Department of Pediatrics, Section of Genetics, University of Oklahoma College of Medicine, Oklahoma City, Oklahoma, USA.
Department of Biomedical Informatics, Vanderbilt University, Nashville, Tennessee, USA.
Genet Med. 2018 Apr;20(4):470-473. doi: 10.1038/gim.2017.131. Epub 2017 Aug 24.
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.
目的
Genomic Oligoarray 和 SNP Array Evaluation Tool 3.0 通过挖掘 OMIM 中包含临床概要的基因条目,将同质性区域内的候选基因与患者表型进行匹配。但是,该工具无法识别 OMIM 条目缺乏(孟德尔)遗传方式描述的基因/疾病。本研究旨在通过构建无法通过 OMIM 诊断的常染色体隐性疾病数据库来提高该工具的诊断能力。
方法
我们从 OMIM 中提取了所有产生疾病表型但缺乏临床概要或其他遗传方式说明的基因列表。然后,我们在 PubMed 上搜索了有关每个基因的文献,以推断其遗传模式。
结果
我们分析了 1392 个基因。与 372 个基因相关的疾病被注释为隐性,430 个为显性。常染色体基因从 1 到 3 排序,3 表示推断的遗传方式背后有最强的证据。在 834 个常染色体基因中,158 个被评为 1,228 个被评为 2,448 个被评为 3。
结论
与隐性疾病相关的 372 个基因将被贡献给 SNP 数组工具,以及整个数据库到 OMIM。我们预计这些发现将在罕见疾病诊断中有用。