Should carbohydrate-modified diets be the first option for weight loss in people with impaired glucose metabolism? A scoping review

While the "precision nutrition" movement is at an early stage of development, several investigations have compared low-fat versus carbohydrate (CHO)-modified diets (i.e., low-or-reduced-CHO, low glycemic index/load diets, and high-fiber) in people with normal versus impaired glucose metabolism. The purpose of this scoping review was to summarize evidence in support of the hypothesis that CHO-modified diets are more effective for weight loss among people with impaired glucose metabolism. Fifteen articles were included in this review: seven retrospective analyses of randomized clinical trials and eight prospective randomized clinical trials with prespecified hypotheses related to a diet (low-fat vs. CHO-modified) × phenotype (normal vs. impaired) interaction. Evidence in support of the hypothesis was identified in six of seven retrospective and three of eight prospective studies, which led to a recommendation of CHO-modified diets as a first-line option for people with impaired glucose metabolism. However, the evidence in support of this recommendation is relatively weak, and dietary prescriptions should consider additional contextual information that may influence overall dietary adherence. Additional and rigorous research using innovative randomized experimental approaches is needed for stronger dietary weight loss recommendations based on pretreatment glycemic status.

The Power of Vitamin D: Is the Future in Precision Nutrition through Personalized Supplementation Plans?

In the last few decades, vitamin D has undeniably been one of the most studied nutrients. Despite our ability to produce vitamin D through sunlight exposure, its presence in several natural food sources and fortified foods, and its widespread availability as a dietary supplement, vitamin D deficiency is a serious public health problem, affecting nearly 50% of the global population. Low serum levels of vitamin D are being associated with increased susceptibility to numerous health conditions, including respiratory infections, mental health, autoimmune diseases, and different cancer types. Although the association between vitamin D status and health is well-established, the exact beneficial effects of vitamin D are still inconclusive and indefinite, especially when considering the prevention and treatment of different health conditions and the determination of an appropriate dosage to exert those beneficial effects in various population groups. Therefore, further research is needed. With constant improvements in our understanding of individual variations in vitamin D metabolism and requirements, in the future, precision nutrition and personalized supplementation plans could prove beneficial.

Nutritional and Lifestyle Features in a Mediterranean Cohort: An Epidemiological Instrument for Categorizing Metabotypes Based on a Computational Algorithm

Background and Objectives: Modern classification and categorization of individuals' health requires personalized variables such as nutrition, physical activity, lifestyle, and medical data through advanced analysis and clustering methods involving machine learning tools. The objective of this project was to categorize Mediterranean dwellers' health factors and design metabotypes to provide personalized well-being in order to develop professional implementation tools in addition to characterizing nutritional and lifestyle features in such populations. Materials and Methods: A two-phase observational study was conducted by the Pharmacists Council to identify Spanish nutritional and lifestyle characteristics. Adults over 18 years of age completed questionnaires on general lifestyle habits, dietary patterns (FFQ, MEDAS-17 p), physical activity (IPAQ), quality of life (SF-12), and validated well-being indices (LS7, MEDLIFE, HHS, MHL). Subsequently, exploratory factor, clustering, and random forest analysis methods were conducted to objectively define the metabotypes considering population determinants. Results: A total of 46.4% of the sample (n = 5496) had moderate-to-high adherence to the Mediterranean diet (>8 points), while 71% of the participants declared that they had moderate physical activity. Almost half of the volunteers had a good self-perception of health (49.9%). Regarding lifestyle index, population LS7 showed a fair cardiovascular health status (7.9 ± 1.7), as well as moderate quality of life by MEDLIFE (9.3 ± 2.6) and MHL scores (2.4 ± 0.8). In addition, five metabotype models were developed based on 26 variables: Westernized Millennial (28.6%), healthy (25.1%), active Mediterranean (16.5%), dysmetabolic/pre-morbid (11.5%), and metabolically vulnerable/pro-morbid (18.3%). Conclusions: The support of tools related to precision nutrition and lifestyle integrates well-being characteristics and contributes to reducing the impact of unhealthy lifestyle habits with practical implications for primary care. Combining lifestyle, metabolic, and quality of life traits will facilitate personalized precision interventions and the implementation of targeted public health policies.

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

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

Meal timing and its role in obesity and associated diseases

Meal timing emerges as a crucial factor influencing metabolic health that can be explained by the tight interaction between the endogenous circadian clock and metabolic homeostasis. Mistimed food intake, such as delayed or nighttime consumption, leads to desynchronization of the internal circadian clock and is associated with an increased risk for obesity and associated metabolic disturbances such as type 2 diabetes and cardiovascular diseases. Conversely, meal timing aligned with cellular rhythms can optimize the performance of tissues and organs. In this review, we provide an overview of the metabolic effects of meal timing and discuss the underlying mechanisms. Additionally, we explore factors influencing meal timing, including internal determinants such as chronotype and genetics, as well as external influences like social factors, cultural aspects, and work schedules. This review could contribute to defining meal-timing-based recommendations for public health initiatives and developing guidelines for effective lifestyle modifications targeting the prevention and treatment of obesity and associated metabolic diseases. Furthermore, it sheds light on crucial factors that must be considered in the design of future food timing intervention trials.

Polyphenols: immunonutrients tipping the balance of immunometabolism in chronic diseases

Mounting evidence progressively appreciates the vital interplay between immunity and metabolism in a wide array of immunometabolic chronic disorders, both autoimmune and non-autoimmune mediated. The immune system regulates the functioning of cellular metabolism within organs like the brain, pancreas and/or adipose tissue by sensing and adapting to fluctuations in the microenvironment's nutrients, thereby reshaping metabolic pathways that greatly impact a pro- or anti-inflammatory immunophenotype. While it is agreed that the immune system relies on an adequate nutritional status to function properly, we are only just starting to understand how the supply of single or combined nutrients, all of them termed immunonutrients, can steer immune cells towards a less inflamed, tolerogenic immunophenotype. Polyphenols, a class of secondary metabolites abundant in Mediterranean foods, are pharmacologically active natural products with outstanding immunomodulatory actions. Upon binding to a range of receptors highly expressed in immune cells (e.g. AhR, RAR, RLR), they act in immunometabolic pathways through a mitochondria-centered multi-modal approach. First, polyphenols activate nutrient sensing via stress-response pathways, essential for immune responses. Second, they regulate mammalian target of rapamycin (mTOR)/AMP-activated protein kinase (AMPK) balance in immune cells and are well-tolerated caloric restriction mimetics. Third, polyphenols interfere with the assembly of NLR family pyrin domain containing 3 (NLRP3) in endoplasmic reticulum-mitochondria contact sites, inhibiting its activation while improving mitochondrial biogenesis and autophagosome-lysosome fusion. Finally, polyphenols impact chromatin remodeling and coordinates both epigenetic and metabolic reprogramming. This work moves beyond the well-documented antioxidant properties of polyphenols, offering new insights into the multifaceted nature of these compounds. It proposes a mechanistical appraisal on the regulatory pathways through which polyphenols modulate the immune response, thereby alleviating chronic low-grade inflammation. Furthermore, it draws parallels between pharmacological interventions and polyphenol-based immunonutrition in their modes of immunomodulation across a wide spectrum of socioeconomically impactful immunometabolic diseases such as Multiple Sclerosis, Diabetes (type 1 and 2) or even Alzheimer's disease. Lastly, it discusses the existing challenges that thwart the translation of polyphenols-based immunonutritional interventions into long-term clinical studies. Overcoming these limitations will undoubtedly pave the way for improving precision nutrition protocols and provide personalized guidance on tailored polyphenol-based immunonutrition plans.

Corrigendum: Revisiting multi-omics-based predictors of the plasma triglyceride response to an omega-3 fatty acid supplementation

[This corrects the article DOI: 10.3389/fnut.2024.1327863.].

