Peter N. Robinson

Walking the Interactome for Prioritization of Candidate Disease Genes

The identification of genes associated with hereditary disorders has contributed to improving medical care and to a better understanding of gene functions, interactions, and pathways. However, there are well over 1500 Mendelian disorders whose molecular basis remains unknown. At present, methods such as linkage analysis can identify the chromosomal region in which unknown disease genes are located, but the regions could contain up to hundreds of candidate genes. In this work, we present a method for prioritization of candidate genes by use of a global network distance measure, random walk analysis, for definition of similarities in protein-protein interaction networks. We tested our method on 110 disease-gene families with a total of 783 genes and achieved an area under the ROC curve of up to 98% on simulated linkage intervals of 100 genes surrounding the disease gene, significantly outperforming previous methods based on local distance measures. Our results not only provide an improved tool for positional-cloning projects but also add weight to the assumption that phenotypically similar diseases are associated with disturbances of subnetworks within the larger protein interactome that extend beyond the disease proteins themselves.

The Human Phenotype Ontology: A Tool for Annotating and Analyzing Human Hereditary Disease

There are many thousands of hereditary diseases in humans, each of which has a specific combination of phenotypic features, but computational analysis of phenotypic data has been hampered by lack of adequate computational data structures. Therefore, we have developed a Human Phenotype Ontology (HPO) with over 8000 terms representing individual phenotypic anomalies and have annotated all clinical entries in Online Mendelian Inheritance in Man with the terms of the HPO. We show that the HPO is able to capture phenotypic similarities between diseases in a useful and highly significant fashion.

The Human Phenotype Ontology project: linking molecular biology and disease through phenotype data

The Human Phenotype Ontology (HPO) project, available at http://www.human-phenotype-ontology.org, provides a structured, comprehensive and well-defined set of 10,088 classes (terms) describing human phenotypic abnormalities and 13,326 subclass relations between the HPO classes. In addition we have developed logical definitions for 46% of all HPO classes using terms from ontologies for anatomy, cell types, function, embryology, pathology and other domains. This allows interoperability with several resources, especially those containing phenotype information on model organisms such as mouse and zebrafish. Here we describe the updated HPO database, which provides annotations of 7,278 human hereditary syndromes listed in OMIM, Orphanet and DECIPHER to classes of the HPO. Various meta-attributes such as frequency, references and negations are associated with each annotation. Several large-scale projects worldwide utilize the HPO for describing phenotype information in their datasets. We have therefore generated equivalence mappings to other phenotype vocabularies such as LDDB, Orphanet, MedDRA, UMLS and phenoDB, allowing integration of existing datasets and interoperability with multiple biomedical resources. We have created various ways to access the HPO database content using flat files, a MySQL database, and Web-based tools. All data and documentation on the HPO project can be found online.

Ontologizer 2.0—a multifunctional tool for GO term enrichment analysis and data exploration

UNLABELLED The Ontologizer is a Java application that can be used to perform statistical analysis for overrepresentation of Gene Ontology (GO) terms in sets of genes or proteins derived from an experiment. The Ontologizer implements the standard approach to statistical analysis based on the one-sided Fishers exact test, the novel parent-child method, as well as topology-based algorithms. A number of multiple-testing correction procedures are provided. The Ontologizer allows users to visualize data as a graph including all significantly overrepresented GO terms and to explore the data by linking GO terms to all genes/proteins annotated to the term and by linking individual terms to child terms. AVAILABILITY The Ontologizer application is available under the terms of the GNU GPL. It can be started as a WebStart application from the project homepage, where source code is also provided: http://compbio.charite.de/ontologizer. REQUIREMENTS Ontologizer requires a Java SE 5.0 compliant Java runtime engine and GraphViz for the optional graph visualization tool.

Effect of Mutation Type and Location on Clinical Outcome in 1,013 Probands with Marfan Syndrome or Related Phenotypes and FBN1 Mutations: An International Study

Mutations in the fibrillin-1 (FBN1) gene cause Marfan syndrome (MFS) and have been associated with a wide range of overlapping phenotypes. Clinical care is complicated by variable age at onset and the wide range of severity of aortic features. The factors that modulate phenotypical severity, both among and within families, remain to be determined. The availability of international FBN1 mutation Universal Mutation Database (UMD-FBN1) has allowed us to perform the largest collaborative study ever reported, to investigate the correlation between the FBN1 genotype and the nature and severity of the clinical phenotype. A range of qualitative and quantitative clinical parameters (skeletal, cardiovascular, ophthalmologic, skin, pulmonary, and dural) was compared for different classes of mutation (types and locations) in 1,013 probands with a pathogenic FBN1 mutation. A higher probability of ectopia lentis was found for patients with a missense mutation substituting or producing a cysteine, when compared with other missense mutations. Patients with an FBN1 premature termination codon had a more severe skeletal and skin phenotype than did patients with an inframe mutation. Mutations in exons 24-32 were associated with a more severe and complete phenotype, including younger age at diagnosis of type I fibrillinopathy and higher probability of developing ectopia lentis, ascending aortic dilatation, aortic surgery, mitral valve abnormalities, scoliosis, and shorter survival; the majority of these results were replicated even when cases of neonatal MFS were excluded. These correlations, found between different mutation types and clinical manifestations, might be explained by different underlying genetic mechanisms (dominant negative versus haploinsufficiency) and by consideration of the two main physiological functions of fibrillin-1 (structural versus mediator of TGF beta signalling). Exon 24-32 mutations define a high-risk group for cardiac manifestations associated with severe prognosis at all ages.

