This document discusses using computational approaches to integrate animal and human phenotype data to identify candidate genes for orphan diseases and enable drug repurposing. It describes using ontologies to make phenotypes comparable across species and using semantic similarity to measure phenotypic similarity. Animal mutant phenotypes are compared to human disease phenotypes to find candidate genes. Pharmacogenomic databases are integrated to enable queries about drugs, genes, genotypes, diseases and pathways. Disease and drug pathways are identified using ontology enrichment analysis. The approach is evaluated using known gene-disease associations, showing it can prioritize candidate genes and predict drug-disease relationships.
This document discusses the automated generation of the Flora Phenotype Ontology (FLOPO) by extracting trait information from plant descriptions. It involves processing text from multiple floras to identify plant entities, qualities, and their relationships. The extracted information is then used to automatically generate and annotate classes in FLOPO, resulting in an ontology integrating plant traits across taxa and languages. Future work includes improving the annotation pipeline and linking FLOPO to genetic and environmental data for comparative analysis.
Ontology-based data access and semantic mining with Aber-OWLRobert Hoehndorf
Aber-OWL is an ontology repository and semantic mining tool that provides ontology-based access to biological data. It utilizes ontologies to integrate data from multiple sources and enrich incomplete data. Aber-OWL allows querying ontologies and data using SPARQL and identifies inconsistent descriptions. It also performs concept recognition in text by finding mentions of ontology classes in PubMed articles in less than 100ms. Aber-OWL aims to be a major ontology repository for biological data through improved interfaces and more expressive reasoning capabilities.
A translational medicine approach to orphan diseasesRobert Hoehndorf
The document discusses using animal models and computational analysis of phenotypes to study rare genetic diseases. It describes integrating human and animal disease phenotypes using ontologies to measure phenotypic similarity. This approach suggested HIP1 as a potential cause of Bassoe Syndrome based on similarities between the disease and HIP1 knockout mouse phenotypes. The approach provides candidates for experimental validation and future work includes integrating additional data sources.
Phenotype terminologies in use for genotype-phenotype databases: a common cor...Human Variome Project
The community needs to be provided with terminology standards in order to achieve interoperability between databases intended for clinical research and including description of phenotypes. This is crucial to interpret genomic rearrangements as well as future high-throughput sequence data. The aim of our work was to promote a core terminology of phenotypes interoperable with all the terminologies in use. Relevant terminologies in use by different communities to describe phenomes were cross–referenced: PhenoDB (2846 terms), London Dysmorphology Database (LDDB; 1318 terms), Orphanet (1243 terms), Human Phenotype Ontology (9895 terms, 22/08/2012), Elements of Morphology (AJMG; 423 terms), ICD10 (1230 terms), as well as medical terminologies in use: UMLS (7,957,179 distinct concept terms), SNOMED CT (>311,000 concepts), MeSH (26,853 concepts) and MedDRA (69,389 concepts). We established a strategy to compare them to find commonalities and differences, using ONAGUI as a tool to pick-up exact matches. The non-exact matches were verified manually by an expert. A core-terminology of 2,300 terms was derived and analysed by a panel of experts (International Consortium for Human Phenotype Terminologies – ICHPT). The resulting consensual terminology will be freely available in a dedicated website (www.ichpt.org) and mappings with other terminologies will be given in order to ease the interoperability between databases without disturbing the habits of the different groups of users.
PhenDisco is a new phenotype discovery system for the Database of Genotypes and Phenotypes (dbGaP) that aims to address challenges in searching and reusing data from dbGaP. It was developed based on user requirements analysis including surveys and interviews. PhenDisco standardizes phenotype variables and generates study metadata. It integrates natural language processing tools and an information model to map search queries to dbGaP. Studies are ranked using the BM25 algorithm. The system allows for more accurate, complete, and efficient searching of dbGaP to facilitate reuse of data.
My ontology is better than yours! Building and evaluating ontologies for inte...Robert Hoehndorf
The document discusses biomedical ontologies and their use in pharmacogenomics research. It introduces the concept of biomedical ontologies as controlled vocabularies that are hierarchically organized to facilitate data integration. Two relevant ontologies for representing phenotypes are discussed: the Mammalian Phenotype Ontology and the Human Phenotype Ontology. Challenges in using ontologies for pharmacogenomics research include comparing human and mouse phenotypes across species and determining how to compute phenotypic similarity based on the ontologies. The talk explores approaches to addressing these challenges.
A systematic approach to Genotype-Phenotype correlationsfisherp
It is increasingly common to combine Microarray and Quantitative Trait Loci data to aid the search for candidate genes responsible for phenotypic variation. Workflows provide a means of systematically processing these large datasets and also represent a framework for the re-use and the explicit declaration of experimental methods. Here we highlight the issues facing the manual analysis of microarray and QTL data for the discovery of candidate genes underlying complex phenotypes. We show how automated approaches provide a systematic means to investigate genotype-phenotype correlations. This methodology was applied to a use case of resistance to African trypanosomiasis in the mouse. Pathways represented in the results identified Daxx as one of the candidate genes within the Tir1 QTL region.
Use of semantic phenotyping to aid disease diagnosismhaendel
This document discusses using semantic phenotyping to aid disease diagnosis. It outlines using ontologies to semantically annotate phenotypes seen in patients, animal models, and genes. This allows computation of semantic similarity between phenotypes to identify potential disease candidates. The document also discusses challenges such as uneven phenotype data distribution and differences in how phenotypes are described across species. It proposes building an integrated cross-species semantic framework called Uberpheno to address these challenges and better leverage animal models for diagnosing rare diseases.
This document discusses the automated generation of the Flora Phenotype Ontology (FLOPO) by extracting trait information from plant descriptions. It involves processing text from multiple floras to identify plant entities, qualities, and their relationships. The extracted information is then used to automatically generate and annotate classes in FLOPO, resulting in an ontology integrating plant traits across taxa and languages. Future work includes improving the annotation pipeline and linking FLOPO to genetic and environmental data for comparative analysis.
