A Path to Implement Precision Child Health Cardiovascular Medicine.

Congenital heart defects (CHDs) affect approximately 1% of live births and are a major source of childhood morbidity and mortality even in countries with advanced healthcare systems. Along with phenotypic heterogeneity, the underlying etiology of CHDs is multifactorial, involving genetic, epigenetic, and/or environmental contributors. Clear dissection of the underlying mechanism is a powerful step to establish individualized therapies. However, the majority of CHDs are yet to be clearly diagnosed for the underlying genetic and environmental factors, and even less with effective therapies. Although the survival rate for CHDs is steadily improving, there is still a significant unmet need for refining diagnostic precision and establishing targeted therapies to optimize life quality and to minimize future complications. In particular, proper identification of disease associated genetic variants in humans has been challenging, and this greatly impedes our ability to delineate gene-environment interactions that contribute to the pathogenesis of CHDs. Implementing a systematic multileveled approach can establish a continuum from phenotypic characterization in the clinic to molecular dissection using combined next-generation sequencing platforms and validation studies in suitable models at the bench. Key elements necessary to advance the field are: first, proper delineation of the phenotypic spectrum of CHDs; second, defining the molecular genotype/phenotype by combining whole-exome sequencing and transcriptome analysis; third, integration of phenotypic, genotypic, and molecular datasets to identify molecular network contributing to CHDs; fourth, generation of relevant disease models and multileveled experimental investigations. In order to achieve all these goals, access to high-quality biological specimens from well-defined patient cohorts is a crucial step. Therefore, establishing a CHD BioCore is an essential infrastructure and a critical step on the path toward precision child health cardiovascular medicine

Role of intermediate filament desmin in development of desmin-related myopathy

Desmin is a major intermediate filament of muscle cells, serving to transmit mechanical forces and propagate mechanochemical signals, to coordinate contraction and relaxation cycles, and to stabilize the positioning of cellular organelles, e.g. mitochondria. Around 70 desmin gene mutations have been reported in conjunction with desmin-related myopathy. Desmin-related myopathy can be described as pathophysiological complex, accompanied by desmin intracellular aggregate accumulation and impairment of desmin interactions with structural proteins, signal molecules, and cell organelles. However, the precise molecular mechanism underlying desmin-related myopathy have not been described yet. There are speculations if it is connected with toxic effects of desmin aggregates or with violation of desmin mechanotransduction functions. The general aim of the present PhD project was to extend existing knowledge about the molecular machinery on how desmin gene mutations lead to the development of desmin-related myopathy, with an emphasis on development of cardiomyopathies. To address this aim the following research questions were stated: (i) genetic study of a group of patients with cardiomyopathies in order to describe novel mutations in the desmin gene, and to assess the frequency of DES A213V; (ii) genetic study by means of next-generation sequencing approach of a group of patients with idiopathic restrictive cardiomyopathy in order to describe novel genetic variants associated with disease; (iii) functional study of desmin gene point mutations effect on mitochondrial properties. The main findings regarding genetic background were: (i) DES A213V represents a disease-modifying polymorphism, rather than disease-related mutation, since it was found both in patients and healthy donors; (ii) combination of disease-related– disease-modifying or disease-related–disease-related genetic variants, rather than single disease-related mutation, determined the development of idiopathic restrictive cardiomyopathy. Most proteins of these combinations belonged to four functional groups: sarcomeric contractile proteins, mechanosensing Z-disc proteins, nuclear membrane, and outer mitochondrial membrane proteins. Functional studies of the impact of desmin mutations on mitochondria showed that aggregate-prone mutations decreased mitochondrial calcium uptake, as well as depressed maximal oxygen consumption rate and spare respiratory capacity. In contrast, non-aggregate-prone mutations did not disturb mitochondrial calcium. They did, however, result in the reduction of maximal oxygen consumption rate and affected spare respiratory capacity. To conclude, (i) distortion of desmin mechanotransduction functions plays an important role in desmin-related myopathy onset, affecting mitochondrial properties; (ii) combination of mutations in genes encoding sarcomeric contractile and mechanosensing proteins, rather than a single mutation, predisposes to the development of cardiomyopathy. These data facilitate understanding of molecular pathways underlying desmin-related myopathy development, and increase existing knowledge of intracellular interactions within the muscle cell

J Biomed Inform

Schizophrenia (SCZ) is a common complex disorder with poorly understood mechanisms and no effective drug treatments. Despite the high prevalence and vast unmet medical need represented by the disease, many drug companies have moved away from the development of drugs for SCZ. Therefore, alternative strategies are needed for the discovery of truly innovative drug treatments for SCZ. Here, we present a disease phenome-driven computational drug repositioning approach for SCZ. We developed a novel drug repositioning system, PhenoPredict, by inferring drug treatments for SCZ from diseases that are phenotypically related to SCZ. The key to PhenoPredict is the availability of a comprehensive drug treatment knowledge base that we recently constructed. PhenoPredict retrieved all 18 FDA-approved SCZ drugs and ranked them highly (recall=1.0, and average ranking of 8.49%). When compared to PREDICT, one of the most comprehensive drug repositioning systems currently available, in novel predictions, PhenoPredict represented clear improvements over PREDICT in Precision-Recall (PR) curves, with a significant 98.8% improvement in the area under curve (AUC) of the PR curves. In addition, we discovered many drug candidates with mechanisms of action fundamentally different from traditional antipsychotics, some of which had published literature evidence indicating their treatment benefits in SCZ patients. In summary, although the fundamental pathophysiological mechanisms of SCZ remain unknown, integrated systems approaches to studying phenotypic connections among diseases may facilitate the discovery of innovative SCZ drugs.20152016-08-01T00:00:00ZDP2 HD084068/HD/NICHD NIH HHS/United StatesDP2HD084068/DP/NCCDPHP CDC HHS/United StatesR25 CA094186/CA/NCI NIH HHS/United StatesR25 CA094186-06/CA/NCI NIH HHS/United StatesUL1 RR024989/RR/NCRR NIH HHS/United StatesUL1 TR000439/TR/NCATS NIH HHS/United States26151312PMC4589865875

