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Biomedical subjects

Teri E Klein

Publications and source records attributed to Teri E Klein.

13 recordsLinked to original sources
PubMed2025

Toward an integrated resource for pharmacogenomics (PGx): Survey findings from the genomic medicine communities.

PURPOSE: Pharmacogenomics (PGx) is a critical component of precision health care that aims to improve drug efficacy and reduce adverse events. Terminologies and standards have not always aligned between PGx and broader genomic medicine communities, which is a barrier to PGx implementation. An updated assessment of community barriers, needs, and perspectives is critical to enable more standardized terminologies and interpretation frameworks. METHODS: The Clinical Genome Resource's PGx Interpretation Committee (PGxIC, formerly referred to as the PGx Working Group, PGxWG) conducted 2 surveys targeting the PGx and genomic medicine communities (n = 508) to evaluate perspectives on PGx clinical validity and actionability frameworks, as well as other barriers to PGx implementation. Surveys were tailored toward self-reported familiarity with PGx. Data primarily consisted of free text, which were analyzed using qualitative content analysis methods. RESULTS: Survey responses indicated conflation of terminology across disciplines, including confusion around differing definitions of terms in PGx and non-PGx contexts. Data also indicated broad support for leveraging existing PGx guidelines and framework structures alongside the standardization of approaches and centralization of resources. CONCLUSION: These novel survey results demonstrate broad consensus on the importance of integrating PGx into clinical practice, including support for development of gene-drug response clinical validity and actionability frameworks aligned with Clinical Genome Resource's frameworks for gene-disease relationships.

Humans↗
PubMed2003

Microenvironment analysis and identification of magnesium binding sites in RNA.

Interactions with magnesium (Mg2+) ions are essential for RNA folding and function. The locations and function of bound Mg2+ ions are difficult to characterize both experimentally and computationally. In particular, the P456 domain of the Tetrahymena thermophila group I intron, and a 58 nt 23s rRNA from Escherichia coli have been important systems for studying the role of Mg2+ binding in RNA, but characteristics of all the binding sites remain unclear. We therefore investigated the Mg2+ binding capabilities of these RNA systems using a computational approach to identify and further characterize their Mg2+ binding sites. The approach is based on the FEATURE algorithm, reported previously for microenvironment analysis of protein functional sites. We have determined novel physicochemical descriptions of site-bound and diffusely bound Mg2+ ions in RNA that are useful for prediction. Electrostatic calculations using the Non-Linear Poisson Boltzmann (NLPB) equation provided further evidence for the locations of site-bound ions. We confirmed the locations of experimentally determined sites and further differentiated between classes of ion binding. We also identified potentially important, high scoring sites in the group I intron that are not currently annotated as Mg2+ binding sites. We note their potential function and believe they deserve experimental follow-up.

Algorithms↗
PubMed2003

WebFEATURE: An interactive web tool for identifying and visualizing functional sites on macromolecular structures.

WebFEATURE (http://feature.stanford.edu/webfeature/) is a web-accessible structural analysis tool that allows users to scan query structures for functional sites in both proteins and nucleic acids. WebFEATURE is the public interface to the scanning algorithm of the FEATURE package, a supervised learning algorithm for creating and identifying 3D, physicochemical motifs in molecular structures. Given an input structure or Protein Data Bank identifier (PDB ID), and a statistical model of a functional site, WebFEATURE will return rank-scored 'hits' in 3D space that identify regions in the structure where similar distributions of physicochemical properties occur relative to the site model. Users can visualize and interactively manipulate scored hits and the query structure in web browsers that support the Chime plug-in. Alternatively, results can be downloaded and visualized through other freely available molecular modeling tools, like RasMol, PyMOL and Chimera. A major application of WebFEATURE is in rapid annotation of function to structures in the context of structural genomics.

Algorithms↗
PubMed2003

A functional analysis of disease-associated mutations in the androgen receptor gene.

Mutations in the androgen receptor (AR) are associated with a variety of diseases including androgen insensitivity syndrome and prostate cancer, but the way in which these mutations cause disease is poorly understood. We present a method for distinguishing likely disease-causing mutations from mutations that are merely associated with disease but have no causal role. Our method uses a measure of nucleotide conservation, and we find that conservation often correlates with severity of the clinical phenotype. Further, by only including mutations whose pathogenicity has been proven experimentally, this correlation is enhanced in the case of prostate cancer-associated mutations. Our method provides a means for assessing the significance of single nucleotide polymorphisms (SNPs) and cancer-associated mutations.

