This document provides an overview of pharmacogenetics and pharmacogenomics. It defines the terms, discusses early examples showing the role of genetics in drug response, and models of inheritance. It also covers goals of the field, examples demonstrating clinical relevance like TPMT and CYP2D6, challenges with polygenic traits, and barriers to clinical implementation. While the field aims to optimize drug efficacy and safety based on genetics, it is noted that the impact of genetics is often complex and not yet clear enough for wide clinical use in many cases.

1. Pharmacogenetics and
Pharmacogenomics
Kevin Zbuk, MD
Medical Oncologist
Juravinski Cancer Centre
McMaster University

2. Outline
• Introduction and definitions
• Basic concepts
• Case studies
• Conclusions

3. Pharmacogenetic versus
Pharmacogenomic
• No universally accepted definitions of either
• Often used interchangeably
• Pharmacogenetics used for more than 40 years to denote the science
about how heritability affects the response to drugs.
• Pharmacogenomics is new science about how the systematic identification
of all the human genes, their products, interindividual variation,
intraindividual variation in expression and function over time affects drug
response/metabolism etc.
• The term pharmacogenomics was coined in connection with the human
genome project
• Most use pharmacogenetics to depict the study of single genes and their
effects on interindividual differences in (mainly) drug metabolising
enzymes, and pharmacogenomics to depict the study of not just single
genes but the functions and interactions of all genes in the genome in the
overall variability of drugs response

6. Pharmacogenetics
• “Pharmacogenetics is the study of how
genetic variations affect the disposition
of drugs, including their metabolism and
transport and their safety and efficacy”
•J. Hoskins et. al NRC 2009

7. Pharmacogenetics involves both PK
and PD
• Pharmacokinetic
“The process by which a drug is absorbed,
distributed, metabolized, and eliminated by the
body”
• Pharmacodynamic
“the biochemical and physiological effects of drugs
and the mechanisms of their actions”

8. Goals of Pharmacogen(etics)omics
• Maximize drug efficacy
• Minimize drug toxicity
• Predict patients who will respond to
intervention
• Aid in new drug development

9. The Hope of Pharmacogenomics
• Individuals genetic makeup with allow
selective use of medications such that
– Efficacy maximized
– Side effect minimized

10. This is the hope/hype

11. In the Beginning
• Mendelian genetics “single gene – single
disease”
– single wild type allele and single disease allele
– Patterns of inheritance included autosomal
dominant (need only one disease allele) and
autosomal recessive (need two disease alleles)
• Followed soon thereafter by additive (co-
dominant) model
– Both alleles contribute to phenotype

12. Dominant/Recessive

13. Co-dominance

14. Empiric observations suggesting
Pharmacogenetics important
• Clinical response to many drugs varies widely
amongst individuals
• Same drug-> same dose -> same indication in
different individuals
– Some respond
– Some don’t
– Some don’t respond and have serious toxicity

15. EARLY PK EXAMPLES

16. The beginning of pharmacogenetics
• 1950s
– “Inheritance might explain variation in individuals
response and adverse effects from drugs”
Motulsty
– “Pharmacogenetics defined as “study of role of
Genetics in drug response” Vogel
– Most of studies for next several decades of “high
penetrance monogenic” gene-drug interactions
– Def: Monogenetic disease. Mutation at single
locus sufficient to result in disorder

17. Penetrance
• Penetrance of a disease-causing mutation is
the proportion of individuals with the
mutation who exhibit clinical symptoms.
– Eg. if a mutation in the gene responsible for a
particular autosomal dominantdisorder has 95%
penetrance, then 95% of those with the mutation
will develop the disease, while 5% will not.

18. Victor McKusick
• Established Online Mendelian Inheritance in
Man in early 80s
• Categorized majority of Mendelian Disorders
• Became very clear that there are many
different disease alleles for many disorders
(allelic heterogeneity)
• Recently many disorders have associated
modifier genes that modify disease phenotype
– Eg. Age-of-onset and severity

20. Example 1- Success of
Pharmacogenetics in Oncology
TPMT

21. TPMT
• Main metabolizer of chemotherapeutic agents
6MP and azothiopurine (used mainly in blood
based malignancies)
• TPMT deficiency leads to severe toxicity
associated with treatment (potential
mortality)

22. TPMT enzyme activity distribution

23. Hematologic toxicity according to TPMT genotype

24. Evans Nature Reviews Cancer 2006

25. FDA approved pharmacogenetic tests
Gene Drug Consequence
TPMT 6MP Toxicity
CYP2D6 Tamoxifen Decreased efficacy
UGT1A1 Irinotecan Toxicity
CYP2D6 Codeine Ineffective analgesia
These genes all modulate Pharmokinetics

26. Contribution of High Penetrance Monogenic Model to
PG
• Contribution likely not as large as initially
anticipated
• For most pharmacologic traits might be 15-20%
at most
– Could consider this penetrance
• Redundancy likely a major contributing factor
• MANY ENZYMES INVOLVED IN DRUG METABOLISM WITH
MANY ALTERNATE PATHWAYS
• Dichotomous disease versus quantitative trait
• Much more likely polygenic model with gene-
environment interactions

