The unmapped chemical complexity of our diet

Multidisciplinary approach combining food metabolomics and epidemiology identifies meglutol as an important bioactive metabolite in tempe, an Indonesian fermented food

This study introduces a multidisciplinary approach to investigate bioactive food metabolites often overlooked due to their low concentrations. We integrated an in-house food metabolite library (n = 494), a human metabolite library (n = 891) from epidemiological studies, and metabolite pharmacological databases to screen for food metabolites with potential bioactivity. We identified six potential metabolites, including meglutol (3-hydroxy-3-methylglutarate), an understudied low-density lipoprotein (LDL)-lowering compound. We further focused on meglutol as a case study to showcase the range of characterizations achievable with this approach. Green pea tempe was identified to contain the highest meglutol concentration (21.8 ± 4.6 mg/100 g). Furthermore, we identified a significant cross-sectional association between plasma meglutol (per 1-standard deviation) and lower LDL cholesterol in two Hispanic adult cohorts (n = 1,628) (β [standard error]: -5.5 (1.6) mg/dl, P = 0.0005). These findings highlight how multidisciplinary metabolomics can serve as a systematic tool for discovering and enhancing bioactive metabolites in food, such as meglutol, with potential applications in personalized dietary approaches for disease prevention.

Dietary intake and glutamine-serine metabolism control pathologic vascular stiffness

Perivascular collagen deposition by activated fibroblasts promotes vascular stiffening and drives cardiovascular diseases such as pulmonary hypertension (PH). Whether and how vascular fibroblasts rewire their metabolism to sustain collagen biosynthesis remains unknown. Here, we found that inflammation, hypoxia, and mechanical stress converge on activating the transcriptional coactivators YAP and TAZ (WWTR1) in pulmonary arterial adventitial fibroblasts (PAAFs). Consequently, YAP and TAZ drive glutamine and serine catabolism to sustain proline and glycine anabolism and promote collagen biosynthesis. Pharmacologic or dietary intervention on proline and glycine anabolic demand decreases vascular stiffening and improves cardiovascular function in PH rodent models. By identifying the limiting metabolic pathways for vascular collagen biosynthesis, our findings provide guidance for incorporating metabolic and dietary interventions for treating cardiopulmonary vascular disease.

The taste for health: the role of taste receptors and their ligands in the complex food/health relationship

Taste, food, and health are terms that have since always accompanied the act of eating, but the association was simple: taste serves to classify a food as good or bad and therefore influences food choices, which determine the nutritional status and therefore health. The identification of taste receptors, particularly, the G protein-coupled receptors that mediate sweet, umami, and bitter tastes, in the gastrointestinal tract has assigned them much more relevant tasks, from nutrient sensing and hormone release to microbiota composition and immune response and finally to a rationale for the gut-brain axis. Particularly interesting are bitter taste receptors since most of the times they do not mediate macronutrients (energy). The relevant roles of bitter taste receptors in the gut indicate that they could become new drug targets and their ligands new medications or components in nutraceutical formulations. Traditional knowledge from different cultures reported that bitterness intensity was an indicator for distinguishing plants used as food from those used as medicine, and many non-cultivated plants were used to control glucose level and treat diabetes, modulate hunger, and heal gastrointestinal disorders caused by pathogens and parasites. This concept represents a means for the scientific integration of ancient wisdom with advanced medicine, constituting a possible boost for more sustainable food and functional food innovation and design.

Effectiveness of anthocyanin-containing foods and nutraceuticals in mitigating oxidative stress, inflammation, and cardiovascular health-related biomarkers: a systematic review of animal and human interventions

Cardiovascular diseases (CVDs) are a group of chronic health disorders prevalent worldwide that claim millions of lives yearly. Inflammation and oxidative stress are intricately associated with myocardial tissue damage, endothelial dysfunction, and increased odds of heart failure. Thus, dietary strategies aimed at decreasing the odds of CVDs are paramount. In this regard, the consumption of anthocyanins, natural pigments found in edible flowers, fruits, and vegetables, has attracted attention due to their potential to promote cardiovascular health. The main mechanisms of action linked with their protective effects on antioxidant and anti-inflammatory activities, serum lipid profile modulation, and other cardiovascular health parameters are explained and exemplified. However, little is known about the dose-dependency nature of the effects, which anthocyanin has better efficiency, and whether anthocyanin-containing foods display better in vivo efficacy than nutraceuticals (i.e., concentrated extracts containing higher levels of anthocyanins than foods). Thus, this systematic review focused on determining the effects of anthocyanin-containing foods and nutraceuticals on biomarkers associated with CVDs using animal studies and human interventions supported by in vitro mechanistic insights. Overall, the results showed that the regular consumption of anthocyanin-containing foods and nutraceuticals improved vascular function, lipid profile, and antioxidant and anti-inflammatory effects. The daily dosage, the participants' health status, and the duration of the intervention also significantly influenced the results.

Lower Diet Quality Associated with Subclinical Gastrointestinal Inflammation in Healthy United States Adults

BACKGROUND

Higher diet quality has been associated with lower risk of developing inflammatory bowel disease, but associations between diet and gastrointestinal (GI) inflammation in healthy adults prior to disease onset are understudied.

OBJECTIVES

The purpose of this project was to examine associations between reported dietary intake and markers of GI inflammation in a healthy adult human cohort.

METHODS

In a cross-sectional observational trial of 358 healthy adults, participants completed ≤3 unannounced 24-h dietary recalls using the Automated Self-Administered Dietary Assessment Tool and a Block 2014 Food Frequency Questionnaire to assess recent and habitual intake, respectively. Those who provided a stool sample were included in this analysis. Inflammation markers from stool, including calprotectin, neopterin, and myeloperoxidase, were measured by ELISA along with LPS-binding protein from plasma.

RESULTS

Recent and habitual fiber intake was negatively correlated with fecal calprotectin concentrations (n = 295, P = 0.011, 0.009). Habitual soluble fiber intake was also negatively correlated with calprotectin (P = 0.01). Recent and habitual legume and vegetable intake was negatively correlated with calprotectin (P = 0.013, 0.026, 0.01, 0.009). We observed an inverse correlation between recent Healthy Eating Index (HEI) scores and calprotectin concentrations (n = 295, P = 0.026). Dietary Inflammatory Index scores were calculated and positively correlated with neopterin for recent intake (n = 289, P = 0.015). When participants with clinically elevated calprotectin were excluded, recent and habitual fiber, legume, vegetable, and fruit intake were negatively correlated with calprotectin (n = 253, P = 0.00001, 0.0002, 0.045, 0.001, 0.009, 0.001, 0.004, 0.014). Recent total HEI score was inversely correlated with subclinical calprotectin (P = 0.003).

