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Genetics and Human variation Nick Martin Queensland Institute of Medical Research Boulder workshop: March 4, 2002 TC-1 TC-2 TC-3 TC-4 YEAR LOCATION 1987 1989 1990 1991 Leuven TC-5 TC-6 TC-7 TC-8 TC-9 TC-10 TC-11 1993 1994 1995 1996 1997 1998 1998 TC-12 TC-13 TC-14 TC-15 1999 2000 2001 2002 Leuven Boulder Leuven Boulder Boulder Helsinki Boulder Boulder Boulder Leuven Boulder Boulder Boulder Boulder # FACULTY # STUDENTS 10 11 11 14 Introductory 12 Advanced 24 41 28 49 13 16 10 10 10 12 Introductory 10 Introductory 13 Advanced 49 43 29 49 55 57 55 62 12 Advanced 12 Introductory 18 Advanced Introductory 37 63 65 55 Attendance at twin workshops Frequency of Attendance Faculty Student Total 1 2 4 8 337 127 345 131 3 4 5 6 7 8 9 13 15 16 TOTAL 1 27 1 12 2 3 2 1 4 0 1 0 1 0 1 0 1 0 6 0 32 507 28 13 5 3 4 1 1 1 1 6 539 People and Ideas Galton (1865-ish) Mendel Correlation Family Resemblance Twins Ancestral Heredity Fisher Darwin (1858,1871) (1865) Natural Selection Sexual Selection Evolution Particulate Inheritance Genes: single in gamete double in zygote Segregation ratios Spearman (1918) (1904) Common Factor Analysis Correlation & Mendel Maximum Likelihood ANOVA: partition of variance Wright (1921) Path Analysis Mather (1949) & Thurstone (1930's) Jinks (1971) Multiple Factor Analysis Biometrical Genetics Model Fitting (plants) Joreskog (1960) Jinks & Fulker (1970) Model Fitting applied to humans Segregation Linkage Morton (1974) Population Genetics Rao, Rice, Reich, Cloninger (1970's) Martin & Eaves (1977) Neale (1990) Mx Covariance Structure Analysis LISREL Path Analysis & Family Resemblance Elston etc (19..) Genetic Analysis of Covariance Structure Watson & Crick (1953) 2000 Assortment Cultural Inheritance Molecular Genetics 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. Individual differences Physical attributes (height, eye color) Disease susceptibility (asthma, anxiety) Behavior (intelligence, personality) Life outcomes (income, children) Stature in adolescent twins Women 700 600 500 400 300 200 Std. Dev = 6.40 100 Mean = 169.1 N = 1785.00 0 145.0 155.0 150.0 Stature 165.0 160.0 175.0 170.0 185.0 180.0 190.0 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” Central Limit Theorem The normal distribution is to be expected whenever variation is produced by the addition of a large number of effects, nonpredominant This plausibly holds quite often Polygenic Traits 1 Gene 2 Genes 3 Genes 4 Genes 3 Genotypes 3 Phenotypes 9 Genotypes 5 Phenotypes 27 Genotypes 7 Phenotypes 81 Genotypes 9 Phenotypes 3 3 2 2 1 1 0 0 7 6 5 4 3 2 1 0 20 15 10 5 0 Multifactorial Threshold Model of Disease Single threshold unaffected Disease liability affected Multiple thresholds normal mild mod Disease liability severe Genetic Epidemiology Establishing the role of genes and environment in variation in disease and complex traits Finding those genes Genetically Complex Diseases Imprecise phenotype Phenocopies / sporadic cases Low penetrance Locus heterogeneity/ polygenic effects Complex Trait Model Linkage Marker Gene1 Linkage disequilibrium Linkage Association Mode of inheritance Gene2 Disease Phenotype Individual environment Common environment Gene3 Polygenic background 3 Stages of Genetic Mapping Are there genes influencing this trait? Where are those genes? Genetic epidemiological studies Linkage analysis What are those genes? Association analysis 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 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) 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 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 MZ concordance for human conditions Asthma 45% Eczema 84% Diabetes (type I) 56% Schizophrenia 50% Cleft lip/palate 30% Club foot 23% Homosexuality (M) 18% Homosexuality (F) 23% 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 MZ twins reared apart - note the same way of supporting their cans of beer Body postures of MZ twins reared apart Body postures of DZ twins reared apart 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 