8 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results:

"Cystic Fibrosis"

These pubmed results were generated on 2016/07/14

PubMed comprises more than 24 million citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

Assessment of pharmacogenomic agreement.

F1000Res. 2016;5:825

Authors: Safikhani Z, El-Hachem N, Quevedo R, Smirnov P, Goldenberg A, Juul Birkbak N, Mason C, Hatzis C, Shi L, Aerts HJ, Quackenbush J, Haibe-Kains B

Abstract
In 2013 we published an analysis demonstrating that drug response data and gene-drug associations reported in two independent large-scale pharmacogenomic screens, Genomics of Drug Sensitivity in Cancer (GDSC) and Cancer Cell Line Encyclopedia (CCLE), were inconsistent. The GDSC and CCLE investigators recently reported that their respective studies exhibit reasonable agreement and yield similar molecular predictors of drug response, seemingly contradicting our previous findings. Reanalyzing the authors' published methods and results, we found that their analysis failed to account for variability in the genomic data and more importantly compared different drug sensitivity measures from each study, which substantially deviate from our more stringent consistency assessment. Our comparison of the most updated genomic and pharmacological data from the GDSC and CCLE confirms our published findings that the measures of drug response reported by these two groups are not consistent. We believe that a principled approach to assess the reproducibility of drug sensitivity predictors is necessary before envisioning their translation into clinical settings.

PMID: 27408686 [PubMed]

Effects of SLC22A1 Polymorphisms on Metformin-Induced Reductions in Adiposity and Metformin Pharmacokinetics in Obese Children with Insulin Resistance.

J Clin Pharmacol. 2016 Jul 13;

Authors: Sam WJ, Roza O, Hon YY, Alfaro RM, Calis KA, Reynolds JC, Yanovski JA

Abstract
Steady state population pharmacokinetics of a non-commercial immediate release metformin (hydrochloride) drug product were characterized in 28 severely obese children with insulin resistance. The concentration-time profiles with double peaks were well described by a one-compartment model with two absorption sites. Mean population apparent clearance (CL/F) was 68.1 L/hr and mean apparent volume of distribution (V/F) was 28.8 L. Body weight was a covariate of CL/F and V/F. Estimated glomerular filtration rate was a significant covariate of CL/F (p<0.001). SLC22A1genotype did not significantly affect metformin pharmacokinetics. The response to 6 months of metformin treatment (HbA1c, HOMA IR, fasting insulin, and glucose changes) was not different between SLC22A1 wild type subjects and carriers of presumably low activity SLC22A1 alleles. However, SLC22A1 variant carriers had smaller reductions in percentage of total trunk fat after metformin therapy, although the percentage reduction in trunk fat was small. The median % change in trunk fat was -2.20 % (-9.00 % - 0.900 %) and -1.20 % (-2.40 % - 7.30 %) for the SLC22A1 wild-type subjects and variant carriers, respectively. Future study is needed to evaluate the effects of SLC22A1 polymorphisms on metformin-mediated weight reduction in obese children. This article is protected by copyright. All rights reserved.

PMID: 27407018 [PubMed - as supplied by publisher]

A Global Health Diagnostic for Personalized Medicine in Resource-Constrained World Settings: A Simple PCR-RFLP Method for Genotyping CYP2B6 g.15582C>T and Science and Policy Relevance for Optimal Use of Antiretroviral Drug Efavirenz.

