Representation of rare diseases in health information systems: The orphanet approach to serve a wide range of end users

By Ana Rath, Annie Olry, Ferdinand Dhombres, Maja Milicic Brandt, Bruno Urbero, Ségolène Aymé. Human Mutation, 2012

351 citations recorded by the source corpus.

Rare disorders are scarcely represented in international classifications and therefore invisible in information systems. One of the major needs in health information systems and for research is to share and/or to integrate data coming from heterogeneous sources with diverse reference terminologies. ORPHANET (www.orpha.net) is a multilingual information portal on rare diseases and orphan drugs. Orphanet information system is supported by a relational database built around the concept of rare disorders. Representation of rare diseases in Orphanet encompasses levels of increasing complexity: lexical (multilingual terminology), nosological (multihierarchical classifications), relational (annotations—epidemiological data—and classes of objects—genes, manifestations, and orphan drugs—integrated in a relational database), and interoperational (semantic interoperability). Rare disorders are mapped to International Classification of Diseases (10th version), SNOMED CT, MeSH, MedDRA, and UMLS. Genes are cross‐referenced with HGNC, UniProt, OMIM, and Genatlas. A suite of tools allow for extraction of massive datasets giving different views that can be used in bioinformatics to answer complex questions, intended to serve the needs of researchers and the pharmaceutical industry in developing medicinal products for rare diseases. An ontology is under development. The Orphanet nomenclature is at the crossroads of scientific data repositories and of clinical terminology standards, and is suitable to be used as a standard terminology. Hum Mutat 33:803–808, 2012. © 2012 Wiley Periodicals, Inc.

Subfields: Artificial Intelligence, Genetics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/2cec9b6655a40a094232b2c2187767780d0649c5

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Citations in the corpus

The DisGeNET knowledge platform for disease genomics: 2019 update (2019, background): “DisGeNET integrates information from databases with a special focus on rare diseases (such as Orphanet) with data coming from other resources, significantly expanding the number of genes, variants and publications annotated to those diseases.”
Settling the score: variant prioritization and Mendelian disease (2017, background): “Similarly, Orphanet 111 , a European rare disease network, also distributes sets of rare conditions and lists of associated genes.”
Ensembl 2013 (2012, background): “For example, we provide up to date external database references to gene names from the HUGO Gene Nomenclature Committee (HGNC) (1), the Universal Protein Resource (UniProt) (2), Orphanet portal for rare diseases and orphan drugs (3), the Online Mendelian Inheritance in Man (OMIM) database (4), the R”
Next-generation diagnostics and disease-gene discovery with the Exomiser (2015, methodology): “…1000 Genomes Project 30 ; the Exome Variant Server (NHLBI GO Exome Sequencing Project 2013, http://evs.gs.washington.edu/EVS/); OMIM 39 ; Orphanet 40 ; the HPO 38 ; mouse phenotype data from the Mouse Genome Database 32 at the Mouse Genome Informatics resource and from the IMPC 33 ; zebrafish…”
The Monarch Initiative: an integrative data and analytic platform connecting phenotypes to genotypes across species (2016, methodology): “Actual PhenoGrid data is best viewed in the context of the web app at https://monarchinitiative.org/Orphanet:284993#compare.”
SymMap: an integrative database of traditional Chinese medicine enhanced by symptom mapping (2018, background): “Similarly, the disease component was also merged from two sources, namely OMIM (version 2017) (21) and Orphanet (version 2017) (22) databases.”
Ensembl 2014 (2013, background): “New data from ClinVar, Orphanet (26), the Developmental Disorder Genotype—Phenotype Database (DDG2P) from DECIPHER (27), dbGaP, Phencode and the MAGIC and GIANT consortiums have now been fully integrated into Ensembl (Figure 1B).”
DisGeNET: a comprehensive platform integrating information on human disease-associated genes and variants (2016, background): “The Comparative Toxicogenomics Database (CTD) that provides information about chemicals and genes, and their effect in human health and disease (3) - UniProt, a repository centred on protein sequence and function, that also include disease annotations from OMIM, and from expert curation of the scien”
ClinVar: public archive of interpretations of clinically relevant variants (2015, neutral): “Diseases and phenotypes may be submitted using several vocabularies, including Unified Medical Language System (UMLS) (7), Online Mendelian Inheritance in Man (OMIM) (8), Human Phenotype Ontology (HPO) (9) and Orphanet (10), which are mapped to common records in NCBI’s MedGen database (11).”
OMIM.org: leveraging knowledge across phenotype–gene relationships (2018, background): “The clinical features in the synopses are linked to controlled vocabularies such as the Unified Medical Language System (UMLS) (4), Human Phenotype Ontology (HPO) (5), International Classification of Diseases (ICD), Disease Ontology (DO) (6) and Orphanet (7) codes.”
The IUPHAR/BPS Guide to PHARMACOLOGY in 2016: towards curated quantitative interactions between 1300 protein targets and 6000 ligands (2015, background): “…Ontology (http://www.orphadata.org/cgi-bin/ inc/ordo orphanet.inc.php) terms, and now use standardised disease names that, wherever possible, are linked to synonyms (which may include more general names for specific subtypes) and entries on the Orphanet (26 ) and OMIM (http://omim.org/) websites.”
Ensembl 2017 (2016, background): “To facilitate data discovery and querying across our various input sources for phenotype, trait and disease annotations––including ClinVar (33), OMIM Morbid (34), the GWAS Catalog (35) and Orphanet (36)––we now map their descriptions onto the Experimental Factor Ontology (EFO) (37), Human Phenotype ”
Genetic variations and diseases in UniProtKB/Swiss-Prot: The ins and outs of expert manual curation (2014, background): “Orphanet maps these disorders to the International Classiﬁcation of Diseases (ICD-10), SNOMED CT, MeSH, MedDRA, and UMLS [Rath et al., 2012].”