ADR substantiation workflow tutorial
Contents
1. 1 2 3 Select the proteins nodes that constitute the Drug Target Profile a Using the nodeType attribute drug select the First neighbours of the drug nodes using the menu Select gt Nodes gt First Neighbours of selected nodes b Create a new graph with the selected nodes File gt New gt Network gt From selected nodes all edges This will create a new sub graph representing the Drug Target Profile Select the proteins nodes that constitute the Event Protein Profile a Repeat the same procedure to create a graph representing the Event Protein Profile Now we will find the intersection between the Drug Target Profile and the Event Protein Profile this intersection will represent the drug event linking proteins a Goto Plugins gt Advance Network Merge b Select operation intersection c Select the networks you want to merge d In the Advanced Network Merge panel choose the attributes of the nodes you will use to merge in this case choose ID e By clicking Merge you will obtain the protein nodes that link the drug and the event In the example using haloperidol and prolongation of QT interval this operation will result in 3 protein nodes KCNH1 KCNH2 CACNA1C You can inspect node and edge attributes to learn more about the connections between the drug and the event through proteins If the drug and the event are no connected through proteins this operation will lead to an empty set Alternatively2. Add URL The signal substantiation workflow seeks 8 NOSADO1 to establish a connection between the Add a new input value clinical event and the drug through different paths i through proteins in common between the drug target and the event protein profiles ii assessing if the proteins in the drug target profile and in the event protein profile participate in a common biological pathway N Workflow author Anna Bauer Mehren Integrative Biomedical Informatics Laboratory GRIB IMIM Hospital del Mar UPF Barcelona Spain This workflow is distributed under the GNU GPL licence http www gnu org licenses gpl html Added new value Edit value on right lt gt Load previous values lt gt Save values Run workflow Cancel 10 ADR Substantiation workflow tutorial The ADR S workflow has the following values as input atc corresponds to the input drug It accepts an ATC Anatomical Therapeutic Chemical http www whocc no atc_ddd_index code for a drug 5th level 7 digits Example value NOSADO1 Figure 5 encoding the antipsychotic drug haloperidol e event corresponds to the input clinical event For the clinical events the following input types are allowed 1 UMLS UMLS concept identifiers for example C0003811 2 EUADR_EVENT clinical events observed as adverse drug reactions according to the EU ADR project for example UGIB See section 6 for more details If you use option 1
3. 8 9 These events were defined in terms of UMLS Metathesaurus concept identifiers as described in 8 10 The event codes and names as defined in the EU ADR project are listed in Table 1 The mapping of events codes or strings to UMLS Metathesaurus concept identifiers and other vocabularies such MeSH and OMIM is implemented within the web services The ADR S workflow accepts events as defined in the EU ADR project or any other clinical event defined by UMLS concept identifier The UMLS concept identifiers are processed to map them to MeSH and OMIM identifiers using UMILS Metathesaurus 17 ADR Substantiation workflow tutorial 7 Service ports http ibi imim es axis2 services AdrPathService wsdl http cgl imim es axis2 services cglAlertService wsdl 8 Workflow URL http www myexperiment org workflows 1988 html 9 References 1 Swanson DR 1986 Fish oil raynaud s syndrome and undiscovered public knowledge Perspect Biol Med 30 1 7 18 2 Garcia Serna R Mestres J 2010 Anticipating drug side effects by comparative pharmacology Expert Opin Drug Metab Toxicol 6 10 1253 1263 3 Bauer Mehren A Rautschka M Sanz F Furlong LI 2010 DisGeNET A cytoscape plugin to visualize integrate search and analyze gene disease networks Bioinformatics 26 22 2924 2926 4 Lenz W 1970 Phenocopy Hum Genet 9 3 227 229 5 Vastrik D Eustachio P Schmidt E Joshi Tope G Gopinath G et al 2007 Reactome A knowled