Understanding and applying gene-environment interactions: a guide for nutrition professionals with an emphasis on integration in African research settings

Noncommunicable diseases (NCDs) are influenced by the interplay between genetics and environmental exposures, particularly diet. However, many healthcare professionals, including nutritionists and dietitians, have limited genetic background and, therefore, they may lack understanding of gene-environment interactions (GxEs) studies. Even researchers deeply involved in nutrition studies, but with a focus elsewhere, can struggle to interpret, evaluate, and conduct GxE studies. There is an urgent need to study African populations that bear a heavy burden of NCDs, demonstrate unique genetic variability, and have cultural practices resulting in distinctive environmental exposures compared with Europeans or Americans, who are studied more. Although diverse and rapidly changing environments, as well as the high genetic variability of Africans and difference in linkage disequilibrium (ie, certain gene variants are inherited together more often than expected by chance), provide unparalleled potential to investigate the omics fields, only a small percentage of studies come from Africa. Furthermore, research evidence lags behind the practices of companies offering genetic testing for personalized medicine and nutrition. We need to generate more evidence on GxEs that also considers continental African populations to be able to prevent unethical practices and enable tailored treatments. This review aims to introduce nutrition professionals to genetics terms and valid methods to investigate GxEs and their challenges, and proposes ways to improve quality and reproducibility. The review also provides insight into the potential contributions of nutrigenetics and nutrigenomics to the healthcare sphere, addresses direct-to-consumer genetic testing, and concludes by offering insights into the field's future, including advanced technologies like artificial intelligence and machine learning.

Optimum ratio of dietary protein and carbohydrate that maximises lifespan is shared among related insect species

Animals often regulate the intake and quantity of nutrients to maximise fitness through life-history traits such as lifespan, but we still lack a proper understanding of how specific nutrients influence these traits. Here, I developed an algorithm which allowed me to create a nutrient-specific database from literature data, and investigated how the requirements of protein (P) and carbohydrate (C) needed to maximise lifespan evolved across nine insect species. I found moderate evidence of a phylogenetic signal on the optimal ratio of protein to carbohydrate ratio (PC ratio) that maximised lifespan, suggesting that optimal PC ratio for lifespan could have evolved non-independently among related species. I also found evidence for weak-to-strong sex-specific optimal PC ratios for lifespan, suggesting that sex-specific nutritional needs to maximise lifespan can emerge and persist in some species. Although limited in the number of species, the approach adopted here is portable to experiments withn number of nutrients and, thus, can be used in complex comparative precision nutrition studies for insights into the evolution of animal nutrition.

Precision Nutrition Unveiled: Gene-Nutrient Interactions, Microbiota Dynamics, and Lifestyle Factors in Obesity Management

BACKGROUND

Obesity is a complex metabolic disorder that is associated with several diseases. Recently, precision nutrition (PN) has emerged as a tailored approach to provide individualised dietary recommendations.

AIM

This review discusses the major intrinsic and extrinsic components considered when applying PN during the management of obesity and common associated chronic conditions.

RESULTS

The review identified three main PN components: gene-nutrient interactions, intestinal microbiota, and lifestyle factors. Genetic makeup significantly contributes to inter-individual variations in dietary behaviours, with advanced genome sequencing and population genetics aiding in detecting gene variants associated with obesity. Additionally, PN-based host-microbiota evaluation emerges as an advanced therapeutic tool, impacting disease control and prevention. The gut microbiome's composition regulates diverse responses to nutritional recommendations. Several studies highlight PN's effectiveness in improving diet quality and enhancing adherence to physical activity among obese patients. PN is a key strategy for addressing obesity-related risk factors, encompassing dietary patterns, body weight, fat, blood lipids, glucose levels, and insulin resistance.

CONCLUSION

PN stands out as a feasible tool for effectively managing obesity, considering its ability to integrate genetic and lifestyle factors. The application of PN-based approaches not only improves current obesity conditions but also holds promise for preventing obesity and its associated complications in the long term.

Revisiting multi-omics-based predictors of the plasma triglyceride response to an omega-3 fatty acid supplementation

Background

The aim of the present study was to identify the metabolomic signature of responders and non-responders to an omega-3 fatty acid (n-3 FA) supplementation, and to test the ability of a multi-omics classifier combining genomic, lipidomic, and metabolomic features to discriminate plasma triglyceride (TG) response phenotypes.

Methods

A total of 208 participants of the Fatty Acid Sensor (FAS). Study took 5 g per day of fish oil, providing 1.9-2.2 g eicosapentaenoic acid (EPA) and 1.1 g docosahexaenoic (DHA) daily over a 6-week period, and were further divided into two subgroups: responders and non-responders, according to the change in plasma TG levels after the supplementation. Changes in plasma levels of 6 short-chain fatty acids (SCFA) and 25 bile acids (BA) during the intervention were compared between subgroups using a linear mixed model, and the impact of SCFAs and BAs on the TG response was tested in a mediation analysis. Genotyping was conducted using the Illumina Human Omni-5 Quad BeadChip. Mass spectrometry was used to quantify plasma TG and cholesterol esters levels, as well as plasma SCFA and BA levels. A classifier was developed and tested within the DIABLO framework, which implements a partial least squares-discriminant analysis to multi-omics analysis. Different classifiers were developed by combining data from genomics, lipidomics, and metabolomics.

Results

Plasma levels of none of the SCFAs or BAs measured before and after the n-3 FA supplementation were significantly different between responders and non-responders. SCFAs but not BAs were marginally relevant in the classification of plasma TG responses. A classifier built by adding plasma SCFAs and lipidomic layers to genomic data was able to even the accuracy of 85% shown by the genomic predictor alone.

Conclusion

These results inform on the marginal relevance of SCFA and BA plasma levels as surrogate measures of gut microbiome in the assessment of the interindividual variability observed in the plasma TG response to an n-3 FA supplementation. Genomic data still represent the best predictor of plasma TG response, and the inclusion of metabolomic data added little to the ability to discriminate the plasma TG response phenotypes.

Precision nutrition in pediatric IBD: A position paper from the ESPGHAN special interest group for basic science and translational research, the IBD Porto group, and allied health professionals

Stratified and precision nutrition refers to disease management or prevention of disease onset, based on dietary interventions tailored to a person's characteristics, biology, gut microbiome, and environmental exposures. Such treatment models may lead to more effective management of inflammatory bowel disease (IBD) and reduce risk of disease development. This societal position paper aimed to report advances made in stratified and precision nutritional therapy in IBD. Following a structured literature search, limited to human studies, we identified four relevant themes: (a) nutritional epidemiology for risk prediction of IBD development, (b) food-based dietary interventions in IBD, (c) exclusive enteral nutrition (EEN) for Crohn's disease (CD) management, and (d) pre- and probiotics for IBD management. There is scarce literature upon which we can make recommendations for precision or stratified dietary therapy for IBD, both for risk of disease development and disease management. Certain single-nucleotide polymorphisms related to polyunsaturated fatty acid (PUFA) metabolism may modify the effect dietary PUFA have in increasing the risk of IBD development. Non-colonic CD, mild-to-moderate CD, and high microbiota richness may predict success of EEN and may be used both for prediction of treatment continuation, but also for early cessation in nonresponders. There is currently insufficient evidence to make recommendations for precision or stratified dietary therapy for patients with established IBD. Despite the great interest in stratified and precision nutrition, we currently lack data to support conclusive recommendations. Replication of early findings by independent research groups and within structured clinical interventions is required.

