Robert Freimuth | Mayo Clinic (original) (raw)
Papers by Robert Freimuth
Journal of Biomedical Informatics, 2016
Genomics is a promising tool that is becoming more widely available to improve the care and treat... more Genomics is a promising tool that is becoming more widely available to improve the care and treatment of individuals. While there is much assertion, genomics will most certainly require the use of clinical decision support (CDS) to be fully realized in the routine clinical setting. The National Human Genome Research Institute (NHGRI) of the National Institutes of Health recently convened an in-person, multi-day meeting on this topic. It was widely recognized that there is a need to promote the innovation and development of resources for genomic CDS such as a CDS sandbox. The purpose of this study was to evaluate a proposed approach for such a genomic CDS sandbox among domain experts and potential users. Survey results indicate a significant interest and desire for a genomic CDS sandbox environment among domain experts. These results will be used to guide the development of a genomic CDS sandbox.
Journal of the American Medical Informatics Association, 2016
The American Medical Informatics Association convened the 2014 Health Policy Invitational Meeting... more The American Medical Informatics Association convened the 2014 Health Policy Invitational Meeting to develop recommendations for updates to current policies and to establish an informatics research agenda for personalizing medicine. In particular, the meeting focused on discussing informatics challenges related to personalizing care through the integration of genomic or other high-volume biomolecular data with data from clinical systems to make health care more efficient and effective. This report summarizes the findings (n = 6) and recommendations (n = 15) from the policy meeting, which were clustered into 3 broad areas: (1) policies governing data access for research and personalization of care; (2) policy and research needs for evolving data interpretation and knowledge representation; and (3) policy and research needs to ensure data integrity and preservation. The meeting outcome underscored the need to address a number of important policy and technical considerations in order to realize the potential of personalized or precision medicine in actual clinical contexts.
Journal of Biomedical Informatics, 2016
Genomics is a promising tool that is becoming more widely available to improve the care and treat... more Genomics is a promising tool that is becoming more widely available to improve the care and treatment of individuals. While there is much assertion, genomics will most certainly require the use of clinical decision support (CDS) to be fully realized in the routine clinical setting. The National Human Genome Research Institute (NHGRI) of the National Institutes of Health recently convened an in-person, multi-day meeting on this topic. It was widely recognized that there is a need to promote the innovation and development of resources for genomic CDS such as a CDS sandbox. The purpose of this study was to evaluate a proposed approach for such a genomic CDS sandbox among domain experts and potential users. Survey results indicate a significant interest and desire for a genomic CDS sandbox environment among domain experts. These results will be used to guide the development of a genomic CDS sandbox.
Amia Joint Summits on Translational Science Proceedings Amia Summit on Translational Science, 2013
The purpose of this paper is to describe pilot work on a semantic model of the pharmacogenomics i... more The purpose of this paper is to describe pilot work on a semantic model of the pharmacogenomics information found in drug product labels. The model's development is driven by a series of use cases that we have developed to demonstrate how structured pharmacogenomics information could be more effectively used to support clinical and translational efforts. Using an iterative process, the semantic model was field-tested by five pharmacists, who used it to manually annotate a subset of the sections that the Food and Drug Administration's Pharmacogenomic Biomarkers in Drug Labels cites as containing pharmacogenomics information. The five pharmacists identified a total of 213 pharmacogenomics statements in 29 sections. The model showed the potential to make the unstructured pharmacogenomic information currently written in product labeling more accessible and actionable through structured annotations of pharmacogenomics effects and clinical recommendations.
Pharmacogenomics, 2015
Many currently available pharmacogenomic assays and algorithms interrogate a set of 'tag&... more Many currently available pharmacogenomic assays and algorithms interrogate a set of 'tag' polymorphisms for inferring haplotypes. We wanted to test the accuracy of such haplotype inferences across different populations. We simulated haplotype inferences made by existing pharmacogenomic assays for seven important pharmacogenes based on full genome data of 2504 persons in the 1000 Genomes dataset. A sizable fraction of samples did not match any of the haplotypes in the star allele nomenclature systems. We found no clear population bias in the accuracy of results of simulated assays. Haplotype nomenclatures and inference algorithms need to be improved to adequately capture pharmacogenomic diversity in human populations.
