# Presentation: 090513

## Genetics for EpidemiologistsLecture 5: Analysis of Genetic Association Studies

- National Human Genome Research Institute

- National  Institutes of Health

- U.S. Department of Health and Human Services

**U.S. Department of Health and Human Services**
**National Institutes of Health**
**National Human Genome Research Institute**

**Teri A. Manolio, M.D., Ph.D.**Director, Office of Population Genomics and
- Senior Advisor to the Director, NHGRI,
- for Population Genomics

## Topics to be Covered

- Discrete traits and quantitative traits
- Measures of association
- Detecting/correcting for false positives
- Genotyping quality control
- Quantile-quantile (Q-Q) plots
- Odds ratios: allelic and genotypic
- Models of genetic transmission
- Interactions: gene-gene, gene-environment

## Larson, G.  The Complete Far Side. 2003.

## Quantitative Genetics

- “...concerned with the inheritance of those differences between individuals that are of degree rather than of kind...”

| Quantitative | Qualitative |
| --- | --- |
|  |  |
|  |  |
|  |  |
|  |  |

- Falconer and Mackay, *Quantitative Genetics *1996.

## Quantitative Genetics

- “...concerned with the inheritance of those differences between individuals that are of degree rather than of kind...”

| Quantitative | Qualitative |
| --- | --- |
| Continuous gradation among individuals from one extreme to other | Sharply demarcated types with little connection by intermediates |
|  |  |
|  |  |
|  |  |

- Falconer and Mackay, *Quantitative Genetics *1996.

## Quantitative Genetics

- “...concerned with the inheritance of those differences between individuals that are of degree rather than of kind...”

| Quantitative | Qualitative |
| --- | --- |
| Continuous gradation among individuals from one extreme to other | Sharply demarcated types with little connection by intermediates |
| Effects of genes are small | Effects of genes are large |
|  |  |
|  |  |

- Falconer and Mackay, *Quantitative Genetics *1996.

## Quantitative Genetics

- “...concerned with the inheritance of those differences between individuals that are of degree rather than of kind...”

| Quantitative | Qualitative |
| --- | --- |
| Continuous gradation among individuals from one extreme to other | Sharply demarcated types with little connection by intermediates |
| Effects of genes are small | Effects of genes are large |
| Usually many genes | Single genes inherited in Mendelian ratios? |
|  |  |

- Falconer and Mackay, *Quantitative Genetics *1996.

## Inheritance Models in Single Gene Trait

## Inheritance Models in Single Gene Trait

|  | Genotype Group |  |  |
| --- | --- | --- | --- |
| Model | AA | Aa | aa |
|  |  |  |  |
|  |  |  |  |
|  |  |  |  |

**Inheritance Models in Single Gene Trait**

## Inheritance Models in Single Gene Trait

|  | Genotype Group |  |  |
| --- | --- | --- | --- |
| Model | AA | Aa | aa |
| A is   Dominant |  |  |  |
|  |  |  |  |
|  |  |  |  |

**Inheritance Models in Single Gene Trait**

## Inheritance Models in Single Gene Trait

|  | Genotype Group |  |  |
| --- | --- | --- | --- |
| Model | AA | Aa | aa |
| A is   Dominant |  |  |  |
|  |  |  |  |
|  |  |  |  |

**Inheritance Models in Single Gene Trait**

## Inheritance Models in Single Gene Trait

|  | Genotype Group |  |  |
| --- | --- | --- | --- |
| Model | AA | Aa | aa |
| A is   Dominant |  |  |  |
| A is Recessive |  |  |  |
|  |  |  |  |

**Inheritance Models in Single Gene Trait**

## Inheritance Models in Single Gene Trait

|  | Genotype Group |  |  |
| --- | --- | --- | --- |
| Model | AA | Aa | aa |
| A is   Dominant |  |  |  |
| A is Recessive |  |  |  |
| A is          Co-Dominant |  |  |  |

