1. SNP Discovery and Analysis Application to Association Studies
Mark J. Rieder, PhD
Dana Crawford, PhD
SeattleSNPs PGA
Morehouse University
May 2, 2005
Thank you and I am pleased to be here today to share with you our work on genetic determinants of warfarin dosing, specifically we looked at the recently discovered gene vitamin K epoxide reductase (VKORC1) and its affect on normal warfarin dosing in clinical patients. I will begin by giving some background on the clinical uses of warfarin, some of the genetic variants in the cytochrome P450 2C9 gene which affect warfarin metabolism and then finally I’ll describe our work VKORC1 hapltoypes which predict warfarin dose across the normal clinical range.

2. Practical Aspects of SNP Association Studies
SNP Discovery:
Where do I find SNPs to use in my association studies?
(e.g. databases, direct resequencing)
SNP Selection:
How do I choose SNPs that are informative?
(i.e. assessing SNP correlation - linkage disequilibrium)
SNP Associations:
What analyses can I perform after genotyping these SNPs?
(e.g. single SNP data, haplotype data)
SNP Replication/Function:
How is function predicted or assessed.
(e.g. nonsynonymous SNPs, conserved non-coding regions (CNS)
transcription factor binding sites, gene expression)

3. SeattleSNPs Program for Genomic Applications: Overview
Aim 1: To establish a variation discovery resource capable of comprehensive resequencing of candidate genes related to HLBS.
Biological Focus: Inflammation
Genes and Pathways: Coagulation, Complement, Cytokines
Interacting Partners

4. SNPs in Candidate Genes
SeattleSNPs
SNPs in Candidate Genes
Average Gene Size kb ~ Compare 2 haploid - 1 in 1,200 bp
~130 SNPs (200 bp) - 15,000,000 SNPs
~ 44 SNPs > 0.05 MAF (600 bp) - 6,000,000 SNPs

5. SeattleSNPs PGA: Candidate Gene SNP Resource
4.6 Mb in 47 individuals = 216 Mb total sequence
Define sequence diversity - catalogue all SNPs
Select “optimal” tagSNPs sets
Determine haplotype structure
Provide necessary baseline data for association studies

6. Warfarin Pharmacogenetics
Background
Warfarin characteristics
Pharmacokinetics/Pharmacodynamics
Discovery of VKORC1
VKORC1 - SNP Discovery
VKORC1 - SNP Selection (tagSNPs)
VKORC1 - SNP Testing
SNP/Haplotype Inference
Haplotype Inference, Testing
VKORC1 - SNP Replication/Function

7. Pharmacogenomics as a Model for Association Studies
Clear genotype-phenotype link
intervention variable response
Pharmacokinetics - 5x variation
Quantitative intervention and response
drug dose, response time, metabolism rate, etc.
Target/metabolism of drug generally known
gene target that can be tested directly with response
Reduce variability and identify outliers.
Prospective testing
Personalized Medicine

8. Warfarin Background Commonly prescribed oral anti-coagulant
In 2003, 21.2 million prescriptions were written for
warfarin (Coumadin)
Prescribed following MI, atrial fibrillation, stroke,
venous thrombosis, prosthetic heart valve replacement,
and following major surgery
Difficult to determine effective dosage
Narrow therapeutic range
- Monitoring of prothrombin time (INR)
Large inter-individual variation
Very effective rat poison!
First let me begin by giving a brief background on warfarin and its signficance in clinical medicine. Point 1, point 2 - and at any given time in the US about 2 million people are on chronic therapeutic warfarin, and this Is generally prescribed for, point 3, and also prophalatically following major surgery. Two important issues come when warfarin is used in the clinic - first a patient must be brought to a stable maintenance dose - and there is a large inter-individual variation here mg/d - patients are generally started at 5 mg/d and then titrated from that point. Once the maintenace dose has been achieved the issue the comes to keeping them with their very narrow therapeutic range. And this improtant of course because excess dosing leads to hemorrhage and low dose can not provide protection against clotting. This whole dosing procedure then is tightly monitored using the prothrombin or bleeding time as measured by the INR and kept with the normalized range of 2-3.

