Gut microbiota predicts body fat change following a low-energy diet: a PREVIEW intervention study

Yoyo Dieting, Post-Obesity Weight Loss, and Their Relationship with Gut Health

Excessive body weight is associated with many chronic metabolic diseases and weight loss, so far, remains the gold standard treatment. However, despite tremendous efforts exploring optimal treatments for obesity, many individuals find losing weight and maintaining a healthy body weight difficult. Weight loss is often not sustainable resulting in weight regain and subsequent efforts to lose weight. This cyclic pattern of weight loss and regain is termed "yoyo dieting" and predisposes individuals to obesity and metabolic comorbidities. How yoyo dieting might worsen obesity complications during the weight recurrence phase remains unclear. In particular, there is limited data on the role of the gut microbiome in yoyo dieting. Gut health distress, especially gut inflammation and microbiome perturbation, is strongly associated with metabolic dysfunction and disturbance of energy homeostasis in obesity. In this review, we summarise current evidence of the crosstalk between the gastrointestinal system and energy balance, and the effects of yoyo dieting on gut inflammation and gut microbiota reshaping. Finally, we focus on the potential effects of post-dieting weight loss in improving gut health and identify current knowledge gaps within the field, including gut-derived peptide hormones and their potential suitability as targets to combat weight regain, and how yoyo dieting and associated changes in the microbiome affect the gut barrier and the enteric nervous system, which largely remain to be determined.

The Future of Obesity Management through Precision Nutrition: Putting the Individual at the Center

PURPOSE OF REVIEW: The prevalence of obesity continues to rise steadily. While obesity management typically relies on dietary and lifestyle modifications, individual responses to these interventions vary widely. Clinical guidelines for overweight and obesity stress the importance of personalized approaches to care. This review aims to underscore the role of precision nutrition in delivering tailored interventions for obesity management. RECENT FINDINGS: Recent technological strides have expanded our ability to detect obesity-related genetic polymorphisms, with machine learning algorithms proving pivotal in analyzing intricate genomic data. Machine learning algorithms can also predict postprandial glucose, triglyceride, and insulin levels, facilitating customized dietary interventions and ultimately leading to successful weight loss. Additionally, given that adherence to dietary recommendations is one of the key predictors of weight loss success, employing more objective methods for dietary assessment and monitoring can enhance sustained long-term compliance. Biomarkers of food intake hold promise for a more objective dietary assessment. Acknowledging the multifaceted nature of obesity, precision nutrition stands poised to transform obesity management by tailoring dietary interventions to individuals' genetic backgrounds, gut microbiota, metabolic profiles, and behavioral patterns. However, there is insufficient evidence demonstrating the superiority of precision nutrition over traditional dietary recommendations. The integration of precision nutrition into routine clinical practice requires further validation through randomized controlled trials and the accumulation of a larger body of evidence to strengthen its foundation.

Gut Microbiome Wellness Index 2 enhances health status prediction from gut microbiome taxonomic profiles

Recent advancements in translational gut microbiome research have revealed its crucial role in shaping predictive healthcare applications. Herein, we introduce the Gut Microbiome Wellness Index 2 (GMWI2), an enhanced version of our original GMWI prototype, designed as a standardized disease-agnostic health status indicator based on gut microbiome taxonomic profiles. Our analysis involves pooling existing 8069 stool shotgun metagenomes from 54 published studies across a global demographic landscape (spanning 26 countries and six continents) to identify gut taxonomic signals linked to disease presence or absence. GMWI2 achieves a cross-validation balanced accuracy of 80% in distinguishing healthy (no disease) from non-healthy (diseased) individuals and surpasses 90% accuracy for samples with higher confidence (i.e., outside the "reject option"). This performance exceeds that of the original GMWI model and traditional species-level α-diversity indices, indicating a more robust gut microbiome signature for differentiating between healthy and non-healthy phenotypes across multiple diseases. When assessed through inter-study validation and external validation cohorts, GMWI2 maintains an average accuracy of nearly 75%. Furthermore, by reevaluating previously published datasets, GMWI2 offers new insights into the effects of diet, antibiotic exposure, and fecal microbiota transplantation on gut health. Available as an open-source command-line tool, GMWI2 represents a timely, pivotal resource for evaluating health using an individual's unique gut microbial composition.

Deep serum lipidomics identifies evaluative and predictive biomarkers for individualized glycemic responses following low-energy diet-induced weight loss: a PREVention of diabetes through lifestyle Intervention and population studies in Europe and around the World (PREVIEW) substudy

BACKGROUND

Weight loss through lifestyle interventions, notably low-energy diets, offers glycemic benefits in populations with overweight-associated prediabetes. However, >50% of these individuals fail to achieve normoglycemia after weight loss. Circulating lipids hold potential for evaluating dietary impacts and predicting diabetes risk.

OBJECTIVES

This study sought to identify serum lipids that could serve as evaluative or predictive biomarkers for individual glycemic changes following diet-induced weight loss.

METHODS

We studied 104 participants with overweight-associated prediabetes, who lost ≥8% weight via a low-energy diet over 8 wk. High-coverage lipidomics was conducted in serum samples before and after the dietary intervention. The lipidomic recalibration was assessed using differential lipid abundance comparisons and partial least squares discriminant analyses. Associations between lipid changes and clinical characteristics were determined by Spearman correlation and Bootstrap Forest of ensemble machine learning model. Baseline lipids, predictive of glycemic parameters changes postweight loss, were assessed using Bootstrap Forest analyses.

RESULTS

We quantified 439 serum lipid species and 9 related organic acids. Dietary intervention significantly reduced diacylglycerols, ceramides, lysophospholipids, and ether-linked phosphatidylethanolamine. In contrast, acylcarnitines, short-chain fatty acids, organic acids, and ether-linked phosphatidylcholine increased significantly. Changes in certain lipid species (e.g., saturated and monounsaturated fatty acid-containing glycerolipids, sphingadienine-based very long-chain sphingolipids, and organic acids) were closely associated with clinical glycemic parameters. Six baseline bioactive sphingolipids primarily predicted changes in fasting plasma glucose. In addition, a number of baseline lipid species, mainly diacylglycerols and triglycerides, were predictive of clinical changes in hemoglobin A1c, insulin and homeostasis model assessment of insulin resistance.

