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Impact of dietary interventions on pre-diabetic oral and gut microbiome, metabolites and cytokines.
Shoer, S, Shilo, S, Godneva, A, Ben-Yacov, O, Rein, M, Wolf, BC, Lotan-Pompan, M, Bar, N, Weiss, EI, Houri-Haddad, Y, et al
Nature communications. 2023;14(1):5384
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Pre-diabetes, a condition characterized by elevated blood glucose levels but below diabetes thresholds, is a significant risk factor for the development of type 2 diabetes, as well as other comorbidities including cardiovascular and kidney diseases. Diet plays a critical role in the development of hyperglycaemia and the onset of pre-diabetes. The aim of this study was to assess the impact of a personalized postprandial glucose-targeting diet (PPT), as well as the standard of care Mediterranean diet (MED), on the oral and gut microbiome, metabolites and cytokines in 200 pre-diabetic individuals. This study was a biphasic, randomised, controlled, single-blind dietary intervention. Phase one included a six-month intervention that compared two diets targeting glycaemic control, while phase two included a six-month follow-up period. Participants (n = 225) were randomly assigned in a 1:1 ratio to a PPT (n = 113) or a MED (n = 112). Results showed that participants assigned to the PPT diet had significant changes in 19 gut microbial species, 14 gut and one oral microbial pathway, 86 serum metabolites and four cytokines. Participants assigned to the MED diet showed significant changes in five gut and one oral microbial species, 18 gut microbial pathways, 27 serum metabolites and four cytokines. Authors conclude that dietary interventions can affect the microbiome, cardiometabolic profile and immune response of the host. Thus, diets such as the PPT used in this study, which takes into account microbiome features, could be designed to affect the microbiome and inflict desired metabolic outcomes.
Abstract
Diabetes and associated comorbidities are a global health threat on the rise. We conducted a six-month dietary intervention in pre-diabetic individuals (NCT03222791), to mitigate the hyperglycemia and enhance metabolic health. The current work explores early diabetes markers in the 200 individuals who completed the trial. We find 166 of 2,803 measured features, including oral and gut microbial species and pathways, serum metabolites and cytokines, show significant change in response to a personalized postprandial glucose-targeting diet or the standard of care Mediterranean diet. These changes include established markers of hyperglycemia as well as novel features that can now be investigated as potential therapeutic targets. Our results indicate the microbiome mediates the effect of diet on glycemic, metabolic and immune measurements, with gut microbiome compositional change explaining 12.25% of serum metabolites variance. Although the gut microbiome displays greater compositional changes compared to the oral microbiome, the oral microbiome demonstrates more changes at the genetic level, with trends dependent on environmental richness and species prevalence in the population. In conclusion, our study shows dietary interventions can affect the microbiome, cardiometabolic profile and immune response of the host, and that these factors are well associated with each other, and can be harnessed for new therapeutic modalities.
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Gut microbiome modulates the effects of a personalised postprandial-targeting (PPT) diet on cardiometabolic markers: a diet intervention in pre-diabetes.
Ben-Yacov, O, Godneva, A, Rein, M, Shilo, S, Lotan-Pompan, M, Weinberger, A, Segal, E
Gut. 2023;72(8):1486-1496
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Diet is a major contributor to cardiometabolic health and plays a fundamental role in the prevention, management and even reversal of many chronic diseases. The gut microbiota has a central role in human health and disease. Specifically, its role in cardiometabolic health has been studied extensively in recent years. The aim of this study was to evaluate the interplay between dietary modifications, microbiome composition and cardiometabolic health outcomes. This study was a randomised controlled trial of a 6-month dietary intervention comparing a personalised postprandial-targeting (PPT) diet versus Mediterranean (MED) diet in 200 adults with pre-diabetes. Results showed that: - PPT intervention induced greater changes in multiple dietary features compared with MED intervention. - PPT intervention increased microbiome diversity and richness and exerted specific microbiome species changes that associate with clinical outcomes. - Changes in specific gut microbiome species partially mediated the effects of dietary modifications on clinical outcomes. Authors conclude that the PPT diet prompted greater changes in gut microbiota composition, consistent with overall greater dietary modifications, as compared with the MED intervention.
