Pharmacogenomics: Implications for Clinical Education

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Pharmacogenomics Implications for Clinical
Education

• Howard J Federoff, MD, PhD
• Georgetown University Medical Center

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Themes

• Progressive reductionism in medicine Right
  direction?
• Post-Genomics forecasting and implications of
  pharmacogenomics (PGx)
• The state of PGx (Warfarin illustration)
• PGx approaches will likely be extended by systems
  approaches
• Systems medicine as a paradigm
• Status of training needs for physicians of
  tomorrow

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Progressive Reductionism Heading in the Right
Direction?

• Galen
• Observation and reasoning first experimental
  physiologist
• Mendel
• Describes dominance and recessiveness
• Darwin
• Natural selection and key role of the environment
• Flexner
• Articulated a standard for educating physicians
• Beadle and Tatum
• One gene - one enzyme
• Watson Crick
• Architecture of DNA and implications for its
  replication
• Human Genome Project
• 3 billion bp comes to life?

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Post-Genomic Forecasting and PGx

• Genetic diseases that are highly penetrant are
  rare
• Important but may not exemplars for
  geno-management of prevalent diseases
• Common diseases are genetically complex
• Small contributions are conveyed by multiple
  genes
• GWAS and massive parallel DNA sequencing may
  prove inadequate to direct clinical management
• Identified key SNPs, haplotypes or DNA code are
  unlikely to guide individual management decisions
• Population differences in linkage disequilibrium
  may diminish generalizability
• Environmental factors contribute substantively
  through several mechanisms to modulate inherited
  read-outs
• Delineation of specifics effectors is required
  (molecules, immune responses, etc)
• Epigenomics appears essential for connecting
  potentiality (genetically/genomically) with
  reality (at-risk, preclinical dz and manifest dz)
• Elucidation of which/where (CpG, location),
  magnitude of effect (gene expressivity) and
  demonstrable clinical impact (dx, prognosis and
  management)

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Status of PGxwww.fda.gov/cder/genomics/genomic_bi
omarkers_table.htm

• Four drugs labeled as Test Required
• Eight drugs labeled as Test Recommended
• Thirteen drugs labeled as Information Only

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State of PGx Warfarin Illustration
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Illustration Warfarin
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The State of PGxwww.fda.gov/cder/genomics/genomic
_biomarkers_table.htm
1 Required 2 Recommended
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Warfarin Interactions

• Increase INR or bleeding risk
• Acetaminophen Alcohol
• Amiodarone Anabolic Steroids
• Antifungals Aspirin and Salicylates
• Cephalosporins Chloral Hydrate
• Cimetidine Clofibrate
• Cranberry Juice (CYP2C9 inhibitor)
• Danazol Diflunisal
• Disulfiram Fluvoxamine
• Ginkgo Biloba Heparin
• HMG CoA Reductase inhibitors
• Isoniazid (INH) Macrolides
• Metronidazole Nalidixic Acid
• NSAIDs Omeprazole
• Paroxetine Penicillin
• Propafenone Quinidine
• Quinolones Sulfinpyrazone
• Tamoxifen Tetracycline
• Thyroid Hormone Ticlopidine

Decrease INR/ Increase clotting risk American
Ginseng Barbiturates Binding
Resins Carbamazepine (Tegretol) Oral
Contraceptives Penicillin Rifampin St.
John's Wort Vitamin K
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Warfarin Summary

• Two genes, CYP2C9 and VKORC, have polymorphisms
  that affect activity and/or expression
• CYP2C9 is potently upregulated by drugs and other
  ingested chemicals
• Together these PGx contributions account for 55
  of inter-individual variability

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Warfarin Dosing A Complex Problem

• Metabolizing enzyme (CYP2C9) genetic variation
  (affecting substrate speciificity, Km or Vmax)
• Metabolizing enzyme regulated transcriptionally
  (affecting absolute rate of mRNA production
  linked to gene product abundance)
• Metabolizing enzyme inhibited catalytically (Ki)
• Drug target (VKORC) genetic variation
  (specificity, Km, Vmax)
• Drug target regulated transcriptionally (rate of
  mRNA synthesis linked to gene product abundance)
• Therefore, INR is a product of multiple dynamic
  effects