CONCLUSIONS

Newly discovered serum lipidomic alterations and the associated changes in lipid-clinical variables suggest broad metabolic reprogramming related to diet-mediated glycemic control. Novel lipid predictors of glycemic outcomes could facilitate early stratification of individuals with prediabetes who are metabolically less responsive to weight loss, enabling more tailored intervention strategies beyond 1-size-fits-all lifestyle modification advice. The PREVIEW lifestyle intervention study was registered at clinicaltrials.gov as NCT01777893 (https://clinicaltrials.gov/study/NCT01777893).

Effect of time-restricted eating regimen on weight loss is mediated by gut microbiome

Time-restricted eating (TRE) is a promising obesity management strategy, but weight-loss efficacy varies among participants, and the underlying mechanism is unclear. The study aimed to investigate the role of gut microbiota in weight-loss response during long-term TRE intervention. We analyzed data from 51 obese adults in a 12-month TRE program, categorizing them into distinct weight loss groups (DG) and moderate weight loss groups (MG) based on their TRE responses. Shotgun metagenomic sequencing analysis revealed a significant increase in species closely associated with weight loss effectiveness and metabolic parameter changes in the DG group. Pathways related to fatty acid biosynthesis, glycogen biosynthesis, and nucleotide metabolism were reduced in the DG group and enhanced in the MG group. Next, we identified nine specific species at baseline that contributed better responses to TRE intervention and significant weight loss. Collectively, gut microbiota contributes to responsiveness heterogeneity in TRE and can predict weight-loss effectiveness.

Role of the Intestine and Its Gut Microbiota in Metabolic Syndrome and Obesity

The metabolic syndrome (MetSyn) is currently one of the biggest global health challenges because of its impact on public health. MetSyn includes the cluster of metabolic disorders including obesity, high blood pressure, hyperglycemia, high triglyceride levels, and hepatic steatosis. Together, these abnormalities increase the cardiovascular risk of individuals and pose a threat to healthcare systems worldwide. To better understand and address this complex issue, recent research has been increasingly focusing on unraveling the delicate interplay between metabolic disorders and the intestines and more specifically our gut microbiome. The gut microbiome entails all microorganisms inhabiting the gastrointestinal tract and plays a pivotal role in metabolic processes and overall health of its host. Emerging evidence proves an association between the gut microbiome composition and aspects of MetSyn, such as obesity. Understanding these relationships is crucial because they offer valuable insights into the mechanisms underlying development and progression of metabolic disorders and possible treatment options. Yet, how should we interpret this relationship? This review focuses on the interplay between the gut and MetSyn. In addition, we have reviewed the existing evidence of the gut microbiome and its association with and impact on metabolic disorders, in an attempt to understand the complex interactions and nature of this association. We also explored potential therapeutic options targeting the gut to modify metabolic disorders and obesity.

Yogurt, in the context of a healthy diet, for the prevention and management of diabetes and obesity: a perspective from Argentina

Diabetes is a non-communicable chronic, but preventable, disease whose occurrence is related to unhealthy lifestyles, including inadequate diet. Obesity is a risk factor for diabetes. In Argentina, 12.7% of the population is living with diabetes. In this work, we aimed at giving a perspective on the role of yogurt, as part of a healthy lifestyle, for the prevention and management of obesity and diabetes. The intake of yogurt declined in the last decade in Argentina. In the context of the global diet, the contribution of a moderate increase of yogurt consumption has the potential to improve up to 10% the nutritional density of the Argentine population's diet, given its present low diversity and wide gaps in nutritive foods. The consumption of yogurt can be beneficial in the prevention and management of obesity and T2DM. The ready availability of yogurt and its easy introduction to diverse diets suggests that educating the general public to incorporate this fermented milk as part of a healthy diet may potentially contribute to improved public health through prevention of NCDs and the costs associated with them.

Akkermansia muciniphila: a potential candidate for ameliorating metabolic diseases

Metabolic diseases are comprehensive disease based on obesity. Numerous cumulative studies have shown a certain correlation between the fluctuating abundance of Akkermansia muciniphila and the occurrence of metabolic diseases. A. muciniphila, a potential probiotic candidate colonized in the human intestinal mucus layer, and its derivatives have various physiological functions, including treating metabolic disorders and maintaining human health. This review systematically explicates the abundance change rules of A. muciniphila in metabolic diseases. It also details the high efficacy and specific molecules mechanism of A. muciniphila and its derivatives in treating obesity, type 2 diabetes mellitus, cardiovascular disease, and non-alcoholic fatty liver disease.

Associations between gut microbiota and three prostate diseases: a bidirectional two-sample Mendelian randomization study

According to previous observational researches and clinical trials, the gut microbiota is related to prostate diseases. However, the potential association between gut microbiota and prostate disorders is still uncertain. We first identified groups of gut microbiota based on the phylum, class, order, family, and genus levels from consortium MiBioGen. And we acquired prostate diseases statistics from the FINNGEN study and PRACTICAL consortium. Next, two-sample Mendelian randomization was used to investigate the potential associations between three prevalent prostate disease and gut microbiota. In addition, we performed a reverse MR analysis and Benjamini-Hochberg (BH) test for further research. We investigated the connection between 196 gut microbiota and three prevalent prostate diseases. We identified 42 nominally significant associations and 2 robust causative links. Upon correction for multiple comparisons using the Benjamini-Hochberg procedure, our analysis revealed a positive correlation between the risk of prostatitis and the presence of the taxonomic order Gastranaerophilales. Conversely, the risk of prostate cancer exhibited an inverse correlation with the presence of the taxonomic class Alphaproteobacteria. Our study revealed the potential association between gut microbiota and prostate diseases. The results may be useful in providing new insights for further mechanistic and clinical studies of prostate diseases.

