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Topic #10 Genomewide Association Studies

Topic #10 Genomewide Association Studies. University of Wisconsin Genetic Analysis Workshop June 2011. Outline. Record of genetic research on complex phenotypes prior to GWAS Record of GWAS findings MCTFR GWAS design and initial results. Mapping the Genetic Basis of Human Disease.

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Topic #10 Genomewide Association Studies

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  1. Topic #10Genomewide Association Studies University of Wisconsin Genetic Analysis Workshop June 2011

  2. Outline • Record of genetic research on complex phenotypes prior to GWAS • Record of GWAS findings • MCTFR GWAS design and initial results

  3. Mapping the Genetic Basis of Human Disease Glazier, A.M. et al. (2002). Science, 298: 2345-2349.

  4. Frequency (%) of the DRD2 A1 Allele in Alcoholics and Controls • OR = 8.73 (8.17, 9.29) Blum, K. et al. (1990). JAMA, 263: 2055-2060

  5. “We therefore conclude that no physiologically significant associationbetween the A1 allele of DRD2 and alcoholism has been proved.” • Gelernter, J. et al. (1993). JAMA, 269: 1677

  6. Cumulative Odds Ratio as a Function of Publication Year Original OR=8.7 Smith et al. (2008) American Journal of Epidemiology, 167(2): 125-138.

  7. Cumulative Odds Ratio as a Function of Publication Year Original OR=8.7 Pooled 1st & 2nd OR= 3.9 Smith et al. (2008) American Journal of Epidemiology, 167(2): 125-138.

  8. Cumulative Odds Ratio as a Function of Publication Year Original OR=8.7 Smith et al. (2008) American Journal of Epidemiology, 167(2): 125-138.

  9. Winner’s Curse Cumulative Odds Ratio as a Function of Publication Year Original OR=8.7 Final OR=1.4 Smith et al. (2008) American Journal of Epidemiology, 167(2): 125-138.

  10. Initial Findings are Problematic Ioannidis, J. P. A., et al. (2001). Replication validity of genetic association studies. Nature Genetics, 29(3), 306-309.

  11. Positional Cloning Strategy Collins F.S. (1992) Nature Genetics 1:3-6

  12. Narrowing to Positional Candidates Owen, M.J. et al. (2005). Trends in Genetics, 21: 518-525

  13. Choosing Candidates

  14. Methodological Strengths • Large sample: ~2000 SZ and 2000 controls • Strong candidates: 14 candidate genes • Strong genetic approach: Multiple SNP variants in each gene • Results Sanders, A.R. et al. (2008). No significant association of 14 candidate genes with Schizophrenia ... American Journal of Psychiatry, 165(4): 497-506.

  15. 4.6% (30/648) were Significant at 5% level 0.5% (3/648) were Significant at 1% level Sanders, A.R. et al. (2008). No significant association of 14 candidate genes with Schizophrenia ... American Journal of Psychiatry, 165(4): 497-506.

  16. Why did Sanders et al. fail? • They followed leads from previous studies and most such leads are false positives • Low power in sample of ~2000 cases and 2000 controls to detect modest size effects • They focused on common variantseffectively excluding rare variants

  17. Allele-specific Odds Ratios (ORs) for Polymorphisms Significantly Associated in Meta-Analyses of Alzheimer’s Disease APOE Polymorphism

  18. www.szgene.org

  19. Outline • Record of genetic research on complex phenotypes prior to GWAS • Record of GWAS findings • MCTFR GWAS design and initial results

  20. Lessons From Height • Twin studies  high heritability (~ 80-90%) • Genes (mendelian) causing extreme stature are known • Genes (polygenic) causing normal height variation not known

  21. Lessons From Height “Despite high heritability estimates … the results have been disappointing and inconsistent, with reports of quantitative trait loci (QTLs) scattered across the genome and rarely replicated.” Perola, M. et al. (2007). PLOS Genetics, 3(6): 1019.

  22. Lessons From Height “In the past 18 months, the first robust common variant associations were identified and there are now 44 loci known to influence normal variation in height.” Weedon, M.W. & Frayling, T.M. (2008). Trends in Genetics, 24: 595-603.