9. Add warfarin dose distribution
Ave: 5.2 mg/d
n = 186
European-American
30x dose variability
Add warfarin dose distribution
However, as I mentioned achieving the proper maintenance dose can be difficult due to the large inter-individual range of dose from about Here is the data from the UW European American clinical patients we looked at this the study. Of course physician can determine the warfarin dose empirically, but really we would like to understand the pharmacokinetic and pharmacodynamic genetic influences which underlie this distribution %
Patient/Clinical/Environmental Factors
Pharmacokinetic/Pharmacodynamic - Genetic

10. Warfarin inhibits the vitamin K cycle
Epoxide
Reductase
 -Carboxylase
(GGCX)
Warfarin
Inactivation
CYP2C9
Pharmacokinetic
Vitamin K-dependent clotting factors
(FII, FVII, FIX, FX, Protein C/S/Z)

11. Warfarin Metabolism (Pharmacokinetics)
Major pathway for termination of pharmacologic effect
is through metabolism of S-warfarin in the liver by CYP2C9
CYP2C9 SNPs alter warfarin metabolism:
CYP2C9*1 (WT) - normal
CYP2C9*2 (Arg144Cys) - low/intermediate
CYP2C9*3 (Ile359Leu) - low
CYP2C9 alleles occur at a significant minor allele frequency
European: * % * %
Asian: *2 - 0% * %
African-American: * % * %
The other important factor is the CYP2C9 variant alleles occur at an appreciable frequency in the general population.

12. Effect of CYP2C9 Genotype on Anticoagulation-Related Outcomes
(Higashi et al., JAMA 2002)
WARFARIN MAINTENANCE DOSE
TIME TO STABLE ANTICOAGULATION
CYP2C9-WT ~90 days
*2 or *3 carriers take longer to reach stable anticoagulation
CYP2C9-Variant ~180 days N
mg warfarin/day
And clear practical implication for the genetic effects of CYP2C9.
- Variant alleles have significant clinical impact
- Still large variability in warfarin dose (15-fold) in *1/*1 “controls”?

13. Analysis of Independent Predictors of Warfarin Dose
Adapted from Gage et al., Thromb Haemost, 2004
Variable Change in Warfarin Dose P value
Target INR, per 0.5 increase 21% <0.0005
BMI, per SD % <0.0001
Ethnicity (African-American, [Asian]) 13%, [ %]
Age, per decade 13% <0.0001
Gender, Female 12% <0.0001
Drugs (Amiodarone) 24%
CYP2C9*2, per allele 19% <0.0001
CYP2C9*3, per allele 30% <0.0001
~ 30% of the variability in warfarin dose is explained by these factors
What other candidate genes are influencing warfarin dosing?

14. Warfarin acts as a vitamin K antagonist
Pharmacodynamic
Epoxide
Reductase
CYP2C9
Inactivation
 -Carboxylase
(GGCX)
Vitamin K-dependent clotting factors
(FII, FVII, FIX, FX, Protein C/S/Z)

15. New Target Protein for Warfarin
Epoxide
Reductase
(VKORC1)
 -Carboxylase
(GGCX)
And encoded for the gene now named VKORC1. In this work by Rost et al that should the overt warfarin resistance was due to non-synonymous mutation in VKORC1 - that is patients needing doses at mg/d had clear predisposing mutations. Interestingly, NO nonsynomymous mutations were found in control chromosomes.
Clotting Factors
(FII, FVII, FIX, FX, Protein C/S/Z)
Rost et al. & Li, et al., Nature (2004)
5 kb - chr 16