The molecular genetics of Marfan syndrome and related disorders.

Marfan syndrome (MFS), a relatively common autosomal dominant hereditary disorder of connective tissue with prominent manifestations in the skeletal, ocular, and cardiovascular systems, is caused by mutations in the gene for fibrillin-1 (FBN1). The leading cause of premature death in untreated individuals with MFS is acute aortic dissection, which often follows a period of progressive dilatation of the ascending aorta. Recent research on the molecular physiology of fibrillin and the pathophysiology of MFS and related disorders has changed our understanding of this disorder by demonstrating changes in growth factor signalling and in matrix-cell interactions. The purpose of this review is to provide a comprehensive overview of recent advances in the molecular biology of fibrillin and fibrillin-rich microfibrils. Mutations in FBN1 and other genes found in MFS and related disorders will be discussed, and novel concepts concerning the complex and multiple mechanisms of the pathogenesis of MFS will be explained.

Improved detection of overrepresentation of Gene-Ontology annotations with parent–child analysis

MOTIVATION High-throughput experiments such as microarray hybridizations often yield long lists of genes found to share a certain characteristic such as differential expression. Exploring Gene Ontology (GO) annotations for such lists of genes has become a widespread practice to get first insights into the potential biological meaning of the experiment. The standard statistical approach to measuring overrepresentation of GO terms cannot cope with the dependencies resulting from the structure of GO because they analyze each term in isolation. Especially the fact that annotations are inherited from more specific descendant terms can result in certain types of false-positive results with potentially misleading biological interpretation, a phenomenon which we term the inheritance problem. RESULTS We present here a novel approach to analysis of GO term overrepresentation that determines overrepresentation of terms in the context of annotations to the terms parents. This approach reduces the dependencies between the individual terms measurements, and thereby avoids producing false-positive results owing to the inheritance problem. ROC analysis using study sets with overrepresented GO terms showed a clear advantage for our approach over the standard algorithm with respect to the inheritance problem. Although there can be no gold standard for exploratory methods such as analysis of GO term overrepresentation, analysis of biological datasets suggests that our algorithm tends to identify the core GO terms that are most characteristic of the dataset being analyzed.

Identity-by-descent filtering of exome sequence data identifies PIGV mutations in hyperphosphatasia mental retardation syndrome

Hyperphosphatasia mental retardation (HPMR) syndrome is an autosomal recessive form of mental retardation with distinct facial features and elevated serum alkaline phosphatase. We performed whole-exome sequencing in three siblings of a nonconsanguineous union with HPMR and performed computational inference of regions identical by descent in all siblings to establish PIGV, encoding a member of the GPI-anchor biosynthesis pathway, as the gene mutated in HPMR. We identified homozygous or compound heterozygous mutations in PIGV in three additional families.

The molecular genetics of Marfan syndrome and related microfibrillopathies

Mutations in the gene for fibrillin-1 (FBN1) have been shown to cause Marfan syndrome, an autosomal dominant disorder of connective tissue characterised by pleiotropic manifestations involving primarily the ocular, skeletal, and cardiovascular systems. Fibrillin-1 is a major component of the 10-12 nm microfibrils, which are thought to play a role in tropoelastin deposition and elastic fibre formation in addition to possessing an anchoring function in some tissues.  Fibrillin-1 mutations have also been found in patients who do not fulfil clinical criteria for the diagnosis of Marfan syndrome, but have related disorders of connective tissue, such as isolated ectopia lentis, familial aortic aneurysm, and Marfan-like skeletal abnormalities, so that Marfan syndrome may be regarded as one of a range of type 1 fibrillinopathies.  There appear to be no particular hot spots since mutations are found throughout the entire fibrillin-1 gene. However, a clustering of mutations associated with the most severe form of Marfan syndrome, neonatal Marfan syndrome, has been noted in a region encompassing exons 24 to 32. The gene for fibrillin-2 (FBN2) is highly homologous to FBN1, and mutations inFBN2 have been shown to cause a phenotypically related disorder termed congenital contractural arachnodactyly. Since mutations in the fibrillin genes are likely to affect the global function of the microfibrils, the term microfibrillopathy may be the most appropriate to designate the spectrum of disease associated with dysfunction of these molecules.  The understanding of the global and the molecular functions of the fibrillin containing microfibrils is still incomplete and, correspondingly, no comprehensive theory of the pathogenesis of Marfan syndrome has emerged to date. Many, but not all, fibrillin-1 gene mutations are expected to exert a dominant negative effect, whereby mutant fibrillin monomers impair the global function of the microfibrils. In this paper we review the molecular physiology and pathophysiology of Marfan syndrome and related microfibrillopathies.

The human phenotype ontology.

Robinson PN, Mundlos S. The Human Phenotype Ontology.