Zebrafish Models of Autosomal Dominant Ataxias.

Hereditary dominant ataxias are a heterogeneous group of neurodegenerative conditions causing cerebellar dysfunction and characterized by progressive motor incoordination. Despite many efforts put into the study of these diseases, there are no effective treatments yet. Zebrafish models are widely used to characterize neuronal disorders due to its conserved vertebrate genetics that easily support genetic edition and their optic transparency that allows observing the intact CNS and its connections. In addition, its small size and external fertilization help to develop high throughput assays of candidate drugs. Here, we discuss the contributions of zebrafish models to the study of dominant ataxias defining phenotypes, genetic function, behavior and possible treatments. In addition, we review the zebrafish models created for X-linked repeat expansion diseases X-fragile/fragile-X tremor ataxia. Most of the models reviewed here presented neuronal damage and locomotor deficits. However, there is a generalized lack of zebrafish adult heterozygous models and there are no knock-in zebrafish models available for these diseases. The models created for dominant ataxias helped to elucidate gene function and mechanisms that cause neuronal damage. In the future, the application of new genetic edition techniques would help to develop more accurate zebrafish models of dominant ataxias

Automated semantic annotation of rare disease cases: a case study

Motivation: As the number of clinical reports in the peer-reviewed medical literature keeps growing, there is an increasing need for online search tools to find and analyze publications on patients with similar clinical characteristics. This problem is especially critical and challenging for rare diseases, where publications of large series are scarce. Through an applied example, we illustrate how to automatically identify new relevant cases and semantically annotate the relevant literature about patient case reports to capture the phenotype of a rare disease named cerebrotendinous xanthomatosis. Results: Our results confirm that it is possible to automatically identify new relevant case reports with a high precision and to annotate them with a satisfactory quality (74% F-measure). Automated annotation with an emphasis to entirely describe all phenotypic abnormalities found in a disease may facilitate curation efforts by supplying phenotype retrieval and assessment of their frequencyNational Institute of Health Carlos III (grant no. FIS2012-PI12/00373: OntoNeurophen). Funding for open access charge: National Institute of Health Carlos III (grant no. FIS2012-PI12/00373)S

Automated semantic annotation of rare disease cases: a case study

MOTIVATION: As the number of clinical reports in the peer-reviewed medical literature keeps growing, there is an increasing need for online search tools to find and analyze publications on patients with similar clinical characteristics. This problem is especially critical and challenging for rare diseases, where publications of large series are scarce. Through an applied example, we illustrate how to automatically identify new relevant cases and semantically annotate the relevant literature about patient case reports to capture the phenotype of a rare disease named cerebrotendinous xanthomatosis. RESULTS: Our results confirm that it is possible to automatically identify new relevant case reports with a high precision and to annotate them with a satisfactory quality (74% F-measure). Automated annotation with an emphasis to entirely describe all phenotypic abnormalities found in a disease may facilitate curation efforts by supplying phenotype retrieval and assessment of their frequency. Availability and Supplementary information: http://www.usc.es/keam/Phenotype Annotation/. Database URL: http://www.usc.es/keam/PhenotypeAnnotation

Querying phenotype-genotype relationships on patient datasets using semantic web technology: the example of cerebrotendinous xanthomatosis

Background: Semantic Web technology can considerably catalyze translational genetics and genomics research in medicine, where the interchange of information between basic research and clinical levels becomes crucial. This exchange involves mapping abstract phenotype descriptions from research resources, such as knowledge databases and catalogs, to unstructured datasets produced through experimental methods and clinical practice. This is especially true for the construction of mutation databases. This paper presents a way of harmonizing abstract phenotype descriptions with patient data from clinical practice, and querying this dataset about relationships between phenotypes and genetic variants, at different levels of abstraction. Methods: Due to the current availability of ontological and terminological resources that have already reached some consensus in biomedicine, a reuse-based ontology engineering approach was followed. The proposed approach uses the Ontology Web Language (OWL) to represent the phenotype ontology and the patient model, the Semantic Web Rule Language (SWRL) to bridge the gap between phenotype descriptions and clinical data, and the Semantic Query Web Rule Language (SQWRL) to query relevant phenotype-genotype bidirectional relationships. The work tests the use of semantic web technology in the biomedical research domain named cerebrotendinous xanthomatosis (CTX), using a real dataset and ontologies. Results: A framework to query relevant phenotype-genotype bidirectional relationships is provided. Phenotype descriptions and patient data were harmonized by defining 28 Horn-like rules in terms of the OWL concepts. In total, 24 patterns of SWQRL queries were designed following the initial list of competency questions. As the approach is based on OWL, the semantic of the framework adapts the standard logical model of an open world assumption. Conclusions: This work demonstrates how semantic web technologies can be used to support flexible representation and computational inference mechanisms required to query patient datasets at different levels of abstraction. The open world assumption is especially good for describing only partially known phenotype-genotype relationships, in a way that is easily extensible. In future, this type of approach could offer researchers a valuable resource to infer new data from patient data for statistical analysis in translational research. In conclusion, phenotype description formalization and mapping to clinical data are two key elements for interchanging knowledge between basic and clinical research.The work presented in this paper has been developed in the funded national project Gestión de Terminologías Médicas para Arquetipos (TIN2009-14159-C05-05) by the Ministerio de Educación y Ciencia. This work was partly supported by the network REGENPSI (2009/019) from the Program of Consolidation and Structure of Competitive Units, Consellería de Educación e Ordenación Universitaria, Xunta de Galicia, and by FEDER funds for regional development. PNR was supported by a grant from the Deutsche Forschungsgemeinschaft (DFGRO2005/4-2)S

