Causal relationships between diseases mined from the literature improve the use of polygenic risk scores.

MOTIVATION: Identifying causal relations between diseases allows for the study of shared pathways, biological mechanisms, and inter-disease risks. Such causal relations can facilitate the identification of potential disease precursors and candidates for drug re-purposing. However, computational methods often lack access to these causal relations. Few approaches have been developed to automatically extract causal relationships between diseases from unstructured text, but they are often only focused on a small number of diseases, lack validation of the extracted causal relations, or do not make their data available. RESULTS: We automatically mined statements asserting a causal relation between diseases from the scientific literature by leveraging lexical patterns. Following automated mining of causal relations, we mapped the diseases to the International Classification of Diseases (ICD) identifiers to allow the direct application to clinical data. We provide quantitative and qualitative measures to evaluate the mined causal relations and compare to UK Biobank (UKB) diagnosis data as a completely independent data source. The validated causal associations were used to create a directed acyclic graph that can be used by causal inference frameworks. We demonstrate the utility of our causal network by performing causal inference using the do-calculus, using relations within the graph to construct and improve polygenic risk scores, and disentangle the pleiotropic effects of variants. AVAILABILITY AND IMPLEMENTATION: The data is available through https://github.com/bio-ontology-research-group/causal-relations-between-diseases. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Bridging mouse and human anatomies; a knowledge-based approach to comparative anatomy for disease model phenotyping.

The laboratory mouse is the foremost mammalian model used for studying human diseases and is closely anatomically related to humans. Whilst knowledge about human anatomy has been collected throughout the history of mankind, the first comprehensive study of the mouse anatomy was published less than 60 years ago. This has been followed by the more recent publication of several books and resources on mouse anatomy. Nevertheless, to date, our understanding and knowledge of mouse anatomy is far from being at the same level as that of humans. In addition, the alignment between current mouse and human anatomy nomenclatures is far from being as developed as those existing between other species, such as domestic animals and humans. To close this gap, more in depth mouse anatomical research is needed and it will be necessary to extent and refine the current vocabulary of mouse anatomical terms.

PATHBIO: an international training program for precision mouse phenotyping.

Design and production of genetically engineered mouse strains by individual research laboratories, research teams, large-scale consortia, and the biopharmaceutical industry have magnified the need for qualified personnel to identify, annotate, and validate (phenotype) these potentially new mouse models of human disease. The PATHBIO project has been recently established and funded by the European Union's ERASMUS+ Knowledge Alliance program to address the current shortfall in formally trained personnel. A series of teaching workshops will be given by experts on anatomy, histology, embryology, imaging, and comparative pathology to increase the availability of individuals with formal training to contribute to this important niche of Europe's biomedical research enterprise. These didactic and hands-on workshops are organized into three modules: (1) embryology, anatomy, histology, and the anatomical basis of imaging, (2) image-based phenotyping, and (3) pathology. The workshops are open to all levels of participants from recent graduates to Ph.D., M.D., and veterinary scientists. Participation is available on a competitive basis at no cost for attending. The first series of Workshop Modules was held in 2019 and these will continue for the next 2 years.

The anatomy of phenotype ontologies: principles, properties and applications.

The past decade has seen an explosion in the collection of genotype data in domains as diverse as medicine, ecology, livestock and plant breeding. Along with this comes the challenge of dealing with the related phenotype data, which is not only large but also highly multidimensional. Computational analysis of phenotypes has therefore become critical for our ability to understand the biological meaning of genomic data in the biological sciences. At the heart of computational phenotype analysis are the phenotype ontologies. A large number of these ontologies have been developed across many domains, and we are now at a point where the knowledge captured in the structure of these ontologies can be used for the integration and analysis of large interrelated data sets. The Phenotype And Trait Ontology framework provides a method for formal definitions of phenotypes and associated data sets and has proved to be key to our ability to develop methods for the integration and analysis of phenotype data. Here, we describe the development and products of the ontological approach to phenotype capture, the formal content of phenotype ontologies and how their content can be used computationally.

DeepPVP: phenotype-based prioritization of causative variants using deep learning.

