substitution of NSBs (the "intended substitution") versus water (the "standard of care substitution") for SSBs on glucose tolerance and microbiota diversity.

DESIGN AND METHODS

The STOP Sugars NOW trial (NCT03543644) is a pragmatic, "head-to-head", open-label, crossover, randomized controlled trial conducted in an outpatient setting. Participants were overweight or obese adults with a high waist circumference who regularly consumed ≥1 SSBs daily. Each participant completed three 4-week treatment phases (usual SSBs, matched NSBs, or water) in random order, which were separated by ≥4-week washout. Blocked randomization was performed centrally by computer with allocation concealment. Outcome assessment was blinded; however, blinding of participants and trial personnel was not possible. The two primary outcomes are oral glucose tolerance (incremental area under the curve) and gut microbiota beta-diversity (weighted UniFrac distance). Secondary outcomes include related markers of adiposity and glucose and insulin regulation. Adherence was assessed by objective biomarkers of added sugars and non-nutritive sweeteners and self-report intake. A subset of participants was included in an Ectopic Fat sub-study in which the primary outcome is intrahepatocellular lipid (IHCL) by 1H-MRS. Analyses will be according to the intention to treat principle.

BASELINE RESULTS

Recruitment began on 1 June 2018, and the last participant completed the trial on 15 October 2020. We screened 1086 participants, of whom 80 were enrolled and randomized in the main trial and 32 of these were enrolled and randomized in the Ectopic Fat sub-study. The participants were predominantly middle-aged (mean age 41.8 ± SD 13.0 y) and had obesity (BMI of 33.7 ± 6.8 kg/m2) with a near equal ratio of female: male (51%:49%). The average baseline SSB intake was 1.9 servings/day. SSBs were replaced with matched NSB brands, sweetened with either a blend of aspartame and acesulfame-potassium (95%) or sucralose (5%).

CONCLUSIONS

Baseline characteristics for both the main and Ectopic Fat sub-study meet our inclusion criteria and represent a group with overweight or obesity, with characteristics putting them at risk for type 2 diabetes. Findings will be published in peer-reviewed open-access medical journals and provide high-level evidence to inform clinical practice guidelines and public health policy for the use NSBs in sugars reduction strategies.

TRIAL REGISTRATION

ClinicalTrials.gov identifier, NCT03543644.

Eating, diet, and nutrition for the treatment of non-alcoholic fatty liver disease

Nutrition and dietary interventions are a central component in the pathophysiology, but also a cornerstone in the management of patients with non-alcoholic fatty liver disease (NAFLD). Summarizing our rapidly advancing understanding of how our diet influences our metabolism and focusing on specific effects on the liver, we provide a comprehensive overview of dietary concepts to counteract the increasing burden of NAFLD. Specifically, we emphasize the importance of dietary calorie restriction independently of the macronutrient composition together with adherence to a Mediterranean diet low in added fructose and processed meat that seems to exert favorable effects beyond calorie restriction. Also, we discuss intermittent fasting as a type of diet specifically tailored to decrease liver fat content and increase ketogenesis, awaiting future study results in NAFLD. Finally, personalized dietary recommendations could be powerful tools to increase the effectiveness of dietary interventions in patients with NAFLD considering the genetic background and the microbiome, among others.

Nutritional benefits of sourdoughs: A systematic review

Food fermentation using sourdough-i.e., consortia of lactic bacteria and yeasts-is increasingly considered among the public as a natural transformation yielding nutritional benefits; however, it is unclear whether its alleged properties are validated by science. The aim of this study was to systematically review the clinical evidence related to the effect of sourdough bread on health. Bibliographic searches were performed in 2 different databases (The Lens and PubMed) up to February 2022. Eligible studies were randomized controlled trials involving adults, healthy or not, given any type of sourdough bread compared with those given any type of yeast bread. A total of 573 articles were retrieved and investigated, of which 25 clinical trials met the inclusion criteria. The 25 clinical trials included a total of 542 individuals. The main outcomes investigated in the retrieved studies were glucose response (N = 15), appetite (N = 3), gastrointestinal markers (N = 5), and cardiovascular markers (N = 2). Overall, it is currently difficult to establish a clear consensus with regards to the beneficial effects of sourdough per se on health when compared with other types of bread because a variety of factors, such as the microbial composition of sourdough, fermentation parameters, cereals, and flour types potentially influence the nutritional properties of bread. Nonetheless, in studies using specific strains and fermentation conditions, significant improvements were observed in parameters related to glycemic response, satiety, or gastrointestinal comfort after bread ingestion. The reviewed data suggest that sourdough has great potential to produce a variety of functional foods; however, its complex and dynamic ecosystem requires further standardization to conclude its clinical health benefits.