OMICS. 2015 Jun;19(6):332-8

Authors: Evans J, Swart M, Soko N, Wonkam A, Huzair F, Dandara C

Abstract
The use of pharmacogenomics (PGx) knowledge in treatment of individual patients is becoming a common phenomenon in the developed world. However, poorly resourced countries have thus far been constrained for three main reasons. First, the cost of whole genome sequencing is still considerably high in comparison to other (non-genomics) diagnostics in the developing world where both science and social dynamics create a dynamic and fragile healthcare ecosystem. Second, studies correlating genomic differences with drug pharmacokinetics and pharmacodynamics have not been consistent, and more importantly, often not indexed to impact on societal end-points, beyond clinical practice. Third, ethics regulatory frames over PGx testing require improvements based on nested accountability systems and in ways that address the user community needs. Thus, CYP2B6 is a crucial enzyme in the metabolism of antiretroviral drugs, efavirenz and nevirapine. More than 40 genetic variants have been reported, but only a few contribute to differences in plasma EFV and NVP concentrations. The most widely reported CYP2B6 variants affecting plasma drug levels include c.516G>T, c.983T>C, and to a lesser extent, g.15582C>T, which should be considered in future PGx tests. While the first two variants are easily characterized, the g.15582C>T detection has been performed primarily by sequencing, which is costly, labor intensive, and requires access to barely available expertise in the developing world. We report here on a simple, practical PCR-RFLP method with vast potentials for use in resource-constrained world regions to detect the g.15582C>T variation among South African and Cameroonian persons. The effects of CYP2B6 g.15582C>T on plasma EFV concentration were further evaluated among HIV/AIDS patients. We report no differences in the frequency of the g.15582T variant between the South African (0.08) and Cameroonian (0.06) groups, which are significantly lower than reported in Asians (0.39) and Caucasians (0.31). The g.15582C/T and T/T genotypes were associated with significantly reduced EFV levels (p=0.006). This article additionally presents the policy relevance of the PGX global health diagnostics and therefore, collectively makes an original interdisciplinary contribution to the field of integrative biology and personalized medicine in developing world. Such studies are, in fact, broadly important because resource-constrained regions exist not only in developing world but also in major geographical parts of the G20 nations and the developed countries.

PMID: 26415139 [PubMed - indexed for MEDLINE]

DBDiaSNP: An Open-Source Knowledgebase of Genetic Polymorphisms and Resistance Genes Related to Diarrheal Pathogens.

OMICS. 2015 Jun;19(6):354-60

Authors: Mehla K, Ramana J

Abstract
Diarrhea is a highly common infection among children, responsible for significant morbidity and mortality rate worldwide. After pneumonia, diarrhea remains the second leading cause of neonatal deaths. Numerous viral, bacterial, and parasitic enteric pathogens are associated with diarrhea. With increasing antibiotic resistance among enteric pathogens, there is an urgent need for global surveillance of the mutations and resistance genes primarily responsible for resistance to antibiotic treatment. Single Nucleotide Polymorphisms are important in this regard as they have a vast potential to be utilized as molecular diagnostics for gene-disease or pharmacogenomics association studies linking genotype to phenotype. DBDiaSNP is a comprehensive repository of mutations and resistance genes among various diarrheal pathogens and hosts to advance breakthroughs that will find applications from development of sequence-based diagnostic tools to drug discovery. It contains information about 946 mutations and 326 resistance genes compiled from literature and various web resources. As of March 2015, it houses various pathogen genes and the mutations responsible for antibiotic resistance. The pathogens include, for example, DEC (Diarrheagenic E.coli), Salmonella spp., Campylobacter spp., Shigella spp., Clostridium difficile, Aeromonas spp., Helicobacter pylori, Entamoeba histolytica, Vibrio cholera, and viruses. It also includes mutations from hosts (e.g., humans, pigs, others) that render them either susceptible or resistant to a certain type of diarrhea. DBDiaSNP is therefore intended as an integrated open access database for researchers and clinicians working on diarrheal diseases. Additionally, we note that the DBDiaSNP is one of the first antibiotic resistance databases for the diarrheal pathogens covering mutations and resistance genes that have clinical relevance from a broad range of pathogens and hosts. For future translational research involving integrative biology and global health, the database offers veritable potentials, particularly for developing countries and worldwide monitoring and personalized effective treatment of pathogens associated with diarrhea. The database is accessible on the public domain at http://www.juit.ac.in/attachments/dbdiasnp/ .

PMID: 25978092 [PubMed - indexed for MEDLINE]

MicroRNA gene expression signatures in long-surviving malignant pleural mesothelioma patients.

