Intake Biomarkers for Nutrition and Health: Review and Discussion of Methodology Issues

Metabolomics profiles from blood, urine, or other body fluids have the potential to assess intakes of foods and nutrients objectively, thereby strengthening nutritional epidemiology research. Metabolomics platforms may include targeted components that estimate the relative concentrations for individual metabolites in a predetermined set, or global components, typically involving mass spectrometry, that estimate relative concentrations more broadly. While a specific metabolite concentration usually correlates with the intake of a single food or food group, multiple metabolites may be correlated with the intake of certain foods or with specific nutrient intakes, each of which may be expressed in absolute terms or relative to total energy intake. Here, I briefly review the progress over the past 20 years on the development and application intake biomarkers for foods/food groups, nutrients, and dietary patterns, primarily by drawing from several recent reviews. In doing so, I emphasize the criteria and study designs for candidate biomarker identification, biomarker validation, and intake biomarker application. The use of intake biomarkers for diet and chronic disease association studies is still infrequent in nutritional epidemiology research. My comments here will derive primarily from our research group's recent contributions to the Women's Health Initiative cohorts. I will complete the contribution by describing some opportunities to build on the collective 20 years of effort, including opportunities related to the metabolomics profiling of blood and urine specimens from human feeding studies that approximate habitual diets.

Transforming Big Data into AI-ready data for nutrition and obesity research

OBJECTIVE

Big Data are increasingly used in obesity and nutrition research to gain new insights and derive personalized guidance; however, this data in raw form are often not usable. Substantial preprocessing, which requires machine learning (ML), human judgment, and specialized software, is required to transform Big Data into artificial intelligence (AI)- and ML-ready data. These preprocessing steps are the most complex part of the entire modeling pipeline. Understanding the complexity of these steps by the end user is critical for reducing misunderstanding, faulty interpretation, and erroneous downstream conclusions.

METHODS

We reviewed three popular obesity/nutrition Big Data sources: microbiome, metabolomics, and accelerometry. The preprocessing pipelines, specialized software, challenges, and how decisions impact final AI- and ML-ready products were detailed.

RESULTS

Opportunities for advances to improve quality control, speed of preprocessing, and intelligent end user consumption were presented.

CONCLUSIONS

Big Data have the exciting potential for identifying new modifiable factors that impact obesity research. However, to ensure accurate interpretation of conclusions arising from Big Data, the choices involved in preparing AI- and ML-ready data need to be transparent to investigators and clinicians relying on the conclusions.

Metabolomics analysis of physicochemical properties associated with freshness degradation in frozen Antarctic krill (Euphausia superba)

This study aimed to determine the effect of different frozen temperatures during storage on the quality of Antarctic krill (Euphausia superba) and assess the change at the metabolite level via a combination of physicochemical property analysis, liquid chromatography-tandem mass spectrometry (LC-MS) based non-targeted metabolomics profiling. Regarding samples stored at -20 °C, the expressions of 7055 metabolites were elevated, while 2313 were downregulated. Lipids and lipid molecules had the highest proportion of differential metabolites. A total of 432 discriminatory metabolites with Kyoto Encyclopedia of Genes and Genomes (KEGG) IDs was obtained. We also observed that the concentrations of differential bitter free amino acids (FAAs) and oxidation products of arachidonic and linoleic acid increased. Moreover, as the storage temperature increased, the freshness, umami, and sweetness components were considerably reduced. Furthermore, results indicated that the color, pH and water-holding capacity (WHC) were potential indicators of quality deterioration, while inosinic acid was a probable biomarker for umami degradation of frozen Antarctic krill. In conclusion, this study demonstrates that storage at lower temperatures can be beneficial for maintaining the freshness of Antarctic krill from macro and micro perspectives.

Implementation of multiomic mass spectrometry approaches for the evaluation of human health following environmental exposure

Omics analyses collectively refer to the possibility of profiling genetic variants, RNA, epigenetic markers, proteins, lipids, and metabolites. The most common analytical approaches used for detecting molecules present within biofluids related to metabolism are vibrational spectroscopy techniques, represented by infrared, Raman, and nuclear magnetic resonance (NMR) spectroscopies and mass spectrometry (MS). Omics-based assessments utilizing MS are rapidly expanding and being applied to various scientific disciplines and clinical settings. Most of the omics instruments are operated by specialists in dedicated laboratories; however, the development of miniature portable omics has made the technology more available to users for field applications. Variations in molecular information gained from omics approaches are useful for evaluating human health following environmental exposure and the development and progression of numerous diseases. As MS technology develops so do statistical and machine learning methods for the detection of molecular deviations from personalized metabolism, which are correlated to altered health conditions, and they are intended to provide a multi-disciplinary overview for researchers interested in adding multiomic analysis to their current efforts. This includes an introduction to mass spectrometry-based omics technologies, current state-of-the-art capabilities and their respective strengths and limitations for surveying molecular information. Furthermore, we describe how knowledge gained from these assessments can be applied to personalized medicine and diagnostic strategies.

mini-MED: study protocol for a randomized, multi-intervention, semi-controlled feeding trial of a Mediterranean-amplified vs. habitual Western dietary pattern for the evaluation of food-specific compounds and cardiometabolic health

BACKGROUND

Diet is among the most influential lifestyle factors impacting chronic disease risk. Nutrimetabolomics, the application of metabolomics to nutrition research, allows for the detection of food-specific compounds (FSCs) that can be used to connect dietary patterns, such as a Mediterranean-style (MED) diet, to health. This validation study is based upon analyses from a controlled feeding MED intervention, where our team identified FSCs from eight foods that can be detected in biospecimens after consumption and may therefore serve as food intake biomarkers.

