FOBI: An ontology to represent food intake data and associate it with metabolomic data

Nutrition research can be conducted by using two complementary approaches: 1) traditional self-reporting methods or 2) via metabolomics techniques to analyze food intake biomarkers in biofluids. However, the complexity and heterogeneity of these two very different types of data often hinder their analysis and integration. To manage this challenge, we have developed a novel ontology that describes food and their associated metabolite entities in a hierarchical way. This ontology uses a formal naming system, category definitions, properties and relations between both types of data. The ontology presented is called FOBI (Food-Biomarker Ontology) and it is composed of two interconnected sub-ontologies. One is a 'Food Ontology' consisting of raw foods and multi-component foods while the second is a 'Biomarker Ontology' containing food intake biomarkers classified by their chemical classes. These two sub-ontologies are conceptually independent but interconnected by different properties. This allows data and information regarding foods and food biomarkers to be visualized in a bidirectional way, going from metabolomics to nutritional data or vice versa. Potential applications of this ontology include the annotation of foods and biomarkers using a well-defined and consistent nomenclature, the standardized reporting of metabolomics workflows (e.g. metabolite identification, experimental design), or the application of different enrichment analysis approaches to analyze nutrimetabolomic data. Availability: FOBI is freely available in both OWL (Web Ontology Language) and OBO (Open Biomedical Ontologies) formats at the project's Github repository (https://github.com/pcastellanoescuder/FoodBiomarkerOntology) and FOBI visualization tool is available in https://polcastellano.shinyapps.io/FOBI_Visualization_Tool/

POMAShiny: A user-friendly web-based workflow for metabolomics and proteomics data analysis

Metabolomics and proteomics, like other omics domains, usually face a data mining challenge in providing an understandable output to advance in biomarker discovery and precision medicine. Often, statistical analysis is one of the most difficult challenges and it is critical in the subsequent biological interpretation of the results. Because of this, combined with the computational programming skills needed for this type of analysis, several bioinformatic tools aimed at simplifying metabolomics and proteomics data analysis have emerged. However, sometimes the analysis is still limited to a few hidebound statistical methods and to data sets with limited flexibility. POMAShiny is a web-based tool that provides a structured, flexible and user-friendly workflow for the visualization, exploration and statistical analysis of metabolomics and proteomics data. This tool integrates several statistical methods, some of them widely used in other types of omics, and it is based on the POMA R/Bioconductor package, which increases the reproducibility and flexibility of analyses outside the web environment. POMAShiny and POMA are both freely available at https://github.com/nutrimetabolomics/POMAShiny and https://github.com/nutrimetabolomics/POMA, respectively

A Polyphenol-Rich Diet Increases the Gut Microbiota Metabolite Indole 3-Propionic Acid in Older Adults with Preserved Kidney Function

Scope: Dietary polyphenols can alter the gut microbiota (GM) and promote the production of bioactive metabolites. Several indoles result of GM metabolism of dietary tryptophan have been associated with intestinal barrier integrity. Our aim is to study the changes in GM-derived indoles during a polyphenol-rich (PR) diet intervention in older adults. Methods and results: Randomized, controlled, crossover trial in adults ≥ 60 years living in a residential care facility during an 8-week PR versus control diet (n = 51). Seven GM-tryptophan metabolites are measured in serum, and metataxonomic analysis of GM is performed on fecal samples. Exploratory subgroup analyses are performed based on renal function (RF). The PR-diet significantly increases serum indole 3-propionic acid (IPA) in subjects with normal RF, but not in subjects with impaired RF. Other GM-tryptophan metabolites are not affected. Comparison of baseline GM composition shows shifts in Bacteroidales order members as well as higher abundance of Clostridiales in participants with normal RF. During the trial, variations of IPA are associated with changes in C-reactive protein (β = 0.32, p = 0.010) and GM, particularly with the Clostridiales (r = 0.35, p < 0.001) and Enterobacteriales (r = -0.15, p < 0.05) orders. Conclusion: A PR diet increases the serum concentration of IPA in older adults with normal RF. Our findings may be important when defining appropriate dietary interventions for older adults

Obo foundry food ontology interconnectivity

Since its creation in 2016, the FoodOn ontology has become an interconnected partner in various academic and government inter-agency ontology work spanning agricultural and public health domains. This paper examines existing and potential data interoperability capabilities arising from FoodOn and partner food-related ontologies belonging to the encyclopedic Open Biological and Biomedical Ontology Foundry (OBO) vocabulary platform, and how research organizations and industry might utilize them for their own operations or for data exchange. Projects are seeking standardized vocabulary across all direct food supply activities ranging from agricultural production, harvesting, preparation, food processing, marketing, distribution and consumption, as well as indirectly, within health, economic, food security and sustainability analysis and reporting tools. To satisfy this demand and provide data requires establishing domain specific ontologies whose curators coordinate closely to produce recommended patterns for food system vocabulary