Randomized controlled trial demonstrates response to a probiotic intervention for metabolic syndrome that may correspond to diet

An individual's immune and metabolic status is coupled to their microbiome. Probiotics offer a promising, safe route to influence host health, possibly via the microbiome. Here, we report an 18-week, randomized prospective study that explores the effects of a probiotic vs. placebo supplement on 39 adults with elevated parameters of metabolic syndrome. We performed longitudinal sampling of stool and blood to profile the human microbiome and immune system. While we did not see changes in metabolic syndrome markers in response to the probiotic across the entire cohort, there were significant improvements in triglycerides and diastolic blood pressure in a subset of probiotic arm participants. Conversely, the non-responders had increased blood glucose and insulin levels over time. The responders had a distinct microbiome profile at the end of the intervention relative to the non-responders and placebo arm. Importantly, diet was a key differentiating factor between responders and non-responders. Our results show participant-specific effects of a probiotic supplement on improving parameters of metabolic syndrome and suggest that dietary factors may enhance stability and efficacy of the supplement.

Personalized Diets based on the Gut Microbiome as a Target for Health Maintenance: from Current Evidence to Future Possibilities

Recently, the concept of personalized nutrition has been developed, which states that food components do not always lead to the same metabolic responses, but vary from person to person. Although this concept has been studied based on individual genetic backgrounds, researchers have recently explored its potential role in the gut microbiome. The gut microbiota physiologically communicates with humans by forming a bidirectional relationship with the micronutrients, macronutrients, and phytochemicals consumed by the host. Furthermore, the gut microbiota can vary from person to person and can be easily shifted by diet. Therefore, several recent studies have reported the application of personalized nutrition to intestinal microflora. This review provides an overview of the interaction of diet with the gut microbiome and the latest evidence in understanding the inter-individual differences in dietary responsiveness according to individual baseline gut microbiota and microbiome-associated dietary intervention in diseases. The diversity of the gut microbiota and the presence of specific microorganisms can be attributed to physiological differences following dietary intervention. The difference in individual responsiveness based on the gut microbiota has the potential to become an important research approach for personalized nutrition and health management, although further well-designed large-scale studies are warranted.

Machine Learning in Nutrition Research

Data currently generated in the field of nutrition are becoming increasingly complex and high-dimensional, bringing with them new methods of data analysis. The characteristics of machine learning (ML) make it suitable for such analysis and thus lend itself as an alternative tool to deal with data of this nature. ML has already been applied in important problem areas in nutrition, such as obesity, metabolic health, and malnutrition. Despite this, experts in nutrition are often without an understanding of ML, which limits its application and therefore potential to solve currently open questions. The current article aims to bridge this knowledge gap by supplying nutrition researchers with a resource to facilitate the use of ML in their research. ML is first explained and distinguished from existing solutions, with key examples of applications in the nutrition literature provided. Two case studies of domains in which ML is particularly applicable, precision nutrition and metabolomics, are then presented. Finally, a framework is outlined to guide interested researchers in integrating ML into their work. By acting as a resource to which researchers can refer, we hope to support the integration of ML in the field of nutrition to facilitate modern research.

Allergenic food protein consumption is associated with systemic IgG antibody responses in non-allergic individuals

Although food-directed immunoglobulin E (IgE) has been studied in the context of allergies, the prevalence and magnitude of IgG responses against dietary antigens are incompletely characterized in the general population. Here, we measured IgG binding against food and environmental antigens obtained from allergen databases and the immune epitope database (IEDB), represented in a phage displayed library of 58,233 peptides. By profiling blood samples of a large cohort representing the average adult Israeli population (n = 1,003), we showed that many food antigens elicited systemic IgG in up to 50% of individuals. Dietary intake of specific food protein correlated with antibody binding, suggesting that diet can shape the IgG epitope repertoire. Our work documents abundant systemic IgG responses against food antigens and provides a reference map of the exact immunogenic epitopes on a population scale, laying the foundation to unravel the role of food- and environmental antigen-directed antibody binding in disease contexts.