Genom Data. 2016 Sep;9:44-9

Authors: Lin RC, Kirschner MB, Cheng YY, van Zandwijk N, Reid G

Abstract
Malignant pleural mesothelioma (MPM) is a tumor originating in the mesothelium, the membrane lining the thoracic cavities, and is induced by exposure to asbestos. Australia suffers one of the world's highest rates of MPM and the incidence is yet to peak. The prognosis for patients with MPM is poor and median survival following diagnosis is 4-18 months. Currently, no or few effective therapies exist for MPM. Trials of targeted agents such as antiangiogenic agents (VEGF, EGFR) or ribonuclease inhibitors (ranpirnase) largely failed to show efficacy in MPM Tsao et al. (2009) [1]. A recent study, however, showed that cisplatin/pemetrexed + bevacizumab (a recombinant humanized monoclonal antibody that inhibit VEGF) treatment has a survival benefit of 2.7 months Zalcman et al. (2016) [2]. It remains to be seen if this targeted therapy will be accepted as a new standard for MPM. Thus the unmet needs of MPM patients remain very pronounced and almost every patient will be confronted with drug resistance and recurrence of disease. We have identified unique gene signatures associated with prolonged survival in mesothelioma patients undergoing radical surgery (EPP, extrapleural pneumonectomy), as well as patients who underwent palliative surgery (pleurectomy/decortication). In addition to data published in Molecular Oncology, 2015;9:715-26 (GSE59180) Kirschner et al. (2015) , we describe here additional data using a system-based approach that support our previous observations. This data provides a resource to further explore microRNA dynamics in MPM.

PMID: 27408810 [PubMed]

A Systems-Level Analysis of the Peripheral Nerve Intrinsic Axonal Growth Program.

Neuron. 2016 Mar 2;89(5):956-70

Authors: Chandran V, Coppola G, Nawabi H, Omura T, Versano R, Huebner EA, Zhang A, Costigan M, Yekkirala A, Barrett L, Blesch A, Michaelevski I, Davis-Turak J, Gao F, Langfelder P, Horvath S, He Z, Benowitz L, Fainzilber M, Tuszynski M, Woolf CJ, Geschwind DH

Abstract
The regenerative capacity of the injured CNS in adult mammals is severely limited, yet axons in the peripheral nervous system (PNS) regrow, albeit to a limited extent, after injury. We reasoned that coordinate regulation of gene expression in injured neurons involving multiple pathways was central to PNS regenerative capacity. To provide a framework for revealing pathways involved in PNS axon regrowth after injury, we applied a comprehensive systems biology approach, starting with gene expression profiling of dorsal root ganglia (DRGs) combined with multi-level bioinformatic analyses and experimental validation of network predictions. We used this rubric to identify a drug that accelerates DRG neurite outgrowth in vitro and optic nerve outgrowth in vivo by inducing elements of the identified network. The work provides a functional genomics foundation for understanding neural repair and proof of the power of such approaches in tackling complex problems in nervous system biology.

PMID: 26898779 [PubMed - indexed for MEDLINE]

BiGG Models: A platform for integrating, standardizing and sharing genome-scale models.

Nucleic Acids Res. 2016 Jan 4;44(D1):D515-22

Authors: King ZA, Lu J, Dräger A, Miller P, Federowicz S, Lerman JA, Ebrahim A, Palsson BO, Lewis NE

Abstract
Genome-scale metabolic models are mathematically-structured knowledge bases that can be used to predict metabolic pathway usage and growth phenotypes. Furthermore, they can generate and test hypotheses when integrated with experimental data. To maximize the value of these models, centralized repositories of high-quality models must be established, models must adhere to established standards and model components must be linked to relevant databases. Tools for model visualization further enhance their utility. To meet these needs, we present BiGG Models (http://bigg.ucsd.edu), a completely redesigned Biochemical, Genetic and Genomic knowledge base. BiGG Models contains more than 75 high-quality, manually-curated genome-scale metabolic models. On the website, users can browse, search and visualize models. BiGG Models connects genome-scale models to genome annotations and external databases. Reaction and metabolite identifiers have been standardized across models to conform to community standards and enable rapid comparison across models. Furthermore, BiGG Models provides a comprehensive application programming interface for accessing BiGG Models with modeling and analysis tools. As a resource for highly curated, standardized and accessible models of metabolism, BiGG Models will facilitate diverse systems biology studies and support knowledge-based analysis of diverse experimental data.

PMID: 26476456 [PubMed - indexed for MEDLINE]

Renal systems biology of patients with systemic inflammatory response syndrome.