**Inheritance Models in Single Gene Trait**

## Inheritance Models in Quantitative Trait

## Inheritance Models in Quantitative Trait

|  |          Population Mean |  |  |
| --- | --- | --- | --- |
| Model | -x |  0 | +x |
|  |  |  |  |
|  |  |  |  |
|  |  |  |  |
|  |  |  |  |
| 
 |  |  |  |

**Inheritance Models in Quantitative Trait**

## Inheritance Models in Quantitative Trait

|  |          Population Mean |  |  |
| --- | --- | --- | --- |
| Model | -x |  0 | +x |
| 
A is Completely  Dominant |  aa |  | AA
Aa |
|  |  |  |  |
|  |  |  |  |
|  |  |  |  |
| 
 |  |  |  |

**Inheritance Models in Quantitative Trait**

## Inheritance Models in Quantitative Trait

|  |          Population Mean |  |  |
| --- | --- | --- | --- |
| Model | -x |  0 | +x |
| 
A is Completely  Dominant |  aa |  | AA
Aa |
|  |  |  |  |
| 
A is Partially Dominant |  aa |           Aa | AA |
|  |  |  |  |
| 
 |  |  |  |

**Inheritance Models in Quantitative Trait**

## Inheritance Models in Quantitative Trait

|  |          Population Mean |  |  |
| --- | --- | --- | --- |
| Model | -x |  0 | +x |
| 
A is Completely  Dominant |  aa |  | AA
Aa |
|  |  |  |  |
| 
A is Partially Dominant |  aa |           Aa | AA |
| 
A is Not (Co-) Dominant |  aa | Aa | AA |
| 
 |  |  |  |

**Inheritance Models in Quantitative Trait**

## Inheritance Models in Quantitative Trait

|  |          Population Mean |  |  |
| --- | --- | --- | --- |
| Model | -x |  0 | +x |
| 
A is Completely  Dominant |  aa |  | AA
Aa |
|  |  |  |  |
| 
A is Partially Dominant |  aa |           Aa | AA |
| 
A is Not (Co-) Dominant |  aa | Aa | AA |
| 
A is Over-Dominant |  aa |  | AA            Aa |

**Inheritance Models in Quantitative Trait**

## Quantitative Traits with Published GWA Studies (16 - 34)

- QT interval
- Lipids and lipoproteins
- Memory
- Nicotine dependence
*ORMDL3* expression
*YKL-40* levels
- Obesity, BMI, waist
- Insulin resistance
- Height

- Bone mineral density
- F-cell distribution
- Fetal hemoglobin levels
- C-Reactive protein
- 18 groups of Framingham traits
- Pigmentation
- Uric Acid Levels
- Recombination Rate

## 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) |  |  |  |  |
| Allelic Odds Ratio = 1.38 |  |  |  |  |  |  |  |
|  |  |  |  |  |  |  |  |
|  |  |  |  |  |  |  |  |
|  |  |  |  |  |  |  |  |
|  |  |  |  |  |  |  |  |
|  |  |  |  |  |  |  |  |

- Samani N et al, *N Engl J Med*  2007; 357:443-453.

## 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) |  |  |  |  |
| Allelic Odds Ratio = 1.38 |  |  |  |  |  |  |  |
|  | CC 
N (%) | CG 
N (%) |  | GG
N (%) |  | 2 (2df)  | P-value |
| Cases | 586 (30.5) |     960 (49.9)  |  | 378 (19.6) |  | 59.7 | 1.1 x 10-14 |
| Controls | 676 (23.0) | 1,431 (48.7) |  | 829 (28.2) |  |  |  |
| Heterozygote Odds Ratio = 1.47 |  |  |  |  |  |  |  |
| Homozygote Odds Ratio = 1.90 |  |  |  |  |  |  |  |

- Samani N et al, *N Engl J Med*  2007; 357:443-453.

## -Log10 P Values for SNP Associations with Myocardial Infarction

**-Log****10**** P Values for SNP Associations with Myocardial Infarction**

- Samani N et al, *N Engl J Med*  2007; 357:443-453.

