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Title: omics, the Path to Personalized Medicine


1
-omics, the Path to Personalized Medicine
  • To
  • -Genomics
  • Transcriptomics
  • Proteomics
  • Lipomics
  • Metabolomics

From -TCM-omics -Druid-omics
Jose M. Ordovas
2
Current and Future Practice of Disease
Prevention/Therapy
2005
Diagnosis
Global Advice/Therapy
Public Health Policy/
Focused Screening
Early detection
Personalized Prevention/Therapy
Therapeutic Monitoring
Predisposition
circa2010
Based on Classical and New Biomarkers
Based on Genetics
3
CVD RISK FACTORS and Prevention Priorities
  • Non-modifiable
  • Risk Factors
  • Age
  • Sex
  • Genes
  • Coronary heart
  • disease
  • Stroke
  • Peripheral vascular
  • disease
  • Health, wellbeing

End Points
Intermediate Risk Factors
  • Behavioural
  • Risk Factors
  • Tobacco
  • Diet
  • Physical Activity
  • Alcohol

Socio-economic, Cultural Environmental
Conditions Modernization, Mechanization, Urbanizat
ion, Globalization
4
Lipoprotein Metabolism Exogenous - Pathway
- Endogenous
5
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When can we predict that things go wrong?
Surrogate biomarkers
Late biomarkers of disease/effect
Early biomarkers of disease/effect
Onset of disease/effect
Measurable risk factor
Changes in pathway dynamics to maintain
homeostasis
Time
7
Treatment of early Type 2 Diabetes will have a
major impact of Health Care
100 75 50 25 0
Beta-cell function in
IGT
Postprandial hyperglycemia
Diabetes Phase 1
Diabetes Phase 2
Diabetes Phase 3
-8 -2 0 2
8 14 Years from diagnosis
8
Subtle changes need sensitive parameters
  • Pronounced effect
  • Single parameter biomarker
  • Univariate statistics
  • Static analysis
  • Subtle effect
  • Multiple parameter biomarker
  • Multivariate statistics
  • Dynamic analysis

Measurable risk factor
Time
9
Genomic principles for Medicine must extend to
all levels of biology Systems Biology
Genomes Information
Organism Phenotype
Genes Expression
Proteins Structure Activity
Metabolites Composition
Metabolomics
Proteomics
Transcriptomics
HEALTH/DISEASE
Genomics
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Building Blocks to Health
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Human genome sequence
  • Genome size 3.2 109 nucleotides.
  • 28 is transcribed into RNA of which 5 is
    translated
  • Total number of genes 32,000
  • Gene density 1 Mb 10 genes.
  • The sequence is 99.9 identical between
    individuals.

20
Sequence variation in the human genome
  • Several large-scale surveys indicate that on
    average there is a polymorphic sequence variant
    every 300-1,000 bp.
  • Single nucleotide polymorphisms (SNPs).

About 3,000,000-10,000,000 in the human genome.
21
Importance of SNPs
  • May influence the susceptibility of an individual
    to a disease or affect response to medication.
  • Elucidate the genetic basis of common complex
    disorders.
  • Pharmacogenetic application.
  • Personalized medicine
  • (i.e. adjust life-style, including dose of
    medications, to genotype).

22
How to identify important SNPs
  • Analysis of frequency data in association studies
    (e.g. cases vs. controls).
  • Susceptibility alleles (and genotypes carrying
    them) should be more common in the patient
    population.

23
CVD RISK FACTORS and Prevention Priorities
  • Non-modifiable
  • Risk Factors
  • Age
  • Sex
  • Genes
  • Coronary heart
  • disease
  • Stroke
  • Peripheral vascular
  • disease
  • Health, wellbeing

End Points
Intermediate Risk Factors
  • Behavioural
  • Risk Factors
  • Tobacco
  • Diet
  • Physical Activity
  • Alcohol

Socio-economic, Cultural Environmental
Conditions Modernization, Mechanization, Urbanizat
ion, Globalization
24
From Genotype to DiseaseBuilding the Bridge
Clinical Disease
Subclinical Disease
TG
HDL-C
LDL-C
Genetic Marker
25
Lipoprotein Metabolism Exogenous - Pathway
- Endogenous
APOE
26
APOE Gene and Plasma Cholesterol
27
Key statin trials
Number of events in control and statin groups
RR() 34 24 24 31 25
4S (n4444) CHD/raised cholesterol
LIPID (n9014) CHD/average to raised cholesterol
CARE (n4159) CHD/average cholesterol
WOSCOPS (n6595) No previous MI/raised cholesterol
AFCAPS/TexCAPS (n6605) No CHD/average cholesterol
28
Percent LDL-C response following 12 months of
atorvastatin therapy (10 mg qd)
Pedro-Botet et al. Atherosclerosis
2001158183-93
29
Differential drug efficacy
Same symptoms Same findings Same disease (?)
Same Drug.
Genetic Differences
Different Effects
?
Possible Reasons Non-Compliance
Drug-drug interactions Chance Or.
SNP
30
The Apolipoprotein E4 Allele Determines Prognosis
and the Effect on Prognosis of Simvastatin in
Survivors of Myocardial Infarction A Substudy
of the 4S
  • Gerdes Circulation, 101, 2000.1366-1371