  23. Genome-Wide Association Study (GWAS):Illumina 1M DNA Analysis BeadChip

  24. Replicated GWAS for Height (Total N > 160,000)

  25. Average Effect of Replicated Genetic Variant = ~0.3-0.4cm

  26. % Height Variance Accounted For Goldstein, D.B. (2009). Common genetic variation and human traits. NEJM, 360: 1696-1698

  27. MAF & OR of GWAS Associations Median = 1.33 Hindorff, L. A. et al. (2009). Potential etiologic and functional implications of genome-wide association loci for human diseases and traits. Proceedings of the National Academy of Sciences of the United States of America, 106(23), 9362-9367.

  28. GWAS is Successful 18 loci in sample of 249,796 account for 1.5% of variance in BMI 180 loci in sample of 183,727 account for ~10% of variance in height 42 loci in sample of 87,802 account for 3.6-6.1% of variance in age at menarche

  29. GWAS of Behavioral Traits As of 1.04.2010 at: http://www.genome.gov/GWAStudies

  30. Design: • ~3300 Sz and 3600 Controls • 1M SNP markers • Results: • Most highly associated SNP had p = 3.4 x 10-7 • Second most highly associated SNP in MHC region

  31. Score Analyses • Split males and females • Take SNPs significant in one sex at P < .50 • Create an aggregate score of ~35,000 SNPs • Apply score to other sex

  32. Results • In aggregrate, score accounts for: • ~ 2-3% for SZ in EA • ~ 2% for BP • ~ 1% for SZ in AA • Common variants may account for ~35%

  33. Maher, B. (2008). Personal genomes: The case of the missing heritability. Nature, 456(7218), 18-21.

  34. Manolio, T. A., Collins, F. S., Cox, N. J., Goldstein, D. B., Hindorff, L. A., Hunter, D. J., et al. (2009). Finding the missing heritability of complex diseases. Nature, 461(7265), 747-753.

  35. Why did Sanders et al. fail? • They followed leads from previous studies and most such leads are false positives • Low power in sample of ~2000 cases and 2000 controls to detect modest size effects • They focused on common variantseffectively excluding rare variants

  36. Rare Variants in Breast Cancer McClellan, J., & King, M. C. (2010). Genetic Heterogeneity in Human Disease. Cell, 141(2), 210-217.

  37. Outline • Record of genetic research on complex phenotypes prior to GWAS • Record of GWAS findings • MCTFR GWAS design and initial results

  38. Minnesota Sample (Genotyped on Illumina 660W, ~ 530K Markers) Mother Father Offspring #1 Offspring #2

  39. Assessments MTFS Younger Cohort 11 14 17 20 24 29 . . . Parents Older Cohort 17 20 24 29 . . . Parents SIBS* 15 18 22 . . . Parents * SIBS Ages are averages

  40. Assessments MTFS Major Domains • Mental Health • Substance Abuse • Personality • Cognitive Ability • Anthropometric • Environment • EEG, ERP & GSR Younger Cohort 11 14 17 20 24 29 . . . Parents Older Cohort 17 20 24 29 . . . Parents SIBS* 15 18 22 . . . Parents * SIBS Ages are averages

  41. GEDI Phenotypic Approach Externalizing Psychopathology .78 .47 .58 .63 .71 Adult Antisocial Conduct Disorder Alcohol Drug (Low) Constraint Krueger et al.(2002). Journal of Abnormal Psychology, 111: 411-424

  42. GEDI Phenotypic Approach Externalizing Psychopathology General Genetic Contributions Adult Antisocial Conduct Disorder Alcohol Drug (Low) Constraint Specific Genetic Contributions

  43. Phenotypic Approach: Hierarchical Phenotype Hicks et al. (2011). Psychometric and Genetic Architecture of Substance Use Disorder and Behavioral Disinhibition Measures for Gene Association Studies. Behavior Genetics, in press.

  44. Phenotypic Approach Hicks et al. (2011). Psychometric and Genetic Architecture of Substance Use Disorder and Behavioral Disinhibition Measures for Gene Association Studies. Behavior Genetics, in press.

  45. Phenotypic Approach Hicks et al. (2011). Psychometric and Genetic Architecture of Substance Use Disorder and Behavioral Disinhibition Measures for Gene Association Studies. Behavior Genetics, in press.

  46. Initial Univariate Analysis • Dependent Variables: 5 component phenotypes • Independent Variables: # minor alleles for ~ 530K markers • Covariates: • Age Age x Generation • Sex Sex x Generation • Birth Year Birth Year x Generation • Generation 10 EIGENSTRAT PCs • Method: RFGLS (Li et al., 2011)

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