Sulforaphane and Sulforaphane-Nitrile Metabolism in Humans Following Broccoli Sprout Consumption: Inter-individual Variation, Association with Gut Microbiome Composition, and Differential Bioactivity

SCOPE

The glucosinolate glucoraphanin from broccoli is converted to sulforaphane (SFN) or sulforaphane-nitrile (SFN-NIT) by plant enzymes or the gut microbiome. Human feeding studies typically observe high inter-individual variation in absorption and excretion of SFN, however, the source of this variation is not fully known. To address this, a human feeding trial to comprehensively evaluate inter-individual variation in the absorption and excretion of all known SFN metabolites in urine, plasma, and stool, and tested the hypothesis that gut microbiome composition influences inter-individual variation in total SFN excretion has been conducted.

METHODS AND RESULTS

Participants (n = 55) consumed a single serving of broccoli or alfalfa sprouts and plasma, stool, and total urine are collected over 72 h for quantification of SFN metabolites and gut microbiome profiling using 16S gene sequencing. SFN-NIT excretion is markedly slower than SFN excretion (72 h vs 24 h). Members of genus Bifidobacterium, Dorea, and Ruminococcus torques are positively associated with SFN metabolite excretion while members of genus Alistipes and Blautia has a negative association.

CONCLUSION

This is the first report of SFN-NIT metabolite levels in human plasma, urine, and stool following consumption of broccoli sprouts. The results help explain factors driving inter-individual variation in SFN metabolism and are relevant for precision nutrition.

Data-driven analysis and prediction of dynamic postprandial metabolic response to multiple dietary challenges using dynamic mode decomposition

Motivation

In the field of precision nutrition, predicting metabolic response to diet and identifying groups of differential responders are two highly desirable steps toward developing tailored dietary strategies. However, data analysis tools are currently lacking, especially for complex settings such as crossover studies with repeated measures.Current methods of analysis often rely on matrix or tensor decompositions, which are well suited for identifying differential responders but lacking in predictive power, or on dynamical systems modeling, which may be used for prediction but typically requires detailed mechanistic knowledge of the system under study. To remedy these shortcomings, we explored dynamic mode decomposition (DMD), which is a recent, data-driven method for deriving low-rank linear dynamical systems from high dimensional data.Combining the two recent developments "parametric DMD" (pDMD) and "DMD with control" (DMDc) enabled us to (i) integrate multiple dietary challenges, (ii) predict the dynamic response in all measured metabolites to new diets from only the metabolite baseline and dietary input, and (iii) identify inter-individual metabolic differences, i.e., metabotypes. To our knowledge, this is the first time DMD has been applied to analyze time-resolved metabolomics data.

Results

We demonstrate the potential of pDMDc in a crossover study setting. We could predict the metabolite response to unseen dietary exposures on both measured (R2 = 0.40) and simulated data of increasing size (R max 2 = 0.65), as well as recover clusters of dynamic metabolite responses. We conclude that this method has potential for applications in personalized nutrition and could be useful in guiding metabolite response to target levels.

Availability and implementation

The measured data analyzed in this study can be provided upon reasonable request. The simulated data along with a MATLAB implementation of pDMDc is available at https://github.com/FraunhoferChalmersCentre/pDMDc.

[Application strategy of artificial intelligence technology in feed-based development of medicinal and edible homologous traditional Chinese medicine(TCM)resources in era of the "antibiotic ban"]

In the context of the "antibiotic ban" era, the feed conversion of medicinal and edible traditional Chinese medicine(TCM) resources is a research hotspot in the field of antibiotic alternatives development. How to develop feed products that are beneficial to agriculture and livestock while ensuring nutrient balance and precision using medicinal and edible TCM resources as raw materials has become a challenge. Artificial intelligence(AI) technology has unique advantages in feed production and improving the efficiency of intelligent breeding. If AI technology is applied to the feed development of medicinal and edible TCM resources, it is possible to realize feeding and antibiotic-replacement value while ensuring precise nutrition. In order to better apply AI technology in the field of feed development of medicinal and edible TCM resources, this article used CiteSpace software to carry out literature visualization analysis and found that AI technology had a good application in the field of feed formulation optimization in recent years. However, there is still a gap in the research on the intelligent utilization of medicinal and edible TCM resources. Nonetheless, it is feasible for AI technology to be applied to the feed conversion of medicinal and edible TCM resources. Therefore, this article proposed for the first time an intelligent formulation system framework for feed materials derived from medicinal and edible TCM resources to provide new ideas for research in the field of feed development of medicinal and edible TCM resources and the research on the development of antibiotic alternatives. At the same time, it can pave the way for a new green industry chain for contemporary animal husbandry and the TCM industry.

Development of a Comprehensive Food Data Citation Standard: A Surprising Gap in the Nutrition Research Literature

Currently, there is no standard for the citation of food composition data. This leads to the questions: how are food and nutrient data cited in research papers, and are they presented in a way that allows studies to be reproduced? To answer these questions, we performed a review of the literature and quantified the accuracy and completeness of data citations from publications (January to December 2020) in the top 5 nutrition journals as ranked by the Scimago Journal Rankings. We then performed a review of citation guidelines currently in place in other disciplines. Similar to the requirement of completing the Preferred Reporting Items for Systematic Reviews and Meta-Analyses checklist for systematic reviews, we have developed a comprehensive data citation checklist, the Comprehensive Food Data Citation (CFDC) checklist. The CFDC checklist was developed through a benchmarking assessment against established data citation standards. Its purpose is to establish a standardized, best-practice approach for reporting food composition data. The CFDC checklist has been designed to cater to both publishers and authors, ensuring consistency and accuracy in food composition data reporting. The CFDC checklist is also available as an interactive citation generator to facilitate the adoption of consistent and comprehensive citation of food composition data and is available at https://www.nutrientinstitute.org/cfdc. Despite general agreement that accurate data citation is paramount, this is the first citation standard specifically developed to capture food composition data. Because food composition data are the foundation of nutrition research, our proposed guidelines aim to provide the field with a much-needed foundation for acknowledging and sharing data in a way that fosters reproducibility.

Imprecision nutrition? Duplicate meals result in unreliable individual glycemic responses measured by continuous glucose monitors across four dietary patterns in adults without diabetes

Background

Continuous glucose monitors (CGMs) are being used to characterize postprandial glycemic responses and thereby provide personalized dietary advice to minimize glycemic excursions. However, the efficacy of such advice depends on reliable CGM responses.

Objective

To explore within-subject variability of CGM responses to duplicate meals in an inpatient setting.

Methods

CGM data were collected in two controlled feeding studies (NCT03407053 and NCT03878108) in 30 participants without diabetes capturing 1056 meal responses in duplicate ~1 week apart from four dietary patterns. One study used two different CGMs (Abbott Freestyle Libre Pro and Dexcom G4 Platinum) whereas the other study used only Dexcom. We calculated the incremental area under the curve (iAUC) for each 2-h post-meal period and compared within-subject iAUCs using the same CGM for the duplicate meals using linear correlations, intra-class correlation coefficients (ICC), Bland-Altman analyses, and compared individual variability of glycemic responses to duplicate meals versus different meals using standard deviations (SDs).

Results

There were weak to moderate positive linear correlations between within- subject iAUCs for duplicate meals (Abbott r=0.47, p<0.0001, Dexcom r=0.43, p<0.0001), with low within-participant reliability indicated by ICC (Abbott 0.31, Dexcom 0.14). Bland-Altman analyses indicated wide limits of agreement (Abbott -31.3 to 31.5 mg/dL, Dexcom -30.8 to 30.4 mg/dL) but no significant bias of mean iAUCs for duplicate meals (Abbott 0.1 mg/dL, Dexcom -0.2 mg/dL). Individual variability of glycemic responses to duplicate meals was similar to that of different meals evaluated each diet week for both Abbott (SDduplicate = 10.7 mg/dL , SDweek 1 =12.4 mg/dL, SDweek 2 =11.6 mg/dL, p=0.38) and Dexcom (SDduplicate = 11.1 mg/dL, SDweek 1 = 11.5 mg/dL, SDweek 2 =11.9 mg/dL, p=0.60).