METHODS

Individuals with overweight/obesity who do not habitually consume a MED dietary pattern will complete a 16-week randomized, multi-intervention, semi-controlled feeding study of isocaloric dietary interventions: (1) MED-amplified dietary pattern, containing 500 kcal/day from eight MED target foods: avocado, basil, cherry, chickpea, oat, red bell pepper, walnut, and a protein source (alternating between salmon or unprocessed, lean beef), and (2) habitual/Western dietary pattern, containing 500 kcal/day from six non-MED target foods: cheesecake, chocolate frozen yogurt, refined grain bread, sour cream, white potato, and unprocessed, lean beef. After a 2-week washout, participants complete four, 4-week intervention periods, with biospecimen sampling and outcome assessments at baseline and at intervention weeks 4, 8, 12, and 16. The primary outcome is change in the relative abundance of FSCs from the eight MED target foods in participant biospecimens from baseline to the end of each intervention period. Secondary outcomes include mean change in cardiometabolic health indicators, inflammatory markers, and adipokines. Exploratory outcomes include change in diversity and community composition of the gut microbiota.

DISCUSSION

Our stepwise strategy, beginning with identification of FSCs in whole diets and biospecimens, followed by relating these to health indicators will lead to improved methodology for assessment of dietary patterns and a better understanding of the relationship between food and health. This study will serve as a first step toward validating candidate food intake biomarkers and allow for assessment of relationships with cardiometabolic health. The identification of food intake biomarkers is critical to future research and has implications spanning health promotion and disease prevention for many chronic conditions.

TRIAL REGISTRATION

Registered at ClinicalTrials.gov: NCT05500976 ; Date of registration: August 15, 2022.

Measuring diet by metabolomics: a 14-d controlled feeding study of weighed food intake

BACKGROUND

Metabolomics has the potential to enhance dietary assessment by revealing objective measures of many aspects of human food intake. Although metabolomics studies indicate that hundreds of metabolites are associated with dietary intake, correlations have been modest (e.g., r < 0.50), and few have been evaluated in controlled feeding studies.

OBJECTIVES

The aim of this study was to evaluate associations between metabolites and weighed food and beverage intake in a controlled feeding study of habitual diet.

METHODS

Healthy postmenopausal females from the Women's Health Initiative (N = 153) were provided with a customized 2-wk controlled diet designed to emulate their usual diet. Metabolites were measured by liquid chromatography tandem mass spectrometry in end-of-study 24-h urine and fasting serum samples (1293 urine metabolites; 1113 serum metabolites). We calculated partial Pearson correlations between these metabolites and intake of 65 food groups, beverages, and supplements during the feeding study. The threshold for significance was Bonferroni-adjusted to account for multiple testing (5.94 × 10-07 for urine metabolites; 6.91 × 10-07 for serum metabolites).

RESULTS

Significant diet-metabolite correlations were identified for 23 distinct foods, beverages, and supplements (171 distinct metabolites). Among foods, strong metabolite correlations (r ≥ 0.60) were evident for citrus (highest r = 0.80), dairy (r = 0.65), and broccoli (r = 0.63). Among beverages and supplements, strong correlations were evident for coffee (r = 0.86), alcohol (r = 0.69), multivitamins (r = 0.69), and vitamin E supplements (r = 0.65). Moderate correlations (r = 0.50-0.60) were also observed for avocado, fish, garlic, grains, onion, poultry, and black tea. Correlations were specific; each metabolite correlated with one food, beverage, or supplement, except for metabolites correlated with juice or multivitamins.

CONCLUSIONS

Metabolite levels had moderate to strong correlations with weighed intake of habitually consumed foods, beverages, and supplements. These findings exceed in magnitude those previously observed in population studies and exemplify the strong potential of metabolomics to contribute to nutrition research. The Women's Health Initiative is registered at clinicaltrials.gov as NCT00000611.

Salmon Food-Specific Compounds and Their Metabolites Increase in Human Plasma and Are Associated with Cardiometabolic Health Indicators Following a Mediterranean-Style Diet Intervention

BACKGROUND

Nutrimetabolomics allows for the comprehensive analysis of foods and human biospecimens to identify biomarkers of intake and begin to probe their associations with health. Salmon contains hundreds of compounds that may provide cardiometabolic benefits.

OBJECTIVES

We used untargeted metabolomics to identify salmon food-specific compounds (FSCs) and their predicted metabolites that were found in plasma after a salmon-containing Mediterranean-style (MED) diet intervention. Associations between changes in salmon FSCs and changes in cardiometabolic health indicators (CHIs) were also explored.

METHODS

For this secondary analysis of a randomized, crossover, controlled feeding trial, 41 participants consumed MED diets with 2 servings of salmon per week for 2 5-wk periods. CHIs were assessed, and fasting plasma was collected pre- and postintervention. Plasma, salmon, and 99 MED foods were analyzed using liquid chromatography-mass spectrometry-based metabolomics. Compounds were characterized as salmon FSCs if detected in all salmon replicates but none of the other foods. Metabolites of salmon FSCs were predicted using machine learning. For salmon FSCs and metabolites found in plasma, linear mixed-effect models were used to assess change from pre- to postintervention and associations with changes in CHIs.

RESULTS

Relative to the other 99 MED foods, there were 508 salmon FSCs with 237 unique metabolites. A total of 143 salmon FSCs and 106 metabolites were detected in plasma. Forty-eight salmon FSCs and 30 metabolites increased after the intervention (false discovery rate <0.05). Increases in 2 annotated salmon FSCs and 2 metabolites were associated with improvements in CHIs, including total cholesterol, low-density lipoprotein cholesterol, triglycerides, and apolipoprotein B.

CONCLUSIONS

A data-driven nutrimetabolomics strategy identified salmon FSCs and their predicted metabolites that were detectable in plasma and changed after consumption of a salmon-containing MED diet. Findings support this approach for the discovery of compounds in foods that may serve, upon further validation, as biomarkers or act as bioactive components influential to health. The trials supporting this work were registered at NCT02573129 (Mediterranean-style diet intervention) and NCT05500976 (ongoing clinical trial).

