PhenoDis: a comprehensive database for phenotypic characterization of rare cardiac diseases.
PhenoDis: a comprehensive database for phenotypic characterization of rare cardiac diseases.
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平球：稀有心脏疾病表型表征的综合数据库。
DOI：
10.1186/s13023-018-0765-y
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发表时间：
2018-01-25
影响因子：
3.7
通讯作者：
Ruepp A
中科院分区：
文献类型：
--
作者：
Adler A;Kirchmeier P;Reinhard J;Brauner B;Dunger I;Fobo G;Frishman G;Montrone C;Mewes HW;Arnold M;Ruepp A
彻底注释的数据资源是精准医学领域疾病表型依赖性分析和诊断的关键要求。最近的工作表明，人类表型数据的整理和系统注释可以显着提高遗传性疾病解释的质量和选择性。因此，我们开发了 PhenoDis，这是一个全面的手动注释数据库，提供有关罕见心脏病的症状、遗传和印记信息。 PhenoDis 包括来自 Orphanet 的 214 种罕见心脏病和来自 OMIM 的 94 种罕见心脏病。为了疾病的表型特征，我们利用生物医学文献中的文章对疾病进行了手动注释。疾病症状的详细描述需要使用人类表型本体 (HPO) 中的 2247 个不同术语。 PhenoDis 列出的疾病通常涵盖广泛的症状，其中 28% 来自“心血管异常”分支，其他来自神经系统（11.5%）和新陈代谢（6%）等领域。我们收集了有关各种疾病的症状频率以及疾病相关基因和印记数据的广泛信息。对患者研究中大量症状的分析表明，大多数注释症状 (71%) 在特定疾病的不到一半的患者中被发现。症状的全面和系统的表征（包括其频率）是基于计算机的疾病和引起疾病的遗传变异预测的关键先决条件。为此，PhenoDis 为一组完整的罕见疾病提供了深入注释，包括 ClinVar 中列出的 206 种疾病的致病性和可能致病性遗传变异信息。我们将所有结果集成到在线数据库 (http://mips.helmholtz-muenchen.de/phenodis/) 中，并提供多个搜索选项，并提供完整的数据集供下载。 PhenoDis 提供了一套全面的手动注释的罕见心脏病，可通过决策支持系统和表型驱动策略来实现疾病预测的计算方法，以识别致病基因。
Thoroughly 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. PhenoDis 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. PhenoDis 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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影响因子：
27.4
作者：
van den Hoogen, Frank;Khanna, Dinesh;Pope, Janet E.
通讯作者：
Pope, Janet E.
影响因子：
14.9
作者：
Köhler S;Doelken SC;Mungall CJ;Bauer S;Firth HV;Bailleul-Forestier I;Black GC;Brown DL;Brudno M;Campbell J;FitzPatrick DR;Eppig JT;Jackson AP;Freson K;Girdea M;Helbig I;Hurst JA;Jähn J;Jackson LG;Kelly AM;Ledbetter DH;Mansour S;Martin CL;Moss C;Mumford A;Ouwehand WH;Park SM;Riggs ER;Scott RH;Sisodiya S;Van Vooren S;Wapner RJ;Wilkie AO;Wright CF;Vulto-van Silfhout AT;de Leeuw N;de Vries BB;Washingthon NL;Smith CL;Westerfield M;Schofield P;Ruef BJ;Gkoutos GV;Haendel M;Smedley D;Lewis SE;Robinson PN
通讯作者：
Robinson PN
影响因子：
5.5
作者：
Makino, Katsunari;Jinnin, Masatoshi;Ihn, Hironobu
通讯作者：
Ihn, Hironobu
影响因子：
15.8
作者：
Piwek L;Ellis DA;Andrews S;Joinson A
通讯作者：
Joinson A
影响因子：
12.3
作者：
Lechner M;Höhn V;Brauner B;Dunger I;Fobo G;Frishman G;Montrone C;Kastenmüller G;Waegele B;Ruepp A
通讯作者：
Ruepp A