ontologyX: a suite of R packages for working with ontological data.

Bioinformatics. 2017 Jan 05;:

Authors: Greene D, Richardson S, Turro E

Abstract
Ontologies are widely used constructs for encoding and analyzing biomedical data, but the absence of simple and consistent tools has made exploratory and systematic analysis of such data unnecessarily difficult. Here we present three packages which aim to simplify such procedures. The ontologyIndex package enables arbitrary ontologies to be read into R, supports representation of ontological objects by native R types, and provides a parsimonius set of performant functions for querying ontologies. ontologySimilarity and ontologyPlot extend ontologyIndex with functionality for straightforward visualization and semantic similarity calculations, including statistical routines.
AVAILABILITY AND IMPLEMENTATION: ontologyIndex, ontologyPlot and ontologySimilarity are all available on the Comprehensive R Archive Network website under https://cran.r-project.org/web/packages/ CONTACT: Daniel Greene dg333@cam.ac.ukSupplementary information: Supplementary data are available at Bioinformatics online.

PMID: 28062448 [PubMed - as supplied by publisher]

DockingApp: a user friendly interface for facilitated docking simulations with AutoDock Vina.

J Comput Aided Mol Des. 2017 Jan 06;:

Authors: Di Muzio E, Toti D, Polticelli F

Abstract
Molecular docking is a powerful technique that helps uncover the structural and energetic bases of the interaction between macromolecules and substrates, endogenous and exogenous ligands, and inhibitors. Moreover, this technique plays a pivotal role in accelerating the screening of large libraries of compounds for drug development purposes. The need to promote community-driven drug development efforts, especially as far as neglected diseases are concerned, calls for user-friendly tools to allow non-expert users to exploit the full potential of molecular docking. Along this path, here is described the implementation of DockingApp, a freely available, extremely user-friendly, platform-independent application for performing docking simulations and virtual screening tasks using AutoDock Vina. DockingApp sports an intuitive graphical user interface which greatly facilitates both the input phase and the analysis of the results, which can be visualized in graphical form using the embedded JMol applet. The application comes with the DrugBank set of more than 1400 ready-to-dock, FDA-approved drugs, to facilitate virtual screening and drug repurposing initiatives. Furthermore, other databases of compounds such as ZINC, available also in AutoDock format, can be readily and easily plugged in.

PMID: 28063067 [PubMed - as supplied by publisher]

The sialic acid to urea ratio as a measure of airway surface hydration.

Am J Physiol Lung Cell Mol Physiol. 2017 Jan 06;:ajplung.00398.2016

Authors: Esther CR, Hill DB, Button B, Shi S, Jania CM, Duncan EA, Doerschuk CM, Chen G, Ranganathan S, Stick SM, Boucher RC

Abstract
INTRODUCTION: Although airway mucus dehydration is key to pathophysiology of cystic fibrosis (CF) and other airways diseases, measuring mucus hydration is challenging. We explored a robust method to estimate mucus hydration using sialic acid as a marker for mucin content.
METHODS: Terminal sialic acid residues from mucins were cleaved by acid hydrolysis from airway samples, and concentrations of sialic acid, urea, and other biomarkers analyzed using mass spectrometry.
RESULTS: In mucins purified from human airway epithelial (HAE), sialic acid concentrations after acid hydrolysis correlated with mucin concentrations (r2=0.92). Sialic acid/urea ratios measured from filters applied to the apical surface of cultured HAE correlated to % solids and were elevated in samples from CF HAEs relative to controls (2.2±1.1 vs. 0.93±1.8, p<0.01). Sialic acid/urea ratios were elevated in bronchoalveolar lavage fluid (BALF) from βENaC transgenic mice, known to have reduced mucus hydration, and mice sensitized to house dust mite allergen. In a translational application, elevated sialic acid/urea ratios were measured in BALF from young children with CF who had airway infection relative to those who did not (5.5±3.7 vs.1.9±1.4, p<0.02), and could be assessed simultaneously with established biomarkers of inflammation.
CONCLUSIONS: The sialic acid/urea ratio performed similarly to % solids, the gold standard measure of mucus hydration. The method proved robust and has potential to serve as flexible techniques to assess mucin hydration, particularly in samples like BALF in which established methods such as % solids cannot be utilized.