Ontology-based data access and semantic mining with Aber-OWLRobert Hoehndorf
Aber-OWL is an ontology repository and semantic mining tool that provides ontology-based access to biological data. It utilizes ontologies to integrate data from multiple sources and enrich incomplete data. Aber-OWL allows querying ontologies and data using SPARQL and identifies inconsistent descriptions. It also performs concept recognition in text by finding mentions of ontology classes in PubMed articles in less than 100ms. Aber-OWL aims to be a major ontology repository for biological data through improved interfaces and more expressive reasoning capabilities.
A translational medicine approach to orphan diseasesRobert Hoehndorf
The document discusses using animal models and computational analysis of phenotypes to study rare genetic diseases. It describes integrating human and animal disease phenotypes using ontologies to measure phenotypic similarity. This approach suggested HIP1 as a potential cause of Bassoe Syndrome based on similarities between the disease and HIP1 knockout mouse phenotypes. The approach provides candidates for experimental validation and future work includes integrating additional data sources.
Phenotype terminologies in use for genotype-phenotype databases: a common cor...Human Variome Project
The community needs to be provided with terminology standards in order to achieve interoperability between databases intended for clinical research and including description of phenotypes. This is crucial to interpret genomic rearrangements as well as future high-throughput sequence data. The aim of our work was to promote a core terminology of phenotypes interoperable with all the terminologies in use. Relevant terminologies in use by different communities to describe phenomes were cross–referenced: PhenoDB (2846 terms), London Dysmorphology Database (LDDB; 1318 terms), Orphanet (1243 terms), Human Phenotype Ontology (9895 terms, 22/08/2012), Elements of Morphology (AJMG; 423 terms), ICD10 (1230 terms), as well as medical terminologies in use: UMLS (7,957,179 distinct concept terms), SNOMED CT (>311,000 concepts), MeSH (26,853 concepts) and MedDRA (69,389 concepts). We established a strategy to compare them to find commonalities and differences, using ONAGUI as a tool to pick-up exact matches. The non-exact matches were verified manually by an expert. A core-terminology of 2,300 terms was derived and analysed by a panel of experts (International Consortium for Human Phenotype Terminologies – ICHPT). The resulting consensual terminology will be freely available in a dedicated website (www.ichpt.org) and mappings with other terminologies will be given in order to ease the interoperability between databases without disturbing the habits of the different groups of users.
PhenDisco is a new phenotype discovery system for the Database of Genotypes and Phenotypes (dbGaP) that aims to address challenges in searching and reusing data from dbGaP. It was developed based on user requirements analysis including surveys and interviews. PhenDisco standardizes phenotype variables and generates study metadata. It integrates natural language processing tools and an information model to map search queries to dbGaP. Studies are ranked using the BM25 algorithm. The system allows for more accurate, complete, and efficient searching of dbGaP to facilitate reuse of data.
My ontology is better than yours! Building and evaluating ontologies for inte...Robert Hoehndorf
The document discusses biomedical ontologies and their use in pharmacogenomics research. It introduces the concept of biomedical ontologies as controlled vocabularies that are hierarchically organized to facilitate data integration. Two relevant ontologies for representing phenotypes are discussed: the Mammalian Phenotype Ontology and the Human Phenotype Ontology. Challenges in using ontologies for pharmacogenomics research include comparing human and mouse phenotypes across species and determining how to compute phenotypic similarity based on the ontologies. The talk explores approaches to addressing these challenges.
A systematic approach to Genotype-Phenotype correlationsfisherp
It is increasingly common to combine Microarray and Quantitative Trait Loci data to aid the search for candidate genes responsible for phenotypic variation. Workflows provide a means of systematically processing these large datasets and also represent a framework for the re-use and the explicit declaration of experimental methods. Here we highlight the issues facing the manual analysis of microarray and QTL data for the discovery of candidate genes underlying complex phenotypes. We show how automated approaches provide a systematic means to investigate genotype-phenotype correlations. This methodology was applied to a use case of resistance to African trypanosomiasis in the mouse. Pathways represented in the results identified Daxx as one of the candidate genes within the Tir1 QTL region.
Use of semantic phenotyping to aid disease diagnosismhaendel
This document discusses using semantic phenotyping to aid disease diagnosis. It outlines using ontologies to semantically annotate phenotypes seen in patients, animal models, and genes. This allows computation of semantic similarity between phenotypes to identify potential disease candidates. The document also discusses challenges such as uneven phenotype data distribution and differences in how phenotypes are described across species. It proposes building an integrated cross-species semantic framework called Uberpheno to address these challenges and better leverage animal models for diagnosing rare diseases.
The Application of the Human Phenotype Ontology mhaendel
Presented at the II International Summer School for Rare Disease and Orphan Drug Registries, September 15-19, 2014, Organized by the National Centre for Rare Diseases
Istituto Superiore di Sanità (ISS), Rome, Italy.
Note the extensive contribution by many consortium members and partners listed in the acknowledgements slide.
The document discusses using structured phenotype data to improve the interpretation and prioritization of candidate genes from exome sequencing data, particularly for undiagnosed diseases. It outlines current challenges in candidate gene prioritization based on phenotypes alone. It then describes how ontologies can be used to semantically represent and compare phenotypes across species to leverage knowledge from model organisms. The document presents results showing that combining phenotype data with variant data using a tool called PhenIX improves the ability to correctly prioritize candidate genes from exome data compared to using variant data alone. This demonstrates the utility of structured phenotype data for computational analysis of exomes to diagnose rare diseases.
The Human Phenotype Ontology (HPO) was developed to describe phenotypic abnormalities, aka, “deep phenotyping”, whereby symptoms and characteristic phenotypic findings (a phenotypic profile) are captured. The HPO has been utilized to great success for assisting computational phenotype comparison against known diseases, other patients, and model organisms to support diagnosis of rare disease patients. Clinicians and geneticists create phenotypic profiles based on clinical evaluation, but this is time consuming and can miss important phenotypic features. Patients are sometimes the best source of information about their symptoms that might otherwise be missed in a clinical encounter. However, HPO primarily use medical terminology, which can be difficult for patients and their families to understand. To make the HPO accessible to patients, we systematically added non-expert terminology (i.e., layperson terms) synonyms. Using semantic similarity, patient-recorded phenotypic profiles can be evaluated against those created clinically for undiagnosed patients to determine the improvement gained from the patient-driven phenotyping, as well as how much the patient phenotyping narrows the diagnosis. This patient-centric HPO can be utilized by all: in patient-centered rare disease websites, in patient community platforms and registries, or even to post one’s hard-to-diagnosed phenotypic profile on the Web.