Algorithms↗
PubMed2002

The functional importance of disease-associated mutation.

BACKGROUND: For many years, scientists believed that point mutations in genes are the genetic switches for somatic and inherited diseases such as cystic fibrosis, phenylketonuria and cancer. Some of these mutations likely alter a protein's function in a manner that is deleterious, and they should occur in functionally important regions of the protein products of genes. Here we show that disease-associated mutations occur in regions of genes that are conserved, and can identify likely disease-causing mutations. RESULTS: To show this, we have determined conservation patterns for 6185 non-synonymous and heritable disease-associated mutations in 231 genes. We define a parameter, the conservation ratio, as the ratio of average negative entropy of analyzable positions with reported mutations to that of every analyzable position in the gene sequence. We found that 84.0% of the 231 genes have conservation ratios less than one. 139 genes had eleven or more analyzable mutations and 88.0% of those had conservation ratios less than one. CONCLUSIONS: These results indicate that phylogenetic information is a powerful tool for the study of disease-associated mutations. Our alignments and analysis has been made available as part of the database at http://cancer.stanford.edu/mut-paper/. Within this dataset, each position is annotated with the analysis, so the most likely disease-causing mutations can be identified.

Computational Biology↗
PubMed2002

Conformational preferences of substituted prolines in the collagen triple helix.

Researchers have recently questioned the role hydroxylated prolines play in stabilizing the collagen triple helix. To address these issues, we have developed new molecular mechanics parameters for the simulation of peptides containing 4(R)-fluoroproline (Flp), 4(R)-hydroxyproline (Hyp), and 4(R)-aminoproline (Amp). Simulations of peptides based on these parameters can be used to determine the components that stabilize hydroxyproline over proline in the triple helix. The dihedrals F-C-C-N, O-C-C-N, and N-C-C-N were built using a N-beta-ethyl amide model. One nanosecond simulations were performed on the trimers [(Pro-Pro-Gly)(10)](3), [(Pro-Hyp-Gly)(10)](3), [(Pro-Amp-Gly)(10)](3), [(Pro-Amp(1+)-Gly)(10)](3), and [(Pro-Flp-Gly)(10)](3) in explicit solvent. The results of our simulations suggest that pyrrolidine ring conformation is mediated by the strength of the gauche effect and classical electrostatic interactions.

Chemical Phenomena↗
PubMed2002

PharmGKB: the Pharmacogenetics Knowledge Base.

The Pharmacogenetics Knowledge Base (PharmGKB; http://www.pharmgkb.org/) contains genomic, phenotype and clinical information collected from ongoing pharmacogenetic studies. Tools to browse, query, download, submit, edit and process the information are available to registered research network members. A subset of the tools is publicly available. PharmGKB currently contains over 150 genes under study, 14 Coriell populations and a large ontology of pharmacogenetics concepts. The pharmacogenetic concepts and the experimental data are interconnected by a set of relations to form a knowledge base of information for pharmacogenetic researchers. The information in PharmGKB, and its associated tools for processing that information, are tailored for leading-edge pharmacogenetics research. The PharmGKB project was initiated in April 2000 and the first version of the knowledge base went online in February 2001.

Biotransformation↗
PubMed2002

A multidomain TIGR/olfactomedin protein family with conserved structural similarity in the N-terminal region and conserved motifs in the C-terminal region.

Based on the similarity between the TIGR (trabecular-meshwork inducible glucocorticoid response) (also known as myocilin) and olfactomedin protein families identified throughout the length of the TIGR protein, we have identified more distantly related proteins to determine the elements essential to the function/structure of the TIGR and olfactomedin proteins. Using a sequence walk method and the Shotgun program, we have identified a family including 31 olfactomedin domain-containing sequences. Multiple sequence alignments and secondary structure analyses were used to identify conserved sequence elements. Pairwise identity in the olfactomedin domain ranges from 8 to 64%, with an average pairwise identity of 24%. The N-terminal regions of the proteins fall into two subgroups, one including the TIGR and olfactomedin families and another group of apparently unrelated domains. The TIGR and olfactomedin sequences display conserved motifs including a residual leucine zipper region and maintain a similar secondary structure throughout the N-terminal region. The correlation between conserved elements and disease-associated mutations and apparent polymorphisms in human TIGR was also examined to evaluate the apparent importance of conserved residues to the function/structure of TIGR. Several residues have been identified as essential to the function and/or structure of the human TIGR protein based on their degree of conservation across the family and their implication in the pathogenesis of primary open-angle glaucoma. Additionally, we have identified a group of chitinase sequences containing several of the highly conserved motifs present in the C-terminal region of the olfactomedin domain-containing sequences.

