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1.
Am J Hum Genet ; 103(1): 58-73, 2018 07 05.
Article in English | MEDLINE | ID: mdl-29961570

ABSTRACT

Integration of detailed phenotype information with genetic data is well established to facilitate accurate diagnosis of hereditary disorders. As a rich source of phenotype information, electronic health records (EHRs) promise to empower diagnostic variant interpretation. However, how to accurately and efficiently extract phenotypes from heterogeneous EHR narratives remains a challenge. Here, we present EHR-Phenolyzer, a high-throughput EHR framework for extracting and analyzing phenotypes. EHR-Phenolyzer extracts and normalizes Human Phenotype Ontology (HPO) concepts from EHR narratives and then prioritizes genes with causal variants on the basis of the HPO-coded phenotype manifestations. We assessed EHR-Phenolyzer on 28 pediatric individuals with confirmed diagnoses of monogenic diseases and found that the genes with causal variants were ranked among the top 100 genes selected by EHR-Phenolyzer for 16/28 individuals (p < 2.2 × 10-16), supporting the value of phenotype-driven gene prioritization in diagnostic sequence interpretation. To assess the generalizability, we replicated this finding on an independent EHR dataset of ten individuals with a positive diagnosis from a different institution. We then assessed the broader utility by examining two additional EHR datasets, including 31 individuals who were suspected of having a Mendelian disease and underwent different types of genetic testing and 20 individuals with positive diagnoses of specific Mendelian etiologies of chronic kidney disease from exome sequencing. Finally, through several retrospective case studies, we demonstrated how combined analyses of genotype data and deep phenotype data from EHRs can expedite genetic diagnoses. In summary, EHR-Phenolyzer leverages EHR narratives to automate phenotype-driven analysis of clinical exomes or genomes, facilitating the broader implementation of genomic medicine.


Subject(s)
Exome/genetics , Adolescent , Child , Child, Preschool , Electronic Health Records , Female , Genetic Testing/methods , Genomics/methods , Genotype , Humans , Infant , Infant, Newborn , Male , Phenotype , Renal Insufficiency, Chronic/genetics , Retrospective Studies
2.
Orbit ; 36(3): 178-182, 2017 Jun.
Article in English | MEDLINE | ID: mdl-28306368

ABSTRACT

Inflammatory myofibroblastic tumor is a rare entity characterized by the presence of myofibroblasts and inflammatory cells within a fibrous stroma. It typically occurs in the pediatric population. The most common site of occurrence is the lung though it has been reported throughout the body. Although rare, it has been reported in the orbit. The clinical course is ill defined in the literature; here we report a case of pediatric IMT with delayed spontaneous regression.


Subject(s)
Neoplasm Regression, Spontaneous , Neoplasms, Muscle Tissue/physiopathology , Orbital Pseudotumor/physiopathology , Actins/metabolism , Biomarkers, Tumor/metabolism , Child , Humans , Leukocyte Common Antigens/metabolism , Magnetic Resonance Imaging , Male , Neoplasm Proteins/metabolism , Neoplasms, Muscle Tissue/diagnostic imaging , Neoplasms, Muscle Tissue/metabolism , Orbital Pseudotumor/diagnostic imaging , Orbital Pseudotumor/metabolism
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