Clinical pharmacology and therapeutics, Jan 19, 2015
This manuscript provides nomenclature recommendations developed by an international workgroup to ... more This manuscript provides nomenclature recommendations developed by an international workgroup to increase transparency and standardization of pharmacogenetic (PGx) result reporting. Presently, sequence variants identified by PGx tests are described using different nomenclature systems. In addition, PGx analysis may detect different sets of variants for each gene, which can affect interpretation of results. This practice has caused confusion and may thereby impede the adoption of clinical PGx testing. Standardization is critical to move PGx forward. This article is protected by copyright. All rights reserved.
Journal of Pathology Informatics, 2015
Genomic, proteomic, epigenomic, and other &am... more Genomic, proteomic, epigenomic, and other "omic" data have the potential to enable precision medicine, also commonly referred to as personalized medicine. The volume and complexity of omic data are rapidly overwhelming human cognitive capacity, requiring innovative approaches to translate such data into patient care. Here, we outline a conceptual model for the application of omic data in the clinical context, called "the omic funnel." This model parallels the classic "Data, Information, Knowledge, Wisdom pyramid" and adds context for how to move between each successive layer. Its goal is to allow informaticians, researchers, and clinicians to approach the problem of translating omic data from bench to bedside, by using discrete steps with clearly defined needs. Such an approach can facilitate the development of modular and interoperable software that can bring precision medicine into widespread practice.
Journal of the American Medical Informatics Association : JAMIA, Jan 3, 2015
Clinicians' ability to use and interpret genetic information depends upon how those data are ... more Clinicians' ability to use and interpret genetic information depends upon how those data are displayed in electronic health records (EHRs). There is a critical need to develop systems to effectively display genetic information in EHRs and augment clinical decision support (CDS). The National Institutes of Health (NIH)-sponsored Clinical Sequencing Exploratory Research and Electronic Medical Records & Genomics EHR Working Groups conducted a multiphase, iterative process involving working group discussions and 2 surveys in order to determine how genetic and genomic information are currently displayed in EHRs, envision optimal uses for different types of genetic or genomic information, and prioritize areas for EHR improvement. There is substantial heterogeneity in how genetic information enters and is documented in EHR systems. Most institutions indicated that genetic information was displayed in multiple locations in their EHRs. Among surveyed institutions, genetic information ent...
AMIA Joint Summits on Translational Science proceedings AMIA Summit on Translational Science, 2013
The Pharmacogenomics Knowledge Base (PharmGKB) [1] is a publicly available central resource for p... more The Pharmacogenomics Knowledge Base (PharmGKB) [1] is a publicly available central resource for pharmacogenomics data and knowledge, which is being widely employed into clinical practice and thus requires using clinical terminologies. Hence, harmonizing PharmGKB drug data with well annotated drug terminologies will facilitate its integration with other related resources and support data representation, interpretation, and exchange within and across heterogeneous sources and applications. In this study, we extracted drug and drug class from PharmGKB, and mapped them to National Drug File Reference Terminology (NDF-RT) [2], which is integrated into RxNorm specified by U.S. Meaningful Use regulations. And the evaluated mapping results will be provided to PharmGKB for further investigation and collaboration.
AMIA Joint Summits on Translational Science proceedings AMIA Summit on Translational Science, 2013
Structured Product Labels (SPLs) contain information about drugs that can be valuable to clinical... more Structured Product Labels (SPLs) contain information about drugs that can be valuable to clinical and translational research, especially if it can be linked to other sources that provide data about drug targets, chemical properties, interactions, and biological pathways. Unfortunately, SPLs currently provide coarsely-structured drug information and lack the detailed annotation that is required to support computational use cases. To help address this issue we created LinkedSPLs, a Linked Data resource that extends the "web of drug identity" using information extracted from SPLs. In this paper we describe the mapping that LinkedSPLs provides between SPL active ingredients and DrugBank chemical entities. These mappings were created using three approaches: InChI chemical structure descriptors comparison, exact string matching based on the chemical name, and automatic (unsupervised) linkage identification. Comparison of the approaches found that, while these three approaches ar...
