The chemical, genetic and immunological basis of idiosyncratic drug-induced liver injury.

Hum Exp Toxicol. 2015 Dec;34(12):1310-7

Authors: Tailor A, Faulkner L, Naisbitt DJ, Park BK

Abstract
Idiosyncratic drug reactions can be extremely severe and are not accounted for by the regular pharmacology of a drug. Thus, the mechanism of idiosyncratic drug-induced liver injury (iDILI), a phenomenon that occurs with many drugs including β-lactams, anti-tuberculosis drugs and non-steroidal anti-inflammatories, has been difficult to determine and remains a pressing issue for patients and drug companies. Evidence has shown that iDILI is multifactorial and multifaceted, which suggests that multiple cellular mechanisms may be involved. However, a common initiating event has been proposed to be the formation of reactive drug metabolites and covalently bound adducts. Although the fate of these metabolites are unclear, recent evidence has shown a possible link between iDILI and the adaptive immune system. This review highlights the role of reactive metabolites, the recent genetic innovations which have provided molecular targets for iDILI, and the current literature which suggests an immunological basis for iDILI.

PMID: 26614821 [PubMed - indexed for MEDLINE]

Combinatorial Versus Individual Gene Pharmacogenomic Testing in Mental Health: A Perspective on Context and Implications on Clinical Utility.

Yale J Biol Med. 2015 Dec;88(4):375-82

Authors: Winner JG, Dechairo B

Abstract
Pharmacogenomic testing in mental health has not yet reached its full potential. An important reason for this involves differentiating individual gene testing (IGT) from a combinatorial pharmacogenomic (CPGx) approach. With IGT, any given gene reveals specific information that may, in turn, pertain to a smaller number of medications. CPGx approaches attempt to encompass more complete genomic information by combining moderate risk alleles and synergistically viewing the results from the perspective of the medication. This manuscript will discuss IGT and CPGx approaches to psychiatric pharmacogenomics and review the clinical validity, clinical utility, and economic parameters of both.

PMID: 26604861 [PubMed - indexed for MEDLINE]

A Liver-Centric Multiscale Modeling Framework for Xenobiotics.

PLoS One. 2016;11(9):e0162428

Authors: Sluka JP, Fu X, Swat M, Belmonte JM, Cosmanescu A, Clendenon SG, Wambaugh JF, Glazier JA

Abstract
We describe a multi-scale, liver-centric in silico modeling framework for acetaminophen pharmacology and metabolism. We focus on a computational model to characterize whole body uptake and clearance, liver transport and phase I and phase II metabolism. We do this by incorporating sub-models that span three scales; Physiologically Based Pharmacokinetic (PBPK) modeling of acetaminophen uptake and distribution at the whole body level, cell and blood flow modeling at the tissue/organ level and metabolism at the sub-cellular level. We have used standard modeling modalities at each of the three scales. In particular, we have used the Systems Biology Markup Language (SBML) to create both the whole-body and sub-cellular scales. Our modeling approach allows us to run the individual sub-models separately and allows us to easily exchange models at a particular scale without the need to extensively rework the sub-models at other scales. In addition, the use of SBML greatly facilitates the inclusion of biological annotations directly in the model code. The model was calibrated using human in vivo data for acetaminophen and its sulfate and glucuronate metabolites. We then carried out extensive parameter sensitivity studies including the pairwise interaction of parameters. We also simulated population variation of exposure and sensitivity to acetaminophen. Our modeling framework can be extended to the prediction of liver toxicity following acetaminophen overdose, or used as a general purpose pharmacokinetic model for xenobiotics.

PMID: 27636091 [PubMed - as supplied by publisher]

CardioTF, a database of deconstructing transcriptional circuits in the heart system.