Basic Formal Ontology (BFO) and DiseaseBarry Smith
The document discusses different approaches to conceptualizing health, disease, and biological kinds across multiple levels of granularity. It notes that traditional biology data conceptualized entities based on observable instances, while new biology data represents entities at the molecular level through genetic sequences. It argues that linking different kinds of phenomena represented at various levels requires annotation with terms from controlled vocabularies like ontologies. Ontologies provide a structured framework for integrating data across databases and supporting logical reasoning by standardizing references to biological entities, processes, and functions.
This document summarizes a study that evaluated the performance of different diagnostic tests for feline infectious peritonitis (FIP) in challenging clinical cases where the diagnosis was difficult. Twelve cats were included that were later confirmed or excluded from having FIP based on immunohistochemistry (IHC) or follow up. The study assessed tests performed in vivo and postmortem, including analysis of effusions, serum protein electrophoresis, anti-feline coronavirus serology, serum α1-acid glycoprotein concentration, and histopathology. Sensitivity, specificity, and concordance with the final diagnosis were calculated for each test. The test with the highest sensitivity and specificity was serum α1-acid glycoprotein concentration, while histopathology had
HIPBI-RD: Harmonising phenomics information for a better interoperability in ...Human Variome Project
Rare disease (RD) research is a field of medicine increasingly reliant on information technology, with the advent of low-cost whole-genome sequencing revolutionising the discovery of genetic causes of disorders. Detailed phenotype data, combined with genomic data, have an enormous potential to accelerate the identification of clinically actionable prognostic or therapeutic implications and to improve our understanding of RD. The harmonisation of phenomics information, including disorders and phenotype traits that are stored in different contexts in a non-standardised way, is a cornerstone for producing sound data to foster research.
HIPBI-RD («Harmonising phenomics information for a better interoperability in the rare disease field ») is a three-year project starting in 2016 funded via the E-Rare 3 ERA-NET. This project builds on three resources largely adopted by the RD community: Orphanet, its ontology ORDO (the Orphanet Rare Disease Ontology), HPO (the Human Phenotype Ontology) and PhenoTips, with the support of outstanding bio-ontologies players, the European Bioinformatics Institute and the Garvan Institute. The project aims to provide the community with an integrated, RD-specific bio-informatics ecosystem that will harmonse the way phenomics information is stored in databases and patient files worldwide, and thereby contribute to interoperability. This ecosystem will consist of a suite of tools and ontologies, optimised to work together, made available through commonly used software repositories.
The HIPBI-RD ecosystem will contribute to the interpretation of variants identified through exome and full genome sequencing by harmonising the way phenotypic information is collected, thus improving diagnostics. The ultimate goal of HIPBI-RD is to provide a resource that will contribute to bridging genome-scale biology and a disease-centered view on human pathobiology.
Acknowledgements:
This project has received funding from the European Union’s Horizon 2020 Research and Innovation Programme under the ERA-NET Cofund action N° 643578, E-Rare3. The project is co-funded by the French National Research Agency (ANR), the German Federal Ministry of Education and Research (BMBF), German Research Foundation (DFG), and the Canadian Institutes for Health Research (CIHR)
Integration of knowledge for personalized medicine: a pharmacogenomics case-s...Robert Hoehndorf
This document discusses integrating knowledge from pharmacogenomics databases to enable personalized medicine approaches. It describes using ontologies to integrate data on drugs, diseases, pathways, and genotypes from multiple sources. Queries over this integrated knowledge can discover disease and drug pathways and relationships between genotypes and drugs/diseases. The goal is to identify aberrant pathways underlying a disease and personalized treatment options based on a patient's gene expression profile. Future work includes expanding to interaction networks and experimental validation.
Integration of knowledge for personalized medicine: a pharmacogenomics...cancerdrg
This document discusses integrating knowledge from multiple data sources in pharmacogenomics to enable personalized medicine approaches. It describes using ontologies to integrate databases on drugs, genes, genotypes, diseases and pathways. Queries over this integrated knowledge can discover disease and drug pathways and relationships between genotypes and drug responses. The authors analyze gene expression data to identify aberrant pathways and candidate drugs for further study. Future work includes expanding the approach to interaction networks and experimental validation. The goal is to transform scientific discoveries into clinical applications to reduce disease burden through personalized treatment.
The document discusses erythropoietic protoporphyria (EPP), a rare blood disorder that can cause light sensitivity, anemia, and fatigue. Researchers from Boston Children's Hospital studied EPP and its symptoms. EPP is caused by a genetic mutation that leads to an excess of the chemical protoporphyrin in the blood and skin. While there is no cure, treatment aims to manage symptoms and improve quality of life. The disorder was proposed as a possible explanation for myths about vampires being sensitive to sunlight.
Fibromyalgia is a disorder characterized by widespread musculoskeletal pain accompanied by fatigue, sleep, memory and mood issues. Researchers believe fibromyalgia amplifies painful sensations by affecting how the brain processes pain signals. The document hypothesizes that the ApolipoproteinE (APOE) gene is the factor that makes siblings of parents with fibromyalgia susceptible to developing the disorder as well. Blood samples from individuals both with and without fibromyalgia will be collected and analyzed using PCR/RFLP techniques to identify the APOE gene and determine if it is present in siblings affected with fibromyalgia.
The first document summarizes a study comparing the usefulness of various diagnostic tests for feline infectious peritonitis (FIP), including analysis of effusions, serum protein electrophoresis, alpha1- acid glycoprotein (AGP), anti-FCoV serology, and immunohistochemistry. It found that AGP was the only test in complete concordance with immunohistochemistry, the gold standard, though more research is needed on AGP. The second document reviews options for treating hip dysplasia in dogs, including exercise restriction, weight control, analgesics, surgery such as triple pelvic osteotomy, and total hip replacement. It notes that more long-term studies are needed to evaluate treatment options.
