Daniel Greene

The Human Phenotype Ontology in 2017

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.

Human phenotype ontology annotation and cluster analysis to unravel genetic defects in 707 cases with unexplained bleeding and platelet disorders.

BackgroundHeritable bleeding and platelet disorders (BPD) are heterogeneous and frequently have an unknown genetic basis. The BRIDGE-BPD study aims to discover new causal genes for BPD by high throughput sequencing using cluster analyses based on improved and standardised deep, multi-system phenotyping of cases.MethodsWe report a new approach in which the clinical and laboratory characteristics of BPD cases are annotated with adapted Human Phenotype Ontology (HPO) terms. Cluster analyses are then used to characterise groups of cases with similar HPO terms and variants in the same genes.ResultsWe show that 60% of index cases with heritable BPD enrolled at 10 European or US centres were annotated with HPO terms indicating abnormalities in organ systems other than blood or blood-forming tissues, particularly the nervous system. Cases within pedigrees clustered closely together on the bases of their HPO-coded phenotypes, as did cases sharing several clinically suspected syndromic disorders. Cases subsequently found to harbour variants in ACTN1 also clustered closely, even though diagnosis of this recently described disorder was not possible using only the clinical and laboratory data available to the enrolling clinician.ConclusionsThese findings validate our novel HPO-based phenotype clustering methodology for known BPD, thus providing a new discovery tool for BPD of unknown genetic basis. This approach will also be relevant for other rare diseases with significant genetic heterogeneity.

A high-throughput sequencing test for diagnosing inherited bleeding, thrombotic, and platelet disorders

Inherited bleeding, thrombotic, and platelet disorders (BPDs) are diseases that affect ∼300 individuals per million births. With the exception of hemophilia and von Willebrand disease patients, a molecular analysis for patients with a BPD is often unavailable. Many specialized tests are usually required to reach a putative diagnosis and they are typically performed in a step-wise manner to control costs. This approach causes delays and a conclusive molecular diagnosis is often never reached, which can compromise treatment and impede rapid identification of affected relatives. To address this unmet diagnostic need, we designed a high-throughput sequencing platform targeting 63 genes relevant for BPDs. The platform can call single nucleotide variants, short insertions/deletions, and large copy number variants (though not inversions) which are subjected to automated filtering for diagnostic prioritization, resulting in an average of 5.34 candidate variants per individual. We sequenced 159 and 137 samples, respectively, from cases with and without previously known causal variants. Among the latter group, 61 cases had clinical and laboratory phenotypes indicative of a particular molecular etiology, whereas the remainder had an a priori highly uncertain etiology. All previously detected variants were recapitulated and, when the etiology was suspected but unknown or uncertain, a molecular diagnosis was reached in 56 of 61 and only 8 of 76 cases, respectively. The latter category highlights the need for further research into novel causes of BPDs. The ThromboGenomics platform thus provides an affordable DNA-based test to diagnose patients suspected of having a known inherited BPD.

A gain-of-function variant in DIAPH1 causes dominant macrothrombocytopenia and hearing loss

Macrothrombocytopenia (MTP) is a heterogeneous group of disorders characterized by enlarged and reduced numbers of circulating platelets, sometimes resulting in abnormal bleeding. In most MTP, this phenotype arises because of altered regulation of platelet formation from megakaryocytes (MKs). We report the identification of DIAPH1, which encodes the Rho-effector diaphanous-related formin 1 (DIAPH1), as a candidate gene for MTP using exome sequencing, ontological phenotyping, and similarity regression. We describe 2 unrelated pedigrees with MTP and sensorineural hearing loss that segregate with a DIAPH1 R1213* variant predicting partial truncation of the DIAPH1 diaphanous autoregulatory domain. The R1213* variant was linked to reduced proplatelet formation from cultured MKs, cell clustering, and abnormal cortical filamentous actin. Similarly, in platelets, there was increased filamentous actin and stable microtubules, indicating constitutive activation of DIAPH1. Overexpression of DIAPH1 R1213* in cells reproduced the cytoskeletal alterations found in platelets. Our description of a novel disorder of platelet formation and hearing loss extends the repertoire of DIAPH1-related disease and provides new insight into the autoregulation of DIAPH1 activity.