PeerJ. 2016;4:e2339

Authors: Zhen Y

Abstract
BACKGROUND: Information on cardiovascular gene transcription is fragmented and far behind the present requirements of the systems biology field. To create a comprehensive source of data for cardiovascular gene regulation and to facilitate a deeper understanding of genomic data, the CardioTF database was constructed. The purpose of this database is to collate information on cardiovascular transcription factors (TFs), position weight matrices (PWMs), and enhancer sequences discovered using the ChIP-seq method.
METHODS: The Naïve-Bayes algorithm was used to classify literature and identify all PubMed abstracts on cardiovascular development. The natural language learning tool GNAT was then used to identify corresponding gene names embedded within these abstracts. Local Perl scripts were used to integrate and dump data from public databases into the MariaDB management system (MySQL). In-house R scripts were written to analyze and visualize the results.
RESULTS: Known cardiovascular TFs from humans and human homologs from fly, Ciona, zebrafish, frog, chicken, and mouse were identified and deposited in the database. PWMs from Jaspar, hPDI, and UniPROBE databases were deposited in the database and can be retrieved using their corresponding TF names. Gene enhancer regions from various sources of ChIP-seq data were deposited into the database and were able to be visualized by graphical output. Besides biocuration, mouse homologs of the 81 core cardiac TFs were selected using a Naïve-Bayes approach and then by intersecting four independent data sources: RNA profiling, expert annotation, PubMed abstracts and phenotype.
DISCUSSION: The CardioTF database can be used as a portal to construct transcriptional network of cardiac development.
AVAILABILITY AND IMPLEMENTATION: Database URL: http://www.cardiosignal.org/database/cardiotf.html.

PMID: 27635320 [PubMed]

Systems Biology - Opportunities and Challenges: The Application of Proteomics to Study the Cardiovascular Extracellular Matrix.

Cardiovasc Res. 2016 Sep 15;

Authors: Barallobre-Barreiro J, Lynch M, Yin X, Mayr M

Abstract
Systems biology approaches including proteomics are becoming more widely used in cardiovascular research. In this review article, we focus on the application of proteomics to the cardiac extracellular matrix. Extracellular matrix remodelling is a hallmark of many cardiovascular diseases. Proteomic techniques using mass spectrometry provide a platform for the comprehensive analysis of extracellular matrix proteins without a priori assumptions. Proteomics overcomes various constraints inherent to conventional antibody detection. On the other hand, studies that use whole tissue lysates for proteomic analysis mask the identification of the less abundant extracellular matrix constituents. In this review, we first discuss decellularization-based methods that enrich for extracellular matrix proteins in cardiac tissue, and how targeted mass spectrometry allows for accurate protein quantification. The second part of the review will focus on post-translational modifications including hydroxylation and glycosylation and on the release of matrix fragments with biological activity (matrikines), all of which can be interrogated by proteomic techniques.

PMID: 27635058 [PubMed - as supplied by publisher]

Systematic network assessment of the carcinogenic activities of cadmium.

Toxicol Appl Pharmacol. 2016 Sep 12;

Authors: Chen P, Duan X, Li M, Huang C, Li J, Chu R, Ying H, Song H, Jia X, Ba Q, Wang H

Abstract
Cadmium has been defined as type I carcinogen for humans, but the underlying mechanisms of its carcinogenic activity and its influence on protein-protein interactions in cells are not fully elucidated. The aim of the current study was to evaluate, systematically, the carcinogenic activity of cadmium with systems biology approaches. From a literature search of 209 studies that performed with cellular models, 208 proteins influenced by cadmium exposure were identified. All of these were assessed by Western blotting and were recognized as key nodes in network analyses. The protein-protein functional interaction networks were constructed with NetBox software and visualized with Cytoscape software. These cadmium-rewired genes were used to construct a scale-free, highly connected biological protein interaction network with 850 nodes and 8770 edges. Of the network, nine key modules were identified and 60 key signaling pathways, including the estrogen, RAS, PI3K-Akt, NF-kB, HIF-1α, Jak-STAT, and TGF-β signaling pathways, were significantly enriched. With breast cancer, colorectal and prostate cancer cellular models, we validated the key node genes in the network that had been previously reported or inferred form the network by Western blotting methods, including STAT3, JNK, p38, SMAD2/3, P65, AKT1, and HIF-1α. These results suggested the established network was robust and provided a systematic view of the carcinogenic activities of cadmium in human.

PMID: 27634459 [PubMed - as supplied by publisher]

Putting RNA to work: Translating RNA fundamentals into biotechnological engineering practice.

