Genome-Wide Association Studies

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Genome-Wide Association Studies

• Xiaole Shirley Liu
• Stat 115/215

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Association Studies

• Association between genetic markers and phenotype
• Especially, find disease genes, SNP / haplotype
  markers, for susceptibility prediction and
  diagnosis
• Influences individual decisions on life styles,
  prevention, screening, and treatment

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Mike Snyders iPOP Reveals Diabetes
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Warfarin and CYP2C9 SNPs in Pharmacogenomics

• Warfarin anticoagulant drug CYP2C9 gene
  metabolizes warfarin.
• A patient requiring low dosage warfarin compared
  to normal population, has an odd ratio of 6.21
  for having ? 1 variant allele
• Subgroup of patients who are poor metabolisers of
  warfarin are potentially at higher risk of
  bleeding

Aithal et al., 1999, Lancet.
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Genome-Wide Association Studies

• Two strategies
• Family-based association studies
• Population-based case-control association studies
• Quality Control
• Unusual similarity between individual
• Wrong sex
• Trio has non-Mendelian inheritance
• Genotyping quality

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Quality Control SNP calls
Bad calls!
Good calls!
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Family-based Association StudiesTDT
Transmission Disequilibrium Test

• Look at allele transmission in unrelated families
  and one affected child in each
• Could also compare
• allele frequency
• between affected vs
• unaffected children
• in the same family

Like coin toss
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Case Control Studies

• SNP/haplotype marker frequency in sample of
  affected cases compared to that in age /sex
  /population-matched sample of unaffected controls
• Size matters

Visscher, AJHG 2012
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From Genotyping to Allele Counts
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Test Significant Associations

• Expected
• (24 278) (24 86) / (24 278 86 296)
  49
• (278296) (86296) / (24 278 86 296)
  321
• ?2 27.5, 1df, p
  lt 0.001
• Multiple hypotheses testing?

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GWAS Pvalues
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GWAS Pvalues for Type II Diabetes

• Bonferroni correction most common, typically p lt
  10-7 or 10-8
• Split samples to improve power

McCarthy et al, Nat Rev Genetics, 2008
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Association of Alleles and Genotypes of rs1333049
(3049) with Myocardial Infarction
C N () G N () ?2 (1df) P-value
Cases 2,132 (55.4) 1,716 (44.6) 55.1 1.2 x 10-13
Controls 2,783 (47.4) 3,089 (52.6) 55.1 1.2 x 10-13
Allelic Odds Ratio 1.38 Allelic Odds Ratio 1.38 Allelic Odds Ratio 1.38 Allelic Odds Ratio 1.38 Allelic Odds Ratio 1.38 Allelic Odds Ratio 1.38

• OR 1, no disease association
• OR gt 1, allele increase risk of disease
• OR lt 1, allele decrease risk of disease

Samani N et al, N Engl J Med 2007 357443-453.
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Manolio et al., Clin Invest 2008
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Pitfalls of Association Studies

• Not very predictive

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Pitfalls of Association Studies

• Not very predictive
• Explain little heritability
• Poor reproducibility
• Poor penetrance (fraction of people with the
  marker who show the trait) and expressivity
  (severity of the effect)
• Focus on common variation
• Difficult when several genes affecting a
  quantitative trait
• Many associated variants are not causal
• No available intervention for many disease risks

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Reproducibility of Association Studies

• Most reported associations have not been
  consistently reproduced
• Hirschhorn et al, Genetics in Medicine, 2002,
  review of association studies
• 603 associations of polymorphisms and disease
• 166 studied in at least three populations
• Only 6 seen in gt 75 studies

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Cause for Inconsistency

• What explains the lack of reproducibility?
• False positives
• Multiple hypothesis testing
• Ethnic admixture / stratification
• False negatives
• Lack of power for weak effects
• Population differences
• Variable LD with causal SNP
• Population-specific modifiers

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Population Stratification

• Population stratification
• e.g. some SNP unique to ethnic group
• Need to make sure sample groups match
• Hidden environmental structure
• Two populations have different disease frequency,
  and different allele frequency.
• Association picks up they are different
  populations!

Balding, Nature Reviews Genetics 2010
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Genotyping Principal Components (PCs) Can Model
Population Stratification

• Li et al., Science 2008

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Causes for Inconsistency

• A sizable fraction (but less than half) of
  reported associations are likely correct
• Genetic effects are generally modest
• Beware the winners curse (auction theory)
• In association studies, first positive report is
  equivalent to the winning bid
• Large study sizes are
• needed to detect these
• reliably

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Should we Believe Association Study Results?

• Initial skepticism is warranted
• Replication, especially with low p values, is
  encouraging
• Large sample sizes are crucial
• E.g. PPARg
• Pro12Ala
• Diabetes

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Replication, Replication, Replication

• Meta-analysis of multiple studies to increase
  GWAS power
• Combine data from different platforms / studies
• Impute unmeasured or missing genotypes based on
  LD (e.g. HapMap haplotypes or 1000 Genomes)
• Analyze all studies together to increase GWAS
  power

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Missing Heritability?
Visccher, AJHG 2011
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Detection Power of GWAS
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Acknowledgement

• Tim Niu
• Kenneth Kidd, Judith Kidd and Glenys Thomson
• Joel Hirschhorn
• Greg Gibson Spencer Muse
• Jim Stankovich
• Teri Manolio