From Genotype to Phenotype

1. From Genotype to Phenotype Presenter: Jerome Ku May 29, 2008

2. Papers • Cambien, F. and L. Tiret. “Genetics of Cardiovascular Diseases: From Single Mutations to the Whole Genome.” Circ., 2007; 116: 1714-1724. • WTCCC. “Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls.” Nature, 2007; 447: 661-683. • Servin, B. and M. Stephens. “Imputation-based analysis of association studies: candidate regions and quantitative traits.” PLoS, 2007; 114: 1296-1308.

3. Additional Papers • Hirschhorn, J. and M. Daly. “Genome-wide Association Studies for common diseases and complex traits.” Nature, 2005; 6: 95-108. • Personalized Medicine Coalition. “The Case for Personalized Medicine.” November 2006.

4. Genotype to Phenotype Motivation Background Genetics of Cardiovascular Disease Genome-Wide Association Studies Future Directions

5. Genotype to Phenotype Motivation Background Genetics of Cardiovascular Disease Genome-Wide Association Studies Future Directions

6. It is the responsibility of those of us involved in today's biomedical research enterprise to translate the remarkable scientific innovations we are witnessing into health gains for the nation… At no other time has the need for a robust, bidirectional information flow between basic and translational scientists been so necessary.Elias A. Zerhouni, M.D., Director, National Institutes of Health

7. Genotype-to-phenotype of disease processes is critical to medicine Source: PMC 2006

8. And can lead to Predictive, Preventative, and more Precise Medicine Source: PMC 2006

9. Genotype to Phenotype Motivation Background Genetics of Cardiovascular Disease Genome-Wide Association Studies Future Directions

10. 3 Key Factors have enabled these advances in genetics and disease Source: Wikipedia, International HapMap Webpage

11. The HapMap Project has helped elucidate structure of human genome Source: International HapMap Webpage

12. The HapMap Project has helped elucidate structure of human genome Source: HapMap Webpage

13. SNPs are Single Nucleotide Polymorphisms Single base pair change that must occur in at least 1% of population Accounts for 90% of all human genetic variation Occur every 100-300 bases along 3bn base human genome in Coding and Non-coding regions Synonymous and Non-synonymous Source: Wikipedia

14. Haplotypes are combinations of alleles at multiple loci that are co-transmitted SNP A SNP B SNP C SNP D 2 Haplotype Blocks Alternatively, haplotypes are a set of statistically-associated SNPs that are in Linkage Disequilibrium.

15. Let’s look at an example… What are possible haplotypes? A1B1 A1B2 SNP A SNP B A2B1 A2B2 What if we only observe: B1 B2 A1 A2 Both SNPs have 2 Alleles A1B1 A1B2 A2B1 Linkage Disequilibrium!

16. Genotype to Phenotype Motivation Background Genetics of Cardiovascular Disease Genome-Wide Association Studies Future Directions

17. Papers • Cambien, F. and L. Tiret. “Genetics of Cardiovascular Diseases: From Single Mutations to the Whole Genome.” Circ., 2007; 116: 1714-1724. • WTCCC. “Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls.” Nature, 2007; 447: 661-683. • Servin, B. and M. Stephens. “Imputation-based analysis of association studies: candidate regions and quantitative traits.” PLoS, 2007; 114: 1296-1308.

18. Traditional genetic studies were based on a Mendelian model of disease Single genetic defect Rare polymorphisms (< 1%) Linkage Analysis on phenotypically well-characterized families

19. We need better model of disease

20. We need better model of disease

21. Association studies are critical to the study of complex diseases Association Tag, or genotype, SNPs on the basis of Linkage Disequilibrium patterns. Select tags to provide as much information about surrounding region based on association with untagged SNPs. Even if causal polymorphism is not tagged, it will be captured by proxy with an associated SNP that is tagged. Source: Hirschhorn and Daly (2005)

22. Let’s walk through an example… Source: Cambien and Tiret (2007)

23. Early discoveries shed light on basic mechanisms of disease Genetic risk factors for Coronary Heart Disease

24. Single genetic risk factors identified are of limited clinical use Fails to take into account gene-environment interaction Fails to take into account gene-gene interactions Need to understand genetics at a systems-level