PMID: 28062483 [PubMed - as supplied by publisher]

Successful survival of an extreme premature infant with cystic fibrosis.

BMJ Case Rep. 2017 Jan 06;2017:

Authors: Goddard T, Andersen C, Tai A

Abstract
Extreme premature infants with cystic fibrosis typically do not survive the neonatal phase. This case report describes the youngest survivor of a premature infant with cystic fibrosis and highlights the importance of advanced neonatal care with cystic fibrosis therapy.

PMID: 28062439 [PubMed - in process]

Exposure of airway epithelial cells to Pseudomonas aeruginosa biofilm-derived quorum sensing molecules decrease the activity of the anti-oxidant response element bound by NRF2.

Biochem Biophys Res Commun. 2017 Jan 03;:

Authors: Roussel L, Rousseau S

Abstract
Chronic bacterial infections in cystic fibrosis lung disease are often characterized by Pseudomonas aeruginosa biofilms that are regulated by bacterial intercellular signals termed quorum sensing (QS), such as N-(3-oxododecanoyl)-l-homoserine lactone (3OC12-HSL). This study reports that biofilm-derived exoproducts decrease the transcriptional activity of the anti-oxidant response element in bronchial epithelial cells. In a live co-culture assay of BEAS-2B cells and P. aeruginosa biofilm, the QS molecule 3OC12-HSL was an important but not sole contributor to the inhibition of basal NRF2 luciferase reporter activity. Moreover, biofilm-derived exoproducts and 3OC12-HSL decrease the expression of endogenous antioxidant response element-regulated genes hemeoxygenase-1 (HO-1) and NAD(P)H Quinone Dehydrogenase-1 (NQO-1) while they increase IL-8 expression. As previously reported, IL-8 expression is partially dependent on p38 MAPK activity, but the inhibitory effect of biofilm QS molecules on HO-1 and NQO-1 expression occurs independently of this protein kinase. Finally, the transfection of CFTRdelF508 but not its wild type counterpart decreases basal, planktonic PsaDM and sulforaphane-driven NRF2 luciferase reporter activity in BEAS-2B cells. Therefore, the presence of quorum sensing molecules derived from bacterial biofilms lowers the transcriptional activity of the anti-oxidant response element, which may contribute to the establishment of chronic bacterial infections, especially in the presence of mutated CFTR. Increasing NRF2 activity may thus be a promising strategy to potentiate anti-biofilm activity in cystic fibrosis lung disease.

PMID: 28062182 [PubMed - as supplied by publisher]

Context-sensitive network-based disease genetics prediction and its implications in drug discovery.

Bioinformatics. 2017 Jan 05;:

Authors: Chen Y, Xu R

Abstract
MOTIVATION: Disease phenotype networks play an important role in computational approaches to identifying new disease-gene associations. Current disease phenotype networks often model disease relationships based on pairwise similarities, therefore ignore the specific context on how two diseases are connected. In this study, we propose a new strategy to model disease associations using context-sensitive networks (CSNs). We developed a CSN-based phenome-driven approach for disease genetics prediction, and investigated the translational potential of the predicted genes in drug discovery.
RESULTS: We constructed CSNs by directly connecting diseases with associated phenotypes. Here, we constructed two CSNs using different data sources; the two networks contain 26 790 and 13 822 nodes respectively. We integrated the CSNs with a genetic functional relationship network and predicted disease genes using a network-based ranking algorithm. For comparison, we built Similarity-Based disease Networks (SBN) using the same disease phenotype data. In a de novo cross validation for 3324 diseases, the CSN-based approach significantly increased the average rank from top 12.6 to top 8.8% for all tested genes comparing with the SBN-based approach ([Formula: see text]). The area under the receiver operating characteristic curve for the CSN approach was also significantly higher than the SBN approach (0.91 versus 0.87, [Formula: see text]). In addition, we predicted genes for Parkinson's disease using CSNs, and demonstrated that the top-ranked genes are highly relevant to PD pathologenesis. We pin-pointed a top-ranked drug target gene for PD, and found its association with neurodegeneration supported by literature. In summary, CSNs lead to significantly improve the disease genetics prediction comparing with SBNs and provide leads for potential drug targets.
AVAILABILITY AND IMPLEMENTATION: nlp.
CASE: edu/public/data/ CONTACT: rxx@case.edu.