Biotechnol Adv. 2015 Dec;33(8):1829-44

Authors: Peters G, Coussement P, Maertens J, Lammertyn J, De Mey M

Abstract
Synthetic biology, in close concert with systems biology, is revolutionizing the field of metabolic engineering by providing novel tools and technologies to rationally, in a standardized way, reroute metabolism with a view to optimally converting renewable resources into a broad range of bio-products, bio-materials and bio-energy. Increasingly, these novel synthetic biology tools are exploiting the extensive programmable nature of RNA, vis-à-vis DNA- and protein-based devices, to rationally design standardized, composable, and orthogonal parts, which can be scaled and tuned promptly and at will. This review gives an extensive overview of the recently developed parts and tools for i) modulating gene expression ii) building genetic circuits iii) detecting molecules, iv) reporting cellular processes and v) building RNA nanostructures. These parts and tools are becoming necessary armamentarium for contemporary metabolic engineering. Furthermore, the design criteria, technological challenges, and recent metabolic engineering success stories of the use of RNA devices are highlighted. Finally, the future trends in transforming metabolism through RNA engineering are critically evaluated and summarized.

PMID: 26514597 [PubMed - indexed for MEDLINE]

Pyruvate production in Candida glabrata: manipulation and optimization of physiological function.

Crit Rev Biotechnol. 2016;36(1):1-10

Authors: Li S, Chen X, Liu L, Chen J

Abstract
Candida glabrata, a multi-vitamin auxotrophic yeast, can accumulate a large amount of pyruvate extracellularly using glucose as the carbon source, a characteristic that has facilitated the cost-effective biotechnological production of pyruvate on an industrial scale. In this review, we describe the current advances in further improving the performance of C. glabrata for efficient pyruvate production, which includes: optimization of the vitamin and dissolved oxygen concentrations, regulation of intracellular cofactor levels and improvement of the environmental robustness of C. glabrata. We also discuss the current efforts using systems biology to understand the metabolism of C. glabrata. Finally, perspectives on engineering and exploiting C. glabrata as a cell factory for efficiently producing various chemicals and materials are discussed.

PMID: 23883073 [PubMed - indexed for MEDLINE]

Annotating the Function of the Human Genome with Gene Ontology and Disease Ontology.

Biomed Res Int. 2016;2016:4130861

Authors: Hu Y, Zhou W, Ren J, Dong L, Wang Y, Jin S, Cheng L

Abstract
Increasing evidences indicated that function annotation of human genome in molecular level and phenotype level is very important for systematic analysis of genes. In this study, we presented a framework named Gene2Function to annotate Gene Reference into Functions (GeneRIFs), in which each functional description of GeneRIFs could be annotated by a text mining tool Open Biomedical Annotator (OBA), and each Entrez gene could be mapped to Human Genome Organisation Gene Nomenclature Committee (HGNC) gene symbol. After annotating all the records about human genes of GeneRIFs, 288,869 associations between 13,148 mRNAs and 7,182 terms, 9,496 associations between 948 microRNAs and 533 terms, and 901 associations between 139 long noncoding RNAs (lncRNAs) and 297 terms were obtained as a comprehensive annotation resource of human genome. High consistency of term frequency of individual gene (Pearson correlation = 0.6401, p = 2.2e - 16) and gene frequency of individual term (Pearson correlation = 0.1298, p = 3.686e - 14) in GeneRIFs and GOA shows our annotation resource is very reliable.

PMID: 27635398 [PubMed - in process]

Stacked Ensemble Combined with Fuzzy Matching for Biomedical Named Entity Recognition of Diseases.

J Biomed Inform. 2016 Sep 12;

Authors: Bhasuran B, Murugesan G, Abdulkadhar S, Natarajan J

Abstract
Biomedical Named Entity Recognition (Bio-NER) is the crucial initial step in the information extraction process and a majorly focused research area in biomedical text mining. In the past years, several models and methodologies have been proposed for the recognition of semantic types related to gene, protein, chemical, drug and other biological relevant named entities. In this paper, we implementeda stacked ensembleapproachcombined with fuzzy matching for biomedical named entity recognition of disease names. The underlying concept of stacked generalizationisto combines the outputs of base-levelclassifiersusing a second-level meta-classifier in an ensemble. We used Conditional Random Field (CRF) as the underlying classification methods that makeuse of a diverse set of features, mostly based on domain specific, orthographic and morphologically relevant. In addition, we used fuzzy string matching to tag rare diseases names from our in-house disease dictionary. For fuzzy matching, we incorporated two best fuzzy search algorithms Rabin Karp and Tuned Boyer Moore. Our proposed approach shows promised result of 94.66%, 89.12% and 84.10%, 76.71% of F-measure while on evaluating training and testing set of both NCBI disease and BioCreative V CDR Corpora.