An ontology-aware integration of clinical models, terminologies and guidelines: an exploratory study of the Scale for the Assessment and Rating of Ataxia (SARA)

Background: Electronic rating scales represent an important resource for standardized data collection. However, the ability to exploit reasoning on rating scale data is still limited. The objective of this work is to facilitate the integration of the semantics required to automatically interpret collections of standardized clinical data. We developed an electronic prototype for the Scale of the Assessment and Rating of Ataxia (SARA), broadly used in neurology. In order to address the modeling challenges of the SARA, we propose to combine the best performances from OpenEHR clinical archetypes, guidelines and ontologies. Methods: A scaled-down version of the Human Phenotype Ontology (HPO) was built, extracting the terms that describe the SARA tests from free-text sources. This version of the HPO was then used as backbone to normalize the content of the SARA through clinical archetypes. The knowledge required to exploit reasoning on the SARA data was modeled as separate information-processing units interconnected via the defined archetypes. Each unit used the most appropriate technology to formally represent the required knowledge. Results: Based on this approach, we implemented a prototype named SARA Management System, to be used for both the assessment of cerebellar syndrome and the production of a clinical synopsis. For validation purposes, we used recorded SARA data from 28 anonymous subjects affected by Spinocerebellar Ataxia Type 36 (SCA36). When comparing the performance of our prototype with that of two independent experts, weighted kappa scores ranged from 0.62 to 0.86. Conclusions: The combination of archetypes, phenotype ontologies and electronic information-processing rules can be used to automate the extraction of relevant clinical knowledge from plain scores of rating scales. Our results reveal a substantial degree of agreement between the results achieved by an ontology-aware system and the human experts.This work presented in this paper was supported by the National Institute of Health Carlos III [grant no. FIS2012-PI12/00373: OntoNeurophen], FEDER for national and European funding; PEACE II, Erasmus Mundus Lot 2 Project [grant no. 2013-2443/001-001-EMA2]; and the Modern University for Business and Science (M.U.B.S)S

Characterizing the phenotype and mode of inheritance of patients with inherited peripheral neuropathies carrying MME mutations

[EN] Background Mutations in the metalloendopeptidase (MME) gene were initially identified as a cause of autosomal recessive Charcot-Marie-Tooth disease type 2 (CMT2). Subsequently, variants in MME were linked to other late-onset autosomal dominant polyneuropathies. Thus, our goal was to define the phenotype and mode of inheritance of patients carrying changes in MME. Methods We screened 197 index cases with a hereditary neuropathy of the CMT type or distal hereditary motor neuropathy (dHMN) and 10 probands with familial amyotrophic lateral sclerosis (fALS) using a custom panel of 119 genes. In addition to the index case subjects, we also studied other clinically and/or genetically affected and unaffected family members. Results We found 17 variants in MME in a total of 20 index cases, with biallelic MME mutations detected in 13 cases from nine families (three in homozygosis and six in compound heterozygosis) and heterozygous variants found in 11 families. All patients with biallelic variants had a similar phenotype, consistent with late-onset axonal neuropathy. Conversely, the phenotype of patients carrying heterozygous mutations was highly variable [CMT type 1 (CMT1), CMT2, dHMN and fALS] and mutations did not segregate with the disease. Conclusion MME mutations that segregate in an autosomal recessive pattern are associated with a late-onset CMT2 phenotype, yet we could not demonstrate that MME variants in heterozygosis cause neuropathy. Our data highlight the importance of establishing an accurate genetic diagnosis in patients carrying MME mutations, especially with a view to genetic counselling.The authors thank the patients and healthy relatives for having participated in this project. We are grateful to the Eurobiobank CIBERER and the Biobank La Fe for their participation in the collection and processing of patient samples. We also thank the technicians at the Department of Genomics and Translational Genetics (CIPF) who participated in the quality control and processing of DNA samples (Virginia Rejas and Laura Ramírez), and the Bachelor¿s thesis student Andrea Ballester who helped with some clinical data collection. This project was funded by the Instituto de Salud Carlos III (ISCIII), FEDER (Grants no. PI12/00946 and PI16/00403 to TS, PI15/00187 to CE). MF holds a grant funded by the IIS La Fe (Grant no. 2015/0085). AS-M holds a grant funded by the Fundació Per Amor a l'Art (FPAA). JFV-C holds a ' Rio Hortega' contract funded by the ISCIII.Lupo, V.; Frasquet, M.; Sánchez-Monteagudo, A.; Pelayo-Negro, A.; García-Sobrino, T.; Sedano, MJ.; Pardo, J.... (2018). Characterizing the phenotype and mode of inheritance of patients with inherited peripheral neuropathies carrying MME mutations. Journal of Medical Genetics. 55(12):814-823. https://doi.org/10.1136/jmedgenet-2018-105650814823551

