Statistical Issues in Human Genetics

1. Statistical Issuesin Human Genetics Jonathan L. Haines Ph.D. Center for Human Genetics Research Vanderbilt University Medical Center

2. Complex Disease COMMON COMPLEX DISEASE Environment Genes

3. Complex Disease COMMON COMPLEX DISEASE Environment Genes

4. What Can The Genes Tell Us? • Give us a better understanding of the underlying biology of the trait in question • Serve as direct targets for better treatments • Pharmacogenetics • Interventions • Give us better predictions of who might develop disease • Give us better predictions of the course of the disease • Lead to knowledge that can help find a cure or prevention

5. Watson and Crick started it all in 1953 with the description of DNA • 53 Year Anniversary of the paper will be in April. • Both Won Nobel Prize

7. The DNA Between Individuals is Identical. All differences are in the 0.1% of DNA that varies. A C C G T C C A G G A C C G T G C A G G It’s hard to believe sometimes!

8. HUMAN CHROMOSOMES

9. Single-Nucleotide Polymorphisms (SNPs)One of the most common types of variation GATCCTGTAGCT < Normal 1st Chromosome GATCCTCTAGCT < Disease 2nd Chromosome G/C Affected Normal GATCCTGTAGCT GATCCTCTAGCT GATCCTGTAGCT GATCCTCTAGCT Extremely frequent across the genome (~1/400 bp) -> high resolution Easy to genotype -> high-throughput techniques

10. What are We Looking For? Earth City Street Address Human Genome Chromosome Gene (DNA) Band

11. 640 cubic yards 3,000 MB 1/100 cubic inch 1 x 10-6 MB It really is like finding a needle in a haystack! (and a very BIG haystack, at that)

12. The Genome Sequence is not THE answer!

13. Disease Gene Discovery In Complex Disease 1. Define Phenotype a. Consistency b. Accuracy 2. Define the Genetic Component a. Twin Studies b. Adoption Studies c. Family Studies d. Heritability e. Segregation Analysis 3. Define Experimental Design 4. Ascertain Families a. Case-Control b. Singleton c. Sib Pairs d. Affected Relative Pairs 5. Collect Data a. Family Histories b. Clinical Results c. Risk Factors d. DNA Samples 6. Perform Genotype Generation a. Genomic Screen b. Candidate Gene 7. Analyze data c. Association studies case-control, family-based b. Model-independent sib-pair, relative pair a. Model-dependent Lod score 8. Identify, Test, and Localize Regions of Interest 9. Bioinformatics and Gene Identification 10. Identify Susceptibility Variation(s) 11. Define Interactions a. Gene-Gene b. Gene-Environment

14. CLASSES OF HUMANGENETIC DISEASE • Diseases of Simple Genetic Architecture • Can tell how trait is passed in a family: follows a recognizable pattern • One gene per family • Often called Mendelian disease • Usually quite rare in population • “Causative” gene • Diseases of Complex Genetic Architecture • No clear pattern of inheritance • Moderate to strong evidence of being inherited • Common in population: cancer, heart disease, dementia etc. • Involves many genes or genes and environment • “Susceptibility” genes

15. CLASSES OF HUMANGENETIC DISEASE • Diseases of Simple Genetic Architecture • Can tell how trait is passed in a family: follows a recognizable pattern • One gene per family • Often called Mendelian disease • Usually quite rare in population • “Causative” gene • Diseases of Complex Genetic Architecture • No clear pattern of inheritance • Moderate to strong evidence of being inherited • Common in population: cancer, heart disease, dementia etc. • Involves many genes or genes and environment • “Susceptibility” genes

16. Modes of Inheritance • Autosomal Dominant • Huntington disease • Autosomal Recessive • Cystic fibrosis • X-linked • Duchenne muscular dystrophy • Mitochondrial • Leber Optic atrophy • Additive • HLA-DR in multiple sclerosis • Combinations of the above • RP (39 loci), Nonsyndromic deafness

17. Linkage Analysis • Traces the segregation of the trait through a family • Traces the segregation of the chromosomes through a family • Statistically measures the correlation of the segregation of the trait with the segregation of the chromosome

18. A SAMPLE PEDIGREE The RED chromosome is key

19. Measures of LinkageParametric Vs Non-Parametric • Two major approaches toward linkage analysis • Parametric: Defines a genetic model of the action of the trait locus (loci). This allows more complete use of the available data (inheritance patterns and phenotype information). • The historical approach towards linkage analysis. Development driven by need to map simple Mendelian diseases • Quite powerful when model is correctly defined • Non-Parametric: Uses either a partial genetic model or no genetic model. Relies on estimates of allele/ haplotype/region sharing across relatives. Makes far fewer assumptions about the action of the underlying trait locus(loci).