Conclusions

Individual postprandial CGM responses to duplicate meals were unreliable in adults without diabetes. Personalized diet advice based on CGM measurements in adults without diabetes requires more reliable methods involving aggregated repeated measurements.

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.

Estimated impact of the UK soft drinks industry levy on childhood hospital admissions for carious tooth extractions: interrupted time series analysis

Introduction

Tooth extraction due to dental caries is associated with socioeconomic deprivation and is a major reason for elective childhood hospital admissions in England. Consumption of sugar-sweetened beverages is a risk factor for dental caries. We examined whether the soft drinks industry levy (SDIL), announced in March 2016 and implemented in April 2018, was associated with changes in incidence rates of hospital admissions for carious tooth extraction in children, 22 months post-SDIL implementation.

Methods

Changes in incidence rates of monthly National Health Service hospital admissions for extraction of teeth due to a primary diagnosis of dental caries (International Classification of Diseases; ICD-10 code: K02) in England, between January 2012 and February 2020, were estimated using interrupted time series and compared with a counterfactual scenario where SDIL was not announced or implemented. Periodical changes in admissions, autocorrelation and population structure were accounted for. Estimates were calculated overall, by Index of Multiple Deprivation (IMD) fifths and by age group (0-4 years, 5-9 years, 10-14 years, 15-18 years).

Results

Compared with the counterfactual scenario, there was a relative reduction of 12.1% (95% CI 17.0% to 7.2%) in hospital admissions for carious tooth extractions in all children (0-18 years). Children aged 0-4 years and 5-9 years had relative reductions of 28.6% (95% CI 35.6% to 21.5%) and 5.5% (95% CI 10.5% to 0.5%), respectively; no change was observed for older children. Reductions were observed in children living in most IMD areas regardless of deprivation.

Conclusion

The UK SDIL was associated with reductions in incidence rates of childhood hospital admissions for carious tooth extractions, across most areas regardless of deprivation status and especially in younger children.

Trial registration number

ISRCTN18042742.

Microbial community-scale metabolic modeling predicts personalized short chain fatty acid production profiles in the human gut

Microbially-derived short chain fatty acids (SCFAs) in the human gut are tightly coupled to host metabolism, immune regulation, and integrity of the intestinal epithelium. However, the production of SCFAs can vary widely between individuals consuming the same diet, with lower levels often associated with disease. A systems-scale mechanistic understanding of this heterogeneity is lacking. We present a microbial community-scale metabolic modeling (MCMM) approach to predict individual-specific SCFA production profiles. We assess the quantitative accuracy of our MCMMs using in vitro, ex vivo, and in vivo data. Next, we show how MCMM SCFA predictions are significantly associated with blood-derived clinical chemistries, including cardiometabolic and immunological health markers, across a large human cohort. Finally, we demonstrate how MCMMs can be leveraged to design personalized dietary, prebiotic, and probiotic interventions that optimize SCFA production in the gut. Our results represent an important advance in engineering gut microbiome functional outputs for precision health and nutrition.

A Commercial Clay-Based Material as a Carrier for Targeted Lysozyme Delivery in Animal Feed

The controlled supply of bioactive molecules is a subject of debate in animal nutrition. The release of bioactive molecules in the target organ, in this case the intestine, results in improved feed, as well as having a lower environmental impact. However, the degradation of bioactive molecules' in transit in the gastrointestinal passage is still an unresolved issue. This paper discusses the feasibility of a simple and cost-effective procedure to bypass the degradation problem. A solid/liquid adsorption procedure was applied, and the operating parameters (pH, reaction time, and LY initial concentration) were studied. Lysozyme is used in this work as a representative bioactive molecule, while Adsorbo®, a commercial mixture of clay minerals and zeolites which meets current feed regulations, is used as the carrier. A maximum LY loading of 32 mgLY/gAD (LY(32)-AD) was obtained, with fixing pH in the range 7.5-8, initial LY content at 37.5 mgLY/gAD, and reaction time at 30 min. A full characterisation of the hybrid organoclay highlighted that LY molecules were homogeneously spread on the carrier's surface, where the LY-carrier interaction was mainly due to charge interaction. Preliminary release tests performed on the LY(32)-AD synthesised sample showed a higher releasing capacity, raising the pH from 3 to 7. In addition, a preliminary Trolox equivalent antioxidant capacity (TEAC) assay showed an antioxidant capacity for the LY of 1.47 ± 0.18 µmol TroloxEq/g with an inhibition percentage of 33.20 ± 3.94%.

Effects of a 5-week intake of erythritol and xylitol on vascular function, abdominal fat and glucose tolerance in humans with obesity: a pilot trial

Introduction

Previous studies in humans and rats suggest that erythritol might positively affect vascular function, xylitol decrease visceral fat mass and both substances improve glycaemic control. The objective of this study was to investigate the impact of a 5-week intake of erythritol and xylitol on vascular function, abdominal fat and blood lipids, glucose tolerance, uric acid, hepatic enzymes, creatinine, gastrointestinal tolerance and dietary patterns in humans with obesity.

Methods

Forty-two participants were randomised to consume either 36 g erythritol, 24 g xylitol, or no substance daily for 5 weeks. Before and after the intervention, arterial stiffness (pulse wave velocity, arteriolar-to-venular diameter ratio), abdominal fat (liver volume, liver fat percentage, visceral and subcutaneous adipose tissue, blood lipids), glucose tolerance (glucose and insulin concentrations), uric acid, hepatic enzymes, creatinine, gastrointestinal tolerance and dietary patterns were assessed. Data were analysed by linear mixed effect model.

Results

The 5-week intake of erythritol and xylitol showed no statistically significant effect on vascular function. Neither the time nor the treatment effects were significantly different for pulse wave velocity (time effect: p=0.079, Cohen's D (95% CI) -0.14 (-0.54-0.25); treatment effect: p=0.792, Cohen's D (95% CI) control versus xylitol: -0.11 (-0.61-0.35), control versus erythritol: 0.05 (0.44-0.54), erythritol versus xylitol: 0.07 (-0.41-0.54)). There was no statistically significant effect on abdominal fat, glucose tolerance, uric acid, hepatic enzymes and creatinine. Gastrointestinal tolerance was good except for a few diarrhoea-related symptoms. Participants of all groups reduced their consumption of sweetened beverages and sweets compared with preintervention.

Conclusions

The 5-week intake of erythritol and xylitol showed no statistically significant effects on vascular function, abdominal fat, or glucose tolerance in people with obesity.

Clinical trial registration

NCT02821923.

Characterizing Precision Nutrition Discourse on Twitter: Quantitative Content Analysis

BACKGROUND

It is possible that tailoring dietary approaches to an individual's genomic profile could provide optimal dietary inputs for biological functioning and support adherence to dietary management protocols. The science required for such nutrigenetic and nutrigenomic profiling is not yet considered ready for broad application by the scientific and medical communities; however, many personalized nutrition products are available in the marketplace, creating the potential for hype and misleading information on social media. Twitter provides a unique big data source that provides real-time information. Therefore, it has the potential to disseminate evidence-based health information, as well as misinformation.

OBJECTIVE

We sought to characterize the landscape of precision nutrition content on Twitter, with a specific focus on nutrigenetics and nutrigenomics. We focused on tweet authors, types of content, and presence of misinformation.

METHODS

Twitter Archiver was used to capture tweets from September 1, 2020, to December 1, 2020, using keywords related to nutrition and genetics. A random sample of tweets was coded using quantitative content analysis by 4 trained coders. Codebook-driven, quantified information about tweet authors, content details, information quality, and engagement metrics were compiled and analyzed.

