Personalized Cardiovascular Medicine: Where We Stand Now,

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• Personalized Cardiovascular Medicine Where We
  Stand Now,
• and The Road Ahead
• Kiran Musunuru, MD, PhD, MPH
• Jeffrey S Berger, MD, MS
• Geoffrey S Ginsburg, MD, PhD, FACC

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Personalized Medicine Definition

• Personalized medicine is the use of diagnostic
  and screening methods to better manage the
  individual patients disease or predisposition
  toward a disease.
• Personalized medicine will enable risk
  assessment, diagnosis, prevention, and therapy
  specifically tailored to the unique
  characteristics of the individual, thus enhancing
  the quality of life and public health.
• NHLBI Strategic Planning, Theme 10

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Disclaimer

• Personalized medicine remains a research concept
  it is not yet ready for clinical practice!

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Addressing the Complexity of Cardiovascular
Disease
Metabolic pathways
Gene expression profile
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Standard Biochemical Pathway
DNA (genome)
RNA (transcript)
metabolites
protein (e.g., enzyme)
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A New Biomarker Toolbox Shift to Personalized
Care
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The Challenge
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Example Gene Expression Profiling
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Concept of Biosignature
Cardiovascular Insult or Therapy
Patient A
Patient B
Gene chips
Biosignatures
Outcome A
Outcome B
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The Path to Personalized Medicine
Health and Economic Outcomes
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Genomics Definitions

• Polymorphism an area of DNA sequence that
  varies from person to person
• Single nucleotide polymorphism (SNP) a
  polymorphism in which a single base in the DNA
  differs from the usual base at that position
• Copy number variant (CNV) a polymorphism in
  which the number of repeats of a DNA sequence at
  a location varies from person to person
• Indel a polymorphism in which a DNA sequence
  is either present (insertion) or absent
  (deletion) at a location, varying from person to
  person

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Types of Polymorphisms
Single Nucleotide Polymorphism (SNP)
Copy Number Variant (CNV)
Indel Polymorphism
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More Definitions

• Locus is the local area on a chromosome around
  a SNP
• Genotype is the identity of the base at a SNP
  position for each of the two alleles (since
  humans have paired chromosomes) a genotype is
  always two letters, unless the SNP is on the X or
  Y chromosome in a man (XY)
• Haplotype is a combination of SNPs at multiple
  linked loci that are usually transmitted as a
  group from parent to child

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Chromosomal Locus (1)

• Groups of SNPs are separated by recombination
  hotspots the SNPs tend to be passed from
  parents to children as a unit, called a linkage
  disequilibrium block
• Thus, SNPs A, B, C, D, E tend to stay together as
  a group the bases at these SNPs make up a
  haplotype whereas SNPs X and Y are not linked
  (not in linkage disequilibrium)
• Because SNPs AE are all linked, only one of
  these SNPs is needed to act as a tag SNP for
  the whole group

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Chromosomal Locus (2)

• Even though (in this example) SNPs A, B, C, and E
  are not in the gene, each is in linkage
  disequilibrium with the gene and remains
  associated with the gene as it is passed from
  parents to children
• If the gene causes a particular outcome (e.g.,
  higher risk for a disease), SNPs AE will be
  associated with that outcome
• This is the basis for genome wide association
  studies

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Genome Wide Association Studies (GWAS)

• HapMap is an international consortium that has
  identified millions of SNP locations in the human
  genome
• Genome wide association studies (GWAS) in the
  HapMap era
• Identify an optimal set of 300,000 tag SNPs
  (to adequately cover genome of 3,000,000,000
  bases)
• Collect gt 1000 cases (e.g., a disease, a
  successful response to a therapy, etc.) and gt
  1000 controls
• Genotype all case/control DNAs for all tagging
  SNPs
• 600 million not 6 trillion for full genomes
  genotypes
• _at_ 0.005/genotype 3 million for each
  disease (but cost is falling rapidly)

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GWAS to Find Outcome-Associated SNPs (1)
Outcome 1 (cases)
Outcome 2 (controls)
G1
G2
A2
A1
G1
G2
A2
A1
G2
G2
A2
A2
G1
G1
A1
A1
G1
G2
A2
A1
Association between SNP variant A1 / gene variant
G1 and outcome 1
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GWAS to Find Outcome-Associated SNPs (2)
Outcome 1 (cases)
Outcome 2 (controls)
G1
G1
B1
B1
G1
G2
B2
B1
G2
G1
B1
B2
G1
G1
B1
B1
G2
G2
B2
B2
No association between SNP variant B1 / gene
variant G1, and outcome 1
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Uses for the Results of GWAS
Genome to genes
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SNPs for Risk Prediction
SNP 1 AA
(0) vs. GA (1) vs. GG (2)
. . . . . . .
SNP 2 ??
(0) vs. ?? (1) vs. ?? (2)
SNP 3 ??
(0) vs. ?? (1) vs. ?? (2)
. . .
. . .
SNP n ??
(0) vs. ?? (1) vs. ?? (2)
Total risk score X (low
risk vs. medium vs. high)
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Genetic Risk Score for Cardiovascular Disease

• A genetic risk score calculated with 9 SNPs
  associated with LDL or HDL cholesterol (score
  from 0-18) is associated with cardiovascular
  disease
• However, the score does not add to traditional
  risk factors for CVD risk prediction

From Kathiresan et al., N Engl J Med, 2008
358,1240-1249
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SNP Panels for Risk Prediction Pitfalls

