Dietary Macronutrient Composition in Relation to Circulating HDL and Non-HDL Cholesterol: A Federated Individual-Level Analysis of Cross-Sectional Data from Adolescents and Adults in 8 European Studies.

BACKGROUND: Associations between increased dietary fat and decreased carbohydrate intake with circulating HDL and non-HDL cholesterol have not been conclusively determined. OBJECTIVE: We assessed these relations in 8 European observational human studies participating in the European Nutritional Phenotype Assessment and Data Sharing Initiative (ENPADASI) using harmonized data. METHODS: Dietary macronutrient intake was recorded using study-specific dietary assessment tools. Main outcome measures were lipoprotein cholesterol concentrations: HDL cholesterol (mg/dL) and non-HDL cholesterol (mg/dL). A cross-sectional analysis on 5919 participants (54% female) aged 13-80 y was undertaken using the statistical platform DataSHIELD that allows remote/federated nondisclosive analysis of individual-level data. Generalized linear models (GLM) were fitted to assess associations between replacing 5% of energy from carbohydrates with equivalent energy from total fats, SFAs, MUFAs, or PUFAs with circulating HDL cholesterol and non-HDL cholesterol. GLM were adjusted for study source, age, sex, smoking status, alcohol intake and BMI. RESULTS: The replacement of 5% of energy from carbohydrates with total fats or MUFAs was statistically significantly associated with 0.67 mg/dL (95% CI: 0.40, 0.94) or 0.99 mg/dL (95% CI: 0.37, 1.60) higher HDL cholesterol, respectively, but not with non-HDL cholesterol concentrations. The replacement of 5% of energy from carbohydrates with SFAs or PUFAs was not associated with HDL cholesterol, but SFAs were statistically significantly associated with 1.94 mg/dL (95% CI: 0.08, 3.79) higher non-HDL cholesterol, and PUFAs with -3.91 mg/dL (95% CI: -6.98, -0.84) lower non-HDL cholesterol concentrations. A statistically significant interaction by sex for the association of replacing carbohydrates with MUFAs and non-HDL cholesterol was observed, showing a statistically significant inverse association in males and no statistically significant association in females. We observed no statistically significant interaction by age. CONCLUSIONS: The replacement of dietary carbohydrates with fats had favorable effects on lipoprotein cholesterol concentrations in European adolescents and adults when fats were consumed as MUFAs or PUFAs but not as SFAs.

Joint Data Analysis in Nutritional Epidemiology: Identification of Observational Studies and Minimal Requirements.

Background: Joint data analysis from multiple nutrition studies may improve the ability to answer complex questions regarding the role of nutritional status and diet in health and disease. Objective: The objective was to identify nutritional observational studies from partners participating in the European Nutritional Phenotype Assessment and Data Sharing Initiative (ENPADASI) Consortium, as well as minimal requirements for joint data analysis. Methods: A predefined template containing information on study design, exposure measurements (dietary intake, alcohol and tobacco consumption, physical activity, sedentary behavior, anthropometric measures, and sociodemographic and health status), main health-related outcomes, and laboratory measurements (traditional and omics biomarkers) was developed and circulated to those European research groups participating in the ENPADASI under the strategic research area of "diet-related chronic diseases." Information about raw data disposition and metadata sharing was requested. A set of minimal requirements was abstracted from the gathered information. Results: Studies (12 cohort, 12 cross-sectional, and 2 case-control) were identified. Two studies recruited children only and the rest recruited adults. All studies included dietary intake data. Twenty studies collected blood samples. Data on traditional biomarkers were available for 20 studies, of which 17 measured lipoproteins, glucose, and insulin and 13 measured inflammatory biomarkers. Metabolomics, proteomics, and genomics or transcriptomics data were available in 5, 3, and 12 studies, respectively. Although the study authors were willing to share metadata, most refused, were hesitant, or had legal or ethical issues related to sharing raw data. Forty-one descriptors of minimal requirements for the study data were identified to facilitate data integration. Conclusions: Combining study data sets will enable sufficiently powered, refined investigations to increase the knowledge and understanding of the relation between food, nutrition, and human health. Furthermore, the minimal requirements for study data may encourage more efficient secondary usage of existing data and provide sufficient information for researchers to draft future multicenter research proposals in nutrition.