AMIA Joint Summits on Translational Science proceedings AMIA Summit on Translational Science, 2013
The purpose of this paper is to describe pilot work on a semantic model of the pharmacogenomics i... more The purpose of this paper is to describe pilot work on a semantic model of the pharmacogenomics information found in drug product labels. The model's development is driven by a series of use cases that we have developed to demonstrate how structured pharmacogenomics information could be more effectively used to support clinical and translational efforts. Using an iterative process, the semantic model was field-tested by five pharmacists, who used it to manually annotate a subset of the sections that the Food and Drug Administration's Table of Pharmacogenomic Biomarkers in Drug Labels cites as containing pharmacogenomics information. The five pharmacists identified a total of 213 pharmacogenomics statements in 29 sections. The model showed the potential to make the unstructured pharmacogenomic information currently written in product labeling more accessible and actionable through structured annotations of pharmacogenomics effects and clinical recommendations.
AMIA Joint Summits on Translational Science proceedings AMIA Summit on Translational Science, 2013
Gene Wiki Plus (GeneWiki+) and the Online Mendelian Inheritance in Man (OMIM) are publicly availa... more Gene Wiki Plus (GeneWiki+) and the Online Mendelian Inheritance in Man (OMIM) are publicly available resources for sharing information about disease-gene and gene-SNP associations in humans. While immensely useful to the scientific community, both resources are manually curated, thereby making the data entry and publication process time-consuming, and to some degree, error-prone. To this end, this study investigates Semantic Web technologies to validate existing and potentially discover new genotype-phenotype associations in GWP and OMIM. In particular, we demonstrate the applicability of SPARQL queries for identifying associations not explicitly stated for commonly occurring chronic diseases in GWP and OMIM, and report our preliminary findings for coverage, completeness, and validity of the associations. Our results highlight the benefits of Semantic Web querying technology to validate existing disease-gene associations as well as identify novel associations although further evalua...
Oncology Reports, 1994
The methylation status of a gene promoter is considered to be an important mechanism for the deve... more The methylation status of a gene promoter is considered to be an important mechanism for the development of many tumors, including colorectal cancer. Recent studies have shown that specific patterns of DNA methylation across multiple CpG loci in some human tumors are more informative than the detection of one single CpG locus in tumor genomes. In the present study, multiple CpG methylations of three genes (CDKN2A, DPYD and MLH1) were detected in DNA samples from patients with colorectal cancer using Pyrosequencing(R) technology. The bisulfite-converted DNA was amplified with a nested PCR and five or six CpG loci of each gene were assessed to determine DNA methylotype. Our data showed that 10/49 (20.4%), 6/48 (12.5%) and 14/49 (28.6%) of tumors were methylated with a DNA methylation level >0.2 in CDKN2A, DPYD and MLH1, respectively. Our study indicated a similar DNA methylation level across the multiple CpG loci for all three genes in the methylated tumor DNA samples, demonstrating a dichotomous trait in DNA methylation. The tumor DNA samples had unique DNA methylation patterns, which were high-degree and multiple-site methylation, but the normal DNA samples had no or a low-degree and dispersed single-site methylation. In addition, an inverse correlation in those methylated tumors was observed between DNA methylation and RNA expression for MLH1 (RS=-0.62, P=0.003), but not for CDKN2A and DPYD. In conclusion, distinctive DNA methylotypes exist in colorectal cancer and may depict a distinct biology in apparently homogeneous tumors.
Current Pharmacogenomics, 2004
... 2, No. 1 McLeod et al. fluorescence data, the genotype of the target DNA can be inferred depe... more ... 2, No. 1 McLeod et al. fluorescence data, the genotype of the target DNA can be inferred depending on which probe is cleaved during the PCR reaction. ... LIGATION METHODS Oligonucleotide Ligation The oligonucleotide ligation assay (OLA) [Landegren et al. ...
Clinical Chemistry, 2003
Mycobacterium primers and hybridization to an M. tuberculosis-specific probe. J Clin Microbiol 19... more Mycobacterium primers and hybridization to an M. tuberculosis-specific probe. J Clin Microbiol 1996;34:918 -23.