This document provides an overview of the General Veterinary Pathology course (PATH-201). It outlines the course aims, objectives, topics covered, and textbooks recommended. The key goals of the course are to introduce students to common pathological terms, pathogens, and gross and microscopic lesions in animal tissues. Students will also learn about disease mechanisms and how to interpret lesions to assist clinicians with diagnosis. The document also defines several important pathology terms and concepts.
This document discusses pathology and methods in general and clinical pathology. It provides definitions of disease and death as basic notions in pathology. It also classifies pathogenic factors and discusses mechanisms of cellular injury, including depletion of ATP, damage to mitochondria, influx of calcium, accumulation of reactive oxygen species, and defects in membrane permeability. Autopsy and biopsy methods used in pathology are described.
Semantic phenotyping for disease diagnosis and discovery mhaendel
Here are a few things to consider about the patient's lower back pain over time:
- Acute vs chronic: Determine if the pain is a new onset (acute) or has been present long-term (chronic). The duration can provide clues.
- Progression: Note if the pain has gotten better, worse or stayed the same over time. Progression may indicate a more serious problem.
- Radiation: Document if the pain radiates anywhere (e.g. legs). Radiating pain can suggest nerve root involvement.
- Relieving/aggravating factors: Identify what makes the pain better or worse (e.g. activity, rest, position). This can help determine the
Enhancing Rare Disease Literature for Researchers and PatientsErin D. Foster
This document discusses efforts to enhance accessibility of rare disease literature for researchers and patients. It describes adding layperson synonyms to the Human Phenotype Ontology to help patients understand disease descriptions. Over 44% of existing synonyms were marked as layperson terms. The document also discusses a pilot project to annotate rare disease case reports with associated genes and phenotypes to identify the rarest cases and facilitate information sharing and community building. Next steps include further literature annotation and incorporating the data into databases. The overall goal is to improve dissemination of information on rare diseases.
Global Phenotypic Data Sharing Standards to Maximize Diagnostics and Mechanis...mhaendel
Presented at the IRDiRC 2017 conference in Paris, Feb 9th, 2017 (http://irdirc-conference.org/). This talk reviews use of the Human Phenotype Ontology for phenotype comparisons against other patients, known diseases, and animal models for diagnostic discovery. It also discusses the new Phenopackets Exchange mechanism for open phenotypic data sharing.
www.monarchinitiative.org
www.phenopackets.org
www.human-phenotype-ontology.org
Pathology is the study and diagnosis of disease. It has four main components: the cause or etiology, the mechanism of development/pathogenesis, structural alterations to cells (morphological changes), and the consequences of these changes (clinical manifestations). Pathology has evolved from autopsy and organ-based examination to cellular pathology and now utilizes various techniques including molecular pathology, genetics, immunology, and quantitative analysis. Key techniques used in pathology include autopsy, biopsy, cytology, animal experimentation, tissue/cell culture, histology, immunohistochemistry, electron microscopy, flow cytometry, image analysis, and molecular biology techniques like PCR and DNA sequencing.
Promoting Wellbeing - Applied Social Psychology - Psychology SuperNotesPsychoTech Services
A proprietary approach developed by bringing together the best of learning theories from Psychology, design principles from the world of visualization, and pedagogical methods from over a decade of training experience, that enables you to: Learn better, faster!
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The Application of the Human Phenotype Ontology mhaendel
Presented at the II International Summer School for Rare Disease and Orphan Drug Registries, September 15-19, 2014, Organized by the National Centre for Rare Diseases
Istituto Superiore di Sanità (ISS), Rome, Italy.
Note the extensive contribution by many consortium members and partners listed in the acknowledgements slide.
The document discusses using structured phenotype data to improve the interpretation and prioritization of candidate genes from exome sequencing data, particularly for undiagnosed diseases. It outlines current challenges in candidate gene prioritization based on phenotypes alone. It then describes how ontologies can be used to semantically represent and compare phenotypes across species to leverage knowledge from model organisms. The document presents results showing that combining phenotype data with variant data using a tool called PhenIX improves the ability to correctly prioritize candidate genes from exome data compared to using variant data alone. This demonstrates the utility of structured phenotype data for computational analysis of exomes to diagnose rare diseases.
The Human Phenotype Ontology (HPO) was developed to describe phenotypic abnormalities, aka, “deep phenotyping”, whereby symptoms and characteristic phenotypic findings (a phenotypic profile) are captured. The HPO has been utilized to great success for assisting computational phenotype comparison against known diseases, other patients, and model organisms to support diagnosis of rare disease patients. Clinicians and geneticists create phenotypic profiles based on clinical evaluation, but this is time consuming and can miss important phenotypic features. Patients are sometimes the best source of information about their symptoms that might otherwise be missed in a clinical encounter. However, HPO primarily use medical terminology, which can be difficult for patients and their families to understand. To make the HPO accessible to patients, we systematically added non-expert terminology (i.e., layperson terms) synonyms. Using semantic similarity, patient-recorded phenotypic profiles can be evaluated against those created clinically for undiagnosed patients to determine the improvement gained from the patient-driven phenotyping, as well as how much the patient phenotyping narrows the diagnosis. This patient-centric HPO can be utilized by all: in patient-centered rare disease websites, in patient community platforms and registries, or even to post one’s hard-to-diagnosed phenotypic profile on the Web.
Basic Formal Ontology (BFO) and DiseaseBarry Smith
The document discusses different approaches to conceptualizing health, disease, and biological kinds across multiple levels of granularity. It notes that traditional biology data conceptualized entities based on observable instances, while new biology data represents entities at the molecular level through genetic sequences. It argues that linking different kinds of phenomena represented at various levels requires annotation with terms from controlled vocabularies like ontologies. Ontologies provide a structured framework for integrating data across databases and supporting logical reasoning by standardizing references to biological entities, processes, and functions.