16. Warfarin Resistance VKORC1 Polymorphisms
Point out that normal warfarin dose is 5 mg/d
Rost, et. al. Nature (2004)
Rare non-synonymous mutations in VKORC1 causative for warfarin resistance (15-35 mg/d)
NO non-synonymous mutations found in ‘control’ chromosomes (n = ~400)

17. VKORC1 nonsynonymous coding Common VKORC1 non-coding SNPs?
Inter-Individual Variability in Warfarin Dose: Genetic Liabilities
SENSITIVITY
CYP2C9 coding
SNPs - *3/*3
RESISTANCE
VKORC1 nonsynonymous coding
SNPs
Frequency
Common VKORC1 non-coding SNPs?
0.5 5 15
Warfarin maintenance dose (mg/day)

18. SNP Discovery: Resequencing VKORC1
PCR amplicons --> Resequencing of the complete genomic region
5 Kb upstream and each of the 3 exons and intronic segments; ~11 Kb
SeattleSNPs PGA - pga.gs.washington.edu (24 African-Am./23 Europeans)
Warfarin treated clinical patients (UWMC): 186 European
Other populations: 96 European, 96 African-Am., 120 Asian

19. SNP Discovery: Resequencing Results
Summary of PGA samples (European, n = 23)
Total: 13 SNPs identified
10 common/3 rare (<5% MAF)
Clinical Samples (European patients n = 186)
Total: 28 SNPs identified
10 common/18 rare (<5% MAF)
15 - intronic/regulatory
7 - promoter SNPs
2 - 3’ UTR SNPs
3 - synonymous SNPs
1 - nonsynonymous
- single heterozygous indiv. - highest warfarin dose = 15.5 mg/d
How does the comprehensive SNP discovery compare to what was known for this gene?

20. SNP Discovery: dbSNP database
-NCBI SNP database

21. SNP Discovery: dbSNP database
SeattleSNPs Resequencing
28 SNPs --> 15 SNPs gene region
10 dbSNPs
8/10 confirmations
3 frequency/genotype data
7 new dbSNP entries generated
by SeattleSNPs resequencing
8 dbSNPs/15 SNPs (~50%)

22. SNP Discovery: dbSNP database
Nickerson and Kruglyak, Nature Genetics, 2001
Mar million (validated - 1/600 bp)
5.0/10.0 = 50% of all common SNPs (validated)!

23. { GTTACGCCAATACAGGATCCAGGAGATTACC GTTACGCCAATACAGCATCCAGGAGATTACC
SNP discovery is dependent on your sample population size {
GTTACGCCAATACAGGATCCAGGAGATTACC
GTTACGCCAATACAGCATCCAGGAGATTACC
2 chromosomes
0.0
0.2
0.3
0.4
0.5
0.1
1.0
Minor Allele Frequency (MAF)
Fraction of SNPs Discovered 2 48 24 16 8 96

24. { SNP Discovery: dbSNP database SeattleSNPs dbSNP (Perlegen/HapMap)
Minor Allele Freq. (MAF)
dbSNP (Perlegen/HapMap)
25% {
75%
50%
Minor Allele Freq. (MAF)
Rarer and population specific SNPs are found by resequencing

25. dbSNP: Increasing numbers of SNPs now have genotype data
HapMap
Phase II
Perlegen
Perlegen
Data

26. Current State of dbSNP
Many SNPs left to validate and characterize.

27. Development of a genome-wide SNP map: How many SNPs?
Nickerson and Kruglyak, Nature Genetics, 2001
~ 10 million common SNPs (>1- 5% MAF) - 1/300 bp
Mar million (validated - 1/600 bp)
5.0/10.0 = 50% of all common SNPs validated!
Coming Soon! 5.0 million validated SNPs with genotypes!