Clinical Cancer Research, 2006
Background: The ability to maintain DNA integrity is a critical cellular function. DNA repair is ... more Background: The ability to maintain DNA integrity is a critical cellular function. DNA repair is conducted by distinct pathways of genes, many of which are thought to be altered in colorectal cancer. However, there has been little characterization of these pathways in colorectal cancer. Method: By using theTaqMan real-time quantitative PCR, RNA expression profiling of 20 DNA repair pathway genes was done in matched tumor and normal tissues from 52 patients with Dukes' C colorectal cancer. Results: The relative mRNA expression level across the 20 DNA repair pathway genes varied considerably, and the individual variability was also quite large, with an 85.4 median fold change in the tumor tissue genes and a 127.2 median fold change in the normal tissue genes. Tumornormal differential expression was found in 13 of 20 DNA repair pathway genes (only XPA had a lower RNA level in the tumor samples; the other 12 genes had significantly higher tumor levels, all P < 0.01). Coordinated expression of ERCC6, HMG1, MSH2, and POLB (R S z 0.60) was observed in the tumor tissues (all P < 0.001). Apoptosis index was not correlated with expression of the 20 DNA repair pathway genes. MLH1 and XRCC1 RNA expression was correlated with microsatellite instability status (P = 0.045 and 0.020, respectively). An inverse correlation was found between tumor MLH1 RNA expression and MLH1 DNA methylation (P = 0.003). Conclusion: Our study provides an initial characterization of the DNA repair pathways for understanding the cellular DNA damage/repair system in human colorectal cancer.
Journal of the American Medical Informatics Association : JAMIA
Objective Meaningful exchange of information is a fundamental challenge in collaborative biomedic... more Objective Meaningful exchange of information is a fundamental challenge in collaborative biomedical research. To help address this, the authors developed the Life Sciences Domain Analysis Model (LS DAM), an information model that provides a framework for communication among domain experts and technical teams developing information systems to support biomedical research. The LS DAM is harmonized with the Biomedical Research Integrated Domain Group (BRIDG) model of protocol-driven clinical research. Together, these models can facilitate data exchange for translational research. Materials and methods The content of the LS DAM was driven by analysis of life sciences and translational research scenarios and the concepts in the model are derived from existing information models, reference models and data exchange formats. The model is represented in the Unified Modeling Language and uses ISO 21090 data types. Results The LS DAM v2.2.1 is comprised of 130 classes and covers several core areas including Experiment, Molecular Biology, Molecular Databases and Specimen.
BMC Medical Informatics and Decision Making, 2015
Background: Every year, hundreds of thousands of patients experience treatment failure or adverse... more Background: Every year, hundreds of thousands of patients experience treatment failure or adverse drug reactions (ADRs), many of which could be prevented by pharmacogenomic testing. However, the primary knowledge needed for clinical pharmacogenomics is currently dispersed over disparate data structures and captured in unstructured or semi-structured formalizations. This is a source of potential ambiguity and complexity, making it difficult to create reliable information technology systems for enabling clinical pharmacogenomics. Methods: We developed Web Ontology Language (OWL) ontologies and automated reasoning methodologies to meet the following goals: 1) provide a simple and concise formalism for representing pharmacogenomic knowledge, 2) finde errors and insufficient definitions in pharmacogenomic knowledge bases, 3) automatically assign alleles and phenotypes to patients, 4) match patients to clinically appropriate pharmacogenomic guidelines and clinical decision support messages and 5) facilitate the detection of inconsistencies and overlaps between pharmacogenomic treatment guidelines from different sources. We evaluated different reasoning systems and test our approach with a large collection of publicly available genetic profiles.
2012 IEEE Second International Conference on Healthcare Informatics, Imaging and Systems Biology, 2012
The clinical element model (CEM) is an information model designed for representing clinical infor... more The clinical element model (CEM) is an information model designed for representing clinical information in electronic health records (EHR) systems across organizations. The current representation of CEMs does not support formal semantic definitions and therefore it is not possible to perform reasoning and consistency checking on derived models. This paper introduces our efforts to represent the CEM specification using the Web Ontology Language (OWL). The CEM-OWL representation connects the CEM content with the Semantic Web environment, which provides authoring, reasoning, and querying tools. This work may also facilitate the harmonization of the CEMs with domain knowledge represented in terminology models as well as other clinical information models such as the openEHR archetype model. We have created the CEM-OWL meta ontology based on the CEM specification. A convertor has been implemented in Java to automatically translate detailed CEMs from XML to OWL. A panel evaluation has been conducted, and the results show that the OWL modeling can faithfully represent the CEM specification and represent patient data.