RESULTS

The most common categories of tweets were precision nutrition products and nutrigenomic concepts. About a quarter (132/504, 26.2%) of tweet authors presented themselves as science experts, medicine experts, or both. Nutrigenetics concepts most frequently came from authors with science and medicine expertise, and tweets about the influence of genes on weight were more likely to come from authors with neither type of expertise. A total of 14.9% (75/504) of the tweets were noted to contain untrue information; these were most likely to occur in the nutrigenomics concepts topic category.

CONCLUSIONS

By evaluating social media discourse on precision nutrition on Twitter, we made several observations about the content available in the information environment through which individuals can learn about related concepts and products. Tweet content was consistent with the indicators of medical hype, and the inclusion of potentially misleading and untrue information was common. We identified a contingent of users with scientific and medical expertise who were active in discussing nutrigenomics concepts and products and who may be encouraged to share credible expert advice on precision nutrition and tackle false information as this technology develops.

Urinary Metabolite Profiling to Non-Invasively Monitor the Omega-3 Index: An Exploratory Secondary Analysis of a Randomized Clinical Trial in Young Adults

The Omega-3 Index (O3I) reflects eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) content in erythrocytes. While the O3I is associated with numerous health outcomes, its widespread use is limited. We investigated whether urinary metabolites could be used to non-invasively monitor the O3I in an exploratory analysis of a previous placebo-controlled, parallel arm randomized clinical trial in males and females (n = 88) who consumed either ~3 g/d olive oil (OO; control), EPA, or DHA for 12 weeks. Fasted blood and first-void urine samples were collected at baseline and following supplementation, and they were analyzed via gas chromatography and multisegment injection-capillary electrophoresis-mass spectrometry (MSI-CE-MS), respectively. We tentatively identified S-carboxypropylcysteamine (CPCA) as a novel urinary biomarker reflecting O3I status, which increased following both EPA and DHA (p < 0.001), but not OO supplementation, and was positively correlated to the O3I (R = 0.30, p < 0.001). Additionally, an unknown dianion increased following DHA supplementation, but not EPA or OO. In ROC curve analyses, CPCA outperformed all other urinary metabolites in distinguishing both between OO and EPA or DHA supplementation groups (AUC > 80.0%), whereas the unknown dianion performed best in discriminating OO from DHA alone (AUC = 93.6%). Candidate urinary biomarkers of the O3I were identified that lay the foundation for a non-invasive assessment of omega-3 status.

Epigenetic Biomarkers of Metabolic Responses to Lifestyle Interventions

Studies have examined the possible utility of epigenetic phenomena (DNA methylation changes, covalent histone modifications, and miRNA expression patterns) in predicting individual responses to different lifestyle programs. Nonetheless, most available evidence is focused on identifying epigenetic marks eventually associated with body composition and adiposity outcomes, whereas their roles in metabolic endings remain less explored. This document comprehensively reviewed the evidence regarding the use of epigenetic signatures as putative biomarkers of metabolic outcomes (glycemic, lipid, blood pressure, and inflammatory/oxidative stress features) in response to different lifestyle interventions in humans. Although more investigation is still necessary in order to translate this knowledge in clinical practice, these scientific insights are contributing to the design of advanced strategies for the precise management of cardiometabolic risk, gaining understanding on metabolic heterogeneity, allowing for the prediction of metabolic outcomes, and facilitating the design of epigenome-based nutritional strategies for a more customized approach for metabolic alterations treatment under the scope of precision nutrition.

Unraveling the Gut Microbiome-Diet Connection: Exploring the Impact of Digital Precision and Personalized Nutrition on Microbiota Composition and Host Physiology

The human gut microbiome, an intricate ecosystem housing trillions of microorganisms within the gastrointestinal tract, holds significant importance in human health and the development of diseases. Recent advances in technology have allowed for an in-depth exploration of the gut microbiome, shedding light on its composition and functions. Of particular interest is the role of diet in shaping the gut microbiome, influencing its diversity, population size, and metabolic functions. Precision nutrition, a personalized approach based on individual characteristics, has shown promise in directly impacting the composition of the gut microbiome. However, to fully understand the long-term effects of specific diets and food components on the gut microbiome and to identify the variations between individuals, longitudinal studies are crucial. Additionally, precise methods for collecting dietary data, alongside the application of machine learning techniques, hold immense potential in comprehending the gut microbiome's response to diet and providing tailored lifestyle recommendations. In this study, we investigated the complex mechanisms that govern the diverse impacts of nutrients and specific foods on the equilibrium and functioning of the individual gut microbiome of seven volunteers (four females and three males) with an average age of 40.9 ± 10.3 years, aiming at identifying potential therapeutic targets, thus making valuable contributions to the field of personalized nutrition. These findings have the potential to revolutionize the development of highly effective strategies that are tailored to individual requirements for the management and treatment of various diseases.

Perspective: Challenges and Future Directions in Clinical Research with Nuts and Berries

Consumption of nuts and berries are considered part of a healthy eating pattern. Nuts and berries contain a complex nutrient profile consisting of essential vitamins and minerals, fiber, polyunsaturated fatty acids, and phenolics in quantities that improve physiological outcomes. The spectrum of health outcomes that may be impacted by the consumptions of nuts and berries includes cardiovascular, gut microbiome, and cognitive, among others. Recently, new insights regarding the bioactive compounds found in both nuts and berries have reinforced their role for use in precision nutrition efforts. However, challenges exist that can affect the generalizability of outcomes from clinical studies, including inconsistency in study designs, homogeneity of test populations, variability in test products and control foods, and assessing realistic portion sizes. Future research centered on precision nutrition and multi-omics technologies will yield new insights. These and other topics such as funding streams and perceived risk-of-bias were explored at an international nutrition conference focused on the role of nuts and berries in clinical nutrition. Successes, challenges, and future directions with these foods are presented here.

The Role of Artificial Intelligence in Deciphering Diet-Disease Relationships: Case Studies

Modernization of society from a rural, hunter-gatherer setting into an urban and industrial habitat, with the associated dietary changes, has led to an increased prevalence of cardiometabolic and additional noncommunicable diseases, such as cancer, inflammatory bowel disease, and neurodegenerative and autoimmune disorders. However, while dietary sciences have been rapidly evolving to meet these challenges, validation and translation of experimental results into clinical practice remain limited for multiple reasons, including inherent ethnic, gender, and cultural interindividual variability, among other methodological, dietary reporting-related, and analytical issues. Recently, large clinical cohorts with artificial intelligence analytics have introduced new precision and personalized nutrition concepts that enable one to successfully bridge these gaps in a real-life setting. In this review, we highlight selected examples of case studies at the intersection between diet-disease research and artificial intelligence. We discuss their potential and challenges and offer an outlook toward the transformation of dietary sciences into individualized clinical translation.

Precision Nutrition: The Hype Is Exceeding the Science and Evidentiary Standards Needed to Inform Public Health Recommendations for Prevention of Chronic Disease

As dietary guidance for populations shifts from preventing deficiency disorders to chronic disease risk reduction, the biology supporting such guidance becomes more complex due to the multifactorial risk profile of disease and inherent population heterogeneity in the diet-disease relationship. Diet is a primary driver of chronic disease risk, and population-based guidance should account for individual responses. Cascading effects on evidentiary standards for population-based guidance are not straightforward. Precision remains a consideration for dietary guidance to prevent deficiency through the identification of population subgroups with unique nutritional needs. Reducing chronic disease through diet requires greater precision in (a) establishing essential nutrient needs throughout the life cycle in both health and disease; (b) considering effects of nutrients and other food substances on metabolic, immunological, inflammatory, and other physiological responses supporting healthy aging; and (c) considering healthy eating behaviors. Herein we provide a template for guiding population-based eating recommendations for reducing chronic diseases in heterogenous populations.