PMID: 27634494 [PubMed - as supplied by publisher]

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A Network-Based Data Integration Approach to Support Drug Repurposing and Multi-Target Therapies in Triple Negative Breast Cancer.

PLoS One. 2016;11(9):e0162407

Authors: Vitali F, Cohen LD, Demartini A, Amato A, Eterno V, Zambelli A, Bellazzi R

Abstract
The integration of data and knowledge from heterogeneous sources can be a key success factor in drug design, drug repurposing and multi-target therapies. In this context, biological networks provide a useful instrument to highlight the relationships and to model the phenomena underlying therapeutic action in cancer. In our work, we applied network-based modeling within a novel bioinformatics pipeline to identify promising multi-target drugs. Given a certain tumor type/subtype, we derive a disease-specific Protein-Protein Interaction (PPI) network by combining different data-bases and knowledge repositories. Next, the application of suitable graph-based algorithms allows selecting a set of potentially interesting combinations of drug targets. A list of drug candidates is then extracted by applying a recent data fusion approach based on matrix tri-factorization. Available knowledge about selected drugs mechanisms of action is finally exploited to identify the most promising candidates for planning in vitro studies. We applied this approach to the case of Triple Negative Breast Cancer (TNBC), a subtype of breast cancer whose biology is poorly understood and that lacks of specific molecular targets. Our "in-silico" findings have been confirmed by a number of in vitro experiments, whose results demonstrated the ability of the method to select candidates for drug repurposing.

PMID: 27632168 [PubMed - as supplied by publisher]

Systems Biology-Based Investigation of Cellular Antiviral Drug Targets Identified by Gene-Trap Insertional Mutagenesis.

PLoS Comput Biol. 2016 Sep;12(9):e1005074

Authors: Cheng F, Murray JL, Zhao J, Sheng J, Zhao Z, Rubin DH

Abstract
Viruses require host cellular factors for successful replication. A comprehensive systems-level investigation of the virus-host interactome is critical for understanding the roles of host factors with the end goal of discovering new druggable antiviral targets. Gene-trap insertional mutagenesis is a high-throughput forward genetics approach to randomly disrupt (trap) host genes and discover host genes that are essential for viral replication, but not for host cell survival. In this study, we used libraries of randomly mutagenized cells to discover cellular genes that are essential for the replication of 10 distinct cytotoxic mammalian viruses, 1 gram-negative bacterium, and 5 toxins. We herein reported 712 candidate cellular genes, characterizing distinct topological network and evolutionary signatures, and occupying central hubs in the human interactome. Cell cycle phase-specific network analysis showed that host cell cycle programs played critical roles during viral replication (e.g. MYC and TAF4 regulating G0/1 phase). Moreover, the viral perturbation of host cellular networks reflected disease etiology in that host genes (e.g. CTCF, RHOA, and CDKN1B) identified were frequently essential and significantly associated with Mendelian and orphan diseases, or somatic mutations in cancer. Computational drug repositioning framework via incorporating drug-gene signatures from the Connectivity Map into the virus-host interactome identified 110 putative druggable antiviral targets and prioritized several existing drugs (e.g. ajmaline) that may be potential for antiviral indication (e.g. anti-Ebola). In summary, this work provides a powerful methodology with a tight integration of gene-trap insertional mutagenesis testing and systems biology to identify new antiviral targets and drugs for the development of broadly acting and targeted clinical antiviral therapeutics.

PMID: 27632082 [PubMed - as supplied by publisher]

The role of ontologies in biological and biomedical research: a functional perspective.

