Paving the Way to Precision Nutrition Through Metabolomics

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

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

The effect of gut microbiota-derived carnosine on mucosal integrity and immunity in broiler chickens challenged with Eimeria maxima

In the first study, an in vitro culture system was developed to investigate the effects of carnosine on macrophage proinflammatory cytokine response using an established chicken macrophage cell line (CMC), gut integrity using a chicken intestinal epithelial cell line (IEC), muscle differentiation in quail muscle cells (QMCs) and primary chicken embryonic muscle cells (PMCs), and direct anti-parasitic effect against Eimeria maxima sporozoites. Cells to be tested were seeded in 24-well plates and treated with carnosine at 4 different concentrations (0.1, 1.0, and 10.0 µg). After 18 h of incubation, cells were harvested to measure gene expression of proinflammatory cytokines in CMC, tight junction (TJ) proteins in IECs, and muscle cell growth markers in QMCs and PMCs. In vivo trials were conducted to investigate the effect of dietary carnosine on disease parameters in broiler chickens challenged with E. maxima. One hundred and twenty male broiler chickens (0-day-old) were allocated into 4 treatment groups: 1) basal diet without infection (NC), 2) basal diet with E. maxima infection (PC), 3) carnosine at 10.0 mg/kg feed with PC (HCS), and 4) carnosine at 1.0 mg/kg feed with PC (LCS). All groups except NC were orally infected with E. maxima on d 14. Jejunal samples were collected for lesion scoring and jejunum gut tissues were used for transcriptomic analysis of cytokines and TJ proteins. In vitro, carnosine treatment significantly decreased IL-1β gene expression in CMC following LPS stimulation. In vivo feeding studies showed that dietary carnosine increased BW and ADG of chickens in E. maxima-infected groups and reduced the jejunal lesion score and fecal oocyst shedding in HCS group. Jejunal IL-1β, IL-8, and IFN-γ expression were suppressed in the HCS group compared to PC. The expression levels of claudin-1 and occludin in IECs were also increased in HCS following carnosine treatment. In conclusion, these findings highlight the beneficial effects of dietary carnosine supplementation on intestinal immune responses and gut barrier function in broiler chickens exposed to E. maxima infection.

Genetics, Nutrition, and Health: A New Frontier in Disease Prevention

The field of nutrition research has traditionally focused on the effects of macronutrients and micronutrients on the body. However, it has become evident that individuals have unique genetic makeups that influence their response to food. Nutritional genomics, which includes nutrigenetics and nutrigenomics, explores the interaction between an individual's genetic makeup, diet, and health outcomes. Nutrigenetics studies the impact of genetic variation on an individual's response to dietary nutrients, while nutrigenomics investigates how dietary components affect gene regulation and expression. These disciplines seek to understand the impact of diet on the genome, transcriptome, proteome, and metabolome. It provides insights into the mechanisms underlying the effect of diet on gene expression. Nutrients can cause the modification of genetic expression through epigenetic changes, such as DNA methylation and histone modifications. The aim of nutrigenomics is to create personalized diets based on the unique metabolic profile of an individual, gut microbiome, and genetic makeup to prevent diseases and promote health. Nutrigenomics has the potential to revolutionize the field of nutrition by combining the practicality of personalized nutrition with knowledge of genetic factors underlying health and disease. Thus, nutrigenomics offers a promising approach to improving health outcomes (in terms of disease prevention) through personalized nutrition strategies based on an individual's genetic and metabolic characteristics.

Potential Mechanisms of Precision Nutrition-Based Interventions for Managing Obesity

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

Metabolome biomarkers linking dietary fibre intake with cardiometabolic effects: results from the Danish Diet, Cancer and Health-Next Generations MAX study

Biomarkers associated with dietary fibre intake, as complements to traditional dietary assessment tools, may improve the understanding of its role in human health. Our aim was to discover metabolite biomarkers related to dietary fibre intake and investigate their association with cardiometabolic risk factors. We used data and samples from the Danish Diet Cancer and Health Next Generation (DCH-NG) MAX-study, a one-year observational study with evaluations at baseline, six and 12 months (n = 624, 55% female, mean age: 43 years, 1353 observations). Direct associations between fibre intake and plasma concentrations of 2,6-dihydroxybenzoic acid (2,6-DHBA) and indolepropionic acid were observed at the three time-points. Both metabolites showed an intraclass-correlation coefficient (ICC) > 0.50 and were associated with the self-reported intake of wholegrain cereals, and of fruits and vegetables, respectively. Other metabolites associated with dietary fibre intake were linolenoyl carnitine, 2-aminophenol, 3,4-DHBA, and proline betaine. Based on the metabolites associated with dietary fibre intake we calculated predicted values of fibre intake using a multivariate, machine-learning algorithm. Metabolomics-based predicted fibre, but not self-reported fibre values, showed negative associations with cardiometabolic risk factors (i.e. high sensitivity C-reactive protein, systolic and diastolic blood pressure, all FDR-adjusted p-values <0.05). Furthermore, different correlations with gut microbiota composition were observed. In conclusion, 2,6-DHBA and indolepropionic acid in plasma may better link dietary fibre intake with its metabolic effects than self-reported values. These metabolites may represent a novel class of biomarkers reflecting both dietary exposure and host and/or gut microbiota characteristics providing a read-out that is differentially related to cardiometabolic risk.

Metabolomics in Preclinical Drug Safety Assessment: Current Status and Future Trends

Metabolomics is emerging as a powerful systems biology approach for improving preclinical drug safety assessment. This review discusses current applications and future trends of metabolomics in toxicology and drug development. Metabolomics can elucidate adverse outcome pathways by detecting endogenous biochemical alterations underlying toxicity mechanisms. Furthermore, metabolomics enables better characterization of human environmental exposures and their influence on disease pathogenesis. Metabolomics approaches are being increasingly incorporated into toxicology studies and safety pharmacology evaluations to gain mechanistic insights and identify early biomarkers of toxicity. However, realizing the full potential of metabolomics in regulatory decision making requires a robust demonstration of reliability through quality assurance practices, reference materials, and interlaboratory studies. Overall, metabolomics shows great promise in strengthening the mechanistic understanding of toxicity, enhancing routine safety screening, and transforming exposure and risk assessment paradigms. Integration of metabolomics with computational, in vitro, and personalized medicine innovations will shape future applications in predictive toxicology.

A comparative metabolomics study of polyphenols in highland barley (Hordeum vulgare L.) grains with different colors

Highland barley (HB) grains are gaining increasing popularity owing to their high nutritional merits. However, only limited information is available on the metabolic profiles of HB grains polyphenols, especially the difference of polyphenols in different colors of HB. In this study, we determined the metabolic profiles of black, blue, and white HB grains via an ultra-performance liquid chromatography-electrospray ionization-tandem mass spectrometry (UPLC-ESI-MS/MS)-based metabolomics. A total of 402 metabolites were identified, among which 198, 62, and 189 metabolites displayed different accumulation patterns in the three comparison groups (WHB vs. BKHB, WHB vs. BEHB, BEHB vs. BKHB), respectively. In particular, flavonoids and phenolic acids contents displayed considerable differences among the three HB cultivars. The phenolics content of black HB was relatively high. Additionally, "Flavonoid biosynthesis" and "flavone and flavonol biosynthesis" were the significantly enriched pathways. In conclusion, this study provides comprehensive insights into the adequate utilization and development of novel HB-based functional foods.