Screening of CACNA1A and ATP1A2 genes in hemiplegic migraine: clinical, genetic and functional studies

Hemiplegic migraine (HM) is a rare and severe subtype of autosomal dominant migraine, characterized by a complex aura including some degree of motor weakness. Mutations in four genes (CACNA1A, ATP1A2, SCN1A and PRRT2) have been detected in familial and in sporadic cases. This genetically and clinically heterogeneous disorder is often accompanied by permanent ataxia, epileptic seizures, mental retardation, and chronic progressive cerebellar atrophy. Here we report a mutation screening in the CACNA1A and ATP1A2 genes in 18 patients with HM. Furthermore, intragenic copy number variant (CNV) analysis was performed in CACNA1A using quantitative approaches. We identified four previously described missense CACNA1A mutations (p.Ser218Leu, p.Thr501Met, p.Arg583Gln, and p.Thr666Met) and two missense changes in the ATP1A2 gene, the previously described p.Ala606Thr and the novel variant p.Glu825Lys. No structural variants were found. This genetic screening allowed the identification of more than 30% of the disease alleles, all present in a heterozygous state. Functional consequences of the CACNA1A-p.Thr501Met mutation, previously described only in association with episodic ataxia, and ATP1A2-p.Glu825Lys, were investigated by means of electrophysiological studies, cell viability assays or Western blot analysis. Our data suggest that both these variants are disease-causing

ClinPrior: an algorithm for diagnosis and novel gene discovery by network-based prioritization

BackgroundWhole-exome sequencing (WES) and whole-genome sequencing (WGS) have become indispensable tools to solve rare Mendelian genetic conditions. Nevertheless, there is still an urgent need for sensitive, fast algorithms to maximise WES/WGS diagnostic yield in rare disease patients. Most tools devoted to this aim take advantage of patient phenotype information for prioritization of genomic data, although are often limited by incomplete gene-phenotype knowledge stored in biomedical databases and a lack of proper benchmarking on real-world patient cohorts.MethodsWe developed ClinPrior, a novel method for the analysis of WES/WGS data that ranks candidate causal variants based on the patient's standardized phenotypic features (in Human Phenotype Ontology (HPO) terms). The algorithm propagates the data through an interactome network-based prioritization approach. This algorithm was thoroughly benchmarked using a synthetic patient cohort and was subsequently tested on a heterogeneous prospective, real-world series of 135 families affected by hereditary spastic paraplegia (HSP) and/or cerebellar ataxia (CA).ResultsClinPrior successfully identified causative variants achieving a final positive diagnostic yield of 70% in our real-world cohort. This includes 10 novel candidate genes not previously associated with disease, 7 of which were functionally validated within this project. We used the knowledge generated by ClinPrior to create a specific interactome for HSP/CA disorders thus enabling future diagnoses as well as the discovery of novel disease genes.ConclusionsClinPrior is an algorithm that uses standardized phenotype information and interactome data to improve clinical genomic diagnosis. It helps in identifying atypical cases and efficiently predicts novel disease-causing genes. This leads to increasing diagnostic yield, shortening of the diagnostic Odysseys and advancing our understanding of human illnesses

Mutations in SLC20A2 are a major cause of familial idiopathic basal ganglia calcification

Familial idiopathic basal ganglia calcification (IBGC) or Fahr's disease is a rare neurodegenerative disorder characterized by calcium deposits in the basal ganglia and other brain regions, which is associated with neuropsychiatric and motor symptoms. Familial IBGC is genetically heterogeneous and typically transmitted in an autosomal dominant fashion. We performed a mutational analysis of SLC20A2, the first gene found to cause IBGC, to assess its genetic contribution to familial IBGC. We recruited 218 subjects from 29 IBGC-affected families of varied ancestry and collected medical history, neurological exam, and head CT scans to characterize each patient's disease status. We screened our patient cohort for mutations in SLC20A2. Twelve novel (nonsense, deletions, missense, and splice site) potentially pathogenic variants, one synonymous variant, and one previously reported mutation were identified in 13 families. Variants predicted to be deleterious cosegregated with disease in five families. Three families showed nonsegregation with clinical disease of such variants, but retrospective review of clinical and neuroimaging data strongly suggested previous misclassification. Overall, mutations in SLC20A2 account for as many as 41 % of our familial IBGC cases. Our screen in a large series expands the catalog of SLC20A2 mutations identified to date and demonstrates that mutations in SLC20A2 are a major cause of familial IBGC. Non-perfect segregation patterns of predicted deleterious variants highlight the challenges of phenotypic assessment in this condition with highly variable clinical presentation