Plasma Metabolites Related to the Consumption of Different Types of Dairy Products and Their Association with New-Onset Type 2 Diabetes: Analyses in the Fenland and EPIC-Norfolk Studies, United Kingdom

SCOPE

To identify metabolites associated with habitual dairy consumption and investigate their associations with type 2 diabetes (T2D) risk.

METHODS AND RESULTS

Metabolomics assays were conducted in the Fenland (n = 10,281) and EPIC-Norfolk (n = 1,440) studies. Using 82 metabolites assessed in both studies, we developed metabolite scores to classify self-reported consumption of milk, yogurt, cheese, butter, and total dairy (Fenland Study-discovery set; n = 6035). Internal and external validity of the scores was evaluated (Fenland-validation set, n = 4246; EPIC-Norfolk, n = 1440). The study assessed associations between each metabolite score and T2D incidence in EPIC-Norfolk (n = 641 cases; 16,350 person-years). The scores classified low and high consumers for all dairy types with internal validity, and milk, butter, and total dairy with external validity. The scores were further associated with lower incident T2D: hazard ratios (95% confidence interval) per standard deviation: milk 0.71 (0.65, 0.77); butter 0.62 (0.57, 0.68); total dairy 0.66 (0.60, 0.72). These associations persisted after adjustment for known dairy-fat biomarkers.

CONCLUSION

Metabolite scores identified habitual consumers of milk, butter, and total dairy products, and were associated with lower T2D risk. These findings hold promise for identifying objective indicators of the physiological response to dairy consumption.

Identification of a β-Carboline Alkaloid from Chemoselectively Derived Vanilla Bean Extract and Its Prevention of Lipid Droplet Accumulation in Human Hepatocytes (HepG2)

Targeting bioactive compounds to prevent lipid droplet accumulation in the liver, we explored an antioxidative extract from vanilla bean (Vainilla planifolia) after chemo-selective derivatization through heating and acid modification. The chemical analysis of vanilla bean extract through chemoselective derivatization resulted in the identification of sixteen compounds (34-50) using LC-MS/MS analysis. A β-carboline alkaloid with a piperidine C-ring and a vanillin moiety at C-1 (34) was identified by molecular networking and diagnostic fragmentation filtering approaches. β-carboline alkaloid 34 exhibited significant inhibitory activity of lipid droplet accumulation (LDAI) in oleic acid-loaded hepatocellular carcinoma HepG2 cells. The LDAI activity was associated with both activation of lipolysis and suppression of lipogenesis in the cells. The study indicates that crude plant extracts, following chemoselective derivatization, may contain bioactive compounds that could be beneficial in preventing hepatosteatosis and could serve as a source of lead compounds for drug development. This approach may be useful to investigate other mixtures of natural products and food resources.

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.

Phytochemical profiling of three Amaranthus species using LC-MS/MS metabolomic approach and chemometric tools

Several Amaranthus vegetables (Amaranthaceae) have been recognized as valuable sources of minerals, vitamins, proteins, and phytonutrients, with health-promoting characteristics. In this study, three edible Amaranthus species, namely A. hybridus (AH), A. blitum (AB), and A. caudatus (AC), were chemically characterized using non-targeted liquid chromatography-tandem mass spectrometry (LC-MS/MS) technique. Further, multivariate chemometric analyses were conducted, including principal component analysis (PCA) and correlation-covariance plot (C-C plot). As a result, forty-one diverse compounds were identified, which varied in distribution and abundance across the investigated species. Amino acids and flavonoid glycosides were the most prevalent metabolites. Other identified compounds comprised nucleoside, chlorogenic acids, hydroxy cinnamoyl amides, and triterpenoid saponins. The most discriminant metabolites were flavonoid glycosides and hydroxy cinnamoyl amides, giving each species a chemotaxonomic identity. Advancing the chemotaxonomy of Amaranthaceae, adenosine nucleoside and N-coumaroyl-ʟ-tryptophan were first reported from this family. Isorhamnetin and tricin glycosides were uniquely identified in AC, offering useful chemotaxonomic markers for this species. Notably, AB and AH profiles shared most metabolites, yet with varying abundance. These include adenosine, nicotiflorin, dicaffeoylquinic acids, and N-trans-feruloyl-4-O-methyldopamine. However, N-coumaroyl-ʟ-tryptophan and kaempferol dirhamnoside were exclusively found in AB, separating it from AH. In conclusion, the applied analytical techniques established molecular fingerprints for the included species, identified specific biomarkers, and investigated their interconnections.

Mass spectrometry as a lens into molecular human nutrition and health

Mass spectrometry (MS) has developed over the last decades into the most informative and versatile analytical technology in molecular and structural biology (). The platform enables discovery, identification, and characterisation of non-volatile biomolecules, such as proteins, peptides, DNA, RNA, nutrients, metabolites, and lipids at both speed and scale and can elucidate their interactions and effects. The versatility, robustness, and throughput have rendered MS a major research and development platform in molecular human health and biomedical science. More recently, MS has also been established as the central tool for 'Molecular Nutrition', enabling comprehensive and rapid identification and characterisation of macro- and micronutrients, bioactives, and other food compounds. 'Molecular Nutrition' thereby helps understand bioaccessibility, bioavailability, and bioefficacy of macro- and micronutrients and related health effects. Hence, MS provides a lens through which the fate of nutrients can be monitored along digestion via absorption to metabolism. This in turn provides the bioanalytical foundation for 'Personalised Nutrition' or 'Precision Nutrition' in which design and development of diets and nutritional products is tailored towards consumer and patient groups sharing similar genetic and environmental predisposition, health/disease conditions and lifestyles, and/or objectives of performance and wellbeing. The next level of integrated nutrition science is now being built as 'Systems Nutrition' where public and personal health data are correlated with life condition and lifestyle factors, to establish directional relationships between nutrition, lifestyle, environment, and health, eventually translating into science-based public and personal heath recommendations and actions. This account provides a condensed summary of the contributions of MS to a precise, quantitative, and comprehensive nutrition and health science and sketches an outlook on its future role in this fascinating and relevant field.