28. SNP Discovery: dbSNP database
dbSNP Issues:
Not comprehensive catalog (50% of SNPs)
Is the data confirmed? (50% are validated)
Information about allele frequency/population (50%)
No information about SNP correlations (linkage disequilibrium)
genotyping efficiency

29. Does common variation in VKORC1 have a role in determining
SNP Selection: Using Linkage Disequilibrium
Common SNPs
VKORC total SNPs > 10% MAF
Evaluate linkage disequilibrium (non-random association of
genotype data)
Warfarin Dose (mg/d)
Frequency
Does common variation in VKORC1 have a role in determining
warfarin dose?

30. SNP Selection: Using Linkage Disequilibrium
Site 1
Site 2
Site 1
Site 2
Maternal C A
C : 50%
A : 50% T G
T : 50%
G : 50%
Paternal
Possible
2-site comb.
Expected Freq.
Observed Freq.
C A X 0.5 = *
C G X 0.5 =
T A X 0.5 =
T G X 0.5 = *
* Sites Correlated

31. SNP Selection: Using Linkage Disequilibrium
SNP discovery data (i.e. population of samples with genotypes)
Find all correlated SNPs to minimize the total number of SNPs
Maintains genetic information (correlations) for that locus
LD_Select - SNP tagging/binning algorithm - based on LD (r2), not haplotypes
Carlson, et al. AJHG (2004)

32. SNP Selection: VG/LD_Select on the Web
pga.gs.washington.ed/VG2

33. SNP Selection: tagSNP Data

34. SNP Selection: VKORC1 tagSNPs

35. SNP Testing: VKORC1 tagSNPs
Five Bins to Test
381, 3673, 6484, 6853, 7566
2653, 6009
861
5808
9041
C/C
C/T
T/T
e.g. Bin 1 - SNP 381
Bin 1 - p < 0.001
Bin 2 - p < 0.02 Bin 3 - p < 0.01 Bin 4 - p < Bin 5 - p < 0.001
SNP x SNP interactions - haplotype analysis?

36. VKORC1 Summary: SNP Discovery/SNP Selection
VKORC1 candidate gene for warfarin dose response
SNP discovery performed using PCR/resequencing to
catalog common SNPs
28 SNPs found
10 common SNPs
SNP discovery using dbSNP
8/10 dbSNPs confirmed
7 new SNPs added
SNP Selection using linkage disequilibrium
10 common SNPs (> 10% MAF)
5 informative SNPs for genotyping

37. Haplotypes in Genetic Association Studies
Two main approaches with haplotypes:
Haplotypes Pick tagSNPs Genotype samples
Pick tagSNPs Infer haplotypes Test for association

38. Haplotypes in Genetic Association Studies
How can you get haplotypes?
What information do you get from haplotypes?
How do you use haplotypes to find tagSNPs?
How do you use haplotypes to test for
associations?

39. Haplotypes – The Definition
“…a unique combination of genetic markers present
in a chromosome.” pg 57 in Hartl & Clark, 1997

40. Constructing Haplotypes
A G
T T
G G
C C
C/T, A/G
C/C, A/G
T/T, G/G
C/T, A/A
Collect pedigrees
Somatic cell hybrids
Human
Rodent
Hybrid
SNP 1
SNP 2
C/T
A/G
Allele-specific PCR

41. Constructing Haplotypes
Examples of Haplotype Inference Software:
EM Algorithm
Haploview
Arlequin
PHASE v2.1
HAPLOTYPER

42. Haplotypes in SeattleSNPs
>200 genes re-sequenced in inflammation response
2 populations: European- and African-Americans
PHASEv2.0 results posted on website
Interactive tool (VH1) to visualize and sort haplotypes