Precision Nutrition to Improve Risk Factors of Obesity and Type 2 Diabetes

PURPOSE OF REVIEW

Existing dietary and lifestyle interventions and recommendations, to improve the risk factors of obesity and type 2 diabetes with the target to mitigate this double global epidemic, have produced inconsistent results due to interpersonal variabilities in response to these conventional approaches, and inaccuracies in dietary assessment methods. Precision nutrition, an emerging strategy, tailors an individual's key characteristics such as diet, phenotype, genotype, metabolic biomarkers, and gut microbiome for personalized dietary recommendations to optimize dietary response and health. Precision nutrition is suggested to be an alternative and potentially more effective strategy to improve dietary intake and prevention of obesity and chronic diseases. The purpose of this narrative review is to synthesize the current research and examine the state of the science regarding the effect of precision nutrition in improving the risk factors of obesity and type 2 diabetes.

RECENT FINDINGS

The results of the research review indicate to a large extent significant evidence supporting the effectiveness of precision nutrition in improving the risk factors of obesity and type 2 diabetes. Deeper insights and further rigorous research into the diet-phenotype-genotype and interactions of other components of precision nutrition may enable this innovative approach to be adapted in health care and public health to the special needs of individuals. Precision nutrition provides the strategy to make individualized dietary recommendations by integrating genetic, phenotypic, nutritional, lifestyle, medical, social, and other pertinent characteristics about individuals, as a means to address the challenges of generalized dietary recommendations. The evidence presented in this review shows that precision nutrition markedly improves risk factors of obesity and type 2 diabetes, particularly behavior change.

Combined analysis of inorganic elements and flavonoid metabolites reveals the relationship between flower quality and maturity of Sophora japonica L

Flos Sophorae (FS), or the dried flower buds of Sophora japonica L., is widely used as a food and medicinal material in China. The quality of S. japonica flowers varies with the developmental stages (S1-S5) of the plant. However, the relationship between FS quality and maturity remains unclear. Inductively coupled plasma optical emission spectrometry (ICP-OES) and ultra-high performance liquid chromatography coupled with electrospray ionization-triple quadrupole-linear ion trap mass spectrometry (UPLC-ESI-Q TRAP-MS/MS) were used to analyze inorganic elements and flavonoid metabolites, respectively. A combined analysis of the inorganic elements and flavonoid metabolites in FS was conducted to determine the patterns of FS quality formation. Sixteen inorganic elements and 173 flavonoid metabolites that accumulated at different developmental stages were identified. Notably, 54 flavonoid metabolites associated with the amelioration of major human diseases were identified, and Ca, P, K, Fe, and Cu were postulated to influence flavonoid metabolism and synthesis. This study offers a novel perspective and foundation for the further exploration of the rules governing the quality of plant materials.

Utilising the precision nutrition toolkit in the path towards precision medicine

The overall aim of precision nutrition is to replace the 'one size fits all' approach to dietary advice with recommendations that are more specific to the individual in order to improve the prevention or management of chronic disease. Interest in precision nutrition has grown with advancements in technologies such as genomics, proteomics, metabolomics and measurement of the gut microbiome. Precision nutrition initiatives have three major applications in precision medicine. First, they aim to provide more 'precision' dietary assessments through artificial intelligence, wearable devices or by employing omic technologies to characterise diet more precisely. Secondly, precision nutrition allows us to understand the underlying mechanisms of how diet influences disease risk and identify individuals who are more susceptible to disease due to gene-diet or microbiota-diet interactions. Third, precision nutrition can be used for 'personalised nutrition' advice where machine-learning algorithms can integrate data from omic profiles with other personal and clinical measures to improve disease risk. Proteomics and metabolomics especially provide the ability to discover new biomarkers of food or nutrient intake, proteomic or metabolomic signatures of diet and disease, and discover potential mechanisms of diet-disease interactions. Although there are several challenges that must be overcome to improve the reproducibility, cost-effectiveness and efficacy of these approaches, precision nutrition methodologies have great potential for nutrition research and clinical application.

Effects of Pera Orange Juice and Moro Orange Juice in Healthy Rats: A Metabolomic Approach

Cardiovascular disease is a leading cause of death worldwide. Heart failure is a cardiovascular disease with high prevalence, morbidity, and mortality. Several natural compounds have been studied for attenuating pathological cardiac remodeling. Orange juice has been associated with cardiovascular disease prevention by attenuating oxidative stress. However, most studies have evaluated isolated phytochemicals rather than whole orange juice and usually under pathological conditions. In this study, we evaluated plasma metabolomics in healthy rats receiving Pera or Moro orange juice to identify possible metabolic pathways and their effects on the heart.

METHODS

Sixty male Wistar rats were allocated into 3 groups: control (C), Pera orange juice (PO), and Moro orange juice (MO). PO and MO groups received Pera orange juice or Moro orange juice, respectively, and C received water with maltodextrin (100 g/L). Echocardiogram and euthanasia were performed after 4 weeks. Plasma metabolomic analysis was performed by high-resolution mass spectrometry. Type I collagen was evaluated in picrosirius red-stained slides and matrix metalloproteinase (MMP)-2 activity by zymography. MMP-9, tissue inhibitor of metalloproteinase (TIMP)-2, TIMP-4, type I collagen, and TNF-α protein expression were evaluated by Western blotting.

RESULTS

We differentially identified three metabolites in PO (N-docosahexaenoyl-phenylalanine, diglyceride, and phosphatidylethanolamine) and six in MO (N-formylmaleamic acid, N2-acetyl-L-ornithine, casegravol isovalerate, abscisic alcohol 11-glucoside, cyclic phosphatidic acid, and torvoside C), compared to controls, which are recognized for their possible roles in cardiac remodeling, such as extracellular matrix regulation, inflammation, oxidative stress, and membrane integrity. Cardiac function, collagen level, MMP-2 activity, and MMP-9, TIMP-2, TIMP-4, type I collagen, and TNF-α protein expression did not differ between groups.

CONCLUSION

Ingestion of Pera and Moro orange juice induces changes in plasma metabolites related to the regulation of extracellular matrix, inflammation, oxidative stress, and membrane integrity in healthy rats. Moro orange juice induces a larger number of differentially expressed metabolites than Pera orange juice. Alterations in plasma metabolomics induced by both orange juice are not associated with modifications in cardiac extracellular matrix components. Our results allow us to postulate that orange juice may have beneficial effects on pathological cardiac remodeling.

Irritable bowel syndrome - controversies in diagnosis and management

INTRODUCTION

The irritable bowel syndrome (IBS) is the best-recognized disorder of gut brain interactions (DGBI). However, it is controversial if the Rome IV criteria iteration for IBS diagnosis is fit for purpose.

AREAS COVERED

This review critically evaluates Rome IV criteria for diagnosis of IBS and addresses clinical considerations in IBS treatment and management, including dietary factors, biomarkers, disease mimics, symptom severity, and subtypes. The role of diet in IBS is critically reviewed along with the influence of the microbiota, including small intestinal bacterial overgrowth.

