Translational Pharmacogenomics: Linking Genetics Research to Drug and Diagnostics Development

1. Discovery Seminar 186569/SS1 – Spring 2011Translational Pharmacogenomics: Linking Genetics Research to Drug and Diagnostics Development and New Treatment ApproachesOntology: Developing a Systematic Approach to Translational Pharmacogenomic Research Data CollectionFebruary 9, 2011 Werner CEUSTERS Center of Excellence in Bioinformatics and Life Sciences Ontology Research Group University at Buffalo, NY, USA

2. Pharmacogenomics • What is it ? • ‘The branch of pharmacology which deals with the influence of genetic variation on drug response in patients by correlating gene expression or single-nucleotide polymorphisms with a drug's efficacy or toxicity’. • ‘Pharmacogenomics is the whole genome application of pharmacogenetics, which examines the single gene interactions with drugs’. • http://en.wikipedia.org/wiki/Pharmacogenomics

3. Typical approach (1) • Building a huge matrix with patient cases in one dimension and patient characteristics in the other dimension

4. Use statistical correlation techniques to find associations between characteristics and (dis)similarities between cases Typical approach (2)

5. What is a characteristic ? What (sorts of) (pharmacogenomically relevant) characteristics go in here ? How can we make distinct pharmacogenomic studies comparable? Because such matrices tend to become huge, how can we make analysis feasible ? How can we make results re-usable? Fundamental questions

6. Q1: What is a characteristic ? • “What is … ?” –questions are problematic • How would you answer the following questions: • what is a human being ? • what is JFK ? • what is yellow ? • what is a unicorn ? • what is a drug ?

7. What do the following juxtapositions reveal? what is a human being? what is JFK? what is yellow? what is a unicorn? what is a drug? what does ‘human being’ mean? what does ‘JFK’ mean? what does ‘yellow’ mean? what does ‘unicorn’ mean? what does ‘drug’ mean?

8. Ontology Terminology What do the following juxtapositions reveal? what is a human being? what is JFK? what is yellow? what is a unicorn? what is a drug? what does ‘human being’ mean? what does ‘JFK’ mean? what does ‘yellow’ mean? what does ‘unicorn’ mean? what does ‘drug’ mean?

9. The terminology of ‘ontology’: Google  ‘define: ontology’: • the study of the broadest range of categories of existence, which also asks questions about the existence of particular kinds of objects; • an explicit representation of the meaning of terms in a vocabulary, and their relationships; • a common vocabulary for describing the concepts that exist in an area of knowledge and the relationships that exist between them; • specification of a conceptualisation of a knowledge domain; • a structured information model of a domain capable of supporting reasoning by human users and software agents; • a data model that represents a set of concepts within a domain and the relationships between those concepts; • …

10. One term, many definitions This raises some questions: • Is it possible for a term to have so many meanings? • Can the authors of these definitions all be right at the same time? • Is it possible for something to which one of these definitions applies to be such that also one or more of the other definitions apply ?

11. Merriam-Webster on ‘bank’ Entry term 27 occurrence types 3 different word types Noun Verb Part of compound term Q1.1: Is it possible for a term to have so many meanings? } http://www.merriam-webster.com/dictionary

12. Q1.1: Is it possible for a term to have so many meanings? • Merriam-Webster on ‘bank’ http://www.merriam-webster.com/dictionary

13. Q1.1: Is it possible for a term to have so many meanings? • Merriam-Webster on ‘bank’ http://www.merriam-webster.com/dictionary

14. Q1.1: Is it possible for a term to have so many meanings? • Clearly: yes ! • This phenomenon is called: Homonymy

15. Term-2 Term-3 Term Meaning Meaning-1 Meaning-2 Meaning-3 Term-1 Meaning-4 Meaning-5 Meaning-6 Meaning-7 This is called: synonymy

16. Homonymous use of the term ‘ontology’ • the studyof the broadest range of categories of existence, which also asks questions about the existence of particular kinds of objects; • an explicit representation of the meaning of terms in a vocabulary, and their relationships; • a common vocabularyfor describing the concepts that exist in an area of knowledge and the relationships that exist between them; • specificationof a conceptualisation of a knowledge domain; • a structured information model of a domain capable of supporting reasoning by human users and software agents; • a data model that represents a set of concepts within a domain and the relationships between those concepts; • …

17. Q1.2: Can the authors of these definitions all be right at the same time? • Yes, if we are dealing with a case of homonymy.

18. Q1.3: Is it possible for something to which one of these definitions applies to be such that also one or more of the other definitions apply ? ? information model is an data model representation is a is a ‘that’ thing is a vocabulary is a is a specification study (hint on next slide)

19. Remember the “what is yellow?”-question • Answers could have been: • a color • a banana • Thus: • can something which is a color be a banana ? • can something which is a banana be a color ?