27. Some of it ain’t genetic
• Age
• Co-morbidities
• Renal and hepatic function (dysfunction)
• Concomitant medications
• Diet and smoking

28. Common Disease Common Variant
Hypothesis
• Most complex
diseases are
strongly
influenced by
combination of
frequent alleles
that each only
exert modest
effect

30. Approach to polygenic pharmacogenomic traits

31. Polygenic Model and PG
• Elucidation unlikely possible before advances
in genomics
• Technologic advances
– High throughput sequencing of DNA
– Affordable genotyping of 100ks to 1-2M SNPs
• Genomic knowledge advances:
– Especially Human Genome Project and HapMap
Projects

39. Cost of Genotyping
• In 2005 (5 years ago!)
– $1600 to genotype 250K SNPs in one individual
• 2009
– $250 to genotype >1Million SNPs
• 2014
-$200-250 to genotype >5 millions SNPs

43. Hapmap project
• There are an estimated 10 million SNPs with
MAF >1%
• Hapmap project genotyped Chinese,
Japanese, African and European individuals
(families)

44. HapMap Project
Phase 1 Phase 2 Phase 3
Samples & POP
panels
269 samples
(4 panels)
270 samples
(4 panels)
1,115 samples
(11 panels)
Genotyping
centers
HapMap
International
Consortium
Perlegen Broad & Sanger
Unique QC+
SNPs
1.1 M 3.8 M
(phase I+II)
1.6 M (Affy 6.0 &
Illumina 1M)
Reference Nature (2005)
437:p1299
Nature (2007)
449:p851
Draft Rel. 3
(2010)

46. A more in depth look at PK in
clinical practice
Tamoxifen use and CYP2D6

47. Tamoxifen metabolism
• Needs to be converted to endoxifen to be
active
– catalysed by the polymorphic enzyme
cytochrome P450 2D6 (CYP2D6)
– 6-10% European population deficient in this
enzyme
• Efficacy of tamoxifen likely low in this population
• Suggests consider alterative treatments

48. J. Hoskins et. al NRC 2009

49. About the CYPs
• Membrane bound enzymatic proteins
– Involved in oxidation, peroxidation and reductive
metabolism
– Responsible for >90% of drug transformation
• Greater than 50 different CYP genes encoding 50
different proteins
• CYP2D6 present mainly in liver and a major player
in drug metabolism from antidepressants to
antihypertensive to chemotherapy

50. Evolution of CYP nomenclature
• Initially astute clinical observation of unusual
drug response
• Such responses then found to be heritable
• Early example of phenotype to genotype
approach
• CYP2D6 polymorphism the first described
• Increasing recognition of poor metabolizer
phenotype occurred at time that genotyping
technology in evolution

51. About CYP2D6
Location 22q 13.1
P arm
Q arm

52. CYP2D6 alleles
• There are >70 described in this gene
– Bottom line: variants either cause no change,
decrease somewhat, or significantly decrease
metabolism
• Extensive metabolizers ( EM), intermediate (IM)
metabolizers, and poor metabolizers (PM)
• EM is the standard metabolism allele against which
others are compared (consider it the wild type)

53. Hoskins et al. Nature Reviews Cancer 2009

54. CYP2D6 alleles
Copy Number Variation
• Throughout the genome there are areas of
DNA that are represented in variable copies in
individuals (CNV)
• CYP2D6 is one such area
• Up to 16 copies seen in some individuals
– “NORMAL VARIANT”
• ULTRARAPID METABOLIZERS

55. Consequence of CYP2D6 alleles?
• EM/EM or EM/IM(PM) normal metabolizers
• IM/IM or IM/PM intermediate metabolizers
• PM/PM poor metabolizers
• Poor/(Intermediate) metabolizers have much
lower levels of endoxifen than intermediate/
rapid metabolizers

56. CYP2D6 Genotype and clinical
outcomes
• Several (small trials) have suggested
decreased efficacy of Tamoxifen in poor
(intermediate) metabolizers both in adjuvant
therapy and in treatment of metastatic
disease (see Hoskins NRC 2009 for details)
– All retrospective
– Largest was only statistically significant association
in univariate analysis
– In additions several trials have not confirmed
these results

57. Reasons for discordant results in
CYP2D6 trials
• Did not genotype many of the rarer poor
metabolizer alleles
• Did not account for concurrent use of other drugs
metabolized by CYP2D6 in many cases
• Different dose of Tamoxifen in several trials
• Did not assay endoxifen levels
• Power (poor metabolizers rare)
• Unknown variants in other genes whose products
involved in tamoxifen metabolism