CONCLUSIONS

Higher diet quality may be protective against GI inflammation even in healthy adults. This trial was registered at clinicaltrials.gov as NCT02367287.

Reassessing the role of phytochemicals in cancer chemoprevention

In this comprehensive review we tried to reassess the role of phytochemicals in cancer chemoprevention. The exploration of the "synergistic effect" concept, advocating combined chemopreventive agents, faces challenges like low bioavailability. The review incorporates personal, occasionally controversial, viewpoints on natural compounds' cancer preventive capabilities, delving into mechanisms. Prioritizing significant contributions within the vast research domain, we aim stimulating discussion to provide a comprehensive insight into the evolving role of phytochemicals in cancer prevention. While early years downplayed the role of phytochemicals, the late nineties witnessed a shift, with leaders exploring their potential alongside synthetic compounds. Challenges faced by chemoprevention, such as limited pharmaceutical interest and cost-effectiveness issues, persist despite successful drugs. Recent studies, including the EPIC study, provide nuanced insights, indicating a modest risk reduction for increased fruit and vegetable intake. Phytochemicals, once attributed to antioxidant effects, face scrutiny due to low bioavailability and conflicting evidence. The Nrf2-EpRE signaling pathway and microbiota-mediated metabolism emerge as potential mechanisms, highlighting the complexity of understanding phytochemical mechanisms in cancer chemoprevention.

Chemical Multiverse and Diversity of Food Chemicals

Food chemicals have a fundamental role in our lives, with an extended impact on nutrition, disease prevention, and marked economic implications in the food industry. The number of food chemical compounds in public databases has substantially increased in the past few years, which can be characterized using chemoinformatics approaches. We and other groups explored public food chemical libraries containing up to 26,500 compounds. This study aimed to analyze the chemical contents, diversity, and coverage in the chemical space of food chemicals and additives and, from here on, food components. The approach to food components addressed in this study is a public database with more than 70,000 compounds, including those predicted via omics techniques. It was concluded that food components have distinctive physicochemical properties and constitutional descriptors despite sharing many chemical structures with natural products. Food components, on average, have large molecular weights and several apolar structures with saturated hydrocarbons. Compared to reference databases, food component structures have low scaffold and fingerprint-based diversity and high structural complexity, as measured by the fraction of sp3 carbons. These structural features are associated with a large fraction of macronutrients as lipids. Lipids in food components were decompiled by an analysis of the maximum common substructures. The chemical multiverse representation of food chemicals showed a larger coverage of chemical space than natural products and FDA-approved drugs by using different sets of representations.

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.

Navigating the B vitamins: Dietary diversity, microbial synthesis, and human health

B vitamins are intricately involved in various physiological processes vital for health. Their significance is complicated by the heterogeneous landscape of B vitamin distribution in diets and the contributions of the gut microbiota. Here, we delve into the impact of these factors on B vitamins and introduce strategies, with a focus on microbiota-based therapeutic options, to enhance their availability for improved well-being. Additionally, we provide an ecological and evolutionary perspective on the importance of B vitamins to human-microbiota interactions. In the dynamic realms of nutrition and microbiome science, these essential micronutrients continue to play a fundamental role in our understanding of disease development.

Multi-nutrient interventions and cognitive ageing: are we barking up the right tree?

As we continue to elucidate the mechanisms underlying age-related brain diseases, the reductionist strategy in nutrition–brain function research has focused on establishing the impact of individual foods. However, the biological processes connecting diet and cognition are complex. Therefore, consideration of a combination of nutritional compounds may be most efficacious. One barrier to establishing the efficacy of multi-nutrient interventions is that the area lacks an established set of evidence-based guidelines for studying their effect on brain health. This review is an output of the International Life Sciences Institute (ILSI) Europe. A multi-disciplinary expert group was assembled with the aim of developing a set of considerations to guide research into the effects of multi-nutrient combinations on brain functions. Consensus recommendations converged on six key issues that should be considered to advance research in this area: (1) establish working mechanisms of the combination and contributions of each individual compound; (2) validate the relevance of the mechanisms for the targeted human condition; (3) include current nutrient status, intake or dietary pattern as inclusion/exclusion criteria in the study design; (4) select a participant population that is clinically and biologically appropriate for all nutritional components of the combination; (5) consider a range of cognitive outcomes; (6) consider the limits of reductionism and the ‘gold standard’ randomised controlled trial. These guiding principles will enhance our understanding of the interactive/complementary activities of dietary components, thereby strengthening the evidence base for recommendations aimed at delaying cognitive decline.

Nutritional metabolomics: Recent developments and future needs

Metabolomics has rapidly been adopted as one of the key methods in nutrition research. This review focuses on the recent developments and updates in the field, including the analytical methodologies that encompass improved instrument sensitivity, sampling techniques and data integration (multiomics). Metabolomics has advanced the discovery and validation of dietary biomarkers and their implementation in health research. Metabolomics has come to play an important role in the understanding of the role of small molecules resulting from the diet-microbiota interactions when gut microbiota research has shifted towards improving the understanding of the activity and functionality of gut microbiota rather than composition alone. Currently, metabolomics plays an emerging role in precision nutrition and the recent developments therein are discussed.

Host-pathogen interactions from a metabolic perspective: methods of investigation

Metabolism shapes immune homeostasis in health and disease. This review presents the range of methods that are currently available to investigate the dialog between metabolism and immunity at the systemic, tissue and cellular levels, particularly during infection.

Association between dietary phytochemical index, cardiometabolic risk factors and metabolic syndrome in Switzerland. The CoLaus study

BACKGROUND AND AIMS

Plant-based diets are associated with reduced cardiometabolic risk factors (CRFs) and lower risk of metabolic syndrome (MetS), probably via phytochemicals acting synergistically. However, dietary phytochemical content estimation is challenging; therefore, the dietary phytochemical index (DPI) was proposed as a practical way to assess total dietary phytochemical content from phytochemical-rich foods (PRFs). We evaluated the association between DPI with CRFs and MetS and its components.

