1. Genomewide Association Studies

2.  1. History –Linkage vs. Association –Power/Sample Size  2. Human Genetic Variation: SNPs  3. Direct vs. Indirect Association –Linkage Disequilibrium  4. SNP selection, Coverage, Study Designs  5. Genotyping Platforms  6. Early (recent) GWA Studies

3. Risch and Merikangas 1996 Sample Size Association < Sample Size for Linkage

4. Risch and Merikangas 1996

5. Sample Size Required  Linkage Analysis with affected sib pairs  Transmission Disequilbrium Test (TDT)  TDT with affected sib pairs

6. Affected Sib Pair Linkage Analysis  2 siblings/family  Both sibs affected  IBD at the marker locus  Expect 50% on average

7. Identity By Descent AA AaaAAAaa Sibling 1 2 11 0 Alleles IBD Frequency 2 25% 25% 1 50% 50% 0 25% 25%

8. Identity By Descent Alleles IBD Frequency 2 25% 25% 1 50% 50% 0 25% 25% Expected number of alleles IBD is = 2*25% + 1*50% + 0*25% = 1 allele = 50% sharing

9. Risch and Merikangas 1996

10. Sample Size Calculation Effect Size Exposure Frequency Identity By Descent (IBD M ) Sample Size Required

11. Sample Size Calculation Effect Size Exposure Frequency Identity By Descent (IBD M ) Sample Size Required High IBD sharing Low IBD sharing

12. TDT Transmitted alleles vs. non-transmitted alleles M 1 M 2 M 2 M 1 M 2

13. TDT Transmitted alleles vs. non-transmitted alleles Non-Transmitted Allele Transmitted M1M1M1M1 M2M2M2M2 M1M1M1M1 n 11 n 12 M2M2M2M2 n 21 n 22 TDT = (n 12 - n 21 ) 2 (n 12 + n 21 ) Asymptotically  2 with 1 degree of freedom

14. TDT Transmitted alleles vs. non-transmitted alleles M 1 M 2 M 2 M 1 M 2

15. TDT For this one Trio: Non-Transmitted Allele Transmitted M1M1M1M1 M2M2M2M2 M1M1M1M101 M2M2M2M201 TDT = (1 - 0) 2 (1 + 0) = 1 p-value = 0.32

16. TDT For one hundred Trios: Non-Transmitted Allele Transmitted M1M1M1M1 M2M2M2M2 M1M1M1M115050 M2M2M2M245155 TDT = (50 - 45) 2 (50 + 45) = 6.58 p-value = 0.01

17. Risch and Merikangas 1996 TDT

18.  Linkage –Good for Large Effect Sizes  Genomewide Association –Good for Modest Effect Sizes –Not good for rare disease alleles

19. Two Hypotheses  Common Disease-Common Variant –Common variants –Small to modest effects  Rare Variant –Rare variants –Larger effects

20. Allele Frequency and Sample Size

21. GWA Issues  Cost –Sample Size  Effect Size  Disease Allele Frequency  Multiple Testing –SNP selection  How many?  Which SNPs?  Available Genotyping Platforms

22. Types of Variants  Single Nucleotide Polymorphism (SNP)  Insertion/Deletion (indel)  Microsatellite or Short Tandem Repeat (STR)

23. What is a SNP? AAGTCAGTCTAGGATCGGG TTCAGTCAGATCCTAGCCC TTCAGTCAGATCCCAGCCC AAGTCAGTCTAGGGTCGGG Chromosome 1 Chromosome 2 SNP

24. What is an insertion/deletion? AAGTCAGTCTAGGATCGGG TTCAGTCAGATCCTAGCCC TTCAGTCAGATCCCTAGCCC AAGTCAGTCTAGGGATCGGG Chromosome 1 Chromosome 2 Insertion/Deletion

25. What is an microsatellite? AAGTGTCGTCGTCGTCTCGGG TTCACAGCAGCAGCAGAGCCC TTCACAGCAGCAGAGCCC AAGTGTCGTCGTCTCGGG Chromosome 1 Chromosome 2 3 vs. 4 trinucleotide repeats

26. Relative frequency of each type of variant

27. The Number of SNPs in the Human Genome

28. How many SNPs?  6 billion humans  12 billion chromosomes  1% frequency SNP  120 million copies of the minor allele

29. Ethnic/Racial Variation in SNP frequency

30. Rare SNPs across populations

31. How many of these SNPs have we found?  dbSNP: http://www.ncbi.nlm.nih.gov/projects/SNP/ –10,430,753 SNPs –4,868,126 are “validated”