Christensenella minuta, a new candidate next-generation probiotic: current evidence and future trajectories

Background

As the field of probiotic research continues to expand, new beneficial strains are being discovered. The Christensenellaceae family and its newly described member, Christensenella minuta, have been shown to offer great health benefits. We aimed to extensively review the existing literature on these microorganisms to highlight the advantages of their use as probiotics and address some of the most challenging aspects of their commercial production and potential solutions.

Methods

We applied a simple search algorithm using the key words "Christensenellaceae" and "Christensenella minuta" to find all articles reporting the biotherapeutic effects of these microorganisms. Only articles reporting evidence-based results were reviewed.

Results

The review showed that Christensenella minuta has demonstrated numerous beneficial properties and a wider range of uses than previously thought. Moreover, it has been shown to be oxygen-tolerant, which is an immense advantage in the manufacturing and production of Christensenella minuta-based biotherapeutics. The results suggest that Christensenellaceae and Christensenella munita specifically can play a crucial role in maintaining a healthy gut microbiome. Furthermore, Christensenellaceae have been associated with weight management. Preliminary studies suggest that this probiotic strain could have a positive impact on metabolic disorders like diabetes and obesity, as well as inflammatory bowel disease.

Conclusion

Christensenellaceae and Christensenella munita specifically offer immense health benefits and could be used in the management and therapy of a wide range of health conditions. In addition to the impressive biotherapeutic effect, Christensenella munita is oxygen-tolerant, which facilitates commercial production and storage.

Dietary intervention improves metabolic levels in patients with type 2 diabetes through the gut microbiota: a systematic review and meta-analysis

Background

Poor dietary structure plays a pivotal role in the development and progression of type 2 diabetes and is closely associated with dysbiosis of the gut microbiota. Thus, the objective of this systematic review was to assess the impact of dietary interventions on improving gut microbiota and metabolic levels in patients with type 2 diabetes.

Methods

We conducted a systematic review and meta-analysis following the PRISMA 2020 guidelines.

Results

Twelve studies met the inclusion criteria. In comparison to baseline measurements, the high-fiber diet produced substantial reductions in FBG (mean difference -1.15 mmol/L; 95% CI, -2.24 to -0.05; I2 = 94%; P = 0.04), HbA1c (mean difference -0.99%; 95% CI, -1.93 to -0.03; I2 = 89%; P = 0.04), and total cholesterol (mean difference -0.95 mmol/L; 95% CI, -1.57 to -0.33; I2 = 77%; P = 0.003); the high-fat and low-carbohydrate diet led to a significant reduction in HbA1c (mean difference -0.98; 95% CI, -1.50 to -0.46; I2 = 0%; P = 0.0002). Within the experimental group (intervention diets), total cholesterol (mean difference -0.69 mmol/L; 95% CI, -1.27 to -0.10; I2 = 52%; P = 0.02) and LDL-C (mean difference -0.45 mmol/L; 95% CI, -0.68 to -0.22; I2 = 0%; P < 0.0001) experienced significant reductions in comparison to the control group (recommended diets for type 2 diabetes). However, no statistically significant differences emerged in the case of FBG, HbA1c, HOMA-IR, and HDL-C between the experimental and control groups. The high dietary fiber diet triggered an augmented presence of short-chain fatty acid-producing bacteria in the intestines of individuals with T2DM. In addition, the high-fat and low-carbohydrate diet resulted in a notable decrease in Bacteroides abundance while simultaneously increasing the relative abundance of Eubacterium. Compared to a specific dietary pattern, personalized diets appear to result in the production of a greater variety of beneficial bacteria in the gut, leading to more effective blood glucose control in T2D patients.

Conclusion

Dietary interventions hold promise for enhancing metabolic profiles in individuals with T2D through modulation of the gut microbiota. Tailored dietary regimens appear to be more effective than standard diets in improving glucose metabolism. However, given the limited and highly heterogeneous nature of the current sample size, further well-designed and controlled intervention studies are warranted in the future.

Maternal smoking during pregnancy increases the risk of gut microbiome-associated childhood overweight and obesity

Childhood obesity is linked to maternal smoking during pregnancy. Gut microbiota may partially mediate this association and could be potential targets for intervention; however, its role is understudied. We included 1,592 infants from the Canadian Healthy Infants Longitudinal Development Cohort. Data on environmental exposure and lifestyle factors were collected prenatally and throughout the first three years. Weight outcomes were measured at one and three years of age. Stool samples collected at 3 and 12 months were analyzed by sequencing the V4 region of 16S rRNA to profile microbial compositions and magnetic resonance spectroscopy to quantify the metabolites. We showed that quitting smoking during pregnancy did not lower the risk of offspring being overweight. However, exclusive breastfeeding until the third month of age may alleviate these risks. We also reported that maternal smoking during pregnancy significantly increased Firmicutes abundance and diversity. We further revealed that Firmicutes diversity mediates the elevated risk of childhood overweight and obesity linked to maternal prenatal smoking. This effect possibly occurs through excessive microbial butyrate production. These findings add to the evidence that women should quit smoking before their pregnancies to prevent microbiome-mediated childhood overweight and obesity risk, and indicate the potential obesogenic role of excessive butyrate production in early life.

Comparative analysis of fasting effects on the cecum microbiome in three guinea pig breeds: Andina, Inti, and Peru

Guinea pigs have historically been used as a food source and are also an important model for studying the human intestines. Fasting is the act of temporarily stopping the intake of food. This process can alter the microbiota of various animals. This study is the first to investigate the impact of fasting on the cecum microbiome of three guinea pig breeds. We investigated the impact of fasting on the microbiome population structure in the cecum of three guinea pig breeds. This was done by sequencing and analyzing the V4 hypervariable region of the 16S rRNA gene in bacterial communities found in cecum mucosa samples. To achieve this, we established two treatment groups (fasting and fed), for each of the three guinea pig breeds: Andina, Inti, and Peru. The study involved twenty-eight guinea pigs, which were divided into the following groups: Andina-fed (five), Andina-fasting (five), Inti-fed (four), Inti-fasting (five), Peru-fed (five), and Peru-fasting (four). The results indicated a significant difference in beta diversity between the treatment groups for the Peru breed (P-value = 0.049), but not for the treatment groups of the Andina and Inti breeds. The dominant phyla across all groups were Firmicutes and Bacteroidetes. We observed variations in the abundance of different taxa in the cecum microbiota when comparing the treatment groups for each breed. Additionally, there was a higher number of unique taxa observed in the fasting groups compared to the fed groups. We discovered that the genus Victivallis was the only one present in all fasting groups across all breeds. Despite the findings, the resilience of the gut microbiome was not challenged in all three breeds, which can lead to disruptive changes that may affect the overall maintenance of the cecum microbiome. Based on the observed differences in the treatment groups of the Peru breed, it can be suggested that fasting has a greater impact on this particular breed.