METHODS AND RESULTS

Cross-sectional analysis of 2009-2012 data of Colaus cohort study (Lausanne, Switzerland), including 3879 participants (mean age 57.6 ± 10.4 years, 53.5% women). Dietary intake was assessed via a validated food frequency questionnaire. DPI was calculated as the total energy intake percentage obtained from PRFs consumption and assessed as quartiles. Associations were determined using multivariable linear and logistic regression for CRFs and MetS, respectively. Median DPI value was 25.5 (interquartile range: 17.7-34.6). After multivariable-adjusted analyses, significant inverse associations were observed between the last two highest DPI quartiles and waist circumference (WC), body mass index (BMI), insulin, leptin, and hs-CRP. No significant associations were observed for MetS or its components except for central obesity, as subjects in the highest DPI quartile had lower odds (OR: 0.78; 95% CI: 0.62, 0.97) than those in lowest quartile.

CONCLUSION

A diet high in PRFs assessed via DPI is associated with lower WC, BMI, insulin, leptin, hs-CRP values, and lower odds of central obesity, indicating a potential protective effect of phytochemical intake on these CRFs and highlighting the importance of high PRFs intake in promoting cardiometabolic health.

Development of a novel (poly)phenol-rich diet score and its association with urinary (poly)phenol metabolites

Background: Estimating (poly)phenol intake is challenging due to inadequate dietary assessment tools and limited food content data. Currently, a priori diet scores to characterise (poly)phenol-rich diets are lacking. This study aimed to develop a novel (poly)phenol-rich diet score (PPS) and explore its relationship with circulating (poly)phenol metabolites. Methods: A total of 543 healthy free-living participants aged 18-80 years completed a food frequency questionnaire (FFQ) (EPIC-Norfolk) and provided 24 h urine samples. The PPS was developed based on the relative intake (quintiles) of 20 selected (poly)phenol-rich food items abundant in the UK diet, including tea, coffee, red wine, whole grains, chocolate and cocoa products, berries, apples and juice, pears, grapes, plums, citrus fruits and juice, potatoes and carrots, onions, peppers, garlic, green vegetables, pulses, soy and soy products, nuts, and olive oil. Foods included in the PPS were chosen based on their (poly)phenol content, main sources of (poly)phenols, and consumption frequencies in the UK population. Associations between the PPS and urinary phenolic metabolites were investigated using linear models adjusting energy intake and multiple testing (FDR adjusted p < 0.05). Result: The total PPS ranged from 25 to 88, with a mean score of 54. A total of 51 individual urinary metabolites were significantly associated with the PPS, including 39 phenolic acids, 5 flavonoids, 3 lignans, 2 resveratrol and 2 other (poly)phenol metabolites. The total (poly)phenol intake derived from FFQs also showed a positive association with PPS (stdBeta 0.32, 95% CI (0.24, 0.40), p < 0.01). Significant positive associations were observed in 24 of 27 classes and subclasses of estimated (poly)phenol intake and PPS, with stdBeta values ranging from 0.12 (0.04, 0.20) for theaflavins/thearubigins to 0.43 (0.34, 0.51) for flavonols (p < 0.01). Conclusion: High adherence to the PPS diet is associated with (poly)phenol intake and urinary biomarkers, indicating the utility of the PPS to characterise diets rich in (poly)phenols at a population level.

Network medicine framework reveals generic herb-symptom effectiveness of traditional Chinese medicine

Understanding natural and traditional medicine can lead to world-changing drug discoveries. Despite the therapeutic effectiveness of individual herbs, traditional Chinese medicine (TCM) lacks a scientific foundation and is often considered a myth. In this study, we establish a network medicine framework and reveal the general TCM treatment principle as the topological relationship between disease symptoms and TCM herb targets on the human protein interactome. We find that proteins associated with a symptom form a network module, and the network proximity of an herb's targets to a symptom module is predictive of the herb's effectiveness in treating the symptom. These findings are validated using patient data from a hospital. We highlight the translational value of our framework by predicting herb-symptom treatments with therapeutic potential. Our network medicine framework reveals the scientific foundation of TCM and establishes a paradigm for understanding the molecular basis of natural medicine and predicting disease treatments.

Metabolomics and machine learning technique revealed that germination enhances the multi-nutritional properties of pigmented rice

Enhancing the dietary properties of rice is crucial to contribute to alleviating hidden hunger and non-communicable diseases in rice-consuming countries. Germination is a bioprocessing approach to increase the bioavailability of nutrients in rice. However, there is a scarce information on how germination impacts the overall nutritional profile of pigmented rice sprouts (PRS). Herein, we demonstrated that germination resulted to increase levels of certain dietary compounds, such as free phenolics and micronutrients (Ca, Na, Fe, Zn, riboflavin, and biotin). Metabolomic analysis revealed the preferential accumulation of dipeptides, GABA, and flavonoids in the germination process. Genome-wide association studies of the PRS suggested the activation of specific genes such as CHS1 and UGT genes responsible for increasing certain flavonoid compounds. Haplotype analyses showed a significant difference (P < 0.05) between alleles associated with these genes. Genetic markers associated with these flavonoids were incorporated into the random forest model, improving the accuracy of prediction of multi-nutritional properties from 89.7% to 97.7%. Deploying this knowledge to breed rice with multi-nutritional properties will be timely to address double burden nutritional challenges.

An integrative analytical framework to identify healthy, impactful, and equitable foods: a case study on 100% orange juice

To identify healthy, impactful, and equitable foods, we combined health scores from six diverse nutrient profiling systems (NPS) into a meta-framework (meta-NPS) and paired this with dietary guideline adherence assessment via multilevel regression and poststratification. In a case-study format, a commonly debated beverage formulation - 100% orange juice (OJ) - was chosen to showcase the utility and depth of our framework, systematically scoring high across multiple food systems (i.e. a Meta-Score percentile = 93rd and Stability percentile = 75th) and leading to an expected increase of US dietary fruit guideline adherence by ∼10%. Moreover, the increased adherence varies across the 300 sociodemographic strata, with the benefit patterns being sensitive to absolute or relative quantification of the difference of adherence affected by OJ. In sum, the adaptable, integrative framework we established deepens the science of nutrient profiling and dietary guideline adherence assessment while shedding light on the nuances of defining equitable health effects.

