1. Design Considerations in Large- Scale Genetic Association Studies Michael Boehnke, Andrew Skol, Laura Scott, Cristen Willer, Gonçalo Abecasis, Anne Jackson, and the FUSION Study Investigators Department of Biostatistics Center for Statistical Genetics University of Michigan

2. Outline Assess the utility of HapMap samples for tagSNP selection in a study of type 2 diabetes in Finnish subjects Discuss the impact of several design factors on cost and efficiency of genome-wide association (GWA) studies

3. FUSION Study: Finland-United States Investigation of NIDDM Genetics National Public Health Institute, Helsinki USC Keck School of Medicine, Los Angeles National Human Genome Research Institute, Bethesda University of Michigan School of Public Health, Ann Arbor University of North Carolina School of Medicine, Chapel Hill

4. Chromosome 14 SNP Selection Used early HapMap (May 2004) to select tagSNPs in 18 Mb linkage interval on chr 14 MAF >.05, Illumina design score >.40 Unselected SNPs had r 2 >.8 with  1 tagSNP Added annotation-based SNPs Double tagged large bins, filled large gaps

5. Chromosome 14 SNP Selection HapMap SNPs in region (MAF >.05)2276 HapMap tagSNPs (r 2 >.8)1132 Annotation-based SNPs28 Double-tag SNPs (large bins)11 Gap-filling SNPs211 Total SNPs attempted1382 Total SNPs genotyped1230 Total SNPs polymorphic and in HWE1192

6. Utility of HapMap for tagSNP Selection for Finnish Subjects Question: How comparable were allele, haplotype frequency and r 2 in HapMap, Finnish data? Compared HapMap data and 1448 Finnish samples from FUSION and Finrisk 2002 studies Poster 1621, Willer et al., Friday 1:30  3:30 pm

7. Allele Frequencies: FUSION vs. HapMap CEU YRI CHB JPT

8. Allele Frequencies: FUSION vs. CEU 7.5% SNP frequencies differ at p <.01 r =.98

9. LD r 2 : FUSION vs. CEU r =.91

10. Haplotype Frequencies: FUSION vs. CEU r =.97

11. Summary: Chromosome 14 SNP Selection CEU excellent basis for tagSNP selection in Finns Strong correlation between allele frequencies, haplotype frequencies, LD in two samples Excess of significant allele and haplotype frequency differences (7% at.01 level), but mostly small Nearly all common haplotypes (frequency >.05) in one sample present in both samples –579/583 from CEU in FUSION –557/563 from FUSION in CEU

12. Design of Genome-wide Association Studies GWA provides unprecedented opportunity to identify genetic variants predisposing to disease Enabled by HapMap,  genotyping costs Since we may type 100s-1000s of samples on 100Ks of SNPs, efficient study design critical Examine two-stage designs for large-scale genetic studies (see Satagopan, Elston, Thomas)

13. 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

14. 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

15. Joint Analysis is More Powerful than Replication-Based Analysis Skol et al., Friday 8:45, 180, Hall 3 300,000 markers genotyped on 1000 cases, 1000 controls Multiplicative model, prevalence 10%, GRR = 1.4 One-stage power

16. Factors that Influence Cost and Efficiency of GWAs Fraction samples typed in Stage 1 (  samples ) Fraction SNPs typed in Stage 2 (  markers ) Stage 2 to Stage 1 per genotype cost ratio (R)

17. For a two-stage GWA study, what is the optimal fraction of samples genotyped in Stage 1 (  samples ) ? Stage 2 per genotype cost R =  Stage 1 per genotype cost Case 1: R = 1 Case 2: R = 1, 2, 5, 10

18. Cost as a Function of Samples Typed in Stage 1 Per Genotype Cost Ratio R=1 Fraction of Markers Followed-up Varies to Ensure Constant Power

19. For a two-stage GWA study, what is the optimal fraction of samples genotyped in Stage 1 (  samples ) ? Stage 2 per genotype cost R =  Stage 1 per genotype cost Case 1: R = 1 Case 2: R = 1, 2, 5, 10

20. Cost as a Function of Samples Typed in Stage 1 Per Genotype Cost Ratio R = 1, 2, 5, 10 Fraction of Markers Followed-up Varies to Ensure Constant Power R=10 R=1 R=5 R=2

21. Summary: Two-Stage GWA Designs Two-stage GWA designs efficient, cost-effective; joint analysis more powerful than replication For equal Stage 1, 2 per genotype costs (R=1), 250K SNPs, genomewide significance  =.05, genotype 20-30% of samples in Stage 1 For R>1, less stringent significance, fewer SNPs, genotype 30-40% SNPs in Stage 1

22. Acknowledgements Chromosome 14: Cristen Willer, Anne Jackson; FUSION, CIDR, and HapMap investigators Two-stage designs: Andrew Skol, Laura Scott, Gonçalo Abecasis Thanks!

24. Excluded slides follow

25. FUSION Chromosome 14 T2D Linkage

26. Power of One- and Two-Stage Designs

27. How does a change in significance level change the optimal proportion of samples in Stage 1 (  samples ) ? Case 1:  =.05/250,000 genomewide significance Case 2:  =10/250,000 less stringent significance Case 2’:  =.05/1,250 candidate gene significance

28. Impact of Significance Level on Optimal Proportion of Samples in Stage 1