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Diet has a pivotal role in shaping the composition, function and diversity of the gut microbiome, with various diets having a profound impact on the stability, functionality and diversity of the microbial community within our gut. Understanding the profound impact of varied diets on the microbiome is crucial, as it will enable us not only to make well-informed dietary decisions for better metabolic and intestinal health, but also to prevent and slow the onset of specific diet-related diseases that stem from suboptimal diets. In this Review, we explore how geographical location affects the gut microbiome and how different diets shape its composition and function. We examine the mechanisms by which whole dietary regimes, such as the Mediterranean diet, high-fibre diet, plant-based diet, high-protein diet, ketogenic diet and Western diet, influence the gut microbiome. Furthermore, we underscore the need for exhaustive studies to better understand the causal relationship between diet, host and microorganisms for the development of precision nutrition and microbiome-based therapies.In this Review, Stanton and colleagues examine the effect of different whole diets on the composition and function of the gut microbiome and explore how the diet–microbiome relationship influences human health and the progression of different chronic diseases.

With the continued interest in the role of the gut microbiota in health, attention has now turned to how to harness the microbiota for the benefit of the host. This Consensus Statement outlines the definition and scope of the term 'prebiotic' as determined by an expert panel convened by the International Scientific Association for Probiotics and Prebiotics in December 2016. In December 2016, a panel of experts in microbiology, nutrition and clinical research was convened by the International Scientific Association for Probiotics and Prebiotics to review the definition and scope of prebiotics. Consistent with the original embodiment of prebiotics, but aware of the latest scientific and clinical developments, the panel updated the definition of a prebiotic: a substrate that is selectively utilized by host microorganisms conferring a health benefit. This definition expands the concept of prebiotics to possibly include non-carbohydrate substances, applications to body sites other than the gastrointestinal tract, and diverse categories other than food. The requirement for selective microbiota-mediated mechanisms was retained. Beneficial health effects must be documented for a substance to be considered a prebiotic. The consensus definition applies also to prebiotics for use by animals, in which microbiota-focused strategies to maintain health and prevent disease is as relevant as for humans. Ultimately, the goal of this Consensus Statement is to engender appropriate use of the term 'prebiotic' by relevant stakeholders so that consistency and clarity can be achieved in research reports, product marketing and regulatory oversight of the category. To this end, we have reviewed several aspects of prebiotic science including its development, health benefits and legislation.

Vitamin D testing and the use of vitamin D supplements have increased substantially in recent years. Currently, the role of vitamin D supplementation, and the optimal vitamin D dose and status, is a subject of debate, because large interventional studies have been unable to show a clear benefit (in mostly vitamin D replete populations). This may be attributed to limitations in trial design, as most studies did not meet the basic requirements of a nutrient intervention study, including vitamin D-replete populations, too small sample sizes, and inconsistent intervention methods regarding dose and metabolites. Vitamin D deficiency (serum 25-hydroxyvitamin D [25(OH)D] < 50 nmol/L or 20 ng/ml) is associated with unfavorable skeletal outcomes, including fractures and bone loss. A 25(OH)D level of >50 nmol/L or 20 ng/ml is, therefore, the primary treatment goal, although some data suggest a benefit for a higher threshold. Severe vitamin D deficiency with a 25(OH)D concentration below <30 nmol/L (or 12 ng/ml) dramatically increases the risk of excess mortality, infections, and many other diseases, and should be avoided whenever possible. The data on a benefit for mortality and prevention of infections, at least in severely deficient individuals, appear convincing. Vitamin D is clearly not a panacea, and is most likely efficient only in deficiency. Given its rare side effects and its relatively wide safety margin, it may be an important, inexpensive, and safe adjuvant therapy for many diseases, but future large and well-designed studies should evaluate this further. A worldwide public health intervention that includes vitamin D supplementation in certain risk groups, and systematic vitamin D food fortification to avoid severe vitamin D deficiency, would appear to be important. In this narrative review, the current international literature on vitamin D deficiency, its relevance, and therapeutic options is discussed.

Since the renaissance of microbiome research in the past decade, much insight has accumulated in comprehending forces shaping the architecture and functionality of resident microorganisms in the human gut. Of the multiple host-endogenous and host-exogenous factors involved, diet emerges as a pivotal determinant of gut microbiota community structure and function. By introducing dietary signals into the nexus between the host and its microbiota, nutrition sustains homeostasis or contributes to disease susceptibility. Herein, we summarize major concepts related to the effect of dietary constituents on the gut microbiota, highlighting chief principles in the diet–microbiota crosstalk. We then discuss the health benefits and detrimental consequences that the interactions between dietary and microbial factors elicit in the host. Finally, we present the promises and challenges that arise when seeking to incorporate microbiome data in dietary planning and portray the anticipated revolution that the field of nutrition is facing upon adopting these novel concepts.

Time-restricted feeding (TRF) improves metabolic health. Both early TRF (eTRF, food intake restricted to the early part of the day) and mid-day TRF (mTRF, food intake restricted to the middle of the day) have been shown to have metabolic benefits. However, the two regimens have yet to be thoroughly compared. We conducted a five-week randomized trial to compare the effects of the two TRF regimens in healthy individuals without obesity (ChiCTR2000029797). The trial has completed. Ninety participants were randomized to eTRF (n=30), mTRF (n=30), or control groups (n=30) using a computer-based random-number generator. Eighty-two participants completed the entire five-week trial and were analyzed (28 in eTRF, 26 in mTRF, 28 in control groups). The primary outcome was the change in insulin resistance. Researchers who assessed the outcomes were blinded to group assignment, but participants and care givers were not. Here we show that eTRF was more effective than mTRF at improving insulin sensitivity. Furthermore, eTRF, but not mTRF, improved fasting glucose, reduced total body mass and adiposity, ameliorated inflammation, and increased gut microbial diversity. No serious adverse events were reported during the trial. In conclusion, eTRF showed greater benefits for insulin resistance and related metabolic parameters compared with mTRF. Clinical Trial Registration URL: http://www.chictr.org.cn/showproj.aspx?proj=49406 . Time-restricted eating, both early (eTRF) and mid-day (mTRF), have been shown to have metabolic benefits. Here the authors report a randomized controlled trial to compare the effects of eTRF and mTRF in healthy volunteers without obesity, and find that eTRF is more effective in improving the primary outcome insulin sensitivity.