EXPERT OPINION

Emerging data suggest the Rome IV criteria are more suitable for identifying severe IBS and least useful for sub-diagnostic patients who are still likely to benefit from IBS treatment. Despite convincing evidence that IBS symptoms are diet-driven and often postprandial, a relationship to eating is not a Rome IV diagnostic criterion. Few IBS biomarkers have been identified, suggesting the syndrome is too heterogeneous to be measured by a single marker, and combined biomarker, clinical, dietary, and microbial profiling may be needed for objective characterization. With many organic diseases mimicking and overlapping with IBS, it's important clinicians are knowledgable about this to mitigate the risk of missing comorbid organic intestinal disease and to optimally treat IBS symptoms.

Demographic, Health and Lifestyle Factors Associated with the Metabolome in Older Women

Demographic and clinical factors influence the metabolome. The discovery and validation of disease biomarkers are often challenged by potential confounding effects from such factors. To address this challenge, we investigated the magnitude of the correlation between serum and urine metabolites and demographic and clinical parameters in a well-characterized observational cohort of 444 post-menopausal women participating in the Women’s Health Initiative (WHI). Using LC-MS and lipidomics, we measured 157 aqueous metabolites and 756 lipid species across 13 lipid classes in serum, along with 195 metabolites detected by GC-MS and NMR in urine and evaluated their correlations with 29 potential disease risk factors, including demographic, dietary and lifestyle factors, and medication use. After controlling for multiple testing (FDR < 0.01), we found that log-transformed metabolites were mainly associated with age, BMI, alcohol intake, race, sample storage time (urine only), and dietary supplement use. Statistically significant correlations were in the absolute range of 0.2–0.6, with the majority falling below 0.4. Incorporation of important potential confounding factors in metabolite and disease association analyses may lead to improved statistical power as well as reduced false discovery rates in a variety of data analysis settings.

NEMoE: a nutrition aware regularized mixture of experts model to identify heterogeneous diet-microbiome-host health interactions

BACKGROUND

Unrevealing the interplay between diet, the microbiome, and the health state could enable the design of personalized intervention strategies and improve the health and well-being of individuals. A common approach to this is to divide the study population into smaller cohorts based on dietary preferences in the hope of identifying specific microbial signatures. However, classification of patients based solely on diet is unlikely to reflect the microbiome-host health relationship or the taxonomic microbiome makeup.

RESULTS

We present a novel approach, the Nutrition-Ecotype Mixture of Experts (NEMoE) model, for establishing associations between gut microbiota and health state that accounts for diet-specific cohort variability using a regularized mixture of experts model framework with an integrated parameter sharing strategy to ensure data-driven diet-cohort identification consistency across taxonomic levels. The success of our approach was demonstrated through a series of simulation studies, in which NEMoE showed robustness with regard to parameter selection and varying degrees of data heterogeneity. Further application to real-world microbiome data from a Parkinson's disease cohort revealed that NEMoE is capable of not only improving predictive performance for Parkinson's Disease but also for identifying diet-specific microbial signatures of disease.

CONCLUSION

In summary, NEMoE can be used to uncover diet-specific relationships between nutritional-ecotype and patient health and to contextualize precision nutrition for different diseases. Video Abstract.

Personalized Dietary Regimens for Inflammatory Bowel Disease: Current Knowledge and Future Perspectives

Inflammatory bowel diseases (IBD) are chronic and incurable conditions of the gastro-intestinal tract with an increasing incidence and prevalence worldwide. Common symptoms are abdominal pain, diarrhea, and weight loss. Despite recent advances in medical management, many patients fail to achieve clinical remission and healing of the mucosa of the bowel. The cause is thought to involve an inappropriate reaction of the immune system, the microbiome and the environment in genetically susceptible individuals, leading to chronic bowel inflammation. Evidence is emerging that diet is a key environmental factor that might influence disease onset and course, and therefore may become a therapeutic strategy to mitigate inflammation and symptoms. Since IBD is a heterogeneous disease on a clinical and a molecular level, personalizing dietary advice could be the crucial factor to achieve long-lasting changes in dietary behaviors that could not only improve nutritional status but also tackle gut inflammation and abdominal symptoms on an individual level. In this review, we first discuss different aspects of personalized nutrition, namely the level, focus, and scope of personalized dietary regimens. Then, we provide a framework for the different goals of nutritional therapy in IBD and current evidence for personalized dietary approaches. Lastly, we discuss the need for adequate trial designs, access to the right data types and the bioinformatic tools that are necessary to develop algorithms that will allow us to move from general "healthy eating" advice to truly personalized nutritional plans for the individual IBD patient.

Linking Air Pollution Exposure to Blood-Based Metabolic Features in a Community-Based Aging Cohort with and without Dementia

BACKGROUND

Long-term exposure to air pollution has been associated with changes in levels of metabolites measured in the peripheral blood. However, most research has been conducted in ethnically homogenous, young or middle-aged populations.

OBJECTIVE

To study the relationship between the plasma metabolome and long-term exposure to three air pollutants: particulate matter (PM) less than 2.5μm in aerodynamic diameter (PM2.5), PM less than 10μm in aerodynamic diameter (PM10), and nitrogen dioxide (NO2) in an ethnically diverse, older population.

METHODS

Plasma metabolomic profiles of 107 participants of the Washington Heights and Inwood Community Aging Project in New York City, collected from 1995-2015, including non-Hispanic white, Caribbean Hispanic, and non-Hispanic Black older adults were used. We estimated the association between each metabolic feature and predicted annual mean exposure to the air pollutants using three approaches: 1) A metabolome wide association study framework; 2) Feature selection using elastic net regression; and 3) A multivariate approach using partial-least squares discriminant analysis.

RESULTS

79 features associated with exposure to PM2.5 but none associated with PM10 or NO2. PM2.5 exposure was associated with altered amino acid metabolism, energy production, and oxidative stress response, pathways also associated with Alzheimer's disease. Three metabolites were associated with PM2.5 exposure through all three approaches: cysteinylglycine disulfide, a diglyceride, and a dicarboxylic acid. The relationship between several features and PM2.5 exposure was modified by diet and metabolic diseases.

CONCLUSIONS

These relationships uncover the mechanisms through which PM2.5 exposure can lead to altered metabolic outcomes in an older population.

A discriminant analysis of plasma metabolomics for the assessment of metabolic responsiveness to red raspberry consumption

Background

Many studies show that the intake of raspberries is beneficial to immune-metabolic health, but the responses of individuals are heterogeneous and not fully understood.

Methods

In a two-arm parallel-group, randomized, controlled trial, immune-metabolic outcomes and plasma metabolite levels were analyzed before and after an 8-week red raspberry consumption. Based on partial least squares discriminant analysis (PLS-DA) on plasma xenobiotic levels, adherence to the intervention was first evaluated. A second PLS-DA followed by hierarchical clustering was used to classify individuals into response subgroups. Clinical immune and metabolic outcomes, including insulin resistance (HOMA-IR) and sensitivity (Matsuda, QUICKI) indices, during the intervention were assessed and compared between response subgroups.

