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

Abstract Nutrition research can be conducted by using two complementary approaches: (i) traditional self-reporting methods or (ii) 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/.

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Sounding Heavy Precipitating Vertical Cloud Structures with Polarimetric Radio Occultations aboard PAZ

10.5194/egusphere-egu21-9405 ◽

2021 ◽

Author(s):

Ramon Padullés ◽

Estel Cardellach ◽

F. Joseph Turk ◽

Chi O. Ao ◽

Kuo Nung Wang ◽

...

Keyword(s):

Radio Occultation ◽

Deep Convection ◽

Heavy Precipitation ◽

Current Data ◽

Data Availability ◽

The Status ◽

Potential Applications ◽

Initial Hypothesis ◽

Forecast Models ◽

Electromagnetic Signals

The Radio Occultation and Heavy Precipitation (ROHP) experiment aboard the Spanish PAZ satellite was activated in May 2018 with the objective to demonstrate the Polarimetric Radio Occultation (PRO) concept for rain detection. This technique enhances standard RO by measuring GNSS signals at two orthogonal linear polarizations (H and V). Owing to hydrometeor asymmetry, electromagnetic signals propagating through regions of heavy precipitation would experience a differential phase delay expected to be measurable by the ROHP experiment. After 2+ years of operations, the initial hypothesis has been verified and the main scientific goals have been achieved. Soon after the activation of the experiment it became clear that PRO observables were sensitive to heavy precipitation, showing positive signatures correlated with the presence and intensity of precipitation. After a thorough on-orbit calibration, it has been demonstrated that the PAZ polarimetric observable can be used as a proxy for heavy precipitation. Furthermore, PRO measurements were shown to be sensitive to the horizontally oriented frozen hydrometeors present throughout the vertical cloud extent, providing valuable information on the vertical structure of precipitating clouds. In addition, PRO can retrieve standard thermodynamic RO products such as temperature, pressure, and water vapor. These products, provided with high vertical resolution, globally distributed and seamlessly over ocean and over land, make PRO observations a unique dataset, with potential applications ranging from the study of deep convection processes to the evaluation and diagnosis of NWP forecast models. In this presentation we will report on the status of the experiment and current data availability. We will also show the results of the sensitivity studies to heavy precipitation and frozen particles, performed using collocated observations between PAZ and GPM-DPR, GPM-GMI, and other radiometers from the GPM constellation, as well as a-priory information from the Cloudsat radar. Finally, we will address potential level-2 products we can expect from PAZ observations.

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Potential of food intake biomarkers in nutrition research

Proceedings of The Nutrition Society ◽

10.1017/s0029665120007053 ◽

2020 ◽

Vol 79 (4) ◽

pp. 487-497

Author(s):

Aoife E. McNamara ◽

Lorraine Brennan

Keyword(s):

Food Intake ◽

Metabolic Pathways ◽

Nutrient Intake ◽

Biomarker Discovery ◽

Dietary Habits ◽

Dietary Assessment ◽

Major Area ◽

Area Of Interest ◽

Nutrition Research ◽

Specific Food

The influence of dietary habits on health/disease is well-established. Accurate dietary assessment is essential to understand metabolic pathways/processes involved in this relationship. In recent years, biomarker discovery has become a major area of interest for improving dietary assessment. Well-established nutrient intake biomarkers exist; however, there is growing interest in identifying and using biomarkers for more accurate and objective measurements of food intake. Metabolomics has emerged as a key tool used for biomarker discovery, employing techniques such as NMR spectroscopy, or MS. To date, a number of putatively identified biomarkers were discovered for foods including meat, cruciferous vegetables and legumes. However, many of the results are associations only and lack the desired validation including dose–response studies. Food intake biomarkers can be employed to classify individuals into consumers/non-consumers of specific foods, or into dietary patterns. Food intake biomarkers can also play a role in correcting self-reported measurement error, thus improving dietary intake estimates. Quantification of food intake was previously performed for citrus (proline betaine), chicken (guanidoacetate) and grape (tartaric acid) intake. However, this area still requires more investigation and expansion to a range of foods. The present review will assess the current literature of identified specific food intake biomarkers, their validation and the variety of biomarker uses. Addressing the utility of biomarkers and highlighting gaps in this area is important to advance the field in the context of nutrition research.