43. Haplotypes in SeattleSNPs

44. Haplotypes in SeattleSNPs

45. Haplotypes in SeattleSNPs

46. Haplotypes in SeattleSNPs

47. Haplotypes in SeattleSNPs

48. Haplotypes in SeattleSNPs

49. Haplotypes in SeattleSNPs

50. Haplotypes in SeattleSNPs

51. Haplotypes in SeattleSNPs

52. Haplotypes in SeattleSNPs

53. Haplotypes in SeattleSNPs

54. Haplotypes in Genetic Association Studies
Two main approaches with haplotypes:
Haplotypes Pick tagSNPs Genotype samples
Recombination
Natural selection
Population history
Population demography
Haplotype block definition
Pick tagSNPs Infer haplotypes Test for association

55. Measuring Pair-wise SNP Correlations
SNP correlation described by linkage disequilibrium (LD)
Pair-wise measures of LD: D´ and r2
D = pAB - pApB; D´ = D/Dmax Recombination
r2 = D2
f(A1)f(A2)f(B1)f(B2) Power

56. Using LD and Haplotypes to Pick tagSNPs
r2 is inversely related to power
1/r2
1,000 cases 1,250 cases
1,000 controls r2=1.0 1,250 controls r2 = 0.80
D´ is related to recombination history
D´ = 1 no recombination
D´ < 1 historical recombination
Example: LDSelect
Example: Haplotype “blocks”

57. Represent most chromosomes
Haplotype “Blocks”
Daly et al Nat. Genet. (2001)
Daly et al 2001
Strong LD
Few Haplotypes
Represent most chromosomes

58. D´ [Gabriel et al Science (2002)]
Block Definitions
Daly et al Nat. Genet. (2001)
Daly et al 2001
D´ [Gabriel et al Science (2002)]

59. Block Definitions Four-gamete test: <4 haplotypes, D´=1 block
To answer this question, we decided to identify blocks using all common SNPs and coding SNPs. To form blocks, we implemented the four-gamete test in the software by Zhang and Jin known as HaploBlockFinder. In this test, each pair of SNPs is tested for evidence of historical recombination. That is, for two sites, A and B, with two alleles each, if all four haplotypes are present in the population, it is considered evidence of recombination. If less than four haplotypes are present in the population, there is no evidence of recombination. A block is defined as SNPs that do not show evidence of historical recombination, and the boundaries are marked by SNPs that have evidence of recombination. I should note that this method to define blocks is very stringent, and that there are other methods used to define blocks, one of which you will hear more about later this afternoon.
Using the four gamete test to define blocks, we find that for some genes, using coding variation yields similar blocks to using all common variation. However, for most genes, we observed fewer blocks when coding SNPs were used compared with all common SNPs. Overall, fewer blocks were observed as the SNP density decreased.
<4 haplotypes, D´=1 block
4 haplotypes, D´<1 boundary

60. Haplotype Blocks and tagSNPs
Identifying blocks and tagSNPs:
Manually
Algorithms
HaploBlockFinder
Haploview

61. Haplotype Blocks and tagSNPs
IL1B:
19 SNPs (MAF >5%)
4 “common” haplotypes

62. Haplotype Blocks and tagSNPs
Identifying blocks and tagSNPs:
Manually
Algorithms
HaploBlockFinder
HaploView

64. HaploBlockFinder Output
VKORC1
European-Americans

65. HaploBlockFinder Output
Haplotype blocks
LD matrix
VKORC1
European-Americans

67. LD and tagSNPs using Haploview
VKORC1
European-Americans
PHASEv2.1 data

71. Minimal set of tagSNPs based on r2

73. Where to Find Tagging Software
HaploBlockFinder
Haploview
LDSelect
SNPtagger
TagIT
tagSNPs

74. Haplotypes, TagSNPs, and Caveats
Haplotypes are inferred
Block-like structure assumed for some software
Different block definitions
Block boundaries sensitive to marker density
Genotype savings may not be great (recombination)

75. Haplotypes in Genetic Association Studies
Two main approaches with haplotypes:
Haplotypes Pick tagSNPs Genotype samples
Pick tagSNPs Infer haplotypes Test for association
Genetic diversity of sample
Multi-SNP analysis