20. Linkage Analysis • Families • Affected sibpairs • Affected relative pairs • Extended families • Traits • Qualitative (affected or not) • Quantitative (ordinal, continuous) • There are numerous different methods that can be applied • These methods differ dramatically depending on the types of families and traits

21. Recombination: Nature’s way of making new combinations of genetic variants A. B. C. D. A. A diploid cell. B. DNA replication and pairing of homologous chromosomes to form bivalent. C. Chiasma are formed between the chromatids of homologous chromosomes D. Recombination is complete by the end of prophase I.

22. Linkage Analysis in Humans • Measure the rate of recombination between two or more loci on a chromosome • Can be done with any loci, but primary application is to find the location of a trait variant by measuring linkage to known marker variants.

23. LOD Score Analysis The likelihood ratio as defined by Morton (1955): L(pedigree| = x) L(pedigree |  = 0.50) where  represents the recombination fraction and where 0 x  0.49. When all meioses are “scorable”, the LR is constructed as: L.R. = : z() is the lod score at a particular value of the recombination fraction : z() is the maximum lod score, which occurs at the MLE of the recombination fraction  The LOD score (z) is the log10 (L.R.)

24. CLASSES OF HUMANGENETIC DISEASE • Diseases of Simple Genetic Architecture • Can tell how trait is passed in a family: follows a recognizable pattern • One gene per family • Often called Mendelian disease • Usually quite rare in population • “Causative” gene • Diseases of Complex Genetic Architecture • No clear pattern of inheritance • Moderate to strong evidence of being inherited • Common in population: cancer, heart disease, dementia etc. • Involves many genes or genes and environment • “Susceptibility” genes

25. Study Designs Linkage Analysis Large Families Small Families Association Studies Family-Based Case-Control

26. Linkage vs. Association Linkage Association Shared within Families Shared across Families

27. TESTING CANDIDATE GENES Disease Normal 5/20 5/20 Gene is not important

28. TESTING CANDIDATE GENES Disease Normal 10/20 5/20 Gene may be important

29. Case-Control Advantages Power Ascertainment Disadvantages Sensitivity to assumptions Matching Family-Based Parent-child Trio Discordant sibpairs Advantages Use existing samples Robustness to assumptions Disadvantages Ascertainment Power Two Basic Study Designsfor Association Analysis

30. Parent-Child AFBAC TDT HHRR QTDT Sibpair S-TDT DAT Sibship SDT WSDT FBAT Pedigree Transmit PDT FBAT METHODS FOR FAMILY-BASED ASSOCIATION STUDIES

31. TRANSMISSION DISEQUILIBRIUM TEST (TDT) • Examines transmission of alleles to affected individuals • Requires: • Linkage (transmission through meioses); and • Association (specific alleles) • Test of linkage if association assumed • Test of association if linkage assumed • Test of linkage AND association if neither assumed • Uses the non-transmitted alleles, effectively, as the control group. Can make “pseudocontrol” by creating genotype of the two non-transmitted alleles • Requires phenotype only for the child

32. 1 2 (B-C)2 TDT= (B+C) TDT calculation Transmitted 2 1 12 12 Non-Transmitted 11 With > 5 per cell, this follows a 2 distribution with 1 df

33. TDT 12 12 Transmitted 1 2 Not transmitted 1 0 0 2 2 0 11

34. TDT 22 12 Transmitted 1 2 Not transmitted 1 0 0 2 1 1 12

35. TDT 22 11 Transmitted 1 2 Not transmitted 1 1 0 2 0 1 12

36. 1 1 2 2 (B-C)2 TDT= (B+C) TDT Example Transmitted Transmitted 2 2 1 1 Non-Transmitted Non-Transmitted (42-25)2 = 4.31 TDT= (42+25)

37. Case-Control Advantages Power Ascertainment Disadvantages Sensitivity to assumptions Matching Family-Based Parent-child Trio Discordant sibpairs Advantages Use existing samples Robustness to assumptions Disadvantages Ascertainment Power Two Basic Study Designsfor Association Analysis

38. Analysis of Case-Control Data • Standard epidemiological approaches can be used • Qualitative trait • Logistic regression • Quantitative trait • Linear regression • The usual concerns about matching but must also worry about false-positives from population substructure

39. Incorporating Geneticsinto Your Studies • Obtain appropriate IRB approval • DNA studies are quite common • Template language exists for IRB approval and consent forms • Genetic Studies Ascertainment Core (GSAC) can help • Kelly Taylor: ktaylor@chgr.mc.vanderbilt.edu • Collect family history information • Obtain DNA sample • Venipuncture • Buccal wash/swab • Finger stick • Extract/Store DNA • DNA Resources Core can help • Cara Sutcliffe: cara@chgr.mc.vanderbilt.edu • http://chgr.mc.vanderbilt.edu/

40. What Can The Genes Tell Us? • Give us a better understanding of the underlying biology of the trait in question • Serve as direct targets for better treatments • Pharmacogenetics • Interventions • Give us better predictions of who might develop disease • Give us better predictions of the course of the disease • Lead to knowledge that can help find a cure or prevention