Comparative evaluation of the fecal microbiota of adult hybrid pigs and Tibetan pigs, and dynamic changes in the fecal microbiota of hybrid pigs

The breed of pig can affect the diversity and composition of fecal microbiota, but there is a lack of research on the fecal microbiota of hybrid pigs. In this study, feces samples from Chuanxiang black pigs (a hybrid of Tibetan and Duroc pigs) aged 3 days (n = 24), 70 days (n = 31), 10 months (n = 13) and 2 years (n = 30) and Tibetan pigs aged 10 months (n = 14) and 2 years (n = 15) were collected and sequenced by 16S rRNA gene sequencing technology. We also measured the weight of all the tested pigs and found that the 10-month-old and two-year-old Chuanxiang black pigs weighed about three times the weight of Tibetan pigs of the same age. After comparing the genus-level microbiota composition of Tibetan pigs and Chuanxiang black pigs at 10 months and two years of age, we found that Treponema and Streptococcus were the two most abundant bacteria in Chuanxiang black pigs, while Treponema and Chirstensenellaceae_R.7_group were the two most abundant bacteria in Tibetan pigs. Prediction of microbial community function in adult Chuanxiang black pigs and Tibetan pigs showed changes in nutrient absorption, disease resistance, and coarse feeding tolerance. In addition, we also studied the changes in fecal microbiota in Chuanxiang black pigs at 3 days, 70 days, 10 months, and 2 years of age. We found that the ecologically dominant bacteria in fecal microbiota of Chuanxiang black pigs changed across developmental stages. For example, the highest relative abundance of 70-day-old Chuanxiang black pigs at the genus level was Prevotella. We identified specific microbiota with high abundance at different ages for Chuanxiang black pigs, and revealed that the potential functions of these specific microbiota were related to the dominant phenotype such as fast growth rate and strong disease resistance. Our findings help to expand the understanding of the fecal microbiota of hybrid pigs and provide a reference for future breeding and management of hybrid pigs.

A Predictive Tool Based on DNA Methylation Data for Personalized Weight Loss through Different Dietary Strategies: A Pilot Study

BACKGROUND AND AIMS

Obesity is a public health problem. The usual treatment is a reduction in calorie intake and an increase in energy expenditure, but not all individuals respond equally to these treatments. Epigenetics could be a factor that contributes to this heterogeneity. The aim of this research was to determine the association between DNA methylation at baseline and the percentage of BMI loss (%BMIL) after two dietary interventions, in order to design a prediction model to evaluate %BMIL based on methylation data.

METHODS AND RESULTS

Spanish participants with overweight or obesity (n = 306) were randomly assigned to two lifestyle interventions with hypocaloric diets: one moderately high in protein (MHP) and the other low in fat (LF) for 4 months (Obekit study; ClinicalTrials.gov ID: NCT02737267). Basal DNA methylation was analyzed in white blood cells using the Infinium MethylationEPIC array. After identifying those methylation sites associated with %BMIL (p < 0.05 and SD > 0.1), two weighted methylation sub-scores were constructed for each diet: 15 CpGs were used for the MHP diet and 11 CpGs for the LF diet. Afterwards, a total methylation score was made by subtracting the previous sub-scores. These data were used to design a prediction model for %BMIL through a linear mixed effect model with the interaction between diet and total score.

CONCLUSION

Overall, DNA methylation predicts the %BMIL of two 4-month hypocaloric diets and was able to determine which type of diet is the most appropriate for each individual. The results of this pioneer study confirm that epigenetic biomarkers may be further used for precision nutrition and the design of personalized dietary strategies against obesity.

The Beneficial Effects of Dietary Interventions on Gut Microbiota-An Up-to-Date Critical Review and Future Perspectives

Different dietary interventions, especially intermittent fasting, are widely used and promoted by physicians; these regimens have been studied lately for their impact on the gut microbiota composition/function and, consequently, on the general physiopathological processes of the host. Studies are showing that dietary components modulate the microbiota, and, at the same time, the host metabolism is deeply influenced by the different products resulting from nutrient transformation in the microbiota compartment. This reciprocal relationship can potentially influence even drug metabolism for chronic drug regimens, significantly impacting human health/disease. Recently, the influence of various dietary restrictions on the gut microbiota and the differences between the effects were investigated. In this review, we explored the current knowledge of different dietary restrictions on animal and human gut microbiota and the impact of these changes on human health.

Successful weight regain attenuation by autologous fecal microbiota transplantation is associated with non-core gut microbiota changes during weight loss; randomized controlled trial