4. define a common XML interoperability structure The first one describes general data types and the second one defines the specific types needed for signal filtering and substantiation in the context of the EU ADR project Both schemas allow a smooth integration of the different modules in Taverna workflows by enabling content and structure validation for the workflow input and output XML files Moreover the use of schemas facilitates further data transformations for example by applying XSL transformation to XML files of the signal substantiation workflow to create XGMML file graphs that can be visualized with Cytoscape All workflows have been implemented and tested using Taverna Workflow Management system version 2 2 Figure 1 The signal substantiation process involves the automatic search for evidences that support the causal inference of the potential signal A Signal substantiation through proteins The profile of targets of the drug and its metabolites is obtained by in silico profiling methods Drug Target Profile The profile of proteins associated with the clinical event is obtained by mining DisGeNET Event Protein Profile The profiles are compared to find proteins in common in both profiles Drug Event Linking Proteins The evidences that support the association of the drug and event with the Drug Event Linking proteins are explored to determine if they support the causal inference of the signal B Signal substantiation through path
5. gt Organic 14 ADR Substantiation workflow tutorial Figure 12 Taverna Workbench 2 2 0 File Edit Insert View Workflows Advanced Help ix avee RITITI BS Design fq Results myExperiment lick on a run to see its values lick on a service in the diagram o see intermediate values if available ADR_substantiation 2011 07 29 17 12 36 Workflow runs Graph Progress report OWS Finished Pause amp Cancel Refresh intermediate values Show workflow results Workflow results E Save all values drugEventLinkingPathways Y drugEventLinkingProteins V drugTargets V drugTargetsOutput V eventProteins V eventProteinsOutput V C aa toscan event __evertame eventTyp2A Jus OtoscapaResultGraph V Clickintreeto viewvalues I Valuetype Refresh E Save value F value 1 Figure 13 0 File Edit View Select Layout Plugins Help Cytoscape Desktop New Session Control Panel SA QQQQ 8B ARs lB se a v Nodes Edges 128 0 1180 0 ID SMILE nodeType styleName Node Attribute Browser Attribute Browser Edge Attribute Browser Network Attribute Browser 15 ADR Substantiation workflow tutorial To find out if the drug and the event are connected through proteins you can use Cytoscape functionalities The following steps will guide you to use Cytoscape functions to select nodes that link the drug and the event nodes Protein linking nodes
6. ATC code for the drug Internal identifier for the node in the network Internal identifier for the metabolite Internal identifier for the node in the network The UMLS CUI for the event Not provided Not applicable Internal identifier for the node in the network The UniProt accession number for the protein Not applicable The SMILE string corresponding to the drug structure Anaphylactic Shock Acute Renal Failure Acute Myocardial Infarction Acute Liver Injury Cardiac Valve Fibrosis Upper gastrointestinal bleeding Rhabdomyolysis Aplastic anemia Pancytopenia Neutropenia Agranulocytosis QT Prolongation styleName Common name for the node The generic drug name Common name for the node Numbered metabolite Common name for the node Name of the UMLS CUI concept extracted from UMLS Common name for the node Gene symbol for the protein as in UniProt nodeType Drug Drug Event Protein 19 ADR Substantiation workflow tutorial Table 3 Edge attributes in the Cytoscape result graph Drug protein Metabolite protein Event protein ID Internal identifier constructed of the ATC code of the drug and the UniProt identifier of the protein Internal identifier constructed of the metabolite identifier and the UniProt identifier for the protein Internal identifier constructed of the UMLS CUI concept and the UniProt identifier of the protein bindingValue The binding aff
7. Substantiation workflow tutorial The workflow will load You can inspect the structure of the workflow in the Workflow Diagram Panel Figure 3 Figure 3 Taverna Workbench 2 2 0 File Edit Insert View Workflows Advanced Help SOx gt ave i COFFEE BY _ Design amp Results Gj myExperiment Service panel Workflow diagram Filter Clear PARQ SHO SH A Import new services v Available services gt Service templates gt Local services gt Biomart http www biomart org biomart martservice gt Biomoby http moby ucalgary ca moby MOBY Central p gt Soaplab http www ebi ac uk soaplab services gt WSDL http soap bind ca wsdl bind wsdl v H Workflow explorer Details Validation report v ADR_substantiation a Y amp Workflow input ports A atc A cytoscape A event A eventName A eventType Y amp Workflow output ports Y CytoscapeResultGraph Y drugEventLinkingPathways Y drugEventLinkingProteins Y drugTargets Y drugTargetsOutput Y eventProteins Y eventProteinsOutput Y amp Services v amp ADR_substantiation_through_proteins atc 72 cytoscape 7 event A eee c Run the workflow Go to File gt Run workflow or use the Run workflow shortcut button in Taverna Before running a workflow Taverna performs a validation of the workflow You will see a pop up window indicating that the workflow has warnings Figu
