American Society for Experimental NeuroTherapeutics 11 th Annual Meeting Arlington Virginia

1. Genomic /Genetic Considerations in CNS Drug Development: Current Status and Approaches1. Basic Science Standpoint American Society for Experimental NeuroTherapeutics 11th Annual Meeting Arlington Virginia 6 March 2009 Orest Hurko, MDAVP, Wyeth ResearchProfessor (Hon.), University of DundeeDirector: Translational Medicine Research Collaboration ASENT.6 March 2009

2. Genomic /Genetic Considerations for CNS drugs Genes & the pharmaceutical enterprise Methods for studying genes Genome-wide association studies Opportunities ASENT.6 March 2009

3. Decoding the human genome delivered lots of promise … but the downstream challenges were underestimated This enabled the shift from 500 pharmacologically proven targets to 10,000’s of unproven targets, changing the entire drug discovery process Easy wins in rare single-gene disorders prompted unrealistic optimism for common diseases with complex genetics Focus was on technology, not on analysis Hundreds of millions were spent with minimal return Millenium has completely exited genetics to become a conventional drug company Many companies have abandoned efforts in genetics In favor of genomics ASENT.6 March 2009

4. But now, ten years on, genetics has finally become a practical translational tool for industry o • Understanding of statistical issues • High-fidelity high-throughput genotyping • Large repositories of population-basedsamples • Consortia with standardized procedures • Growing appreciation of the heuristic value of outliers • Ever-growing number of robust validations Target Validation Target/Compound Interaction Pharmacodynamic Activity Disease Biomarker & Disease Modification Patient Stratification ASENT.6 March 2009

5. Rare diseases have simple genetics. Common diseases have complex genetics. ASENT.6 March 2009

6. Why should a big drug company be interested in a rare disease? Goldstein JL, Brown MS(1973)Familial hypercholesterolemia: identification of a defect in the regulation of 3-hydroxy-3-methylglutaryl coenzyme A reductase activity associated with overproduction of cholesterol. Proc Natl Acad Sci U S A. 70: 2804-8. “The homozygous form of the autosomal dominant disorder, familial hypercholesterolemia, is characterized by the presence in children of profound hypercholesterolemia, cutaneous planar xanthomas, and rapidly progressive coronary vascular disease that usually results in death before age 30 years….. “ . ASENT.6 March 2009

7. Demonstrable value of studying extreme phenotypes Goldstein JL, Brown MS(1973)Familial hypercholesterolemia: identification of a defect in the regulation of 3-hydroxy-3-methylglutaryl coenzyme A reductase activity associated with overproduction of cholesterol. Proc Natl Acad Sci U S A. 70: 2804-8. “The homozygous form of the autosomal dominant disorder, familial hypercholesterolemia, is characterized by the presence in children of profound hypercholesterolemia, cutaneous planar xanthomas, and rapidly progressive coronary vascular disease that usually results in death before age 30 years. ….” . • Abbott stands to gain as cholesterol-fighters cut risk in other heart issue • By Bruce Japsen | Tribune reporter November 13, 2008 ASENT.6 March 2009

8. But now, genome-wide association studies allow efficient study of common diseases as well. ASENT.6 March 2009

9. Genomic /Genetic Considerations for CNS drugs Genes & the pharmaceutical enterprise Methods for studying genes Genome-wide association studies Opportunities ASENT.6 March 2009

10. Three distinct methodologies for three different questions Genetics The study of variationand its inheritance Intrinsically probabilistic Heritability, segregation analysis, linkage, association Genomics The study of expressionof all genes of an organism Deterministic Transcriptional profiling , in situ hybdrization, difference libraries Molecular Biology The study of molecules underlying genetics & genomics Deterministic Cloning; sequence and structural analyses; cross hybridization; site-directed mutagenesis; si RNA knockdowns; transgenics &b knockout abimal models ASENT.6 March 2009

11. Genetic analyses should only be undertaken if there is significant heritability • Heritability estimates are always relative to the genetic and environmental factors in the population • Heritability describes the population, not individuals within that population Heritability can be estimated in controlled experiments & in population studies Phenotype (P) = Genotype (G) + Environment (E). Var(P) = Var(G) + Var(E) + 2 Cov(G,E). If Cov(G,E) = 0. then H2 = Var(G)/ Var(P) ASENT.6 March 2009

12. The pattern of inheritance dictates the optimal genetic approach Rare sporadic childhood disorders -- Chromosomal rearrangements (or recessives) -- Responsible genes in breakpoints or duplications/deletions Sequencing Unusual high density families -- dominant -- point mutations (or microdeletions / duplications) in genes of major effect Linkage Common, adult disorders without pronounced familial grouping -- multiple genes of additive effect -- often major environmental interactions Association ASENT.6 March 2009

13. High-density families ideal for linkage analysis Figure 1. Pedigree structure of the two Chinese families with tooth agenesis. ASENT.6 March 2009