## Genome-Wide Scan for Type 2 Diabetes in a Scandinavian Cohort 

**Genome-Wide Scan for Type 2 Diabetes in a Scandinavian Cohort **

## GWA Study of Serum Uric Acid Levels

- Linear regression of inverse normalized levels against number of alleles
- Additive model
- Sex, age, age2 as  covariates

**GWA Study of Serum Uric Acid Levels**

- Li S et al, *PLoS Genet* 2007; 3:e194.

## Association of rs6855911 and Uric Acid Levels

- Li S et al, *PLoS Genet* 2007; 3:e194.

|  |  | Genotype Means (mg/dl) |  |  |
| --- | --- | --- | --- | --- |
| Cohort | Additive Effect  | AA | AG | GG |
| SardiNIA | -0.317 | 4.66 (1.51) | 4.48 (1.59) | 4.02 (1.63) |
| InCHIANTI | -0.397 | 5.27 (1.44) | 4.94 (1.31) | 4.33 (1.37) |

## Association Methods for Quantitative Traits

- Linear regression of multivariable adjusted residual against number of alleles (Kathiresan,*Nat Genet* 2008; 40:189-97)
- Linear regression of log transformed or centralized BMI against genotype (Frayling, *Science* 2007; 316:889-94)
- Variance components based Z-score analysis of quantile normalized height (Sanna, *Nat Genet* 2008; 40:198-203)

## Ways of Dealing with Multiple Testing

- Control family wise error rate (FWER): Bonferroni (α’ = α/n) or Sĭdák (α’ = 1- [1- α]1/n)
- False discovery rate: proportion of significant associations that are actually false positives
- False positive report probability: probability that the null hypothesis is true, given a statistically significant finding
- Bayes factors analysis: avoids need for assessing genome-wide error rates but must  identify reasonable alternative model

- Hogart CJ et al, *Genet Epidemiol*  2008; 32:179-85.

## Larson, G.  The Complete Far Side. 2003.

## Quality Control of SNP Genotyping: Samples

- Identity with forensic markers (Identifiler)
- Blind duplicates
- Gender checks
- Cryptic relatedness or unsuspected twinning
- Degradation/fragmentation
- Call rate (> 80-90%)
- Heterozygosity: outliers
- Plate/batch calling effects

- Chanock et al, *Nature* 2007; Manolio et al *Nat Genet* 2007

## Quality Control of SNP Genotyping: SNPs

- Duplicate concordance (CEPH samples)
- Mendelian errors (typically _<_ 1)
- Hardy-Weinberg errors (often > 10-5)
- Heterozygosity (outliers)
- Call rate (typically > 98%)
- Minor allele frequency (often > 1%)
- Validation of most critical results on independent genotyping platform

- Chanock et al, *Nature* 2007; Manolio et al *Nat Genet* 2007

## Hardy-Weinberg Equilibrium

- Occurrence of two alleles of a SNP in the same individual are two *independent* events
- Ideal conditions:
- random mating       -  no selection (equal survival)
- no migration	         -  no mutation
- no inbreeding         -  large population sizes
- gene frequencies equal in males and females)...
- If alleles **A** and **a** of SNP rs1234 have frequencies **p** and **1-p**, expected frequencies of the three genotypes are:

- After G. Thomas, NCI

- Freq AA = p2

- Freq Aa = 2p(1-p)

- Freq aa = (1-p)2

## Coverage, Call Rates, and Concordance of Perlegen and  Affymetrix Platforms on HapMap Phase II

| Metric | Perlegen |  | Affymetrix/Broad |  |
| --- | --- | --- | --- | --- |
| Number of SNPs  | 480,744 |  | 439,249  |  |
| Coverage | Single Marker | Multi-Marker | Single Marker | Multi-Marker |
|    CEU | 0.90 | 0.96 | 0.78 | 0.87 |
|    CHB + JPT | 0.87 | 0.93 | 0.78 | 0.86 |
|    YRI | 0.64 | 0.78 | 0.63 | 0.75 |
| Average call rate | 98.9% |  | 99.3% |  |
| Concordance |  |  |  |  |
|    Homozygous
   genotypes | 99.8% |  | 99.9% |  |
|    Heterozygous 
   genotypes | 99.8% |  | 99.8% |  |

**Coverage, Call Rates, and Concordance of Perlegen and  Affymetrix Platforms on HapMap Phase II**

- GAIN Collaborative Group, *Nat Genet *2007; 39:1045-51.