8. a drug encoded by the ATC code at the 7 digits level and provides as output the chemical structure by means of SMILE Simplified Molecular Input Line Entry Specification getUniprotListFromSmile cglAlertService This method accepts as input a drug or metabolite encoded by a SMILE and returns a list of proteins that are related to the drug Drug Target Profile We use known drug target associations and extend them with in silico target profiling methods 2 Drug metabolites are obtained from a commercial database GVK Biosciences and are also processed by in silico target profiling The evidences that support each drug target relationship such as the binding affinity of the compound to the protein or the source database are provided getDiseaseAssociatedProteins adrPathService This method accepts as input a clinical event encoded as a list of UMLS concept identifiers or as a string as defined in Table 1 and returns a list of proteins associated to the event Event Protein Profile by interrogating the DisGeNET database 3 Evidences that support each association including the association type source database publications discussing the association and in the case of text mining derived associations the sentence that reports the gene disease association are provided getPathways adrPathService This method assesses if proteins associated to the drug and the event are annotated to the same biological pathway by interrogating React
9. pop up window will appear indicating the results Figure 10 Figure 10 A YES this drug event pair is connected through proteins There are 3 drug event linking proteins To inspect the results in more detail 1 Save the CytoscapeResultGraph as xgmml file 2 Open the file using Cytoscape 3 Load the visual style available at http ibi imim es eu adr EUADR_style props into Cytoscape al When the second part of the workflow execution finishes a pop up window will appear indicating the results Figure 11 Once the workflow execution finishes all results are found in the Taverna results panel Figure 12 Figure 11 YES this drug event pair is connected through pathways There are 5 pathways that link the drug and the event To inspect the results in more detail 1 Save the drugEventLinkingPathways as html file 2 Open the file in a web browser Cytoscape graph results If you provided the path of your local Cytoscape installation and the workflow generated results on the drug targets and the event proteins the outcome will be displayed as a Cytoscape graph Cytoscape will launch automatically load the Cytoscape graph file Figure 13 Green nodes represent Drug or Metabolite pink nodes represent the Event and blue nodes represent Protein Node and Edge attributes are described in Tables 2 and 3 Figure 13 displays the Cytoscape graph using the Organic Layout found in the Cytoscape function Layout gt yFiles
10. seeks to establish a connection between the clinical event and the drug through different paths i through proteins in common between the drug target and the event protein profiles ii assessing if the proteins in the drug target profile and in the event protein profile participate ina common biological pathway Workflow author Anna Bauer Mehren Integrative Biomedical Informatics Laboratory GRIB IMIM Hospital del Mar UPF Barcelona Spain This workflow is distributed under the GNU GPL licence http www gnu org licenses gpl html Drag to re arrange or drag files URLs or text to add lt gt Load previous values lt gt Save values Run workflow 3 Cancel e cytoscape indicate the path of your Cytoscape installation Figure 8 Example home laura Cytoscape_v2 7 0 e Once you have specified all the input values click Run workflow e For this example we will use the default values provided by the workflow which represent the association of haloperidol NOSADO1 with a list of UMLS concept identifiers representing the clinical event prolongation of QT interval e You will be prompted to Results panel where you can monitor the progress of the workflow run Figure 9 12 ADR Substantiation workflow tutorial Figure 8 Diagram ac event Port description Insert here the path to your local Cytoscape installation Example value home user Cytoscape_v2 7 0 Workflow descrip
11. 12 Information about this document OLL Creative Commons License ADR substantiation workflow tutorial by Laura Furlong is licensed under a Creative Commons Attribution ShareAlike 3 0 Unported License 21