A dominant gain-of-function mutation in universal tyrosine kinase SRC causes thrombocytopenia, myelofibrosis, bleeding, and bone pathologies

E527K hyperactive SRC results in megakaryocytes with increased podosome formation, thrombocytopenia, myelofibrosis, bleeding, and bone pathologies. SRC shows its stripes The nonreceptor tyrosine kinase SRC is a proto-oncogene that has been associated with cancer progression. Now, Turro et al. find a gain-of-function mutation in SRC in nine patients with myelofibrosis, bleeding, and bone disorders. This mutation prevented SRC from inhibiting itself, and the overactive SRC resulted in enhanced tyrosine phosphorylation in a zebrafish model as well as in patient-derived cells. In patients with myelofibrosis, this SRC mutation was associated with increased outgrowth of myeloid and megakaryocyte colonies, with abnormal platelet production, which could be rescued by SRC kinase inhibition. These findings may be important for understanding the severe bleeding in cancer patients treated with Src family kinase inhibitors. The Src family kinase (SFK) member SRC is a major target in drug development because it is activated in many human cancers, yet deleterious SRC germline mutations have not been reported. We used genome sequencing and Human Phenotype Ontology patient coding to identify a gain-of-function mutation in SRC causing thrombocytopenia, myelofibrosis, bleeding, and bone pathologies in nine cases. Modeling of the E527K substitution predicts loss of SRC’s self-inhibitory capacity, which we confirmed with in vitro studies showing increased SRC kinase activity and enhanced Tyr419 phosphorylation in COS-7 cells overexpressing E527K SRC. The active form of SRC predominates in patients’ platelets, resulting in enhanced overall tyrosine phosphorylation. Patients with myelofibrosis have hypercellular bone marrow with trilineage dysplasia, and their stem cells grown in vitro form more myeloid and megakaryocyte (MK) colonies than control cells. These MKs generate platelets that are dysmorphic, low in number, highly variable in size, and have a paucity of α-granules. Overactive SRC in patient-derived MKs causes a reduction in proplatelet formation, which can be rescued by SRC kinase inhibition. Stem cells transduced with lentiviral E527K SRC form MKs with a similar defect and enhanced tyrosine phosphorylation levels. Patient-derived and E527K-transduced MKs show Y419 SRC–positive stained podosomes that induce altered actin organization. Expression of mutated src in zebrafish recapitulates patients’ blood and bone phenotypes. Similar studies of platelets and MKs may reveal the mechanism underlying the severe bleeding frequently observed in cancer patients treated with next-generation SFK inhibitors.

Phenotype Similarity Regression for Identifying the Genetic Determinants of Rare Diseases

Rare genetic disorders, which can now be studied systematically with affordable genome sequencing, are often caused by high-penetrance rare variants. Such disorders are often heterogeneous and characterized by abnormalities spanning multiple organ systems ascertained with variable clinical precision. Existing methods for identifying genes with variants responsible for rare diseases summarize phenotypes with unstructured binary or quantitative variables. The Human Phenotype Ontology (HPO) allows composite phenotypes to be represented systematically but association methods accounting for the ontological relationship between HPO terms do not exist. We present a Bayesian method to model the association between an HPO-coded patient phenotype and genotype. Our method estimates the probability of an association together with an HPO-coded phenotype characteristic of the disease. We thus formalize a clinical approach to phenotyping that is lacking in standard regression techniques for rare disease research. We demonstrate the power of our method by uncovering a number of true associations in a large collection of genome-sequenced and HPO-coded cases with rare diseases.

Phenopolis: an open platform for harmonization and analysis of genetic and phenotypic data.