## Sample and SNP QC Metrics for Affymetrix 5.0 and 6.0 Platforms in GAIN

| Metric | 5.0 | % fail | 6.0 | % fail |
| --- | --- | --- | --- | --- |
| Total Samples | 1,829 | -- | 2,289 | -- |
| Passing QC | 1,817 | 0.44 | 2,192 |  4.24 |
| > 98% call rate | 1,815 | 0.55 | 2,257 | 1.40 |
|  |  |  |  |  |
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**Sample and SNP QC Metrics for Affymetrix 5.0 and 6.0 Platforms in GAIN**

- Courtesy, J Paschall, NCBI

## Sample and SNP QC Metrics for Affymetrix 5.0 and 6.0 Platforms in GAIN

| Metric | 5.0 | % fail | 6.0 | % fail |
| --- | --- | --- | --- | --- |
| Total Samples | 1,829 | -- | 2,289 | -- |
| Passing QC | 1,817 | 0.44 | 2,192 |  4.24 |
| > 98% call rate | 1,815 | 0.55 | 2,257 | 1.40 |
|  |  |  |  |  |
| Total SNPs | 457,645 | -- | 906,660 | -- |
| Passing QC | 429,309 | 6.19 | 845,814 | 6.70 |
| MAF > 1% | 457,466 | 0.04 | 888,234 | 2.03 |
| > 98% call rate  | 419,810 | 8.27 | 821,942 | 9.34 |
| > 95% call rate  | 439,272 | 4.01 | 873,856 | 3.61 |
| HWE < 10 -6 | 455,899 | 0.38 | 904,275 | 0.26 |
| < 1 Mendel error | 417,722 | 8.72 | 899,721 | 0.01 |
| < 1 Duplicate error | 454,820 | 0.01 | 892,103 | 0.02 |

**Sample and SNP QC Metrics for Affymetrix 5.0 and 6.0 Platforms in GAIN**

- Courtesy, J Paschall, NCBI

## Sample Heterozygosity in GAIN

- Courtesy, J Paschall, NCBI

## Sample Heterozygosity in GAIN

- Courtesy, J Paschall, NCBI

**Notes:**
Signal intensity plot and transformed signal intensity plot
Can be dealt with by revised clustering algorithms, genomic control, fuzzy calls

## Signal Intensity Plots for rs10801532 in AREDS

- http://www.ncbi.nlm.nih.gov/sites/entrez

**Notes:**
Signal intensity plot and transformed signal intensity plot
Can be dealt with by revised clustering algorithms, genomic control, fuzzy calls

## Signal Intensity Plots for rs4639796 in AREDS

- http://www.ncbi.nlm.nih.gov/sites/entrez

**Notes:**
Signal intensity plot and transformed signal intensity plot
Can be dealt with by revised clustering algorithms, genomic control, fuzzy calls

## Signal Intensity Plots for rs534399 in AREDS

- http://www.ncbi.nlm.nih.gov/sites/entrez

**Notes:**
Signal intensity plot and transformed signal intensity plot
Can be dealt with by revised clustering algorithms, genomic control, fuzzy calls

## Signal Intensity Plots for rs572515 in AREDS

- http://www.ncbi.nlm.nih.gov/sites/entrez

**Notes:**
Signal intensity plot and transformed signal intensity plot
Can be dealt with by revised clustering algorithms, genomic control, fuzzy calls

## Signal Intensity Plots for CD44 SNP rs9666607

- Clayton DG et al, *Nat Genet*  2005; 37:1243-1246.