EURRECA-Estimating selenium requirements for deriving dietary reference values.

Current reference values for selenium, an essential micronutrient, are based on the intake of selenium that is required to achieve maximal glutathione peroxidase activity in plasma or erythrocytes. In order to assess the evidence of relevance to setting dietary reference values for selenium, the EURRECA Network of Excellence focused on systematic searches, review, and evaluation of (i) selenium status biomarkers and evidence for relationships between intake and status biomarkers, (ii) selenium and health (including the effect of intake and/or status biomarkers on cancer risk, immune function, HIV, cognition, and fertility), (iii) bioavailability of selenium from the diet, and (iv) impact of genotype/single nucleotide polymorphisms on status or health outcomes associated with selenium. The main research outputs for selenium and future research priorities are discussed further in this review.

EURRECA-Evidence-based methodology for deriving micronutrient recommendations.

The EURopean micronutrient RECommendations Aligned (EURRECA) Network of Excellence explored the process of setting micronutrient recommendations to address the variance in recommendations across Europe. Work centered upon the transparent assessment of nutritional requirements via a series of systematic literature reviews and meta-analyses. In addition, the necessity of assessing nutritional requirements and the policy context of setting micronutrient recommendations was investigated. Findings have been presented in a framework that covers nine activities clustered into four stages: stage one "Defining the problem" describes Activities 1 and 2: "Identifying the nutrition-related health problem" and "Defining the process"; stage two "Monitoring and evaluating" describes Activities 3 and 7: "Establishing appropriate methods," and "Nutrient intake and status of population groups"; stage three "Deriving dietary reference values" describes Activities 4, 5, and 6: "Collating sources of evidence," "Appraisal of the evidence," and "Integrating the evidence"; stage four "Using dietary reference values in policy making" describes Activities 8 and 9: "Identifying policy options," and "Evaluating policy implementation." These activities provide guidance on how to resolve various issues when deriving micronutrient requirements and address the methodological and policy decisions, which may explain the current variation in recommendations across Europe. [Supplementary materials are available for this article. Go to the publisher's online edition of Critical Reviews in Food Science and Nutrition for the following free supplemental files: Additional text, tables, and figures.].

A domino effect in drug action: from metabolic assault towards parasite differentiation.

Awareness is growing that drug target validation should involve systems analysis of cellular networks. There is less appreciation, though, that the composition of networks may change in response to drugs. If the response is homeostatic (e.g. through upregulation of the target protein), this may neutralize the inhibitory effect. In this scenario the effect on cell growth and survival would be less than anticipated based on affinity of the drug for its target. Glycolysis is the sole free-energy source for the deadly parasite Trypanosoma brucei and is therefore a possible target pathway for anti-trypanosomal drugs. Plasma-membrane glucose transport exerts high control over trypanosome glycolysis and hence the transporter is a promising drug target. Here we show that at high inhibitor concentrations, inhibition of trypanosome glucose transport causes cell death. Most interestingly, sublethal concentrations initiate a domino effect in which network adaptations enhance inhibition. This happens via (i) metabolic control exerted by the target protein, (ii) decreases in mRNAs encoding the target protein and other proteins in the same pathway, and (iii) partial differentiation of the cells leading to (low) expression of immunogenic insect-stage coat proteins. We discuss how these 'anti-homeostatic' responses together may facilitate killing of parasites at an acceptable drug dosage.

The human gastrointestinal microbiota--an unexplored frontier for pharmaceutical discovery.

The mammalian gastrointestinal tract (GIT) harbors microorganisms (the microbiota) of vast phylogentic, genomic, and metabolic diversity, and recent years have seen a rapid development in the techniques for studying these complex microbial ecosystems. It is increasingly apparent that the GIT microbiota plays an intricate role in host health and disease. Targeted strategies for modulating human health through the modification of the GIT microbiota, however, are developing and in their infancy. This perspective article discusses the rationale, benefits and limitations of using the GIT microbiota as a pharmacological and nutritional target in the treatment of various diseases and disorders linked to imbalances in our microbiota.

FAIR Digital Twins for Data-Intensive Research.