12. ADR substantiation workflow tutorial ADR yAstantiation Drug Event Protein _ Biological networks Metabolite SNP PRB s4 con f ADR Substantiation workflow tutorial Contents Mey CANIN EAD tse oes E ce ee ee nae atte alee ca ae eae ocr EEE E A IA ene 2 ZA WESCEIP UO OL MENOR NOW osere ne E A 3 EHS TSU SLATE AOI CONC CINE ieaS E T E tas saan ane 3 Implementation of the substantiation concept cccccccccceceeceeceeceecceeeeceeeeeeeeeeeseeseeseeeeeaeeaaeaaaaaaaaaaaaegas 4 Ds UC SUAS ats cece easier csv oneal NAE sec cs T ait ae E dees oa notte EE E E EEE 7 AIR CGA TING MUS eyer E O vansatonui vane sane ooncecgunsassenumeeateaeseo titan 7 a Mal ETNE enee a A TE E TOARN 8 DSC NOSIE anona a N a a a N 8 Je OwO ran THE Woko W aaa E E A E E TTA 8 de Lonne E B en eae eo Se SP ern ee OE 8 OCIS SV OKO Whe 8 erce tects netics ast a aalacctese st iaaecas a saeane cuter nace eon eee oose nc eee a 8 Ce RU LAG WOON oe i Gecate eecersenitent acceso Aeciecel E S A tebe 9 EWO KONTE SU ca hcg cate ae ear Seemed tere ota ayn tas ets ea cath se vee ead eee 14 CYO DEAETE N Mn en Or eee ee aR ee oe ee 14 PAG yy ie SUNS hase Aas tceak treads hee nae Soneeeeunt auc fanaa ciyhg Susea caer aaa ustaaasaeeucdie Aenea 17 ee Miya d Input Vales hapten tenscoaraceectonadsd E EE sieved scuestcnacats 17 CEA DR OV 01 1c are een eee ee me ee A NE te ee PET AS Seen eee ee eT ee 17 GRE SS Gof LS 018 0 EEIE Rene a ere R eee OR A E Re eee ee TT IAR
13. E ee ny a eee 18 Be YY OE NO Wy a BEE IE EET EINO ce ies EEE TE OS EEEIEE ENA PE E O E 18 EROT TT OE e E ee eee ee eer te me 18 WO SA El EEEIEI cinta buscar tase ers E IR EENE AEN EE E EIIE EN T ETS D EET TEN 19 LiF ULI Gl IM as E AA 21 12 Intormati On apon 1S COCUMICIN sesini E TA 21 1 Summary Drug safety issues pose serious health threats to the population and constitute a major cause of mortality worldwide Due to the prominent implications to both public health and the pharmaceutical industry it is of great importance to unravel the molecular mechanisms by which an adverse drug reaction can be potentially elicited These mechanisms can be investigated by placing the pharmaco epidemiologically detected adverse drug reaction in an information rich context and by exploiting all currently available biomedical knowledge to substantiate it We present a computational framework for 2 ADR Substantiation workflow tutorial the biological annotation of potential adverse drug reactions The proposed framework seeks to provide a biological explanation signal substantiation by exploring mechanistic connections that might explain why a drug produces a specific adverse reaction The mechanistic connections include the activity of the drug related compounds and drug metabolites on protein targets the association of protein targets to clinical events and the annotation of proteins both protein targets and proteins associated with clinical events t
14. Trust Once or Trust Always to continue Figure 2 Figure 2 e File Edit Insert View Workflows Advanced Help ox Pp avee Athn BY Design 4 Results Gj myExperiment 4 am Untrusted HTTPS connection Filter View service s certificate Import new services The service host bioinformatics ua pt requires HTTPS connection and has identified itself with the certificate below v Available services Do you want to trust this service Refusing to trust means you will not be able to invoke services on this host from a workflow gt Service templates gt Local services gt Biomoby http moby ucalga aoa gt amp Soaplab http www ebi ac u Common Name CN bioinformatics ua pt gt WSDL http soap bind ca w Organisation 0 Universidade de Aveiro x S WSDL http soap genome jp Organisation Unit OU IEETA Serial Number 3A 45 7F 12 F7 10 55 45 9D 6A A1 45 11 2F 62 7F Version 3 Workflow explorer Details Validatic Issued By v x Workflowl Common Name CN TERENA SSL CA D Workflow input ports Organisation 0 TERENA Workflow output ports Organisation Unit OU IEETA O Services Validity O Data links Issued On Mon Mar 29 02 00 00 CEST 2010 Control links Expires On Fri Mar 29 00 59 59 CET 2013 Merges Fingerprints SHA1 Fingerprint E4 09 20 F2 F7 4C EC A3 CE 7D 8E 72 DC D3 F3 62 F0 04 E6 0C MDS Fingerprint OF E8 29 53 CF D2 47 55 4E 83 07 8B 71 A9 B4 42 Trust always Do not trust k ADR
15. ge base of biologic pathways and processes Genome Biol 8 R39 6 Bauer Mehren A Furlong LI Sanz F 2009 Pathway databases and tools for their exploitation Benefits current limitations and challenges Mol Syst Biol 5 290 7 Uhlen M Oksvold P Fagerberg L Lundberg E Jonasson K et al 2010 Towards a knowledge based human protein atlas Nat Biotechnol 28 12 1248 1250 8 Trifiro G Pariente A Coloma PM Kors JA Polimeni G et al 2009 Data mining on electronic health record databases for signal detection in pharmacovigilance Which events to monitor Pharmacoepidemiol Drug Saf 18 12 1176 1184 9 Coloma PM Schuemie MJ Trifiro G Gini R Herings R et al 2011 Combining electronic healthcare databases in europe to allow for large scale drug safety monitoring The EU ADR project Pharmacoepidemiol Drug Saf 20 1 1 11 10 Avillach P Mougin F Joubert M Thiessard F Pariente A et al 2009 A semantic approach for the homogeneous identification of events in eight patient databases A contribution to the european eu ADR project Stud Health Technol Inform 150 190 194 18 ADR Substantiation workflow tutorial 10 Tables Table 1 Event code BE Event name Bullous Eruptions AS ARF AMI ALI CARDFIB UGIB RHABD PANCYTOP NEUTROP QTPROL Table 2 Node attributes in the Cytoscape graph Entity Drug Metabolite Event Protein ID SMILE Internal identifier for the node in the network The