Results

Two subgroups of participants, type 1 responders (n = 17) and type 2 responders (n = 5), were identified based on plasma metabolite levels measured during the intervention. Type 1 responders showed neutral to negative effects on immune-metabolic clinical parameters after raspberry consumption, and type 2 responders showed positive effects on the same parameters. Changes in waist circumference, waist-to-hip ratio, fasting plasma apolipoprotein B, C-reactive protein and insulin levels as well as Matsuda, HOMA-IR and QUICKI were significantly different between the two response subgroups. A deleterious effect of two carotenoid metabolites was also observed in type 1 responders but these variables were significantly associated with beneficial changes in the QUICKI index and in fasting insulin levels in type 2 responders. Increased 3-ureidopropionate levels were associated with a decrease in the Matsuda index in type 2 responders, suggesting that this metabolite is associated with a decrease in insulin sensitivity for those subjects, whereas the opposite was observed for type 1 responders.

Conclusion

The beneficial effects associated with red raspberry consumption are subject to inter-individual variability. Metabolomics-based clustering appears to be an effective way to assess adherence to a nutritional intervention and to classify individuals according to their immune-metabolic responsiveness to the intervention. This approach may be replicated in future studies to provide a better understanding of how interindividual variability impacts the effects of nutritional interventions on immune-metabolic health.

Applying Image-Based Food-Recognition Systems on Dietary Assessment: A Systematic Review

Dietary assessment can be crucial for the overall well-being of humans and, at least in some instances, for the prevention and management of chronic, life-threatening diseases. Recall and manual record-keeping methods for food-intake monitoring are available, but often inaccurate when applied for a long period of time. On the other hand, automatic record-keeping approaches that adopt mobile cameras and computer vision methods seem to simplify the process and can improve current human-centric diet-monitoring methods. Here we present an extended critical literature overview of image-based food-recognition systems (IBFRS) combining a camera of the user's mobile device with computer vision methods and publicly available food datasets (PAFDs). In brief, such systems consist of several phases, such as the segmentation of the food items on the plate, the classification of the food items in a specific food category, and the estimation phase of volume, calories, or nutrients of each food item. A total of 159 studies were screened in this systematic review of IBFRS. A detailed overview of the methods adopted in each of the 78 included studies of this systematic review of IBFRS is provided along with their performance on PAFDs. Studies that included IBFRS without presenting their performance in at least 1 of the above-mentioned phases were excluded. Among the included studies, 45 (58%) studies adopted deep learning methods and especially convolutional neural networks (CNNs) in at least 1 phase of the IBFRS with input PAFDs. Among the implemented techniques, CNNs outperform all other approaches on the PAFDs with a large volume of data, since the richness of these datasets provides adequate training resources for such algorithms. We also present evidence for the benefits of application of IBFRS in professional dietetic practice. Furthermore, challenges related to the IBFRS presented here are also thoroughly discussed along with future directions.

Emergence of nutrigenomics and dietary components as a complementary therapy in cancer prevention

Cancer is an illness characterized by abnormal cell development and the capability to infiltrate or spread to rest of the body. A tumor is the term for this abnormal growth that develops in solid tissues like an organ, muscle, or bone and can spread to other parts of the body through the blood and lymphatic systems. Nutrition is a critical and immortal environmental component in the development of all living organisms encoding the relationship between a person's nutrition and their genes. Nutrients have the ability to modify gene expression and persuade alterations in DNA and protein molecules which is researched scientifically in nutrigenomics. These interactions have a significant impact on the pharmacokinetic properties of bioactive dietary components as well as their site of action/molecular targets. Nutrigenomics encompasses nutrigenetics, epigenetics, and transcriptomics as well as other "omic" disciplines like proteomics and metabolomics to explain the vast disparities in cancer risk among people with roughly similar life style. Clinical trials and researches have evidenced that alternation of dietary habits is potentially one of the key approaches for reducing cancer risk in an individual. In this article, we will target how nutrigenomics and functional food work as preventive therapy in reducing the risk of cancer.

Polymorphisms, diet and nutrigenomics

Every human being possesses an exclusive nutritional blueprint inside their genes. Bioactive food components and nutrients affect the expression of such genes. Nutrigenomics is the science that analyzes gene-nutrient interactions (nutrigenetics), which can lead to the development of personalized nutritional recommendations to maintain optimal health and prevent disease. Genomic diversity among various ethnic groups might affect nutrients bioavailability as well as their metabolism. Nutrigenomics combines different branches of science including nutrition, bioinformatics, genomics, molecular biology, molecular medicine, and epidemiology. Genes regulate intake and metabolism of different nutrients, while nutrients positively or negatively influence the expression of a number of genes; testing of specific genetic polymorphisms may therefore become a useful tool to manage weight loss and to fully understand gene-nutrient interactions. Indeed, several approaches are used to study gene-nutrient interactions: epigenetics, the study of genome modification not related to changes in nucleotide sequence; transcriptomics, the study of tissue-specific and time-specific RNA transcripts; proteomics, the study of proteins involved in biological processes; and metabolomics, the study of changes of primary and secondary metabolites in body fluids and tissues. Hence, the use of nutrigenomics to improve and optimize a healthy, balanced diet in clinical settings could be an effective approach for long-term lifestyle changes that might lead to consistent weight loss and improve quality of life.

Metabolomics-Driven Mining of Metabolite Resources: Applications and Prospects for Improving Vegetable Crops

Vegetable crops possess a prominent nutri-metabolite pool that not only contributes to the crop performance in the fields, but also offers nutritional security for humans. In the pursuit of identifying, quantifying and functionally characterizing the cellular metabolome pool, biomolecule separation technologies, data acquisition platforms, chemical libraries, bioinformatics tools, databases and visualization techniques have come to play significant role. High-throughput metabolomics unravels structurally diverse nutrition-rich metabolites and their entangled interactions in vegetable plants. It has helped to link identified phytometabolites with unique phenotypic traits, nutri-functional characters, defense mechanisms and crop productivity. In this study, we explore mining diverse metabolites, localizing cellular metabolic pathways, classifying functional biomolecules and establishing linkages between metabolic fluxes and genomic regulations, using comprehensive metabolomics deciphers of the plant’s performance in the environment. We discuss exemplary reports covering the implications of metabolomics, addressing metabolic changes in vegetable plants during crop domestication, stage-dependent growth, fruit development, nutri-metabolic capabilities, climatic impacts, plant-microbe-pest interactions and anthropogenic activities. Efforts leading to identify biomarker metabolites, candidate proteins and the genes responsible for plant health, defense mechanisms and nutri-rich crop produce are documented. With the insights on metabolite-QTL (mQTL) driven genetic architecture, molecular breeding in vegetable crops can be revolutionized for developing better nutritional capabilities, improved tolerance against diseases/pests and enhanced climate resilience in plants.

Lipidomics in nutrition research

PURPOSE OF REVIEW

This review focuses on the recent findings from lipidomics studies as related to nutrition and health research.

RECENT FINDINGS

Several lipidomics studies have investigated malnutrition, including both under- and overnutrition. Focus has been both on the early-life nutrition as well as on the impact of overfeeding later in life. Multiple studies have investigated the impact of different macronutrients in lipidome on human health, demonstrating that overfeeding with saturated fat is metabolically more harmful than overfeeding with polyunsaturated fat or carbohydrate-rich food. Diet rich in saturated fat increases the lipotoxic lipids, such as ceramides and saturated fatty-acyl-containing triacylglycerols, increasing also the low-density lipoprotein aggregation rate. In contrast, diet rich in polyunsaturated fatty acids, such as n-3 fatty acids, decreases the triacylglycerol levels, although some individuals are poor responders to n-3 supplementation.