Recent Advances and Perspectives in Relation to the Metabolomics-Based Study of Diabetic Retinopathy

Diabetic retinopathy (DR), a prevalent microvascular complication of diabetes, is a major cause of acquired blindness in adults. Currently, a clinical diagnosis of DR primarily relies on fundus fluorescein angiography, with a limited availability of effective biomarkers. Metabolomics, a discipline dedicated to scrutinizing the response of various metabolites within living organisms, has shown noteworthy advancements in uncovering metabolic disorders and identifying key metabolites associated with DR in recent years. Consequently, this review aims to present the latest advancements in metabolomics techniques and comprehensively discuss the principal metabolic outcomes derived from analyzing blood, vitreous humor, aqueous humor, urine, and fecal samples.

Comprehensive metabolomic profiling of nutrients in fish and shrimp

Although fish and shrimp are commonly consumed in daily life and recognized as nutrient-rich species, global profiling of the endogenous nutrients in these species is lacking. Here, we optimized the sample preparation and data acquisition methods of metabolomics to comprehensively characterize the nutrients in selected fish and shrimp species and compared them with those in beef, leading to the identification of 71 differentially expressed metabolites. Of these, docosahexaenoic acid, taurine, choline and (lyso)phosphatidylcholines were found to be abundant in the examined fish species, while several nonessential amino acids were rich in the analyzed shrimp samples. Subsequently, the biological functions of the metabolites rich in shrimp were queried. Intriguingly, the examined nutrients exemplified by proline can significantly mitigate the lipopolysaccharide (LPS)-stimulated inflammatory responses in BV2 cells and RAW264.7 cells. Collectively, our findings imply that the dietary intake of certain fish and shrimp species may benefit human health through alleviating inflammatory responses.

Houttuynia cordata Polysaccharide Ameliorates Chronic Inflammation-Induced Intestinal Impairment by Zonula Occludens-1 in Rats

This study aimed to investigate the protective effects of Houttuynia cordata polysaccharide (HCP) against chronic intestinal inflammation in rats that were subjected to low-dose lipopolysaccharide once weekly for 6 weeks. Here, administration of HCP significantly restored morphological changes in the intestine along with enhancement of antioxidant enzymes including superoxide dismutase, catalase, and glutathione peroxidase activities, and reduction of malondialdehyde contents. HCP treatment was also found to attenuate the inflammatory mediators nitric oxide, inducible nitric oxide synthase, total nitric oxide synthase, and interleukin-1beta (IL-lβ) and enhanced the production of short-chain fatty acids. Correspondingly, a significant elevation of zonula occludens-1 (ZO-1) was displayed in the intestine of HCP-treated rats, indicating that the intestinal mechanical barrier could be repaired by HCP treatment. Therefore, these findings suggested that HCP performed protective effects against chronic inflammation-induced intestinal impairment through alleviating inflammation, modifying the redox system, and recovering the intestinal mechanical barrier, mediated by the control of ZO-1 in rats.

L, E. E, Qi R, Mu X, Feng L, Ba G, Li Y, Zhang J, Bai L, Fu M. Metabolomics analysis reveals amelioration effects of yellowhorn tea extract on hyperlipidemia, inflammation, and oxidative stress in high-fat diet-fed mice

Yellowhorn tea (YT) is traditionally used as a lipid-lowering beverage in Mongolian minorities. However, the pharmacological effects of YT extract and its specific metabolic changes in hyperlipidemia models are not fully understood. The aim of this study was to identify biomarkers using untargeted metabolomics techniques and to investigate the mechanisms underlying the changes in metabolic pathways associated with lipid lowering, anti-inflammation and anti-oxidant in hyperlipidemic mice. A high-fat diet (HFD)-induced hyperlipidemic mouse model was established. YT extract was administered as oral gavage at 0.15, 0.3, and 0.6 g/kg doses for 10 weeks. HFD-induced hyperlipidemia and the therapeutic effect of YT extract were evaluated based on histopathology and by assessing blood lipid levels. Liver inflammatory factors and oxidative stress indices were determined using enzyme-linked immunosorbent assays. Liver metabolites were evaluated using untargeted metabolomics. Biochemical and histological examinations showed that YT extract significantly reduced body-weight gain (p < 0.01) and fat deposition in tissues. YT extract significantly reduced the levels of serum and liver triglyceride and total cholesterol; inflammatory factors [interleukin (IL)-6, IL-1β, and tumor necrosis factor-α]; malondialdehyde; and leptin (p < 0.05) in hyperlipidemic mice. YT extract also significantly increased the levels of oxidative stress indicators (superoxide dismutase, catalase, and glutathione peroxidase) and adiponectin. Metabolomics studies revealed several endogenous molecules were altered by the high-fat diet and recovery following intervention with YT extract. The metabolites that were significantly different in the liver after YT intake included citicoline, acetylcholine, pyridoxine, and NAD. Pathway analysis indicated that YT extract ameliorated HFD-induced hyperlipidemia in mice via three major metabolic pathways, namely, glycerophospholipid metabolism, vitamin B6 metabolism, and nicotinate and nicotinamide metabolism. This study demonstrates YT extract has profound effects on the alleviation of HFD-induced hyperlipidemia, inflammation and oxidative stress.

Nutrition and stem cell integrity in aging

Adult stem cells (SCs) represent the regenerative capacity of organisms throughout their lifespan. The maintenance of robust SC populations capable of renewing organs and physiological systems is one hallmark of healthy aging. The local environment of SCs, referred to as the niche, includes the nutritional milieu, which is essential to maintain the quantity and quality of SCs available for renewal and regeneration. There is increased recognition that SCs have unique metabolism and conditional nutrient needs compared to fully differentiated cells. However, the contribution of SC nutrition to overall human nutritional requirements is an understudied and underappreciated area of investigation. Nutrient needs vary across the lifespan and are modified by many factors including individual health, disease, physiological states including pregnancy, age, sex, and during recovery from injury. Although current nutrition guidance is generally derived for apparently healthy populations and to prevent nutritional deficiency diseases, there are increased efforts to establish nutrient-based and food-based recommendations based on reducing chronic disease. Understanding the dynamics of SC nutritional needs throughout the life span, including the role of nutrition in extending biological age by blunting biological systems decay, is fundamental to establishing food and nutrient guidance for chronic disease reduction and health maintenance. This review summarizes a 3-day symposium of the Marabou Foundation (www.marabousymposium.org) held to examine the metabolic properties and unique nutritional needs of adult SCs and their role in healthy aging and age-related chronic disease.

