1. Statistical Analysis of Candidate Gene Association Studies (Categorical Traits) of Biallelic Single Nucleotide Polymorphisms Maani Beigy MD-MPH Student at Tehran University of Medical Sciences

2. Rheumatology Research Center (RRC) Objectives Review of Genetic Studies (Linkage vs. Association) Preliminary analyses of Candidate gene association studies Strategy of Analysis Practical Steps of Analysis

3. Genetic Markers

4. Linkage vs. Association Linkage analyses look for relationship between a marker and disease within a family (could be different marker in each family) Association analyses look for relationship between a marker and disease between families (must be same marker in all families) Rheumatology Research Center (RRC)

5. Strategy 1. Ascertain families with multiple affecteds 2. Linkage analyses to identify chromosomal regions 3. Association analyses to identify specific genes  allele-sharing among affecteds within a family Gene AGene BGene C

7. Allelic Association: Three Common Forms Direct Association Mutant or ‘susceptible’ polymorphism Allele of interest is itself involved in phenotype Indirect Association Allele itself is not involved, but a nearby correlated marker changes phenotype Spurious association Apparent association not related to genetic aetiology (most common outcome…) Rheumatology Research Center (RRC)

8. Current Association Study Challenges Genome-wide screen or candidate gene Genome-wide screen Hypothesis-free High-cost: large genotyping requirements Multiple-testing issues – Possible many false positives, fewer misses Candidate gene Hypothesis-driven Low-cost: small genotyping requirements Multiple-testing less important – Possible many misses, fewer false positives

9. Current Association Study Challenges What constitutes a replication? GOLD Standard for association studies Replicating association results in different laboratories is often seen as most compelling piece of evidence for ‘true’ finding But…. in any sample, we measure Multiple traits Multiple genes Multiple markers in genes and we analyse all this using multiple statistical tests What is a true replication?

10. Association to same trait, but different gene Association to same trait, same gene, different SNPs (or haplotypes) Association to same trait, same gene, same SNP – but in opposite direction (protective  disease) Association to different, but correlated phenotype(s) No association at all Genetic heterogeneity Allelic heterogeneity Allelic heterogeneity/pop differences Phenotypic heterogeneity Sample size too small Replication Outcome Explanation

11. Preliminary Analysis Hardy–Weinberg equilibrium (Shesis) Missing genotype data Linkage Disequilibrium for Haplotypes(Shesis) Population stratification (Ancestry Checking, Ethnicity, family-based enrollment of individual etc.) Case-Control Matching (Gender-Age)

12. Case-Control Matching Rheumatology Research Center (RRC)

13. Case-Control Matching Rheumatology Research Center (RRC)

14. Case-Control Matching Rheumatology Research Center (RRC)

15. Case-Control Matching Rheumatology Research Center (RRC)

16. Case-Control Matching Rheumatology Research Center (RRC)

17. Case-Control Matching Rheumatology Research Center (RRC)

18. Case-Control Matching Rheumatology Research Center (RRC)

19. Case-Control Matching Rheumatology Research Center (RRC)

20. Case-Control Matching Rheumatology Research Center (RRC)

21. Allele based test? – 2 alleles  1 df E(Y) = a + bX X = 0/1 for presence/absence Genotype-based test? – 3 genotypes  2 df E(Y) = a + b 1 A+ b 2 DA = 0/1 additive (hom); W = 0/1 dom (het) Haplotype-based test? – For M markers, 2 M possible haplotypes  2 M -1 df E(Y) = a +  bHH coded for haplotype effects Multilocus test? – Epistasis, G x E interactions, many possibilities Strategy of Analysis

22. Allele-Genotyped Based Test Rheumatology Research Center (RRC)

23. Shesis: Excel Preparation Rheumatology Research Center (RRC)

24. Shesis Rheumatology Research Center (RRC)

25. Shesis Rheumatology Research Center (RRC)

26. Shesis Rheumatology Research Center (RRC)

27. Shesis Rheumatology Research Center (RRC)

28. Shesis Rheumatology Research Center (RRC)

29. Shesis Rheumatology Research Center (RRC)

30. SPSS: Binary Logistic for Genotypes Rheumatology Research Center (RRC)

31. SPSS: Binary Logistic for Genotypes Rheumatology Research Center (RRC)

32. SPSS: Binary Logistic for Genotypes Rheumatology Research Center (RRC)

33. SPSS: Binary Logistic for Genotypes Rheumatology Research Center (RRC)

34. SPSS: Binary Logistic for Genotypes Rheumatology Research Center (RRC)

35. Special Thanks to David Balding Rheumatology Research Center (RRC)

36. Special Thanks to Danielle Dick, Sarah Medland, Ben Neale Rheumatology Research Center (RRC)