SUMMARY

The results highlight the benefits of lipidomics in clinical nutrition research, also providing an opportunity for personalized nutrition. An area of increasing interest is the interplay of diet, gut microbiome, and metabolome, and how they together impact individuals' responses to nutritional challenges.

Asparagine, colorectal cancer, and the role of sex, genes, microbes, and diet: A narrative review

Asparagine (Asn) and enzymes that catalyze the metabolism of Asn have been linked to the regulation and propagation of colorectal cancer (CRC). Increased Asn and asparagine synthetase (ASNS) expression, both contribute to CRC progression and metastasis. In contradistinction, L-asparaginase (ASNase) which breaks down Asn, exhibits an anti-tumor effect. Metabolic pathways such as KRAS/PI3K/AKT/mTORC1 signaling and high SOX12 expression can positively regulate endogenous Asn production. Conversely, the tumor suppressor, TP53, negatively impacts ASNS, thus limiting Asn synthesis and reducing tumor burden. Asn abundance can be altered by factors extrinsic to the cancer cell such as diet, the microbiome, and therapeutic use of ASNase. Recent studies have shown that sex-related factors can also influence the regulation of Asn, and high Asn production results in poorer prognosis for female CRC patients but not males. In this narrative review, we critically review studies that have examined endogenous and exogenous modulators of Asn bioavailability and summarize the key metabolic networks that regulate Asn metabolism. We also provide new hypotheses regarding sex-related influences on Asn, including the involvement of the sex-steroid hormone estrogen and estrogen receptors. Further, we hypothesize that sex-specific factors that influence Asn metabolism can influence clinical outcomes in CRC patients.

Metabolomics based inferences to unravel phenolic compound diversity in cereals and its implications for human gut health

Background

Scope and approach

Key findings and conclusion

•

Phenolic compounds are critical in avoiding metabolic disorders associated with oxidative stress.

•

Breeding cereal crops to enrich phenolic compounds in grains contributes to personalized nutrition.

•

A diet rich in cereal phenolics likely to increase human gut health, thereby lowering the risk of non-communicable illness.

Role of precision nutrition in improving military performance

Graphical abstract [Formula: see text] Role of precision nutrition in improving military performance.

Metabotyping for Precision Nutrition and Weight Management: Hype or Hope?

PURPOSE OF REVIEW

Precision nutrition requires a solid understanding of the factors that determine individual responses to dietary treatment. We review the current state of knowledge in identifying human metabotypes - based on circulating biomarkers - that can predict weight loss or other relevant physiological outcomes in response to diet treatment.

RECENT FINDINGS

Not many studies have been conducted in this area and the ones identified here are heterogeneous in design and methodology, and therefore difficult to synthesize and draw conclusions. The basis of the creation of metabotypes varies widely, from using thresholds for a single metabolite to using complex algorithms to generate multi-component constructs that include metabolite and genetic information. Furthermore, available studies are a mix of hypothesis-driven and hypothesis-generating studies, and most of them lack experimental testing in human trials. Although this field of research is still in its infancy, precision-based dietary intervention strategies focusing on the metabotype group level hold promise for designing more effective dietary treatments for obesity.

Feasibility and acceptability of a mixed model digital study to explore the effect of a daily collagen peptide supplement on digestive symptoms in healthy females: findings from a pilot study. (Preprint)

Background

Objective

Methods

Results

Conclusions

Trial Registration

The impact of ethnicity and intra-pancreatic fat on the postprandial metabolome response to whey protein in overweight Asian Chinese and European Caucasian women with prediabetes

The "Thin on the Outside Fat on the Inside" TOFI_Asia study found Asian Chinese to be more susceptible to Type 2 Diabetes (T2D) compared to European Caucasians matched for gender and body mass index (BMI). This was influenced by degree of visceral adipose deposition and ectopic fat accumulation in key organs, including liver and pancreas, leading to altered fasting plasma glucose, insulin resistance, and differences in plasma lipid and metabolite profiles. It remains unclear how intra-pancreatic fat deposition (IPFD) impacts TOFI phenotype-related T2D risk factors associated with Asian Chinese. Cow's milk whey protein isolate (WPI) is an insulin secretagogue which can suppress hyperglycemia in prediabetes. In this dietary intervention, we used untargeted metabolomics to characterize the postprandial WPI response in 24 overweight women with prediabetes. Participants were classified by ethnicity (Asian Chinese, n=12; European Caucasian, n=12) and IPFD (low IPFD < 4.66%, n=10; high IPFD ≥ 4.66%, n=10). Using a cross-over design participants were randomized to consume three WPI beverages on separate occasions; 0 g (water control), 12.5 g (low protein, LP) and 50 g (high protein, HP), consumed when fasted. An exclusion pipeline for isolating metabolites with temporal (T_0-240mins) WPI responses was implemented, and a support vector machine-recursive feature elimination (SVM-RFE) algorithm was used to model relevant metabolites by ethnicity and IPFD classes. Metabolic network analysis identified glycine as a central hub in both ethnicity and IPFD WPI response networks. A depletion of glycine relative to WPI concentration was detected in Chinese and high IPFD participants independent of BMI. Urea cycle metabolites were highly represented among the ethnicity WPI metabolome model, implicating a dysregulation in ammonia and nitrogen metabolism among Chinese participants. Uric acid and purine synthesis pathways were enriched within the high IPFD cohort's WPI metabolome response, implicating adipogenesis and insulin resistance pathways. In conclusion, the discrimination of ethnicity from WPI metabolome profiles was a stronger prediction model than IPFD in overweight women with prediabetes. Each models' discriminatory metabolites enriched different metabolic pathways that help to further characterize prediabetes in Asian Chinese women and women with increased IPFD, independently.

Comparative metagenomics analysis reveals how the diet shapes the gut microbiota in several small mammals

The gut microbiomes of the host are large and complex communities, which helps to maintain homeostasis, improves digestive efficiency, and promotes the development of the immune system. The small mammals distributed in Sichuan Province are the most popular species for biodiversity research in Southwest China. However, the effects of different diets on the structure and function of the gut microbial community of these small mammals are poorly understood. In this study, whole-metagenome shotgun sequencing has been used to analyze the composition and functional structures of the gut microbiota of seven small mammals in Laojunshan National Nature Reserve, Sichuan Province, China. Taxonomic classification revealed that the most abundant phyla in the gut of seven small mammals were Bacteroides, Proteobacteria, and Firmicutes. Moreover, Hafnia, Lactobacillus, and Yersinia were the most abundant genus in the gut microbiomes of these seven species. At the functional level, we annotated a series of KEGG functional pathways, six Cazy categories, and 46,163 AROs in the gut microbiomes of the seven species. Comparative analysis found that the difference in the gut microbiomes between the Soricidea and Muridae concentrated on the increase in the F/B (Firmicutes/Bacteroides) ratio in the Soricidea group, probably driven by the high-fat and -calorie digestive requirements due to their insectivorous diet. The comparative functional profiling revealed that functions related to metabolism and carbohydrates were significantly more abundant in Muridae group, which may be attributed to their high carbohydrate digestion requirements caused by their herbivorous diet. These data suggested that different diets in the host may play an important role in shaping the gut microbiota, and lay the foundation for teasing apart the influences of heritable and environmental factors on the evolution of gut microbial communities.