In-cell NMR: Why and how?

NMR spectroscopy has been applied to cells and tissues analysis since its beginnings, as early as 1950. We have attempted to gather here in a didactic fashion the broad diversity of data and ideas that emerged from NMR investigations on living cells. Covering a large proportion of the periodic table, NMR spectroscopy permits scrutiny of a great variety of atomic nuclei in all living organisms non-invasively. It has thus provided quantitative information on cellular atoms and their chemical environment, dynamics, or interactions. We will show that NMR studies have generated valuable knowledge on a vast array of cellular molecules and events, from water, salts, metabolites, cell walls, proteins, nucleic acids, drugs and drug targets, to pH, redox equilibria and chemical reactions. The characterization of such a multitude of objects at the atomic scale has thus shaped our mental representation of cellular life at multiple levels, together with major techniques like mass-spectrometry or microscopies. NMR studies on cells has accompanied the developments of MRI and metabolomics, and various subfields have flourished, coined with appealing names: fluxomics, foodomics, MRI and MRS (i.e. imaging and localized spectroscopy of living tissues, respectively), whole-cell NMR, on-cell ligand-based NMR, systems NMR, cellular structural biology, in-cell NMR… All these have not grown separately, but rather by reinforcing each other like a braided trunk. Hence, we try here to provide an analytical account of a large ensemble of intricately linked approaches, whose integration has been and will be key to their success. We present extensive overviews, firstly on the various types of information provided by NMR in a cellular environment (the "why", oriented towards a broad readership), and secondly on the employed NMR techniques and setups (the "how", where we discuss the past, current and future methods). Each subsection is constructed as a historical anthology, showing how the intrinsic properties of NMR spectroscopy and its developments structured the accessible knowledge on cellular phenomena. Using this systematic approach, we sought i) to make this review accessible to the broadest audience and ii) to highlight some early techniques that may find renewed interest. Finally, we present a brief discussion on what may be potential and desirable developments in the context of integrative studies in biology.

Effects of Xinjiang wild cherry plum (Prunus divaricata Ledeb) anthocyanin-rich extract on the plasma metabolome of atherosclerotic apoE-deficient mice fed a high-fat diet

It is well-known that many vegetables and fruits have abundant polyphenols, such as anthocyanins, which benefit many cardiovascular diseases due to their anti-oxidative and anti-inflammatory effects. To explore the protective effect of anthocyanin on atherosclerosis from a metabolic perspective, alterations in plasma metabolic profiling of apoE-deficient (apoE^–/–) mice in response to treatment with anthocyanin extracts derived from Xinjiang wild cherry plum (Prunus divaricata Ledeb) peel was investigated through UHPLC-Q-TOF/MS. The mice were fed with a normal diet or high-fat diet supplementation with or without anthocyanin extracts (ACNE, 75, 150, 250 mg/kg body weight) for 18 weeks, corresponding to control (Con), model (Mod), and treatment group (LD, low dose; MD, medium dose; HD, high dose), respectively, along with a positive control group (posCon, treatment with Atorvastatin, 0.003 mg/kg body weight). The results showed that ACNE could significantly enhance the antioxidant capacity and lower the plasma lipid, but have no evident influence on the body weight of apoE^–/– mice. A series of differential metabolites, predominantly related to lipid metabolism, were identified, including docosahexaenoic acid, palmitoyl ethanolamide, stearoylcarnitine, L-palmitoylcarnitine, indoxyl sulfate (IS), 1-palmitoyl-lysophosphatidylcholine, phenylacetylglycine (PAGly), and so on. Among these, both IS and PAGly were host-microbial metabolites. These differential metabolites were mainly enriched in the pathway of glycerophospholipid metabolism and linoleic acid metabolism. Several important enzymes related to glycerophospholipid metabolisms such as LCAT, LPCAT, GPCPD1, PLA2G1B, PPARG, LIPE, PNPLA2, AGPAT1, and ENPP2 were recognized as underlying targets for anti-atherogenic effects of ACNE. These findings suggest that ACNE derived from Xinjiang wild cherry plum exhibits protective effects against atherosclerosis via modulating glycerophospholipid metabolism.

Metabolomics as a valid analytical technique in environmental exposure research: application and progress

BACKGROUND

In recent years, studies have shown that exposure to environmental pollutants (e.g., radiation, heavy metal substances, air pollutants, organic pollutants) is a leading cause of human non-communicable diseases. The key to disease prevention is to clarify the harmful mechanisms and toxic effects of environmental pollutants on the body. Metabolomics is a high-sensitivity, high-throughput omics technology that can obtain detailed metabolite information of an organism. It is a crucial tool for gaining a comprehensive understanding of the pathway network regulation mechanism of the organism. Its application is widespread in many research fields such as environmental exposure assessment, medicine, systems biology, and biomarker discovery.

AIM OF REVIEW

Recent findings show that metabolomics can be used to obtain molecular snapshots of organisms after environmental exposure, to help understand the interaction between environmental exposure and organisms, and to identify potential biomarkers and biological mechanisms.

KEY SCIENTIFIC CONCEPTS OF REVIEW

This review focuses on the application of metabolomics to understand the biological effects of radiation, heavy metals, air pollution, and persistent organic pollutants exposure, and examines some potential biomarkers and toxicity mechanisms.

