Browsing by Author "Turro, Ernest"

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    The Human Phenotype Ontology in 2017
    (Oxford Journals, 2016-11-24) Köhler, Sebastian; Vasilevsky, Nicole A.; Engelstad, Mark; Foster, Erin D.; McMurry, Julie A.; Aymé, Ségolène; Baynam, Gareth; Bello, Susan M.; Boerkoel, Cornelius F.; Boycott, Kym M.; Brudno, Michael; Buske, Orion J.; Chinnery, Patrick F.; Cipriani, Valentina; Connell, Laureen E.; Dawkins, Hugh J.S.; DeMare, Laura E.; Devereau, Andrew D.; de Vries, Bert B.A.; Firth, Helen V.; Freson, Kathleen; Greene, Daniel; Hamosh, Ada; Helbig, Ingo; Hum, Courtney; Jähn, Johanna A.; James, Roger; Krause, Roland; Laulederkind, Stanley J. F.; Lochmüller, Hanns; Lyon, Gholson J.; Ogishima, Soichi; Olry, Annie; Ouwehand, Willem H.; Pontikos, Nikolas; Rath, Ana; Schaefer, Franz; Scott, Richard H.; Segal, Michael; Sergouniotis, Panagiotis I.; Sever, Richard; Smith, Cynthia L.; Straub, Volker; Thompson, Rachel; Turner, Catherine; Turro, Ernest; Veltman, Marijcke W.M.; Vulliamy, Tom; Yu, Jing; von Ziegenweidt, Julie; Zankl, Andreas; Züchner, Stephan; Zemojtel, Tomasz; Jacobsen, Julius O.B.; Groza, Tudor; Smedley, Damian; Mungall, Christopher J.; Haendel, Melissa A.; Robinson, Peter N.
    Deep phenotyping has been defined as the precise and comprehensive analysis of phenotypic abnormalities in which the individual components of the phenotype are observed and described. The three components of the Human Phenotype Ontology (HPO; www.human-phenotype-ontology.org) project are the phenotype vocabulary, disease-phenotype annotations and the algorithms that operate on these. These components are being used for computational deep phenotyping and precision medicine as well as integration of clinical data into translational research. The HPO is being increasingly adopted as a standard for phenotypic abnormalities by diverse groups such as international rare disease organizations, registries, clinical labs, biomedical resources, and clinical software tools and will thereby contribute toward nascent efforts at global data exchange for identifying disease etiologies. This update article reviews the progress of the HPO project since the debut Nucleic Acids Research database article in 2014, including specific areas of expansion such as common (complex) disease, new algorithms for phenotype driven genomic discovery and diagnostics, integration of cross-species mapping efforts with the Mammalian Phenotype Ontology, an improved quality control pipeline, and the addition of patient-friendly terminology.
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    Mutational and phenotypic characterization of hereditary hemorrhagic telangiectasia
    (American Society of Hematology, 2020-10-22) Shovlin, Claire L.; Simeoni, Ilenia; Downes, Kate; Frazer, Zoe C.; Megy, Karyn; Bernabeu-Herrero, Maria E.; Shurr, Abigail; Brimley, Jennifer; Patel, Dilipkumar; Kell, Loren; Stephens, Jonathan; Turbin, Isobel G.; Aldred, Micheala A.; Penkett, Christopher J.; Ouwehand, Willem H.; Jovine, Luca; Turro, Ernest; Medicine, School of Medicine
    Hereditary hemorrhagic telangiectasia (HHT) is an autosomal dominant vascular dysplasia. Care delivery for HHT patients is impeded by the need for laborious, repeated phenotyping and gaps in knowledge regarding the relationships between causal DNA variants in ENG, ACVRL1, SMAD4 and GDF2, and clinical manifestations. To address this, we analyzed DNA samples from 183 previously uncharacterized, unrelated HHT and suspected HHT cases using the ThromboGenomics high-throughput sequencing platform. We identified 127 rare variants across 168 heterozygous genotypes. Applying modified American College of Medical Genetics and Genomics Guidelines, 106 variants were classified as pathogenic/likely pathogenic and 21 as nonpathogenic (variant of uncertain significance/benign). Unlike the protein products of ACVRL1 and SMAD4, the extracellular ENG amino acids are not strongly conserved. Our inferences of the functional consequences of causal variants in ENG were therefore informed by the crystal structure of endoglin. We then compared the accuracy of predictions of the causal gene blinded to the genetic data using 2 approaches: subjective clinical predictions and statistical predictions based on 8 Human Phenotype Ontology terms. Both approaches had some predictive power, but they were insufficiently accurate to be used clinically, without genetic testing. The distributions of red cell indices differed by causal gene but not sufficiently for clinical use in isolation from genetic data. We conclude that parallel sequencing of the 4 known HHT genes, multidisciplinary team review of variant calls in the context of detailed clinical information, and statistical and structural modeling improve the prognostication and treatment of HHT.