Introduction Integration and querying Discovering disease pathways Outlook and conclusions

Integration of knowledge for personalizedmedicine: a pharmacogenomics case-study

Robert Hoehndorf, Michel Dumontier and George Gkoutos

University of CambridgeCarleton University

Aberystwyth University

18 September 2012

2007 2008 2009 2010 2011 2012

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Introduction Integration and querying Discovering disease pathways Outlook and conclusions

Translational research

National Cancer Institute:

Translational research transforms scientific discoveries arising fromlaboratory, clinical, or population studies into clinical applicationsto reduce [disease] incidence, morbidity, and mortality.

Pharmacogenomics databases

Introduction Integration and querying Discovering disease pathways Outlook and conclusions

Ontology

Gruber (1993):

An ontology is the explicit specification of a conceptualization of adomain.

controlled vocabulary

provide background knowledge

hierarchically organized

Introduction Integration and querying Discovering disease pathways Outlook and conclusions

OntologyOntologies in pharmacogenomics

drugs and chemicals:

ATCChEBIMeSHUMLS

diseases:

HumanDOHuman Phenotype OntologyICDMeSHSNOMED CTUMLS

Introduction Integration and querying Discovering disease pathways Outlook and conclusions

OntologyOntologies alone do not resolve heterogeneity.

Euzenat (2007):

“[M]erely using ontologies [...] does not reduce heterogeneity: itjust raises heterogeneity problems to a higher level.”

Introduction Integration and querying Discovering disease pathways Outlook and conclusions

OntologyData-driven approach to integration

data- and question-driven integration of ontologies

integration of data and databases through integratedontologies

reduction of complexitybackground knowledgehierarchical abstraction

ontology-based data analysis

semantic similaritystatistical testsgraph-/network-based algorithms

data- and question-driven evaluation

Introduction Integration and querying Discovering disease pathways Outlook and conclusions

Aims: queries and integrated analysis

integrate and query knowledge in pharmacogenomics

identify aberrant pathways and patho-physiology underlyingdisease

identify drug pathways (pharmacokinetics andpharmacodynamics)

personalized treatment and dosage guidelines based on geneexpression profile

Introduction Integration and querying Discovering disease pathways Outlook and conclusions

Required: integration of multiple data sources

drugs and drug targets

pathways, genetic interactions, protein interactions, generegulation

drug–disease associations

gene–disease associations

genotypes–drug response

Introduction Integration and querying Discovering disease pathways Outlook and conclusions

Approach to data integration in pharmacogenomics

integration of databases containing drug, gene, genotype,disease and pathway information

DrugBank: drugs and drugs targetsPharmGKB: genotype and drug responsePathway Interaction Database: biological pathwaysCTD: toxicogenomics information (chemical–gene–disease)

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Queries

What drugs can be used to treat parasitic infectious diseases(DOID:1398)?

Chloroquine

Arthemeter

...

Introduction Integration and querying Discovering disease pathways Outlook and conclusions

Queries

What drugs are effective for diseases affecting the joints(FMA:7490)?

Folic acid (for arthritis)

Chloroquine (for Chikungunya virus)

...

Introduction Integration and querying Discovering disease pathways Outlook and conclusions

Queries

What genotypes are related to diseases affecting the joints(FMA:7490)?

RSID:rs70991108 (with arthritis)

RSID:rs1207421 (Osteoarthritis, Knee)

...

Introduction Integration and querying Discovering disease pathways Outlook and conclusions

Queries

What genotypes are related to response to steroids(CHEBI:35341)?

RSID:rs45566039 (with estrogen)

RSID:rs1042713 (with budesonide)

...

Introduction Integration and querying Discovering disease pathways Outlook and conclusions

Disease and drug pathwaysOntology enrichment analysis can identify over-represented ontology classes.

ontology-based, statistical approach to identify drug anddisease pathways

use graph structure of ontology to identify statistically over-and under-represented ontology classes

aims:

identify over-represented disease classes (in disease ontology)for genes in a pathway (disease pathways)identify over-represented chemical classes (from chemicalontology) for genes in a pathway (drug pathways)

Introduction Integration and querying Discovering disease pathways Outlook and conclusions

Disease and drug pathwaysOntoFUNC enables enrichment analyses over OWL ontologies.

OntoFUNC: http://ontofunc.googlecode.com

based on FUNC (http://func.eva.mpg.de)

supports

hypergeometric testWilcoxon rank testbinomial testMcDonaldKreitman (2x2 contingency) testcorrection for multiple testing (FWER, FDR)

Introduction Integration and querying Discovering disease pathways Outlook and conclusions

Disease and drug pathwaysOntoFUNC identifies disease classes that are enriched in pathways.

hypergeometric test over Disease Ontology

genes participating in pathway P vs. all other genes

carcinosarcoma (DOID:4236) and Zidovudine Pathway(PharmGKB:PA165859361) (p < 10−10).

mood disorder (DOID:3324) and Zidovudine Pathway(PharmGKB:PA165859361) (p < 0.01).

(All results at http://pharmgkb-owl.googlecode.com)

Introduction Integration and querying Discovering disease pathways Outlook and conclusions

Gene expression and drug responseOngoing research

Based on a (differential) gene expression profile, can we findcandidate drugs that act (only) on the aberrant pathways?

aberrant pathways from (differential) gene expression

Wilcoxon signed rank test

(types of) drugs acting on these pathways

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Limitations and future work

only works for known pathways

extension to interaction networks

(experimental) validation

include directionality of interactions

drug–gene/proteingene regulationprotein–protein

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Conclusions

knowledge in pharmacogenomics is distributed across multipledatabases

ontologies can enable data integration and integrated dataanalysis

integration of knowledge is necessary to enable personalizedmedicine

http://pharmgkb-owl.googlecode.com

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Acknowledgements

Michel Dumontier

George Gkoutos

Introduction Integration and querying Discovering disease pathways Outlook and conclusions

Thank you!