16. inity value as reported in the original database The binding affinity value as reported in the original database or transferred during in silico profiling Not applicable evidenceLink Not applicable Not applicable PubMed identifier of the publication supporting the association empty if not available evidenceSource Database providing the association Database providing the association Database providing the association evidenceType OBSERVATIONAL for associations taken from databases SIMILARITY for associations from in silico profiling OBSERVATIONAL for associations taken from databases SIMILARITY for associations from in silico profiling OBSERVATIONAL for associations from curated databases TEXT MINING for text mining derived associations relationshipType BINDS for drug target binding BINDS for metabolite target binding Association type according to the gene disease association ontology available in 3 20 ADR Substantiation workflow tutorial 11 Funding This work was supported by the European Commission EU ADR ICT 215847 Innovative Medicines Initiative eTOX 115002 the AGAUR to A B M Instituto de Salud Carlos IIl FEDER CP10 00524 and COMBIOMED grants The Research Unit on Biomedical Informatics GRIB is a node of the Spanish National Institute of Bioinformatics INB The authors wish to thank the NLM for making UMLS and MesH available free of charge
17. insert here a single UMLS concept identifier or a list of identifiers Figure 6 If you use option 2 insert here the name of the EUADR_EVENT as defined in section 6 Figure 6 Diagram atc cytoscape event eventName eventType Port description The clinical event input ee T a For the clinical events the following input types are allowed i io 1 UMLS UMLS concept identifiers SE a 2 EUADR_EVENT clinical events observed as adverse drug reactions according to the EU ADR project see miia ae ao el sale ee inaia T http ibi imim es ADR_Substantiation html for details g ft Katsed de If you use option 1 insert here a single UMLS concept identifier or a list of identifiers 5 a p ore If you use option 2 insert here the name of the EUADR_EVENT as defined in http ibi imim es ADR_Substantiation html Example value a Workflow description 4 C0003811 The signal substantiation workflow seeks C0023976 to establish a connection between the C0035828 clinical event and the drug through C0040479 different paths C1563715 C1832916 i through proteins in C1833154 common between the drug target and the C1835325 v event protein profiles p eee i Delete ati New value Add file location s Add URL ii assessing if the proteins in the drug target profile and in the xa CO003811C C0035828 event protein profile participate ina C0040479 common biological pathway v C1563715 C1832916 Workflow autho
18. nerated The graph is composed of three types of nodes drug event and proteins and two types of edges drug protein protein event The attributes of the edges contain supporting information for each association such as source databases association type binding value for the drug etc As result of the pathway analysis the output port connectingPathways provides a list of all pathways connecting drug and event that can be visualized as HTML file Workflow run The different web services run in parallel The drug ATC code is first processed by the module getSmileFromATC which returns the SMILE code of the drug The SMILE code is then further processed by the module getUniprotListFromSmile which returns the relationships between the drug and its targets including targets of the metabolites of the drug The event is processed by the module getDiseaseAssociatedProteins which returns relationships between the event and associated proteins The lists of proteins associated with drug or event are extracted by means of Java scripts using XPath queries and are further processed to remove duplicates The module ConvertToCytoscapeGraph converts the output of the web services to a Cytoscape graph for user friendly visualization by means of XSL transformation For the signal substantiation through proteins the two protein profiles are combined to determine the proteins in common between the two profiles module Checkintersection For the signal substantiati