Kidney Int. 2015 Oct;88(4):804-14

Authors: Tsalik EL, Willig LK, Rice BJ, van Velkinburgh JC, Mohney RP, McDunn JE, Dinwiddie DL, Miller NA, Mayer ES, Glickman SW, Jaehne AK, Glew RH, Sopori ML, Otero RM, Harrod KS, Cairns CB, Fowler VG, Rivers EP, Woods CW, Kingsmore SF, Langley RJ

Abstract
A systems biology approach was used to comprehensively examine the impact of renal disease and hemodialysis (HD) on patient response during critical illness. To achieve this, we examined the metabolome, proteome, and transcriptome of 150 patients with critical illness, stratified by renal function. Quantification of plasma metabolites indicated greater change as renal function declined, with the greatest derangements in patients receiving chronic HD. Specifically, 6 uremic retention molecules, 17 other protein catabolites, 7 modified nucleosides, and 7 pentose phosphate sugars increased as renal function declined, consistent with decreased excretion or increased catabolism of amino acids and ribonucleotides. Similarly, the proteome showed increased levels of low-molecular-weight proteins and acute-phase reactants. The transcriptome revealed a broad-based decrease in mRNA levels among patients on HD. Systems integration revealed an unrecognized association between plasma RNASE1 and several RNA catabolites and modified nucleosides. Further, allantoin, N1-methyl-4-pyridone-3-carboxamide, and N-acetylaspartate were inversely correlated with the majority of significantly downregulated genes. Thus, renal function broadly affected the plasma metabolome, proteome, and peripheral blood transcriptome during critical illness; changes were not effectively mitigated by hemodialysis. These studies allude to several novel mechanisms whereby renal dysfunction contributes to critical illness.

PMID: 25993322 [PubMed - indexed for MEDLINE]

dbPTM 2016: 10-year anniversary of a resource for post-translational modification of proteins.

Nucleic Acids Res. 2016 Jan 4;44(D1):D435-46

Authors: Huang KY, Su MG, Kao HJ, Hsieh YC, Jhong JH, Cheng KH, Huang HD, Lee TY

Abstract
Owing to the importance of the post-translational modifications (PTMs) of proteins in regulating biological processes, the dbPTM (http://dbPTM.mbc.nctu.edu.tw/) was developed as a comprehensive database of experimentally verified PTMs from several databases with annotations of potential PTMs for all UniProtKB protein entries. For this 10th anniversary of dbPTM, the updated resource provides not only a comprehensive dataset of experimentally verified PTMs, supported by the literature, but also an integrative interface for accessing all available databases and tools that are associated with PTM analysis. As well as collecting experimental PTM data from 14 public databases, this update manually curates over 12 000 modified peptides, including the emerging S-nitrosylation, S-glutathionylation and succinylation, from approximately 500 research articles, which were retrieved by text mining. As the number of available PTM prediction methods increases, this work compiles a non-homologous benchmark dataset to evaluate the predictive power of online PTM prediction tools. An increasing interest in the structural investigation of PTM substrate sites motivated the mapping of all experimental PTM peptides to protein entries of Protein Data Bank (PDB) based on database identifier and sequence identity, which enables users to examine spatially neighboring amino acids, solvent-accessible surface area and side-chain orientations for PTM substrate sites on tertiary structures. Since drug binding in PDB is annotated, this update identified over 1100 PTM sites that are associated with drug binding. The update also integrates metabolic pathways and protein-protein interactions to support the PTM network analysis for a group of proteins. Finally, the web interface is redesigned and enhanced to facilitate access to this resource.

PMID: 26578568 [PubMed - indexed for MEDLINE]

14 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results:

("orphan disease" OR "rare disease" OR "orphan diseases" OR "rare diseases")

These pubmed results were generated on 2016/07/13

PubMed comprises more than 24 million citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

7 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results:

"Cystic Fibrosis"

These pubmed results were generated on 2016/07/13

PubMed comprises more than 24 million citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

Comparing Drug Images and Repurposing Drugs with BioGPS and FLAPdock: The Thymidylate Synthase Case.