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Metabolomics Meets Nutritional Epidemiology: Harnessing the Potential in Metabolomics Data

Metabolites ◽

10.3390/metabo11100709 ◽

2021 ◽

Vol 11 (10) ◽

pp. 709

Author(s):

Lorraine Brennan ◽

Frank B. Hu ◽

Qi Sun

Keyword(s):

Food Intake ◽

Systems Approach ◽

Metabolite Identification ◽

Population Level ◽

Nutritional Epidemiology ◽

Metabolomics Data ◽

Epidemiologic Evidence ◽

Physiological Processes ◽

Biomarker Validation ◽

The Impact

Traditionally, nutritional epidemiology is the study of the relationship between diet and health and disease in humans at the population level. Commonly, the exposure of interest is food intake. In recent years, nutritional epidemiology has moved from a “black box” approach to a systems approach where genomics, metabolomics and proteomics are providing novel insights into the interplay between diet and health. In this context, metabolomics is emerging as a key tool in nutritional epidemiology. The present review explores the use of metabolomics in nutritional epidemiology. In particular, it examines the role that food-intake biomarkers play in addressing the limitations of self-reported dietary intake data and the potential of using metabolite measurements in assessing the impact of diet on metabolic pathways and physiological processes. However, for full realisation of the potential of metabolomics in nutritional epidemiology, key challenges such as robust biomarker validation and novel methods for new metabolite identification need to be addressed. The synergy between traditional epidemiologic approaches and metabolomics will facilitate the translation of nutritional epidemiologic evidence to effective precision nutrition.

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Leptin Deficiency Induced by Fasting Impairs the Satiety Response to Cholecystokinin**This work was supported by grants from the NIH (DK-12829, DK-52989, and NS-32272) and by the Royalty Research Fund, the Diabetes Endocrinology Research Center, and the Clinical Nutrition Research Unit of the University of Washington.

Endocrinology ◽

10.1210/endo.141.12.7815 ◽

2000 ◽

Vol 141 (12) ◽

pp. 4442-4448 ◽

Cited By ~ 69

Author(s):

Julie E. McMinn ◽

Dana K. Sindelar ◽

Peter J. Havel ◽

Michael W. Schwartz

Keyword(s):

Food Intake ◽

Research Unit ◽

Research Fund ◽

Fed State ◽

Satiety Response ◽

Leptin Deficiency ◽

Nutrition Research ◽

Physiological Relevance ◽

The University ◽

Fasted Rats

Abstract Leptin administration potentiates the satiety response to signals such as cholecystokinin (CCK), that are released from the gut during a meal. To investigate the physiological relevance of this observation, we hypothesized that leptin deficiency, induced by fasting, attenuates the satiety response to CCK. To test this hypothesis, 48-h-fasted or fed rats were injected with ip saline or CCK. Fasting blunted the satiety response to 3.0 μg/kg CCK, such that 30-min food intake was suppressed by 65.1% (relative to saline-treated controls) in fasted rats vs. 85.9% in the fed state (P< 0.05). In a subsequent experiment, rats were divided into three groups: 1) vehicle/fed; 2) vehicle/fasted; and 3) leptin-replaced/fasted; and each group received 3.0 μg/kg ip CCK. As expected, the satiety response to CCK was attenuated by fasting in vehicle-treated rats (30-min food intake: vehicle/fed, 0.3 ± 0.1 g; vehicle/fasted, 1.7 ± 0.4 g; P < 0.01), and this effect was prevented by leptin replacement (0.7 ± 0.2 g, P < 0.05 vs. vehicle/fasted; P = not significant vs. vehicle/fed). To investigate whether elevated neuropeptide Y (NPY) signaling plays a role in the effect of leptin deficiency to impair the response to CCK, we measured the response to 3.0 μg/kg ip CCK after treatment with 7.5 μg intracerebroventricular NPY. We found that both CCK-induced satiety and its ability to increase c-Fos-like-immunoreactivity in key brainstem-feeding centers were attenuated by NPY pretreatment. We conclude that an attenuated response to meal-related satiety signals is triggered by leptin deficiency and may contribute to increased food intake.