We previously reported that autologous-fecal-microbiota-transplantation (aFMT), following 6 m of lifestyle intervention, attenuated subsequent weight regain and insulin rebound for participants consuming a high-polyphenol green-Mediterranean diet. Here, we explored whether specific changes in the core (abundant) vs. non-core (low-abundance) gut microbiome taxa fractions during the weight-loss phase (0-6 m) were differentially associated with weight maintenance following aFMT. Eighty-two abdominally obese/dyslipidemic participants (age = 52 years; 6 m weightloss = -8.3 kg) who provided fecal samples (0 m, 6 m) were included. Frozen 6 m's fecal samples were processed into 1 g, opaque and odorless aFMT capsules. Participants were randomly assigned to receive 100 capsules containing their own fecal microbiota or placebo over 8 m-14 m in ten administrations (adherence rate > 90%). Gut microbiome composition was evaluated using shotgun metagenomic sequencing. Non-core taxa were defined as ≤ 66% prevalence across participants. Overall, 450 species were analyzed. At baseline, 13.3% were classified as core, and Firmicutes presented the highest core proportion by phylum. During 6 m weight-loss phase, abundance of non-core species changed more than core species (P < .0001). Subject-specific changes in core and non-core taxa fractions were strongly correlated (Jaccard Index; r = 0.54; P < .001). Following aFMT treatment, only participants with a low 6 m change in core taxa, and a high change in non-core taxa, avoided 8-14 m weight regain (aFMT = -0.58 ± 2.4 kg, corresponding placebo group = 3.18 ± 3.5 kg; P = .02). In a linear regression model, low core/high non-core 6 m change was the only combination that was significantly associated with attenuated 8-14 m weight regain (P = .038; P = .002 for taxa patterns/treatment intervention interaction). High change in non-core, low-abundance taxa during weight-loss might mediate aFMT treatment success for weight loss maintenance.ClinicalTrials.gov: NCT03020186.

Gut microbiota profiles in two New Zealand cohorts with overweight and prediabetes: a Tū Ora/PREVIEW comparative study

Obesity-related metabolic diseases such as type 2 diabetes (T2D) are major global health issues, affecting hundreds of millions of people worldwide. The underlying factors are both diverse and complex, incorporating biological as well as cultural considerations. A role for ethnicity - a measure of self-perceived cultural affiliation which encompasses diet, lifestyle and genetic components - in susceptibility to metabolic diseases such as T2D is well established. For example, Asian populations may be disproportionally affected by the adverse 'TOFI' (Thin on the Outside, Fat on the Inside) profile, whereby outwardly lean individuals have increased susceptibility due to excess visceral and ectopic organ fat deposition. A potential link between the gut microbiota and metabolic disease has more recently come under consideration, yet our understanding of the interplay between ethnicity, the microbiota and T2D remains incomplete. We present here a 16S rRNA gene-based comparison of the fecal microbiota of European-ancestry and Chinese-ancestry cohorts with overweight and prediabetes, residing in New Zealand. The cohorts were matched for mean fasting plasma glucose (FPG: mean ± SD, European-ancestry: 6.1 ± 0.4; Chinese-ancestry: 6.0 ± 0.4 mmol/L), a consequence of which was a significantly higher mean body mass index in the European group (BMI: European-ancestry: 37.4 ± 6.8; Chinese-ancestry: 27.7 ± 4.0 kg/m2; p < 0.001). Our findings reveal significant microbiota differences between the two ethnicities, though we cannot determine the underpinning factors. In both cohorts Firmicutes was by far the dominant bacterial phylum (European-ancestry: 93.4 ± 5.5%; Chinese-ancestry: 79.6 ± 10.4% of 16S rRNA gene sequences), with Bacteroidetes and Actinobacteria the next most abundant. Among the more abundant (≥1% overall relative sequence abundance) genus-level taxa, four zero-radius operational taxonomic units (zOTUs) were significantly higher in the European-ancestry cohort, namely members of the Subdoligranulum, Blautia, Ruminoclostridium, and Dorea genera. Differential abundance analysis further identified a number of additional zOTUs to be disproportionately overrepresented across the two ethnicities, with the majority of taxa exhibiting a higher abundance in the Chinese-ancestry cohort. Our findings underscore a potential influence of ethnicity on gut microbiota composition in the context of individuals with overweight and prediabetes.

Gut microbiota in the pathogenesis and therapeutic approaches of diabetes

The gut-liver axis plays a prominent role in the pathogenesis and therapy of metabolic diseases such as diabetes. The intestinal specific origin of several hormones that guide both inter- and post-prandial metabolism of carbohydrates and lipids, drives the attention of scientists and clinicians on the gut as a major site to intervene with novel diagnostic or prognostic markers. The role of intestinal ecology in the metabolic syndrome was postulated when gut microbiota was directly connected with inflammation, hyperinsulinemia, and diabetes. There have been several discoveries with the role of gut microbiota and gut-liver axis in diabetes. Also, there are several trials ongoing on the therapeutic efficacy of probiotic administration in diabetes and its complications. Here we point to the metabolic action of microbiota and discuss the actual state of the art on gut microbiota as a novel prognostic biomarker with a putative therapeutic role in diabetes.

Genetic causal relationship between gut microbiome and psoriatic arthritis: a bidirectional two-sample Mendelian randomization study

Background

Several observational studies have suggested a potential relationship between gut microbiome and psoriatic arthritis (PsA). However, the causality of this relationship still remains unclear. We aim to explore if the specific gut microbiome is causally associated with PsA at the genetic level and offer valuable insights into the etiology of PsA.

Methods

In this study, we employed a bidirectional two-sample Mendelian randomization (MR) analysis to investigate the causal effects of the gut microbiome on PsA. Publicly accessible genome-wide association study summary data of gut microbiome were obtained from the MiBioGen consortium (n = 14,306), while the summary statistics of psoriatic arthropathies were sourced from the FinnGen consortium R8 release data (2,776 cases and 221,323 controls). The primary analytical method employed was inverse variance weighted (IVW), complemented by supplementary methods including MR-Egger, weighted median, weighted mode, maximum likelihood, MR-PRESSO, and cML-MA. Reverse MR analysis was performed on the bacteria that were found to be causally associated with PsA in forward MR analysis. Cochran's IVW Q statistic was utilized to assess the heterogeneity of instrumental variables among the selected single nucleotide polymorphisms.

Results

IVW estimates revealed that Ruminococcaceae_UCG-002 (odds ratio (OR) = 0.792, 95% confidence interval (CI), 0.643-0.977, p = 0.029) exhibited a protective effect on PsA. Conversely, Blautia (OR = 1.362, 95% CI, 1.008-1.842, p = 0.044), Eubacterium_fissicatena_group (OR = 1.28, 95% CI, 1.075-1.524, p = 0.006), and Methanobrevibacter (OR = 1.31, 95% CI, 1.059-1.621, p = 0.013) showed a positive correlation with the risk of PsA. No significant heterogeneity, horizontal pleiotropy, or outliers were observed, and the results of the MR analysis remained unaffected by any single nucleotide polymorphisms. According to the results of reverse MR analysis, no significant causal effect of PsA was found on gut microbiome.