ChemMedChem. 2016 Jul 12;

Authors: Siragusa L, Luciani R, Borsari C, Ferrari S, Costi MP, Cruciani G, Spyrakis F

Abstract
Repurposing and repositioning drugs has become a frequently pursued and successful strategy in the current era, as new chemical entities are increasingly difficult to find and get approved. Herein we report an integrated BioGPS/FLAPdock pipeline for rapid and effective off-target identification and drug repurposing. Our method is based on the structural and chemical properties of protein binding sites, that is, the ligand image, encoded in the GRID molecular interaction fields (MIFs). Protein similarity is disclosed through the BioGPS algorithm by measuring the pockets' overlap according to which pockets are clustered. Co-crystallized and known ligands can be cross-docked among similar targets, selected for subsequent in vitro binding experiments, and possibly improved for inhibitory potency. We used human thymidylate synthase (TS) as a test case and searched the entire RCSB Protein Data Bank (PDB) for similar target pockets. We chose casein kinase IIα as a control and tested a series of its inhibitors against the TS template. Ellagic acid and apigenin were identified as TS inhibitors, and various flavonoids were selected and synthesized in a second-round selection. The compounds were demonstrated to be active in the low-micromolar range.

PMID: 27404817 [PubMed - as supplied by publisher]

Screening a Commercial Library of Pharmacologically Active Small Molecules Against Staphylococcus aureus Biofilms.

Antimicrob Agents Chemother. 2016 Jul 11;

Authors: Torres NS, Abercrombie JJ, Srinivasan A, Lopez-Ribot JL, Ramasubramanian AK, Leung KP

Abstract
It is now well established that bacterial infections are often associated with biofilm phenotypes that demonstrate increased resistance to common antimicrobials. Further, due to the collective attrition of new-antibiotic development programs by the pharmaceutical industries, drug repurposing is an attractive alternative. In this work, we have screened 1,280 existing commercially available drugs in the Prestwick Chemical Library, some with previously unknown antimicrobial activity, against Staphylococcus aureus, one of the commonly encountered causative pathogen of burn and wound infections. From the primary screen of the entire Prestwick Chemical Library at a fixed concentration of 10μM, 104 drugs were found to be effective against planktonic S. aureus, and not surprisingly, these were mostly antimicrobials and antiseptics. The activity of 18 selected repurposing candidates, that is, drugs that show antimicrobial activity that are not already considered antimicrobials, observed in the primary screen was confirmed in dose response experiments. Finally, a subset of nine of these drug candidates was tested against pre-formed biofilms of S. aureus We found that three of these drugs, Niclosamide, Carmofur, and Auranofin, possessed antimicrobial activity against pre-formed biofilms, making them attractive candidates for repurposing as novel anti-biofilm therapies.

PMID: 27401577 [PubMed - as supplied by publisher]

FANTOM5 transcriptome catalog of cellular states based on Semantic MediaWiki.

Database (Oxford). 2016;2016

Authors: Abugessaisa I, Shimoji H, Sahin S, Kondo A, Harshbarger J, Lizio M, Hayashizaki Y, Carninci P, FANTOM consortium, Forrest A, Kasukawa T, Kawaji H

Abstract
The Functional Annotation of the Mammalian Genome project (FANTOM5) mapped transcription start sites (TSSs) and measured their activities in a diverse range of biological samples. The FANTOM5 project generated a large data set; including detailed information about the profiled samples, the uncovered TSSs at high base-pair resolution on the genome, their transcriptional initiation activities, and further information of transcriptional regulation. Data sets to explore transcriptome in individual cellular states encoded in the mammalian genomes have been enriched by a series of additional analysis, based on the raw experimental data, along with the progress of the research activities. To make the heterogeneous data set accessible and useful for investigators, we developed a web-based database called Semantic catalog of Samples, Transcription initiation And Regulators (SSTAR). SSTAR utilizes the open source wiki software MediaWiki along with the Semantic MediaWiki (SMW) extension, which provides flexibility to model, store, and display a series of data sets produced during the course of the FANTOM5 project. Our use of SMW demonstrates the utility of the framework for dissemination of large-scale analysis results. SSTAR is a case study in handling biological data generated from a large-scale research project in terms of maintenance and growth alongside research activities.Database URL: http://fantom.gsc.riken.jp/5/sstar/.

PMID: 27402679 [PubMed - in process]

Publication, Discovery and Interoperability of Clinical Decision Support Systems: a Linked Data Approach.