Journal of Biomedical Informatics, 2016
Genomics is a promising tool that is becoming more widely available to improve the care and treat... more Genomics is a promising tool that is becoming more widely available to improve the care and treatment of individuals. While there is much assertion, genomics will most certainly require the use of clinical decision support (CDS) to be fully realized in the routine clinical setting. The National Human Genome Research Institute (NHGRI) of the National Institutes of Health recently convened an in-person, multi-day meeting on this topic. It was widely recognized that there is a need to promote the innovation and development of resources for genomic CDS such as a CDS sandbox. The purpose of this study was to evaluate a proposed approach for such a genomic CDS sandbox among domain experts and potential users. Survey results indicate a significant interest and desire for a genomic CDS sandbox environment among domain experts. These results will be used to guide the development of a genomic CDS sandbox.
Journal of the American Medical Informatics Association, 2016
The American Medical Informatics Association convened the 2014 Health Policy Invitational Meeting... more The American Medical Informatics Association convened the 2014 Health Policy Invitational Meeting to develop recommendations for updates to current policies and to establish an informatics research agenda for personalizing medicine. In particular, the meeting focused on discussing informatics challenges related to personalizing care through the integration of genomic or other high-volume biomolecular data with data from clinical systems to make health care more efficient and effective. This report summarizes the findings (n = 6) and recommendations (n = 15) from the policy meeting, which were clustered into 3 broad areas: (1) policies governing data access for research and personalization of care; (2) policy and research needs for evolving data interpretation and knowledge representation; and (3) policy and research needs to ensure data integrity and preservation. The meeting outcome underscored the need to address a number of important policy and technical considerations in order to realize the potential of personalized or precision medicine in actual clinical contexts.
Journal of Biomedical Informatics, 2016
Genomics is a promising tool that is becoming more widely available to improve the care and treat... more Genomics is a promising tool that is becoming more widely available to improve the care and treatment of individuals. While there is much assertion, genomics will most certainly require the use of clinical decision support (CDS) to be fully realized in the routine clinical setting. The National Human Genome Research Institute (NHGRI) of the National Institutes of Health recently convened an in-person, multi-day meeting on this topic. It was widely recognized that there is a need to promote the innovation and development of resources for genomic CDS such as a CDS sandbox. The purpose of this study was to evaluate a proposed approach for such a genomic CDS sandbox among domain experts and potential users. Survey results indicate a significant interest and desire for a genomic CDS sandbox environment among domain experts. These results will be used to guide the development of a genomic CDS sandbox.
Amia Joint Summits on Translational Science Proceedings Amia Summit on Translational Science, 2013
The purpose of this paper is to describe pilot work on a semantic model of the pharmacogenomics i... more The purpose of this paper is to describe pilot work on a semantic model of the pharmacogenomics information found in drug product labels. The model's development is driven by a series of use cases that we have developed to demonstrate how structured pharmacogenomics information could be more effectively used to support clinical and translational efforts. Using an iterative process, the semantic model was field-tested by five pharmacists, who used it to manually annotate a subset of the sections that the Food and Drug Administration's Pharmacogenomic Biomarkers in Drug Labels cites as containing pharmacogenomics information. The five pharmacists identified a total of 213 pharmacogenomics statements in 29 sections. The model showed the potential to make the unstructured pharmacogenomic information currently written in product labeling more accessible and actionable through structured annotations of pharmacogenomics effects and clinical recommendations.
Pharmacogenomics, 2015
Many currently available pharmacogenomic assays and algorithms interrogate a set of 'tag&... more Many currently available pharmacogenomic assays and algorithms interrogate a set of 'tag' polymorphisms for inferring haplotypes. We wanted to test the accuracy of such haplotype inferences across different populations. We simulated haplotype inferences made by existing pharmacogenomic assays for seven important pharmacogenes based on full genome data of 2504 persons in the 1000 Genomes dataset. A sizable fraction of samples did not match any of the haplotypes in the star allele nomenclature systems. We found no clear population bias in the accuracy of results of simulated assays. Haplotype nomenclatures and inference algorithms need to be improved to adequately capture pharmacogenomic diversity in human populations.
