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Inferred inheritance of MorbidMap genes without OMIM clinical synopsis.
Shakir, Aamina; Ripperger, Michael; Jiang, Zhijie; Wierenga, Klaas J.
Affiliation
  • Shakir A; Department of Pediatrics, Section of Genetics, University of Oklahoma College of Medicine, Oklahoma City, Oklahoma, USA.
  • Ripperger M; Department of Biomedical Informatics, Vanderbilt University, Nashville, Tennessee, USA.
  • Jiang Z; Center for Computational Studies, University of Miami, Miami, Florida, USA.
  • Wierenga KJ; Department of Pediatrics, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, USA.
Genet Med ; 20(4): 470-473, 2018 04.
Article in En | MEDLINE | ID: mdl-28837159
ABSTRACT
PurposeThe Genomic Oligoarray and SNP Array Evaluation Tool 3.0 matches candidate genes within regions of homozygosity with a patient's phenotype, by mining OMIM for gene entries that contain a Clinical Synopsis. However, the tool cannot identify genes/disorders whose OMIM entries lack a descriptor of the mode of (Mendelian) inheritance. This study aimed to improve the tool's diagnostic power by building a database of autosomal recessive diseases not diagnosable through OMIM.MethodsWe extracted a list of all genes in OMIM that produce disease phenotypes but lack Clinical Synopses or other statements of mode of inheritance. We then searched PubMed for literature regarding each gene in order to infer its inheritance pattern.ResultsWe analyzed 1,392 genes. Disorders associated with 372 genes were annotated as recessive and 430 as dominant. Autosomal genes were ranked from 1 to 3, with 3 indicating the strongest evidence behind the inferred mode of inheritance. Of 834 autosomal genes, 158 were ranked as 1, 228 as 2, and 448 as 3.ConclusionThe 372 genes associated with recessive disorders will be contributed to the SNP array tool, and the entire database to OMIM. We anticipate that these findings will be useful in rare disease diagnostics.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Computational Biology / Genetic Predisposition to Disease / Databases, Genetic / Inheritance Patterns / Genome-Wide Association Study Type of study: Prognostic_studies / Systematic_reviews Limits: Humans Language: En Journal: Genet Med Journal subject: GENETICA MEDICA Year: 2018 Type: Article Affiliation country: United States

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Computational Biology / Genetic Predisposition to Disease / Databases, Genetic / Inheritance Patterns / Genome-Wide Association Study Type of study: Prognostic_studies / Systematic_reviews Limits: Humans Language: En Journal: Genet Med Journal subject: GENETICA MEDICA Year: 2018 Type: Article Affiliation country: United States