76. Multi-SNP testing: Haplotypes
Five tagSNPs (10 total SNPs)
186 warfarin patients (European)
PHASE v2.1
9 haplotypes/5 common (>5%)

77. Multi-SNP testing: Haplotypes
Test for association between haplotype and warfarin dose using multiple linear regression
Adjusted for all significant covariates: age, sex, amiodarone, CYP2C9 genotype

78. Multi-SNP testing: Haplotypes
Explore the evolutionary relationship across haplotypes
(381, 3673, 6484, 6853, 7566)
5808
CCGATCTCTG-H1 A
CCGAGCTCTG-H2
861
TCGGTCCGCA-H7
TAGGTCCGCA-H8 B
9041
TACGTTCGCG-H9
VKORC1 haplotypes cluster into divergent clades
Patients can be assigned a clade diplotype:
e.g. Patient 1 - H1/H2 = A/A
Patient 2 - H1/H7 = A/B
Patient 3 - H7/H9 = B/B

79. Independent of INR levels across all groups
VKORC1 clade diplotypes show a strong association with warfarin dose
Low
High
A/A
A/B
B/B * †
All patients
2C9 WT patients
2C9 VAR patients AA AB BB
(n = 181)
(n = 124)
(n = 57)
Independent of INR levels across all groups

80. Multi-SNP testing: Haplotypes
European - mean ~ 5 mg/d
African-American - higher ~ mg/d
Asian - lower ~ mg/d
Hypothesis: VKORC1 haplotypes contribute to racial
variability in warfarin dosing.
“Control” populations: 120 Europeans
96 African-Americans
120 Asian

81. Multi-SNP testing: Haplotypes
Explore the evolutionary relationship across populations
European (CEPH)
Clade Distribution B
(58%) A
(37%)
Asian (Han)
Clade Distribution
Low dose phenotype A
(89%) B
(11%)
African-American
Clade Distribution
High dose phenotype A
(14%) B
(47%)
Other
(39%)
Clade A = Low
Clade B = High

82. Common Errors in Association Studies
Bell and Cardon (2001)
Small sample size
Subgroup analysis and multiple testing
Random error
Poorly matched control group
Failure to attempt study replication
Failure to detect LD with adjacent loci
Overinterpreting results and positive publication bias
Unwarranted ‘candidate gene’ declaration after identifying
association in arbitrary genetic region
e.g., Second case/control study
Gene expression studies

83. SNP Replication: VKORC1
Univ. of Washington
n = 185 * †
All patients
2C9 WT patients
2C9 VAR patients AA AB BB
Washington University
n = 386
Brian Gage
Howard McCleod
Charles Eby
All patients
2C9 WT patients
2C9 VAR patients AA AB BB † *
In a patient population nearly double in size our results were nearly identical. This is done at a completely independent site, different physicians
21% variance in dose explained

84. mechanism SNP Function: VKORC1 Expression No nonsynonymous SNPs
Several SNPs are present in evolutionarily conserved non-coding regions
No nonsynonymous SNPs
- mRNA expression in human liver cell lines

85. SNP Function: VKORC1 Expression
Expression in human liver tissue (n = 53) shows a graded
change in expression.

86. VKORC1 SNP alters liver-specific binding site
Biological plausibility leads us to believe that VKROC1 is the and that it is SNPs within this gene that are leading to expression changes. However we thought it would be interesting to perform a bioinformatic experiment to see how far a SNP association with warfarin dose could extend.

87. SNP Discovery and Analysis Application to Association Studies
Summary
Databases and resources available for SNP discovery
Software for tagSNP selection available
Both single and multi-SNP analysis are useful
Replication required by several journals

88. SeattleSNPs Genotyping Service
Free genotyping (BeadArray or SNPlex)
Emphasis on young investigators
Research related to heart, lung, blood, or sleep disorders
Moderate to large population samples
Apply at pga.gs.washington.edu
Due: May 15th, 2005