Nutritional redundancy in the human diet and its application in phenotype association studies

Studying human dietary intake may help us identify effective measures to treat or prevent many chronic diseases whose natural histories are influenced by nutritional factors. Here, by examining five cohorts with dietary intake data collected on different time scales, we show that the food intake profile varies substantially across individuals and over time, while the nutritional intake profile appears fairly stable. We refer to this phenomenon as 'nutritional redundancy' and attribute it to the nested structure of the food-nutrient network. This network enables us to quantify the level of nutritional redundancy for each diet assessment of any individual. Interestingly, this nutritional redundancy measure does not strongly correlate with any classical healthy diet scores, but its performance in predicting healthy aging shows comparable strength. Moreover, after adjusting for age, we find that a high nutritional redundancy is associated with lower risks of cardiovascular disease and type 2 diabetes.

Dead rats, dopamine, performance metrics, and peacock tails: Proxy failure is an inherent risk in goal-oriented systems

When a measure becomes a target, it ceases to be a good measure. For example, when standardized test scores in education become targets, teachers may start "teaching to the test," leading to breakdown of the relationship between the measure - test performance - and the underlying goal - quality education. Similar phenomena have been named and described across a broad range of contexts, such as economics, academia, machine learning, and ecology. Yet it remains unclear whether these phenomena bear only superficial similarities, or if they derive from some fundamental unifying mechanism. Here, we propose such a unifying mechanism, which we label proxy failure. We first review illustrative examples and their labels, such as the "cobra effect," "Goodhart's law," and "Campbell's law." Second, we identify central prerequisites and constraints of proxy failure, noting that it is often only a partial failure or divergence. We argue that whenever incentivization or selection is based on an imperfect proxy measure of the underlying goal, a pressure arises that tends to make the proxy a worse approximation of the goal. Third, we develop this perspective for three concrete contexts, namely neuroscience, economics, and ecology, highlighting similarities and differences. Fourth, we outline consequences of proxy failure, suggesting it is key to understanding the structure and evolution of goal-oriented systems. Our account draws on a broad range of disciplines, but we can only scratch the surface within each. We thus hope the present account elicits a collaborative enterprise, entailing both critical discussion as well as extensions in contexts we have missed.

Multi-Omics Profiling for Health

The world has witnessed a steady rise in both non-infectious and infectious chronic diseases, prompting a cross-disciplinary approach to understand and treating disease. Current medical care focuses on treating people after they become patients rather than preventing illness, leading to high costs in treating chronic and late-stage diseases. Additionally, a "one-size-fits all" approach to health care does not take into account individual differences in genetics, environment, or lifestyle factors, decreasing the number of people benefiting from interventions. Rapid advances in omics technologies and progress in computational capabilities have led to the development of multi-omics deep phenotyping, which profiles the interaction of multiple levels of biology over time and empowers precision health approaches. This review highlights current and emerging multi-omics modalities for precision health and discusses applications in the following areas: genetic variation, cardio-metabolic diseases, cancer, infectious diseases, organ transplantation, pregnancy, and longevity/aging. We will briefly discuss the potential of multi-omics approaches in disentangling host-microbe and host-environmental interactions. We will touch on emerging areas of electronic health record and clinical imaging integration with muti-omics for precision health. Finally, we will briefly discuss the challenges in the clinical implementation of multi-omics and its future prospects.

Machine learning prediction of the degree of food processing

Despite the accumulating evidence that increased consumption of ultra-processed food has adverse health implications, it remains difficult to decide what constitutes processed food. Indeed, the current processing-based classification of food has limited coverage and does not differentiate between degrees of processing, hindering consumer choices and slowing research on the health implications of processed food. Here we introduce a machine learning algorithm that accurately predicts the degree of processing for any food, indicating that over 73% of the US food supply is ultra-processed. We show that the increased reliance of an individual's diet on ultra-processed food correlates with higher risk of metabolic syndrome, diabetes, angina, elevated blood pressure and biological age, and reduces the bio-availability of vitamins. Finally, we find that replacing foods with less processed alternatives can significantly reduce the health implications of ultra-processed food, suggesting that access to information on the degree of processing, currently unavailable to consumers, could improve population health.

Improving the generalizability of protein-ligand binding predictions with AI-Bind

Identifying novel drug-target interactions is a critical and rate-limiting step in drug discovery. While deep learning models have been proposed to accelerate the identification process, here we show that state-of-the-art models fail to generalize to novel (i.e., never-before-seen) structures. We unveil the mechanisms responsible for this shortcoming, demonstrating how models rely on shortcuts that leverage the topology of the protein-ligand bipartite network, rather than learning the node features. Here we introduce AI-Bind, a pipeline that combines network-based sampling strategies with unsupervised pre-training to improve binding predictions for novel proteins and ligands. We validate AI-Bind predictions via docking simulations and comparison with recent experimental evidence, and step up the process of interpreting machine learning prediction of protein-ligand binding by identifying potential active binding sites on the amino acid sequence. AI-Bind is a high-throughput approach to identify drug-target combinations with the potential of becoming a powerful tool in drug discovery.

Estimated micronutrient shortfalls of the EAT-Lancet planetary health diet

Unhealthy diets are a major contributor to the global burden of disease, and food systems cause substantial environmental destruction. To lay out how to achieve healthy diets for all, within planetary boundaries, the landmark EAT-Lancet Commission proposed the planetary health diet, which includes a range of possible intakes by food group and substantially restricts the intake of highly processed foods and animal source foods globally. However, concerns have been raised about the extent to which the diet provides adequate essential micronutrients, particularly those generally found in higher quantities and in more bioavailable forms in animal source foods. To address these concerns, we matched each food group point estimate within the respective range with globally representative food composition data. We then compared the resulting dietary nutrient intakes with globally harmonised recommended nutrient intakes for adults and women of reproductive age for six micronutrients that are globally scarce. To fill the dietary gaps that were estimated for vitamin B12, calcium, iron, and zinc, we suggest modifications to the original planetary health diet to achieve micronutrient adequacy (without fortification or supplementation) for adults, which included increasing the proportion of animal source foods and reducing foods high in phytate.