25. Genome-Wide Association (GWA) addresses some of these issues.

26. GWA has multiple advantages Discovery Studies not limited to current biological knowledge Quantitative Better characterize complex, quantitative traits

27. GWA has multiple advantages Discovery Studies not limited to current biological knowledge Recent GWA studies discovered: Associated regions containing no annotated genes Tagged SNPs not associated with any established risk factors

28. GWA has multiple advantages Quantitative Better characterize complex, quantitative traits Identification of polymorphism accounting for variance of quantitative trait

29. GWA enables characterization of quantitative traits Cardiac Arrhythmias Out-of-sync heartbeat can lead to sudden death QT interval (QTi) is a measure of the time to repolarization of cardiac cells during heart beat and an indicator of cardiac arrhythmias. QTi is a quantitative, heritable trait. Source: Wikipedia

30. GWA helps explain genetic cause of quantitative traits Multi-stage GWA studied 2 extremes of QTi distribution to identify genomic regions of interest. Identified frequent polymorphisms in nitric oxide synthase 1 adaptor protein (NOS1AP) gene that were consistently associated with QTi in both men and women. NOS1AP not previously linked to cardiac repolarization Accounts for ~1.5% of variance of the QTi in population

31. Papers • Cambien, F. and L. Tiret. “Genetics of Cardiovascular Diseases: From Single Mutations to the Whole Genome.” Circ., 2007; 116: 1714-1724. • WTCCC. “Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls.” Nature, 2007; 447: 661-683. • Servin, B. and M. Stephens. “Imputation-based analysis of association studies: candidate regions and quantitative traits.” PLoS, 2007; 114: 1296-1308.

32. Genotype to Phenotype Motivation Background Genetics of Cardiovascular Disease Genome-Wide Association Studies Future Directions

33. WTCCC’s GWA study was one of the largest to date Wellcome Trust Case Control Consortium (WTCCC) 50 research groups across the UK with expertise ranging from clinical, to genotyping, informatics, and statistics. 2,000 cases and 3,000 shared controls for 7 complex human diseases Bipolar Disorder Coronary Artery Disease Crohn’s Disease Hypertension Rheumatoid Arthritis Type 1 Diabetes Type 2 Diabetes

34. Goal of the study was manifold Understand genetics underlying each disease Differences in allelic structure across the diseases Address Design and Analysis of GWA studies

35. Goal of the study was manifold Understand genetics underlying each disease Overall Results Two Specific Diseases

36. Goal of the study was manifold Understand genetics underlying each disease Overall Results Two Specific Diseases

37. Associations both confirmed previous results and found new regions of interest Confirmed 15 variants previously shown to be associated with one or more of the 7 diseases studied Identified 21 signals across 7 diseases with P-value < 5x10-7 4 additional: 1 sex-differentiated, 2 multi-locus and 1 combined case 58 additional signals with P-values between 10-5 and 5x10-7

38. Associations that replicated past findings

39. 25 Strongest Association Signals

40. Goal of the study was manifold Understand genetics underlying each disease Overall Results Two Specific Diseases

41. A deeper look at two specific diseases Rheumatoid Arthritis Hypertension

42. A deeper look at two specific diseases Rheumatoid Arthritis Hypertension

43. Rheumatoid Arthritis: Disease State Rheumatoid Arthritis Chronic, systemic autoimmune disorder that causes the immune system to attack the joints and organs, such as the lung and skin, leading to inflammation. Susceptibility and severity is due to both genetic and environmental factors. Source: Wikipedia

44. Previous associations were confirmed by study

45. GWA led to 9 new associations Outlined are 2 SNPs that map close to both alpha and beta chains of the IL2 receptor. IL2 receptor mediates stimulation of T lymphocytes and is thought to have an important role in preventing autoimmunity.

46. And also revealed strong sex-differentiated signal Sex-related prevalence difference characteristic Genotype has no apparent effect on Males but is strongly associated with Females

47. In addition to identifying new common susceptibility variants with Type I Diabetes

48. A deeper look at two specific diseases Rheumatoid Arthritis Hypertension

49. Hypertension: Disease State Hypertension (HT) Clinically significant increase in blood pressure Important risk factor for heart disease. Source: Wikipedia

50. Failed to discover associations of statistical significance None of the variants previously associated with HT showed evidence of association No SNPs with significance < 5x10-7 were identified in study