PMID: 28062449 [PubMed - as supplied by publisher]

Metabolomics: A potential way to know the role of vitamin D on multiple sclerosis.

J Pharm Biomed Anal. 2016 Dec 29;136:22-31

Authors: Luque-Córdoba D, Luque de Castro MD

Abstract
The literature about the influence of vitamin D on multiple sclerosis (MS) is very controversial, possibly as a result of the way through which the research on the subject has been conducted. The studies developed so far have been focused exclusively on gene expression: the effect of a given vitamin D metabolite on target receptors. The influence of the vitamin D status (either natural or after supplementation) on MS has been studied by measurement of the 25 monohydroxylated metabolite (also known as circulating form), despite the 1,25 dihydroxylated metabolite is considered the active form. In the light of the multiple metabolic pathways in which both forms of vitamin D (D2 and D3) are involved, monitoring of the metabolites is crucial to know the activity of the target enzymes as a function of both the state of the MS patient and the clinical treatment applied. The study of metabolomics aspects is here proposed to clarify the present controversy. In "omics" terms, our proposal is to take profit from up-stream information-thus is, from metabolomics to genomics-with a potential subsequent step to systems biology, if required.

PMID: 28063332 [PubMed - as supplied by publisher]

Glioblastoma on a microfluidic chip: Generating pseudopalisades and enhancing aggressiveness through blood vessel obstruction events.

Neuro Oncol. 2017 Jan 06;:

Authors: Ayuso JM, Monge R, Martínez-González A, Virumbrales-Muñoz M, Llamazares GA, Berganzo J, Hernández-Laín A, Santolaria J, Doblaré M, Hubert C, Rich JN, Sánchez-Gómez P, Pérez-García VM, Ochoa I, Fernández LJ

Abstract
BACKGROUND: Glioblastoma (GBM) is one of the most lethal tumor types. Hypercellular regions, named pseudopalisades, are characteristic in these tumors and have been hypothesized to be waves of migrating glioblastoma cells. These "waves" of cells are thought to be induced by oxygen and nutrient depletion caused by tumor-induced blood vessel occlusion. Although the universal presence of these structures in GBM tumors suggests that they may play an instrumental role in GBM's spread and invasion, the recreation of these structures in vitro has remained challenging.
METHODS: Here we present a new microfluidic model of GBM that mimics the dynamics of pseudopalisade formation. To do this, we embedded U-251 MG cells within a collagen hydrogel in a custom-designed microfluidic device. By controlling the medium flow through lateral microchannels, we can mimic and control blood-vessel obstruction events associated with this disease.
RESULTS: Through the use of this new system, we show that nutrient and oxygen starvation triggers a strong migratory process leading to pseudopalisade generation in vitro. These results validate the hypothesis of pseudopalisade formation and show an excellent agreement with a systems-biology model based on a hypoxia-driven phenomenon.
CONCLUSIONS: This paper shows the potential of microfluidic devices as advanced artificial systems capable of modeling in vivo nutrient and oxygen gradients during tumor evolution.

PMID: 28062831 [PubMed - as supplied by publisher]

Integrated Cellular and Plasma Proteomics of Contrasting B-cell Cancers Reveals Common, Unique and Systemic Signatures.

Mol Cell Proteomics. 2017 Jan 04;:

Authors: Johnston HE, Carter MJ, Cox KL, Dunscombe M, Manousopoulou A, Townsend PA, Garbis SD, Cragg MS