Although all the technical components supporting fully orchestrated Digital Twins (DT) currently exist, what remains missing is a conceptual clarification and analysis of a more generalized concept of a DT that is made FAIR, that is, universally machine actionable. This methodological overview is a first step toward this clarification. We present a review of previously developed semantic artifacts and how they may be used to compose a higher-order data model referred to here as a FAIR Digital Twin (FDT). We propose an architectural design to compose, store and reuse FDTs supporting data intensive research, with emphasis on privacy by design and their use in GDPR compliant open science.

HDHL-INTIMIC: A European Knowledge Platform on Food, Diet, Intestinal Microbiomics, and Human Health.

Studies indicate that the intestinal microbiota influences general metabolic processes in humans, thereby modulating the risk of chronic diseases such as type 2 diabetes, allergy, cardiovascular disease, and colorectal cancer (CRC). Dietary factors are also directly related to chronic disease risk, and they affect the composition and function of the gut microbiota. Still, detailed knowledge on the relation between diet, the microbiota, and chronic disease risk is limited. The overarching aim of the HDHL-INTIMIC (INtesTInal MICrobiomics) knowledge platform is to foster studies on the microbiota, nutrition, and health by assembling available knowledge of the microbiota and of the other aspects (e.g., food science and metabolomics) that are relevant in the context of microbiome research. The goal is to make this information findable, accessible, interoperable, and reusable (FAIR) to the scientific community, and to share information with the various stakeholders. Through these efforts a network of transnational and multidisciplinary collaboration has emerged, which has contributed to further develop and increase the impact of microbiome research in human health. The roles of microbiota in early infancy, during ageing, and in subclinical and clinically manifested disease are identified as urgent areas of research in this knowledge platform.

Metabolic regulation rather than de novo enzyme synthesis dominates the osmo-adaptation of yeast.

Intracellular accumulation of glycerol is essential for yeast cells to survive hyperosmotic stress. Upon hyperosmotic stress the gene expression of enzymes in the glycerol pathway is strongly induced. Recently, however, it was shown that this gene-expression response is not essential for survival of an osmotic shock [Mettetal JT et al. (2008) Science 319: 482­484 and Westfall PJ et al. (2008) Proc Natl Acad Sci 105: 12212­12217]. Instead, pure metabolic adaptation can rescue the yeast. The existence of two alternative mechanisms urged the question which of these mechanisms dominates time-dependent adaptation of wild-type yeast to osmotic stress under physiological conditions. The regulation of the glycerol pathway was analysed in aerobic, glucose-limited cultures upon addition of 1 M of sorbitol, leading to a hyperosmotic shock. In agreement with earlier studies, the mRNA levels of the glycerol-producing enzymes as well as their catalytic capacities increased. Qualitatively this induction followed a similar time course to the increase of the glycerol flux. However, a quantitative regulation analysis of the data revealed an initial regulation by metabolism alone. After only a few minutes gene expression came into play, but even after an hour, 80% of the increase in the glycerol flux was explained by metabolic changes in the cell, and 20% by induction of gene expression. This demonstrates that the novel metabolic mechanism is not just a secondary rescue mechanism, but the most important mechanism to regulate the glycerol flux under physiological conditions.

Microbiota in Health and Disease-Potential Clinical Applications.

Within the last two decades tremendous efforts in biomedicine have been undertaken to understand the interplay of commensal bacteria living in and on our human body with our own human physiology. It became clear that (1) a high diversity especially of the microbial communities in the gut are important to preserve health and that (2) certain bacteria via nutrition-microbe-host metabolic axes are beneficially affecting various functions of the host, including metabolic control, energy balance and immune function. While a large set of evidence indicate a special role for small chain fatty acids (SCFA) in that context, recently also metabolites of amino acids (e.g., tryptophan and arginine) moved into scientific attention. Of interest, microbiome alterations are not only important in nutrition associated diseases like obesity and diabetes, but also in many chronic inflammatory, oncological and neurological abnormalities. From a clinician's point of view, it should be mentioned, that the microbiome is not only interesting to develop novel therapies, but also as a modifiable factor to improve efficiency of modern pharmaceutics, e.g., immune-therapeutics in oncology. However, so far, most data rely on animal experiments or human association studies, whereas controlled clinical intervention studies are spare. Hence, the translation of the knowledge of the last decades into clinical routine will be the challenge of microbiome based biomedical research for the next years. This review aims to provide examples for future clinical applications in various entities and to suggest bacterial species and/or microbial effector molecules as potential targets for intervention studies.