J Biomed Inform. 2016 Jul 8;

Authors: Marco-Ruiz L, Pedrinaci C, Maldonado JA, Panziera L, Chen R, Gustav Bellika J

Abstract
BACKGROUND: The high costs involved in the development of Clinical Decision Support Systems (CDSS) make it necessary to share their functionality across different systems and organizations. Service Oriented Architectures (SOA) have been proposed to allow reusing CDSS by encapsulating them in a Web service. However, strong barriers in sharing CDS functionality are still present as a consequence of lack of expressiveness of services' interfaces. Linked Services are the evolution of the Semantic Web Services paradigm to process Linked Data. They aim to provide semantic descriptions over SOA implementations to overcome the limitations derived from the syntactic nature of Web services technologies.
OBJECTIVE: To facilitate the publication, discovery and interoperability of CDS services by evolving them into Linked Services that expose their interfaces as Linked Data.
MATERIALS AND METHODS: We developed methods and models to enhance CDS SOA as Linked Services that define a rich semantic layer based on machine interpretable ontologies that powers their interoperability and reuse. These ontologies provided unambiguous descriptions of CDS services properties to expose them to the Web of Data.
RESULTS: We developed models compliant with Linked Data principles to create a semantic representation of the components that compose CDS services. To evaluate our approach we implemented a set of CDS Linked Services using a Web service definition ontology. The definitions of Web services were linked to the models developed in order to attach unambiguous semantics to the service components. All models were bound to SNOMED-CT and public ontologies (e.g. Dublin Core) in order to count on a lingua franca to explore them. Discovery and analysis of CDS services based on machine interpretable models was performed reasoning over the ontologies built.
DISCUSSION: Linked Services can be used effectively to expose CDS services to the Web of Data by building on current CDS standards. This allows building shared Linked Knowledge Bases to provide machine interpretable semantics to the CDS service description alleviating the challenges on interoperability and reuse. Linked Services allow for building 'digital libraries' of distributed CDS services that can be hosted and maintained in different organizations.

PMID: 27401856 [PubMed - as supplied by publisher]

Enhanced reproducibility of SADI web service workflows with Galaxy and Docker.

Gigascience. 2015;4:59

Authors: Aranguren ME, Wilkinson MD

Abstract
BACKGROUND: Semantic Web technologies have been widely applied in the life sciences, for example by data providers such as OpenLifeData and through web services frameworks such as SADI. The recently reported OpenLifeData2SADI project offers access to the vast OpenLifeData data store through SADI services.
FINDINGS: This article describes how to merge data retrieved from OpenLifeData2SADI with other SADI services using the Galaxy bioinformatics analysis platform, thus making this semantic data more amenable to complex analyses. This is demonstrated using a working example, which is made distributable and reproducible through a Docker image that includes SADI tools, along with the data and workflows that constitute the demonstration.
CONCLUSIONS: The combination of Galaxy and Docker offers a solution for faithfully reproducing and sharing complex data retrieval and analysis workflows based on the SADI Semantic web service design patterns.

PMID: 26640691 [PubMed - indexed for MEDLINE]

Investigation of 7-dehydrocholesterol reductase pathway to elucidate off-target prenatal effects of pharmaceuticals: a systematic review.

Pharmacogenomics J. 2016 Jul 12;

Authors: Boland MR, Tatonetti NP

Abstract
Mendelian diseases contain important biological information regarding developmental effects of gene mutations that can guide drug discovery and toxicity efforts. In this review, we focus on Smith-Lemli-Opitz syndrome (SLOS), a rare Mendelian disease characterized by compound heterozygous mutations in 7-dehydrocholesterol reductase (DHCR7) resulting in severe fetal deformities. We present a compilation of SLOS-inducing DHCR7 mutations and the geographic distribution of those mutations in healthy and diseased populations. We observed that several mutations thought to be disease causing occur in healthy populations, indicating an incomplete understanding of the condition and highlighting new research opportunities. We describe the functional environment around DHCR7, including pharmacological DHCR7 inhibitors and cholesterol and vitamin D synthesis. Using PubMed, we investigated the fetal outcomes following prenatal exposure to DHCR7 modulators. First-trimester exposure to DHCR7 inhibitors resulted in outcomes similar to those of known teratogens (50 vs 48% born-healthy). DHCR7 activity should be considered during drug development and prenatal toxicity assessment.The Pharmacogenomics Journal advance online publication, 12 July 2016; doi:10.1038/tpj.2016.48.