Cardiometabolic health, diet and the gut microbiome: a meta-omics perspective

Cardiometabolic diseases have become a leading cause of morbidity and mortality globally. They have been tightly linked to microbiome taxonomic and functional composition, with diet possibly mediating some of the associations described. Both the microbiome and diet are modifiable, which opens the way for novel therapeutic strategies. High-throughput omics techniques applied on microbiome samples (meta-omics) hold the unprecedented potential to shed light on the intricate links between diet, the microbiome, the metabolome and cardiometabolic health, with a top-down approach. However, effective integration of complementary meta-omic techniques is an open challenge and their application on large cohorts is still limited. Here we review meta-omics techniques and discuss their potential in this context, highlighting recent large-scale efforts and the novel insights they provided. Finally, we look to the next decade of meta-omics research and discuss various translational and clinical pathways to improving cardiometabolic health.

Friend or Foe? The Role of Animal-Source Foods in Healthy and Environmentally Sustainable Diets

Scientific and political discussions around the role of animal-source foods (ASFs) in healthy and environmentally sustainable diets are often polarizing. To bring clarity to this important topic, we critically reviewed the evidence on the health and environmental benefits and risks of ASFs, focusing on primary trade-offs and tensions, and summarized the evidence on alternative proteins and protein-rich foods. ASFs are rich in bioavailable nutrients commonly lacking globally and can make important contributions to food and nutrition security. Many populations in Sub-Saharan Africa and South Asia could benefit from increased consumption of ASFs through improved nutrient intakes and reduced undernutrition. Where consumption is high, processed meat should be limited, and red meat and saturated fat should be moderated to lower noncommunicable disease risk-this could also have cobenefits for environmental sustainability. ASF production generally has a large environmental impact; yet, when produced at the appropriate scale and in accordance with local ecosystems and contexts, ASFs can play an important role in circular and diverse agroecosystems that, in certain circumstances, can help restore biodiversity and degraded land and mitigate greenhouse gas emissions from food production. The amount and type of ASF that is healthy and environmentally sustainable will depend on the local context and health priorities and will change over time as populations develop, nutritional concerns evolve, and alternative foods from new technologies become more available and acceptable. Efforts by governments and civil society organizations to increase or decrease ASF consumption should be considered in light of the nutritional and environmental needs and risks in the local context and, importantly, integrally involve the local stakeholders impacted by any changes. Policies, programs, and incentives are needed to ensure best practices in production, curb excess consumption where high, and sustainably increase consumption where low.

A novel food processing-based nutrition classification scheme for guiding policy actions applied to the Australian food supply

Unhealthy diets are a leading risk factor for non-communicable diseases and negatively impact environmental sustainability. Policy actions recommended to address dietary risk factors, such as restrictions on marketing and front-of-pack labelling, are informed by nutrition classification schemes (NCSs). Ultra-processed foods are associated with adverse population and planetary health outcomes, yet the concept is rarely incorporated in nutrition classification schemes for policy actions. This study aims to develop a novel food processing-based nutrition classification scheme for guiding policy actions. A secondary aim is to validate the scheme by classifying food and beverage items in the Australian food supply (face validity) and comparing them to the classifications of existing NCSs (convergent validity). Two versions of a model were developed, classifying foods and beverages in two steps, first using the NOVA classification system and secondly by applying upper thresholds for added free sugars and sodium, producing a binary output of either healthy or unhealthy. All food and beverage items (n = 7,322) in a dataset combining the Australian Food Composition Database (AUSNUT 2011-2013) and Mintel's Global New Product Database (2014-2019) were classified using the two models. The same dataset was also classified by the Health Star Rating system (HSR), The Australian Dietary Guidelines (ADGs), The Pan American Health Organization's Nutrient Profile Model (PAHO NPM), and the NOVA classification scheme, and pairwise agreement between all NCSs and the two models was determined (using Cohen's Kappa coefficient). A higher proportion of food categories consistent with dietary patterns that are associated with positive health outcomes, such and fruits, vegetables, and eggs were classified as healthy. And the clear majority of food categories consistent with dietary patterns associated with adverse health outcomes, such as confectionery, snack foods, and convenience foods were classified as unhealthy. The two versions of the model showed substantial agreement with NOVA and the PAHO NPM, fair agreement with the ADGs and slight to moderate agreement with the HSR system. A model NCS combining level of processing and nutrient criteria presents a valid alternative to existing methods to classify the health potential of individual foods for policy purposes.

Food composition databases in the era of Big Data: Vegetable oils as a case study

Understanding the population's dietary patterns and their impacts on health requires many different sources of information. The development of reliable food composition databases is a key step in this pursuit. With them, nutrition and health care professionals can provide better public health advice and guide society toward achieving a better and healthier life. Unfortunately, these databases are full of caveats. Focusing on the specific case of vegetable oils, we analyzed the possible obsolescence of the information and the differences or inconsistencies among databases. We show that in many cases, the information is limited, incompletely documented, old or unreliable. More importantly, despite the many efforts carried out in the last decades, there is still much work to be done. As such, institutions should develop long-standing programs that can ensure the quality of the information on what we eat in the long term. In the face of climate change and complex societal challenges in an interconnected world, the full diversity of the food system needs to be recognized and more efforts should be put toward achieving a data-driven food system.

Research gaps and opportunities in precision nutrition: an NIH workshop report

Precision nutrition is an emerging concept that aims to develop nutrition recommendations tailored to different people's circumstances and biological characteristics. Responses to dietary change and the resulting health outcomes from consuming different diets may vary significantly between people based on interactions between their genetic backgrounds, physiology, microbiome, underlying health status, behaviors, social influences, and environmental exposures. On 11-12 January 2021, the National Institutes of Health convened a workshop entitled "Precision Nutrition: Research Gaps and Opportunities" to bring together experts to discuss the issues involved in better understanding and addressing precision nutrition. The workshop proceeded in 3 parts: part I covered many aspects of genetics and physiology that mediate the links between nutrient intake and health conditions such as cardiovascular disease, Alzheimer disease, and cancer; part II reviewed potential contributors to interindividual variability in dietary exposures and responses such as baseline nutritional status, circadian rhythm/sleep, environmental exposures, sensory properties of food, stress, inflammation, and the social determinants of health; part III presented the need for systems approaches, with new methods and technologies that can facilitate the study and implementation of precision nutrition, and workforce development needed to create a new generation of researchers. The workshop concluded that much research will be needed before more precise nutrition recommendations can be achieved. This includes better understanding and accounting for variables such as age, sex, ethnicity, medical history, genetics, and social and environmental factors. The advent of new methods and technologies and the availability of considerably more data bring tremendous opportunity. However, the field must proceed with appropriate levels of caution and make sure the factors listed above are all considered, and systems approaches and methods are incorporated. It will be important to develop and train an expanded workforce with the goal of reducing health disparities and improving precision nutritional advice for all Americans.