Gut Microbiome Composition in Obese and Non-Obese Persons: A Systematic Review and Meta-Analysis.

Whether the gut microbiome in obesity is characterized by lower diversity and altered composition at the phylum or genus level may be more accurately investigated using high-throughput sequencing technologies. We conducted a systematic review in PubMed and Embase including 32 cross-sectional studies assessing the gut microbiome composition by high-throughput sequencing in obese and non-obese adults. A significantly lower alpha diversity (Shannon index) in obese versus non-obese adults was observed in nine out of 22 studies, and meta-analysis of seven studies revealed a non-significant mean difference (-0.06, 95% CI -0.24, 0.12, I2 = 81%). At the phylum level, significantly more Firmicutes and fewer Bacteroidetes in obese versus non-obese adults were observed in six out of seventeen, and in four out of eighteen studies, respectively. Meta-analyses of six studies revealed significantly higher Firmicutes (5.50, 95% 0.27, 10.73, I2 = 81%) and non-significantly lower Bacteroidetes (-4.79, 95% CI -10.77, 1.20, I2 = 86%). At the genus level, lower relative proportions of Bifidobacterium and Eggerthella and higher Acidaminococcus, Anaerococcus, Catenibacterium, Dialister, Dorea, Escherichia-Shigella, Eubacterium, Fusobacterium, Megasphera, Prevotella, Roseburia, Streptococcus, and Sutterella were found in obese versus non-obese adults. Although a proportion of studies found lower diversity and differences in gut microbiome composition in obese versus non-obese adults, the observed heterogeneity across studies precludes clear answers.

A Machine Learning Algorithm for Quantitatively Diagnosing Oxidative Stress Risks in Healthy Adult Individuals Based on Health Space Methodology: A Proof-of-Concept Study Using Korean Cross-Sectional Cohort Data.

Oxidative stress aggravates the progression of lifestyle-related chronic diseases. However, knowledge and practices that enable quantifying oxidative stress are still lacking. Here, we performed a proof-of-concept study to predict the oxidative stress status in a healthy population using retrospective cohort data from Boramae medical center in Korea (n = 1328). To obtain binary performance measures, we selected healthy controls versus oxidative disease cases based on the "health space" statistical methodology. We then developed a machine learning algorithm for discrimination of oxidative stress status using least absolute shrinkage and selection operator (LASSO)/elastic net regression with 10-fold cross-validation. A proposed fine-tune model included 16 features out of the full spectrum of diverse and complex data. The predictive performance was externally evaluated by generating receiver operating characteristic curves with area under the curve of 0.949 (CI 0.925 to 0.974), sensitivity of 0.923 (CI 0.879 to 0.967), and specificity of 0.855 (CI 0.795 to 0.915). Moreover, the discrimination power was confirmed by applying the proposed diagnostic model to the full dataset consisting of subjects with various degrees of oxidative stress. The results provide a feasible approach for stratifying the oxidative stress risks in the healthy population and selecting appropriate strategies for individual subjects toward implementing data-driven precision nutrition.

Identification and Characterization of Human Observational Studies in Nutritional Epidemiology on Gut Microbiomics for Joint Data Analysis.

In any research field, data access and data integration are major challenges that even large, well-established consortia face. Although data sharing initiatives are increasing, joint data analyses on nutrition and microbiomics in health and disease are still scarce. We aimed to identify observational studies with data on nutrition and gut microbiome composition from the Intestinal Microbiomics (INTIMIC) Knowledge Platform following the findable, accessible, interoperable, and reusable (FAIR) principles. An adapted template from the European Nutritional Phenotype Assessment and Data Sharing Initiative (ENPADASI) consortium was used to collect microbiome-specific information and other related factors. In total, 23 studies (17 longitudinal and 6 cross-sectional) were identified from Italy (7), Germany (6), Netherlands (3), Spain (2), Belgium (1), and France (1) or multiple countries (3). Of these, 21 studies collected information on both dietary intake (24 h dietary recall, food frequency questionnaire (FFQ), or Food Records) and gut microbiome. All studies collected stool samples. The most often used sequencing platform was Illumina MiSeq, and the preferred hypervariable regions of the 16S rRNA gene were V3-V4 or V4. The combination of datasets will allow for sufficiently powered investigations to increase the knowledge and understanding of the relationship between food and gut microbiome in health and disease.