32. What Risch and Merikangas proposed:  5 genetic polymorphisms per gene  100,000 genes (1996)  = 500,000 genotypes per subject  Candidate Gene Study Design –All genes are candidates  Direct or Sequence-based approach –Causal variant is one of the variants tested

33. Direct vs. Indirect Sequence-based vs. Map-based

34. Indirect Association relies on LD Decay  Variants that are close will have high LD  Variants that are far apart will have low LD  Indirect Association is a form of Positional Cloning

35. LD Decay E(D t ) = D 1 * (1-  ) t where D t is the current amount of LD and t is the number of generations t is the number of generations If  = 0.5, LD decays at a rate of 50% per generation If  < 0.5, LD decay is slower

36. LD Decay over time

37. Observed LD Decay

38. Linkage Disequilibrium ABABABAB abababab AbAbAbAb aBaBaBaB r 2 = (pAB*pab – pAb*paB) 2 pA * pa * pB * pb

39. Indirect Association and LD  Sample size required for Direct Association, n  Sample size for Indirect Association =n/ r 2  For r 2 = 0.8, increase is 25%  For r 2 = 0.5, increase is 100%

40. Coverage  Percent of all SNPs captured by genotyped SNPs  More genotyped SNPs = better coverage

41. Diminishing Marginal Returns (Wang and Todd 2003) r 2 = 0.5 r 2 = 0.8 600,000 SNPs 1,500,000 SNPs

42. Number of SNPs needed to capture all SNPs  Depends on: –Population studied –Minor allele frequency of causal SNP –Level of LD (r 2 ) used as a cutoff  1.4 million selected SNPs for –Caucasians/Asians –5% and above –r 2 = 0.8

43. The HapMap Project  Initial Goal: –600,000 SNPs for indirect association –LD information between SNPs  Phase 1: 1 million SNPs  Phase 2: additional 2.9 million SNPs

44. HapMap  270 subjects  45 Chinese  45 Japanese  90 Yoruban and 90 European-American –30 Trios –2 parents, 1 child

45. HapMap  SNPs from dbSNP were genotyped  Looked for 1 every 5kb  SNP Validation –Polymorphic –Frequency  Haplotype Estimation –Haplotype tagging SNPs

46. Haplotype Tagging

47. Two approaches  Positional cloning –expand LD mapping to entire genome –Tool: HapMap SNPs  Candidate gene or Gene-based –Expand the number of genes to all genes –25,000 genes –Tools: jSNPs, SeattleSNPs, NIEHSSNPs

48. Genome-wide Association LD Based Gene Based

49. Potentially Functional Regions of a Gene cis regulator ? Amino acid coding RNA processing Transcription regulation promoter

50. Comparison of Gene-based and Positional Cloning Designs  Positional Cloning –Agnostic (no biological knowledge needed) –Regulatory regions –SNP sets currently incomplete –Expensive  Gene-based –Efficient: Less SNPs need to be genotyped –May miss regulatory regions –Not all SNPs are known

51. Genotyping Platforms  Affymetrix 500K –Randomly distributed SNPs  Illumina 250K –“Gene-based”  Parallele 20K –Nonsynonymous SNPs –code for an amino acid change

52. Multistage Study Designs

53. 1,2,3,………………………,N 1,2,3,……………………………, M SNPs Samples One-Stage Design Stage 1 Stage 2  samples  markers Two-Stage Design 1,2,3,……………………………, M SNPs Samples 1,2,3,………………………,N One- and Two-Stage GWA Designs

54. SNPs Samples Replication-based analysis SNPs Samples Stage 1 Stage 2 One-Stage Design Joint analysis SNPs Samples Stage 1 Stage 2 Two-Stage Design

55. Multistage Designs  Joint analysis is more power than replication  p-value in Stage 1 must be liberal  Lower cost—do not gain power

56. GWA studies have been published  Myocardial Infarction –65K Gene-based SNPs  Age related Macular Degeneration –Affymetrix 100K  Parkinson’s Disease –Perlegen 200K chip –1,793 SNPs in second stage

57. Myocardial Infarction

58. Functional SNP approach

59. Myocardial Infarction

60. Macular Degeneration

62. Macular Degeneration Results

63. Macular Degeneration

64.  Small Sample  Sparse SNP set  Large Effect Size  High Minor Allele Frequency (>20%)  Under a previous linkage peak  Missed other loci

65. Parkinson’s Disease

66.  Tier 1: –443 Discordant sib pairs –198,345 SNPs  Tier 2: –332 case-control pairs –1,793 SNPs –11 positives at p < 0.01 –Expect 18 positives under the Null

67. Parkinson’s second stage