Abstract
Approximately 800,000 leukaemia and lymphoma cases are diagnosed worldwide each year. Burkitt's lymphoma (BL) and chronic lymphocytic leukaemia (CLL), are examples of contrasting B-cell cancers; BL is a highly aggressive lymphoid tumour, frequently affecting children, whilst CLL typically presents as an indolent, slow-progressing leukaemia affecting the elderly. The B-cell-specific over-expression of the myc and tcl1 oncogenes in mice induce spontaneous malignancies modelling BL and CLL, respectively. Quantitative mass spectrometry proteomics and isobaric labelling were employed to examine the biology underpinning contrasting Eμ-myc and Eμ-TCL1 B-cell tumours. Additionally, the plasma proteome was evaluated using sub-proteome enrichment to interrogate biomarker emergence and the systemic effects of tumour burden. Over 10,000 proteins were identified (q<0.01) of which 8270 cellular and 2095 plasma proteins were quantitatively profiled. A common B-cell tumour signature of 695 over-expressed proteins highlighted ribosome biogenesis, cell-cycle promotion and chromosome segregation. Eμ-myc tumours over-expressed several methylating enzymes and under-expressed many cytoskeletal components. Eμ-TCL1 tumours specifically over-expressed ER stress response proteins and signalling components in addition to both subunits of the interleukin-5 (IL5) receptor. IL5 treatment promoted Eμ-TCL1 tumour proliferation, suggesting an amplification of IL5-induced AKT signalling by TCL1. Tumour plasma contained a substantial tumour lysis signature, most prominent in Eμ-myc plasma, whilst Eμ-TCL1 plasma contained signatures of immune-response, inflammation and microenvironment interactions, with putative biomarkers in early-stage cancer. These findings provide a detailed characterisation of contrasting B-cell tumour models, identifying common and specific tumour mechanisms. Integrated plasma proteomics allowed the dissection of a systemic response and a tumour lysis signature present in early- and late-stage cancers, respectively. Overall, this study suggests common B-cell cancer signatures exist and illustrates the potential of the further evaluation of B-cell cancer subtypes by integrative proteomics.

PMID: 28062796 [PubMed - as supplied by publisher]

Coordinated regulation of acid resistance in Escherichia coli.

BMC Syst Biol. 2017 Jan 06;11(1):1

Authors: Aquino P, Honda B, Jaini S, Lyubetskaya A, Hosur K, Chiu JG, Ekladious I, Hu D, Jin L, Sayeg MK, Stettner AI, Wang J, Wong BG, Wong WS, Alexander SL, Ba C, Bensussen SI, Bernstein DB, Braff D, Cha S, Cheng DI, Cho JH, Chou K, Chuang J, Gastler DE, Grasso DJ, Greifenberger JS, Guo C, Hawes AK, Israni DV, Jain SR, Kim J, Lei J, Li H, Li D, Li Q, Mancuso CP, Mao N, Masud SF, Meisel CL, Mi J, Nykyforchyn CS, Park M, Peterson HM, Ramirez AK, Reynolds DS, Rim NG, Saffie JC, Su H, Su WR, Su Y, Sun M, Thommes MM, Tu T, Varongchayakul N, Wagner TE, Weinberg BH, Yang R, Yaroslavsky A, Yoon C, Zhao Y, Zollinger AJ, Stringer AM, Foster JW, Wade J, Raman S, Broude N, Wong WW, Galagan JE

Abstract
BACKGROUND: Enteric Escherichia coli survives the highly acidic environment of the stomach through multiple acid resistance (AR) mechanisms. The most effective system, AR2, decarboxylates externally-derived glutamate to remove cytoplasmic protons and excrete GABA. The first described system, AR1, does not require an external amino acid. Its mechanism has not been determined. The regulation of the multiple AR systems and their coordination with broader cellular metabolism has not been fully explored.
RESULTS: We utilized a combination of ChIP-Seq and gene expression analysis to experimentally map the regulatory interactions of four TFs: nac, ntrC, ompR, and csiR. Our data identified all previously in vivo confirmed direct interactions and revealed several others previously inferred from gene expression data. Our data demonstrate that nac and csiR directly modulate AR, and leads to a regulatory network model in which all four TFs participate in coordinating acid resistance, glutamate metabolism, and nitrogen metabolism. This model predicts a novel mechanism for AR1 by which the decarboxylation enzymes of AR2 are used with internally derived glutamate. This hypothesis makes several testable predictions that we confirmed experimentally.
CONCLUSIONS: Our data suggest that the regulatory network underlying AR is complex and deeply interconnected with the regulation of GABA and glutamate metabolism, nitrogen metabolism. These connections underlie and experimentally validated model of AR1 in which the decarboxylation enzymes of AR2 are used with internally derived glutamate.