Predicting weight loss success on a new Nordic diet: an untargeted multi-platform metabolomics and machine learning approach

Background and aim

Results from randomized controlled trials indicate that no single diet performs better than other for all people living with obesity. Regardless of the diet plan, there is always large inter-individual variability in weight changes, with some individuals losing weight and some not losing or even gaining weight. This raises the possibility that, for different individuals, the optimal diet for successful weight loss may differ. The current study utilized machine learning to build a predictive model for successful weight loss in subjects with overweight or obesity on a New Nordic Diet (NND).

Methods

Ninety-one subjects consumed an NND ad libitum for 26 weeks. Based on their weight loss, individuals were classified as responders (weight loss ≥5%, n = 46) or non-responders (weight loss <2%, n = 24). We used clinical baseline data combined with baseline urine and plasma untargeted metabolomics data from two different analytical platforms, resulting in a data set including 2,766 features, and employed symbolic regression (QLattice) to develop a predictive model for weight loss success.

Results

There were no differences in clinical parameters at baseline between responders and non-responders, except age (47 ± 13 vs. 39 ± 11 years, respectively, p = 0.009). The final predictive model for weight loss contained adipic acid and argininic acid from urine (both metabolites were found at lower levels in responders) and generalized from the training (AUC 0.88) to the test set (AUC 0.81). Responders were also able to maintain a weight loss of 4.3% in a 12 month follow-up period.

Conclusion

We identified a model containing two metabolites that were able to predict the likelihood of achieving a clinically significant weight loss on an ad libitum NND. This work demonstrates that models based on an untargeted multi-platform metabolomics approach can be used to optimize precision dietary treatment for obesity.

Perspective: Developing a Nutrient-Based Framework for Protein Quality

The future of precision nutrition requires treating amino acids as essential nutrients. Currently, recognition of essential amino acid requirements is embedded within a generalized measure of protein quality known as the PDCAAS (Protein Digestibility-Corrected Amino Acid Score). Calculating the PDCAAS includes the FAO/WHO/UNU amino acid score, which is based on the limiting amino acid in a food, that is, the single amino acid with the lowest concentration compared to the reference standard. That "limiting" amino acid score is then multiplied by a bioavailability factor to obtain the PDCAAS, which ranks proteins from 0.0 (poor quality) to 1.0 (high quality). However, the PDCAAS has multiple limitations: it only allows for direct protein quality comparison between 2 proteins, and it is not scalable, transparent, or additive. We therefore propose that shifting the protein quality evaluation paradigm from the current generalized perspective to a precision nutrition focus treating amino acids as unique, metabolically active nutrients will be valuable for multiple areas of science and public health. We report the development and validation of the Essential Amino Acid 9 (EAA-9) score, an innovative, nutrient-based protein quality scoring framework. EAA-9 scores can be used to ensure that dietary recommendations for each essential amino acid are met. The EAA-9 scoring framework also offers the advantages of being additive and, perhaps most importantly, allows for personalization of essential amino acid needs based on age or metabolic conditions. Comparisons of the EAA-9 score with PDCAAS demonstrated the validity of the EAA-9 framework, and practical applications demonstrated that the EAA-9 framework is a powerful tool for precision nutrition applications.

A randomized clinical trial comparing low-fat with precision nutrition-based diets for weight loss: impact on glycemic variability and HbA1c

BACKGROUND

Recent studies have demonstrated considerable interindividual variability in postprandial glucose response (PPGR) to the same foods, suggesting the need for more precise methods for predicting and controlling PPGR. In the Personal Nutrition Project, the investigators tested a precision nutrition algorithm for predicting an individual's PPGR.

OBJECTIVE

This study aimed to compare changes in glycemic variability (GV) and HbA1c in 2 calorie-restricted weight loss diets in adults with prediabetes or moderately controlled type 2 diabetes (T2D), which were tertiary outcomes of the Personal Diet Study.

METHODS

The Personal Diet Study was a randomized clinical trial to compare a 1-size-fits-all low-fat diet (hereafter, standardized) with a personalized diet (hereafter, personalized). Both groups received behavioral weight loss counseling and were instructed to self-monitor diets using a smartphone application. The personalized arm received personalized feedback through the application to reduce their PPGR. Continuous glucose monitoring (CGM) data were collected at baseline, 3 mo and 6 mo. Changes in mean amplitude of glycemic excursions (MAGEs) and HbA1c at 6 mo were assessed. We performed an intention-to-treat analysis using linear mixed regressions.

RESULTS

We included 156 participants [66.5% women, 55.7% White, 24.1% Black, mean age 59.1 y (standard deviation (SD) = 10.7 y)] in these analyses (standardized = 75, personalized = 81). MAGE decreased by 0.83 mg/dL per month for standardized (95% CI: 0.21, 1.46 mg/dL; P = 0.009) and 0.79 mg/dL per month for personalized (95% CI: 0.19, 1.39 mg/dL; P = 0.010) diet, with no between-group differences (P = 0.92). Trends were similar for HbA1c values.

CONCLUSIONS

Personalized diet did not result in an increased reduction in GV or HbA1c in patients with prediabetes and moderately controlled T2D, compared with a standardized diet. Additional subgroup analyses may help to identify patients who are more likely to benefit from this personalized intervention. This trial was registered at clinicaltrials.gov as NCT03336411.

Precision Nutrition Opportunities to Help Mitigate Nutrition and Health Challenges in Low- and Middle-Income Countries: An Expert Opinion Survey

Precision nutrition involves several data collection methods and tools that aim to better inform nutritional recommendations and improve dietary intake, nutritional status, and health outcomes. While the benefits of collecting precise data and designing well-informed interventions are vast, it is presently unclear whether precision nutrition is a relevant approach for tackling nutrition challenges facing populations in low- and middle-income countries (LMIC), considering infrastructure, affordability, and accessibility of approaches. The Swiss Food & Nutrition Valley (SFNV) Precision Nutrition for LMIC project working group assessed the relevance of precision nutrition for LMIC by first conducting an expert opinion survey and then hosting a workshop with nutrition leaders who live or work in LMIC. The experts were interviewed to discuss four topics: nutritional problems, current solutions, precision nutrition, and collaboration. Furthermore, the SFNV Precision Nutrition for LMIC Virtual Workshop gathered a wider group of nutrition leaders to further discuss precision nutrition relevance and opportunities. Our study revealed that precision public health nutrition, which has a clear focus on the stratification of at-risk groups, may offer relevant support for nutrition and health issues in LMIC. However, funding, affordability, resources, awareness, training, suitable tools, and safety are essential prerequisites for implementation and to equitably address nutrition challenges in low-resource communities.

Need for a nutrition-specific scientific paradigm for research quality improvement

Nutrition science has been criticised for its methodology, apparently contradictory findings and generating controversy rather than consensus. However, while certain critiques of the field are valid and informative for developing a more cogent science, there are also unique considerations for the study of diet and nutrition that are either overlooked or omitted in these discourses. The ongoing critical discourse on the utility of nutrition sciences occurs at a time when the burden of non-communicable cardiometabolic disease continues to rise in the population. Nutrition science, along with other disciplinary fields, is tasked with producing a translational evidence-base fit for the purpose of improving population and individual health and reducing disease risk. Thus, an exploration of the unique methodological and epistemic considerations for nutrition research is important for nutrition researchers, students and practitioners, to further develop an improved scientific discipline for nutrition. This paper will expand on some of the challenges facing nutrition research, discussing methodological facets of nutritional epidemiology, randomised controlled trials and meta-analysis, and how these considerations may be applied to improve research methodology. A pragmatic research paradigm for nutrition science is also proposed, which places methodology at its centre, allowing for questions over both how we obtain knowledge and research design as the method to produce that knowledge to be connected, providing the field of nutrition research with a framework within which to capture the full complexity of nutrition and diet.