This document summarizes a study that evaluated the performance of different diagnostic tests for feline infectious peritonitis (FIP) in challenging clinical cases where the diagnosis was difficult. Twelve cats were included that were later confirmed or excluded from having FIP based on immunohistochemistry (IHC) or follow up. The study assessed tests performed in vivo and postmortem, including analysis of effusions, serum protein electrophoresis, anti-feline coronavirus serology, serum α1-acid glycoprotein concentration, and histopathology. Sensitivity, specificity, and concordance with the final diagnosis were calculated for each test. The test with the highest sensitivity and specificity was serum α1-acid glycoprotein concentration, while histopathology had
HIPBI-RD: Harmonising phenomics information for a better interoperability in ...Human Variome Project
Rare disease (RD) research is a field of medicine increasingly reliant on information technology, with the advent of low-cost whole-genome sequencing revolutionising the discovery of genetic causes of disorders. Detailed phenotype data, combined with genomic data, have an enormous potential to accelerate the identification of clinically actionable prognostic or therapeutic implications and to improve our understanding of RD. The harmonisation of phenomics information, including disorders and phenotype traits that are stored in different contexts in a non-standardised way, is a cornerstone for producing sound data to foster research.
HIPBI-RD («Harmonising phenomics information for a better interoperability in the rare disease field ») is a three-year project starting in 2016 funded via the E-Rare 3 ERA-NET. This project builds on three resources largely adopted by the RD community: Orphanet, its ontology ORDO (the Orphanet Rare Disease Ontology), HPO (the Human Phenotype Ontology) and PhenoTips, with the support of outstanding bio-ontologies players, the European Bioinformatics Institute and the Garvan Institute. The project aims to provide the community with an integrated, RD-specific bio-informatics ecosystem that will harmonse the way phenomics information is stored in databases and patient files worldwide, and thereby contribute to interoperability. This ecosystem will consist of a suite of tools and ontologies, optimised to work together, made available through commonly used software repositories.
The HIPBI-RD ecosystem will contribute to the interpretation of variants identified through exome and full genome sequencing by harmonising the way phenotypic information is collected, thus improving diagnostics. The ultimate goal of HIPBI-RD is to provide a resource that will contribute to bridging genome-scale biology and a disease-centered view on human pathobiology.
Acknowledgements:
This project has received funding from the European Union’s Horizon 2020 Research and Innovation Programme under the ERA-NET Cofund action N° 643578, E-Rare3. The project is co-funded by the French National Research Agency (ANR), the German Federal Ministry of Education and Research (BMBF), German Research Foundation (DFG), and the Canadian Institutes for Health Research (CIHR)
Integration of knowledge for personalized medicine: a pharmacogenomics case-s...Robert Hoehndorf
This document discusses integrating knowledge from pharmacogenomics databases to enable personalized medicine approaches. It describes using ontologies to integrate data on drugs, diseases, pathways, and genotypes from multiple sources. Queries over this integrated knowledge can discover disease and drug pathways and relationships between genotypes and drugs/diseases. The goal is to identify aberrant pathways underlying a disease and personalized treatment options based on a patient's gene expression profile. Future work includes expanding to interaction networks and experimental validation.
Integration of knowledge for personalized medicine: a pharmacogenomics...cancerdrg
This document discusses integrating knowledge from multiple data sources in pharmacogenomics to enable personalized medicine approaches. It describes using ontologies to integrate databases on drugs, genes, genotypes, diseases and pathways. Queries over this integrated knowledge can discover disease and drug pathways and relationships between genotypes and drug responses. The authors analyze gene expression data to identify aberrant pathways and candidate drugs for further study. Future work includes expanding the approach to interaction networks and experimental validation. The goal is to transform scientific discoveries into clinical applications to reduce disease burden through personalized treatment.
The document discusses erythropoietic protoporphyria (EPP), a rare blood disorder that can cause light sensitivity, anemia, and fatigue. Researchers from Boston Children's Hospital studied EPP and its symptoms. EPP is caused by a genetic mutation that leads to an excess of the chemical protoporphyrin in the blood and skin. While there is no cure, treatment aims to manage symptoms and improve quality of life. The disorder was proposed as a possible explanation for myths about vampires being sensitive to sunlight.
Fibromyalgia is a disorder characterized by widespread musculoskeletal pain accompanied by fatigue, sleep, memory and mood issues. Researchers believe fibromyalgia amplifies painful sensations by affecting how the brain processes pain signals. The document hypothesizes that the ApolipoproteinE (APOE) gene is the factor that makes siblings of parents with fibromyalgia susceptible to developing the disorder as well. Blood samples from individuals both with and without fibromyalgia will be collected and analyzed using PCR/RFLP techniques to identify the APOE gene and determine if it is present in siblings affected with fibromyalgia.
The first document summarizes a study comparing the usefulness of various diagnostic tests for feline infectious peritonitis (FIP), including analysis of effusions, serum protein electrophoresis, alpha1- acid glycoprotein (AGP), anti-FCoV serology, and immunohistochemistry. It found that AGP was the only test in complete concordance with immunohistochemistry, the gold standard, though more research is needed on AGP. The second document reviews options for treating hip dysplasia in dogs, including exercise restriction, weight control, analgesics, surgery such as triple pelvic osteotomy, and total hip replacement. It notes that more long-term studies are needed to evaluate treatment options.
This document provides an overview of the General Veterinary Pathology course (PATH-201). It outlines the course aims, objectives, topics covered, and textbooks recommended. The key goals of the course are to introduce students to common pathological terms, pathogens, and gross and microscopic lesions in animal tissues. Students will also learn about disease mechanisms and how to interpret lesions to assist clinicians with diagnosis. The document also defines several important pathology terms and concepts.
This document discusses pathology and methods in general and clinical pathology. It provides definitions of disease and death as basic notions in pathology. It also classifies pathogenic factors and discusses mechanisms of cellular injury, including depletion of ATP, damage to mitochondria, influx of calcium, accumulation of reactive oxygen species, and defects in membrane permeability. Autopsy and biopsy methods used in pathology are described.
Semantic phenotyping for disease diagnosis and discovery mhaendel
Here are a few things to consider about the patient's lower back pain over time:
- Acute vs chronic: Determine if the pain is a new onset (acute) or has been present long-term (chronic). The duration can provide clues.
- Progression: Note if the pain has gotten better, worse or stayed the same over time. Progression may indicate a more serious problem.