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Personalized Metabolic Profile by Synergic Use of NMR and HRMS

Molecules ◽

10.3390/molecules26144167 ◽

2021 ◽

Vol 26 (14) ◽

pp. 4167

Author(s):

Greta Petrella ◽

Camilla Montesano ◽

Sara Lentini ◽

Giorgia Ciufolini ◽

Domitilla Vanni ◽

...

Keyword(s):

Metabolic Profile ◽

Missing Values ◽

Metabolite Identification ◽

Chronic Cystitis ◽

Normal Ranges ◽

New Strategy ◽

Potential Applications ◽

Minimum Number ◽

Analytical Standards ◽

Detailed Picture

A new strategy that takes advantage of the synergism between NMR and UHPLC–HRMS yields accurate concentrations of a high number of compounds in biofluids to delineate a personalized metabolic profile (SYNHMET). Metabolite identification and quantification by this method result in a higher accuracy compared to the use of the two techniques separately, even in urine, one of the most challenging biofluids to characterize due to its complexity and variability. We quantified a total of 165 metabolites in the urine of healthy subjects, patients with chronic cystitis, and patients with bladder cancer, with a minimum number of missing values. This result was achieved without the use of analytical standards and calibration curves. A patient’s personalized profile can be mapped out from the final dataset’s concentrations by comparing them with known normal ranges. This detailed picture has potential applications in clinical practice to monitor a patient’s health status and disease progression.

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Measurement Issues Related to Studies of Childhood Obesity: Assessment of Body Composition, Body Fat Distribution, Physical Activity, and Food Intake

PEDIATRICS ◽

10.1542/peds.101.s2.505 ◽

1998 ◽

Vol 101 (Supplement_2) ◽

pp. 505-518 ◽

Cited By ~ 6

Author(s):

Michael I. Goran

Keyword(s):

Physical Activity ◽

Body Composition ◽

Food Intake ◽

Body Fat ◽

Research Priorities ◽

Fat Distribution ◽

Body Fat Distribution ◽

Current Status ◽

Nutrition Research ◽

Distribution Energy

This article reviews the current status of various methodologies used in obesity and nutrition research in children, with particular emphasis on identifying priorities for research needs. The focus of the article is 1) to review methodologic aspects involved with measurement of body composition, body-fat distribution, energy expenditure and substrate use, physical activity, and food intake in children; and 2) to present an inventory of research priorities.

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Detailed Streetspace Modelling for Multiple Applications: Discussions on the Proposed CityGML 3.0 Transportation Model

ISPRS International Journal of Geo-Information ◽

10.3390/ijgi9100603 ◽

2020 ◽

Vol 9 (10) ◽

pp. 603

Author(s):

Christof Beil ◽

Roland Ruhdorfer ◽

Theresa Coduro ◽

Thomas H. Kolbe

Keyword(s):

