MODELING THE PHARMACOGENOMICS OF MODELING THE PHARMACOGENOMICS OF DEPRESSIONDEPRESSION

Michel Dumontier, Muhammad Faizan, Joseph Obeng, Natalia Villanueva-Rosales

Carleton University

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“If it were not for the great variability among individuals,

medicine might as well be a science and not an art”

Sir William Osler, 1892

Pharmacogenomics: The application of genomics to the study of human variability in drug

response

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PERSONALIZED MEDICINEPERSONALIZED MEDICINEThe ability to offer • The Right Drug• To The Right Patient• For The Right

Disease• At The Right Time• With The Right

Dosage

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PHARMGKB

+Role of genes, gene variants , drugs +pharmacokinetics +pharmacodynamics + clinical outcomes. + Links to publications

- Natural language descriptions- Variant details in publications

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SOPHARMSuggested Ontology for Pharmacogenomics

+ OWL ontology +/- Ontology reuse

-High complexity- 14 ontologies: ChEBI, PATO, Unit Ontology, Disease Ontology, Mammalian Phenotype Ontology, MEO, Sequence Ontology, SNP-Ontology, Amino-Acid Ontology, Family Bond Ontology, Pharmacogenetics Ontology, Relationship Ontology and CTO/OBI (Ontology of Clinical Investigation)- SOPHARM: 70 classes, 56 properties- OTHER: 84786 classes, 189 properties

- Very expensive to reason with

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Pharmacogenomics Ontology: simpler knowledge representation

Pharmacogenomics of Depression: explicit knowledge representation

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1. Define the scope of the ontology from use cases.

2. Derive essential concepts.

3. Construct concept taxonomy.

4. Map to an upper level ontology

5. Assign relations between concepts and attributes.

6. Add complex class descriptions.

METHODOLOGY

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1 SCOPE• researcher, doctor or patient • personalized medicine

What is the most effective drug treatment for an individual with a particular genetic profile that suffers from a particular disease?

Which gene variants affect therapeutic outcomes?

What is the clinical response for treating individuals with a particular drug and having a particular allele?

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2a SEVEN ESSENTIAL CONCEPTS (out of 20)

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2b N-ARY MODELING

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English name (rdfs:label) Clear and precise definition (rdfs:comment).

Concepts that subsumed each other were hierarchically organized and a child term is differentiable from its parent term. In line with general normalization techniques, all ontological terms are asserted to have but a single parent.

Refactored and Expanded SOPHARM’s measures- differences in values different from values

3 ONTOLOGY

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Basic Relation Ontology (BRO)• 50+ domain independent relations

• e.g. hasPart• Anticipated compatibility with RO• huge reuse opportunities

Specialized Relations• enormous number of possible domain dependent relations

• isVariantOf• set usage with domain / range restrictions.

5 RELATIONS

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Class InstancesGene 1396SNP 60IntronicSNP 607

NS-SNP 101

S-SNP 79Drug 269Disease 156Phenotype 75Publication 71ClinicalOutcomeMeasure 36GenotypeMeasure 35PharmacokineticMeasure 30PharmacodynamicMeasure 26Pathway 18OneDimensionalRegion 417Chromosome 14CrickStrand 14WatsonStrand 14Frequency 847DatabaseSource 1Total 4266

Ontology Population

Queried PharmGKB web services, mapped to ontology

Contained generic relationship to other named entities

Instance representation- Reuse individuals

- Drug(nortryptiline)- reduces KB size

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contains statements from 11/40 relevant publications involving 45 genes / gene variants, 57 drugs annotated with 19 classes of antidepressants, 45 drug treatments, 47 drug-gene interactions, 29 clinical outcomes, 10 drug-induced side-effects, and 8 gene-disease interactions.

PHARMACOGENOMICS OF DEPRESSION KNOWLEDGE BASE

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Nortriptyline treatments for postural hypotension having drug interactions with the ABCB1 gene

DrugTreatment that hasPart some (DrugInducedSideEffect that hasParticipant value PosturalHypotension) and hasParticipant

value PA450657 and hasParticipant value ABCB1_3435_C

QUERYING THE PGDKB

Recommended nortriptyline dose for postural hypotension for CYP2D6 heterozygous individuals

Dose that isParticipantIn some (DoseRecommendation that hasParticipant value CYP2D6_4 and hasParticipant value CYP2D6_6 and hasParticipant value PA450657)

Protégé 4, FaCT++, DL Query TabHCLS2008 @ WWW2008 16

Simplified pharmacogenomics / pharmacogenetics KR

Reasoning-capable knowledge base for pharmacogenomics of depression

Further extend for pharmacogenomics of other diseases

Work with PharmGKB & SOPHARM

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CONCLUSIONS

michel_dumontier@carleton.ca

http://dumontierlab.com

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Michel Dumontier