19. o biological pathways Hence the substantiation workflow ADR S workflow integrates modules for in silico drug target profiling and analyses based on gene disease networks and biological pathways The ADR S workflow offers a novel approach to explore the molecular mechanisms underlying adverse drug reactions This tutorial accompanies the article Bauer Mehren A van Mullingen EM Avillach P Carrascosa MC Singh B Garcia Serna R Lopes P Oliveira JL Diallo G Mestres J Ahlberg Helgee E Boyer S Sanz F Kors JA Furlong LI Automatic filtering and substantiation of drug safety signals submitted 2 Description of the workflow The substantiation concept The substantiation concept for drug safety signals here presented consists of placing the signal in the context of current knowledge of biological mechanisms that might explain it Essentially we are searching for evidence that supports causal inference of the signal i e feasible paths that connect the drug with the clinical event of the adverse reaction The signal substantiation process can be framed as a closed knowledge discovery process analogous to the Swanson model based on hidden literature relationships 1 We extend this framework by considering not only relationships found in the literature but also relationships discovered by mining other data sources or found by applying different bioinformatics methods vide infra For a drug event association we collect information about
20. ome 5 In general pathway databases such as Reactome contain a canonical general description of biological processes and pathways 6 These pathways can be found in different cell types and tissues or in different time points in the life of an organism however not all the pathway components might be active in all circumstances Combining information from pathways with protein expression in tissues and cell types can result in a cell and tissue type specific view of a given pathway Thus this method combines annotation of proteins to pathways with information of protein expression in cells and tissues Briefly we determine if the proteins associated to the drug and the event are expressed in the same tissue and cell type according to the The Human Protein Atlas version 7 1 7 Only the proteins that share expression at both levels tissue and cell type are kept for the next step Then for this list of proteins we retrieve all annotations to pathways using the Reactome web service Figure 1B The input of the method is composed of two lists of UniProt identifiers and the output is an XML document listing the pathways the annotated proteins and their expression profile Workflow input The substantiation workflow has five input ports called atc event eventType eventName and cytoscape The signal is represented by the ATC code of the drug at the 7 digits level e g MO1AHO2 for celecoxib and the event which is defined by the three input por
21. on through pathways the two protein profiles are subjected to the module getPathways which returns a list of pathways to which at least one drug and one event protein that are expressed in the same tissue are annotated to The output is further processed by module ConvertTOHTML which generates an HTML file listing the pathways that connect the drug and the event 3 License The ADR substantiation workflow is distributed under the GNU GENERAL PUBLIC LICENSE version 3 http www gnu org licenses gpl html 4 Requirements The workflow was developed and tested in Taverna workbench 2 2 To visualize the results as a graph you will need Cytoscape You can use Cytoscape versions 2 7 or 2 8 ADR Substantiation workflow tutorial a Install Taverna Download Taverna workbench 2 2 http www taverna org uk download workbench 2 2 Follow the instructions provided for installation and launch b Install Cytoscape Cytoscape version 2 7 or version 2 8 can be downloaded from http www cytoscape org To install follow the instructions according to your platform as explained in the Cytoscape web page For more information about Cytoscape functionalities check the Cytoscape user manual corresponding to the Cytoscape version you are using 5 How to run the workflow a Launch Taverna b Open the workflow Open the workflow file ADR_substantiation t2flow A pop up window showing the information on the https certificate will pop up click on
22. r C1833154 C1835325 Anna Bauer Mehren C1859062 Integrative Biomedical Informatics Laboratory C1859063 GRIB IMIM Hospital del Mar UPF C1860467 Barcelona Spain C1863518 C1863519 This workflow is distributed under the GNU C1867899 GPL licence C1867904 http www gnu org licenses gpl html C1970119 C2678483 C2678484 x Drag to re arrange or drag files URLs or text to add lt gt Load previous values lt gt Save values Run workflow 3 Cancel e eventType Type of the event to be processed For the clinical events the following types are allowed 1 UMLS if you use UMLS concept identifiers single identifier or a list of identifiers 2 EUADR_EVENT if you use clinical events as defined in the EU ADR project see section 6 1 ADR Substantiation workflow tutorial Irr s Attention the eventType is CASE SENSITIVE eeventName use this option to define a name for the clinical event This is required for user friendly visualization of the results Figure 7 Example long QT syndrome Figure 7 Diagram atc cytoscape event eventName eventType Port description padar maaga Define a name for the clinical event z This is required for user friendly Visualization of the results ee nadia manent Sanana Viagangan ipamana Example value Long QT syndrome Workflow description 3 Delete ati New elie E Add file location s Add URL The signal substantiation workflow