31
Kaplan-Meier curves for all-cause mortality in
placebo-treated MI patients with and without E4
allele
Gerdes Circulation, 101, 2000.1366-1371
32
Kaplan-Meier curves for all-cause mortality in
statin-treated MI patients with and without E4
allele
Gerdes Circulation, 101, 2000.1366-1371
33
From Genotype to DiseaseBuilding the Bridge
Physical Activity
Clinical Disease
Smoking
Subclinical Disease
TG
HDL-C
LDL-C
DIET
Genetic Marker
34
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Age adjusted CVD odds ratios by APOE genotype in
men stratified on the basis of the number of
cigarettes smoked per day in the Framingham
Offspring Study compared to non-smoking E3
homozygotes
Talmud et al. (Annals Hum Genet, in press)
36
PL
PL
Ch
Ch
Ch
Pre-beta2 HDL
Ch
Pre-beta1 HDL
Pre-beta3 HDL
LCAT
HDL3
ApoA-I
HDL3
HDL-R
HL
HDL2b
HDL2a
CE
CETP
FA
Ch
Liver
CE
TG
Ch
To apoB containing lipoproteins
To periphery
37
Genetic Variation 5 to the LIPC gene
Four polymorphisms in complete linkage
disequilibrium have been identified in the region
upstream of the transcription initiation site of
the HL gene (LIPC), defining what is known as the
-514T allele.
38
Plasma HDL-C by LIPC Genotypes
CT
TT
CC
Ordovas et al. Circulation 2002106 2315-2321
39
Tai ES, et al. Dietary fat interacts with the
-514CT polymorphism in the HL gene promoter on
plasma lipid profiles in a multiethnic Asian
population the 1998 Singapore National Health
Survey. J Nutr. 20031333399-408.
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Perilipin function and Gene Structure
Hormone sensitive lipase
Perilipin
Triacylglycerols
Exon1 Exon2
Exon3 Exon4 Exon5 Exon6
Exon7 Exon8 Exon9
Perilipin
6209
10171 11482 13041
14995 (TC)
(AT) (GA)
(AG) (AT)
42
Knock-out mice the effects on body fat
accumulation
Martinez-Botas J , Nat Genet. 2000
Dec26(4)474-9
43

Association between PLIN1 (6209TC) and PLIN4
(11482GA) polymorphisms and BMI in Women

44

Weight reduction in response to a low caloric
diet depending on the PLIN (11482GA )
polymorphism in obese subjects
P0.015 for interaction detween diet and PLIN

45
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NMR Farm
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TrueMass Analysis (Lipomics)
CLINICAL / HEALTH INFORMATION
Phosphatidylcholine
PATIENT
Phosphatidylserine
Phosphatidylethanolamine
Cardiolipin
Sphingomyelin
Phosphatidylinositol
Lipid Extract
Lyso-PLCholine
Triglycerides
SAMPLE
Diglycerides
DATABASE
Free Fatty Acids
Cholesterol Esters
Sterols
50
Surveyor Data Visualization
51
Metabonomics Tools800 MHz Ultrashielded NMR
spectrometer
AVANCE 800 spectrometer with the
UltraShield- UltraStabilized 800 magnet at Bruker
Application Lab
52
Extract from Inevitable FatumA 16th Century
Medical Textbook
The Urine Chart
Urine and other discharge are the means by
which the body restores its natural balance, and
all physicians know that they are filled with
clues and excess humors
53
900 MHz 1H 1D NMR Spectrum of Human Urine
Intensity (proportional to micromolar proton
concentration)
Nmr radiofrequency scale in arbitary units
54
Rapid and noninvasive diagnosis of the presence
and severity of coronary heart disease using
1H-NMR-based metabonomics
  • Joanne T. Brindle et al. Nature Medicine
    8, 1439 - 1445 (2002)

55
Prediction of coronary artery status using the
PLS-DA model.
Comparison of patients with severe
atherosclerosis (TVD) and patients with normal
coronary arteries(NCA).
Joanne T. Brindle et al. Nature Medicine
8, 1439 - 1445 (2002)
56
Human Population Response Vector
Analysis Multivariate Effect of Statin Treatment
subjects
124
Strong increase in TRG
Strong decrease in TRG
111
122
108
121
113
114
123
129
104
107
102
103
105
112
106
128
125
119
101
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increase in TRG, LDL, CHOL and HDL (bis sample
trajectory)
125
120
128
129
PC1
PHARMACO-METABONOMICS EACH LINE REPRESENTS AN
INDIVIDUALS RESPONSE VECTOR CONNECTING PRE-AND
POST-TREATMENT
57
The Close Up
58
The Big Picture
59
Therapeutic recommendations Current vs Targeted
todayempirical recommendationmass market
futurerational recommendationindividualized
Begin therapy
Begin therapy
trial switch
definetreat
D I E T B
DIET C
DIET A
DIET D Successful Treatment!!
DIET D Successful Treatment!!
informed physician diagnosisSavings time, money
illness
individual physician experienceCost time, money
well-being
60
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