**Notes:**
Signal intensity plot and transformed signal intensity plot
Can be dealt with by revised clustering algorithms, genomic control, fuzzy calls

## Principal Component Analysis of Structured Population: First to Third Components 

**Principal Component Analysis of Structured Population: First to Third Components **

## Principal Component Analysis of Structured Population: Fourth and Fifth Components 

**Principal Component Analysis of Structured Population: Fourth and Fifth Components **

## Influence of Relatedness on Principal Component Analysis 

**Influence of Relatedness on Principal Component Analysis **

## Principal Component Analysis of Structured Population: Fourth and Fifth Components 

**Principal Component Analysis of Structured Population: Fourth and Fifth Components **

## Principal Component Analysis of Structured Population: Fourth and Fifth Components 

**Principal Component Analysis of Structured Population: Fourth and Fifth Components **

## Summary Points: Genotyping Quality Control 

- Sample checks for identity, gender error, cryptic relatedness
- Sample handling differences can introduce artifacts but probably can be adjusted for
- Association analysis is often quickest way to find genotyping errors
- Low MAF SNPs are most difficult to call
- Inspection of genotyping cluster plots is crucial!

## Quantile-Quantile Plot for Test Statistics, 

**Quantile-Quantile Plot for Test Statistics, **
**390 Breast Cancer Cases, 364 Controls**

**205,586 SNPs**
**λ**** = 1.03**

## Observed and Expected Associations after Stage 2 of Breast Cancer GWA

**Observed and Expected Associations after Stage 2 of Breast Cancer GWA**

| Significance | Observed |  | Observed Adjusted |  | Expected |  | Ratio |
| --- | --- | --- | --- | --- | --- | --- | --- |
| 0.01 - 0.05 | 1,239 |  | 1,162 |  | 934 |  | 1.24 |
| 10-3 – 10-2 | 574 |  | 517 |  | 348 |  | 1.49 |
| 10-4 – 10-3 | 112 |  | 88 |  | 53 |  | 1.65 |
| 10-5 – 10-4 | 16 |  | 12 |  | 7 |  | 1.71 |
| < 10-5 | 15 |  | 13 |  | 1 |  |    13.5  |
| All p < 0.05 | 1,956 |  | 1,792 |  | 1,343 |  | 1.33 |

## Q-Q Plot for Multiple Sclerosis; Effect of MHC

**Q-Q Plot for Multiple Sclerosis; Effect of MHC**

- Hafler D et al, *N Engl J Med* 2007; 357:851-862.

**Notes:**
All 334,923 SNPs (gray), exclusion of SNPs across extended MHC region (black), excess at < 0.001 (- log 3)

## Q-Q Plot for Prostate Cancer, 

**Q-Q Plot for Prostate Cancer, **
**all SNPs**

- Gudmundsson J et al, *Nat Genet* 2007; 39:977-983.

## Q-Q Plot for Prostate Cancer, 

**Q-Q Plot for Prostate Cancer, **
**excluding Chromosome 8**

- Gudmundsson J et al, *Nat Genet* 2007; 39:977-983.

## Q-Q Plot for Myocardial Infarction

**Q-Q Plot for Myocardial Infarction**

- Samani N et al, *N Engl J Med*  2007; 357:443-453.

- Expected chi-squared statistic

- 0                   5                  10                  15                  20                 25

- Observed chi-squared statistic

- 0                    20                   40                   60

## -Log10 P Values for SNP Associations with Myocardial Infarction

**-Log****10**** P Values for SNP Associations with Myocardial Infarction**

- Samani N et al, *N Engl J Med*  2007; 357:443-453.

## -Log10 P Values for SNP Associations with Myocardial Infarction

**-Log****10**** P Values for SNP Associations with Myocardial Infarction**

- Samani N et al, *N Engl J Med*  2007; 357:443-453.

## SNP Associations with 1,928 MI Cases and 2,938 Controls from UK

**SNP Associations with 1,928 MI Cases and 2,938 Controls from UK**

- Samani N et al, *N Engl J Med*  2007; 357:443-453.

## Association Signal for Coronary Artery Disease on Chromosome 9

**Association Signal for Coronary Artery Disease on Chromosome 9**

**’****3049**

- Samani N et al, *N Engl J Med*  2007; 357:443-453.