Abstract
OBJECTIVE To explore the interplay between dietary modifications, microbiome composition and host metabolic responses in a dietary intervention setting of a personalised postprandial-targeting (PPT) diet versus a Mediterranean (MED) diet in pre-diabetes. DESIGN In a 6-month dietary intervention, adults with pre-diabetes were randomly assigned to follow an MED or PPT diet (based on a machine-learning algorithm for predicting postprandial glucose responses). Data collected at baseline and 6 months from 200 participants who completed the intervention included: dietary data from self-recorded logging using a smartphone application, gut microbiome data from shotgun metagenomics sequencing of faecal samples, and clinical data from continuous glucose monitoring, blood biomarkers and anthropometrics. RESULTS PPT diet induced more prominent changes to the gut microbiome composition, compared with MED diet, consistent with overall greater dietary modifications observed. Particularly, microbiome alpha-diversity increased significantly in PPT (p=0.007) but not in MED arm (p=0.18). Post hoc analysis of changes in multiple dietary features, including food-categories, nutrients and PPT-adherence score across the cohort, demonstrated significant associations between specific dietary changes and species-level changes in microbiome composition. Furthermore, using causal mediation analysis we detect nine microbial species that partially mediate the association between specific dietary changes and clinical outcomes, including three species (from Bacteroidales, Lachnospiraceae, Oscillospirales orders) that mediate the association between PPT-adherence score and clinical outcomes of hemoglobin A1c (HbA1c), high-density lipoprotein cholesterol (HDL-C) and triglycerides. Finally, using machine-learning models trained on dietary changes and baseline clinical data, we predict personalised metabolic responses to dietary modifications and assess features importance for clinical improvement in cardiometabolic markers of blood lipids, glycaemic control and body weight. CONCLUSIONS Our findings support the role of gut microbiome in modulating the effects of dietary modifications on cardiometabolic outcomes, and advance the concept of precision nutrition strategies for reducing comorbidities in pre-diabetes. TRIAL REGISTRATION NUMBER NCT03222791.
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Effects of personalized diets by prediction of glycemic responses on glycemic control and metabolic health in newly diagnosed T2DM: a randomized dietary intervention pilot trial.
Rein, M, Ben-Yacov, O, Godneva, A, Shilo, S, Zmora, N, Kolobkov, D, Cohen-Dolev, N, Wolf, BC, Kosower, N, Lotan-Pompan, M, et al
BMC medicine. 2022;20(1):56
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Type 2 diabetes mellitus (T2DM) affects around 10% of the global population. The primary goal in its management is to improve glycemic control. Modifying the diet can help, but many patients fail to achieve improvements with diet alone. The aim of the randomized dietary intervention pilot trial is to evaluate the effects of a personalized postprandial-targeting (PPT) diet on glycemic control and metabolic health in 23 adults with newly diagnosed T2DM, as compared to the commonly recommended Mediterranean-style (MED) diet. The PPT diet led to significant lower levels of continuous-glucose-monitoring (CGM)-based measures as compared to the MED diet. In the additional 6-months intervention, metabolic parameters were further improved and 61% of the participants exhibited diabetes remission. Improvements in clinical outcomes were also accompanied by changes in the gut microbiome. These findings may be useful for the design of larger studies in the future that may have implications for dietary advice in clinical practice.