BACKGROUND: Prioritization of variants in personal genomic data is a major challenge. Recently, computational methods that rely on comparing phenotype similarity have shown to be useful to identify causative variants. In these methods, pathogenicity prediction is combined with a semantic similarity measure to prioritize not only variants that are likely to be dysfunctional but those that are likely involved in the pathogenesis of a patient's phenotype. RESULTS: We have developed DeepPVP, a variant prioritization method that combined automated inference with deep neural networks to identify the likely causative variants in whole exome or whole genome sequence data. We demonstrate that DeepPVP performs significantly better than existing methods, including phenotype-based methods that use similar features. DeepPVP is freely available at https://github.com/bio-ontology-research-group/phenomenet-vp . CONCLUSIONS: DeepPVP further improves on existing variant prioritization methods both in terms of speed as well as accuracy.

Ontology-based validation and identification of regulatory phenotypes.

Motivation: Function annotations of gene products, and phenotype annotations of genotypes, provide valuable information about molecular mechanisms that can be utilized by computational methods to identify functional and phenotypic relatedness, improve our understanding of disease and pathobiology, and lead to discovery of drug targets. Identifying functions and phenotypes commonly requires experiments which are time-consuming and expensive to carry out; creating the annotations additionally requires a curator to make an assertion based on reported evidence. Support to validate the mutual consistency of functional and phenotype annotations as well as a computational method to predict phenotypes from function annotations, would greatly improve the utility of function annotations. Results: We developed a novel ontology-based method to validate the mutual consistency of function and phenotype annotations. We apply our method to mouse and human annotations, and identify several inconsistencies that can be resolved to improve overall annotation quality. We also apply our method to the rule-based prediction of regulatory phenotypes from functions and demonstrate that we can predict these phenotypes with Fmax of up to 0.647. Availability and implementation: https://github.com/bio-ontology-research-group/phenogocon.

Nail abnormalities identified in an ageing study of 30 inbred mouse strains.

In a large-scale ageing study, 30 inbred mouse strains were systematically screened for histologic evidence of lesions in all organ systems. Ten strains were diagnosed with similar nail abnormalities. The highest frequency was noted in NON/ShiLtJ mice. Lesions identified fell into two main categories: acute to chronic penetration of the third phalangeal bone through the hyponychium with associated inflammation and bone remodelling or metaplasia of the nail matrix and nail bed associated with severe orthokeratotic hyperkeratosis replacing the nail plate. Penetration of the distal phalanx through the hyponychium appeared to be the initiating feature resulting in nail abnormalities. The accompanying acute to subacute inflammatory response was associated with osteolysis of the distal phalanx. Evaluation of young NON/ShiLtJ mice revealed that these lesions were not often found, or affected only one digit. The only other nail unit abnormality identified was sporadic subungual epidermoid inclusion cysts which closely resembled similar lesions in human patients. These abnormalities, being age-related developments, may have contributed to weight loss due to impacts upon feeding and should be a consideration for future research due to the potential to interact with other experimental factors in ageing studies using the affected strains of mice.

The tubercular badger and the uncertain curve:- The need for a multiple stressor approach in environmental radiation protection.

This article presents the results of a workshop held in Stirling, Scotland in June 2018, called to examine critically the effects of low-dose ionising radiation on the ecosphere. The meeting brought together participants from the fields of low- and high-dose radiobiology and those working in radioecology to discuss the effects that low doses of radiation have on non-human biota. In particular, the shape of the low-dose response relationship and the extent to which the effects of low-dose and chronic exposure may be predicted from high dose rate exposures were discussed. It was concluded that high dose effects were not predictive of low dose effects. It followed that the tools presently available were deemed insufficient to reliably predict risk of low dose exposures in ecosystems. The workshop participants agreed on three major recommendations for a path forward. First, as treating radiation as a single or unique stressor was considered insufficient, the development of a multidisciplinary approach is suggested to address key concerns about multiple stressors in the ecosphere. Second, agreed definitions are needed to deal with the multiplicity of factors determining outcome to low dose exposures as a term can have different meanings in different disciplines. Third, appropriate tools need to be developed to deal with the different time, space and organisation level scales. These recommendations permit a more accurate picture of prospective risks.

Hyaline Arteriolosclerosis in 30 Strains of Aged Inbred Mice.