Enhancing untargeted metabolomics using metadata-based source annotation

Human untargeted metabolomics studies annotate only ~10% of molecular features. We introduce reference-data-driven analysis to match metabolomics tandem mass spectrometry (MS/MS) data against metadata-annotated source data as a pseudo-MS/MS reference library. Applying this approach to food source data, we show that it increases MS/MS spectral usage 5.1-fold over conventional structural MS/MS library matches and allows empirical assessment of dietary patterns from untargeted data.

Comparing the Chemical Profiles of Plant-Based and Traditional Meats Using GC–MS-Based Metabolomics

As the consumer interest and market for plant-based meat alternatives grows, understanding the nutritional differences between alternative and traditional meats is essential. This article describes an untargeted gas chromatography–mass spectrometry (GC–MS)-based metabolomics approach that compares the chemical profiles of a popular plant-based meat alternative and grass-fed ground beef using a GC system coupled to a GC–MS device. The samples were derivatized to simplify the chromatographic process and render the polar metabolites more volatile for GC–MS analysis. Statistical and multivariate analysis of the acquired and processed GC–MS data revealed that 90% of the annotated compounds differed between the plant-based alternative meat and the grass-fed ground beef samples. The ground beef and plant-based products each contained several compounds that were found in much smaller quantities, or not at all, in the other product. These results indicate differences in organic composition even though the nutritional labels on the back of the products were nearly identical. Heat maps, principal component analysis (PCA) score plots, variable importance plots (VIPs), and the clustering of compounds into metabolite classes provided further insights into the differences between the two types of meat products. The biological significance of the comparative data was studied using online databases and pathway analysis tools.

In silico investigation of molecular networks linking gastrointestinal diseases, malnutrition, and sarcopenia

Malnutrition (MN) is a common primary or secondary complication in gastrointestinal diseases. The patient’s nutritional status also influences muscle mass and function, which can be impaired up to the degree of sarcopenia. The molecular interactions in diseases leading to sarcopenia are complex and multifaceted, affecting muscle physiology, the intestine (nutrition), and the liver at different levels. Although extensive knowledge of individual molecular factors is available, their regulatory interplay is not yet fully understood. A comprehensive overall picture of pathological mechanisms and resulting phenotypes is lacking. In silico approaches that convert existing knowledge into computationally readable formats can help unravel mechanisms, underlying such complex molecular processes. From public literature, we manually compiled experimental evidence for molecular interactions involved in the development of sarcopenia into a knowledge base, referred to as the Sarcopenia Map. We integrated two diseases, namely liver cirrhosis (LC), and intestinal dysfunction, by considering their effects on nutrition and blood secretome. We demonstrate the performance of our model by successfully simulating the impact of changing dietary frequency, glycogen storage capacity, and disease severity on the carbohydrate and muscle systems. We present the Sarcopenia Map as a publicly available, open-source, and interactive online resource, that links gastrointestinal diseases, MN, and sarcopenia. The map provides tools that allow users to explore the information on the map and perform in silico simulations.

Integrative proteomics and metabolomics of Guizhou Miao Sour Soup affecting simple obese rats

Miao Sour Soup (MSS) is a fermented product from the Qiandongnan region of Guizhou Province, which enrich many beneficial ingredients and is widely consumed in the whole China. Fermented food is beneficial to physical health with the potential positive regulating affection on simple obesity. In this study, we analyzed the mechanism of action of MSS to prevent simple obesity induced by high-fat diet by proteomics and metabolomics. Quantitative proteomics with tandem mass tagging labeling and liquid chromatography-mass spectrometry was used to analyze the changes of liver proteins and metabolites after the MSS intervention. MSS intervention upregulated 33 proteins and 9 metabolites and downregulated 19 proteins and 10 metabolites. Bioinformatics analysis showed that MSS could prevent simple obesity by acting on the PPAR signaling pathway, retinol metabolism, fatty acid β-oxidation, fatty acid degradation, fatty acid biosynthesis, glycine, serine and threonine metabolism, pyruvate metabolism, citrate cycle (TCA cycle) and other signaling pathways. This study provides new insights into the use of MSS to prevent simple obesity caused by high-fat diets and the search for healthy eating patterns with MSS.

Fermented foods and cardiometabolic health: Definitions, current evidence, and future perspectives

Unhealthy diets contribute to the increasing burden of non-communicable diseases. Annually, over 11 million deaths worldwide are attributed to dietary risk factors, with the vast majority of deaths resulting from cardiometabolic diseases (CMDs) including cardiovascular disease (∼10 million) and type II diabetes (∼339,000). As such, defining diets and dietary patterns that mitigate CMD risk is of great public health importance. Recently, the consumption of fermented foods has emerged as an important dietary strategy for improving cardiometabolic health. Fermented foods have been present in the human diet for over 10,000 years, but knowledge on whether their consumption benefits human health, and the molecular and microbiological mechanisms underpinning their purported health benefits, is relatively nascent. This review provides an overview of the definitions of fermented foods, types and qualities of fermented foods consumed in Europe and globally, possible mechanisms between the consumption of fermented foods and cardiometabolic health, as well as the current state of the epidemiological evidence on fermented food intake and cardiometabolic health. Finally, we outline future perspectives and opportunities for improving the role of fermented foods in human diets.

MilkyBase, a database of human milk composition as a function of maternal-, infant- and measurement conditions

This study describes the development of a database, called MilkyBase, of the biochemical composition of human milk. The data were selected, digitized and curated partly by machine-learning, partly manually from publications. The database can be used to find patterns in the milk composition as a function of maternal-, infant- and measurement conditions and as a platform for users to put their own data in the format shown here. The database is an Excel workbook of linked sheets, making it easy to input data by non-computationally minded nutritionists. The hierarchical organisation of the fields makes sure that statistical inference methods can be programmed to analyse the data. Uncertainty quantification and recording dynamic (time-dependent) compositions offer predictive potentials.