Perspective: Towards Automated Tracking of Content and Evidence Appraisal of Nutrition Research.

Robust recommendations for healthy diets and nutrition require careful synthesis of available evidence. Given the increasing volume of research articles generated, the retrieval and synthesis of evidence are increasingly becoming laborious and time-consuming. Information technology could help to reduce workload for humans. To guide supervised learning however, human identification of key study characteristics is necessary. Reporting guidelines recommend that authors include essential content in articles and could generate manually labeled training data for automated evidence retrieval and synthesis. Here, we present a semiautomated approach to annotate, link, and track the content of nutrition research manuscripts. We used the STROBE extension for nutritional epidemiology (STROBE-nut) reporting guidelines to manually annotate a sample of 15 articles and converted the semantic information into linked data in a Neo4j graph database through an automated process. Six summary statistics were computed to estimate the reporting completeness of the articles. The content structure, presence of essential study characteristics as well as the reporting completeness of the articles are visualized automatically from the graph database. The archived linked data are interoperable through their annotations and relations. A graph database with linked data on essential study characteristics can enable Natural Language Processing in nutrition.

A Proof-of-Concept System Dynamics Simulation Model of the Development of Burnout and Recovery Using Retrospective Case Data.

The phenomenon of burnout is a complex issue, which despite major efforts from researchers and organizations remains hard to prevent. The current literature highlights an increasing global prevalence of employees that are dealing with burnout. What has been largely missing is a more systemic, dynamic, and personal perspective on the interactions of the key determinants of burnout. Burnout can be seen as the outcome of a complex system involving feedback loops between individual mental models, individual behavior, and external social influences. Understanding the feedback loops involved may enable employees and organizations to intervene in burnout trajectories early and effectively. System dynamics (SD) modeling is a methodology that can describe the structure and behavior of a complex system. The current paper describes the development of an SD model of burnout. First, an expert- and literature-informed causal loop diagram (CLD) of burnout is developed. Then, a novel approach is developed to collect personal retrospective scenario data. Finally, the CLD and data are translated into a quantitative SD model. The potential of the SD model is illustrated by simulating the behavior of three realistic personas during the onset of and recovery from burnout. The process of development of an SD model of burnout is presented and the strengths and limitations of the approach are discussed.

Digital Resilience Biomarkers for Personalized Health Maintenance and Disease Prevention.

Health maintenance and disease prevention strategies become increasingly prioritized with increasing health and economic burden of chronic, lifestyle-related diseases. A key element in these strategies is the empowerment of individuals to control their health. Self-measurement plays an essential role in achieving such empowerment. Digital measurements have the advantage of being measured non-invasively, passively, continuously, and in a real-world context. An important question is whether such measurement can sensitively measure subtle disbalances in the progression toward disease, as well as the subtle effects of, for example, nutritional improvement. The concept of resilience biomarkers, defined as the dynamic evaluation of the biological response to an external challenge, has been identified as a viable strategy to measure these subtle effects. In this review, we explore the potential of integrating this concept with digital physiological measurements to come to digital resilience biomarkers. Additionally, we discuss the potential of wearable, non-invasive, and continuous measurement of molecular biomarkers. These types of innovative measurements may, in the future, also serve as a digital resilience biomarker to provide even more insight into the personal biological dynamics of an individual. Altogether, digital resilience biomarkers are envisioned to allow for the measurement of subtle effects of health maintenance and disease prevention strategies in a real-world context and thereby give personalized feedback to improve health.

OBEDIS Core Variables Project: European Expert Guidelines on a Minimal Core Set of Variables to Include in Randomized, Controlled Clinical Trials of Obesity Interventions.

Heterogeneity of interindividual and intraindividual responses to interventions is often observed in randomized, controlled trials for obesity. To address the global epidemic of obesity and move toward more personalized treatment regimens, the global research community must come together to identify factors that may drive these heterogeneous responses to interventions. This project, called OBEDIS (OBEsity Diverse Interventions Sharing - focusing on dietary and other interventions), provides a set of European guidelines for a minimal set of variables to include in future clinical trials on obesity, regardless of the specific endpoints. Broad adoption of these guidelines will enable researchers to harmonize and merge data from multiple intervention studies, allowing stratification of patients according to precise phenotyping criteria which are measured using standardized methods. In this way, studies across Europe may be pooled for better prediction of individuals' responses to an intervention for obesity - ultimately leading to better patient care and improved obesity outcomes.