Metagenomic-Metabolomic Mining of Kinema, a Naturally Fermented Soybean Food of the Eastern Himalayas

Kinema is a popular sticky fermented soybean food of the Eastern Himalayan regions of North East India, east Nepal, and south Bhutan. We hypothesized that some dominant bacteria in kinema may contribute to the formation of targeted and non-targeted metabolites for health benefits; hence, we studied the microbiome-metabolite mining of kinema. A total of 1,394,094,912 bp with an average of 464,698,304 ± 120,720,392 bp was generated from kinema metagenome, which resulted in the identification of 47 phyla, 331 families, 709 genera, and 1,560 species. Bacteria (97.78%) were the most abundant domain with the remaining domains of viruses, eukaryote, and archaea. Firmicutes (93.36%) was the most abundant phylum with 280 species of Bacillus, among which Bacillus subtilis was the most dominant species in kinema followed by B. glycinifermentans, B. cereus, B. licheniformis, B. thermoamylovorans, B. coagulans, B. circulans, B. paralicheniformis, and Brevibacillus borstelensis. Predictive metabolic pathways revealed the abundance of genes associated with metabolism (60.66%), resulting in 216 sub-pathways. A total of 361 metabolites were identified by metabolomic analysis (liquid chromatography-mass spectrophotometry, LC-MS). The presence of metabolites, such as chrysin, swainsonine, and 3-hydroxy-L-kynurenine (anticancer activity) and benzimidazole (antimicrobial, anticancer, and anti-HIV activities), and compounds with immunomodulatory effects in kinema supports its therapeutic potential. The correlation between the abundant species of Bacillus and primary and secondary metabolites was constructed with a bivariate result. This study proves that Bacillus spp. contribute to the formation of many targeted and untargeted metabolites in kinema for health-promoting benefits.

Perspective: Novel Approaches to Evaluate Dietary Quality: Combining Methods to Enhance Measurement for Dietary Surveillance and Interventions

Refining existing dietary assessment methods to reduce measurement error and facilitate the routine evaluation of dietary quality is essential to inform health policy. Notable advancements in technology in the past decade have enhanced the precision and transformation of dietary assessment methods with applications toward both population health and precision nutrition. Within population health, innovative applications of big data including use of automatically collected food purchasing data, quantitative measurement of food environments, and novel, yet simplified dietary quality metrics provide important complementary data to traditional self-report methods. Precision nutrition is similarly advancing with greater use of validated biomarkers for assessing dietary patterns and understanding individual variability in metabolism. Concurrently enhancing our understanding of diet-disease relations at the population health and precision nutrition levels provides tremendous potential to generate evidence needed to advance public health nutrition policy. This commentary highlights the importance of these advances toward progressing the field of dietary assessment and discusses the application of food purchasing data, data analytics, alternative dietary quality metrics, and -omics technology in population and clinical medicine.

Metabolomics for personalized medicine: the input of analytical chemistry from biomarker discovery to point-of-care tests

Metabolomics refers to the large-scale detection, quantification, and analysis of small molecules (metabolites) in biological media. Although metabolomics, alone or combined with other omics data, has already demonstrated its relevance for patient stratification in the frame of research projects and clinical studies, much remains to be done to move this approach to the clinical practice. This is especially true in the perspective of being applied to personalized/precision medicine, which aims at stratifying patients according to their risk of developing diseases, and tailoring medical treatments of patients according to individual characteristics in order to improve their efficacy and limit their toxicity. In this review article, we discuss the main challenges linked to analytical chemistry that need to be addressed to foster the implementation of metabolomics in the clinics and the use of the data produced by this approach in personalized medicine. First of all, there are already well-known issues related to untargeted metabolomics workflows at the levels of data production (lack of standardization), metabolite identification (small proportion of annotated features and identified metabolites), and data processing (from automatic detection of features to multi-omic data integration) that hamper the inter-operability and reusability of metabolomics data. Furthermore, the outputs of metabolomics workflows are complex molecular signatures of few tens of metabolites, often with small abundance variations, and obtained with expensive laboratory equipment. It is thus necessary to simplify these molecular signatures so that they can be produced and used in the field. This last point, which is still poorly addressed by the metabolomics community, may be crucial in a near future with the increased availability of molecular signatures of medical relevance and the increased societal demand for participatory medicine.

Defining the Scope of Exposome Studies and Research Needs from a Multidisciplinary Perspective

The concept of the exposome was introduced over 15 years ago to reflect the important role that the environment exerts on health and disease. While originally viewed as a call-to-arms to develop more comprehensive exposure assessment methods applicable at the individual level and throughout the life course, the scope of the exposome has now expanded to include the associated biological response. In order to explore these concepts, a workshop was hosted by the Gunma University Initiative for Advanced Research (GIAR, Japan) to discuss the scope of exposomics from an international and multidisciplinary perspective. This Global Perspective is a summary of the discussions with emphasis on (1) top-down, bottom-up, and functional approaches to exposomics, (2) the need for integration and standardization of LC- and GC-based high-resolution mass spectrometry methods for untargeted exposome analyses, (3) the design of an exposomics study, (4) the requirement for open science workflows including mass spectral libraries and public databases, (5) the necessity for large investments in mass spectrometry infrastructure in order to sequence the exposome, and (6) the role of the exposome in precision medicine and nutrition to create personalized environmental exposure profiles. Recommendations are made on key issues to encourage continued advancement and cooperation in exposomics.

Metabolomics Approaches for the Comprehensive Evaluation of Fermented Foods: A Review

Fermentation is an important process that can provide new flavors and nutritional and functional foods, to deal with changing consumer preferences. Fermented foods have complex chemical components that can modulate unique qualitative properties. Consequently, monitoring the small molecular metabolites in fermented food is critical to clarify its qualitative properties and help deliver personalized nutrition. In recent years, the application of metabolomics to nutrition research of fermented foods has expanded. In this review, we examine the application of metabolomics technologies in food, with a primary focus on the different analytical approaches suitable for food metabolomics and discuss the advantages and disadvantages of these approaches. In addition, we summarize emerging studies applying metabolomics in the comprehensive analysis of the flavor, nutrition, function, and safety of fermented foods, as well as emphasize the applicability of metabolomics in characterizing the qualitative properties of fermented foods.