The evolution of folate supplementation - from one size for all to personalized, precision, poly-paths

Folate is a crucial nutrient that supports physiological functions. Low folate levels is a risk factor for several diseases, including cardiovascular diseases and neural tube defects. The most used folate supplement is folic acid, a synthetic oxidative form, and folic acid grain fortification is a success story of public health. However, the metabolic conversion of folic acid to bioactive tetrahydrofolate requires several enzymes and cofactors. Therefore, these factors influence its bioavailability and efficacy. In contrast, 5-methyltetrahydrofolate is used directly and participates in one-carbon metabolism, and the use of 5-methyltetrahydrofolate as an alternative folate supplement has increased. The metabolism of 5-methyltetrahydrofolate is primarily dependent on the transmembrane transporter, reduced folate carrier (RFC), and the RFC gene SLC19A1 variant is a functional polymorphism that affects folate status indexes. Recent studies demonstrated that the expression of RFC and cystathionine β-synthase, another enzyme required for homocysteine clearance, increases significantly by supplementation with calcitriol (vitamin D3), suggesting that calcitriol intake promotes the bioavailability of folate and has synergistic effects in homocysteine clearance. The advancements in biomedical and cohort studies and clinical trials have enhanced our understanding of the critical roles of folate and the regulation of one-carbon metabolism. We anticipate that the field of folate supplementation is poised to evolve from one size for all to personalized, precision, poly-paths (3Ps), which is a critical measure to meet individual needs, maximize health benefits, and minimize side effects.

Lipid-Related Genetic Variants for Personalized Dietary Interventions: A Systematic Review

Dyslipidemias are known risk factors for chronic diseases. Precision nutrition interventions are designed according to characteristics, such as diet, phenotype, and genotype. This systematic review aims to define a panel of genetic variants associated with lipid abnormalities that could be later used in nutrigenetic intervention studies. A systematic review is conducted following the PRISMA-P. Studies published from January 2010 to December 2020 in English language and humans are included from PubMed and ScienceDirect databases. Articles that demonstrate a strong association between polymorphisms (single nucleotide variation) of genes involved in lipid metabolism and increased risk for dyslipidemia are included. A total of 3031 articles are screened, but only 51 articles fulfill the inclusion criteria. The genes included are FABP2, MTTP related to CM synthesis and secretion; LPL, LIPC involved in triglyceride hydrolysis; CETP, APOA1, LCAT, ABCA1, and APOA5 related to lipoprotein metabolism, and APOE, LDLR, SCARB1, APOC3 involved in lipid clearance. In this systematic review, genetic variants related to chylomicron synthesis, triglyceride hydrolysis, lipoprotein metabolism, and lipid clearance demonstrate a strong association with lipid abnormalities, which can be used to design precision nutrition interventions that may help to prevent and treat dyslipidemia effectively.

Harnessing the Magic of the Dairy Matrix for Next-Level Health Solutions: A Summary of a Symposium Presented at Nutrition 2022

An emerging body of scientific evidence demonstrates that the food matrix-the interaction among nutrients, bioactive components, and physical structure of a food-can affect health in significant, unexpected ways beyond its individual nutrients. In particular, research suggests that consumption of dairy foods such as milk, yogurt, and cheese may affect human health in a matrix-dependent fashion. To disseminate and discuss the growing body of evidence surrounding the role of the dairy food matrix on cardiometabolic health, 3 expert researchers on the topic of the food matrix shared the latest science in a session entitled "Next-Level Health Solutions: The Magic of the Matrix" at the American Society for Nutrition's 2022 LIVE ONLINE Conference. This article is a summary of the literature presented and discussed during that session. A substantial body of literature demonstrates that full-fat dairy foods, particularly fermented dairy foods, may beneficially modulate cardiometabolic outcomes depending on an individual's health status. These findings have important implications for current authoritative dietary guidance that recommends the consumption of low-fat or fat-free dairy foods. Furthermore, this evidence may inform practical applications of harnessing dairy's unique profile of bioactives for health promotion and disease prevention at the individual and community levels.

Nutritional Composition of Hass Avocado Pulp

Avocados (Persea americana) are a unique fruit that can provide health benefits when included in a healthy diet. As health care moves towards precision health and targeted therapies or preventative medicine, it is critical to understand foods and their dietary components. The nutritional composition and plant physiology of the Hass avocado is strikingly different from other fruits. This paper reviews the nutrient and bioactive composition of the edible portion of the Hass avocado (pulp) reported in the literature and from commercial lab analyses of the current market supply of fresh Hass avocados. These results provide comprehensive data on what nutrients and bioactives are in avocado and the quantity of these nutrients. We discuss the reasons for nutrient composition variations and review some potential health benefits of bioactive compounds found in Hass avocados.

Crop, Host, and Gut Microbiome Variation Influence Precision Nutrition: An Example of Blueberries

Epidemiological studies have shown associations between polyphenol-rich fruit intake and bone health, and preclinical studies have shown that blueberries improve bone health. To determine the genotype and dose of blueberries that are effective in ameliorating age-related bone loss, a multi-institutional team of investigators performed in vitro, preclinical, and clinical studies on blueberry varieties that differed in flavonoid profiles. Principal component analysis was used to select blueberry genotypes that varied in anthocyanin profiles. Total phenolic content did not predict the bioavailability of polyphenolic compounds in rats. A range in bioavailability was observed in individual polyphenolic compounds across genotypes. Both alpha and beta diversity analyses indicated that gut microbiome profiles varied with blueberry dose in rats. Additionally, the identification of specific taxa, such as Prevotellaceae_UCG-001 and Coriobacteriales, increasing after blueberry consumption adds to the mounting evidence of their role in polyphenol metabolism. All of the sources of variation can inform blueberry breeding practices to influence precision nutrition.

Dietary interventions and precision nutrition in cancer therapy

In recent years dietary interventions have become a promising tool in cancer treatment and have demonstrated a powerful ability to alter metabolism and tumor growth, development, and therapeutic response. However, because the mechanisms underlying dietary therapeutics are poorly understood, they are frequently ignored as a potential line of treatment for cancer. We discuss the proposed mechanisms behind the anticancer effects of various diets and their development for clinical use. This review aims to provide researchers and clinicians in the field of oncology with a complete overview of the contemporary landscape of nutritional interventions and precision nutrition as cancer therapeutics, and offers a perspective on the steps necessary to establish nutritional interventions as a standard line of treatment.

Dietary Oncopharmacognosy as a Crosswalk between Precision Oncology and Precision Nutrition

While diet and nutrition are modifiable risk factors for many chronic and infectious diseases, their role in cancer prevention and control remains under investigation. The lack of clarity of some diet-cancer relationships reflects the ongoing debate about the relative contribution of genetic factors, environmental exposures, and replicative errors in stem cell division as determinate drivers of cancer risk. In addition, dietary guidance has often been based upon research assuming that the effects of diet and nutrition on carcinogenesis would be uniform across populations and for various tumor types arising in a specific organ, i.e., that one size fits all. Herein, we present a paradigm for investigating precision dietary patterns that leverages the approaches that led to successful small-molecule inhibitors in cancer treatment, namely understanding the pharmacokinetics and pharmacodynamics of small molecules for targeting carcinogenic mechanisms. We challenge the scientific community to refine the paradigm presented and to conduct proof-in-concept experiments that integrate existing knowledge (drug development, natural products, and the food metabolome) with developments in artificial intelligence to design and then test dietary patterns predicted to elicit drug-like effects on target tissues for cancer prevention and control. We refer to this precision approach as dietary oncopharmacognosy and envision it as the crosswalk between the currently defined fields of precision oncology and precision nutrition with the goal of reducing cancer deaths.

Heterogeneity in the response to n-3 polyunsaturated fatty acids

PURPOSE OF REVIEW

A central goal in the study of long chain n-3 polyunsaturated fatty acids (PUFA) is to translate findings from the basic sciences to the population level to improve human health and prevent chronic diseases. A tenet of this vision is to think in terms of precision medicine and nutrition, that is, stratification of individuals into differing groups that will have different needs across the lifespan for n-3 PUFAs. Therefore, there is a critical need to identify the sources of heterogeneity in the human population in the dietary response to n-3 PUFA intervention.