Conclusion

This study establishes for the first time a causal relationship between the gut microbiome and PsA, providing potential valuable strategies for the prevention and treatment of PsA. Further randomized controlled trials are urgently warranted to support the targeted protective mechanisms of probiotics on PsA.

Gut Microbiome Wellness Index 2 for Enhanced Health Status Prediction from Gut Microbiome Taxonomic Profiles

Recent advancements in human gut microbiome research have revealed its crucial role in shaping innovative predictive healthcare applications. We introduce Gut Microbiome Wellness Index 2 (GMWI2), an advanced iteration of our original GMWI prototype, designed as a robust, disease-agnostic health status indicator based on gut microbiome taxonomic profiles. Our analysis involved pooling existing 8069 stool shotgun metagenome data across a global demographic landscape to effectively capture biological signals linking gut taxonomies to health. GMWI2 achieves a cross-validation balanced accuracy of 80% in distinguishing healthy (no disease) from non-healthy (diseased) individuals and surpasses 90% accuracy for samples with higher confidence (i.e., outside the "reject option"). The enhanced classification accuracy of GMWI2 outperforms both the original GMWI model and traditional species-level α-diversity indices, suggesting a more reliable tool for differentiating between healthy and non-healthy phenotypes using gut microbiome data. Furthermore, by reevaluating and reinterpreting previously published data, GMWI2 provides fresh insights into the established understanding of how diet, antibiotic exposure, and fecal microbiota transplantation influence gut health. Looking ahead, GMWI2 represents a timely pivotal tool for evaluating health based on an individual's unique gut microbial composition, paving the way for the early screening of adverse gut health shifts. GMWI2 is offered as an open-source command-line tool, ensuring it is both accessible to and adaptable for researchers interested in the translational applications of human gut microbiome science.

The Role of Diet and Gut Microbiota Interactions in Metabolic Homeostasis

Diet is a pivotal determinant in shaping the structure and function of resident microorganisms in the gut through different food components, nutritive proportion, and calories. The effects of diet on host metabolism and physiology can be mediated through the gut microbiota. Gut microbiota-derived metabolites have been shown to regulate glucose and lipid metabolism, energy consumption, and the immune system. On the other hand, emerging evidence indicates that baseline gut microbiota could predict the efficacy of diet intervention, highlighting gut microbiota can be harnessed as a biomarker in personalized nutrition. In this review, the alterations of gut microbiota in different dietary components and dietary patterns, and the potential mechanisms in the diet-microbiota crosstalk are summarized to understand the interactions of diet and gut microbiota on the impact of metabolic homeostasis.

Roles of the gut microbiome in weight management

Overweight, obesity, undernutrition and their respective sequelae have devastating tolls on personal and public health worldwide. Traditional approaches for treating these conditions with diet, exercise, drugs and/or surgery have shown varying degrees of success, creating an urgent need for new solutions with long-term efficacy. Owing to transformative advances in sequencing, bioinformatics and gnotobiotic experimentation, we now understand that the gut microbiome profoundly impacts energy balance through diverse mechanisms affecting both sides of the energy balance equation. Our growing knowledge of microbial contributions to energy metabolism highlights new opportunities for weight management, including the microbiome-aware improvement of existing tools and novel microbiome-targeted therapies. In this Review, we synthesize current knowledge concerning the bidirectional influences between the gut microbiome and existing weight management strategies, including behaviour-based and clinical approaches, and incorporate a subject-level meta-analysis contrasting the effects of weight management strategies on microbiota composition. We consider how emerging understanding of the gut microbiome alters our prospects for weight management and the challenges that must be overcome for microbiome-focused solutions to achieve success.

Impact of caloric restriction on the gut microbiota

Caloric restriction (CR) and related time-restricted diets have been popularized as means of preventing metabolic disease while improving general well-being. However, evidence as to their long-term efficacy, adverse effects, and mechanisms of activity remains incompletely understood. The gut microbiota is modulated by such dietary approaches, yet causal evidence to its possible downstream impacts on host metabolism remains elusive. Herein, we discuss the positive and adverse influences of restrictive dietary interventions on gut microbiota composition and function, and their collective impacts on host health and disease risk. We highlight known mechanisms of microbiota influences on the host, such as modulation of bioactive metabolites, while discussing challenges in achieving mechanistic dietary-microbiota insights, including interindividual variability in dietary responses as well as other methodological and conceptual challenges. In all, causally understanding the impact of CR approaches on the gut microbiota may enable to better decode their overall influences on human physiology and disease.

Robust Bioinformatics Approaches Result in the First Polygenic Risk Score for BMI in Greek Adults

Quantifying the role of genetics via construction of polygenic risk scores (PRSs) is deemed a resourceful tool to enable and promote effective obesity prevention strategies. The present paper proposes a novel methodology for PRS extraction and presents the first PRS for body mass index (BMI) in a Greek population. A novel pipeline for PRS derivation was used to analyze genetic data from a unified database of three cohorts of Greek adults. The pipeline spans various steps of the process, from iterative dataset splitting to training and test partitions, calculation of summary statistics and PRS extraction, up to PRS aggregation and stabilization, achieving higher evaluation metrics. Using data from 2185 participants, implementation of the pipeline enabled consecutive repetitions in splitting training and testing samples and resulted in a 343-single nucleotide polymorphism PRS yielding an R² = 0.3241 (beta = 1.011, p-value = 4 × 10^-193) for BMI. PRS-included variants displayed a variety of associations with known traits (i.e., blood cell count, gut microbiome, lifestyle parameters). The proposed methodology led to creation of the first-ever PRS for BMI in Greek adults and aims at promoting a facilitating approach to reliable PRS development and integration in healthcare practice.

