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

2. COMMON COMPLEX DISEASE Complex Disease Environmen t Genes

3. COMMON COMPLEX DISEASE Complex Disease Environmen t 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. ACCGTCCAGGACCGTCCAGG ACCGTGCAGGACCGTGCAGG It’s hard to believe sometimes!

8. HUMAN CHROMOSOMES

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

10. What are We Looking For? Human Genome Chromosome Gene (DNA) EarthCityStreetAddress Band

11. 640 cubic yards 1/100 cubic inch 3,000 MB 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. 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 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 7. Analyze data a. Model-dependent Lod score b. Model-independent sib-pair, relative pair c. Association studies case-control, family-based Disease Gene Discovery In Complex Disease

14. CLASSES OF HUMAN GENETIC 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 HUMAN GENETIC DISEASE

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 Linkage Parametric 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. = The LOD score (z) is the log 10 (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 

24. CLASSES OF HUMAN GENETIC DISEASE

25. Large FamiliesSmall Families Linkage Analysis Association Studies Family-BasedCase-Control Study Designs

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

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

28. TESTING CANDIDATE GENES DiseaseNormal 10/205/20 Gene may be important

29. Two Basic Study Designs for Association Analysis 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

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

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

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

34. 2212 TDT Transmitted 1 2 Not transmitted 1 0 0 2 1 1

35. 2211 12 TDT Transmitted 1 2 Not transmitted 1 1 0 2 0 1

36. TDT Example AB CD Transmitted Non-Transmitted 1 2 2 1 (B-C) 2 TDT= (B+C) 2542 2542 Transmitted Non-Transmitted 1 2 2 1 (42-25) 2 TDT= (42+25) = 4.31

37. Two Basic Study Designs for Association Analysis Case-Control Advantages –Power –Ascertainment Disadvantages –Sensitivity to assumptions –Matching

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 Genetics into 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