PMID: 27401223 [PubMed - as supplied by publisher]

Lithium-responsive genes and gene networks in bipolar disorder patient-derived lymphoblastoid cell lines.

Pharmacogenomics J. 2016 Jul 12;

Authors: Breen MS, White CH, Shekhtman T, Lin K, Looney D, Woelk CH, Kelsoe JR

Abstract
Lithium (Li) is the mainstay mood stabilizer for the treatment of bipolar disorder (BD), although its mode of action is not yet fully understood nor is it effective in every patient. We sought to elucidate the mechanism of action of Li and to identify surrogate outcome markers that can be used to better understand its therapeutic effects in BD patients classified as good (responders) and poor responders (nonresponders) to Li treatment. To accomplish these goals, RNA-sequencing gene expression profiles of lymphoblastoid cell lines (LCLs) were compared between BD Li responders and nonresponders with healthy controls before and after treatment. Several Li-responsive gene coexpression networks were discovered indicating widespread effects of Li on diverse cellular signaling systems including apoptosis and defense response pathways, protein processing and response to endoplasmic reticulum stress. Individual gene markers were also identified, differing in response to Li between BD responders and nonresponders, involved in processes of cell cycle and nucleotide excision repair that may explain part of the heterogeneity in clinical response to treatment. Results further indicated a Li gene expression signature similar to that observed with clonidine treatment, an α2-adrenoceptor agonist. These findings provide a detailed mechanism of Li in LCLs and highlight putative surrogate outcome markers that may permit for advanced treatment decisions to be made and for facilitating recovery in BD patients.The Pharmacogenomics Journal advance online publication, 12 July 2016; doi:10.1038/tpj.2016.50.

PMID: 27401222 [PubMed - as supplied by publisher]

Genotype-guided versus standard vitamin K antagonist dosing algorithms in patients initiating anticoagulation. A systematic review and meta-analysis.

Thromb Haemost. 2015 Oct;114(4):768-77

Authors: Belley-Cote EP, Hanif H, D'Aragon F, Eikelboom JW, Anderson JL, Borgman M, Jonas DE, Kimmel SE, Manolopoulos VG, Baranova E, Maitland-van der Zee AH, Pirmohamed M, Whitlock RP

Abstract
Variability in vitamin K antagonist (VKA) dosing is partially explained by genetic polymorphisms. We performed a meta-analysis to determine whether genotype-guided VKA dosing algorithms decrease a composite of death, thromboembolic events and major bleeding (primary outcome) and improve time in therapeutic range (TTR). We searched MEDLINE, EMBASE, CENTRAL, trial registries and conference proceedings for randomised trials comparing genotype-guided and standard (non genotype-guided) VKA dosing algorithms in adults initiating anticoagulation. Data were pooled using a random effects model. Of the 12 included studies (3,217 patients), six reported all components of the primary outcome of mortality, thromboembolic events and major bleeding (2,223 patients, 87 events). Our meta-analysis found no significant difference between groups for the primary outcome (relative risk 0.85, 95% confidence interval [CI] 0.54-1.34; heterogeneity Χ(²)=4.46, p=0.35, I(²)=10%). Based on 10 studies (2,767 patients), TTR was significantly higher in the genotype-guided group (mean difference (MD) 4.31%; 95% CI 0.35, 8.26; heterogeneity Χ(²)=43.31, p<0.001, I(²)=79%). Pre-specified exploratory analyses demonstrated that TTR was significantly higher when genotype-guided dosing was compared with fixed VKA dosing (6 trials, 997 patients: MD 8.41%; 95% CI 3.50,13.31; heterogeneity Χ(²)=15.18, p=0.01, I(²)=67%) but not when compared with clinical algorithm-guided dosing (4 trials, 1,770 patients: MD -0.29%; 95% CI -2.48,1.90; heterogeneity Χ(²)=1.53, p=0.68, I(²)=0%; p for interaction=0.002). In conclusion, genotype-guided compared with standard VKA dosing algorithms were not found to decrease a composite of death, thromboembolism and major bleeding, but did result in improved TTR. An improvement in TTR was observed in comparison with fixed VKA dosing algorithms, but not with clinical algorithms.

PMID: 26158747 [PubMed - indexed for MEDLINE]