PMID: 28061857 [PubMed - in process]

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

"Rare Diseases"[Mesh] OR "orphan disease"

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10 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 2017/01/07

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Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System.

J Vis Exp. 2016 Dec 11;(118):

Authors: Regan K, Moosavinasab S, Payne P, Lin S

Abstract
The promise of drug repurposing is that existing drugs may be used for new disease indications in order to curb the high costs and time for approval. The goal of computational methods for drug repurposing is to enable solutions for safer, cheaper and faster drug discovery. Towards this end, we developed a novel method that integrates genetic and clinical phenotype data from large-scale GWAS and PheWAS studies with detailed drug information on the concept of transitive Drug-Gene-Disease triads. We created "RE:fine Drugs," a freely available, interactive dashboard that automates gene, disease and drug-based searches to identify drug repurposing candidates. This web-based tool supports a user-friendly interface that includes an array of advanced search and export options. Results can be prioritized in a variety of ways, including but not limited to, biomedical literature support, strength and statistical significance of GWAS and/or PheWAS associations, disease indications and molecular drug targets. Here we provide a protocol that illustrates the functionalities available in the "RE:fine Drugs" system and explores the different advanced options through a case study.

PMID: 28060329 [PubMed - in process]

Predicting High-Impact Pharmacological Targets by Integrating Transcriptome and Text-Mining Features.

J Pharm Pharm Sci. 2016 Oct - Dec;19(4):475-495

Authors: Mayburd A, Baranova A

Abstract
PURPOSE: Novel, "outside of the box" approaches are needed for evaluating candidate molecules, especially in oncology. Throughout the years of 2000-2010, the efficiency of drug development fell to barely acceptable levels, and in the second decade of this century, levels have improved only marginally. This dismal condition continues despite unprecedented progress in the development of a variety of high-throughput tools, computational methods, aggregated databases, drug repurposing programs and innovative chemistries. Here we tested a hypothesis that the economic impact of targeting a particular gene product is predictable a priori by employing a combination of transcriptome profiles and quantitative metrics reflecting existing literature.
METHODS: To extract classification features, the gene expression patterns of a posteriori high-impact and low-impact anti-cancer target sets were compared. To minimize the possible bias of text-mining, the number of manuscripts published prior to the first clinical trial or relevant review paper, as well as its first derivative in this interval, were collected and used as quantitative metrics of public interest.
RESULTS: By combining the gene expression and literature mining features, a 4-fold enrichment in high-impact targets was produced, resulting in a favourable ROC curve analysis for the top impact targets. The dataset was enriched by the highest impact anti-cancer targets, while demonstrating drastic differences in economic value between high and low-impact targets. Known anti-cancer products of EGFR, ERBB2, CYP19A1/aromatase, MTOR, PTGS2, tubulin, VEGFA, BRAF, PGR, PDGFRA, SRC, REN, CSF1R, CTLA4 and HSP90AA1 genes received the highest scores for predicted impact, while microsomal steroid sulfatase, anticoagulant protein C, p53, CDKN2A, c-Jun, and TNSFS11 were highlighted as most promising research-stage targets.
CONCLUSIONS: A significant cost reduction may be achieved by a priori impact assessment of targets and ligands before their development or repurposing. Expanding a suite of combinational treatments could also decrease the costs, while achieving a higher impact per developed ligand. This article is open to POST-PUBLICATION REVIEW. Registered readers (see "For Readers") may comment by clicking on ABSTRACT on the issue's contents page.

PMID: 28057171 [PubMed - in process]

SegNet: A Deep Convolutional Encoder-Decoder Architecture for Scene Segmentation.