Apolipoprotein E and sex modulate fatty acid metabolism in a prospective observational study of cognitive decline

Background: Fatty acids play prominent roles in brain function as they participate in structural, metabolic and signaling processes. The homeostasis of fatty acids and related pathways is known to be impaired in cognitive decline and dementia, but the relationship between these metabolic disturbances and common risk factors, namely the ɛ4 allele of the apolipoprotein E (ApoE-ɛ4) gene and sex, remains elusive. Methods: In order to investigate early alterations associated with cognitive decline in the fatty acid-related serum metabolome, we here applied targeted metabolomics analysis on a nested case-control study (N=368), part of a prospective population cohort on dementia. Results: When considering the entire study population, circulating levels of free fatty acids, acyl-carnitines and pantothenic acid were found to be increased among those participants who had greater odds of cognitive decline over a 12-year follow-up. Interestingly, stratified analyses indicated that these metabolomic alterations were specific for ApoE-ɛ4 non-carriers and women. Conclusions: Altogether, our results highlight that the regulation of fatty acids and related metabolic pathways during ageing and cognitive decline depends on complex inter-relationships between the ApoE-ε4 genotype and sex. A better understanding of the ApoE-ɛ4 and sex dependent modulation of metabolism is essential to elucidate the individual variability in the onset of cognitive decline, which would help develop personalized therapeutic approaches

Assessing Adherence to Healthy Dietary Habits Through the Urinary Food Metabolome:Results From a European Two-Center Study

BACKGROUND: Diet is one of the most important modifiable lifestyle factors in human health and in chronic disease prevention. Thus, accurate dietary assessment is essential for reliably evaluating adherence to healthy habits. OBJECTIVES: The aim of this study was to identify urinary metabolites that could serve as robust biomarkers of diet quality, as assessed through the Alternative Healthy Eating Index (AHEI-2010). DESIGN: We set up two-center samples of 160 healthy volunteers, aged between 25 and 50, living as a couple or family, with repeated urine sampling and dietary assessment at baseline, and 6 and 12 months over a year. Urine samples were subjected to large-scale metabolomics analysis for comprehensive quantitative characterization of the food-related metabolome. Then, lasso regularized regression analysis and limma univariate analysis were applied to identify those metabolites associated with the AHEI-2010, and to investigate the reproducibility of these associations over time. RESULTS: Several polyphenol microbial metabolites were found to be positively associated with the AHEI-2010 score; urinary enterolactone glucuronide showed a reproducible association at the three study time points [false discovery rate (FDR): 0.016, 0.014, 0.016]. Furthermore, other associations were found between the AHEI-2010 and various metabolites related to the intake of coffee, red meat and fish, whereas other polyphenol phase II metabolites were associated with higher AHEI-2010 scores at one of the three time points investigated (FDR < 0.05 or β ≠ 0). CONCLUSION: We have demonstrated that urinary metabolites, and particularly microbiota-derived metabolites, could serve as reliable indicators of adherence to healthy dietary habits. CLINICAL TRAIL REGISTRATION: www.ClinicalTrials.gov, Identifier: NCT03169088

Exposing and Overcoming Limitations of Clinical Laboratory Tests in COVID-19 by Adding Immunological Parameters; A Retrospective Cohort Analysis and Pilot Study

BackgroundTwo years since the onset of the COVID-19 pandemic no predictive algorithm has been generally adopted for clinical management and in most algorithms the contribution of laboratory variables is limited. ObjectivesTo measure the predictive performance of currently used clinical laboratory tests alone or combined with clinical variables and explore the predictive power of immunological tests adequate for clinical laboratories. Methods: Data from 2,600 COVID-19 patients of the first wave of the pandemic in the Barcelona area (exploratory cohort of 1,579, validation cohorts of 598 and 423 patients) including clinical parameters and laboratory tests were retrospectively collected. 28-day survival and maximal severity were the main outcomes considered in the multiparametric classical and machine learning statistical analysis. A pilot study was conducted in two subgroups (n=74 and n=41) measuring 17 cytokines and 27 lymphocyte phenotypes respectively. Findings1) Despite a strong association of clinical and laboratory variables with the outcomes in classical pairwise analysis, the contribution of laboratory tests to the combined prediction power was limited by redundancy. Laboratory variables reflected only two types of processes: inflammation and organ damage but none reflected the immune response, one major determinant of prognosis. 2) Eight of the thirty variables: age, comorbidity index, oxygen saturation to fraction of inspired oxygen ratio, neutrophil-lymphocyte ratio, C-reactive protein, aspartate aminotransferase/alanine aminotransferase ratio, fibrinogen, and glomerular filtration rate captured most of the combined statistical predictive power. 3) The interpretation of clinical and laboratory variables was moderately improved by grouping them in two categories i.e., inflammation related biomarkers and organ damage related biomarkers; Age and organ damage-related biomarker tests were the best predictors of survival, and inflammatory-related ones were the best predictors of severity. 4) The pilot study identified immunological tests (CXCL10, IL-6, IL-1RA and CCL2), that performed better than most currently used laboratory tests. ConclusionsLaboratory tests for clinical management of COVID 19 patients are valuable but limited predictors due to redundancy; this limitation could be overcome by adding immunological tests with independent predictive power. Understanding the limitations of tests in use would improve their interpretation and simplify clinical management but a systematic search for better immunological biomarkers is urgent and feasible