Brief Bioinform. 2015 Nov;16(6):1069-80

Authors: Hoehndorf R, Schofield PN, Gkoutos GV

Abstract
Ontologies are widely used in biological and biomedical research. Their success lies in their combination of four main features present in almost all ontologies: provision of standard identifiers for classes and relations that represent the phenomena within a domain; provision of a vocabulary for a domain; provision of metadata that describes the intended meaning of the classes and relations in ontologies; and the provision of machine-readable axioms and definitions that enable computational access to some aspects of the meaning of classes and relations. While each of these features enables applications that facilitate data integration, data access and analysis, a great potential lies in the possibility of combining these four features to support integrative analysis and interpretation of multimodal data. Here, we provide a functional perspective on ontologies in biology and biomedicine, focusing on what ontologies can do and describing how they can be used in support of integrative research. We also outline perspectives for using ontologies in data-driven science, in particular their application in structured data mining and machine learning applications.

PMID: 25863278 [PubMed - indexed for MEDLINE]

ePGA: A Web-Based Information System for Translational Pharmacogenomics.

PLoS One. 2016;11(9):e0162801

Authors: Lakiotaki K, Kartsaki E, Kanterakis A, Katsila T, Patrinos GP, Potamias G

Abstract
One of the challenges that arise from the advent of personal genomics services is to efficiently couple individual data with state of the art Pharmacogenomics (PGx) knowledge. Existing services are limited to either providing static views of PGx variants or applying a simplistic match between individual genotypes and existing PGx variants. Moreover, there is a considerable amount of haplotype variation associated with drug metabolism that is currently insufficiently addressed. Here, we present a web-based electronic Pharmacogenomics Assistant (ePGA; http://www.epga.gr/) that provides personalized genotype-to-phenotype translation, linked to state of the art clinical guidelines. ePGA's translation service matches individual genotype-profiles with PGx gene haplotypes and infers the corresponding diplotype and phenotype profiles, accompanied with summary statistics. Additional features include i) the ability to customize translation based on subsets of variants of clinical interest, and ii) to update the knowledge base with novel PGx findings. We demonstrate ePGA's functionality on genetic variation data from the 1000 Genomes Project.

PMID: 27631363 [PubMed - as supplied by publisher]

Pharmacogenomics of Rosuvastatin: A Glocal (Global+Local) African Perspective and Expert Review on a Statin Drug.

OMICS. 2016 Sep;20(9):498-509

Authors: Soko ND, Masimirembwa C, Dandara C

Abstract
The incidence of cardiovascular diseases (CVDs) in African populations residing in the African continent is on the rise fueled by both a steady increase in CVD risk factors and comorbidities such as human immunodeficiency virus/acquired immune deficiency syndrome (HIV/AIDS), tuberculosis, and parasitic diseases such as bilharzia. Statins are recommended together with lifestyle changes in the treatment of hypercholesterolemia and overall reduction of cardiovascular events. Rosuvastatin in particular is an attractive candidate in the management of CVDs in African populations often plagued with multimorbidities owing to both its potency and low drug-to-drug interaction potential. In this expert review, we describe the pharmacogenetics of rosuvastatin and how it may instrumentally affect the African populations. We describe polymorphisms in the candidate genes, ABCG2, SLCO1B1, CYP2C9, APOE, PCSK9, LDLR, LPA, and HMGCR, and their role in the potency and safety of rosuvastatin therapy. We report on qualitative and quantitative differences in the distribution of genetic variants that affect efficacy and toxicity of rosuvastatin. These differences are observed across world populations (Caucasian, European, and Asian) as well as within African populations. Finally, we advocate for extensive pharmacogenetic studies in African populations that take into account the genetic diversity of intra-African ethnic groups and the genetic differences between African populations and other global populations, with a collaborative and collective aim to provide effective and safe use of rosuvastatin in management of CVD in Africa. Our key thesis presented in this innovation field analysis is that rosuvastatin precision medicine can serve as a veritable Glocal (Global and Local) model to offer pharmacogenetic-guided optimal therapeutics for the public in both developing and developed regions of the world.

PMID: 27631189 [PubMed - as supplied by publisher]

Functional characterization of CYP2D6 novel allelic variants identified in the Chinese Han population.