## Winner’s Curse: Odds Ratios for CHD Associated with LTA Genotypes in Multiple Studies  

- Clarke et al, *PLoS Genet*  2006; 2:e107.

## Genome-Wide Scan for Alzheimer’s Disease in 861 Cases and 550 Controls

**Genome-Wide Scan for Alzheimer’s Disease in 861 Cases and 550 Controls**

- Reiman E et al, *Neuron* 2007; 54:713-20.

## Genome-Wide Scan for Alzheimer’s Disease in ApoE*e4Carriers

**Genome-Wide Scan for Alzheimer’s Disease in *****ApoE******e4Carriers**

- Reiman E et al, *Neuron* 2007; 54:713-20.

## LOAD Odds Ratios Associated with rs2373115 GG by APOE*e4 Status

| APOE*e4 Group | APOE*e4 
OR [95% CI] | rs2373115
OR [95%CI] |
| --- | --- | --- |
| APOE*e4 - |  | 1.12 [0.82,1.53] |
| APOE*e4 + |  | 2.88 [1.90,4.36] |
| All | 6.07 [4.63-7.95] | 1.34 [1.06,1.70] |

- Reiman et al, *Neuron* 2007; 54:713-720.

## P Values of GWA Scan for Age-Related Macular Degeneration

**P Values of GWA Scan for Age-Related Macular Degeneration**

**Notes:**
How many SNPs were done?

## Odds Ratios and Population Attributable Risks for AMD

**Odds Ratios and Population Attributable Risks for AMD**

| Attribute (SNP)  | rs380390 (C/G)  | rs1329428 (C/T)  |
| --- | --- | --- |
| Risk allele  | C  | C  |
| Allelic association χ2 P value  | 4.1 x 10–8  | 1.4 x 10–6  |
| Odds ratio (dominant) | 4.6 [2.0-11]  | 4.7 [1.0-22] |
| Frequency in HapMap CEU  | 0.70  | 0.82  |
| Population Attributable Risk | 70% [42-84%]  | 80% [0-96%]  |
| Odds ratio (recessive) | 7.4 [2.9-19]  | 6.2 [2.9-13]  |
| Frequency in HapMap CEU  | 0.23  | 0.41  |
| Population Attributable Risk | 46% [31-57%]  | 61% [43-73%]  |

## Risk of Developing AMD by CFH Y402H and Modifiable Risk Factors

- Schaumberg DA et al, *Arch Ophthalmol* 2007; 125:55-62.

| Risk Factor | CFH Y402H Genotype |  |  |
| --- | --- | --- | --- |
|  | YY | YH | HH |
| BMI < 30 kg/m2 | 1.00 | 1.95 
[1.42-2.67] | 3.96 
[2.69-5.82] |
| BMI > 30 kg/m2 | 1.98 
[0.91-4.31] | 2.19 
[1.11-4.30] | 12.28 
[4.88-30.90] |
| Non-smoker | 1.00 | 1.95 
[1.41-2.71] | 4.23 
[2.86-6.27] |
| Current smoker | 2.34 
[1.20-4.55] | 3.20 
[1.85-5.55] | 8.69 
[3.86-19.57] |

## Interaction: Is LIPC Genotype Related to HDL-C?

- TT

- CC

- CT

- Ordovas et al, *Circulation* 2002; 106:2315-2321.

**Interaction: Is *****LIPC***** Genotype Related to HDL-C?**

- TT

- CC

- CT

## Inverse Relation between Endotoxin Exposure and Allergic Sensitization by CD14 Genotype 

- Simpson A et al, *Am J Respir Crit Care Med* 2006;174:386-392.

## Challenges in Studying Gene-Environment Interactions

| Challenge |  | Genes | Environment |
| --- | --- | --- | --- |
| Ease of measure |  | Pretty easy | Often hard  |
| Variability over time |  | Low/none | High |
| Recall bias |  | None | Possible |
| Temporal relation to disease |  | Easy | Hard |

## Larson, G.  The Complete Far Side. 2003.

## Slide 70