Algorithms↗
PubMed2002

Structural models of osteogenesis imperfecta-associated variants in the COL1A1 gene.

Osteogenesis imperfecta (OI) is a genetic disease in which the most common mutations result in substitutions for glycine residues in the triple helical domain of the chains of type I collagen. Currently there is no way to use sequence information to predict the clinical OI phenotype. However, structural models coupled with biophysical and machine learning methods may be able to predict sequences that, when mutated, would be associated with more severe forms of OI. To build appropriate structural models, we have applied a high throughput molecular dynamic approach. Homotrimeric peptides covering 57 positions in which mutations are associated with OI were simulated both with and without mutations. Our models revealed structural differences that occur with different substituting amino acids. When mutations were introduced, we observed a decrease in helix stability, as caused by fewer main chain backbone hydrogen bonds, and an increase in main chain root mean square deviation and specifically bound water molecules.

Collagen Type I↗
PubMed2002

Challenges for biomedical informatics and pharmacogenomics.

Pharmacogenomics requires the integration and analysis of genomic, molecular, cellular, and clinical data, and it thus offers a remarkable set of challenges to biomedical informatics. These include infrastructural challenges such as the creation of data models and databases for storing these data, the integration of these data with external databases, the extraction of information from natural language text, and the protection of databases with sensitive information. There are also scientific challenges in creating tools to support gene expression analysis, three-dimensional structural analysis, and comparative genomic analysis. In this review, we summarize the current uses of informatics within pharmacogenomics and show how the technical challenges that remain for biomedical informatics are typical of those that will be confronted in the postgenomic era.

Communication↗
PubMed2002

Ontology development for a pharmacogenetics knowledge base.

Research directed toward discovering how genetic factors influence a patient's response to drugs requires coordination of data produced from laboratory experiments, computational methods, and clinical studies. A public repository of pharmacogenetic data should accelerate progress in the field of pharmacogenetics by organizing and disseminating public datasets. We are developing a pharmacogenetics knowledge base (PharmGKB) to support the storage and retrieval of both experimental data and conceptual knowledge. PharmGKB is an Internet-based resource that integrates complex biological, pharmacological, and clinical data in such a way that researchers can submit their data and users can retrieve information to investigate genotype-phenotype correlations. Successful management of the names, meaning, and organization of concepts used within the system is crucial. We have selected a frame-based knowledge-representation system for development of an ontology of concepts and relationships that represent the domain and that permit storage of experimental data. Preliminary experience shows that the ontology we have developed for gene-sequence data allows us to accept, store, and query data submissions.

Antineoplastic Agents↗
PubMed2002

Automating data acquisition into ontologies from pharmacogenetics relational data sources using declarative object definitions and XML.

Ontologies are useful for organizing large numbers of concepts having complex relationships, such as the breadth of genetic and clinical knowledge in pharmacogenomics. But because ontologies change and knowledge evolves, it is time consuming to maintain stable mappings to external data sources that are in relational format. We propose a method for interfacing ontology models with data acquisition from external relational data sources. This method uses a declarative interface between the ontology and the data source, and this interface is modeled in the ontology and implemented using XML schema. Data is imported from the relational source into the ontology using XML, and data integrity is checked by validating the XML submission with an XML schema. We have implemented this approach in PharmGKB (http://www.pharmgkb.org/), a pharmacogenetics knowledge base. Our goals were to (1) import genetic sequence data, collected in relational format, into the pharmacogenetics ontology, and (2) automate the process of updating the links between the ontology and data acquisition when the ontology changes. We tested our approach by linking PharmGKB with data acquisition from a relational model of genetic sequence information. The ontology subsequently evolved, and we were able to rapidly update our interface with the external data and continue acquiring the data. Similar approaches may be helpful for integrating other heterogeneous information sources in order make the diversity of pharmacogenetics data amenable to computational analysis.

Databases, Factual↗