Abstract
BACKGROUND Dietary modifications are crucial for managing newly diagnosed type 2 diabetes mellitus (T2DM) and preventing its health complications, but many patients fail to achieve clinical goals with diet alone. We sought to evaluate the clinical effects of a personalized postprandial-targeting (PPT) diet on glycemic control and metabolic health in individuals with newly diagnosed T2DM as compared to the commonly recommended Mediterranean-style (MED) diet. METHODS We enrolled 23 adults with newly diagnosed T2DM (aged 53.5 ± 8.9 years, 48% males) for a randomized crossover trial of two 2-week-long dietary interventions. Participants were blinded to their assignment to one of the two sequence groups: either PPT-MED or MED-PPT diets. The PPT diet relies on a machine learning algorithm that integrates clinical and microbiome features to predict personal postprandial glucose responses (PPGR). We further evaluated the long-term effects of PPT diet on glycemic control and metabolic health by an additional 6-month PPT intervention (n = 16). Participants were connected to continuous glucose monitoring (CGM) throughout the study and self-recorded dietary intake using a smartphone application. RESULTS In the crossover intervention, the PPT diet lead to significant lower levels of CGM-based measures as compared to the MED diet, including average PPGR (mean difference between diets, - 19.8 ± 16.3 mg/dl × h, p < 0.001), mean glucose (mean difference between diets, - 7.8 ± 5.5 mg/dl, p < 0.001), and daily time of glucose levels > 140 mg/dl (mean difference between diets, - 2.42 ± 1.7 h/day, p < 0.001). Blood fructosamine also decreased significantly more during PPT compared to MED intervention (mean change difference between diets, - 16.4 ± 37 μmol/dl, p < 0.0001). At the end of 6 months, the PPT intervention leads to significant improvements in multiple metabolic health parameters, among them HbA1c (mean ± SD, - 0.39 ± 0.48%, p < 0.001), fasting glucose (- 16.4 ± 24.2 mg/dl, p = 0.02) and triglycerides (- 49 ± 46 mg/dl, p < 0.001). Importantly, 61% of the participants exhibited diabetes remission, as measured by HbA1c < 6.5%. Finally, some clinical improvements were significantly associated with gut microbiome changes per person. CONCLUSION In this crossover trial in subjects with newly diagnosed T2DM, a PPT diet improved CGM-based glycemic measures significantly more than a Mediterranean-style MED diet. Additional 6-month PPT intervention further improved glycemic control and metabolic health parameters, supporting the clinical efficacy of this approach. TRIAL REGISTRATION ClinicalTrials.gov number, NCT01892956.
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BREAst Cancer Personalised NuTrition (BREACPNT): dietary intervention in breast cancer survivors treated with endocrine therapy - a protocol for a randomised clinical trial.
Rein, MS, Dadiani, M, Godneva, A, Bakalenik-Gavry, M, Morzaev-Sulzbach, D, Vachnish, Y, Kolobkov, D, Lotan-Pompan, M, Weinberger, A, Segal, E, et al
BMJ open. 2022;(11):e062498
Abstract
INTRODUCTION Breast cancer survivors treated with adjuvant endocrine therapy commonly experience weight gain, which has been associated with low adherence to therapy and worse breast cancer prognosis. We aim to assess whether a personalised postprandial glucose targeting diet will be beneficial for weight management as compared with the recommended Mediterranean diet in this patient population METHODS AND ANALYSIS The BREAst Cancer Personalised NuTrition study is a phase-2 randomised trial in hormone receptor positive patients with breast cancer, treated with adjuvant endocrine therapy. The study objective is to assess whether dietary intervention intended to improve postprandial glycaemic response to meals results in better weight and glycaemic control in this population as compared with the standard recommended Mediterranean diet. Consenting participants will be assigned in a single blinded fashion to either of two dietary arms (Mediterranean diet or an algorithm-based personalised diet). They will be asked to provide a stool sample for microbiome analysis and will undergo continuous glucose monitoring for 2 weeks, at the initiation and termination of the intervention period. Microbiome composition data will be used to tailor personal dietary recommendations. After randomisation and provision of dietary recommendations, participants will be asked to continuously log their diet and lifestyle activities on a designated smartphone application during the 6-month intervention period, during which they will be monthly monitored by a certified dietitian. Participants' clinical records will be followed twice yearly for 5 years for treatment adherence, disease-free survival and recurrence. ETHICS AND DISSEMINATION The study has been approved by the ethics committee in the Sheba medical centre (file 5725-18-SMC, Ramat Gan, Israel) and the Weizmann Institutional Review Board (file 693-2, Rehovot, Israel). The findings of this study will be published in a peer reviewed publication. TRIAL REGISTRATION NUMBER NCT04079270.
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Metabolomic and microbiome profiling reveals personalized risk factors for coronary artery disease.