- Radiation: Document if the pain radiates anywhere (e.g. legs). Radiating pain can suggest nerve root involvement.
- Relieving/aggravating factors: Identify what makes the pain better or worse (e.g. activity, rest, position). This can help determine the
Enhancing Rare Disease Literature for Researchers and PatientsErin D. Foster
This document discusses efforts to enhance accessibility of rare disease literature for researchers and patients. It describes adding layperson synonyms to the Human Phenotype Ontology to help patients understand disease descriptions. Over 44% of existing synonyms were marked as layperson terms. The document also discusses a pilot project to annotate rare disease case reports with associated genes and phenotypes to identify the rarest cases and facilitate information sharing and community building. Next steps include further literature annotation and incorporating the data into databases. The overall goal is to improve dissemination of information on rare diseases.
Global Phenotypic Data Sharing Standards to Maximize Diagnostics and Mechanis...mhaendel
Presented at the IRDiRC 2017 conference in Paris, Feb 9th, 2017 (http://irdirc-conference.org/). This talk reviews use of the Human Phenotype Ontology for phenotype comparisons against other patients, known diseases, and animal models for diagnostic discovery. It also discusses the new Phenopackets Exchange mechanism for open phenotypic data sharing.
www.monarchinitiative.org
www.phenopackets.org
www.human-phenotype-ontology.org
Pathology is the study and diagnosis of disease. It has four main components: the cause or etiology, the mechanism of development/pathogenesis, structural alterations to cells (morphological changes), and the consequences of these changes (clinical manifestations). Pathology has evolved from autopsy and organ-based examination to cellular pathology and now utilizes various techniques including molecular pathology, genetics, immunology, and quantitative analysis. Key techniques used in pathology include autopsy, biopsy, cytology, animal experimentation, tissue/cell culture, histology, immunohistochemistry, electron microscopy, flow cytometry, image analysis, and molecular biology techniques like PCR and DNA sequencing.
Promoting Wellbeing - Applied Social Psychology - Psychology SuperNotesPsychoTech Services
A proprietary approach developed by bringing together the best of learning theories from Psychology, design principles from the world of visualization, and pedagogical methods from over a decade of training experience, that enables you to: Learn better, faster!
- Video recording of this lecture in English language: https://youtu.be/kqbnxVAZs-0
- Video recording of this lecture in Arabic language: https://youtu.be/SINlygW1Mpc
- Link to download the book free: https://nephrotube.blogspot.com/p/nephrotube-nephrology-books.html
- Link to NephroTube website: www.NephroTube.com
- Link to NephroTube social media accounts: https://nephrotube.blogspot.com/p/join-nephrotube-on-social-media.html
Muktapishti is a traditional Ayurvedic preparation made from Shoditha Mukta (Purified Pearl), is believed to help regulate thyroid function and reduce symptoms of hyperthyroidism due to its cooling and balancing properties. Clinical evidence on its efficacy remains limited, necessitating further research to validate its therapeutic benefits.
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Osteoporosis is an increasing cause of morbidity among the elderly.
In this document , a brief outline of osteoporosis is given , including the risk factors of osteoporosis fractures , the indications for testing bone mineral density and the management of osteoporosis
Rasamanikya is a excellent preparation in the field of Rasashastra, it is used in various Kushtha Roga, Shwasa, Vicharchika, Bhagandara, Vatarakta, and Phiranga Roga. In this article Preparation& Comparative analytical profile for both Formulationon i.e Rasamanikya prepared by Kushmanda swarasa & Churnodhaka Shodita Haratala. The study aims to provide insights into the comparative efficacy and analytical aspects of these formulations for enhanced therapeutic outcomes.
These lecture slides, by Dr Sidra Arshad, offer a simplified look into the mechanisms involved in the regulation of respiration:
Learning objectives:
1. Describe the organisation of respiratory center
2. Describe the nervous control of inspiration and respiratory rhythm
3. Describe the functions of the dorsal and respiratory groups of neurons
4. Describe the influences of the Pneumotaxic and Apneustic centers
5. Explain the role of Hering-Breur inflation reflex in regulation of inspiration
6. Explain the role of central chemoreceptors in regulation of respiration
7. Explain the role of peripheral chemoreceptors in regulation of respiration
8. Explain the regulation of respiration during exercise
9. Integrate the respiratory regulatory mechanisms
10. Describe the Cheyne-Stokes breathing
Study Resources:
1. Chapter 42, Guyton and Hall Textbook of Medical Physiology, 14th edition
2. Chapter 36, Ganong’s Review of Medical Physiology, 26th edition
3. Chapter 13, Human Physiology by Lauralee Sherwood, 9th edition
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These lecture slides, by Dr Sidra Arshad, offer a quick overview of the physiological basis of a normal electrocardiogram.
Learning objectives:
1. Define an electrocardiogram (ECG) and electrocardiography
2. Describe how dipoles generated by the heart produce the waveforms of the ECG
3. Describe the components of a normal electrocardiogram of a typical bipolar lead (limb II)
4. Differentiate between intervals and segments
5. Enlist some common indications for obtaining an ECG
6. Describe the flow of current around the heart during the cardiac cycle
7. Discuss the placement and polarity of the leads of electrocardiograph
8. Describe the normal electrocardiograms recorded from the limb leads and explain the physiological basis of the different records that are obtained
9. Define mean electrical vector (axis) of the heart and give the normal range
10. Define the mean QRS vector
11. Describe the axes of leads (hexagonal reference system)
12. Comprehend the vectorial analysis of the normal ECG
13. Determine the mean electrical axis of the ventricular QRS and appreciate the mean axis deviation
14. Explain the concepts of current of injury, J point, and their significance
Study Resources:
1. Chapter 11, Guyton and Hall Textbook of Medical Physiology, 14th edition
2. Chapter 9, Human Physiology - From Cells to Systems, Lauralee Sherwood, 9th edition
3. Chapter 29, Ganong’s Review of Medical Physiology, 26th edition
4. Electrocardiogram, StatPearls - https://www.ncbi.nlm.nih.gov/books/NBK549803/
5. ECG in Medical Practice by ABM Abdullah, 4th edition
6. Chapter 3, Cardiology Explained, https://www.ncbi.nlm.nih.gov/books/NBK2214/
7. ECG Basics, http://www.nataliescasebook.com/tag/e-c-g-basics
Cell Therapy Expansion and Challenges in Autoimmune DiseaseHealth Advances
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In addition to infrastructure and capacity constraints, CAR-Ts face a very different risk-benefit dynamic in autoimmune compared to oncology, highlighting the need for tolerable therapies with low adverse event risk. CAR-NK and Treg-based therapies are also being developed in certain autoimmune disorders and may demonstrate favorable safety profiles. Several novel non-cell therapies such as bispecific antibodies, nanobodies, and RNAi drugs, may also offer future alternative competitive solutions with variable value propositions.