Statistical methods for intake prediction and biological significance analysis in nutrimetabolomic studies

[eng] This thesis is the product of three and a half years working on the complex world of metabolomics and nutrition. All the work presented here is focussed on the problems arising from associating and integrating metabolomics data with nutritional or dietary data. This issue has been approached using both observational and interventional studies and from a mainly bioinformatic point of view, proposing different methods and tools to reduce the complexity of nutrimetabolomics data analysis. Thus, this work consists of four chapters divided into three parts, in addition to a summary of the content of the entire thesis in Catalan, the references, and the appendices. The first part consists of a global introduction, where the fundamental concepts needed for the correct understanding of the thesis are reviewed, as well as basic concepts about metabolomics and nutrition, the state of the art of the nutrimetabolomics field, and the fundamentals of biological significance analyses, among others. Then, this first part ends with a brief definition of the objectives of this work. In the second part, the results of this thesis are carefully presented and discussed. The results are presented in a compact format, with each section being a summary of a scientific publication. These results include the develompent of an ontology that defines the relationships between dietary metabolites and foods, the development of an open source tool for metabolomics data analysis, the development of an open source tool for nutrimetabolomics enrichment analysis, other open source tools developed in the context of this work, and a section with different publications where the methods and tools developed have been applied. Then, all these individual results are discussed together, providing a global and unified context where all the developments of this thesis are related. Lastly, the third part of this thesis presents the conclusions, contextualizing all the obtained results within the main objective of the thesis: contribute to the improvement of the integration and interpretation of nutrimetabolomics data. Additionally, in the appendices, the published results and some extra information used in carrying out this research are presented. Finally, although this thesis is made up of contents from the fields of metabolomics, nutrition, bioinformatics and biostatistics, it has been written for a wide scientific audience, trying to be as comprehensible as possible for any profile of researchers, avoiding unnecessary complexities and always following the transversal objective of the thesis. I hope you find it useful but, above all, that you enjoy reading it

Crosstalk among intestinal barrier, gut microbiota and serum metabolome after a polyphenol-rich diet in older subjects with leaky gut: The MaPLE trial

Background &aim: The MaPLE study was a randomized, controlled, crossover trial involving adults 60 y.o. (n ¼ 51) living in a residential care facility during an 8-week polyphenol-rich (PR)-diet. Results from the MaPLE trial showed that the PR-diet reduced the intestinal permeability (IP) in older adults by inducing changes to gut microbiota (GM). The present work aimed at studying the changes in serum metabolome in the MaPLE trial, as a further necessary step to depict the complex crosstalk between dietary polyphenols, GM, and intestinal barrier. Methods: Serum metabolome was monitored using a semi-targeted UHPLC-MS/MS analysis. Metataxonomic analysis (16S rRNA gene profiling) of GM was performed on faecal samples. Clinical characteristics and serum levels of the IP marker zonulin were linked to GM and metabolomics data in a multi-omics network. Results: Compared to the control diet, the PR-diet increased serum metabolites related to polyphenols and methylxanthine intake. Theobromine and methylxanthines, derived from cocoa and/or green tea, were positively correlated with butyrate-producing bacteria (the order Clostridiales and the genera Roseburia, Butyricicoccus and Faecalibacterium) and inversely with zonulin. A direct correlation between polyphenol metabolites hydroxyphenylpropionic acid-sulfate, 2-methylpyrogallol-sulfate and catecholsulfate with Butyricicoccus was also observed, while hydroxyphenylpropionic acid-sulfate and 2- methylpyrogallol-sulfate negatively correlated with Methanobrevibacter. The multi-omics network indicated that participant's age, baseline zonulin levels, and changes in Porphyromonadaceae abundance were the main factors driving the effects of a PR-diet on zonulin. Conclusion: Overall, these results reveal the complex relationships among polyphenols consumption, intestinal permeability, and GM composition in older adults, and they may be important when setting personalized dietary interventions for older adults. Trial registration number: ISRCTN10214981. © 2021 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY licens