Clinical pharmacology and therapeutics, Jan 19, 2015
This manuscript provides nomenclature recommendations developed by an international workgroup to ... more This manuscript provides nomenclature recommendations developed by an international workgroup to increase transparency and standardization of pharmacogenetic (PGx) result reporting. Presently, sequence variants identified by PGx tests are described using different nomenclature systems. In addition, PGx analysis may detect different sets of variants for each gene, which can affect interpretation of results. This practice has caused confusion and may thereby impede the adoption of clinical PGx testing. Standardization is critical to move PGx forward. This article is protected by copyright. All rights reserved.
Journal of Pathology Informatics, 2015
Genomic, proteomic, epigenomic, and other &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;am... more Genomic, proteomic, epigenomic, and other &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot;omic&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot; data have the potential to enable precision medicine, also commonly referred to as personalized medicine. The volume and complexity of omic data are rapidly overwhelming human cognitive capacity, requiring innovative approaches to translate such data into patient care. Here, we outline a conceptual model for the application of omic data in the clinical context, called &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot;the omic funnel.&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot; This model parallels the classic &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot;Data, Information, Knowledge, Wisdom pyramid&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot; and adds context for how to move between each successive layer. Its goal is to allow informaticians, researchers, and clinicians to approach the problem of translating omic data from bench to bedside, by using discrete steps with clearly defined needs. Such an approach can facilitate the development of modular and interoperable software that can bring precision medicine into widespread practice.
Journal of the American Medical Informatics Association : JAMIA, Jan 3, 2015
Clinicians' ability to use and interpret genetic information depends upon how those data are ... more Clinicians' ability to use and interpret genetic information depends upon how those data are displayed in electronic health records (EHRs). There is a critical need to develop systems to effectively display genetic information in EHRs and augment clinical decision support (CDS). The National Institutes of Health (NIH)-sponsored Clinical Sequencing Exploratory Research and Electronic Medical Records & Genomics EHR Working Groups conducted a multiphase, iterative process involving working group discussions and 2 surveys in order to determine how genetic and genomic information are currently displayed in EHRs, envision optimal uses for different types of genetic or genomic information, and prioritize areas for EHR improvement. There is substantial heterogeneity in how genetic information enters and is documented in EHR systems. Most institutions indicated that genetic information was displayed in multiple locations in their EHRs. Among surveyed institutions, genetic information ent...
AMIA Joint Summits on Translational Science proceedings AMIA Summit on Translational Science, 2013
The Pharmacogenomics Knowledge Base (PharmGKB) [1] is a publicly available central resource for p... more The Pharmacogenomics Knowledge Base (PharmGKB) [1] is a publicly available central resource for pharmacogenomics data and knowledge, which is being widely employed into clinical practice and thus requires using clinical terminologies. Hence, harmonizing PharmGKB drug data with well annotated drug terminologies will facilitate its integration with other related resources and support data representation, interpretation, and exchange within and across heterogeneous sources and applications. In this study, we extracted drug and drug class from PharmGKB, and mapped them to National Drug File Reference Terminology (NDF-RT) [2], which is integrated into RxNorm specified by U.S. Meaningful Use regulations. And the evaluated mapping results will be provided to PharmGKB for further investigation and collaboration.
AMIA Joint Summits on Translational Science proceedings AMIA Summit on Translational Science, 2013
Structured Product Labels (SPLs) contain information about drugs that can be valuable to clinical... more Structured Product Labels (SPLs) contain information about drugs that can be valuable to clinical and translational research, especially if it can be linked to other sources that provide data about drug targets, chemical properties, interactions, and biological pathways. Unfortunately, SPLs currently provide coarsely-structured drug information and lack the detailed annotation that is required to support computational use cases. To help address this issue we created LinkedSPLs, a Linked Data resource that extends the "web of drug identity" using information extracted from SPLs. In this paper we describe the mapping that LinkedSPLs provides between SPL active ingredients and DrugBank chemical entities. These mappings were created using three approaches: InChI chemical structure descriptors comparison, exact string matching based on the chemical name, and automatic (unsupervised) linkage identification. Comparison of the approaches found that, while these three approaches ar...