Talmor-Barkan, Y, Bar, N, Shaul, AA, Shahaf, N, Godneva, A, Bussi, Y, Lotan-Pompan, M, Weinberger, A, Shechter, A, Chezar-Azerrad, C, et al
Nature medicine. 2022;(2):295-302
Abstract
Complex diseases, such as coronary artery disease (CAD), are often multifactorial, caused by multiple underlying pathological mechanisms. Here, to study the multifactorial nature of CAD, we performed comprehensive clinical and multi-omic profiling, including serum metabolomics and gut microbiome data, for 199 patients with acute coronary syndrome (ACS) recruited from two major Israeli hospitals, and validated these results in a geographically distinct cohort. ACS patients had distinct serum metabolome and gut microbial signatures as compared with control individuals, and were depleted in a previously unknown bacterial species of the Clostridiaceae family. This bacterial species was associated with levels of multiple circulating metabolites in control individuals, several of which have previously been linked to an increased risk of CAD. Metabolic deviations in ACS patients were found to be person specific with respect to their potential genetic or environmental origin, and to correlate with clinical parameters and cardiovascular outcomes. Moreover, metabolic aberrations in ACS patients linked to microbiome and diet were also observed to a lesser extent in control individuals with metabolic impairment, suggesting the involvement of these aberrations in earlier dysmetabolic phases preceding clinically overt CAD. Finally, a metabolomics-based model of body mass index (BMI) trained on the non-ACS cohort predicted higher-than-actual BMI when applied to ACS patients, and the excess BMI predictions independently correlated with both diabetes mellitus (DM) and CAD severity, as defined by the number of vessels involved. These results highlight the utility of the serum metabolome in understanding the basis of risk-factor heterogeneity in CAD.
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Personalized Postprandial Glucose Response-Targeting Diet Versus Mediterranean Diet for Glycemic Control in Prediabetes.
Ben-Yacov, O, Godneva, A, Rein, M, Shilo, S, Kolobkov, D, Koren, N, Cohen Dolev, N, Travinsky Shmul, T, Wolf, BC, Kosower, N, et al
Diabetes care. 2021;(9):1980-1991
Abstract
OBJECTIVE To compare the clinical effects of a personalized postprandial-targeting (PPT) diet versus a Mediterranean (MED) diet on glycemic control and metabolic health in prediabetes. RESEARCH DESIGN AND METHODS We randomly assigned adults with prediabetes (n = 225) to follow a MED diet or a PPT diet for a 6-month dietary intervention and additional 6-month follow-up. The PPT diet relies on a machine learning algorithm that integrates clinical and microbiome features to predict personal postprandial glucose responses. During the intervention, all participants were connected to continuous glucose monitoring (CGM) and self-reported dietary intake using a smartphone application. RESULTS Among 225 participants randomized (58.7% women, mean ± SD age 50 ± 7 years, BMI 31.3 ± 5.8 kg/m2, HbA1c, 5.9 ± 0.2% [41 ± 2.4 mmol/mol], fasting plasma glucose 114 ± 12 mg/dL [6.33 ± 0.67 mmol/L]), 200 (89%) completed the 6-month intervention. A total of 177 participants also contributed 12-month follow-up data. Both interventions reduced the daily time with glucose levels >140 mg/dL (7.8 mmol/L) and HbA1c levels, but reductions were significantly greater in PPT compared with MED. The mean 6-month change in "time above 140" was -0.3 ± 0.8 h/day and -1.3 ± 1.5 h/day for MED and PPT, respectively (95% CI between-group difference -1.29 to -0.66, P < 0.001). The mean 6-month change in HbA1c was -0.08 ± 0.19% (-0.9 ± 2.1 mmol/mol) and -0.16 ± 0.24% (-1.7 ± 2.6 mmol/mol) for MED and PPT, respectively (95% CI between-group difference -0.14 to -0.02, P = 0.007). The significant between-group differences were maintained at 12-month follow-up. No significant differences were noted between the groups in a CGM-measured oral glucose tolerance test. CONCLUSIONS In this clinical trial in prediabetes, a PPT diet improved glycemic control significantly more than a MED diet as measured by daily time of glucose levels >140 mg/dL (7.8 mmol/L) and HbA1c. These findings may have implications for dietary advice in clinical practice.
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A reference map of potential determinants for the human serum metabolome.