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 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 Placentation and zygosity Dichorionic Two placentas Dichorionic Fused placentas Monochorionic Diamniotic Monochorionic Monoamniotic MZ 19% DZ 58% MZ 14% DZ 42% MZ 63% DZ 0% MZ 4% DZ 0% Identity at marker loci except for rare mutation MZ and DZ twins: determining zygosity using ABI Profiler™ genotyping (9 STR markers + sex) MZ DZ DZ Twin studies that changed the world Multiple sclerosis Autism ADHD Schizophrenia Total mole count for MZ and DZ twins DZ twins - 199 pairs, r = 0.60 400 400 300 300 Twin 1 Twin 1 MZ twins - 153 pairs, r = 0.94 200 200 100 100 0 0 0 100 200 300 Twin 2 400 0 100 200 300 Twin 2 400 Decomposing variance E Covariance A C 0 Adoptive Siblings 0.5 DZ 1 MZ 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) Variance components Unique Environment Shared Environment Additive Genetic Effects C A E c Dominance Genetic Effects D a e d Phenotype P = eE + aA + cC + dD ACE Model for twin data 1 MZ=1.0 / DZ=0.5 E C e c PT1 A a A C a c PT2 E e Fit of ACE model to mole count A = 64%, C = 30%, E = 6% drop A, Χ21= 124.0 (P < .001) drop C, Χ21 = 13.2 (P < .001) therefore can’t drop A or C and can’t drop E ! 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 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) E G VAR 1 G VAR 2 E G VAR 3 E G E Sources of variation in male sexual orientation EC AC Homosexuality Orientation of sexual feelings AF EF Attitude to sex with a man Number of same-sex partners AA AP EA EP Direction of causation modeling with cross-sectional twin data Model Full Bivariate Reciprocal Distress Parenting Parenting Distress No causation Final c2 145.66 146.00 161.74 146.71 376.29 151.26 A AIC -69.34 .34 -70.00 16.08 -56.26 1.05 -71.29 230.63 156.29 5.60 -80.74 A E .45 .38 DISTRESS .63 C .55 .56 ANX E .20 .25 PARENTING + .18 .49 .67 DEP C Dc2 df 107 108 109 109 110 116 SOM COLD E A E A E .36 .13 .21 .11 .40 C .52 .16 OVERP E .17 .26 A C E .21 .14 .49 AUTON C E .11 .37 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 cm cm cf Gendercommon Additive Genes mf mm Malespecific Additive Genes Female Unique Environment Malespecific Additive Genes cm 0.5 0.5 ef Female Twin Environment 0.5 hfc em sf tm Male parent Environment wmm dm wff Female Dominant Genes Gendercommon Additive Genes hfc Male Dominant Genes Female Unique Environment Malespecific Additive Genes Malespecific Additive Genes Male Unique Environment hmm ef rt tf Female Twin Male Twin Environment Environment Female twin hmc tm Male twin sf df em Gendercommon Additive Genes sm Female Sibling Environment rs Female Dominant Genes rd Male Sibling Environment Male Dominant Genes dm Extended kinship model • twins sm Male Sibling wfm wmf df Male Twin Environment hmc Female parent 0.5 0.5 0.5 tf Female Sibling Environment 0.5 hmm 0.5 Gendercommon Additive Genes Male Unique Environment • siblings • parents • children • grandparents • aunts, uncles • cousins 3 Stages of Genetic Mapping Are there genes influencing this trait? Where are those genes? Epidemiological studies Linkage analysis What are those genes? Association analysis Linkage analysis Linkage = Co-segregation A3A4 A1A2 A1A3 A1A2 A1A4 A2A4 A3A4 A2A3 A3A2 Marker allele A1 cosegregates with dominant disease 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 rMZ = rDZ = 1 rMZ = 1, rDZ = 0.5 E e E ^ rMZ = 1, rDZ = C c C A a Twin 1 mole count A Q Q q q a Twin 2 mole count c e Flat mole count - genome scan in 274 twin families 3 Stages of Genetic Mapping Are there genes influencing this trait? Where are those genes? Epidemiological studies Linkage analysis What are those genes? Association analysis Association Analysis Sharing between unrelated individuals Trait alleles originate in common ancestor High resolution Powerful if assumptions are met Recombination since common ancestor Large number of independent tests Same disease haplotype shared by many patients Sensitive to population structure First (unequivocal) positional cloning of a complex disease QTL ! but can we find the God gene? Time will tell….