IEEE Trans Pattern Anal Mach Intell. 2017 Jan 02;:

Authors: Badrinarayanan V, Kendall A, Cipolla R

Abstract
We present a novel and practical deep fully convolutional neural network architecture for semantic pixel-wise segmentation termed SegNet. This core trainable segmentation engine consists of an encoder network, a corresponding decoder network followed by a pixel-wise classification layer. The architecture of the encoder network is topologically identical to the 13 convolutional layers in the VGG16 network [1]. The role of the decoder network is to map the low resolution encoder feature maps to full input resolution feature maps for pixel-wise classification. The novelty of SegNet lies is in the manner in which the decoder upsamples its lower resolution input feature map(s). Specifically, the decoder uses pooling indices computed in the max-pooling step of the corresponding encoder to perform non-linear upsampling. This eliminates the need for learning to upsample. The upsampled maps are sparse and are then convolved with trainable filters to produce dense feature maps. We compare our proposed architecture with the widely adopted FCN [2] and also with the well known DeepLab-LargeFOV [3], DeconvNet [4] architectures. This comparison reveals the memory versus accuracy trade-off involved in achieving good segmentation performance. SegNet was primarily motivated by scene understanding applications. Hence, it is designed to be efficient both in terms of memory and computational time during inference. It is also significantly smaller in the number of trainable parameters than other competing architectures and can be trained end-to-end using stochastic gradient descent. We also performed a controlled benchmark of SegNet and other architectures on both road scenes and SUN RGB-D indoor scene segmentation tasks. These quantitative assessments show that SegNet provides good performance with competitive inference time and most efficient inference memory-wise as compared to other architectures. We also provide a Caffe implementation of SegNet and a web demo at http://mi.eng.cam.ac.uk/projects/segnet/.

PMID: 28060704 [PubMed - as supplied by publisher]

An "integrated health neighbourhood" framework to optimise the use of EHR data.

J Innov Health Inform. 2016 Oct 04;23(3):826

Authors: Liaw ST, De Lusignan S

Abstract
 General practice should become the hub of integrated health neighbourhoods (IHNs), which involves sharing of information to ensure that medical homes are also part of learning organisations that use electronic health record (EHR) data for care, decision making, teaching and learning, quality improvement and research. The IHN is defined as the primary and ambulatory care services in a locality that relates largely to a single hospital-based secondary care service provider and is the logical denominator and unit of comparison for the optimal use of EHR data and health information exchange (HIE) to facilitate integration and coordination of care. Its size may vary based on the geography and requirements of the population, for example between city, suburban and rural areas. The conceptual framework includes context; integration of data, information and knowledge; integration of clinical workflow and practice; and inter-professional integration to ensure coordinated shared care to deliver safe and effective services that are equitable, accessible and culturally respectful. We illustrate how this HIE-supported IHN vision may be achieved with an Australian case study demonstrating the integration of linked pseudonymised records with knowledge- and evidence-based guidelines using semantic web tools and informatics-based methods, researching causal links bewteen data quality and quality of care and the key issues to address. The data presented in this paper form part of the evaluation of the informatics infrastructure - HIE and data repository - for its reliability and utility in supporting the IHN. An IHN can only be created if the necessary health informatics infrastructure is put in place. Integrated care may struggle to be effective without HIE.

PMID: 28059689 [PubMed - in process]

SemanticSCo: a Platform to Support the Semantic Composition of Services for Gene Expression Analysis.

J Biomed Inform. 2017 Jan 02;:

Authors: Guardia GD, Pires LF, da Silva EG, de Farias CR

Abstract
Gene expression studies often require the combined use of a number of analysis tools. However, manual integration of analysis tools can be cumbersome and error prone. To support a higher level of automation in the integration process, efforts have been made in the biomedical domain towards the development of semantic web services and supporting composition environments. Yet, most environments consider only the execution of simple service behaviours and requires users to focus on technical details of the composition process. We propose a novel approach to the semantic composition of gene expression analysis services that addresses the shortcomings of the existing solutions. Our approach includes an architecture designed to support the service composition process for gene expression analysis, and a flexible strategy for the (semi) automatic composition of semantic web services. Finally, we implement a supporting platform called SemanticSCo to realize the proposed composition approach and demonstrate its functionality by successfully reproducing a microarray study documented in the literature. The SemanticSCo platform provides support for the composition of RESTful web services semantically annotated using SAWSDL. Our platform also supports the definition of constraints/conditions regarding the order in which service operations should be invoked, thus enabling the definition of complex service behaviours. Our proposed solution for semantic web service composition takes into account the requirements of different stakeholders and addresses all phases of the service composition process. It also provides support for the definition of analysis workflows at a high-level of abstraction, thus enabling users to focus on biological research issues rather than on the technical details of the composition process. The SemanticSCo source code is available at https://github.com/usplssb/SemanticSCo.