Pharmacogenomics. 2016;17(2):119-9

Authors: Xu Q, Wu Z, Yang L, Zhang X, Gai Z, Chen L, He L, Qin S

Abstract
AIM: This study was aimed to functionally characterize four novel CYP2D6 alleles identified in Chinese Han population.
MATERIALS & METHODS: CYP2D6 proteins of wild-type and the four novel variants along with CYP2D6.2 and CYP2D6.10 were heterologously expressed in yeast cells and the kinetic parameters were determined.
RESULTS: Compared with CYP2D6.1 (frequency in Chinese 24.65%), CYP2D6.X (1.63%), CYP2D6.Y (1.50%), CYP2D6.Z (0.81%), CYP2D6.10 (52.53%) and CYP2D6.75 (0.13%) exhibited low activity at different degrees, whereas the kinetic parameters of CYP2D6.2 (11.06%) were much the same with CYP2D6.1. The novel allele CYP2D6.75 showed decreased enzyme activity.
CONCLUSION: This is the first study to conduct functional analysis of CYP2D6 four novel alleles in Chinese Han population, which might be helpful for optimizing pharmacotherapy and the design of personalized medicine.

PMID: 26652007 [PubMed - indexed for MEDLINE]

The 3-I framework: a framework for developing public policies regarding pharmacogenomics (PGx) testing in Canada.

Genome. 2015 Dec;58(12):527-40

Authors: Bashir NS, Ungar WJ

Abstract
The 3-I framework of analyzing the ideas, interests, and institutions around a topic has been used by political scientists to guide public policy development. In Canada, there is a lack of policy governing pharmacogenomics (PGx) testing compared to other developed nations. The goal of this study was to use the 3-I framework, a policy development tool, and apply it to PGx testing to identify and analyze areas where current policy is limited and challenges exist in bringing PGx testing into wide-spread clinical practice in Canada. A scoping review of the literature was conducted to determine the extent and challenges of PGx policy implementation at federal and provincial levels. Based on the 3-I analysis, contentious ideas related to PGx are (i) genetic discrimination, (ii) informed consent, (iii) the lack of knowledge about PGx in health care, (iv) the value of PGx testing, (v) the roles of health care workers in the coordination of PGx services, and (vi) confidentiality and privacy. The 3-I framework is a useful tool for policy makers, and applying it to PGx policy development is a new approach in Canadian genomics. Policy makers at every organizational level can use this analysis to help develop targeted PGx policies.

PMID: 26623513 [PubMed - indexed for MEDLINE]

The Pharmacogenomics of Anti-Platelet Intervention (PAPI) Study: Variation in Platelet Response to Clopidogrel and Aspirin.

Curr Vasc Pharmacol. 2016;14(1):116-24

Authors: Bozzi LM, Mitchell BD, Lewis JP, Ryan KA, Herzog WR, O'Connell JR, Horenstein RB, Shuldiner AR, Yerges-Armstrong LM

Abstract
Clopidogrel and aspirin are commonly prescribed anti-platelet medications indicated for patients who have experienced, or are at risk for, ischemic cardiovascular events. The Pharmacogenomics of Anti-Platelet Intervention (PAPI) Study was designed to characterize determinants of clopidogrel and dual anti-platelet therapy (DAPT) response in a healthy cohort of Old Order Amish from Lancaster, PA. Following a loading dose, clopidogrel was taken once a day for 7 days. One hour after the last dose of clopidogrel, 325 mg of aspirin was given. Ex vivo platelet aggregometry was performed at baseline, post-clopidogrel, and post-DAPT. Platelet aggregation measurements were significantly lower after both interventions for all agonists tested (p <0.05), although there was large inter-individual variation in the magnitude of anti-platelet response. Female sex and older age were associated with higher platelet aggregation at all three time-points. Change in aggregation was correlated among the various agonists at each time point. Heritability (h2) of change in platelet aggregation was significant for most traits at all time-points (range h2=0.14-0.57). Utilization of a standardized, short-term intervention provided a powerful approach to investigate sources of variation in platelet aggregation response due to drug therapy. Further, this short-term intervention approach may provide a useful paradigm for pharmacogenomics studies.

PMID: 26374108 [PubMed - indexed for MEDLINE]