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Genetic research designs in the real world Vishwajit L Nimgaonkar MD, PhD University of Pittsburgh [email protected] Complex disorders: models of causation Genetic factors: Several genes induce cumulative, small but discrete effects + Environmental factors: etiological role / increased variability -No Etiological Factor Necessary or Sufficient -Formal proof dependent on statistical analyses Factors influencing mapping efforts • What is the phenotype? • What polymorphisms are being used? • What is the study design? Key phenotype issues • Is the phenotype heritable? – Proportion of risk due to genetic factors? – Proportion of risk due to an individual gene (# genes?) • Familial aggregation does not necessarily prove genetic etiology • Can the phenotype be evaluated reliably? What is the phenotype? Discrete Continuous (disease) (liability) 0 1 t (L Almasy, PhD) Phenotypes • Qualitative (diagnostic status) – Clinically relevant – Difficulties in delineating ‘genetic’ phenotype • Quantitative (‘endophenotype’) – Heritable – Differences between cases and controls – Differences between unaffected relatives & controls – Plausible role in pathogenesis, proximate to Dx What polymorphisms? • Single nucleotide polymorphisms: SNPs • Repeat polymorphisms • Insertions / deletions What is the study design? Gene mapping studies: concepts • Examine correlation between genetic variation and trait of interest • Significant correlation establishes genetic etiology Human genome: 3 billion base pairs (estimated variations = 8,000,000 – 10,000,000) Problems 1. All genetic variations unknown 2. All variants can not be evaluated Recombination Gene mapping concepts control Marker A1 Marker B1 case Marker A2 *Mutation* Marker B2 Haplotype 1 Recombination based gene mapping Ill Individual Transmission Of Disease Gene Generations: 1 2 3 n Healthy Individual Transmission Of Normal Gene Linkage / Association generations founder Linkage Association What is the study design? POSITIONAL CLONING Step 1: Identify large shared chromosomal segments among cases within families (LINKAGE) Step 2: Narrow the shared region using cases and controls (ASSOCIATION). Linkage: haplotype sharing Related issues • Ascertainment and recruitment! • Power: more is better! ‘much, much more’ preferred • Design modification – Two stage design (accept lower lod cutoffs) – Covariate based analyses Linkage: affected sib-pairs (identity by descent) A,B C,D Alleles shared 0 IBD: Prevalence: 0.25 A,B A,C 1 0.50 A,B A,B 2 0.25 ASP analysis • Convenient design • Concerns – Truncation of family size due to morbidity – ‘True’ sibling recurrence risk – Uncertain paternity – Twinning • Power: n = 400 ASPs; power > 80% for λs = 3.0 (LOD = 3) Quantitative trait mapping • Quantitative trait analyses – Standard variance component analyses – Multipoint analyses – Sequential search strategies – Epistasis – Multivariate analyses – Bivariate analyses with diagnosis + trait Sample size required for 80% power to detect linkage to a QTL at a LOD of 3 (Almasy et al.) Number of Individuals 100,000 Pedigree Sibship (2) Sibship (4) 10,000 1,000 100 0 0.1 0.2 0.3 Heritability due to QTL 0.4 0.5 Associations at the population-level Ill Individual Transmission Of Disease Gene Generations: 1 2 3 n Healthy Individual Transmission Of Normal Gene Factors influencing associations • • • • • • Sample selection & size Population history (fitness, drift, migration) Features of mutations (no, age, frequency) Features of markers (informativeness, LD) Number of comparisons Ethnic admixture Family based associations (haplotype relative risk) A, B C, D A, C B, D Hypothetical control Transmission Disequilibrium Test (TDT) A1, A1 A2, A2 A1, A2 A3, A4 A2, A1 A4, A3 A1, A2 A1, A3 A1, A4 Reject Accept Accept Family based associations • • • • Recruitment expensive Ascertainment may be biased Easier than multiplex pedigrees Power: Issues – Uncertain paternity – Genotyping errors – Power diminishes for case-parent duos ‘Novel’ designs • Cytogenetic abnormalities • Pooled DNA analyses Thank you!! • Collaborators: – Laura Almasy, PhD – Bernie Devlin, PhD – Rodeny Go, PhD – Ruben Gur, PhD – Raquel Gur, MD, PhD