Literature DB >> 33473205

The role of phenotype-based search approaches using public online databases in diagnostics of Mendelian disorders.

Avi Fellner1,2, Noa Ruhrman-Shahar3,4, Naama Orenstein4,5, Gabriel Lidzbarsky3, Alan R Shuldiner6, Claudia Gonzaga-Jauregui6, Hadar Brown-Shalev3, Ofir Hagari-Bechar3, Lily Bazak3, Lina Basel-Salmon3,4,7.   

Abstract

PURPOSE: To investigate the effectiveness of phenotype-based search approaches using publicly available online databases.
METHODS: We included consecutively solved cases from our exome database. For each case, the combination of Human Phenotype Ontology terms reported by the referring clinician was used to perform a search in three commonly used databases: OMIM (first 300 results), Phenolyzer (first 300 results), and Mendelian (all 100 results).
RESULTS: One hundred cases were included (43 females; mean age: 10 years). The actual molecular diagnosis identified through exome sequencing was not included in the search results of any of the queried databases in 33% of cases. In 85% of cases it was not found within the top five search results. When included, its median rank was 61 (range: 1-295), 21 (1-270), and 29 (1-92) in OMIM, Phenolyzer and Mendelian, respectively.
CONCLUSION: This study demonstrates that, in most cases, phenotype-based search approaches using public online databases is ineffective in providing a probable diagnosis for Mendelian conditions. Genotype-first approach through molecular-guided diagnostics with backward phenotyping may be a more appropriate approach for these disorders, unless a specific diagnosis is considered a priori based on highly unique phenotypic features or a specific facial gestalt.

Entities:  

Mesh:

Year:  2021        PMID: 33473205     DOI: 10.1038/s41436-020-01085-7

Source DB:  PubMed          Journal:  Genet Med        ISSN: 1098-3600            Impact factor:   8.822


  2 in total

1.  Encoding Clinical Data with the Human Phenotype Ontology for Computational Differential Diagnostics.

Authors:  Sebastian Köhler; N Christine Øien; Orion J Buske; Tudor Groza; Julius O B Jacobsen; Craig McNamara; Nicole Vasilevsky; Leigh C Carmody; J P Gourdine; Michael Gargano; Julie A McMurry; Daniel Danis; Christopher J Mungall; Damian Smedley; Melissa Haendel; Peter N Robinson
Journal:  Curr Protoc Hum Genet       Date:  2019-09

Review 2.  Precision Medicine for Continuing Phenotype Expansion of Human Genetic Diseases.

Authors:  Hui Yu; Victor Wei Zhang
Journal:  Biomed Res Int       Date:  2015-06-07       Impact factor: 3.411

  2 in total
  2 in total

1.  PhenoApt leverages clinical expertise to prioritize candidate genes via machine learning.

Authors:  Zefu Chen; Yu Zheng; Yongxin Yang; Yingzhao Huang; Sen Zhao; Hengqiang Zhao; Chenxi Yu; Xiying Dong; Yuanqiang Zhang; Lianlei Wang; Zhengye Zhao; Shengru Wang; Yang Yang; Yue Ming; Jianzhong Su; Guixing Qiu; Zhihong Wu; Terry Jianguo Zhang; Nan Wu
Journal:  Am J Hum Genet       Date:  2022-01-20       Impact factor: 11.043

Review 2.  Intellectual disability genomics: current state, pitfalls and future challenges.

Authors:  Nuno Maia; Maria João Nabais Sá; Manuel Melo-Pires; Arjan P M de Brouwer; Paula Jorge
Journal:  BMC Genomics       Date:  2021-12-20       Impact factor: 3.969

  2 in total

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