During a screen for vascular phenotypes in aged laboratory mice, a unique discrete phenotype of hyaline arteriolosclerosis of the intertubular arteries and arterioles of the testes was identified in several inbred strains. Lesions were limited to the testes and did not occur as part of any renal, systemic, or pulmonary arteriopathy or vasculitis phenotype. There was no evidence of systemic or pulmonary hypertension, and lesions did not occur in ovaries of females. Frequency was highest in males of the SM/J (27/30, 90%) and WSB/EiJ (19/26, 73%) strains, aged 383 to 847 days. Lesions were sporadically present in males from several other inbred strains at a much lower (<20%) frequency. The risk of testicular hyaline arteriolosclerosis is at least partially underpinned by a genetic predisposition that is not associated with other vascular lesions (including vasculitis), separating out the etiology of this form and site of arteriolosclerosis from other related conditions that often co-occur in other strains of mice and in humans. Because of their genetic uniformity and controlled dietary and environmental conditions, mice are an excellent model to dissect the pathogenesis of human disease conditions. In this study, a discrete genetically driven phenotype of testicular hyaline arteriolosclerosis in aging mice was identified. These observations open the possibility of identifying the underlying genetic variant(s) associated with the predisposition and therefore allowing future interrogation of the pathogenesis of this condition.

The Human Phenotype Ontology: Semantic Unification of Common and Rare Disease.

The Human Phenotype Ontology (HPO) is widely used in the rare disease community for differential diagnostics, phenotype-driven analysis of next-generation sequence-variation data, and translational research, but a comparable resource has not been available for common disease. Here, we have developed a concept-recognition procedure that analyzes the frequencies of HPO disease annotations as identified in over five million PubMed abstracts by employing an iterative procedure to optimize precision and recall of the identified terms. We derived disease models for 3,145 common human diseases comprising a total of 132,006 HPO annotations. The HPO now comprises over 250,000 phenotypic annotations for over 10,000 rare and common diseases and can be used for examining the phenotypic overlap among common diseases that share risk alleles, as well as between Mendelian diseases and common diseases linked by genomic location. The annotations, as well as the HPO itself, are freely available.

Semantic prioritization of novel causative genomic variants.

Discriminating the causative disease variant(s) for individuals with inherited or de novo mutations presents one of the main challenges faced by the clinical genetics community today. Computational approaches for variant prioritization include machine learning methods utilizing a large number of features, including molecular information, interaction networks, or phenotypes. Here, we demonstrate the PhenomeNET Variant Predictor (PVP) system that exploits semantic technologies and automated reasoning over genotype-phenotype relations to filter and prioritize variants in whole exome and whole genome sequencing datasets. We demonstrate the performance of PVP in identifying causative variants on a large number of synthetic whole exome and whole genome sequences, covering a wide range of diseases and syndromes. In a retrospective study, we further illustrate the application of PVP for the interpretation of whole exome sequencing data in patients suffering from congenital hypothyroidism. We find that PVP accurately identifies causative variants in whole exome and whole genome sequencing datasets and provides a powerful resource for the discovery of causal variants.

When a duck is not a duck; a new interdisciplinary synthesis for environmental radiation protection.

This consensus paper presents the results of a workshop held in Essen, Germany in September 2017, called to examine critically the current approach to radiological environmental protection. The meeting brought together participants from the field of low dose radiobiology and those working in radioecology. Both groups have a common aim of identifying radiation exposures and protecting populations and individuals from harmful effects of ionising radiation exposure, but rarely work closely together. A key question in radiobiology is to understand mechanisms triggered by low doses or dose rates, leading to adverse outcomes of individuals while in radioecology a key objective is to recognise when harm is occurring at the level of the ecosystem. The discussion provided a total of six strategic recommendations which would help to address these questions.

The role of ontologies in biological and biomedical research: a functional perspective.

Ontologies are widely used in biological and biomedical research. Their success lies in their combination of four main features present in almost all ontologies: provision of standard identifiers for classes and relations that represent the phenomena within a domain; provision of a vocabulary for a domain; provision of metadata that describes the intended meaning of the classes and relations in ontologies; and the provision of machine-readable axioms and definitions that enable computational access to some aspects of the meaning of classes and relations. While each of these features enables applications that facilitate data integration, data access and analysis, a great potential lies in the possibility of combining these four features to support integrative analysis and interpretation of multimodal data. Here, we provide a functional perspective on ontologies in biology and biomedicine, focusing on what ontologies can do and describing how they can be used in support of integrative research. We also outline perspectives for using ontologies in data-driven science, in particular their application in structured data mining and machine learning applications.