Widespread adoption of cell therapies will not only require strong efficacy and safety data, but also adapted pricing and access strategies. At oncology-based price points, CAR-Ts are unlikely to achieve broad market access in autoimmune disorders, with eligible patient populations that are potentially orders of magnitude greater than the number of currently addressable cancer patients. Developers have made strides towards reducing cell therapy COGS while improving manufacturing efficiency, but payors will inevitably restrict access until more sustainable pricing is achieved.
Despite these headwinds, industry leaders and investors remain confident that cell therapies are poised to address significant unmet need in patients suffering from autoimmune disorders. However, the extent of this impact on the treatment landscape remains to be seen, as the industry rapidly approaches an inflection point.
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We’re talking about Vedic Meditation, a form of meditation that has been around for at least 5,000 years. Back then, the people who lived in the Indus Valley, now known as India and Pakistan, practised meditation as a fundamental part of daily life. This knowledge that has given us yoga and Ayurveda, was known as Veda, hence the name Vedic. And though there are some written records, the practice has been passed down verbally from generation to generation.
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Integrative and translational analysis of the phenome
1. Introduction Animal and disease phenotypes Pharmacogenomics Pathways Summary
Integrative and translational analysis of the
phenome
Robert Hoehndorf
Department of Physiology, Development and Neuroscience
University of Cambridge
26 September 2012
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3. Introduction Animal and disease phenotypes Pharmacogenomics Pathways Summary
Translational research
National Cancer Institute:
Translational research transforms scientific discoveries arising from
laboratory, clinical, or population studies into clinical applications
to reduce [disease] incidence, morbidity, and mortality.
4.
5.
6. Introduction Animal and disease phenotypes Pharmacogenomics Pathways Summary
Genetic diseases
Almost 4,000 genetic diseases in OMIM have an unknown molecular basis.
7. Introduction Animal and disease phenotypes Pharmacogenomics Pathways Summary
Genetic diseases
OrphaNet
5,917 orphan diseases
2,543 genes linked to 2,544 diseases
2,700 diseases indexed with clinical signs
8. Introduction Animal and disease phenotypes Pharmacogenomics Pathways Summary
Genetic diseases
Animal models have been shown to be highly successful in studying human disease
9. Introduction Animal and disease phenotypes Pharmacogenomics Pathways Summary
Approach
Can we use phenotypes of mutant animal organisms to find
candidate genes for orphan diseases?
10. Introduction Animal and disease phenotypes Pharmacogenomics Pathways Summary
Approach
Can we use phenotypes of mutant animal organisms to find
candidate genes for orphan diseases?
1 make animal and human phenotypes comparable
2 systematically analyze the phenome for possible causative
mutations
3 evaluate using real biomedical data
11. Introduction Animal and disease phenotypes Pharmacogenomics Pathways Summary
Genetic diseases
PATO and the EQ method enable the integration of phenotype ontologies across species.
use of Entity-Quality definitions
homologous anatomical structures
integration based on species-independent ontologies
Gene Ontology
ChEBI, Protein ontology, Celltype ontology
12. Introduction Animal and disease phenotypes Pharmacogenomics Pathways Summary
Genetic diseases
Integration of phenotypes enables direct comparison between species
Proximal fibular overgrowth
Abnormal fibula morphology
(HPO):
(MP):
E: Proximal epiphysis of
E: fibula (MA)
fibula (FMA)
Q: morphology (abnormal)
Q: hypertrophic
UBERON: fibula (MA) orthologous to Fibula (FMA)
FMA: Proximal epiphysis of fibula part-of Fibula
PATO: hypertrophic is-a morphology
Proximal fibular overgrowth is-a Abnormal fibula morphology
13. Introduction Animal and disease phenotypes Pharmacogenomics Pathways Summary
Genetic diseases
Experimental data can be integrated through ontologies and explored using automated
reasoning.
integration of phenotype ontologies
yeast, fly, slime mold, worm, fish, mouse, rat, human
ontology-based integration of phenotypes
mutant phenotypes for yeast, fly, slime mold, worm, fish,
mouse, rat
human disease phenotypes from OMIM and OrphaNet
OWL ontology with more than 500,000 classes
OWL reasoner reveals connections between phenotypes
14. Introduction Animal and disease phenotypes Pharmacogenomics Pathways Summary
Genetic diseases
Semantic similarity over phenotype ontologies measures phenotypic similarity.
semantic similarity: metric based on information contained in
the axioms of an ontology
pairwise comparison of disease and animal phenotypes
IC (x)
x∈Cl(P)∩Cl(D)
sim(P, D) =
IC (y )
y ∈Cl(P)∪Cl(D)
15. Introduction Animal and disease phenotypes Pharmacogenomics Pathways Summary
Genetic diseases
Similarity-based comparison
Evaluation against known gene–disease associations:
OMIM
MGI
OrphaNet
24. Introduction Animal and disease phenotypes Pharmacogenomics Pathways Summary
Bassoe Syndrome
Computational analysis of mouse phenotypes provides a strong
indication that HIP1 may be involved in Bassoe syndrome.
27. Introduction Animal and disease phenotypes Pharmacogenomics Pathways Summary
Question
Is there a similarity between a knock-out/knock-down of a gene
(through targeted mutation) and the inhibition/negative regulation
of a gene (through a drug action)?
28.