Defining Blood Plasma and Serum Metabolome by GC-MS

Metabolomics uses advanced analytical chemistry methods to analyze metabolites in biological samples. The most intensively studied samples are blood and its liquid components: plasma and serum. Armed with advanced equipment and progressive software solutions, the scientific community has shown that small molecules’ roles in living systems are not limited to traditional “building blocks” or “just fuel” for cellular energy. As a result, the conclusions based on studying the metabolome are finding practical reflection in molecular medicine and a better understanding of fundamental biochemical processes in living systems. This review is not a detailed protocol of metabolomic analysis. However, it should support the reader with information about the achievements in the whole process of metabolic exploration of human plasma and serum using mass spectrometry combined with gas chromatography.

A Global Metabolic Map Defines the Effects of a Si-Based Biostimulant on Tomato Plants under Normal and Saline Conditions

The ongoing unpredictability of climate changes is exponentially exerting a negative impact on crop production, further aggravating detrimental abiotic stress effects. Several research studies have been focused on the genetic modification of crop plants to achieve more crop resilience against such stress factors; however, there has been a paradigm shift in modern agriculture focusing on more organic, eco-friendly and long-lasting systems to improve crop yield. As such, extensive research into the use of microbial and nonmicrobial biostimulants has been at the core of agricultural studies to improve crop growth and development, as well as to attain tolerance against several biotic and abiotic stresses. However, the molecular mechanisms underlying the biostimulant activity remain enigmatic. Thus, this study is a liquid chromatography-mass spectrometry (LC-MS)-based untargeted metabolomics approach to unravel the hypothetical biochemical framework underlying effects of a nonmicrobial biostimulant (a silicon-based formulation) on tomato plants (Solanum lycopersium) under salinity stress conditions. This metabolomics study postulates that Si-based biostimulants could alleviate salinity stress in tomato plants through modulation of the primary metabolism involving changes in the tricarboxylic acid cycle, fatty acid and numerous amino acid biosynthesis pathways, with further reprogramming of several secondary metabolism pathways such as the phenylpropanoid pathway, flavonoid biosynthesis pathways including flavone and flavanol biosynthesis. Thus, the postulated hypothetical framework, describing biostimulant-induced metabolic events in tomato plants, provides actionable knowledge necessary for industries and farmers to, confidently and innovatively, explore, design, and fully implement Si-based formulations and strategies into agronomic practices for sustainable agriculture and food production.

[Analysis of metabolite differences in skin between Clapp's Favorite and its mutant Red Clapp's Favorite through non-targeted metabolomics]

为了探究西洋梨品种茄梨及其红色芽变红茄梨成熟期果皮代谢产物差异,采用超高效液相色谱-质谱联用技术,对茄梨和红茄梨成熟期果皮进行非靶向代谢组学研究。通过主成分分析和正交偏最小二乘判别分析,构建了多变量统计分析模型,结合模型和变量重要性投影与最大差异倍数值,基于精确质量数、二级碎片以及同位素分布,使用PMDB(Plant Metabolome Database)数据库进行定性,筛选并鉴定出茄梨和红茄梨果皮中显著性变化(P<0.05, VIP(variable importance in project)≥1)的差异代谢物有83种,主要包括酚酸类、黄酮类和氨基酸类物质,涉及类黄酮代谢、氨基酸代谢、苯丙烷类代谢等代谢途径,其中53种物质含量上调,30种物质表达下调。通过KEGG(Kyoto Encyclopedia of Genes and Genomes)数据库进一步对差异代谢物质进行通路富集分析,差异代谢物主要分布在20条代谢途径中,P<0.05的代谢途径有6条,分别是类黄酮生物合成、黄酮和黄酮醇生物合成、苯丙烷生物合成、丁酸酯代谢、苯丙氨酸代谢、酪氨酸代谢。这些差异代谢物的变化可能是导致茄梨和红茄梨果皮色泽不同的原因。该研究从植物代谢组学角度初步揭示了茄梨和红茄梨成熟期果皮的代谢产物差异性。

Urinary metabolites of type 2 diabetes rats fed with palm oil-enriched high fat diet

High fat diet (HFD) is one of the risk factors of obesity and diabetes. Recommended diet regimen for diabetes is difficult to abide by especially for HFD as it adds flavour to the taste buds. In this study, palm oil-enriched HFD and normal diet were fed to nicotinamide-induced type 2 diabetes rats, respectively for six weeks. Additionally, metformin, a common drug used to treat diabetes was given to rats under treatment groups. We evaluated the change of urinary metabolites of diabetes rats fed with palm oil-enriched HFD, and also after metformin treatment. Rats were divided into six-groups with different feeding diets, disease condition and with or without metformin treatment. Rats’ urine were collected at the end of six weeks feeding program and subjected to 1H-NMR and multivariate data analysis to evaluate their metabolite profiles. At the early phase of diabetes, metabolites changes in diabetic rats were associated with the disease itself. Our data showed that continuous consumption of HFD altered various metabolic pathways of diabetic rats and caused detrimental effects to the rats. On the other hand, metformin treatment combined with normal diet lessened the physiological impacts caused by diabetes condition.

Liquid Chromatography-Mass Spectrometry for Clinical Metabolomics: An Overview

Metabolomics is a discipline that offers a comprehensive analysis of metabolites in biological samples. In the last decades, the notable evolution in liquid chromatography and mass spectrometry technologies has driven an exponential progress in LC-MS-based metabolomics. Targeted and untargeted metabolomics strategies are important tools in health and medical science, especially in the study of disease-related biomarkers, drug discovery and development, toxicology, diet, physical exercise, and precision medicine. Clinical and biological problems can now be understood in terms of metabolic phenotyping. This overview highlights the current approaches to LC-MS-based metabolomics analysis and its applications in the clinical research.

A New Pipeline for the Normalization and Pooling of Metabolomics Data

Pooling metabolomics data across studies is often desirable to increase the statistical power of the analysis. However, this can raise methodological challenges as several preanalytical and analytical factors could introduce differences in measured concentrations and variability between datasets. Specifically, different studies may use variable sample types (e.g., serum versus plasma) collected, treated, and stored according to different protocols, and assayed in different laboratories using different instruments. To address these issues, a new pipeline was developed to normalize and pool metabolomics data through a set of sequential steps: (i) exclusions of the least informative observations and metabolites and removal of outliers; imputation of missing data; (ii) identification of the main sources of variability through principal component partial R-square (PC-PR2) analysis; (iii) application of linear mixed models to remove unwanted variability, including samples' originating study and batch, and preserve biological variations while accounting for potential differences in the residual variances across studies. This pipeline was applied to targeted metabolomics data acquired using Biocrates AbsoluteIDQ kits in eight case-control studies nested within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. Comprehensive examination of metabolomics measurements indicated that the pipeline improved the comparability of data across the studies. Our pipeline can be adapted to normalize other molecular data, including biomarkers as well as proteomics data, and could be used for pooling molecular datasets, for example in international consortia, to limit biases introduced by inter-study variability. This versatility of the pipeline makes our work of potential interest to molecular epidemiologists.