Efficacy of the Digital Therapeutic sinCephalea in the prophylaxis of migraine in patients with episodic migraine: study protocol for a digital, randomized, open-label, standard treatment controlled trial

BACKGROUND

The German government implemented the Digital Healthcare Act in order to bring Digital Therapeutics into standard medical care. This is one of the first regulatory pathways to reimbursement for Digital Therapeutics (DTx). The Digital Therapeutic sinCephalea is intended to act as a prophylactic treatment of migraine by reducing the migraine days. For this, sinCephalea determines personalized nutritional recommendations using continuous glucose monitoring (CGM) data and enables the patients to follow a personalized low-glycemic nutrition. Migraine is a headache disorder with the highest socioeconomic burden. Emerging evidence shows that CGM-based personalized nutritional recommendations are of prophylactic use in episodic migraine. However, prospective data are yet missing to demonstrate clinical effectiveness. This study is designed to fill this gap.

METHODS

Patients between 18 and 65 years of age with proven migraine and a minimal disease severity of 3 migraine days per month are included. After a 4-week baseline phase as a pre-study, patients are randomized to the DTx intervention or a waiting-list control. The objective of the study is to show differences between the intervention and control groups regarding the change of migraine symptoms and of effects of migraine on daily life.

DISCUSSION

To our knowledge, this is the first systematic clinical trial with a fully digital program to enable patients with migraine to follow a personalized low-glycemic nutrition in order to reduce their number of migraine days and the migraine-induced impact on daily life. Designing a clinical study using a digital intervention includes some obstacles, which are addressed in this study approach.

TRIAL REGISTRATION

German Registry of Clinical Studies (Deutsches Register Klinischer Studien) DRKS-ID DRKS00024657. Registered on March 8, 2021.

Microbiome-Targeted Therapies as an Adjunct to Traditional Weight Loss Interventions: A Systematic Review and Meta-Analysis

Objective

This study evaluated the effect of microbiome-targeted therapies (pre-, pro-, and synbiotics) on weight loss and other anthropometric outcomes when delivered as an adjunct to traditional weight loss interventions in overweight and obese adults.

Methods

A systematic review of three databases (Medline [PubMed], Embase, and the Cochrane Central Register of Controlled Trials) was performed to identify randomized controlled trials published between January 1, 2010 and December 31, 2020, that evaluated anthropometric outcomes following microbiome-targeted supplements in combination with dietary or dietary and exercise interventions. The pooled mean difference (MD) between treatment and control groups was calculated using a random effects model.

Results

Twenty-one trials with 1233 adult participants (76.4% female) with overweight or obesity were included. Separate meta-analyses were conducted for probiotics (n=11 trials) and synbiotics (n=10 trials) on each anthropometric outcome; prebiotics were excluded as only a single study was found. Patient characteristics and methodologies varied widely between studies. All studies incorporated some degree of caloric restriction, while only six studies included recommendations for adjunct exercise. Compared with dietary or dietary and exercise interventions only, probiotics resulted in reductions in body weight (MD: -0.73 kg; 95% confidence interval [CI]: -1.02 to -0.44, p < 0.001), fat mass (MD: -0.61 kg; 95% CI: -0.77 to -0.45; p<0.001) and waist circumference (MD: -0.53 cm; 95% CI: -0.99 to -0.07, p=0.024) while synbiotics resulted in reductions in fat mass (MD: -1.53 kg; 95% CI: -2.95 to -0.12, p=0.034) and waist circumference (MD: -1.31 cm; 95% CI: -2.05 to -0.57, p<0.001).

Conclusion

This analysis indicates that microbiome-targeted supplements may enhance weight loss and other obesity outcomes in adults when delivered as an adjunct to dietary or dietary and exercise interventions. Personalized therapy to include microbiome-targeted supplements may help to optimize weight loss in overweight and obese individuals.

Gut-liver axis: Pathophysiological concepts and clinical implications

Bidirectional crosstalk along the gut-liver axis controls gastrointestinal health and disease and exploits environmental and host mediators. Nutrients, microbial antigens, metabolites, and bile acids regulate metabolism and immune responses in the gut and liver, which reciprocally shape microbial community structure and function. Perturbation of such host-microbe interactions is observed in a variety of experimental liver diseases and is facilitated by an impaired intestinal barrier, which is fueling hepatic inflammation and disease progression. Clinical evidence describes perturbation of the gut-liver crosstalk in non-alcoholic fatty liver disease, alcoholic liver disease, and primary sclerosing cholangitis. In liver cirrhosis, a common sequela of these diseases, the intestinal microbiota and microbial pathogen-associated molecular patterns constitute liver inflammation and clinical complications, such as hepatic encephalopathy. Understanding the intricate metabolic interplay between the gut and liver in health and disease opens an avenue for targeted therapies in the future, which is probed in controlled clinical trials.