29. Introduction Animal and disease phenotypes Pharmacogenomics Pathways Summary
PhenomeNET compares phenotypes across species
30. Introduction Animal and disease phenotypes Pharmacogenomics Pathways Summary
Statistical testing to rank drug–disease pairs
one-sided Wilcoxon signed rank test
result: ranking of drugs for each disease based on p-value
31. Introduction Animal and disease phenotypes Pharmacogenomics Pathways Summary
Phenotype-based comparison can provide some information
about drug indications
PhenomeDrug improved
1
0.9
0.8
0.7
AUC (CTD): 0.61
True Positive Rate
0.6
AUC (FDA): 0.67
0.5
0.4
0.3
0.2
0.1 x
original
latest
0
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
False Positive Rate
32. Introduction Animal and disease phenotypes Pharmacogenomics Pathways Summary
Future: phenotype-based drug repurposing
similarity between inhibition (drug action) and
knock-out/knock-down (mutation)
effects
indications
targets
combination with interaction networks
D inhibits G1 and G1 positively regulated G2 ⇒ D inhibits G2 .
drug pathways
pharmacodynamics
pharmacokinetics
physiological pathways
34. Introduction Animal and disease phenotypes Pharmacogenomics Pathways Summary
Aims: queries and integrated analysis
integrate and query knowledge in pharmacogenomics
identify aberrant pathways and patho-physiology underlying
disease
identify drug pathways (pharmacokinetics and
pharmacodynamics)
personalized treatment and dosage guidelines
35. Introduction Animal and disease phenotypes Pharmacogenomics Pathways Summary
Approach to data integration in pharmacogenomics
integration of databases containing drug, gene, genotype,
disease and pathway information
DrugBank: drugs and drugs targets
PharmGKB: genotype and drug response
Pathway Interaction Database: biological pathways
CTD: toxicogenomics information (chemical–gene–disease)
36. Introduction Animal and disease phenotypes Pharmacogenomics Pathways Summary
Queries
What drugs can be used to treat parasitic infectious diseases
(DOID:1398)?
Chloroquine
Arthemeter
...
37. Introduction Animal and disease phenotypes Pharmacogenomics Pathways Summary
Queries
What drugs are effective for diseases affecting the joints
(FMA:7490)?
Folic acid (for arthritis)
Chloroquine (for Chikungunya virus)
...
38. Introduction Animal and disease phenotypes Pharmacogenomics Pathways Summary
Queries
What genotypes are related to diseases affecting the joints
(FMA:7490)?
RSID:rs70991108 (with arthritis)
RSID:rs1207421 (Osteoarthritis, Knee)
...
39. Introduction Animal and disease phenotypes Pharmacogenomics Pathways Summary
Queries
What genotypes are related to response to steroids
(CHEBI:35341)?
RSID:rs45566039 (with estrogen)
RSID:rs1042713 (with budesonide)
...
40. Introduction Animal and disease phenotypes Pharmacogenomics Pathways Summary
Disease and drug pathways
Ontology enrichment analysis can identify over-represented ontology classes.
ontology-based, statistical approach to identify drug and
disease pathways
use graph structure of ontology to identify statistically over-
and under-represented ontology classes
aims:
identify over-represented disease classes (in disease ontology)
for genes in a pathway (disease pathways)
identify over-represented chemical classes (from chemical
ontology) for genes in a pathway (drug pathways)
41. Introduction Animal and disease phenotypes Pharmacogenomics Pathways Summary
Disease and drug pathways
OntoFUNC enables enrichment analyses over OWL ontologies.
OntoFUNC: http://ontofunc.googlecode.com
based on FUNC (http://func.eva.mpg.de)
supports
hypergeometric test
Wilcoxon rank test
binomial test
McDonaldKreitman (2x2 contingency) test
correction for multiple testing (FWER, FDR)
42. Introduction Animal and disease phenotypes Pharmacogenomics Pathways Summary
Disease and drug pathways
OntoFUNC identifies disease classes that are enriched in pathways.
hypergeometric test over Disease Ontology
genes participating in pathway P vs. all other genes
carcinosarcoma (DOID:4236) and Zidovudine Pathway
(PharmGKB:PA165859361) (p < 10−10 ).
mood disorder (DOID:3324) and Zidovudine Pathway
(PharmGKB:PA165859361) (p < 0.01).
(All results at http://pharmgkb-owl.googlecode.com)
43.
44.
45.
46. Species Inferred p-value
Fish 1717 0.240
Yeast 14047 0.162
Fly 1633 0.041
Worm 9221 0.003
Mouse 15693 7 · 10−5
D. dario D. melanogaster S. cerevisiae
1 1 1
0.9 0.9 0.9
0.8 0.8 0.8
0.7 0.7 0.7
True Positive Rate
True Positive Rate
True Positive Rate
0.6 0.6 0.6
0.5 0.5 0.5
0.4 0.4 0.4
0.3 0.3 0.3
0.2 0.2 0.2
0.1 original 0.1 original 0.1 original
new new new
x x x
0 0 0
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
False Positive Rate False Positive Rate False Positive Rate
M. musculus C. elegans
1 1
0.9 0.9
0.8 0.8
0.7 0.7
True Positive Rate
True Positive Rate
0.6 0.6
0.5 0.5
0.4 0.4
0.3 0.3
0.2 0.2
0.1 original 0.1 original
new new
x x
0 0
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
False Positive Rate False Positive Rate
47.
48. Introduction Animal and disease phenotypes Pharmacogenomics Pathways Summary
Summary
Ontologies can be used to enable integrative biology.
1 integration of ontologies
2 integration of data through ontologies
3 ontology-based data analysis
semantic similarity
statistical tests
graph-/network-based algorithms
4 quantitative evaluation on real biological data
49. Introduction Animal and disease phenotypes Pharmacogenomics Pathways Summary
Acknowledgements
George Gkoutos
Pierre Grenon
Paul Schofield
Midori Harris
Michel Dumontier
Pascal Hitzler
Heinrich Herre
Simon Jupp
Janet Kelso
Frank Loebe
Dietrich
Kay Pruefer
Rebholz-Schuhmann
Gabrielle Rustici
Dan Cook
Stefan Schulz
John Gennari
Robert Stevens
Anika Oellrich
Sarala Wimalaratne
Nico Adams
...
Bernard de Bono