Mouse genome-wide association study identifies polymorphisms on chromosomes 4, 11, and 15 for age-related cardiac fibrosis.

Dystrophic cardiac calcinosis (DCC), also called epicardial and myocardial fibrosis and mineralization, has been detected in mice of a number of laboratory inbred strains, most commonly C3H/HeJ and DBA/2J. In previous mouse breeding studies between these DCC susceptible and the DCC-resistant strain C57BL/6J, 4 genetic loci harboring genes involved in DCC inheritance were identified and subsequently termed Dyscalc loci 1 through 4. Here, we report susceptibility to cardiac fibrosis, a sub-phenotype of DCC, at 12 and 20 months of age and close to natural death in a survey of 28 inbred mouse strains. Eight strains showed cardiac fibrosis with highest frequency and severity in the moribund mice. Using genotype and phenotype information of the 28 investigated strains, we performed genome-wide association studies (GWAS) and identified the most significant associations on chromosome (Chr) 15 at 72 million base pairs (Mb) (P < 10(-13)) and Chr 4 at 122 Mb (P < 10(-11)) and 134 Mb (P < 10(-7)). At the Chr 15 locus, Col22a1 and Kcnk9 were identified. Both have been reported to be morphologically and functionally important in the heart muscle. The strongest Chr 4 associations were located approximately 6 Mb away from the Dyscalc 2 quantitative trait locus peak within the boundaries of the Extl1 gene and in close proximity to the Trim63 and Cap1 genes. In addition, a single-nucleotide polymorphism association was found on chromosome 11. This study provides evidence for more than the previously reported 4 genetic loci determining cardiac fibrosis and DCC. The study also highlights the power of GWAS in the mouse for dissecting complex genetic traits.

Genetic determinants of fibro-osseous lesions in aged inbred mice.

Fibro-osseous lesions in mice are progressive aging changes in which the bone marrow is replaced to various degrees by fibrovascular stroma and bony trabeculae in a wide variety of bones. The frequency and severity varied greatly among 28 different inbred mouse stains, predominantly affecting females, ranging from 0% for 10 strains to 100% for KK/HlJ and NZW/LacJ female mice. Few lesions were observed in male mice and for 23 of the strains, no lesions were observed in males for any of the cohorts. There were no significant correlations between strain-specific severities of fibro-osseous lesions and ovarian (r=0.11; P=0.57) or endometrial (r=0.03; P=0.89) cyst formation frequency or abnormalities in parathyroid glands. Frequency of fibro-osseous lesions was most strongly associated (P<10(-6)) with genome variations on chromosome (Chr) 8 at 90.6 and 90.8Mb (rs33108071, rs33500669; P=5.0·10(-10), 1.3·10(-6)), Chr 15 at 23.6 and 23.8Mb (rs32087871, rs45770368; P=7.3·10(-7), 2.7·10(-6)), and Chr 19 at 33.2, 33.4, and 33.6Mb (rs311004232, rs30524929, rs30448815; P=2.8·10(-6), 2.8·10(-6), 2.8·10(-6)) in genome-wide association studies (GWAS). The relatively large number of candidate genes identified in the GWAS analyses suggests that this may be an extremely complex polygenic disease. These results indicate that fibro-osseous lesions are surprisingly common in many inbred strains of laboratory mice as they age. While this presents little problem in most studies that utilize young animals, it may complicate aging studies, particularly those focused on bone.

Aber-OWL: a framework for ontology-based data access in biology.

BACKGROUND: Many ontologies have been developed in biology and these ontologies increasingly contain large volumes of formalized knowledge commonly expressed in the Web Ontology Language (OWL). Computational access to the knowledge contained within these ontologies relies on the use of automated reasoning. RESULTS: We have developed the Aber-OWL infrastructure that provides reasoning services for bio-ontologies. Aber-OWL consists of an ontology repository, a set of web services and web interfaces that enable ontology-based semantic access to biological data and literature. Aber-OWL is freely available at http://aber-owl.net . CONCLUSIONS: Aber-OWL provides a framework for automatically accessing information that is annotated with ontologies or contains terms used to label classes in ontologies. When using Aber-OWL, access to ontologies and data annotated with them is not merely based on class names or identifiers but rather on the knowledge the ontologies contain and the inferences that can be drawn from it.