RECENT FINDINGS

We briefly review key sources of heterogeneity in the response to intake of long chain n-3 PUFAs. These include background diet, host genome, composition of the gut microbiome, and sex. We also discuss the need to integrate data from newer rodent models (e.g. population-based approaches), multi -omics, and analyses of big data using machine learning and data-driven cluster analyses.

SUMMARY

Accounting for vast heterogeneity in the human population, particularly with the use of big data integrated with preclinical evidence, will drive the next generation of precision nutrition studies and randomized clinical trials with long-chain n-3 PUFAs.

Supplementation with inulin-type fructans affects gut microbiota and attenuates some of the cardiometabolic benefits of a plant-based diet in individuals with overweight or obesity

Background

The gut microbiota has emerged as a potential therapeutic target to improve the management of obesity and its comorbidities.

Objective

We investigated the impact of a high fiber (∼38 g/d) plant-based diet, consumed ad libitum, with or without added inulin-type fructans (ITF), on the gut microbiota composition and cardiometabolic outcomes in subjects with obesity. We also tested if baseline Prevotella/Bacteroides (P/B) ratio predicts weight loss outcomes.

Methods

This is a secondary exploratory analysis from the PREVENTOMICS study, in which 100 subjects (82 completers) aged 18-65 years with body mass index 27-40 kg/m2 were randomized to 10 weeks of double-blinded treatment with a personalized or a generic plant-based diet. Changes from baseline to end-of-trial in gut microbiota composition (16S rRNA gene amplicon sequencing), body composition, cardiometabolic health and inflammatory markers were evaluated in the whole cohort (n = 82), and also compared in the subgroup of subjects who were supplemented with an additional 20 g/d ITF-prebiotics (n = 21) or their controls (n = 22).

Results

In response to the plant-based diet, all subjects lost weight (-3.2 [95% CI -3.9, -2.5] kg) and experienced significant improvements in body composition and cardiometabolic health indices. Addition of ITF to the plant-based diet reduced microbial diversity (Shannon index) and selectively increased Bifidobacterium and Faecalibacterium (q < 0.05). The change in the latter was significantly associated with higher values of insulin and HOMA-IR and lower HDL cholesterol. In addition, the LDL:HDL ratio and the concentrations of IL-10, MCP-1 and TNFα were significantly elevated in the ITF-subgroup. There was no relationship between baseline P/B ratio and changes in body weight (r = -0.07, p = 0.53).

Conclusion

A plant-based diet consumed ad libitum modestly decreases body weight and has multiple health benefits in individuals with obesity. Addition of ITF-prebiotics on top this naturally fiber-rich background selectively changes gut microbiota composition and attenuates some of the realized cardiometabolic benefits.

Clinical trial registration

[https://clinicaltrials.gov/ct2/show/NCT04590989], identifier [NCT04590989].

Consumption of Common Bean Suppresses the Obesogenic Increase in Adipose Depot Mass: Impact of Dose and Biological Sex

Obesity prevention is stated as a simple objective in the public health guidelines of most countries: avoid adult weight gain. However, the success of the global population in accomplishing this goal is limited as reflected in the persisting pandemic of overweight and obesity. While many intervention strategies have been proposed, most are directed at mitigating the consequences of obesity. Efforts intended to prevent unintentional weight gain and associated adiposity are termed anti-obesogenic. Herein, evidence is presented that a neglected category of foods, pulses, i.e., grain legumes, have anti-obesogenic activity. Using a preclinical mouse model of obesity, a dose-response study design in animals of both biological sexes, and cooked, freeze-dried, and milled common bean as a representative pulse, data are presented showing that the rate of body weight gain is slowed, and fat accumulation is suppressed when 70% of the dietary protein is provided from common bean. These anti-obesogenic effects are reduced at lower amounts of common bean (17.5% or 35%). The anti-obesogenic responsiveness is greater in female than in male mice. RNA sequence analysis indicates that the sex-related differences extend to gene expression patterns, particularly those related to immune regulation within adipose tissue. In addition, our findings indicate the potential value of a precision nutrition approach for human intervention studies that identify "pulse anti-obesogenic responders". A precision approach may reduce the concentration of pulses required in the diet for benefits, but candidate biomarkers of responsivity to pulse consumption remain to be determined.

Biological Activities of Miracle Berry Supercritical Extracts as Metabolic Regulators in Chronic Diseases

Synsepalum dulcificum (Richardella dulcifica) is a berry fruit from West Africa with the ability to convert the sour taste into a sweet taste, and for this reason, the fruit is also known as the "miracle berry" (MB). The red and bright berry is rich in terpenoids. The fruit's pulp and skin contain mainly phenolic compounds and flavonoids, which correlate with their antioxidant activity. Different polar extracts have been described to inhibit cell proliferation and transformation of cancer cell lines in vitro. In addition, MB has been shown to ameliorate insulin resistance in a preclinical model of diabetes induced by a chow diet enriched in fructose. Herein, we have compared the biological activities of three supercritical extracts obtained from the seed-a subproduct of the fruit-and one supercritical extract obtained from the pulp and the skin of MB. The four extracts have been characterized in terms of total polyphenols content. Moreover, the antioxidant, anti-inflammatory, hypo-lipidemic, and inhibition of colorectal cancer cell bioenergetics have been compared. Non-polar supercritical extracts from the seed are the ones with the highest effects on the inhibition of bioenergetic of colorectal (CRC) cancer cells. At the molecular level, the effects on cell bioenergetics seems to be related to the inhibition of main drivers of the de novo lipogenesis, such as the sterol regulatory element binding transcription factor (SREBF1) and downstream molecular targets fatty acid synthase (FASN) and stearoyl coenzyme desaturase 1 (SCD1). As metabolic reprograming is considered as one of the hallmarks of cancer, natural extracts from plants may provide complementary approaches in the treatment of cancer. Herein, for the first time, supercritical extracts from MB have been obtained, where the seed, a by-product of the fruit, seems to be rich in antitumor bioactive compounds. Based on these results, supercritical extracts from the seed merit further research to be proposed as co-adjuvants in the treatment of cancer.

Nutrition-Related N-of-1 Studies Warrant Further Research to Provide Evidence for Dietitians to Practice Personalized (Precision) Medical Nutrition Therapy: A Systematic Review

N-of-1 trials provide a higher level of evidence than randomized controlled trials for determining which treatment works best for an individual, and the design readily accommodates testing of personalized nutrition. The aim of this systematic review was to synthesize nutrition-related studies using an N-of-1 design. The inclusion criterion was adult participants; the intervention/exposure was any nutrient, food, beverage, or dietary pattern; the comparators were baseline values, a control condition untreated or placebo, or an alternate treatment, alongside any outcomes such as changes in diet, body weight, biochemical outcomes, symptoms, quality of life, or a disease outcome resulting from differences in nutritional conditions. The information sources used were Medline, Embase, Scopus, Cochrane Central, and PsychInfo. The quality of study reporting was assessed using the Consort Extension for N-of-1 trials (CENT) statement or the STrengthening Reporting of OBservational Studies in Epidemiology (STROBE) guidelines, as appropriate. From 211 articles screened, a total of 7 studies were included and were conducted in 5 countries with a total of 83 participants. The conditions studied included prediabetes, diabetes, irritable bowel syndrome, weight management, and investigation of the effect of diet in healthy people. The quality of reporting was mostly adequate, and dietary assessment quality varied from poor to good. The evidence base is small, but served to illustrate the main characteristics of N-of-1 study designs and considerations for moving research forward in the era of personalized medical nutrition therapy.