23. re 4 you can ignore them and press yes to proceed Then a pop up window with the input values required to run the workflow will appear Figure 5 ADR Substantiation workflow tutorial Figure 4 lt s0 File Edit Insert View Workflows Advanced Help CH x Pp aVae i C F RE B S Design amp Results Gj myExperiment Service panel Workflow diagram Filter 23a BHO BH A v Available services gt Service templates gt Local services gt i Biomart http www biomart org biomart martservice Biowoby http moby ucalgary ca moby MOBY Central pl gt Soaplab http www ebi ac uk soaplab services Workflow problems Yy i ADR_substantiation Y amp Workflow input ports A atc A cytoscape A event A eventName TERR Tea hea nee eRe gets ten in wenger enausway a A T A eventType Y amp Workflow output ports SO ETN A ETA NT r aN i Y CytoscapeResultGraph Y drugEventLinkingPathways Y drugEventLinkingProteins Y drugTargets Y drugTargetsOutput Y eventProteins Y eventProteinsOutput Y Services ATEAN ANa TNA TET v 8 ADR_substantiation_through_proteins 7 atc 7 cytoscape 7 event Figure 5 _Diagram atc _cytoscape event eventName eventType Port description The drug input The ATC code of a drug Sth level 7 digits Example value NOSADO1 Workflow description Delete t New value E Add file location s
24. re proteins in common between the drug target and the ADR Substantiation workflow tutorial event protein profile Figure 1A Many ADRs are caused by altered drug metabolism for which genetic variants in metabolizing enzymes are often responsible Consequently we also consider drug metabolism phenomena as an underlying mechanism of the observed ADR by assessing if the drug metabolites are targeting proteins that are known to be associated with the clinical event Second the association between the drug and the clinical event can involve proteins that are not directly associated with the drug and the clinical event but indirectly in the context of biological networks The final consequence of the drug action is the observed clinical event Thus the proteins in the drug target profile and event protein profile are mapped onto biological pathways to evaluate if the drug and the event can be connected through biological pathways Figure 1B Implementation of the substantiation concept The signal substantiation concept has been implemented by means of software modules that perform specific tasks of the processes To allow access and integration of the modules in high level analysis pipelines the modules were implemented as web services and combined into data processing workflows to achieve the aforementioned signal substantiation To standardize data exchanges between the different web services we have developed two complementary schemas using XSD to
25. the targets of the drug by querying publicly available databases and by applying drug target profiling methods 2 In parallel we retrieve information about the genes and proteins associated with the clinical event from a database covering knowledge about the genetic basis of diseases 3 Then we combine these two pieces of information under the following assumption if the disease phenotype elicited by the drug is similar to the phenotype observed in a genetic disease then the drug acts on the same molecular processes that are altered in the disease This can be regarded as phenocopy a term originally coined by Goldschmidt in 1935 4 to describe an individual whose phenotype under a particular environmental condition is identical to the one of another individual whose phenotype is determined by the genotype In other words in the phenocopy the environmental condition mimics the phenotype produced by a gene In the case of ADRs the environmental condition is represented by the exposure to the drug whose effect mimics the phenotype disease produced by a gene in an individual In this way we can capitalize on all the knowledge about the genetic basis of diseases to explore mechanisms underlying ADRs Currently we consider two scenarios able to provide a causal inference of the signal see Figure 1 First we look for connections between the drug and the event through their associated protein profiles Here a connection is established if there a