20. Q1.3: Is it possible for something to which one of these definitions applies to be such that also one or more of the other definitions apply ? Not for all ! Only for some

21. Homonymous use of the term ‘ontology’:at least one clear cut distinction • the studyof the broadest range of categories of existence, which also asks questions about the existence of particular kinds of objects; • an explicit representation of the meaning of terms in a vocabulary, and their relationships; • a common vocabularyfor describing the concepts that exist in an area of knowledge and the relationships that exist between them; • specificationof a conceptualisation of a knowledge domain; • a structured information model of a domain capable of supporting reasoning by human users and software agents; • a data model that represents a set of concepts within a domain and the relationships between those concepts; • …

22. ‘Ontology’ as the study of what exists • Key questions: • What exists ? • How do things that exist relate to each other ? • Some hypotheses: • An external reality, time, space • Ideas, concepts • Particulars, universals, objects, processes • God • Ontologists from distinct ‘schools’ differ in opinion about the existence of some of the above: • Realism, nominalism, conceptualism, monism, …

23. Anontology as a representation • Terms WordNet, MedDRA, RxNORM • Concepts  the majority of ‘ontologies’ But … overwhelming lack of clarity about what ‘concepts’ are: • meaning shared in common by synonymous terms ? • idea shared in common in the minds of those who use these terms ? • unit of knowledge describing meanings ? • feature or property or characteristic shared in common by entities in the world ? • Universals  Realism-based ontology Key question: of what ?

24. The Ontology-Terminology divide • Ontology (in the ‘study’ sense) is about what things are. • Terminology is about how to name things, without caring about whether what is named exists. • Sadly, this distinction is by many people who call themselves ‘ontologists’ or build ‘ontologies’ either not understood at all, or applied in the wrong way.

25. Terminological versus Ontological approach • The terminologist defines: • ‘a clinical drug is a pharmaceutical product given to (or taken by) a patient with a therapeutic or diagnostic intent’. (RxNorm) • The (good, real) ontologist thinks: • Does ‘given’ includes ‘prescribed’? • Is manufactured with the intent to … not sufficient? • Are newly marketed products – available in the pharmacy, but not yet prescribed – not clinical drugs? • Are products stolen from a pharmacy not clinical drugs? • What about such products taken by persons that are not patients? • e.g. children mistaking tablets for candies.

26. A multi-disciplinary approach to ontology • In philosophy: • Ontology(no plural) is the study of what entities exist and how they relate to each other; • In mainstream computer science and biomedical informatics: • An ontology(plural: ontologies) is a shared and agreed upon conceptualization of a domain; • Our ‘realist’ view within the Ontology Research Group combines the two: • We use Ontological Realism, a specific theory of ontology, as the basis for building high quality ontologies, using reality as benchmark. Smith B, Ceusters W. Ontological Realism as a Methodology for Coordinated Evolution of Scientific Ontologies. Applied Ontology, 2010;5(3-4):139-188.

27. Realism-based Ontology Ontological Realism: assumes 3 levels of reality • There is an external reality which is ‘objectively’ the way it is; • That reality is accessible to us; • We build in our brains cognitive representations of reality; • We communicate with others about what is there, and what we believe there is there. Smith B, Ceusters W. Ontological Realism as a Methodology for Coordinated Evolution of Scientific Ontologies. Applied Ontology, 2010.

29. Three levels of reality in Ontological Realism Representations L3. Linguistic representations about (1), (2) or (3) L2. Clinicians’ beliefs about (1) L1. Entities (particular or generic) with objective existence which are not about anything First Order Reality

30. ‘person’ ‘drug’ ‘penicillin’ ‘W. Ceusters’ ‘my pneumonia’ CONTRA-INDICATION my doctor’s work plan my doctor’s diagnosis INDICATION my pharmacist’s computer my doctor PATHOLOGICAL STRUCTURE PERSON me my bronchitis DISEASE DRUG my toxic reaction to penicillin PORTION OF PENICILLIN MOLECULE The three levels applied to medication management Generic Specific 3. Representation 2. Beliefs (knowledge) 1. First-order reality

31. A realism-basedontology • is a representation of some pre-existing domain of realitywhich • (1) reflects the properties of the objects within its domain in such a waythat there obtains a systematic correlation between realityand the representation itself, • (2) is intelligible to a domain expert • (3) is formalized in a way that allows it to support automatic information processing

32. Can we now answer Q1 ? • Q1: what is a characteristic ? • it is for sure not a category entities can belong to: there is no generic entity for which the name ‘characteristic’ would be appropriate on an exclusive basis; • there is also no particular entity that you could point to and state ‘that over there is the only existing characteristic’ • thus: there are no characteristics, there is just the term ‘characteristic’ which is used to describe that some entities are (acknowledged to be) in some way of interest in some context and for some purpose.