Summary Phenopolis is an open-source web server providing an intuitive interface to genetic and phenotypic databases. It integrates analysis tools such as variant filtering and gene prioritization based on phenotype. The Phenopolis platform will accelerate clinical diagnosis, gene discovery and encourage wider adoption of the Human Phenotype Ontology in the study of rare genetic diseases. Availability and Implementation A demo of the website is available at https://phenopolis.github.io . If you wish to install a local copy, source code and installation instruction are available at https://github.com/phenopolis . The software is implemented using Python, MongoDB, HTML/Javascript and various bash shell scripts. Contact n.pontikos@ucl.ac.uk. Supplementary information Supplementary data are available at Bioinformatics online.

A comprehensive high-throughput sequencing test for the diagnosis of inherited bleeding, thrombotic and platelet disorders

Inherited bleeding, thrombotic, and platelet disorders (BPDs) are diseases that affect ∼300 individuals per million births. With the exception of hemophilia and von Willebrand disease patients, a molecular analysis for patients with a BPD is often unavailable. Many specialized tests are usually required to reach a putative diagnosis and they are typically performed in a step-wise manner to control costs. This approach causes delays and a conclusive molecular diagnosis is often never reached, which can compromise treatment and impede rapid identification of affected relatives. To address this unmet diagnostic need, we designed a high-throughput sequencing platform targeting 63 genes relevant for BPDs. The platform can call single nucleotide variants, short insertions/deletions, and large copy number variants (though not inversions) which are subjected to automated filtering for diagnostic prioritization, resulting in an average of 5.34 candidate variants per individual. We sequenced 159 and 137 samples, respectively, from cases with and without previously known causal variants. Among the latter group, 61 cases had clinical and laboratory phenotypes indicative of a particular molecular etiology, whereas the remainder had an a priori highly uncertain etiology. All previously detected variants were recapitulated and, when the etiology was suspected but unknown or uncertain, a molecular diagnosis was reached in 56 of 61 and only 8 of 76 cases, respectively. The latter category highlights the need for further research into novel causes of BPDs. The ThromboGenomics platform thus provides an affordable DNA-based test to diagnose patients suspected of having a known inherited BPD.

Rare variants in GP1BB are responsible for autosomal dominant macrothrombocytopenia

The von Willebrand receptor complex, which is composed of the glycoproteins Ibα, Ibβ, GPV, and GPIX, plays an essential role in the earliest steps in hemostasis. During the last 4 decades, it has become apparent that loss of function of any 1 of 3 of the genes encoding these glycoproteins (namely, GP1BA, GP1BB, and GP9) leads to autosomal recessive macrothrombocytopenia complicated by bleeding. A small number of variants in GP1BA have been reported to cause a milder and dominant form of macrothrombocytopenia, but only 2 tentative reports exist of such a variant in GP1BB By analyzing data from a collection of more than 1000 genome-sequenced patients with a rare bleeding and/or platelet disorder, we have identified a significant association between rare monoallelic variants in GP1BB and macrothrombocytopenia. To strengthen our findings, we sought further cases in 2 additional collections in the United Kingdom and Japan. Across 18 families exhibiting phenotypes consistent with autosomal dominant inheritance of macrothrombocytopenia, we report on 27 affected cases carrying 1 of 9 rare variants in GP1BB.

ontologyX: a suite of R packages for working with ontological data

Summary: Ontologies are widely used constructs for encoding and analyzing biomedical data, but the absence of simple and consistent tools has made exploratory and systematic analysis of such data unnecessarily difficult. Here we present three packages which aim to simplify such procedures. The ontologyIndex package enables arbitrary ontologies to be read into R, supports representation of ontological objects by native R types, and provides a parsimonius set of performant functions for querying ontologies. ontologySimilarity and ontologyPlot extend ontologyIndex with functionality for straightforward visualization and semantic similarity calculations, including statistical routines. Availability and Implementation: ontologyIndex, ontologyPlot and ontologySimilarity are all available on the Comprehensive R Archive Network website under https://cran.r‐project.org/web/packages/. Contact: Daniel Greene dg333@cam.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online.