A framework for the study of diseases and adverse drug reactions

Transcription

1 A framework for the study of diseases and adverse drug reactions Laura I. Furlong IBI group Research Programme on Biomedical Informatics (GRIB) Hospital del Mar Research Institute (IMIM)

2 Information on the genetic basis of human diseases is abundant but scattered among different sources 2

3 Information on the genetic basis of human diseases is abundant but scattered among different sources Research on drug adverse reactions indicate a genetic contribution to drug toxicity. but in this case the information is more difficult to find 3

4 Neuregulin 1 gene (NRG1) Susceptibility to Schizophrenia (OMIM database) Amphetamine-related disorders, Heart failure, Stomach Ulcer, Schizophrenia (Comparative Toxicogenomics Database ) Schizophrenia, Osteoporosis, Hirschsprung disease, Cardiovascular diseases (Genetic Association Database) 4

5 Knowledge pockets in genetics of diseases Anna Bauer-Mehren, Markus Bundschus, Michael Rautschka, Miguel A. Mayer, Ferran Sanz, Laura I. Furlong. Gene-disease network analysis reveals functional modules in mendelian, complex and environmental diseases. PLoS ONE (6): e

6 A comprehensive resource on gene-disease associations Mendelian, complex and environmental disorders Integrates information from publicly available databases and the literature (text mining) Information from human and animal models (mouse) 6

7 Source databases Organism Human Mouse Human UniProt MGD MEDLINE CTD CTD GAD Human orthologs of mouse genes 7

8 Source databases UniProt MGD MEDLINE CTD CTD GAD Human orthologs of mouse genes Curated Predicted Text Mining 8

9 Current release (v2.0) 9

10 Disease terminology mapping Source databases Noonan Syndrome (MeSH, D009634) Turner phenotype with normal karyotype (MIM, ) UMLS Metathesaurus CUI SAB STR C DXP NOONAN SYNDROME C DXP PSEUDO-TURNER SYNDROME C MSH Noonan Syndrome C MTH Noonan Syndrome C NCI Noonan Syndrome C OMIM TURNER PHENOTYPE WITH NORMAL KARYOTYPE C OMIM NS1 C OMIM NOONAN SYNDROME 1 C SNOMEDCT Noonan-Ehmke syndrome C SNOMEDCT Turner-like syndrome C SNOMEDCT Turner's phenotype, karyotype normal DisGeNET Noonan Syndrome (UMLS, C ) is a Musculoskeletal disease, etc 12

11 Gene-disease association ontology 13

12 Availability Web interface Cytoscape plugin Database (sqlite format) RDF (in progress) 14

13 Availability Web interface: Based on Onexus ( Easy-to-use interface to query the database Different types of queries supported Download data as tsv files or using scripts in several languages (Perl, Python, R, bash) 15

14 16

15 Cytoscape plugin Build gene-disease association networks and projections Search by database source, association type and disease class Inspect various node and edge attributes Integrate other data sources (e.g. gene lists from microarray experiments) Use functionalities for network analysis available from the Cytoscape community Bauer-Mehren, A., Rautschka, M., Sanz, F. & Furlong, L.I. DisGeNET: a Cytoscape plugin to visualize, integrate, search and analyze gene disease networks. Bioinformatics 26, (2010). 17

16 Cytoscape plugin Bauer-Mehren, A., Rautschka, M., Sanz, F. & Furlong, L.I. DisGeNET: a Cytoscape plugin to visualize, integrate, search and analyze gene disease networks. Bioinformatics 26, (2010). 18

17 Applications Study of adverse drug reactions Identification of shared mechanisms for comorbid disorders 20

18 Applications Study of adverse drug reactions Identification of shared mechanisms for comorbid disorders 21

19 Adverse Drug Reactions Drug safety issues pose serious health threats to the population and constitute a major cause of mortality worldwide. Thus, 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 drug safety signal in an information-rich context and by exploiting all currently available biomedical knowledge to substantiate it. 22

20 EHR EHR EHR Drug Safety Signals Mechanistic hypothesis for drug adverse reactions 23

21 CE 25

22 CE 26

23 CE In silico profiling 27

24 CE 28

25 Implementation Bioinformatic modules accessed through web services Workflow implemented in Taverna Results available as drug-target-event network visualized in Cytoscape Availability MyExperiment: Bauer-Mehren A, van Mullingen EM, Avillach P, Carrascosa MC, Garcia-Serna R, Piñero J, Singh B, 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, PLoS Comput Biol Apr;8(4):e

26 M. Cases et al. Networking drug toxicity events, in preparation 30

27 Applications Study of adverse drug reactions Identification of shared mechanisms for comorbid disorders 31

28 Comorbidities D1 Genome D2 D3 D4 32

29 Comorbidities D1 Genome D2 D1 D2 D3 D4 33

30 Comorbidities D1 Genome D2 D1 D2 D3 D3 D4 D4 34

31 Comorbidities D1 Genome D2 D1 D2 D3 D3 D4 D4 Interactome 35

32 Comorbidities D1 Genome Diseasome D2 D1 D2 D3 D3 D4 D4 Interactome 36

33 Chronic Obstructive Pulmonary Disease (COPD) and comorbid conditions Collaboration with CIBERES 37

34 Team Curators Solène Grosdidier Janet Piñero Developers Coordination Montse Cases Àlex Bravo Núria Queralt Laura I. Furlong Contact: 38

35 Thank you 39