33. This requires rephrasing Q2 What (sorts of) (pharmacogenomically relevant) characteristics go in here? What entities described as being characteristic for pharmacogenomic purposes should be represented here?

34. The basis of our ontologies: Basic Formal Ontology • The world consists of • entities that are • Either particulars or universals; • Either occurrents or continuants; • Either dependent or independent; and, • relationships between these entities of the form • <particular , universal> e.g. is-instance-of, • <particular , particular> e.g. is-member-of • <universal , universal> e.g. isa (is-subtype-of) Smith B, Kusnierczyk W, Schober D, Ceusters W. Towards a Reference Terminology for Ontology Research and Development in the Biomedical Domain. Proceedings of KR-MED 2006, November 8, 2006, Baltimore MD, USA

35. Basic BFO distinctions universals Continuant Occurrent process, event Independent Continuant thing Dependent Continuant quality .... ..... ....... particulars

36. Basic BFO distinctions universals has_participant Continuant Occurrent process, event isa isa Independent Continuant thing Dependent Continuant quality inheres_in instance_of (at t) .... ..... ....... particulars

37. The importance of temporal reference • A-temporal and temporal questions: • Can something which is green be yellow? • Can something which is now green be now yellow? • Can something which is now green be yellow tomorrow? • For the clever ones: • what relationship is expressed here by ‘is’ and ‘be’?  inheres

38. Universals Particulars Continuant Independent Continuant • portion of C19H17ClN2O4 • human being • gene • portion of Glifanan in the tablet in front of me • me • the HTR2A gene on chromosome 13 of the most frontal cell in the tip of my nose Dependent Continuant • shape • temperature • length • the shape of my nose • the temperature of the Glifanan tablet in front of me • the length of that HTR21 gene Occurrent • change in shape • motion • rise in temperature • unfolding of a DNA molecule • the circulation of a Glifanan molecule in my bloodstream • the rise of my body temperature while teaching this seminar Examples

39. Two distinct (?) sorts of relevant entities phenotypic genotypic

40. Gene Ontology Human Phenotype ‘Ontology’ genes gene products features Genotype / Phenotype

41. The Gene Ontology components • Molecular Function = elemental activity/task • the tasks performed by individual gene products; examples are carbohydrate binding and ATPase activity • Biological Process = biological goal or objective • broad biological goals, such as mitosis or purine metabolism, that are accomplished by ordered assemblies of molecular functions • Cellular Component = location or complex • subcellular structures, locations, and macromolecular complexes; examples include nucleus, telomere, and RNA polymerase II holoenzyme

42. Application of good ontological principles

43. Human Phenotype ‘Ontology’ http://www.human-phenotype-ontology.org/index.php/hpo_home.html

44. Q3: How can we make distinct pharmacogenomic studies comparable? • Map any characteristic used to relevant, standard and high quality ontologies

45. The positive effects of appropriate mappings

46. The positive effects of appropriate mappings • identification of ontological relations prior to statistical correlation: • ch1 and ch4 • ch1 and ch5 • ch1 and ch2 • … • Contributes to answering ‘Q4: how can we make analysis feasible’ • this method allows for data-reduction without information loss.

47. Filling the grid • We know now that here go labels from appropriate ontologies • But, what goes here?

48. Remember we had this … Universals Particulars Continuant Independent Continuant • portion of C19H17ClN2O4 • human being • gene • portion of Glifanan in the tablet in front of me • me • the HTR2A gene on chromosome 13 of the most frontal cell in the tip of my nose Dependent Continuant • shape • temperature • length • the shape of my nose • the temperature of the Glifanan tablet in front of me • the length of that HTR21 gene Occurrent • change in shape • motion • rise in temperature • unfolding of a DNA molecule • the circulation of a Glifanan molecule in my bloodstream • the rise of my body temperature while teaching this seminar

49. Or after transposition … Universals Continuant Occurrent Independent Continuant Dependent Continuant portion of C19H17ClN2O4 human being gene shape temperature length change in shape motion rise in temperature Particulars • portion of Glifanan in the tablet in front of me • me • the HTR2A gene on chromosome 13 of the most frontal cell in the tip of my nose • the shape of my nose • the temperature of the Glifanan tablet in front of me • the length of that HTR21 gene • unfolding of a DNA molecule • the circulation of a Glifanan molecule in my bloodstream • the rise of my body temperature while teaching this seminar

50. case1 . . . . . case2 . . . case3 . . . case4 . . . . . . Particulars case5 . . . . . . . . case6 . . . case7 . . . case8 . . … . … and for many patients