Prebiotic mechanisms of resistant starches from dietary beans and pulses on gut microbiome and metabolic health in a humanized murine model of aging

Dietary pulses, being a rich source of fiber and proteins, offer an ideal and inexpensive food choice for older adults to promote gut and metabolic health. However, the prebiotic effects of dietary pulses-derived resistant starches (RS), compared to RS from cereals and tubers, remain relatively underexplored, particularly in context to their gut modulatory potential in old age. We herein investigate the prebiotic effects of pulses-derived RS on the gut microbiome and intestinal health in aged (60-week old) mice colonized with human microbiota. C57B6/J mice were fed for 20 weeks with either a western-style high-fat diet (control; CTL) or CTL diet supplemented (5% w/w) with RS from pinto beans (PTB), black-eyed-peas (BEP), lentils (LEN), chickpeas (CKP), or inulin (INU; reference control). We find that the RS supplementation modulates gut microbiome in a sex-dependent manner. For instance, CKP enriched α-diversity only in females, while β-diversity deviated for both sexes. Further, different RS groups exhibited distinct microbiome differences at bacterial phyla and genera levels. Notably, LEN fostered Firmicutes and depleted Proteobacteria abundance, whereas Bacteroidota was promoted by CKP and INU. Genus Dubosiella increased dominantly in males for all groups except PTB, whilst Faecalibaculum decreased in females by CKP and INU groups. Linear discriminant analysis effect size (LEfSe) and correlational analyzes reveal RS-mediated upregulation of key bacterial genera associated with short-chain fatty acids (butyrate) production and suppression of specific pathobionts. Subsequent machine-learning analysis validate decreased abundance of notorious genera, namely, Enterococcus, Odoribacter, Desulfovibrio, Alistipes and Erysipelatoclostridium among RS groups. CKP and LEN groups partly protected males against post-prandial glycemia. Importantly, RS ameliorated high-fat diet-induced gut hyperpermeability and enhanced expression of tight-junction proteins (claudin-1 and claudin-4), which were more pronounced for LEN. In addition, IL10 upregulation was more prominent for LEN, while TNF-α was downregulated by LEN, CKP, and INU. Together, these findings demonstrate that RS supplementation beneficially modulates the gut microbiome with a reduction in gut leakiness and inflammation, indicating their prebiotic potential for functional food and nutritional applications.

A Non-Randomized Trial Investigating the Impact of Brown Rice Consumption on Gut Microbiota, Attention, and Short-Term Working Memory in Thai School-Aged Children

While dietary fiber has been shown to influence the composition of gut microbiota and cognitive function in adults, much less is known about the fiber-microbiome-cognition association in children. We profiled gut microbiota using quantitative PCR (qPCR) and evaluated cognitive function using the Corsi block-tapping test (CBT) and the psychomotor vigilance test (PVT) before, during, and after the dietary intervention of 127 school-aged children in northern Thailand. While we found that Sinlek rice (SLR) consumption did not significantly alter the abundance of gut microbiota or the cognitive performance of school-aged children, we did find age to be associated with variations in both the gut microbiota profiles and cognitive outcomes. Gammaproteobacteria was significantly lower in the control and SLR groups during the middle time points of both phases (Weeks 4 and 61), and its abundance was associated with age. Cognitive performance using CBT and PVT were also found to be age-sensitive, as older children outperformed younger children on both of these cognitive assessments. Finally, a multiple factor analysis (MFA) revealed that age and cognitive performance best explain individual variation in this study. Collectively, these findings further describe the influence of host variables on the microbial profiles and cognitive outcomes of school-aged children consuming Sinlek rice in Thailand.

Novel weight loss diet attenuates dietary-induced obesity in mice and might correlate with altered gut microbiota and metabolite profiles

Although many dietary patterns have been studied for weight loss, various limitations still exist. Therefore, we designed a novel weight loss diet (NWLD) with carbohydrate, protein, and fat (energy) contents of 45%, 20%, and 35%, respectively. The saturated fatty acids: monounsaturated fatty acids:polyunsaturated fatty acids ratio was 1:2:1, and the insoluble: soluble dietary fiber ratio was 2:1. We aimed to observe the effect of NWLD on weight loss and understand the underlying metabolic mechanisms. Twenty-nine male C57BL/6J mice were selected. Nine mice were fed ordinary feed in a blank control group, and the rest were fed a high-fat diet (HFD) to establish obese mouse models. Twelve weeks later, obesity models were established, and 10 obese mice were switched to NWLD feeding. Six weeks after switching the diet, the serum, intestinal feces, and kidneys of mice were collected. Obesity-related indicators, gut microbial composition, and fecal metabolite profiles of all the mice were determined, and the correlations among these indicators were analyzed. Kidney function indicators were also assessed. The results showed that the NWLD attenuated HFD-induced weight gain, serum triglycerides (TG), and inflammatory factors, optimized the body composition without kidney function impairment. Amino acid metabolism pathways and metabolites might play key roles in this process. The findings of this research imply that NWLD could be an effective nutritional remedy for managing dietary-induced obesity.

Influence of Adiposity on the Gut Microbiota Composition of Arab Women: A Case-Control Study

Recent evidence has suggested that the gut microbiota is a possible risk factor for obesity. However, limited evidence is available on the association between the gut microbiota composition and obesity markers in the Middle-Eastern region. We aimed to investigate the association between gut microbiota and obesity markers in a case-control study including 92 Saudi women aged 18-25 years, including participants with obesity (case, n = 44) and with normal weight (control, n = 48). Anthropometric, body composition, and biochemical data were collected. The whole-genome shotgun technique was used to analyze the gut microbiota. The Shannon alpha and Bray-Curtis beta diversity were determined. The microbial alpha diversity was significantly associated with only the waist-to-hip ratio (WHR) (p-value = 0.04), while the microbial beta diversity was significantly associated with body mass index (p-value = 0.048), %body fat (p-value = 0.018), and WHR (p-value = 0.050). Specific bacteria at different taxonomic levels, such as Bacteroidetes and Synergistetes, were positively associated with different obesity markers. Alistipes was higher in the control group compared with the case group. The results highlight the association of the gut microbiota with obesity and suggest that the gut microbiota of Saudi women is associated with specific obesity markers. Future studies are needed to determine the role of the identified strains in the metabolism of individuals with obesity.