PMID: 28057566 [PubMed - as supplied by publisher]

Primer design for SNP genotyping based on allele-specific amplification-Application to organ transplantation pharmacogenomics.

J Pharm Biomed Anal. 2016 Dec 29;136:14-21

Authors: Tortajada-Genaro LA, Puchades R, Maquieira Á

Abstract
Diagnostic methods based on single nucleotide polymorphism (SNP) biomarkers are essential for the real adoption of personalized medicine. Allele specific amplification in a homogeneous format or combined to microarray hybridization are powerful approaches for SNP genotyping. However, primers must be properly selected to minimize cross-reactivity, dimer formation and nonspecific hybridization. This study presents a design workflow diagram for the selection of required oligonucleotides for multiplex assays. Based on thermodynamic restrictions, the oligonucleotide sets are chosen for a specific amplification of wild- and mutant-type templates. Design constraints include the structural stability of primer-template duplexes, template-probe duplexes and self-annealing complexes or hairpins for each targeted gene. The performance of the design algorithm was evaluated for the simultaneous genotyping of three SNPs related to immunosuppressive drugs administered after solid organ transplantation. The assayed polymorphisms were rs1045642 (ABCB1 gene), rs1801133 (MTHFR gene) and rs776746 (CYP3A5 gene). Candidates were confirmed by discriminating homozygote and heterozygote populations using a fluorescence solution method and two colorimetric microarray methods on polycarbonate chips. The analysis of patient samples provided excellent genotyping results compared to those obtained by a reference method. The study demonstrates that the development of the allele-specific methods as pharmacogenetic tools can be simplified.

PMID: 28061365 [PubMed - as supplied by publisher]

Nontraditional Career Opportunities for Pharmacists.

Hosp Pharm. 2016 Dec;51(11):944-949

Authors: Bai S, Hertig JB, Weber RJ

Abstract
The changing landscape of health care mirrors that of health-system pharmacy, with pharmacists' scope of practice and provider status being the most significant changes. This creates new roles and opportunities; many of these roles are considered to be nontraditional in today's practice. This article reviews some new roles for pharmacy leaders that provide different career options and pathways. Nontraditional career opportunities discussed include expanded consulting roles in pricing analytics and drug pricing programs (contracting, 340B programs), pharmacogenomics patient consult services and clinics, specialty drug pharmacies, and compounding pharmacy services. To continue to develop high-performing pharmacy departments, pharmacy directors should recognize these roles and ensure they are clearly defined and managed. With the advent of these nontraditional opportunities, pharmacy departments can further expand their ability to provide advanced patient-centered pharmacy services.

PMID: 28057956 [PubMed - in process]

Genomic translational research: Paving the way to individualized cardiac functional analyses and personalized cardiology.

Int J Cardiol. 2016 Dec 21;:

Authors: Pasipoularides A

Abstract
For most of Medicine's past, the best that physicians could do to cope with disease prevention and treatment was based on the expected response of an average patient. Currently, however, a more personalized/precise approach to cardiology and medicine in general is becoming possible, as the cost of sequencing a human genome has declined substantially. As a result, we are witnessing an era of precipitous advances in biomedicine and bourgeoning understanding of the genetic basis of cardiovascular and other diseases, reminiscent of the resurgence of innovations in physico-mathematical sciences and biology-anatomy-cardiology in the Renaissance, a parallel time of radical change and reformation of medical knowledge, education and practice. Now on the horizon is an individualized, diverse patient-centered, approach to medical practice that encompasses the development of new, gene-based diagnostics and preventive medicine tactics, and offers the broadest range of personalized therapies based on pharmacogenetics. Over time, translation of genomic and high-tech approaches unquestionably will transform clinical practice in cardiology and medicine as a whole, with the adoption of new personalized medicine approaches and procedures. Clearly, future prospects far outweigh present accomplishments, which are best viewed as a promising start. It is now essential for pluridisciplinary health care providers to examine the drivers and barriers to the clinical adoption of this emerging revolutionary paradigm, in order to expedite the realization of its potential. So, we are not there yet, but we are definitely on our way.

PMID: 28057368 [PubMed - as supplied by publisher]