tim aitman 1 st imperial bhf symposium, june 5 th 2009 profiting from genomics physiological...
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Tim Aitman
1st Imperial BHF Symposium, June 5th 2009
PROFITING FROM GENOMICS
Physiological Genomics and MedicineMRC Clinical Sciences CentreHammersmith HospitalImperial CollegeLondon
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Mendelian traits Complex Traits
1980 1985 1990 1995 2000
Identification of Genes underlying Mendelian and Complex Traits
1980-2002
Glazier, Nadeau, Aitman, Science, 2002
Mendelian traits
All complex traits
Human complex traits
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Published Genome-Wide Associations through 3/2009, 398 published GWA at p < 5 x 10-8 NHGRI GWA Catalog
www.genome.gov/GWAStudies
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Most GWAS SNPs have very low odds ratios
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March, 2009
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• Genome-wide association studies have
dramatically advanced our understanding
of the molecular genetic basis of common
human diseases, and potentially disease
prediction
• But do genomic approaches have any
relevance to drug discovery pipelines?
CONCLUSION
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• Statins
• Thiazolidinediones
• Angiotensin receptor blockers in Marfan
Syndrome
Three drug discovery stories
• Genomic approaches to understanding
cardiovascular phenotypes
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Statins and the cholesterol synthesis pathway
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Prior to loss of patent protection (2006),the statin market was worth over
16 billion dollars
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Could genomics have helped
discover the target of the
statins?
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Nature Genetics, 2008
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Kathiresan et al, Nat Genet, 2008
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• Development of statins followed the
discovery of the LDL receptor as a cause of
familial hypercholesterolaemia, and HMG CoA
reductase as the rate-limiting enzyme in
cholesterol synthesis
• Thirty years later, GWAS identifies SNPs in
HMG CoA reductase (and other genes) as
(minor) cause of hypercholesterolaemia
CONCLUSION
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Could genomics have helped
discover the target of the
TZD’s?
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• TZD’s were developed through the classical
drug discovery pipeline
• The target of the TZD’s (Ppar) is a genetic
risk factor for type 2 diabetes
CONCLUSION
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Michael Phelps
Marfan Syndrome
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Arachnodactyly
Lens dislocation
Dissection of aorta
Marfan – clinical features
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Nature 1991
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Overactive TGF- in Marfan mice
Anti TGF- neutralising antibodies reduce lung lesions
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• Positional cloning of the Marfan gene, and
study of disease mechanism in a mouse
model led to rational development of a new
treatment for this rare, single gene disorder
CONCLUSION
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Genomic approaches to identification
of new genes underlying complex
cardiovascular traits
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QTL Plots of Chromosome 4 for Defects in Insulin Action and Fatty
Acid Metabolism
0
2
4
6
8Lod
0
1
2
3
4
Wox21Ae2
Arb13Il6
Wox7Mgh4
Mgh17 Mgh8
10 cM
Ae2Arb13Il6
Wox7Wox21Mgh4
Mgh17 Mgh8
10 cM
F2 cross Backcross
Aitman et al, Nature Genet 1997
Identification of Cd36 as SHR Insulin Resistance Gene
+
Microarray to Detect Differential Gene Expression between Tissues from
Affected and Control Animals
Aitman et al, Nature Genet 1999
Integrated DNA microarray and linkage analysis in the spontaneously hypertensive rat
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Can integrated genomic approaches give insights into gene function at the
level of the genome?