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Estimation of Warfarin Dose with Clinical and
Pharmacogenetic Data
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 Required Patient Information  Age 
          Sex        Ethnicity  Race
   Weight              Height    Smokes
      Liver Disease   Indication
 -Select-Atrial fibrillation/ Cardioembolic/
stroke/ Deep venous thrombosis/ Heart
failure/cardiomyopathy/ Heart valve
replacement/ Hip fracture/ Hip replacement/
Knee replacement/ Myocardial infarction/
Pulmonary embolism/ Pulmonary
hypertension Baseline INR      Target
INR  CYP2C9 Genotype CYP2C91/1
(wildtype)CYP2C91/2CYP2C92/2CYP2C91/
3CYP2C92/3CYP2C93/ VKORC1-1639/3673
Genotype   Amiodarone/Cordarone Dose 
mg/day Statin/HMG CoA Reductase
Inhibitor -Select-Atorvastatin/Lipitor/CaduetFl
uvastatin/ LescolLovastatin/Mevacor/Altoprev/Ad
vicorPravastatin/PravacholRosuvastatin/ Crestor
Simvastatin/Zocor/VytorinNo statin/Any azole
(eg. Fluconazole) Sulfamethoxazole/Septra/Bact
rim/Cotrim/Sulfatrim  
13 Variables
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Where is PGx heading?

• PGx, while nascent, is derivative of genomics
• In the extreme, genomic information will be mined
  to derive an understanding of a restricted set of
  genes that confer variability to drug metabolism
  and drug target action
• While likely to drive drug discovery and
  development and biomarker validation it will
  likely have modest impact on individualizing
  patient care
• For greater precision a more comprehensive
  approach is required incorporation genomic,
  epigenomic and environmental assessments
• Systems medicine is an example

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Systems Medicine

• A holistic quantitative approach to defining the
  properties of a biological entity
• Premised on Systems Biology, it examines the
  interactions of elements (genes, proteins,
  metabolites and environmental factors)
  dynamically
• The elements are nodes, their interactions edges
  and their behavior constitutes a network
• Networks are measured quantitatively, modeled and
  their emergent properties herald unanticipated
  biological outcomes
• The continuum between wellness and disease is not
  discontinuous but rather characterized by a
  quantifiable perturbation to a network
• When sufficiently robust the network perturbation
  is manifest somatically by a symptom or sign

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Systems Medicine Dynamic Networks

• Elements (genes, proteins, etc)
  nodes--measurements!
• Interactions between the elements
  edges--dynamic
• Elements and their interactions are affected by
  the context of other systems within--cells and
  people AND the environment
• Interactions between/among elements give rise to
  the systems Emergent properties

Modified from Lee Hood
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Disease Arises from Perturbed Networks
dynamics of pathophysiology
diagnosis
therapy
prevention
Non-Diseased
Diseased
Courtesy of Lee Hood
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Getting ThereEpigenomics links inherited
vulnerability to environment
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The Central DogmaInformation Flow
DNA
RNA
Proteins
Metabolites
Biological Molecular Cast
But the dogma has changed!
Figures from Alberts, Johnson, Lewis, Raff,
Roberts, Walter, Molecular Biology of the Cell,
4th Edition, Garland Science, New York, NY (2002).
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DNA can be Modified by Methylation
What promotes non-coding epigenomic alteration?
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Environment-Gene Interaction
1,2 Epigenetic Changes
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Is epigenomic methylation a dynamic process?
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Global Change in Methylation in 7 years
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Epigenomics and Medicine

• Genomic methylation appears highly dynamic in
  populations
• As methylation and other epigenomic modifications
  are linked to transcription this plasticity will
  be likely reflected by altered gene expression
  AND altered biology
• Environmental factors are overwhelmingly likely
  to be contributory to such epigenomic changes
• Characterizing these epigenomic loci, their
  functional correlates, implications for disease
  and its management are critical for the future of
  clinical medicine
• A full understanding of these processes will
  likely refine our understanding of disease
  mechanisms, the selection of therapeutics,
  measurements of responses and titration of dosing
  

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Training the Next Generation

• Design and implement curricula that include
  systems medicine
• Develop training modules for clinical educators
• Develop inpatient electives and outpatient
  modules
• Develop new measures and utilize existing
  measures of the performance of graduates
• First graduates 2015
• Develop GME and CME content

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Thank you
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A Strategy for Catalysis

• Structure a partnership comprising key
  stakeholders Industry, the academy and the
  relevant Federal agencies
• Focus on small but scaleable investigative,
  educational, clinical and ethical objectives
• Leverage all available high quality digital data
  that has application to human disease and its
  management
• Leverage supercomputing capacity through the DOE
  funded national laboratories
• Commit to blending of open source and proprietary
  IP
• Develop infrastructure to support varied growth
  rates