58. So what is needed to clarify the issue of
relevance of CYP2D6 genotype and clinical
relevance?
• Large randomized trial that compares
standard dosing of tamoxifen to genotype
adjusted dosing
• Until that point clinical utility of testing
(commerically available) unclear
– Should recommend avoiding SSRIs that inhibit
CYP2D6 significantly (see later)

59. Provocative thoughts
• In post-menopausal breast cancer tamoxifen is
falling out of favor due to the efficacy of
Aromatase Inhibitors (inhibit extragonadal
production of estrogen)
– AI shows increased efficacy c/w tamoxifen
• BUT MUCH MORE EXPENSIVE AND DIFFERENT S/E PROFILE
• Some suggestion that increased efficacy of AI
completely explained by decreased efficacy of
Tamoxifen in CYP2D6 IM and PM
– Punglia (2008) JNCI

60. More relevant to pre-menopausal
woman
• Can’t use AI alone
• In poor metabolizer could consider
– Increased dose???
– Alternative estrogen receptor modulator not
metabolized by CYP2D6 (eg. raloxifen)
– Consider AI with ovarian ablation (chemical or
otherwise)

61. Ethnic Differences in IM and PM of
CYP2D6
• PM alleles more common in European
population
• IM alleles much more common in East Asian
and African population
– In East Asians Intermediate Metabolizers show
similar in vitro CYP2D6 activity c/w Poor
Metabolizers in European populations
• Gene-gene or gene-environment interactions

62. Drug Co-administration
• Antidepressant use common in breast cancer patients
– Depression more common in breast cancer patients and
antidepressant often used to treat how flashes associated with
tamoxifen use
• SSRIs (eg. Fluoxetine and paroxetine) inhibit CYP2D6
• Level of inhibition varies between different drugs with
paroxetine having most inhibition and venlafaxine causing
none
• Kelly et al. BMJ 2010
– Population based cohort study of women receiving tamoxifen
adjuvantly for treatment breast cancer
– Mortality from breast cancer increased in group
using paroxtetine concurrent with tamoxifen

63. Irinotecan – PK example in Colon Cancer
• Excreted after conjugation (glucuronidation) by UGT1A1
• TATA element (consists of TA repeats) in UGT1A1 promoter
shows correlation with transcription levels
– More repeats lower transcription levels
– An example of a non-SNP variant with clinical relevance
• Homozygosity for 7-repeat allele, also known as
UGT1A1*28 associated with severe toxicity (diarrhea and
low WBC counts mainly)
– Results have been somewhat inconsistent but meta-analysis
confirms same especially with higher doses of Irinotecan
– Homozygosity only in 5-15% of individuals

64. PD example in Colon Cancer Treatment
• EGFR inhibitors used in
treatment of advanced
colon cancer (eg.
Cetuximab)
• Tumors with k-RAS (and
probably BRAF)
mutations will NOT
respond to EGFR
inhibition
Nature Rev. Cancer July 2009

65. Review Paper by Pare et al.

66. Effect of Clopidogrel as Compared with Placebo on Clinical Outcomes among Patients with
Acute Coronary Syndromes in the CURE trial, Stratified According to Metabolizer Phenotype.
Paré G et al. N Engl J Med 2010;363:1704-1714

67. Kaplan–Meier Curves for Event-free Survival According to CYP2C19 Loss-of-Function and
Gain-of-Function Allele Carrier Status among European and Latin American Patients with
Acute Coronary Syndromes in the CURE Trial.
Paré G et al. N Engl J Med 2010;363:1704-1714

68. Effect of Clopidogrel as Compared with Placebo on Clinical Outcomes among Patients with
Atrial Fibrillation in ACTIVE A, Stratified According to Metabolizer Phenotype.
Paré G et al. N Engl J Med 2010;363:1704-1714

69. Kaplan–Meier Curves for Event-free Survival According to CYP2C19 Loss-of-Function and
Gain-of-Function Allele Carrier Status among European Patients with Atrial Fibrillation in
ACTIVE A.
Paré G et al. N Engl J Med 2010;363:1704-1714

70. Baseline Characteristics of Genotyped Patients in the CURE and ACTIVE A Trials.
Paré G et al. N Engl J Med 2010;363:1704-1714

71. Why is pharmacogenomics not widely
utilized in the clinic
• It required a shift in clinician attitude and beliefs “not
one dose fits all”
• Paucity of studies demonstrating improved clinical
benefit from use of pharmacogenomic data
– Still much to be learned
• Even some of the black block warnings
currently on drug labels may be overcalls of
importance
• Genome wide interrogation will likely be important
to get the entire picture

72. Conclusion
• Genetic variation contributes to inter-individual differences
in drug response phenotype at every pharmacologic step
• Through individualized treatments, pharmacogenetics and
pharmacogenomics are expected to lead to:
• Better, safer drugs the first time
• More accurate methods of determining appropriate drug
dosages
• Pharmacogenomics offers unprecedented opportunities to
understand the genetic architecture of drug response
• HOWEVER IN MANY CASES NOT YET READY FOR PRIME
TIME!!!