• Several companies are marketing SNP panels to the
  general public, charging hundreds to thousands of
  
• The premise for these panels is that they will
  let patients know if they are at higher risk for
  particular diseases
• None of these panels have yet been shown to add
  value to traditional risk factor algorithms, and
  they should not be recommended to patients at
  this time
• The panels do not include rare mutations that
  cause disease
• Because all genome-wide studies to date have been
  done in Caucasian populations, the SNP panels are
  not relevant to non-Caucasian individuals

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Pharmacogenomics Gene-Based Clinical Trial
Randomization
Endpoints
Usual practice of prescribing warfarin
Control group
Time to adequate INR Complications bleeds,
hospitalization
Warfarin dose adjusted to genotype/haplotype
CYP2C9 genotype VKORC1 haplotype
Warfarin Resistance and Sensitivity
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Pharmacogenomics Mixed Success for Warfarin
Formula for dosing Estimated weekly coumadin
dose 1.64 expe3.984 11(0) 12(-0.197)
13(-0.360) 23(-0.947) 22(-0.265)
33(-1.892) Vk-CT(-0.304) Vk-TT(-0.569)
Vk-CC(0) age(-0.009) male sex(0.094) female
sex(0) weight in kg(0.003) where expe is the
exponential to base e 1, 2, 3 refer to CYP2C9
wild-type (1) or variant (2, 3) genotypes,
respectively and Vk refers to VKORC1 with
variants CT, TT, or CC

• In an early clinical trial, use of this formula
  improved the accuracy and efficiency of warfarin
  initiation, though it did not significantly
  reduce out-of-range INRs

From Anderson et al., Circulation, 2007
116,2563-2570
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Pharmacogenomics Mixed Success for Warfarin

• The International Warfarin Pharmacogenetics
  Consortium (IWPC) used a large retrospective
  study of warfarin users to develop an algorithm
  to predict weekly dosing of warfarin
• The algorithm includes age, height, weight, race,
  CYP2C9 genotype, VKORC1 haplotype, and use of
  interacting medications (amiodarone, statins,
  azoles, sulfa drugs)
• The IWPC tested the algorithm in a
  (retrospective) validation cohort of warfarin
  users, comparing with a fixed-dose approach and a
  clinical algorithm (i.e., no genetics information)

From The International Warfarin Pharmacogenetics
Consortium, N Engl J Med, 2009 360,753-764
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Pharmacogenomics Mixed Success for Warfarin

• For most patients, there was no predictive
  advantage to the pharmacogenetic algorithm
• However, for outlierspatients requiring low or
  high doses of warfarin to maintain stable INRthe
  pharmacogenetic algorithm was significantly
  better
• Algorithms such as this one need to be validated
  in prospective clinical trials

From The International Warfarin Pharmacogenetics
Consortium, N Engl J Med, 2009 360,753-764
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Pharmacogenomics Response to Clopidogrel

• The cytochrome P-450 2C19 enzyme converts
  clopidogrel into its active metabolite
• CYP2C19 was genotyped in subjects of 3 large
  studies of post-ACS patients receiving
  clopidogrel
• In all 3 studies, carriers of reduced-function
  CYP2C19 alleles had increased death, subsequent
  MI, and stroke
• Will this be clinically useful?

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Pharmacogenomics Statin-Induced Myopathy

• GWAS of statin-induced myopathy found SNP in
  SLCO1B1 gene associated with the condition
• Individuals with CC genotype have 17 times higher
  risk of myopathy than those with TT
• May be useful for predicting risk before starting
  statin therapyneeds to be tested in clinical
  trial

From The SEARCH Collaborative Group, N Engl J
Med, 2008 359,789-799
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Candidate Genes for Lipid Traits from Genomic
Studies
lipid level
lipid level
LDL HDL Triglycerides
APOB ABCA1 APOA cluster
APOE cluster CETP ANGPTL3
LDLR LIPC MLXIPL
HMGCR LIPG GCKR
PCSK9 LPL TRIB1
CSPG3 GALNT2
SORT1 MVK
From (1) Willer et al., Nat Genet 2008
40,161-169 (2) Kathiresan et al., Nat Genet
2008 40,189-197 (3) Kooner et al., Nat Genet
2008 40,149-151 (4) Sandhu et al., Lancet 2008
371,483-491
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Candidate Genes for CAD/MI from Genomic Studies

• Myocyte Enhancer Factor 2A (MEF2A)
• Wang et al., Science 2003 320,1578-81
• 5-lipoxygenase activating protein (FLAP)
• Helgadottir et al., Nat Genet 2004 36, 233-239
• GATA-2
• Connelly et al., PLOS Genet 2006 2, 1265-1273
• Chromosome 9p21 (gene not known)
• Samani et al., N Engl J Med 2007 357, 443-453

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What to Expect

• Although there are no applications of
  personalized medicine being routinely used in
  cardiology yet, examples from other specialties
  suggest whats on the horizon
• E.g., HLA-B5701 allele testing is now done
  before abacavir therapy to reduce the risk of
  hypersensitivity reactions
• Genetic counselors will play an increasingly
  important role in patient management as genetic
  information becomes incorporated into everyday
  clinical practice
• Referrals to genetic counselors are encouraged
  if no counselors are available at ones
  institution, local counselors can be found
  through the website www.nsgc.org

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Conclusion
We look to a future in which medicine will be
predictive, preventive, preemptive and
personalized