ArticleOrphanet journal of rare diseases2018
PhenoDis: a comprehensive database for phenotypic characterization of rare cardiac diseases.
Article in Orphanet journal of rare diseases, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 24 citations in OpenAlex.
- A custom phenotypic profile for Fanconi anemia: Addressing gaps in existing disease annotations.medRxiv : the preprint server for health sciences · 2026Article
- Bottlenecks in advancing and applying multiomic data integration-common data resources as rate-limiting drivers-the high-impact use case of atherosclerotic cardiovascular disease.Briefings in bioinformatics · 2025Review
- CardioGraph: a platform to study variations associated with familiar cardiopathies.BMC medical informatics and decision making · 2024Article
- Prevalence of comorbidities in individuals with neurodevelopmental disorders from the aggregated phenomics data of 51,227 pediatric individuals.Nature medicine · 2024Article
- DiSMVC: a multi-view graph collaborative learning framework for measuring disease similarity.Bioinformatics (Oxford, England) · 2024Article
- Functional genomics provide key insights to improve the diagnostic yield of hereditary ataxia.Brain : a journal of neurology · 2023Article
- Rare diseases in Tanzania: a National Call for Action to address policy and urgent needs of individuals with rare diseases.Orphanet journal of rare diseases · 2022Article
- Data Sharing Under the General Data Protection Regulation: Time to Harmonize Law and Research Ethics?Hypertension (Dallas, Tex. : 1979) · 2021Review
- CancerLivER: a database of liver cancer gene expression resources and biomarkers.Database : the journal of biological databases and curation · 2020Article
- Expansion of the Human Phenotype Ontology (HPO) knowledge base and resources.Nucleic acids research · 2019Article
- The utility of phenomics in diagnosis of inherited metabolic disorders.Clinical medicine (London, England) · 2019Review
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Authors and funding
11 authors at 2 institutions in 1 country.
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Abstract
backgroundThoroughly annotated data resources are a key requirement in phenotype dependent analysis and diagnosis of diseases in the area of precision medicine. Recent work has shown that curation and systematic annotation of human phenome data can significantly improve the quality and selectivity for the interpretation of inherited diseases. We have therefore developed PhenoDis, a comprehensive, manually annotated database providing symptomatic, genetic and imprinting information about rare cardiac diseases.
resultsPhenoDis includes 214 rare cardiac diseases from Orphanet and 94 more from OMIM. For phenotypic characterization of the diseases, we performed manual annotation of diseases with articles from the biomedical literature. Detailed description of disease symptoms required the use of 2247 different terms from the Human Phenotype Ontology (HPO). Diseases listed in PhenoDis frequently cover a broad spectrum of symptoms with 28% from the branch of 'cardiovascular abnormality' and others from areas such as neurological (11.5%) and metabolism (6%). We collected extensive information on the frequency of symptoms in respective diseases as well as on disease-associated genes and imprinting data. The analysis of the abundance of symptoms in patient studies revealed that most of the annotated symptoms (71%) are found in less than half of the patients of a particular disease. Comprehensive and systematic characterization of symptoms including their frequency is a pivotal prerequisite for computer based prediction of diseases and disease causing genetic variants. To this end, PhenoDis provides in-depth annotation for a complete group of rare diseases, including information on pathogenic and likely pathogenic genetic variants for 206 diseases as listed in ClinVar. We integrated all results in an online database ( http://mips.helmholtz-muenchen.de/phenodis/ ) with multiple search options and provide the complete dataset for download.
conclusionPhenoDis provides a comprehensive set of manually annotated rare cardiac diseases that enables computational approaches for disease prediction via decision support systems and phenotype-driven strategies for the identification of disease causing genes.
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