Measurement(s)	Concentration of biochemical compounds in human milk or/and derived quantities, like their sums or ratios.
Technology Type(s)	Data mining, by means of Machine Learning and targeted manual literature search within available scientific publications in the internet.
Factor Type(s)	Georgaphical region • Cohort size • Measurement Method • Various characteristics (including history) of mother, child, breast milk and measurement
Sample Characteristic - Organism	Human milk
Sample Characteristic - Environment	Standard birth environment
Sample Characteristic - Location	Various regions of the world

Child dietary patterns in Homo sapiens evolution: A systematic review

Dietary patterns spanning millennia could inform contemporary public health nutrition. Children are largely absent from evidence describing diets throughout human evolution, despite prevalent malnutrition today signaling a potential genome-environment divergence. This systematic review aimed to identify dietary patterns of children ages 6 months to 10 years consumed before the widespread adoption of agriculture. Metrics of mention frequency (counts of food types reported) and food groups (globally standardized categories) were applied to: compare diets across subsistence modes [gatherer-hunter-fisher (GHF), early agriculture (EA) groups]; examine diet quality and diversity; and characterize differences by life course phase and environmental context defined using Köppen-Geiger climate zones. The review yielded child diet information from 95 cultural groups (52 from GHF; 43 from EA/mixed subsistence groups). Animal foods (terrestrial and aquatic) were the most frequently mentioned food groups in dietary patterns across subsistence modes, though at higher frequencies in GHF than in EA. A broad range of fruits, vegetables, roots and tubers were more common in GHF, while children from EA groups consumed more cereals than GHF, associated with poor health consequences as reported in some studies. Forty-eight studies compared diets across life course phases: 28 showed differences and 20 demonstrated similarities in child versus adult diets. Climate zone was a driver of food patterns provisioned from local ecosystems. Evidence from Homo sapiens evolution points to the need for nutrient-dense foods with high quality proteins and greater variety within and across food groups. Public health solutions could integrate these findings into food-based dietary guidelines for children.

Valuing the Diversity of Research Methods to Advance Nutrition Science

The ASN Board of Directors appointed the Nutrition Research Task Force to develop a report on scientific methods used in nutrition science to advance discovery, interpretation, and application of knowledge in the field. The genesis of this report was growing concern about the tone of discourse among nutrition professionals and the implications of acrimony on the productive study and translation of nutrition science. Too often, honest differences of opinion are cast as conflicts instead of areas of needed collaboration. Recognition of the value (and limitations) of contributions from well-executed nutrition science derived from the various approaches used in the discipline, as well as appreciation of how their layering will yield the strongest evidence base, will provide a basis for greater productivity and impact. Greater collaborative efforts within the field of nutrition science will require an understanding that each method or approach has a place and function that should be valued and used together to create the nutrition evidence base. Precision nutrition was identified as an important emerging nutrition topic by the preponderance of task force members, and this theme was adopted for the report because it lent itself to integration of many approaches in nutrition science. Although the primary audience for this report is nutrition researchers and other nutrition professionals, a secondary aim is to develop a document useful for the various audiences that translate nutrition research, including journalists, clinicians, and policymakers. The intent is to promote accurate, transparent, verifiable evidence-based communication about nutrition science. This will facilitate reasoned interpretation and application of emerging findings and, thereby, improve understanding and trust in nutrition science and appropriate characterization, development, and adoption of recommendations.

An Integrative Glycomic Approach for Quantitative Meat Species Profiling

It is estimated that food fraud, where meat from different species is deceitfully labelled or contaminated, has cost the global food industry around USD 6.2 to USD 40 billion annually. To overcome this problem, novel and robust quantitative methods are needed to accurately characterise and profile meat samples. In this study, we use a glycomic approach for the profiling of meat from different species. This involves an O-glycan analysis using LC-MS qTOF, and an N-glycan analysis using a high-resolution non-targeted ultra-performance liquid chromatography-fluorescence-mass spectrometry (UPLC-FLR-MS) on chicken, pork, and beef meat samples. Our integrated glycomic approach reveals the distinct glycan profile of chicken, pork, and beef samples; glycosylation attributes such as fucosylation, sialylation, galactosylation, high mannose, α-galactose, Neu5Gc, and Neu5Ac are significantly different between meat from different species. The multi-attribute data consisting of the abundance of each O-glycan and N-glycan structure allows a clear separation between meat from different species through principal component analysis. Altogether, we have successfully demonstrated the use of a glycomics-based workflow to extract multi-attribute data from O-glycan and N-glycan analysis for meat profiling. This established glycoanalytical methodology could be extended to other high-value biotechnology industries for product authentication.

Perspective: Darwinian Applications to Nutrition-The Value of Evolutionary Insights to Teachers and Students

Evolutionary biology informs us that the living world is a product of evolution, guided by the Darwinian mechanism of natural selection. This recognition has been fruitfully employed in a number of issues in health and nutrition sciences; however, it has not been incorporated into education. Nutrition and dietetics students generally learn very little or nothing on the subject of evolution, despite the fact that evolution is the process by which our genetically determined physiological traits and needs were shaped. In the present Perspective article, 3 examples of topics (inflammatory diseases, nutrition transition, and food intolerance) that can benefit from evolutionary information and reasoning are given, with relevant lines of research and inquiry provided throughout. It is argued that the application of evolutionary science to these and other areas of nutrition education can facilitate a deeper and more coherent teaching and learning experience. By recognizing and reframing nutrition as an aspect and discipline of biology, grounded in the fundamental principle of adaptation, revelatory light is shed on physiological states and responses, contentious and unresolved issues, genomic, epigenomic, and microbiomic features, and optimal nutrient status and intakes.