26. tion The signal substantiation workflow seeks to establish a connection between the clinical event and the drug through different paths i through proteins in common between the drug target and the event protein profiles ii assessing if the proteins in the drug target profile and in the event protein profile participate ina common biological pathway Workflow author Anna Bauer Mehren Integrative Biomedical Informatics Laboratory GRIB IMIM Hospital del Mar UPF Barcelona Spain This workflow is distributed under the GNU GPL licence http www gnu org licenses gpl html Added new value Edit value on right lt gt Load previous values lt gt Save values Figure 9 Taverna Workbench 2 2 0 File Edit Insert View Workflows Advanced Help jose avee B C YF RE Bs fy Results Gj my xperiment Graph Progress report lick on a run to see its values yA Q lick on a service in the diagram o see intermediate values if available ADR_substantiation 2011 07 29 17 12 36 yy p Running Workflow results drugEventLinkingPathways Y drugEventLinkingProteins V drugTargets V drugTargetsOutput V gt Run workflow Cancel Refresh intermediate values E Show workflow results R Save all values eventProteinsOutput Y apeRes tGrapn Vv BB Save value 13 ADR Substantiation workflow tutorial d Workflow results When the first part of the workflow execution finishes a
27. ts event eventName and eventType We allow two different types of event definitions events as defined in the EU ADR project Table 1 and events defined by a set of UMLS concept identifiers The input port eventType is then used to distinguish between the two definitions for events The eventName can be set by the user and is only required for user friendly visualization of the results The cytoscape input port defines the location of the local Cytoscape installation e g home user cytoscape v2 7 0 it is ADR Substantiation workflow tutorial optional and only required for the visualization of the signal substantiation results Workflow output The output of the signal substantiation workflow consists of 7 ports representing different layers of the results Besides the raw outputs from the individual web services druglargetOutput and diseaseProteinOutput the protein profile of the drug or its metabolites drugTargets and the protein profile of the event diseaseProteins are provided The signal substantiation workflow combines two ways of connecting drug and event through proteins or through biological pathways The outcome of these results is shown to the user during workflow execution by pop up windows The list of connecting proteins that is the protein annotated to both the drug and the event is provided connectingProteins For a user friendly visualization and analysis of the results a Cytoscape graph CytoscapeResultGraph is ge
28. ways Proteins in the Drug Target Profile and in the Event Protein Profile are searched in The Human Protein Atlas database to determine if they are expressed in the same tissue and cell type Proteins that share expression at both levels tissue and cell type are used to query Reactome database and pathways that contain at least one protein from the Drug Target Profile and one protein from the Event Protein Profile are retrieved Then these pathways are explored to determine if they support the causal inference of the signal http bioinformatics ua pt euadr common_types xsd http bioinformatics ua pt euadr euadr_types xsd ADR Substantiation workflow tutorial A Signal Substantiation through proteins Drug E gt Drug Target Profile In silico profiling Drug ar Intersection of Profiles gt MN Protein associated with the event E Protein associated with the drug HH Protein associated with the event and the drug drug event linking protein TL LL 5 B Signal Substantiation through pathways Drug Target Profile Drug Target Profile Event Protein Profile Event Protein Profile x m gt de THE HUMAN PROTEIN ATLAS oo sse oo a td pooenenenan oo Y Proteins expressed in same cell and tissue type ea aw a ek Se REACT ME ADR Substantiation workflow tutorial getSmileFromATC cglAlertService This method accepts as input
29. you can store the results as a Cytoscape XGMML file Go to the CytoscapeResultGraph and save the Value as XGMML file To inspect the results later follow these steps 1 2 Open Cytoscape Load the XGMML file in Cytoscape Go to Import gt Network Multiple Fyle Types and select the XGMML file Change the layout to Organic to explore the network Got to Layout gt yFiles gt Organic If required load the visual style located in this URL to have a nice visualization of the results http ibi imim es eu adr EUADR_cytoscape props 16 ADR Substantiation workflow tutorial Pathway results To visualize the results of the Pathway analysis go to the drugEventLinkingPathways tab and save the Value as an html file You can inspect the results in any web browser e Invalid Input values If you enter an invalid string for the drug you will get the following message EUADR signal substantiation WARNING A Invalid ATC Drug code invalid ATC format Ex HOLA Alternatively if you enter an invalid string for the event you will get the following error message EUADR signal substantiation WARNING A Invalid Event code invalid Event format Ex 12345 Attention the eventType parameter is CASE SENSITIVE 6 EU ADR events The EU ADR project focuses on a selection of adverse drug reactions that are monitored in electronic health records and further analyzed by the filtering and substantiation workflows
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