14. Genomic /Genetic Considerations for CNS drugs Genes & the pharmaceutical enterprise Methods for studying genes Genome-wide association studies Opportunities ASENT.6 March 2009

15. Linkage & Association – same general principle, different time scales Linkage Association 20 generations Crossovers increase with distance ASENT.6 March 2009

16. Genome–wide association studies are based on a very simple idea Genome-wide • Score genomic DNA from a very large sample of cases & controls for a very large number of single-nucleotide polymorphisms (SNPs) • Compare the frequencies among cases & controls • Sites that differ significantly between cases and controls • are then validated in independent samples ASENT.6 March 2009

17. Genome-Wide Association Studies (GWAS) work • Effect sizes are usually small, so big samples needed • Rigorous quality control is paramount • GWAS may fail to detect certain susceptibility genes • Important to look well beyond the top few ‘hits’ • Collaboration is important • Phenotype/selection is important • Validation is critical • Every SNP counts • “Low-hanging fruit” lead to more variants Lessons learned from Genome-Wide Association Studies (GWAS) ASENT.6 March 2009

18. Genome-Wide Association Studies (GWAS) work • Proof of Principle • Complement factor H gene - -age-related macular degeneration • Reliable reproduction in follow-up studies: • PPARg& transcription factor TCF7L2 - Diabetes mellitus • IL23R, CARD15, NOD2 -- Crohn’s disease • chromosome region 8q24 - prostate cancer • GSTM1 null -- bladder cancer & acute leukemia • NAT2 slow acetylator -- bladder cancer • MTHFR C677T -- gastric cancer • Confident associations in other common diseases • coronary artery disease • atrial fibrillation • asthma • rheumatoid arthritis • obesity • breast cancer • coeliac disease ASENT.6 March 2009

19. Effect sizes are usually small, so big samples are needed • Theory predicts that alleles of small effect are more frequent than alleles of large effect • Wellcome Trust Case Control Consortium (WTCCC) GWASs of seven • common diseases found per-allele odds ratios of 1.2–1.5 • Reasonable power to detect such loci requires 2000 cases and 2000 controls • Failures to replicate findings in modestly sized samples do not constitute refutation • Confidence attributable to a ‘significance level’ is influenced by sample size • Rate of true positives increases with sample size because power to detect • true effects increases ASENT.6 March 2009

20. Rigorous quality control is paramount • Enormous data sets (samples & SNPs) in GWASs provide large opportunities for spurious ‘associations’ • Data must be cleaned thoroughly to remove low-quality DNA samples, genotype calls & individual samples • Within WTCCC the best predictor of an SNP with poor QC was a highly significant difference in genotype distributions between • cases and controls -- validation is critical ASENT.6 March 2009

21. GWAS fail to detect some susceptibility genes • Underpowered studies were a leading cause of failure • Current technology surveys only a limited subset of potentially relevant sequence variation • Poor coverage of large genes • Some mutations – such as copy number variations (CNVs) from microduplications or microdeletions –are not detectable in many SNP-based platforms used for GWAS ASENT.6 March 2009

22. Phenotype & case-selection is important Example: association of FTO gene with Type 2 Diabetes Mellitus • WTCCC (not matched for body mass) -- 2000 cases & 3000 common controls • -- significant association @ P = 1.3 x 10-12 • DGI (matched for body mass) -- 14,000 cases and controls • -- no association whatsoever Subsequent work has shown that fat mass & obesity-associated (FTO) influences risk of T2D through a primary effect on body mass ASENT.6 March 2009

23. Collaboration is important • Benefits from collaborations that increase total sample sizes , test consistency & generalizability of findings • Aggressive, very early, proactive data sharing key to identification of several susceptibility loci not evident in any single study alone • Standard phenotyping, threshholds for genome calls, raw data sharing • Diabetes Mellitus (Types 1 & 2), coronary artery disease, ankylosing spondylitis benefited from collaborations ASENT.6 March 2009

24. Genomic /Genetic Considerations for CNS drugs Genes & the pharmaceuticals enterprise Methods for studying genes Association studies Opportunities ASENT.6 March 2009

25. Lessons for Experimental Neurotherapeutics • Learn from rare Mendelian variants of genes encoding potential drug targets (OMIM) • Schizophrenia, autism, restless legs syndrome, early onset depression, bipolar disease, multiple sclerosis, Alzheimer disease, ADHD, & dyslexia are heritable common diseases tractable for GWAS • Do not succumb to the temptation of relaxing diagnostic criteria to boost sample size ASENT.6 March 2009

26. Special Thanks Douglas Blackwood Neil Craddock Dan Crowther Charles ffrench-ConstantFred ImmermanMaha Karnoub Robin Fears Gino Miele Ralph McGinnisVictor McKusick E.A.MurphyColin Palmer David Porteous Nigel Spurr David St. Clair Keith Vass ASENT.6 March 2009