Best behaviour? Ontologies and the formal description of animal behaviour.

The development of ontologies for describing animal behaviour has proved to be one of the most difficult of all scientific knowledge domains. Ranging from neurological processes to human emotions, the range and scope needed for such ontologies is highly challenging, but if data integration and computational tools such as automated reasoning are to be fully applied in this important area the underlying principles of these ontologies need to be better established and development needs detailed coordination. Whilst the state of scientific knowledge is always paramount in ontology and formal description framework design, this is a particular problem with neurobehavioural ontologies where our understanding of the relationship between behaviour and its underlying biophysical basis is currently in its infancy. In this commentary, we discuss some of the fundamental problems in designing and using behaviour ontologies, and present some of the best developed tools in this domain.

Mouse model phenotypes provide information about human drug targets.

MOTIVATION: Methods for computational drug target identification use information from diverse information sources to predict or prioritize drug targets for known drugs. One set of resources that has been relatively neglected for drug repurposing is animal model phenotype. RESULTS: We investigate the use of mouse model phenotypes for drug target identification. To achieve this goal, we first integrate mouse model phenotypes and drug effects, and then systematically compare the phenotypic similarity between mouse models and drug effect profiles. We find a high similarity between phenotypes resulting from loss-of-function mutations and drug effects resulting from the inhibition of a protein through a drug action, and demonstrate how this approach can be used to suggest candidate drug targets. AVAILABILITY AND IMPLEMENTATION: Analysis code and supplementary data files are available on the project Web site at https://drugeffects.googlecode.com.

Excavating the Genome: Large-Scale Mutagenesis Screening for the Discovery of New Mouse Models.

Technology now exists for rapid screening of mutated laboratory mice to identify phenotypes associated with specific genetic mutations. Large repositories exist for spontaneous mutants and those induced by chemical mutagenesis, many of which have never been fully studied or comprehensively evaluated. To supplement these resources, a variety of techniques have been consolidated in an international effort to create mutations in all known protein coding genes in the mouse. With targeted embryonic stem cell lines now available for almost all protein coding genes and more recently CRISPR/Cas9 technology, large-scale efforts are underway to create further novel mutant mouse strains and to characterize their phenotypes. However, accurate diagnosis of skin, hair, and nail diseases still relies on careful gross and histological analysis, and while not automated to the level of the physiological phenotyping, histopathology still provides the most direct and accurate diagnosis and correlation with human diseases. As a result of these efforts, many new mouse dermatological disease models are being characterized and developed.

Dsp rul: a spontaneous mouse mutation in desmoplakin as a model of Carvajal-Huerta syndrome.

Studies of spontaneous mutations in mice have provided valuable disease models and important insights into the mechanisms of human disease. Ruffled (rul) is a new autosomal recessive mutation causing abnormal hair coat in mice. The rul allele arose spontaneously in the RB156Bnr/EiJ inbred mouse strain. In addition to an abnormal coat texture, we found diffuse epidermal blistering, abnormal electrocardiograms (ECGs), and ventricular fibrosis in mutant animals. Using high-throughput sequencing (HTS) we found a frameshift mutation at 38,288,978bp of chromosome 13 in the desmoplakin gene (Dsp). The predicted mutant protein is truncated at the c-terminus and missing the majority of the plakin repeat domain. The phenotypes found in Dsp(rul) mice closely model a rare human disorder, Carvajal-Huerta syndrome. Carvajal-Huerta syndrome (CHS) is a rare cardiocutaneous disorder that presents in humans with wooly hair, palmoplantar keratoderma and ventricular cardiomyopathy. CHS results from an autosomal recessive mutation on the 3' end of desmoplakin (DSP) truncating the full length protein. The Dsp(rul) mouse provides a new model to investigate the pathogenesis of CHS, as well as the underlying basic biology of the adhesion molecules coded by the desmosomal genes.