High-Coverage Metabolome Analysis Reveals Significant Diet Effects of Autoclaved and Irradiated Feed on Mouse Fecal and Urine Metabolomics

SCOPE

Using metabolomics to study the relations of nutrition and health requires stringent control of the experimental conditions used in an animal model. This work investigates the diet effects of autoclaved and irradiated feed on mouse urine and fecal metabolomics.

METHODS AND RESULTS

C57BL/6 mice are fed normal-irradiation sterilized diet (n = 9), autoclave sterilized diet (n = 9), and high-irradiation sterilized diet (n = 9) for 4 weeks. Differential chemical isotope labeling liquid chromatography mass spectrometry is used to quantify the metabolome variations of urine and feces collected at five time points. Significant differences are observed in urine or fecal metabolomes of mice fed autoclaved diet versus mice fed high-irradiation diet or fed normal-irradiation diet, while the differences are small between the mice fed normal-irradiation and high-irradiation diet. Correlation studies of metabolite changes of diet- and aging-related biomarkers indicate a large overlap of significantly affected metabolites by the two factors.

CONCLUSIONS

Diet can be a confounding factor that needs to be carefully considered when a metabolomics study is designed and metabolomic results of a mouse model of nutritional or other biological study are interpreted. Using the same sterilized diet for a given metabolomics project is essential to control the diet effect.

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.

Genetic and environmental influences on covariation in reproducible diet-metabolite associations

BACKGROUND

Early applications of metabolomics in nutrition and health research identified associations between dietary patterns and metabolomic profiles. Twin studies show that diet-related phenotypes and diet-associated metabolites are influenced by genes. However, studies have not examined whether diet-metabolite associations are explained by genetic or environmental factors and whether these associations are reproducible over multiple time points.

OBJECTIVE

This research aims to examine the genetic and environmental factors influencing covariation in diet-metabolite associations that are reproducible over time in healthy twins.

METHODS

The UCD Twin Study is a semi-longitudinal classic twin study that collected repeated dietary, anthropometric, and urinary data over 2 months. Correlation analysis identified associations between diet quality measured using the Healthy Eating Index (HEI) and urinary metabolomic profiles at 3 time points. Diet-associated metabolites were examined using linear regression to identify those significantly influenced by familial factors between twins and those significantly influenced by unique factors. Cholesky decomposition modeling quantified the genetic and environmental path coefficients through associated dietary components onto the metabolites.

RESULTS

The HEI was associated with 14 urinary metabolites across 3 metabolomic profiles (r: ±0.15-0.49). For 8 diet-metabolite associations, genetic or shared environmental factors influencing HEI component scores significantly influenced variation in metabolites (β: 0.40-0.52). A significant relation was observed between dietary intakes of whole grain and acetoacetate (β: -0.50, P < 0.001) and β-hydroxybutyrate (β: -0.46, P < 0.001), as well as intakes of saturated fat and acetoacetate (β: 0.47, P < 0.001) and β-hydroxybutyrate (β: 0.52, P < 0.001). For these diet-metabolite associations a common shared environmental factor explained 66-69% of variance in the metabolites.

CONCLUSIONS

This study shows that diet-metabolite associations are reproducible in 3 urinary metabolomic profiles. Components of the HEI covary with metabolites, and covariation is largely due to the shared environment.

Investigating metabolism by mass spectrometry: From steady state to dynamic view

Metabolism is the set of life-sustaining reactions in organisms. These biochemical reactions are organized in metabolic pathways, in which one metabolite is converted through a series of steps catalyzed by enzymes in another chemical compound. Metabolic reactions are categorized as catabolic, the breaking down of metabolites to produce energy, and/or anabolic, the synthesis of compounds that consume energy. The balance between catabolism of the preferential fuel substrate and anabolism defines the overall metabolism of a cell or tissue. Metabolomics is a powerful tool to gain new insights contributing to the identification of complex molecular mechanisms in the field of biomedical research, both basic and translational. The enormous potential of this kind of analyses consists of two key aspects: (i) the possibility of performing so-called targeted and untargeted experiments through which it is feasible to verify or formulate a hypothesis, respectively, and (ii) the opportunity to run either steady-state analyses to have snapshots of the metabolome at a given time under different experimental conditions or dynamic analyses through the use of labeled tracers. In this review, we will highlight the most important practical (e.g., different sample extraction approaches) and conceptual steps to consider for metabolomic analysis, describing also the main application contexts in which it is used. In addition, we will provide some insights into the most innovative approaches and progress in the field of data analysis and processing, highlighting how this part is essential for the proper extrapolation and interpretation of data.

Personalized Nutrition and -Omics

With change in global concern toward food quality over food quantity, consumer concern and choice of healthy food has become a matter of prime importance. It gave rise to concept of “personalized or precision nutrition”. The theory behind personalization of nutrition is supported by multiple factors including advances in food analytics, nutrition based diseases and public health programs, increasing use of information technology in nutrition science, concept of gene-diet interaction and growing consumer capacity or concern by better and healthy foods. The advances in “omics” tools and related analytical techniques have resulted into tremendous scope of their application in nutrition science. As a consequence, a better understanding of underlying interaction between diet and individual is expected with addressing of key challenges for successful implementation of this science. In this chapter, the above aspects are discussed to get an insight into driving factors for increasing concern in personalized nutrition.