A fruitful fly forward : the role of the fly in drug discovery for neurodegeneration

AD, Alzheimer’s disease; APP, amyloid precursor protein; BBB, blood brain barrier; GFP, green fluorescent protein; HTS, high-throughput screening; HD, Huntington’s disease; LB, Lewy bodies; PD, Parkinson’s disease; PolyQ, Polyglutamine; RNAi, RNA interference; SNCA, α-synuclein gene; UAS, Upstream Activating Sequence.peer-reviewe

Systematic reanalysis of partial trisomy 21 cases with or without Down syndrome suggests a small region on 21q22.13 as critical to the phenotype

A "Down Syndrome critical region" (DSCR) sufficient to induce the most constant phenotypes of Down syndrome (DS) had been identified by studying partial (segmental) trisomy 21 (PT21) as an interval of 0.6-8.3 Mb within human chromosome 21 (Hsa21), although its existence was later questioned. We propose an innovative, systematic reanalysis of all described PT21 cases (from 1973 to 2015). In particular, we built an integrated, comparative map from 125 cases with or without DS fulfilling stringent cytogenetic and clinical criteria. The map allowed to define or exclude as candidates for DS fine Hsa21 sequence intervals, also integrating duplication copy number variants (CNVs) data. A highly restricted DSCR (HR-DSCR) of only 34 kb on distal 21q22.13 has been identified as the minimal region whose duplication is shared by all DS subjects and is absent in all non-DS subjects. Also being spared by any duplication CNV in healthy subjects, HR-DSCR is proposed as a candidate for the typical DS features, the intellectual disability and some facial phenotypes. HR-DSCR contains no known gene and has relevant homology only to the chimpanzee genome. Searching for HR-DSCR functional loci might become a priority for understanding the fundamental genotype-phenotype relationships in DS

The Infectious Disease Ontology in the Age of COVID-19

The Infectious Disease Ontology (IDO) is a suite of interoperable ontology modules that aims to provide coverage of all aspects of the infectious disease domain, including biomedical research, clinical care, and public health. IDO Core is designed to be a disease and pathogen neutral ontology, covering just those types of entities and relations that are relevant to infectious diseases generally. IDO Core is then extended by a collection of ontology modules focusing on specific diseases and pathogens. In this paper we present applications of IDO Core within various areas of infectious disease research, together with an overview of all IDO extension ontologies and the methodology on the basis of which they are built. We also survey recent developments involving IDO, including the creation of IDO Virus; the Coronaviruses Infectious Disease Ontology (CIDO); and an extension of CIDO focused on COVID-19 (IDO-CovID-19).We also discuss how these ontologies might assist in information-driven efforts to deal with the ongoing COVID-19 pandemic, to accelerate data discovery in the early stages of future pandemics, and to promote reproducibility of infectious disease research

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.The National Science Foundation (IOS:1340112 to G.V.G.), the European Commission H2020 (grant agreement number 731075) to G.V.G. and the King Abdullah University of Science and Technology (to R.H.)

Development of bioinformatics tools and studies in biomedical association networks for the analysis of human genetic diseases

Fecha de lectura de Tesis Doctoral: 18 de marzo 2019.El presente trabajo de tesis doctoral se centra en el análisis en red y desarrollo de herramientas bioinformáticas para la determinación de las causas que dan lugar a las enfermedades con base genética. Mediante el análisis de sistemas de red se pueden asociar fenotipos patológicos y las regiones del genoma que potencialmente sean su causa a partir de información de pacientes. Estas asociaciones fenotipo-genotipo pueden emplearse para el desarrollo de herramientas de apoyo al diagnóstico genético de pacientes con un cuadro fenotípico complejo, de manera que puedan dar información sobre las regiones del genoma que potencialmente estén afectadas en un paciente a partir de sus fenotipos patológicos observados. Del mismo modo, estas regiones asociadas a fenotipos patológicos pueden analizarse para determinar los elementos funcionales del genoma que sean la causa de la enfermedad. Este análisis incluye tanto genes como elementos reguladores, ya que se ha demostrado que un 80% de las enfermedades caracterizadas mediante análisis del genoma completo han sido asociadas a regiones no codificantes del genoma, en las cuales se encuentran los elementos reguladores. Una vez determinados los elementos funcionales existentes en las regiones del genoma asociadas a fenotipos patológicos, se pueden determinar los sistemas biológicos que estén afectados en el paciente. Sin embargo, no todos los genes tienen anotaciones funcionales que muestren a qué sistemas afectan. Esta funcionalidad viene dada por el producto génico, las proteínas, que a su vez constan de dominios que les confieren su función y/o estructura. De nuevo, mediante análisis de red se pueden asociar dominios de proteínas con anotaciones funciones a partir de información de proteínas, con el fin de poder usar esas asociaciones dominio-función para predecir la posible función desconocida de proteínas en base a sus dominios