The evolving landscape of untargeted metabolomics

AIMS

Untargeted Metabolomics is a "hypothesis-generating discovery strategy" that compares groups of samples (e.g., cases vs controls); identifies the metabolome and establishes (early signs of) perturbations. Targeted Metabolomics helped gather key information in life sciences and disclosed novel strategies for the treatment of major clinical entities (e.g., malignancy, cardiovascular diabetes mellitus, drug toxicity). Because of its relevance in biomarker discovery, attention is now devoted to improving the translational potential of untargeted Metabolomics.

DATA SYNTHESIS

Expertise in laboratory medicine and in bioinformatics helps solve challenges/pitfalls that may bias metabolite profiling in untargeted Metabolomics. Clinical validation (availability/reliability of analytical instruments) and profitability (how many people will use the test) are mandatory steps for potential biomarkers. Biomarkers to predict individual patient response, patient populations that will best respond to specific strategies and/or approaches for an optimal response to treatment are now being developed. Additional help is expected from professional, and regulatory Agencies as to guidelines for study design and data acquisition and analysis, to be applied from the very beginning of a project. Evidence from food, plant, human, environmental, and animal research argues for the need of miniaturized approaches that employ low-cost, easy to use, mobile devices. ELISA kits with such characteristics that employ targeted metabolites are already available.

CONCLUSIONS

Improving knowledge of the mechanisms behind the disease status (pathophysiology) will help untargeted Metabolomics gather a direct positive impact on welfare and industrial advancements, and fade uncertainties perceived by regulators/payers and patients concerning variables related to miniaturised instruments and user-friendly software and databases.

Higher Alkylresorcinol Concentrations, a Consequence of Whole-Grain Intake, are Inversely Associated with Gestational Diabetes Mellitus in Iceland

BACKGROUND

A diet rich in whole grains may provide benefits for pregnant women due to whole grains' high nutritional value and dietary fiber content.

OBJECTIVES

To study the associations of whole-grain consumption, as well as the plasma alkylresorcinol concentration, a whole-grain consumption biomarker, in early pregnancy with gestational diabetes mellitus (GDM) diagnoses.

METHODS

Subjects were women from the prospective study Pregnant Women in Iceland II (PREWICE II; n = 853) who attended their ultrasound appointment in gestational weeks 11-14 during the period from October 2017 to March 2018. During that visit, whole-grain consumption was estimated using a diet screening questionnaire, and blood samples were collected for analysis of plasma alkylresorcinols (ARs). Information on GDM diagnoses was later extracted from medical records. Multivariate log-binomial regression was used to evaluate the association of dietary whole-grain and AR concentrations with GDM.

RESULTS

In total, 14.9% of the women adhered to the national food-based dietary guidelines (n = 127), which recommend 2 portions of whole grains daily. GDM was diagnosed in 127 women (14.9%). The frequency of whole-grain consumption was lower in women who were later diagnosed with GDM compared to the women without GDM (median, 5 times/week vs. 6 times/week, respectively; P = 0.02). This difference was reflected in the lower median concentration of total AR in women diagnosed with GDM (163 nmol/L vs. 209 nmol/L, respectively; P < 0.01). The quartile with the highest concentrations of AR had a RR of 0.50 (95% CI: 0.27-0.90) of being diagnosed with GDM, in comparison to the lowest quartile. There was a significant dose response in the GDM risk with higher AR levels.

CONCLUSIONS

We found that a higher consumption of whole grains, reflected both by reported consumption according to the FFQ and AR biomarkers, was associated with a decreased risk of receiving a GDM diagnosis.

Development of Personalized Nutrition: Applications in Lactose Intolerance Diagnosis and Management

Recent discoveries in the “omics” field and the growing focus on preventive health have opened new avenues for personalized nutrition (PN), which is becoming an important theme in the strategic plans of organizations that are active in healthcare, food, and nutrition research. PN holds great potential for individual health optimization, disease management, public health interventions, and product innovation. However, there are still multiple challenges to overcome before PN can be truly embraced by the public and healthcare stakeholders. The diagnosis and management of lactose intolerance (LI), a common condition with a strong inter-individual component, is explored as an interesting example for the potential role of these technologies and the challenges of PN. From the development of genetic and metabolomic LI diagnostic tests that can be carried out in the home, to advances in the understanding of LI pathology and individualized treatment optimization, PN in LI care has shown substantial progress. However, there are still many research gaps to address, including the understanding of epigenetic regulation of lactase expression and how lactose is metabolized by the gut microbiota, in order to achieve better LI detection and effective therapeutic interventions to reverse the potential health consequences of LI.

Metabolomic Biomarkers of Healthy Dietary Patterns and Cardiovascular Outcomes

PURPOSE OF REVIEW

Healthy dietary patterns are recommended for prevention of CVD. Recently, metabolomics has been used to identify biomarkers of healthy dietary patterns and elucidate mechanisms underlying diet-disease associations. This review provides an overview of approaches to define healthy dietary patterns, discusses important issues related to using metabolomics to describe healthy dietary patterns, and summarizes studies identifying blood metabolites associated with hypothesis-driven healthy dietary patterns and cardiovascular risk factors and incident CVD.

RECENT FINDINGS

We identified 17 studies which reported on blood metabolomic signatures of 5 healthy dietary patterns (Healthy Eating Index, Alternative Healthy Eating Index, the Dietary Approaches to Stop Hypertension diet, Mediterranean diet, vegetarian diet). Four of these studies evaluated associations between diet-related metabolites and cardiovascular outcomes. Many metabolites replicated across different healthy dietary patterns, which suggest that they may represent biomarkers of generally healthy diets. Unsaturated lipids positively associated with healthy dietary patterns were inversely associated with incident CVD, suggesting that they may be a pathway through which diet is associated with a lower risk of CVD. Although many metabolites replicated across cross-sectional studies, few metabolites identified as candidate biomarkers of healthy diets in feeding studies replicated in observational studies. Additionally, limited evidence exists on the ability of diet-related metabolites to predict cardiovascular outcomes. Replication of candidate biomarkers of dietary patterns in different study designs and more studies evaluating the associations between diet-related metabolites and cardiovascular outcomes are needed.

Diet affects glycosylation of serum proteins in women at risk for cardiometabolic disease

Background

Glycoproteomics deals with glycoproteins that are formed by post-translational modification when sugars (like fucose and sialic acid) are attached to protein. Glycosylation of proteins influences function, but whether glycosylation is altered by diet is unknown.

Objective

To evaluate the effect of consuming a diet based on the Dietary Guidelines for Americans on circulating glycoproteins that have previously been associated with cardiometabolic diseases.

Design

Forty-four women, with one or more metabolic syndrome characteristics, completed an 8-week randomized controlled feeding intervention (n = 22) consuming a diet based on the Dietary Guidelines for Americans (DGA 2010); the remaining consumed a ‘typical American diet’ (TAD, n = 22). Fasting serum samples were obtained at week0 (baseline) and week8 (post-intervention); 17 serum proteins were chosen for targeted analyses. Protein standards and serum samples were analyzed in a UHPLC-MS protocol to determine peptide concentration and their glycan (fucosylation or sialylation) profiles. Data at baseline were used in correlational analyses; change in proteins and glycans following intervention were used in non-parametric analyses.

