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Comprehensive Analysis of Tissue-wide Gene Expression and Phenotype Data Reveals Tissues Affected in Rare Genetic Disorders.
Feiglin, Ariel; Allen, Bryce K; Kohane, Isaac S; Kong, Sek Won.
Afiliação
  • Feiglin A; Department of Biomedical Informatics, Harvard Medical School, Boston, MA 02115, USA.
  • Allen BK; Department of Biomedical Informatics, Harvard Medical School, Boston, MA 02115, USA.
  • Kohane IS; Department of Biomedical Informatics, Harvard Medical School, Boston, MA 02115, USA. Electronic address: isaac_kohane@harvard.edu.
  • Kong SW; Computational Health Informatics Program, Boston Children's Hospital, Boston, MA 02115, USA; Department of Pediatrics, Harvard Medical School, Boston, MA 02115, USA.
Cell Syst ; 5(2): 140-148.e2, 2017 08 23.
Article em En | MEDLINE | ID: mdl-28822752
ABSTRACT
Linking putatively pathogenic variants to the tissues they affect is necessary for determining the correct diagnostic workup and therapeutic regime in undiagnosed patients. Here, we explored how gene expression across healthy tissues can be used to infer this link. We integrated 6,665 tissue-wide transcriptomes with genetic disorder knowledge bases covering 3,397 diseases. Receiver-operating characteristics (ROC) analysis using expression levels in each tissue and across tissues indicated significant but modest associations between elevated expression and phenotype for most tissues (maximum area under ROC curve = 0.69). At extreme elevation, associations were marked. Upregulation of disease genes in affected tissues was pronounced for genes associated with autosomal dominant over recessive disorders. Pathways enriched for genes expressed and associated with phenotypes highlighted tissue functionality, including lipid metabolism in spleen and DNA repair in adipose tissue. These results suggest features useful for evaluating the likelihood of particular tissue manifestations in genetic disorders. The web address of an interactive platform integrating these data is provided.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Doenças Raras / Doenças Genéticas Inatas Tipo de estudo: Etiology_studies / Prognostic_studies Limite: Humans Idioma: En Revista: Cell Syst Ano de publicação: 2017 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Doenças Raras / Doenças Genéticas Inatas Tipo de estudo: Etiology_studies / Prognostic_studies Limite: Humans Idioma: En Revista: Cell Syst Ano de publicação: 2017 Tipo de documento: Article País de afiliação: Estados Unidos