Integrated Analys of High-Fat Challenge-Induced Changes in Blood Cell Whole-Genome Gene Expression.

SCOPE: Several studies have examined the whole-genome gene expression response in blood cells to high-fat challenges with differing results. The study aims to identify consistently up- or downregulated genes and pathways in response to a high-fat challenge using several integration methods. METHODS AND RESULTS: Three studies measuring the gene expression response to a high-fat challenge in white blood cells are evaluated for common trends using several integration methods. Overlap in differentially expressed genes between separate studies is examined, p-values of each separate study are combined, and data are analyzed as one merged dataset. Differentially expressed genes and pathways are compared between these methods. Selecting genes differentially expressed in the three separate studies result in 67 differentially expressed genes, primarily involved in circadian pathways. Using the Fishers p-value method and a merged dataset analysis, changes in 1097 and 1182 genes, respectively, are observed. The upregulated genes upon a high-fat challenge are related to inflammation, whereas downregulated genes are related to unfolded protein response, protein processing, cholesterol biosynthesis, and translation. CONCLUSION: A general gene expression response to a high-fat challenge is identified. Compared to separate analyses, integrated analysis provides added value for the discovery of a consistent gene expression response.

Current and Future Nutritional Strategies to Modulate Inflammatory Dynamics in Metabolic Disorders.

Obesity, type 2 diabetes, and other metabolic disorders have a large impact on global health, especially in Western countries. An important hallmark of metabolic disorders is chronic low-grade inflammation. A key player in chronic low-grade inflammation is dysmetabolism, which is defined as the inability to keep homeostasis resulting in loss of lipid control, oxidative stress, inflammation, and insulin resistance. Although often not yet detectable in the circulation, chronic low-grade inflammation can be present in one or multiple organs. The response to a metabolic challenge containing lipids may magnify dysfunctionalities at the tissue level, causing an overflow of inflammatory markers into the circulation and hence allow detection of early low-grade inflammation. Here, we summarize the evidence of successful application of metabolic challenge tests in type 2 diabetes, metabolic syndrome, obesity, and unhealthy aging. We also review how metabolic challenge tests have been successfully applied to evaluate nutritional intervention effects, including an "anti-inflammatory" mixture, dark chocolate, whole grain wheat and overfeeding. Additionally, we elaborate on future strategies to (re)gain inflammatory flexibility. Through epigenetic and metabolic regulation, the inflammatory response may be trained by regular mild and metabolic triggers, which can be understood from the perspective of trained immunity, hormesis and pro-resolution. New strategies to optimize dynamics of inflammation may become available.

An Ontology to Standardize Research Output of Nutritional Epidemiology: From Paper-Based Standards to Linked Content.

BACKGROUND: The use of linked data in the Semantic Web is a promising approach to add value to nutrition research. An ontology, which defines the logical relationships between well-defined taxonomic terms, enables linking and harmonizing research output. To enable the description of domain-specific output in nutritional epidemiology, we propose the Ontology for Nutritional Epidemiology (ONE) according to authoritative guidance for nutritional epidemiology. METHODS: Firstly, a scoping review was conducted to identify existing ontology terms for reuse in ONE. Secondly, existing data standards and reporting guidelines for nutritional epidemiology were converted into an ontology. The terms used in the standards were summarized and listed separately in a taxonomic hierarchy. Thirdly, the ontologies of the nutritional epidemiologic standards, reporting guidelines, and the core concepts were gathered in ONE. Three case studies were included to illustrate potential applications: (i) annotation of existing manuscripts and data, (ii) ontology-based inference, and (iii) estimation of reporting completeness in a sample of nine manuscripts. RESULTS: Ontologies for "food and nutrition" (n = 37), "disease and specific population" (n = 100), "data description" (n = 21), "research description" (n = 35), and "supplementary (meta) data description" (n = 44) were reviewed and listed. ONE consists of 339 classes: 79 new classes to describe data and 24 new classes to describe the content of manuscripts. CONCLUSION: ONE is a resource to automate data integration, searching, and browsing, and can be used to assess reporting completeness in nutritional epidemiology.