Results

At baseline, women with more metabolic syndrome characteristics had more fucosylation (total di-fucosylated proteins: p = 0.045) compared to women with a lesser number of metabolic syndrome characteristics. Dietary refined grain intake was associated with increased total fucosylation (ρ = − 0.530, p < 0.001) and reduced total sialylation (ρ = 0.311, p = 0.042). After the 8-week intervention, there was higher sialylation following the DGA diet (Total di-sialylated protein p = 0.018, poly-sialylated orosomucoid p = 0.012) compared to the TAD diet.

Conclusions

Based on this study, glycosylation of proteins is likely affected by dietary patterns; higher sialylation was associated with a healthier diet pattern. Altered glycosylation is associated with several diseases, particularly cancer and type 2 diabetes, and this study raises the possibility that diet may influence disease state by altering glycosylation.

Clinical trial registration

NCT02298725 at clinicaltrials.gov; https://clinicaltrials.gov/ct2/show/NCT02298725.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00394-021-02539-7.

The Gut Microbiome and Ozone-induced Airway Hyperresponsiveness. Mechanisms and Therapeutic Prospects

In recent years, several new asthma therapeutics have been developed. Although many of these agents show promise in treating allergic asthma, they are less effective against nonallergic forms of asthma. The gut microbiome has important roles in human health and disease, and a growing body of evidence indicates a link between the gut microbiome and asthma. Here, we review those data focusing on the role of the microbiome in mouse models of nonallergic asthma including obese asthma and asthma triggered by exposure to air pollutants. We describe the impact of antibiotics, diet, and early life events on airway responses to the air pollutant ozone, including in the setting of obesity. We also review potential mechanisms responsible for gut-lung interactions focusing on bacterial-derived metabolites, the immune system, and hormones. Finally, we discuss future prospects for gut microbiome-targeted therapies such as fecal microbiome transplantation, prebiotics, probiotics, and prudent use of antibiotics. Better understanding of the role of the microbiome in airway responses may lead to exploration of new microbiome-targeted therapies to control asthma, especially nonallergic forms of asthma.

Metabolite Differences of Polyphenols in Different Litchi Cultivars (Litchi chinensis Sonn.) Based on Extensive Targeted Metabonomics

Litchi is an important fruit cultivated in tropical and subtropical areas with high nutritious and delicious flavor and the pulp is the main part of the fruit consumed. Previous studies found that litchi had high total phenol content and antioxidant activity, but most of them focused on the identification of single or a few phenolic components with a low throughput test, and the metabolic differences of cultivars are still unknown to a some extent. In this study we used widely targeted metabolome based on ultra-performance liquid chromatography coupled with mass spectrometry (UPLC-MS/MS) to analyze the polyphenol metabolites of five different genotypes of mature litchi fruit. A total of 126 polyphenol metabolites in eight categories were identified to reveal the composition and differences of polyphenol; 15 common differential metabolites and 20 specific differential metabolites to each cultivar were found for the first time. The results infer that flavonoids, flavonols, hydroxycinnamoyls and catechins are the main polyphenol metabolites of litchi pulp. Cluster analysis showed that there were three groups of polyphenols from high to low; early maturing Feizhixiao is a kind of high polyphenol content cultivars, especially in catechins, anthocyanins, flavonols, quinic acids and hydroxycinnamoyls. The polyphenols in the flesh of mature litchi are rich, and there are significant differences among cultivars; there was a level of correlation between the contents of phenolics and the maturity of litchi cultivars; the content of phenolics in early maturing litchi cultivars appeared higher than those of mid- to late-maturing cultivars. This experiment will provide significant reference information for cultivation, breeding, processing and consumption.

Identification of Accessible Hepatic Gene Signatures for Interindividual Variations in Nutrigenomic Response to Dietary Supplementation of Omega-3 Fatty Acids

Dietary supplementation is a widely adapted strategy to maintain nutritional balance for improving health and preventing chronic diseases. Conflicting results in studies of similar design, however, suggest that there is substantial heterogenicity in individuals’ responses to nutrients, and personalized nutrition is required to achieve the maximum benefit of dietary supplementation. In recent years, nutrigenomics studies have been increasingly utilized to characterize the detailed genomic response to a specific nutrient, but it remains a daunting task to define the signatures responsible for interindividual variations to dietary supplements for tissues with limited accessibility. In this work, we used the hepatic response to omega-3 fatty acids as an example to probe such signatures. Through comprehensive analysis of nutrigenomic response to eicosapentaneoid acid (EPA) and/or docosahexaenoic acid (DHA) including both protein coding and long noncoding RNA (lncRNA) genes in human hepatocytes, we defined the EPA- and/or DHA-specific signature genes in hepatocytes. By analyzing gene expression variations in livers of healthy and relevant disease populations, we identified a set of protein coding and lncRNA signature genes whose responses to omega-3 fatty acid exhibit very high interindividual variabilities. The large variabilities of individual responses to omega-3 fatty acids were further validated in human hepatocytes from ten different donors. Finally, we profiled RNAs in exosomes isolated from the circulation of a liver-specific humanized mouse model, in which the humanized liver is the sole source of human RNAs, and confirmed the in vivo detectability of some signature genes, supporting their potential as biomarkers for nutrient response. Taken together, we have developed an efficient and practical procedure to identify nutrient-responsive gene signatures as well as accessible biomarkers for interindividual variations.

The complexities of the diet-microbiome relationship: advances and perspectives

Personalised dietary modulation of the gut microbiota may be key to disease management. Current investigations provide a broad understanding of the impact of diet on the composition and activity of the gut microbiota, yet detailed knowledge in applying diet as an actionable tool remains limited. Further to the relative novelty of the field, approaches are yet to be standardised and extremely heterogeneous research outcomes have ensued. This may be related to confounders associated with complexities in capturing an accurate representation of both diet and the gut microbiota. This review discusses the intricacies and current methodologies of diet-microbial relations, the implications and limitations of these investigative approaches, and future considerations that may assist in accelerating applications. New investigations should consider improved collection of dietary data, further characterisation of mechanistic interactions, and an increased focus on -omic technologies such as metabolomics to describe the bacterial and metabolic activity of food degradation, together with its crosstalk with the host. Furthermore, clinical evidence with health outcomes is required before therapeutic dietary strategies for microbial amelioration can be made. The potential to reach detailed understanding of diet-microbiota relations may depend on re-evaluation, progression, and unification of research methodologies, which consider the complexities of these interactions.

A Protocol for Untargeted Metabolomic Analysis: From Sample Preparation to Data Processing

Untargeted metabolomics has rapidly become a profiling method of choice in many areas of research, including mitochondrial biology. Most commonly, untargeted metabolomics is performed with liquid chromatography/mass spectrometry because it enables measurement of a relatively wide range of physiochemically diverse molecules. Specifically, to assess energy pathways that are associated with mitochondrial metabolism, hydrophilic interaction liquid chromatography (HILIC) is often applied before analysis with a high-resolution accurate mass instrument. The workflow produces large, complex data files that are impractical to analyze manually. Here, we present a protocol to perform untargeted metabolomics on biofluids such as plasma, urine, and cerebral spinal fluid with a HILIC separation and an Orbitrap mass spectrometer. Our protocol describes each step of the analysis in detail, from preparation of solvents for chromatography to selecting parameters during data processing.