Long-Term Protein Restriction Modulates Lipid Metabolism in White Adipose Tissues and Alters Colonic Microbiota of Shaziling Pigs

Obesity is a matter of concern to the public. Abundant evidence has been accumulated that nutritional intervention is a promising strategy to address this health issue. The objective of this study is to investigate alterations in the lipid metabolism in white adipose tissues and the gut microbiota of Shaziling pigs challenged by long-term protein restriction. Results showed that compared with the control group, reducing the protein level by 20% (−20%) increased the mRNA abundance of FABP4 in white adipose tissues (p < 0.05). This occurred in conjunction with increases in PPARγ protein expression. Conversely, the protein expression of C/EBPα was reduced in the −20% group (p < 0.05). Moreover, the −20% group had increased/decreased phosphorylation of AMPKα/mTOR, respectively (p < 0.05). As for the colonic gut microbiota, a 20% reduction in the protein level led to increased Lachnospiraceae XPB1014 group abundance at the genus level (p < 0.01). Collectively, these results indicated that a 20% protein reduction could modulate lipid metabolism and alter the colonic microbiota of Shaziling pigs, an approach which might be translated into a treatment for obesity.

The microbiota composition drives personalized nutrition: Gut microbes as predictive biomarkers for the success of weight loss diets

The investigation of the human gut microbiome during recent years has permitted us to understand its relevance for human health at a systemic level, making it possible to establish different functional axes (e.g., the gut-brain, gut-liver, and gut-lung axes), which support the organ-like status conferred to this microecological component of our body. The human gut microbiota is extremely variable but modifiable via diet, a fact that allows targeting of microbes through defined dietary strategies to uncover cost-effective therapies to minimize the burden of non-communicable diseases such as pandemic obesity and overweight and its metabolic comorbidities. Nevertheless, randomly controlled dietary interventions regularly exhibit low to moderate degrees of success in weight control, making their implementation difficult in clinical practice. Here, we review the predictive value of the baseline gut microbiota configurations to anticipate the success of dietary interventions aimed at weight loss, mostly based on caloric restriction regimes and oral fiber supplementation. This emergent research concept fits into precision medicine by considering different diet patterns and adopting the best one, based on the individual microbiota composition, to reach significant adiposity reduction and improve metabolic status. We review the results from this fresh perspective of investigation, taking into account studies released very recently. We also discuss some future outlooks in the field and potential pitfalls to overcome with the aim of gaining knowledge in the field and achieving breakthroughs in personalized nutrition.

Association between Microbiome-Related Human Genetic Variants and Fasting Plasma Glucose in a High-Cardiovascular-Risk Mediterranean Population

Background and Objectives: The gut microbiota has been increasingly recognized as a relevant factor associated with metabolic diseases. However, directly measuring the microbiota composition is a limiting factor for several studies. Therefore, using genetic variables as proxies for the microbiota composition is an important issue. Landmark microbiome-host genome-wide association studies (mbGWAS) have identified many SNPs associated with gut microbiota. Our aim was to analyze the association between relevant microbiome-related genetic variants (Mi-RSNPs) and fasting glucose and type 2 diabetes in a Mediterranean population, exploring the interaction with Mediterranean diet adherence. Materials and Methods: We performed a cross-sectional study in a high-cardiovascular-risk Mediterranean population (n = 1020), analyzing the association of Mi-RSNPs (from four published mbGWAS) with fasting glucose and type 2 diabetes. A single-variant approach was used for fitting fasting glucose and type 2 diabetes to a multivariable regression model. In addition, a Mendelian randomization analysis with multiple variants was performed as a sub-study. Results: We obtained several associations between Mi-RSNPs and fasting plasma glucose involving gut Gammaproteobacteria_HB, the order Rhizobiales, the genus Rumminococcus torques group, and the genus Tyzzerella as the top ranked. For type 2 diabetes, we also detected significant associations with Mi-RSNPs related to the order Rhizobiales, the family Desulfovibrionaceae, and the genus Romboutsia. In addition, some Mi-RSNPs and adherence to Mediterranean diet interactions were detected. Lastly, the formal Mendelian randomization analysis suggested combined effects. Conclusions: Although the use of Mi-RSNPs as proxies of the microbiome is still in its infancy, and although this is the first study analyzing such associations with fasting plasma glucose and type 2 diabetes in a Mediterranean population, some interesting associations, as well as modulations, with adherence to the Mediterranean diet were detected in these high-cardiovascular-risk subjects, eliciting new hypotheses.

Dietary regulation in health and disease

Nutriments have been deemed to impact all physiopathologic processes. Recent evidences in molecular medicine and clinical trials have demonstrated that adequate nutrition treatments are the golden criterion for extending healthspan and delaying ageing in various species such as yeast, drosophila, rodent, primate and human. It emerges to develop the precision-nutrition therapeutics to slow age-related biological processes and treat diverse diseases. However, the nutritive advantages frequently diversify among individuals as well as organs and tissues, which brings challenges in this field. In this review, we summarize the different forms of dietary interventions extensively prescribed for healthspan improvement and disease treatment in pre-clinical or clinical. We discuss the nutrient-mediated mechanisms including metabolic regulators, nutritive metabolism pathways, epigenetic mechanisms and circadian clocks. Comparably, we describe diet-responsive effectors by which dietary interventions influence the endocrinic, immunological, microbial and neural states responsible for improving health and preventing multiple diseases in humans. Furthermore, we expatiate diverse patterns of dietotheroapies, including different fasting, calorie-restricted diet, ketogenic diet, high-fibre diet, plants-based diet, protein restriction diet or diet with specific reduction in amino acids or microelements, potentially affecting the health and morbid states. Altogether, we emphasize the profound nutritional therapy, and highlight the crosstalk among explored mechanisms and critical factors to develop individualized therapeutic approaches and predictors.