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

被引:25
作者
Castellano-Escuder, Pol [1 ,2 ,3 ]
Gonzalez-Dominguez, Ral [1 ,3 ]
Wishart, David S. [4 ]
Andres-Lacueva, Cristina [1 ,3 ]
Sanchez-Pla, Alex [2 ,3 ]
机构
[1] Univ Barcelona, Dept Nutr Food Sci & Gastron, Biomarkers & Nutr & Food Metab Res Grp, Barcelona, Spain
[2] Univ Barcelona, Dept Genet Microbiol & Stat, Stat & Bioinformat Res Grp, Barcelona, Spain
[3] Inst Salud Carlos III, CIBERFES, Madrid, Spain
[4] Univ Alberta, Dept Biol Sci, Edmonton, AB T6G 2E8, Canada
来源
DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION | 2020年
关键词
WORKING;
D O I
10.1093/databa/baaa033
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
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.
引用
收藏
页数:8
相关论文
共 35 条
[1]   Statistical mechanics of complex networks [J].
Albert, R ;
Barabási, AL .
REVIEWS OF MODERN PHYSICS, 2002, 74 (01) :47-97
[2]   Gene Ontology: tool for the unification of biology [J].
Ashburner, M ;
Ball, CA ;
Blake, JA ;
Botstein, D ;
Butler, H ;
Cherry, JM ;
Davis, AP ;
Dolinski, K ;
Dwight, SS ;
Eppig, JT ;
Harris, MA ;
Hill, DP ;
Issel-Tarver, L ;
Kasarskis, A ;
Lewis, S ;
Matese, JC ;
Richardson, JE ;
Ringwald, M ;
Rubin, GM ;
Sherlock, G .
NATURE GENETICS, 2000, 25 (01) :25-29
[3]   ChEBI:: a database and ontology for chemical entities of biological interest [J].
Degtyarenko, Kirill ;
de Matos, Paula ;
Ennis, Marcus ;
Hastings, Janna ;
Zbinden, Martin ;
McNaught, Alan ;
Alcantara, Rafael ;
Darsow, Michael ;
Guedj, Mickael ;
Ashburner, Michael .
NUCLEIC ACIDS RESEARCH, 2008, 36 :D344-D350
[4]  
Djoumbou Feunang Yannick, 2016, J Cheminform, V8, P61
[5]   FoodOn: a harmonized food ontology to increase global food traceability, quality control and data integration [J].
Dooley, Damion M. ;
Griffiths, Emma J. ;
Gosal, Gurinder S. ;
Buttigieg, Pier L. ;
Hoehndorf, Robert ;
Lange, Matthew C. ;
Schriml, Lynn M. ;
Brinkman, Fiona S. L. ;
Hsiao, William W. L. .
NPJ SCIENCE OF FOOD, 2018, 2 (01) :1-10
[6]   Is the average shortest path length of gene set a reflection of their biological relatedness? [J].
Embar, Varsha ;
Handen, Adam ;
Ganapathiraju, Madhavi K. .
JOURNAL OF BIOINFORMATICS AND COMPUTATIONAL BIOLOGY, 2016, 14 (06)
[7]  
Erdos P., 1959, Publ. Math. (Debr.), V6, P290, DOI DOI 10.5486/PMD.1959.6.3-4.12
[8]   Biomarkers of food intake for nuts and vegetable oils: an extensive literature search [J].
Garcia-Aloy, Mar ;
Hulshof, Paul J. M. ;
Estruel-Amades, Sheila ;
Oste, Maryse C. J. ;
Lankinen, Maria ;
Geleijnse, Johanna M. ;
de Goede, Janette ;
Ulaszewska, Marynka ;
Mattivi, Fulvio ;
Bakker, Stephan J. L. ;
Schwab, Ursula ;
Andres-Lacueva, Cristina .
GENES AND NUTRITION, 2019, 14 (1)
[9]   Quantifying the human diet in the crosstalk between nutrition and health by multi-targeted metabolomics of food and microbiota-derived metabolites [J].
Gonzalez-Dominguez, Raul ;
Jauregui, Olga ;
Mena, Pedro ;
Hanhineva, Kati ;
Tinahones, Francisco Jose ;
Angelino, Donato ;
Andres-Lacueva, Cristina .
INTERNATIONAL JOURNAL OF OBESITY, 2020, 44 (12) :2372-2381
[10]   Quantitative Dietary Fingerprinting (QDF) -A Novel Tool for Comprehensive Dietary Assessment Based on Urinary Nutrimetabolomics [J].
Gonzalez-Dominguez, Raul ;
Urpi-Sarda, Mireia ;
Jauregui, Olga ;
Needs, Paul W. ;
Kroon, Paul A. ;
Andres-Lacueva, Cristina .
JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY, 2020, 68 (07) :1851-1861