A Guide to Dietary Pattern-Microbiome Data Integration

The human gut microbiome is linked to metabolic and cardiovascular disease risk. Dietary modulation of the human gut microbiome offers an attractive pathway to manipulate the microbiome to prevent microbiome-related disease. However, this promise has not been realized. The complex system of diet and microbiome interactions is poorly understood. Integrating observational human diet and microbiome data can help researchers and clinicians untangle the complex systems of interactions that predict how the microbiome will change in response to foods. The use of dietary patterns to assess diet-microbiome relations holds promise to identify interesting associations and result in findings that can directly translate into actionable dietary intake recommendations and eating plans. In this article, we first highlight the complexity inherent in both dietary and microbiome data and introduce the approaches generally used to explore diet and microbiome simultaneously in observational studies. Second, we review the food group and dietary pattern-microbiome literature focusing on dietary complexity-moving beyond nutrients. Our review identified a substantial and growing body of literature that explores links between the microbiome and dietary patterns. However, there was very little standardization of dietary collection and assessment methods across studies. The 54 studies identified in this review used ≥7 different methods to assess diet. Coupled with the variation in final dietary parameters calculated from dietary data (e.g., dietary indices, dietary patterns, food groups, etc.), few studies with shared methods and assessment techniques were available for comparison. Third, we highlight the similarities between dietary and microbiome data structures and present the possibility that multivariate and compositional methods, developed initially for microbiome data, could have utility when applied to dietary data. Finally, we summarize the current state of the art for diet-microbiome data integration and highlight ways dietary data could be paired with microbiome data in future studies to improve the detection of diet-microbiome signals.

Foodomics: A Data-Driven Approach to Revolutionize Nutrition and Sustainable Diets

Globally, we are failing to meet numerous nutritional, health, and environmental targets linked to food. Defining food composition in its full chemical and quantitative diversity is central to data-driven decision making for supporting nutrition and sustainable diets. "Foodomics"-the application of omics-technology to characterize and quantify biomolecules to improve wellbeing-has the potential to comprehensively elucidate what is in food, how this composition varies across the food system, and how diet composition as an ensemble of foods guides outcomes for nutrition, health, and sustainability. Here, we outline: (i) challenges of evaluating food composition; (ii) state-of-the-art omics technology and innovations for the analysis of food; and (iii) application of foodomics as a complementary data-driven approach to revolutionize nutrition and sustainable diets. Featuring efforts of the Periodic Table of Food Initiative, a participatory effort to create a globally shared foodomics platform, we conclude with recommendations to accelerate foodomics in ways that strengthen the capacity of scientists and benefit all people.

Nutrient concentrations in food display universal behaviour

Extensive programmes around the world endeavour to measure and catalogue the composition of food. Here we analyse the nutrient content of the full US food supply and show that the concentration of each nutrient follows a universal single-parameter scaling law that accurately captures the eight orders of magnitude in nutrient content variability. We show that the universality is rooted in the biochemical constraints obeyed by the metabolic pathways responsible for nutrient modulation, allowing us to confirm the empirically observed scaling law and to predict its variability in agreement with the data. We propose that the natural nutrient variability in food can be quantitatively formalized. This provides a mathematical rationale for imputing missing values in food composition databases and paves the way towards a quantitative understanding of the impact of food processing on nutrient balance and health effects.

Mediterranean-Type Diets as a Protective Factor for Asthma and Atopy

We are currently riding the second wave of the allergy epidemic, which is ongoing in affluent societies, but now also affecting developing countries. This increase in the prevalence of atopy/asthma in the Western world has coincided with a rapid improvement in living conditions and radical changes in lifestyle, suggesting that this upward trend in allergic manifestations may be associated with cultural and environmental factors. Diet is a prominent environmental exposure that has undergone major changes, with a substantial increase in the consumption of processed foods, all across the globe. On this basis, the potential effects of dietary habits on atopy and asthma have been researched rigorously, but even with a considerable body of evidence, clear associations are far from established. Many factors converge to obscure the potential relationship, including methodological, pathophysiological and cultural differences. To date, the most commonly researched, and highly promising, candidate for exerting a protective effect is the so-called Mediterranean diet (MedDi). This dietary pattern has been the subject of investigation since the mid twentieth century, and the evidence regarding its beneficial health effects is overwhelming, although data on a correlation between MedDi and the incidence and severity of asthma and atopy are inconclusive. As the prevalence of asthma appears to be lower in some Mediterranean populations, it can be speculated that the MedDi dietary pattern could indeed have a place in a preventive strategy for asthma/atopy. This is a review of the current evidence of the associations between the constituents of the MedDi and asthma/atopy, with emphasis on the pathophysiological links between MedDi and disease outcomes and the research pitfalls and methodological caveats which may hinder identification of causality. MedDi, as a dietary pattern, rather than short-term supplementation or excessive focus on single nutrient effects, may be a rational option for preventive intervention against atopy and asthma.

foodMASST a mass spectrometry search tool for foods and beverages

There is a growing interest in unraveling the chemical complexity of our diets. To help the scientific community gain insight into the molecules present in foods and beverages that we ingest, we created foodMASST, a search tool for MS/MS spectra (of both known and unknown molecules) against a growing metabolomics food and beverage reference database. We envision foodMASST will become valuable for nutrition research and to assess the potential uniqueness of dietary biomarkers to represent specific foods or food classes.

A Need for a Paradigm Shift in Healthy Nutrition Research

Research in the field of sustainable and healthy nutrition is calling for the application of the latest advances in seemingly unrelated domains such as complex systems and network sciences on the one hand and big data and artificial intelligence on the other. This is because the confluence of these fields, whose methodologies have experienced explosive growth in the last few years, promises to solve some of the more challenging problems in sustainable and healthy nutrition, i.e., integrating food and behavioral-based dietary guidelines. Focusing here primarily on nutrition and health, we discuss what kind of methodological shift is needed to open current disciplinary borders to the methods, languages, and knowledge of the digital era and a system thinking approach. Specifically, we advocate for the adoption of interdisciplinary, complex-systems-based research to tackle the huge challenge of dealing with an evolving interdependent system in which there are multiple scales-from the metabolome to the population level-, heterogeneous and-more often than not- incomplete data, and population changes subject to many behavioral and environmental pressures. To illustrate the importance of this methodological innovation we focus on the consumption aspects of nutrition rather than production, but we recognize the importance of system-wide studies that involve both these components of nutrition. We round off the paper by outlining some specific research directions that would make it possible to find new correlations and, possibly, causal relationships across scales and to answer pressing questions in the area of sustainable and healthy nutrition.