| Literature DB >> 35811979 |
Liliana Andrés-Hernández1, Kai Blumberg2, Ramona L Walls2,3, Damion Dooley4, Ramil Mauleon1, Matthew Lange5, Magalie Weber6, Lauren Chan7, Adnan Malik8, Anders Møller9, Jayne Ireland9, Lucia Segovia10, Xuhuiqun Zhang11, Britt Burton-Freeman11, Paul Magelli12, Andrew Schriever12, Shavawn M Forester13, Lei Liu1, Graham J King1,14.
Abstract
Informed policy and decision-making for food systems, nutritional security, and global health would benefit from standardization and comparison of food composition data, spanning production to consumption. To address this challenge, we present a formal controlled vocabulary of terms, definitions, and relationships within the Compositional Dietary Nutrition Ontology (CDNO, www.cdno.info) that enables description of nutritional attributes for material entities contributing to the human diet. We demonstrate how ongoing community development of CDNO classes can harmonize trans-disciplinary approaches for describing nutritional components from food production to diet.Entities:
Keywords: FAIR data; dietary composition; food composition; human health; knowledge representation; nutritional security; ontologies
Year: 2022 PMID: 35811979 PMCID: PMC9265659 DOI: 10.3389/fnut.2022.928837
Source DB: PubMed Journal: Front Nutr ISSN: 2296-861X
Figure 1Compositional Dietary Nutrition Ontology (CDNO) class relationships and interaction with FoodON. (A) Relationships and associations between major ontology classes. Solid symbols (circles and triangle) represent class hierarchies that may be used individually or in combination by curators to annotate datasets in the continuum between agriculture and health. Many terms within the ‘dietary nutritional component’ (blue solid circle) hierarchy are imported and reused from ChEBI (purple arrow). Grey arrows indicate relationships between independent classes that may in future be adopted where evidence is available. The ‘dietary nutritional component’ [CDNO:0000001] provides a framework where terms are reused in the ‘concentration of dietary nutritional component in material entity’ [CDNO:0200001] class hierarchy (green solid circle). A distinction is made between the latter class and that required an independent ‘analytical methods' class (Figure 1, blue triangle) to provide vocabulary to describe analytical methods where terms would be used in combination to represent relevant metadata (Figure 1, green dotted arrow). The ‘dietary material physical attribute’ class [CDNO:0400001] (cream solid circle) provides structured subclasses to describe properties that may inhere either in a food material or be associated with a specific ‘dietary nutritional component’ [CDNO:0000001]. The ‘nutritional functional attribute’ [CDNO:0300001] class hierarchy (pink solid circle) allows the description of quantifiable functional attributes that may be associated with or inhere in terms from the ‘dietary nutritional component’ [CDNO:0000001] class hierarchy. Where evidence is available, terms from this class may also be associated with a human dietary role (Figure 1, pink dotted line). The ‘human dietary role’ [CDNO:0500001] class (orange solid circle) includes structured terms representing biological roles that may be assigned to a specific ‘dietary nutritional component’ [CDNO:0000001], where it is left to experts and data curators to assign supporting evidence that indicates a function defined at the levels of molecular interaction, cellular process or physiological role. (B) The interaction between CDNO and FoodOn is shown with a purple double arrow. FoodOn reuses ~500 terms from the CDNO ‘dietary nutritional component’ [CDNO:0000001] hierarchy within the ‘chemical food component’ [FOODON:03411041] hierarchy (cyan solid circle). The FoodOn ‘food product by organism’ [FOODON:00002381] class (olive solid circle) is not directly associated with CDNO classes, but can be used to describe a food source. These represent independent classes that may be combined and used in a relational, RDF or graph database by data curators to annotate and perform information extraction based on particular evidence that may require annotation.
Figure 2Vocabularies for annotating the food to health continuum. Schematic of proposed workflows using ontology classes to associate component concentration with independent concepts of nutritional attribute and dietary role. In data curation, each assignment requires identification of supporting evidence. Adoption of common vocabularies in diverse data repositories would facilitate data mining and inference. The FoodOn organismal source (olive solid circle) is used to filter available datasets, alongside the nutritional component terms (green solid circle). The structured vocabulary and definitions within the ‘nutritional functional attribute' class (pink solid circle) and the ‘human dietary role' class (orange solid circle), will then be available to represent concepts associated with one or more nutritional components, where a domain specialist has identified sufficient supporting evidence. These terms may be mapped and reused from existing OBO ontologies such as: the Experimental Factor Ontology (EFO) (42), the Human Phenotype Ontology (HP) (43), the Ontology for Biomedical Investigations (OBI) and the Ontology of Biological Attributes (OBA) (44).