1. Genetics and Human variation Nick Martin Queensland Institute of Medical Research Boulder workshop: March 4, 2002

9. Paradigm clash ? Genes which cause X, rather than genes which cause variation in X not necessarily same (e.g. having a nose vs nose size ?) - but often so physiologists, experimental psychologists, sociobiologists vs. Quant Genet, BG, GenEpi see Baker BS, Taylor BJ, Hall JC (2001) Are complex behaviors specified by dedicated regulatory genes ? Cell 105:13-24.

10. Individual differences Physical attributes (height, eye color) Disease susceptibility (asthma, anxiety) Behavior (intelligence, personality) Life outcomes (income, children)

11. Stature in adolescent twins

12. Continuous or Categorical ? Body Mass Index vs “obesity” Blood pressure vs “hypertensive” Bone Mineral Density vs “fracture” Bronchial reactivity vs “asthma” Neuroticism vs “anxious/depressed” Reading ability vs “dyslexic” Externalizing behavior vs “delinquent”

13. Central Limit Theorem The normal distribution is to be expected whenever variation is produced by the addition of a large number of effects, non- predominant This plausibly holds quite often

14. Polygenic Traits 1 Gene  3 Genotypes  3 Phenotypes 2 Genes  9 Genotypes  5 Phenotypes 3 Genes  27 Genotypes  7 Phenotypes 4 Genes  81 Genotypes  9 Phenotypes

15. unaffected affected Disease liability Single threshold severe Disease liability Multiple thresholds mildnormalmod Multifactorial Threshold Model of Disease

16. Genetic Epidemiology Establishing the role of genes and environment in variation in disease and complex traits Finding those genes

17. Genetically Complex Diseases Imprecise phenotype Phenocopies / sporadic cases Low penetrance Locus heterogeneity/ polygenic effects

18. Complex Trait Model Disease Phenotype Common environment MarkerGene 1 Individual environment Polygenic background Gene 2 Gene 3 Linkage disequilibrium Mode of inheritance Linkage Association

19. 3 Stages of Genetic Mapping Are there genes influencing this trait? Genetic epidemiological studies Where are those genes? Linkage analysis What are those genes? Association analysis

20. Sources of variance Additive genetic - A Interaction between alleles at same locus (dominance) or different loci (epistasis) – D Common environmental influences shared by members of the same family – C Non-shared environmental influences unique to the individual – E Measurement error (confounded with E) unless replicate test-retest sample

21. Designs to disentangle G + E Resemblance between relatives caused by: shared Genes (G = A + D) environment Common to family members (C) Differences between relatives caused by: nonshared Genes Unique environment (U or E)

22. Designs to disentangle G + E Family studies – G + C confounded MZ twins alone – G + C confounded MZ twins reared apart – rare, atypical, selective placement ? Adoptions – increasingly rare, atypical, selective placement ? MZ and DZ twins reared together Extended twin design

24. Designs to disentangle G + E Family studies – G + C confounded MZ twins alone – G + C confounded MZ twins reared apart – rare, atypical, selective placement ? Adoptions – increasingly rare, atypical, selective placement ? MZ and DZ twins reared together Extended twin design

26. MZ concordance for human conditions Asthma45% Eczema84% Diabetes (type I)56% Schizophrenia 50% Cleft lip/palate30% Club foot23% Homosexuality (M)18% Homosexuality (F)23%

27. Designs to disentangle G + E Family studies – G + C confounded MZ twins alone – G + C confounded MZ twins reared apart – rare, atypical, selective placement ? Adoptions – increasingly rare, atypical, selective placement ? MZ and DZ twins reared together Extended twin design

28. MZ twins reared apart - note the same way of supporting their cans of beer

29. Body postures of MZ twins reared apart Body postures of DZ twins reared apart

31. Designs to disentangle G + E Family studies – G + C confounded MZ twins alone – G + C confounded MZ twins reared apart – rare, atypical, selective placement ? Adoptions – increasingly rare, atypical, selective placement ? MZ and DZ twins reared together Extended twin design

32. Percentage of adoptees convicted of violent and property offenses by biological parents’ convictions Denmark 14,427 nonfamilial adoptions 1927-47 Court convictions available for biological and adoptive parents Mednick et al (1984) Science 224:891-4

33. Designs to disentangle G + E Family studies – G + C confounded MZ twins alone – G + C confounded MZ twins reared apart – rare, atypical, selective placement ? Adoptions – increasingly rare, atypical, selective placement ? MZ and DZ twins reared together Extended twin design

34. Placentation and zygosity Dichorionic Two placentas MZ 19% DZ 58% Dichorionic Fused placentas MZ 14% DZ 42% Monochorionic Diamniotic MZ 63% DZ 0% Monochorionic Monoamniotic MZ 4% DZ 0%

35. MZ and DZ twins: determining zygosity using ABI Profiler™ genotyping (9 STR markers + sex) MZDZ Identity at marker loci - except for rare mutation