Bar, N, Korem, T, Weissbrod, O, Zeevi, D, Rothschild, D, Leviatan, S, Kosower, N, Lotan-Pompan, M, Weinberger, A, Le Roy, CI, et al
Nature. 2020;(7836):135-140
Abstract
The serum metabolome contains a plethora of biomarkers and causative agents of various diseases, some of which are endogenously produced and some that have been taken up from the environment1. The origins of specific compounds are known, including metabolites that are highly heritable2,3, or those that are influenced by the gut microbiome4, by lifestyle choices such as smoking5, or by diet6. However, the key determinants of most metabolites are still poorly understood. Here we measured the levels of 1,251 metabolites in serum samples from a unique and deeply phenotyped healthy human cohort of 491 individuals. We applied machine-learning algorithms to predict metabolite levels in held-out individuals on the basis of host genetics, gut microbiome, clinical parameters, diet, lifestyle and anthropometric measurements, and obtained statistically significant predictions for more than 76% of the profiled metabolites. Diet and microbiome had the strongest predictive power, and each explained hundreds of metabolites-in some cases, explaining more than 50% of the observed variance. We further validated microbiome-related predictions by showing a high replication rate in two geographically independent cohorts7,8 that were not available to us when we trained the algorithms. We used feature attribution analysis9 to reveal specific dietary and bacterial interactions. We further demonstrate that some of these interactions might be causal, as some metabolites that we predicted to be positively associated with bread were found to increase after a randomized clinical trial of bread intervention. Overall, our results reveal potential determinants of more than 800 metabolites, paving the way towards a mechanistic understanding of alterations in metabolites under different conditions and to designing interventions for manipulating the levels of circulating metabolites.
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Bread Affects Clinical Parameters and Induces Gut Microbiome-Associated Personal Glycemic Responses.
Korem, T, Zeevi, D, Zmora, N, Weissbrod, O, Bar, N, Lotan-Pompan, M, Avnit-Sagi, T, Kosower, N, Malka, G, Rein, M, et al
Cell metabolism. 2017;25(6):1243-1253.e5
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Bread is a key ingredient of the human diet. Wheat is the most commonly used cereal for baking bread. The aim of this study was to compare the effects of traditionally milled and prepared whole-grain sourdough bread and industrial white bread made from refined wheat on multiple clinical and disease markers and on the composition and function of the gut microbiome. The study is a randomized crossover trial with 20 healthy subjects. Participants received either industrial white bread made from mostly refined wheat flour or a sourdough-leavened bread made from whole-grain wheat flour. Results indicate that there were no significant differences on a broad array of clinical parameters between the two 1-week-long dietary interventions. Additionally, gut microbiome analysis showed that the microbiota composition remained generally stable and person specific throughout the trial. Authors conclude that their study underlines the importance of personalisation in dietary recommendations as the interpersonal variation in the effect of bread would allow the personalisation of bread-related nutritional recommendations and optimisation of food choices worldwide.
Abstract
Bread is consumed daily by billions of people, yet evidence regarding its clinical effects is contradicting. Here, we performed a randomized crossover trial of two 1-week-long dietary interventions comprising consumption of either traditionally made sourdough-leavened whole-grain bread or industrially made white bread. We found no significant differential effects of bread type on multiple clinical parameters. The gut microbiota composition remained person specific throughout this trial and was generally resilient to the intervention. We demonstrate statistically significant interpersonal variability in the glycemic response to different bread types, suggesting that the lack of phenotypic difference between the bread types stems from a person-specific effect. We further show that the type of bread that induces the lower glycemic response in each person can be predicted based solely on microbiome data prior to the intervention. Together, we present marked personalization in both bread metabolism and the gut microbiome, suggesting that understanding dietary effects requires integration of person-specific factors.
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Personalized Nutrition by Prediction of Glycemic Responses.
Zeevi, D, Korem, T, Zmora, N, Israeli, D, Rothschild, D, Weinberger, A, Ben-Yacov, O, Lador, D, Avnit-Sagi, T, Lotan-Pompan, M, et al
Cell. 2015;(5):1079-1094
Abstract
Elevated postprandial blood glucose levels constitute a global epidemic and a major risk factor for prediabetes and type II diabetes, but existing dietary methods for controlling them have limited efficacy. Here, we continuously monitored week-long glucose levels in an 800-person cohort, measured responses to 46,898 meals, and found high variability in the response to identical meals, suggesting that universal dietary recommendations may have limited utility. We devised a machine-learning algorithm that integrates blood parameters, dietary habits, anthropometrics, physical activity, and gut microbiota measured in this cohort and showed that it accurately predicts personalized postprandial glycemic response to real-life meals. We validated these predictions in an independent 100-person cohort. Finally, a blinded randomized controlled dietary intervention based on this algorithm resulted in significantly lower postprandial responses and consistent alterations to gut microbiota configuration. Together, our results suggest that personalized diets may successfully modify elevated postprandial blood glucose and its metabolic consequences. VIDEO ABSTRACT.