AMIA Joint Summits on Translational Science proceedings AMIA Summit on Translational Science, 2013
The purpose of this paper is to describe pilot work on a semantic model of the pharmacogenomics i... more The purpose of this paper is to describe pilot work on a semantic model of the pharmacogenomics information found in drug product labels. The model's development is driven by a series of use cases that we have developed to demonstrate how structured pharmacogenomics information could be more effectively used to support clinical and translational efforts. Using an iterative process, the semantic model was field-tested by five pharmacists, who used it to manually annotate a subset of the sections that the Food and Drug Administration's Table of Pharmacogenomic Biomarkers in Drug Labels cites as containing pharmacogenomics information. The five pharmacists identified a total of 213 pharmacogenomics statements in 29 sections. The model showed the potential to make the unstructured pharmacogenomic information currently written in product labeling more accessible and actionable through structured annotations of pharmacogenomics effects and clinical recommendations.
AMIA Joint Summits on Translational Science proceedings AMIA Summit on Translational Science, 2013
Gene Wiki Plus (GeneWiki+) and the Online Mendelian Inheritance in Man (OMIM) are publicly availa... more Gene Wiki Plus (GeneWiki+) and the Online Mendelian Inheritance in Man (OMIM) are publicly available resources for sharing information about disease-gene and gene-SNP associations in humans. While immensely useful to the scientific community, both resources are manually curated, thereby making the data entry and publication process time-consuming, and to some degree, error-prone. To this end, this study investigates Semantic Web technologies to validate existing and potentially discover new genotype-phenotype associations in GWP and OMIM. In particular, we demonstrate the applicability of SPARQL queries for identifying associations not explicitly stated for commonly occurring chronic diseases in GWP and OMIM, and report our preliminary findings for coverage, completeness, and validity of the associations. Our results highlight the benefits of Semantic Web querying technology to validate existing disease-gene associations as well as identify novel associations although further evalua...
Oncology Reports, 1994
The methylation status of a gene promoter is considered to be an important mechanism for the deve... more The methylation status of a gene promoter is considered to be an important mechanism for the development of many tumors, including colorectal cancer. Recent studies have shown that specific patterns of DNA methylation across multiple CpG loci in some human tumors are more informative than the detection of one single CpG locus in tumor genomes. In the present study, multiple CpG methylations of three genes (CDKN2A, DPYD and MLH1) were detected in DNA samples from patients with colorectal cancer using Pyrosequencing(R) technology. The bisulfite-converted DNA was amplified with a nested PCR and five or six CpG loci of each gene were assessed to determine DNA methylotype. Our data showed that 10/49 (20.4%), 6/48 (12.5%) and 14/49 (28.6%) of tumors were methylated with a DNA methylation level &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;gt;0.2 in CDKN2A, DPYD and MLH1, respectively. Our study indicated a similar DNA methylation level across the multiple CpG loci for all three genes in the methylated tumor DNA samples, demonstrating a dichotomous trait in DNA methylation. The tumor DNA samples had unique DNA methylation patterns, which were high-degree and multiple-site methylation, but the normal DNA samples had no or a low-degree and dispersed single-site methylation. In addition, an inverse correlation in those methylated tumors was observed between DNA methylation and RNA expression for MLH1 (RS=-0.62, P=0.003), but not for CDKN2A and DPYD. In conclusion, distinctive DNA methylotypes exist in colorectal cancer and may depict a distinct biology in apparently homogeneous tumors.
Current Pharmacogenomics, 2004
... 2, No. 1 McLeod et al. fluorescence data, the genotype of the target DNA can be inferred depe... more ... 2, No. 1 McLeod et al. fluorescence data, the genotype of the target DNA can be inferred depending on which probe is cleaved during the PCR reaction. ... LIGATION METHODS Oligonucleotide Ligation The oligonucleotide ligation assay (OLA) [Landegren et al. ...
Clinical Chemistry, 2003
Mycobacterium primers and hybridization to an M. tuberculosis-specific probe. J Clin Microbiol 19... more Mycobacterium primers and hybridization to an M. tuberculosis-specific probe. J Clin Microbiol 1996;34:918 -23.
