Tim Aitman

1. Tim Aitman 1st Imperial BHF Symposium, June 5th 2009 PROFITING FROM GENOMICS Physiological Genomics and Medicine MRC Clinical Sciences Centre Hammersmith Hospital Imperial College London

2. Identification of Genes underlying Mendelian and Complex Traits 1980-2002 Mendelian traits Complex Traits Mendelian traits All complex traits Human complex traits 1980 1985 1990 1995 2000 Glazier, Nadeau, Aitman, Science, 2002

3. Published Genome-Wide Associations through 3/2009, 398 published GWA at p < 5 x 10-8 NHGRI GWA Catalog www.genome.gov/GWAStudies

4. Most GWAS SNPs have very low odds ratios

5. March, 2009

6. CONCLUSION 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?

7. Three drug discovery stories Statins Thiazolidinediones Angiotensin receptor blockers in Marfan Syndrome • Genomic approaches to understanding cardiovascular phenotypes

10. Statins and the cholesterol synthesis pathway

11. Prior to loss of patent protection (2006), the statin market was worth over 16 billion dollars

12. Could genomics have helped discover the target of the statins?

13. Nature Genetics, 2008

14. Kathiresan et al, Nat Genet, 2008

15. CONCLUSION 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

18. Could genomics have helped discover the target of the TZD’s?

20. CONCLUSION TZD’s were developed through the classical drug discovery pipeline The target of the TZD’s (Pparg) is a genetic risk factor for type 2 diabetes

21. Michael Phelps Marfan Syndrome

22. Lens dislocation Dissection of aorta Marfan – clinical features Arachnodactyly

23. Nature 1991

24. Overactive TGF-b in Marfan mice Anti TGF-b neutralising antibodies reduce lung lesions

27. CONCLUSION 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

28. Genomic approaches to identification of new genes underlying complex cardiovascular traits

29. QTL Plots of Chromosome 4 for Defects in Insulin Action and Fatty Acid Metabolism Microarray to Detect Differential Gene Expression between Tissues from Affected and Control Animals Lod 8 F2 cross Backcross 4 + 6 3 4 2 10 cM 10 cM 2 1 0 0 Il6 Il6 Ae2 Ae2 Wox7 Arb13 Wox7 Mgh4 Arb13 Wox21 Mgh4 Wox21 Aitman et al, Nature Genet 1999 Mgh17 Mgh8 Mgh8 Mgh17 Integrated DNA microarray and linkage analysis in the spontaneously hypertensive rat Aitman et al, Nature Genet 1997 Identification of Cd36 as SHR Insulin Resistance Gene

30. Can integrated genomic approaches give insights into gene function at the level of the genome?

31. Fat Aorta Left ventricle Liver Skeletal muscle 6000 Genome-wide significance 5000 0.05 0.01 0.001 Number of eQTLs 4000 0.0001 0.00001 0.000001 3000 2000 1000 0 adrenal fat kidney aorta LV liver SKM Tissue eQTL datasets generated in the BXH/HXB RI strains eQTL mapping (~1,000 microsatellites and ~2,000 SNPs)

32. Previous linkage analysis showed chromosome 17 QTL regulating left ventricular mass in SHR Peak LOD 4.0

33. A cluster of cis-eQTL genes on chromosome 17 shows striking correlation with Left Ventricular Mass Petretto, Cook

34. Peak LOD 4.0 Hbld2 Ogn Two cis-eQTL genes reside within 1-Lod support interval for the chromosome 17 LV mass QTL

35. Ogn regulates heart mass in the mouse

36. TGFbeta / fibroblast Ogn is most strongly correlated with LVM in humans out of ~22,000 possible transcripts Cook, Petretto, Pinto

37. WT (n=9) Survival (%) Ogn -/- (n=17) Days post-MI Ogn deletion predisposes to cardiac rupture post-MI Stuart Cook

38. Nature Genetics – Rat Focus Issue May 2008

39. Enriched in inflammatory response genes GO:0002376 7.5 x 10-12 immune system GO:0006955 2.1 x 10-11 immune response Identification of inflammatory network in rat heart Posterior probability for non-zero edge = 0.95 Transcription Factor activity Inflammatory Network Rat heart eQTL Corresponding network now replicated in human monocytes

40. 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, Pravenec Birney, Flicek, Hubner, Cuppen, Kurtz, Jones

41. EURATRANS – building a multimodality phenotypic model

42. CONCLUSION 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

43. Prague/San Francisco Michal Pravenec Vladimir Kren Ted Kurtz Berlin/Utrecht Norbert Hübner/Edwin Cuppen Oxford Jonathan Flint Vancouver Steve Jones EBI Ewan Birney, Xose Fernandez Paul Flicek ACKNOWLEDGEMENTS IC/Clinical Sciences Centre Enrico Petretto Santosh Atanur Laurence Game Stuart Cook Terry Cook James Scott Funding BHF MRC Wellcome EU FP6 Leducq Foundation