Urban Areas ◽

Smart Cities ◽

Three Dimensional ◽

Data Availability ◽

Minor Role ◽

Extensive Literature ◽

Transportation Model ◽

Potential Applications ◽

A Minor ◽

City Models

In the context of smart cities and digital twins, three-dimensional semantic city models are increasingly used for the analyses of large urban areas. While the representation of buildings, terrain, and vegetation has become standard for most city models, detailed spatio-semantic representations of streetspace have played a minor role so far. This is now changing (1) because of data availability, and (2) because recent and emerging applications require having detailed data about the streetspace. The upcoming version 3.0 of the international standard CityGML provides a substantially updated data model regarding the transportation infrastructure, including the representation of the streetspace. However, there already exist a number of other standards and data formats dealing with the representation and exchange of streetspace data. Thus, based on an extensive literature review of potential applications as well as discussions and collaborations with relevant stakeholders, seven key modelling aspects of detailed streetspace models are identified. This allows a structured discussion of representational capabilities of the proposed CityGML3.0 Transportation Model with respect to these aspects and in comparison to the other standards. Subsequently, it is shown that CityGML3.0 meets most of these aspects and that streetspace models can be derived from various data sources and for different cities. Models generated compliant to the CityGML standard are immediately usable for a number of applications. This is demonstrated for some applications, such as land use management, solar potential analyses, and traffic and pedestrian simulations.

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

Nutrients ◽

10.3390/nu11061300 ◽

2019 ◽

Vol 11 (6) ◽

pp. 1300 ◽

Cited By ~ 3

Author(s):

Chen Yang ◽

Henry Ambayo ◽

Bernard De Baets ◽

Patrick Kolsteren ◽

Nattapon Thanintorn ◽

...

Keyword(s):

Research Output ◽

Reporting Guidelines ◽

Nutritional Epidemiology ◽

Specific Population ◽

Data Description ◽

Domain Specific ◽

Nutrition Research ◽

Food And Nutrition ◽

Core Concepts ◽

Potential Applications

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.

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Use of Orbital LIDAR in the Brazilian Cerrado Biome: Potential Applications and Data Availability

Remote Sensing ◽

10.3390/rs3102187 ◽

2011 ◽

Vol 3 (10) ◽

pp. 2187-2206 ◽

Cited By ~ 4

Author(s):

Laerte Guimarães Ferreira ◽

Timothy J. Urban ◽

Amy Neuenschawander ◽

Fernando Moreira de Araújo

Keyword(s):

Data Availability ◽

Brazilian Cerrado ◽

Cerrado Biome ◽

Potential Applications

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The Potential of Multi-Biomarker Panels in Nutrition Research: Total Fruit Intake as an Example

Frontiers in Nutrition ◽

10.3389/fnut.2020.577720 ◽

2021 ◽

Vol 7 ◽

Author(s):

Aoife E. McNamara ◽

Janette Walton ◽

Albert Flynn ◽

Anne P. Nugent ◽

Breige A. McNulty ◽

...

Keyword(s):

Food Intake ◽

Intervention Study ◽

Dietary Habits ◽

Cross Sectional Study ◽

Fruit Intake ◽

Sectional Study ◽

Cross Sectional ◽

Biomarker Panel ◽

Nutrition Research ◽

The Cross

Dietary and food intake biomarkers offer the potential of improving the accuracy of dietary assessment. An extensive range of putative intake biomarkers of commonly consumed foods have been identified to date. As the field of food intake biomarkers progresses toward solving the complexities of dietary habits, combining biomarkers associated with single foods or food groups may be required. The objective of this work was to examine the ability of a multi-biomarker panel to classify individuals into categories of fruit intake. Biomarker data was measured using 1H NMR spectroscopy in two studies: (1) An intervention study where varying amounts of fruit was consumed and (2) the National Adult Nutrition Survey (NANS). Using data from an intervention study a biomarker panel (Proline betaine, Hippurate, and Xylose) was constructed from three urinary biomarker concentrations. Biomarker cut-off values for three categories of fruit intake were developed. The biomarker sum cut-offs were ≤ 4.766, 4.766–5.976, >5.976 μM/mOsm/kg for <100, 101–160, and >160 g fruit intake. The ability of the biomarker sum to classify individuals into categories of fruit intake was examined in the cross-sectional study (NANS) (N = 565). Examination of results in the cross-sectional study revealed excellent agreement with self-reported intake: a similar number of participants were ranked into each category of fruit intake. The work illustrates the potential of multi-biomarker panels and paves the way forward for further development in the field. The use of such panels may be key to distinguishing foods and adding specificity to the predictions of food intake.

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