Building a Resilient, Sustainable, and Healthier Food Supply Through Innovation and Technology

The modern food supply faces many challenges. The global population continues to grow and people are becoming wealthier, so the food production system must respond by creating enough high-quality food to feed everyone with minimal damage to our environment. The number of people suffering or dying from diet-related chronic diseases, such as obesity, diabetes, heart disease, stroke, and cancer, continues to rise, which is partly linked to overconsumption of highly processed foods, especially high-calorie or rapidly digestible foods. After falling for many years, the number of people suffering from starvation or malnutrition is rising, and thishas been exacerbated by the global COVID-19 pandemic. The highly integrated food supply chains that spread around the world are susceptible to disruptions due to policy changes, economic stresses, and natural disasters, as highlighted by the recent pandemic. In this perspective article, written by members of the Editorial Committee of the Annual Review of Food Science and Technology, we highlight some of the major challenges confronting the modern food supply chain as well as how innovations in policy and technology can be used to address them. Pertinent technological innovations include robotics, machine learning, artificial intelligence, advanced diagnostics, nanotechnology, biotechnology, gene editing, vertical farming, and soft matter physics. Many of these technologies are already being employed across the food chain by farmers, distributors, manufacturers, and consumers to improve the quality, nutrition, safety, and sustainability of the food supply. These innovations are required to stimulate the development and implementation of new technologies to ensure a more equitable, resilient, and efficient food production system. Where appropriate, these technologies should be carefully tested before widespread implementation so that proper risk-benefit analyses can be carried out. They can then be employed without causing unforeseen adverse consequences. Finally, it is important to actively engage all stakeholders involved in the food supply chain throughout the development and testing of these new technologies to support their adoption if proven safe and effective.

Quantifying the human diet in the crosstalk between nutrition and health by multi-targeted metabolomics of food and microbiota-derived metabolites

BACKGROUND

Metabolomics is a powerful tool for investigating the association between nutrition and health status. Although urine is commonly employed for studying the metabolism and transformation of food components, the use of blood samples could be preferable to gain new insights into the bioavailability of diet-derived compounds and their involvement in health. However, the chemical complexity of blood samples hinders the analysis of this biological fluid considerably, which makes the development of novel and comprehensive analytical methods mandatory.

METHODS

In this work, we optimized a multi-targeted metabolomics platform for the quantitative and simultaneous analysis of 450 food-derived metabolites by ultra-high performance liquid chromatography coupled to tandem mass spectrometry. To handle the chemical complexity of blood samples, three complementary extraction methods were assayed and compared in terms of recovery, sensitivity, precision and matrix effects with the aim of maximizing metabolomics coverage: protein precipitation, reversed solid-phase extraction, and hybrid protein precipitation with solid-phase extraction-mediated phospholipid removal.

RESULTS

After careful optimization of the extraction conditions, protein precipitation enabled the most efficient and high-throughput extraction of the food metabolome in plasma, although solid-phase extraction-based protocols provided complementary performance for the analysis of specific polyphenol classes. The developed method yielded accurate recovery rates with negligible matrix effects, and good linearity, as well as high sensitivity and precision for most of the analyzed metabolites.

CONCLUSIONS

The multi-targeted metabolomics platform optimized in this work enables the simultaneous detection and quantitation of 450 dietary metabolites in short-run times using small volumes of biological sample, which facilitates its application to epidemiological studies.

Human urine 1H NMR metabolomics reveals alterations of protein and carbohydrate metabolism when comparing habitual Average Danish diet vs. healthy New Nordic diet

OBJECTIVES

The aim of this study was to investigate the alteration of the human urine metabolome by means of diet and to compare the metabolic effects of the nutritionally healthy New Nordic Diet (NND) with an Average Danish Diet (ADD). The NND was designed a decade ago by scientists and chefs, based on local and sustainable foods, including fish, shellfish, vegetables, roots, fruit, and berries. The NND has been proven to lower blood pressure, reduce glycemia, and lead to weight loss.

METHODS

The human urine metabolome was measured by untargeted proton nuclear magnetic resonance spectroscopy in samples from 142 centrally obese Danes (20-66 years old), randomized to consume the ADD or the NND. The resulting metabolomics data was processed and analyzed using advanced multivariate data analysis methods to reveal effects related to the design factors, including diet, season, sex, and changes in body weight.

RESULTS

Exploration of the nuclear magnetic resonance profiles revealed unique metabolite markers reflecting changes in protein and carbohydrate metabolism between the two diets. Glycine betaine, glucose, trimethylamine N-oxide and creatinine were increased in urine of the individuals following the NND compared with the ADD population, whereas relative concentrations of tartrate, dimethyl sulfone, and propylene glycol were decreased. Propylene glycol had a strong association with the homeostatic model assessment for insulin resistance in the NND group. The food intake biomarkers found in this study confirm the importance of these as tools for nutritional research.

CONCLUSIONS

Findings from this study provided new insights into the effects of a healthy diet on glycemia, reduction of inflammation, and weight loss among obese individuals, and alteration of the gut microbiota metabolism.

Effect of Hesperidin on Cardiovascular Disease Risk Factors: The Role of Intestinal Microbiota on Hesperidin Bioavailability

Recently, hesperidin, a flavonone mainly present in citrus fruits, has emerged as a new potential therapeutic agent able to modulate several cardiovascular diseases (CVDs) risk factors. Animal and in vitro studies demonstrate beneficial effects of hesperidin and its derived compounds on CVD risk factors. Thus, hesperidin has shown glucose-lowering and anti-inflammatory properties in diabetic models, dyslipidemia-, atherosclerosis-, and obesity-preventing effects in CVDs and obese models, and antihypertensive and antioxidant effects in hypertensive models. However, there is still controversy about whether hesperidin could contribute to ameliorate glucose homeostasis, lipid profile, adiposity, and blood pressure in humans, as evidenced by several clinical trials reporting no effects of treatments with this flavanone or with orange juice on these cardiovascular parameters. In this review, we focus on hesperidin's beneficial effects on CVD risk factors, paying special attention to the high interindividual variability in response to hesperidin-based acute and chronic interventions, which can be partly attributed to differences in gut microbiota. Based on the current evidence, we suggest that some of hesperidin's contradictory effects in human trials are partly due to the interindividual hesperidin variability in its bioavailability, which in turn is highly dependent on the α-rhamnosidase activity and gut microbiota composition.