Precision nutrition in diabetes: when population-based dietary advice gets personal

Diet plays a fundamental role in maintaining long-term health, with healthful diets being endorsed by current dietary guidelines for the prevention and management of type 2 diabetes. However, the response to dietary interventions varies widely, highlighting the need for refinement and personalisation beyond population-based 'one size fits all'. This article reviews the clinical evidence supporting precision nutrition as a fundamental approach for dietary advice in diabetes. Further, it proposes a framework for the eventual implementation of precision nutrition and discusses key challenges for the application of this approach in the prevention of diabetes. One implication of this approach is that precision nutrition would not exclude the parallel goal of population-based healthy dietary advice. Nevertheless, the shift in prioritising precision nutrition is needed to reflect the dynamic nature of responses to dietary interventions that vary among individuals and change over the life course.

Integrated gut microbiome and metabolome analyses identified fecal biomarkers for bowel movement regulation by Bifidobacterium longum BB536 supplementation: A RCT

Background

Bifidobacterium longum BB536 supplementation can be used to regulate bowel movements in various people, including healthy subjects and patients with irritable bowel syndrome (IBS); however, individuals vary in their responses to B. longum BB536 treatment. One putative factor is the gut microbiota; recent studies have reported that the gut microbiota mediates the effects of diet or drugs on the host. Here, we investigated intestinal features, such as the microbiome and metabolome, related to B. longum BB536 effectiveness in increasing bowel movement frequency.

Results

A randomized, double-blind controlled crossover trial was conducted with 24 adults who mainly tended to be constipated. The subjects received a two-week dietary intervention consisting of B. longum BB536 in acid-resistant seamless capsules or similarly encapsulated starch powder as the placebo control. Bowel movement frequency was recorded daily, and fecal samples were collected at several time points, and analyzed by metabologenomic approach that consists of an integrated analysis of metabolome data obtained using mass spectrometry and microbiome data obtained using high-throughput sequencing. There were differences among subjects in B. longum intake-induced bowel movement frequency. The responders were predicted by machine learning based on the microbiome and metabolome features of the fecal samples collected before B. longum intake. The abundances of eight bacterial genera were significantly different between responders and nonresponders.

Conclusions

Intestinal microbiome and metabolome profiles might be utilized as potential markers of improved bowel movement after B. longum BB536 supplementation. These findings have implications for the development of personalized probiotic treatments.

Personalized nutrition, microbiota, and metabolism: A triad for eudaimonia

During the previous few years, the relationship between the gut microbiota, metabolic disorders, and diet has come to light, especially due to the understanding of the mechanisms that particularly link the gut microbiota with obesity in animal models and clinical trials. Research has led to the understanding that the responses of individuals to dietary inputs vary remarkably therefore no single diet can be suggested to every individual. The variations are attributed to differences in the microbiome and host characteristics. In general, it is believed that the immanent nature of host-derived factors makes them difficult to modulate. However, diet can more easily shape the microbiome, potentially influencing human physiology through modulation of digestion, absorption, mucosal immune response, and the availability of bioactive compounds. Thus, diet could be useful to influence the physiology of the host, as well as to ameliorate various disorders. In the present study, we have described recent developments in understanding the disparities of gut microbiota populations between individuals and the primary role of diet-microbiota interactions in modulating human physiology. A deeper understanding of these relationships can be useful for proposing personalized nutrition strategies and nutrition-based therapeutic interventions to improve human health.

The Metabolic Role and Therapeutic Potential of the Microbiome

We are host to an assembly of microorganisms that vary in structure and function along the length of the gut and from the lumen to the mucosa. This ecosystem is collectively known as the gut microbiota and significant efforts have been spent during the past 2 decades to catalog and functionally describe the normal gut microbiota and how it varies during a wide spectrum of disease states. The gut microbiota is altered in several cardiometabolic diseases and recent work has established microbial signatures that may advance disease. However, most research has focused on identifying associations between the gut microbiota and human diseases states and to investigate causality and potential mechanisms using cells and animals. Since the gut microbiota functions on the intersection between diet and host metabolism, and can contribute to inflammation, several microbially produced metabolites and molecules may modulate cardiometabolic diseases. Here we discuss how the gut bacterial composition is altered in, and can contribute to, cardiometabolic disease, as well as how the gut bacteria can be targeted to treat and prevent metabolic diseases.