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eQTL datasets generated in the BXH/HXB RI strains
eQTL mapping(~1,000 microsatellites and ~2,000 SNPs)
FatAorta Skeletal muscleLiverLeft ventricle
Nu
mb
er o
f eQ
TL
s
Tissue
Genome-wide significance
fat LVadrenal aortakidney liver SKM0
1000
2000
3000
4000
5000
6000
0.050.010.0010.00010.000010.000001
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Peak LOD 4.0
Previous linkage analysis showed chromosome 17
QTL regulating left ventricular mass in SHR
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A cluster of cis-eQTL genes on chromosome 17 shows striking correlation with Left Ventricular Mass
Petretto, Cook
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Peak LOD 4.0
Hbld2 Ogn
Two cis-eQTL genes reside within 1-Lod support
interval for the chromosome 17 LV mass QTL
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Ogn regulates heart mass in the mouse
LV
M (
%)
Baseline Hypertrophic stimulation
Ogn-/-
Ogn+/-
Ogn+/+
Ogn-/-
Ogn+/-
Ogn+/+
0.0
0.1
0.2
0.3
0.4
0.5
** *
ns ns
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Probeset ID Gene title Gene name Fold
change1 FDR (%)2
Correlation with LVMI3
P-value of correlation
218730_s_at Osteoglycin OGN 1.8 2.8 0.62 8E-04
208370_s_at Down syndrome critical region 1 DSCR1 2.0 1.4 0.61 9E-04
207173_x_at Cadherin 11, type 2, CDH11 1.8 2.8 0.54 4E-03
204472_at GTP binding protein GEM 2.7 1.4 0.53 5E-03
205841_at Janus kinase 2 JAK2 2.1 2.1 0.53 6E-03
219087_at Asporin ASPN 2.6 1.4 0.52 7E-03
213765_at Microfibrillar associated protein 5 MFAP5 2.2 1.4 0.51 7E-03
203570_at Lysyl oxidase-like 1 LOXL1 1.7 1.4 0.51 7E-03
209101_at Connective tissue growth factor CTGF 3.0 1.4 0.51 8E-03
213764_s_at Microfibrillar associated protein 5 MFAP5 1.8 1.4 0.51 8E-03
211161_s_at Collagen, type III, alpha 1 COL3A1 3.2 1.4 0.50 9E-03
205478_at Protein phosphatase 1subunit 1A PPP1R1A -1.6 1.4 -0.59 2E-03
210096_at Cytochrome P450, family 4 CYP4B1 -1.5 2.8 -0.60 1E-03
213524_s_at G0/G1switch 2 G0S2 -2.1 1.4 -0.60 1E-03
TGFbeta / fibroblast
Ogn is most strongly correlated with LVM in humans out of ~22,000 possible transcripts
Cook, Petretto, Pinto
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0 2 4 6 8 10 12 140
25
50
75
100
Su
rviv
al (
%)
Days post-MI
WT (n=9)
Ogn -/- (n=17)
Ogn deletion predisposes to cardiac rupture post-MI
Stuart Cook
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Nature Genetics – Rat Focus IssueMay 2008
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TranscriptionFactor activity
eQTL
GO:0002376 7.5 x 10-12 immune system
GO:0006955 2.1 x 10-11 immune response
Enriched in inflammatory response genes
Posterior probability for non-zero edge = 0.95
Identification of inflammatory network in rat heart
Corresponding network now replicated in human monocytes
Inflammatory Network Rat heart
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Generation of SHR Genome Sequence by short-read sequencing
• Paired-end sequence, Illumina GAII
• Mapped to BN reference sequence – MAQ 0.6.6
• 78 lanes, 11 x coverage
• SNP calling– 3 or more reads, MAQ score>30– 3.1 Million SNPs– 436K short indels (1-5bp)– 22K indels (5bp-1Mbp)
Aitman, Cook, PravenecBirney, Flicek, Hubner, Cuppen, Kurtz, Jones
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EURATRANS – building a multimodality phenotypic model
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• High throughput and integrative genomic
techniques are increasing our understanding of
the molecular pathogenesis of common
diseases
• Multiple types of genome-wide data, together
with informatics and modelling stand to identify
new preventive strategies, including new
approaches to screening and new drug targets
CONCLUSION
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ACKNOWLEDGEMENTS
IC/Clinical Sciences CentreEnrico PetrettoSantosh AtanurLaurence GameStuart Cook Terry CookJames Scott
FundingBHFMRCWellcomeEU FP6Leducq Foundation
Prague/San FranciscoMichal Pravenec
Vladimir Kren
Ted Kurtz
Berlin/UtrechtNorbert Hübner/Edwin Cuppen
OxfordJonathan Flint
VancouverSteve Jones
EBIEwan Birney, Xose Fernandez
Paul Flicek
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