Clinical Cancer Research, 2006
Background: The ability to maintain DNA integrity is a critical cellular function. DNA repair is ... more Background: The ability to maintain DNA integrity is a critical cellular function. DNA repair is conducted by distinct pathways of genes, many of which are thought to be altered in colorectal cancer. However, there has been little characterization of these pathways in colorectal cancer. Method: By using theTaqMan real-time quantitative PCR, RNA expression profiling of 20 DNA repair pathway genes was done in matched tumor and normal tissues from 52 patients with Dukes' C colorectal cancer. Results: The relative mRNA expression level across the 20 DNA repair pathway genes varied considerably, and the individual variability was also quite large, with an 85.4 median fold change in the tumor tissue genes and a 127.2 median fold change in the normal tissue genes. Tumornormal differential expression was found in 13 of 20 DNA repair pathway genes (only XPA had a lower RNA level in the tumor samples; the other 12 genes had significantly higher tumor levels, all P < 0.01). Coordinated expression of ERCC6, HMG1, MSH2, and POLB (R S z 0.60) was observed in the tumor tissues (all P < 0.001). Apoptosis index was not correlated with expression of the 20 DNA repair pathway genes. MLH1 and XRCC1 RNA expression was correlated with microsatellite instability status (P = 0.045 and 0.020, respectively). An inverse correlation was found between tumor MLH1 RNA expression and MLH1 DNA methylation (P = 0.003). Conclusion: Our study provides an initial characterization of the DNA repair pathways for understanding the cellular DNA damage/repair system in human colorectal cancer.
Journal of the American Medical Informatics Association : JAMIA
Objective Meaningful exchange of information is a fundamental challenge in collaborative biomedic... more Objective Meaningful exchange of information is a fundamental challenge in collaborative biomedical research. To help address this, the authors developed the Life Sciences Domain Analysis Model (LS DAM), an information model that provides a framework for communication among domain experts and technical teams developing information systems to support biomedical research. The LS DAM is harmonized with the Biomedical Research Integrated Domain Group (BRIDG) model of protocol-driven clinical research. Together, these models can facilitate data exchange for translational research. Materials and methods The content of the LS DAM was driven by analysis of life sciences and translational research scenarios and the concepts in the model are derived from existing information models, reference models and data exchange formats. The model is represented in the Unified Modeling Language and uses ISO 21090 data types. Results The LS DAM v2.2.1 is comprised of 130 classes and covers several core areas including Experiment, Molecular Biology, Molecular Databases and Specimen.
BMC Medical Informatics and Decision Making, 2015
Background: Every year, hundreds of thousands of patients experience treatment failure or adverse... more Background: Every year, hundreds of thousands of patients experience treatment failure or adverse drug reactions (ADRs), many of which could be prevented by pharmacogenomic testing. However, the primary knowledge needed for clinical pharmacogenomics is currently dispersed over disparate data structures and captured in unstructured or semi-structured formalizations. This is a source of potential ambiguity and complexity, making it difficult to create reliable information technology systems for enabling clinical pharmacogenomics. Methods: We developed Web Ontology Language (OWL) ontologies and automated reasoning methodologies to meet the following goals: 1) provide a simple and concise formalism for representing pharmacogenomic knowledge, 2) finde errors and insufficient definitions in pharmacogenomic knowledge bases, 3) automatically assign alleles and phenotypes to patients, 4) match patients to clinically appropriate pharmacogenomic guidelines and clinical decision support messages and 5) facilitate the detection of inconsistencies and overlaps between pharmacogenomic treatment guidelines from different sources. We evaluated different reasoning systems and test our approach with a large collection of publicly available genetic profiles.
2012 IEEE Second International Conference on Healthcare Informatics, Imaging and Systems Biology, 2012
The clinical element model (CEM) is an information model designed for representing clinical infor... more The clinical element model (CEM) is an information model designed for representing clinical information in electronic health records (EHR) systems across organizations. The current representation of CEMs does not support formal semantic definitions and therefore it is not possible to perform reasoning and consistency checking on derived models. This paper introduces our efforts to represent the CEM specification using the Web Ontology Language (OWL). The CEM-OWL representation connects the CEM content with the Semantic Web environment, which provides authoring, reasoning, and querying tools. This work may also facilitate the harmonization of the CEMs with domain knowledge represented in terminology models as well as other clinical information models such as the openEHR archetype model. We have created the CEM-OWL meta ontology based on the CEM specification. A convertor has been implemented in Java to automatically translate detailed CEMs from XML to OWL. A panel evaluation has been conducted, and the results show that the OWL modeling can faithfully represent the CEM specification and represent patient data.