36. Twin studies that changed the world Multiple sclerosis Autism ADHD Schizophrenia

37. Total mole count for MZ and DZ twins 0 100 200 300 400 0100200300400 Twin 2 Twin 1 0 100 200 300 400 0100200300400 Twin 2 Twin 1 MZ twins - 153 pairs, r = 0.94DZ twins - 199 pairs, r = 0.60

38. Decomposing variance 0 Adoptive Siblings 0.51 DZMZ A C E Covariance

39. Path analysis allows us to diagrammatically represent linear models for the relationships between variables easy to derive expectations for the variances and covariances of variables in terms of the parameters of the proposed linear model permits translation into matrix formulation (Mx)

40. Phenotype ECA D Unique Environment Additive Genetic Effects Shared Environment Dominance Genetic Effects e a c d P = eE + aA + cC + dD Variance components

41. ACE Model for twin data P T1 ACE P T2 ACE 1 MZ=1.0 / DZ=0.5 eaceca

42. Fit of ACE model to mole count A = 64%, C = 30%, E = 6% drop A, Χ 2 1 = 124.0 (P <.001) drop C, Χ 2 1 = 13.2 (P <.001) therefore can’t drop A or C and can’t drop E !

43. Structural equation modeling Both continuous and categorical variables Systematic approach to hypothesis testing Tests of significance Can be extended to: More complex questions Multiple variables Other relatives

44. SEM : more complex questions Are the same genes acting in males and females ? (sex limitation) Role of age on (a) mean (b) variance (c) variance components Are G & E equally important in age, country cohorts ? (heterogeneity) Are G & E same in other strata (e.g. married/unmarried) ? ( G x E interaction)

45. VAR 1VAR 2VAR 3 G GGG E E EE

46. ACAC ECEC A EFEF EAEA APAP EPEP 0.30 Homosexuality 0.70 0.94 0.88 0.73 < 0.01 AFAF 0.06 0.080.040.16 0.11 Sources of variation in male sexual orientation Number of same-sex partners Orientation of sexual feelings Attitude to sex with a man

47. +.18 Direction of causation modeling with cross-sectional twin data

48. Designs to disentangle G + E Family studies – G + C confounded MZ twins alone – G + C confounded MZ twins reared apart – rare, atypical, selective placement ? Adoptions – increasingly rare, atypical, selective placement ? MZ and DZ twins reared together Extended twin design

49. Female parentMale parent Gender- common Additive Genes Female Unique Environment Male- specific Additive Genes Female Sibling Environment Gender- common Additive Genes Male Unique Environment Male- specific Additive Genes Male Twin Environment Male Sibling Environment Male Dominant Genes Gender- common Additive Genes Female Unique Environment Male- specific Additive Genes Gender- common Additive Genes Male- specific Additive Genes tftf sfsf dfdf 0.5 tmtm smsm dmdm w mf w ff w mm w fm  0.5 h fc h mc efef emem Female twinMale twin Female Twin Environment Female Sibling Environment Female Dominant Genes Male Twin Environment Male Sibling Environment Male Dominant Genes tftf sfsf dfdf tmtm smsm dmdm rtrt rsrs rdrd h mm efef h fc h mm emem h mc  cf  mf  cm  mm  cm  cm Female Twin Environment Female Dominant Genes Extended kinship model twins siblings parents children grandparents aunts, uncles cousins Male Unique Environment

50. 3 Stages of Genetic Mapping Are there genes influencing this trait? Epidemiological studies Where are those genes? Linkage analysis What are those genes? Association analysis

51. Linkage analysis

52. Linkage = Co-segregation A2A4A2A4 A3A4A3A4 A1A3A1A3 A1A2A1A2 A2A3A2A3 A1A2A1A2 A1A4A1A4 A3A4A3A4 A3A2A3A2 Marker allele A 1 cosegregates with dominant disease

53. Linkage Analysis Sharing between relatives Identifies large regions Include several candidates Complex disease Scans on sets of small families popular No strong assumptions about disease alleles Low power Limited resolution

54. Twin 1 mole count Twin 2 mole count E C A Q Q A C E r MZ = 1, r DZ =  ^ r MZ = 1, r DZ = 0.5 r MZ = r DZ = 1 qq aa c c ee

55. Flat mole count - genome scan in 274 twin families

56. 3 Stages of Genetic Mapping Are there genes influencing this trait? Epidemiological studies Where are those genes? Linkage analysis What are those genes? Association analysis

58. Association Analysis Sharing between unrelated individuals Trait alleles originate in common ancestor High resolution Recombination since common ancestor Large number of independent tests Powerful if assumptions are met Same disease haplotype shared by many patients Sensitive to population structure

61. First (unequivocal) positional cloning of a complex disease QTL !

62. but can we find the God gene? Time will tell….