Conceptual scientific and medical advances have led to a recent realization that there may be no single, one-size-fits-all diet and that differential human responses to dietary inputs may rather be driven by unique and quantifiable host and microbiome features. Integration of these person-specific host and microbiome readouts into actionable modules may complement traditional food measurement approaches in devising diets that are of benefit to the individual. Although many host-derived factors are hardwired and difficult to modulate, the microbiome may be more readily reshaped by environmental factors such as dietary exposures and is increasingly recognized to potentially impact human physiology by participating in digestion, the absorption of nutrients, shaping of the mucosal immune response and the synthesis or modulation of a plethora of potentially bioactive compounds. Thus, diet-induced microbiota alterations may be harnessed in order to induce changes in host physiology, including disease development and progression. However, major limitations in ‘big-data’ processing and analysis still limit our interpretive and translational capabilities concerning these person-specific host, microbiome and diet interactions. In this Review, we describe the latest advances in understanding diet–microbiota interactions, the individuality of gut microbiota composition and how this knowledge could be harnessed for personalized nutrition strategies to improve human health.

Bioelectrical impedance analysis is an extremely popular method for assessment of body composition. Despite its wide-spread use over the past thirty years, its accuracy and clinical value is still questioned. Most frequently, criticisms focus on its purported poor absolute accuracy and that different impedance analysers or prediction equations fail to measure body composition identically. This perspective review highlights that the magnitude of errors associated with impedance methods are not dissimilar to those observed for so-called gold standard methods. It is argued that the focus on statistically significant but small differences between methods can obscure operational equivalence and that such differences may be of minor clinical significance. Finally, the need for better standardization of protocols and the need for consensus on what is a minimal clinically important difference between methods is highlighted.

Increased intake of dietary carbohydrate that is fermented in the colon by the microbiota has been reported to decrease body weight, although the mechanism remains unclear. Here we use in vivo 11 C-acetate and PET-CT scanning to show that colonic acetate crosses the blood–brain barrier and is taken up by the brain. Intraperitoneal acetate results in appetite suppression and hypothalamic neuronal activation patterning. We also show that acetate administration is associated with activation of acetyl-CoA carboxylase and changes in the expression profiles of regulatory neuropeptides that favour appetite suppression. Furthermore, we demonstrate through 13 C high-resolution magic-angle-spinning that 13 C acetate from fermentation of 13 C-labelled carbohydrate in the colon increases hypothalamic 13 C acetate above baseline levels. Hypothalamic 13 C acetate regionally increases the 13 C labelling of the glutamate–glutamine and GABA neuroglial cycles, with hypothalamic 13 C lactate reaching higher levels than the ‘remaining brain’. These observations suggest that acetate has a direct role in central appetite regulation. The consumption of fermentable carbohydrates, or fibre, is associated with weight loss. Here the authors show that the metabolite acetate, created by fermentation of fibre in the mouse colon, is taken up into the brain where it induces appetite-suppressing neuronal activity in the hypothalamus.

Knowledge of the effect of foods on gut microbiota composition and functionality is expanding. To isolate the effect of single foods and/or single nutrients (i.e., fiber, polyphenols), this protocol describes an in vitro batch fermentation procedure to be carried out after an in vitro gastrointestinal digestion. Therefore, this is an extension of the previous protocol described by Brodkorb et al. (2019) for studying in vitro digestion. The current protocol uses an oligotrophic fermentation medium with peptone and a high concentration of fecal inoculum from human fecal samples both to provide the microbiota and as the main source of nutrients for the bacteria. This protocol is recommended for screening work to be performed when many food samples are to be studied. It has been used successfully to study gut microbiota fermentation of different foodstuffs, giving insights into their functionality, community structure or ability to degrade particular substances, which can contribute to the development of personalized nutrition strategies. The procedure does not require a specific level of expertise. The protocol takes 4–6 h for preparation of fermentation tubes and 20 h for incubation. This extension of a previous in vitro digestion protocol provides a subsequent in vitro batch fermentation stage that is carried out afterward to enable investigation of the effect of food on the gut microbiome.

Despite the accumulating evidence that increased consumption of ultra-processed food has adverse health implications, it remains difficult to decide what constitutes processed food. Indeed, the current processing-based classification of food has limited coverage and does not differentiate between degrees of processing, hindering consumer choices and slowing research on the health implications of processed food. Here we introduce a machine learning algorithm that accurately predicts the degree of processing for any food, indicating that over 73% of the US food supply is ultra-processed. We show that the increased reliance of an individual’s diet on ultra-processed food correlates with higher risk of metabolic syndrome, diabetes, angina, elevated blood pressure and biological age, and reduces the bio-availability of vitamins. Finally, we find that replacing foods with less processed alternatives can significantly reduce the health implications of ultra-processed food, suggesting that access to information on the degree of processing, currently unavailable to consumers, could improve population health. Evidence suggests that increased consumption of ultra-processed food has adverse health implications, however, it remains difficult to classify processed food. Here, the authors introduce FPro , a machine learning-based score predicting the degree of food processing.