# Presentation: 174873

## Genome-Wide Association (GWA) 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.Senior Advisor to the Director, NHGRI,
- for Population Genomics
- Director, Office of Population Genomics

## There’s a revolution going on...

- Williard, AM.  *Spirit of ‘76*

## There’s a revolution going on...

- Williard, AM.  *Spirit of ‘76*

- Technologic advances now allow us to measure hundreds of thousands of variable points across human genome
- Relatively low cost
- Relatively little DNA
- Can be applied to unrelated individuals studied over years or decades
- Can identify multitude of subtle genetic effects increasing risk of “complex” disease

## What is a GWA Study?

- Method for interrogating all 10 million variable points across human genome
- Variation inherited in groups, or blocks, so not all 10 million points have to be tested
- Blocks are shorter (so need to test more points) the less closely people are related
- Technology now allows studies in unrelated persons, assuming ~10,000 base pair lengths in common (300,000 - 500,000 markers)

## Mapping the Relationships Among SNPs

**Mapping the Relationships Among SNPs**

## One SNP May Serve as Proxy for Many

**One SNP May Serve as Proxy for Many**

## Progress in Genotyping Technology

**1**

**10**

**10****2**

**10****3**

**10****4**

**10****5**

**10****6**

**Nb of **
**SNPs**

**Cost per genotype (Cents, USD)**

**10**

**1**

**10****2**

**ABI**
**TaqMan**

**ABI**
**SNPlex**

**Illumina**
**Golden Gate**** **

**Illumina**
**Infinium/Sentrix**** **

**Affymetrix**
**100K/500K**** **

**Perlegen **

**Affymetrix**
**MegAllele**** **

**2001**

**2005**

**Affymetrix**
**10K**

**Courtesy S. Chanock, NCI**

## Continued Progress in Genotyping Technology

**Affymetrix**
** ****500K**

**Illumina**
** ****317K**

**Illumina**
** ****550K**

**Illumina**
** ****650Y**

**Continued Progress in Genotyping Technology**

**Courtesy S. Gabriel, Broad/MIT**

**July 2005**

**Oct 2006**

**Cost per person (USD)**

## Intensity Data for Three Combinations of Two Alleles 

**Intensity Data for Three Combinations of Two Alleles **

## GWA Genotyping Data, Chromosome 22, Parkinson’s Study

| Study ID | Case/
Control Status | rs5747620 |  | rs2236639  |  |  |
| --- | --- | --- | --- | --- | --- | --- |
|  |  | Allele 1 | Allele 2 |  | Allele 1 | Allele 2 |
| 14 | Case | T | T |  | G | G |
| 20 | Case | T | C |  | G | G |
| 41 | Case | T | C |  | G | G |
| 412  | Control | T | C |  | G | G |
| 592 | Control | C | C |  | G | G |
| 665 | Control | T | C |  | A | G |

**http://ccr.coriell.org/ninds/**

## Association of rs2236639 Alleles with Development of Parkinson Disease (Made Up!)

|  | Development of Disease |  |  |
| --- | --- | --- | --- |
| Variant Allele (A) | Develop Disease | Do Not Develop          Disease | Total |
| Present | 10 |   70 |      80 |
| Absent | 40 | 880 |    920 |
| Total | 50 | 950 | 1,000 |

| Relative Risk = | Risk in Exposed | = | 10/80 | = | 12.5% | = | 2.9 |
| --- | --- | --- | --- | --- | --- | --- | --- |
|  | Risk in Unexposed |  | 40/920 |  | 4.3% |  |  |

## Measures of Association: The Odds Ratio

- Odds are related to probability: odds = p/(1-p)
- If probability of horse winning race is 50%, odds are 1/1
- If probability of horse winning race is 25%, odds are 1/3 for win or 3 to 1 *against* win
- If probability of exposed person getting disease is 25%, odds = p/(1-p) = 25/75 = 1/3
- When don’t have denominators for risk estimates, can calculate *odds ratio* = cross-product ratio (“ad/bc”); computationally easier
- If disease is rare, odds ratio approximates relative risk but always overestimates effect

## Association of rsxxxx3207 Alleles with Occurrence of Myocardial Infarction

|  | Presence of Disease |  |  |
| --- | --- | --- | --- |
| Variant Allele (G) | Present | Absent | Total |
| Present |    813 | 3,061 | ? |
| Absent |    794 | 3,667 | ? |
| Total | 1,507 | 6,728 | ?? |

| OR = | Odds in Exposed | = | 813 / 3,061 | = | 813 x 3,667 | = | 1.23 |
| --- | --- | --- | --- | --- | --- | --- | --- |
|  | Odds in Unexposed |  | 794 / 3,667 |  | 794 x 3,061 |  |  |

- Helgadottir et al, *Sciencexpress *3 May 2007.

## Association of rsxxxx3207 Alleles with Occurrence of Myocardial Infarction

|  | Presence of Disease |  |  |
| --- | --- | --- | --- |
| Variant Allele (G) | Present | Absent | Total |
| Present |    813 | 3,061 | ? |
| Absent |    794 | 3,667 | ? |
| Total | 1,507 | 6,728 | ?? |

| OR = | Odds in Exposed | = | 813 / 3,061 | = | 813 x 3,667 | = | 1.23 |
| --- | --- | --- | --- | --- | --- | --- | --- |
|  | Odds in Unexposed |  | 794 / 3,667 |  | 794 x 3,061 |  |  |

- Embargoed until May 3, 2007

- Helgadottir et al, *Sciencexpress *3 May 2007.

## This is a tsunami of data...

- Hokusai, K. *The Great Wave*

## This is a tsunami of data...

- Hokusai, K. *The Great Wave*

- New approaches needed for accessing, manipulating, visualizing
- Requires entirely new perspective
- Recognize potential for differences to be observed by chance alone

## A Few Epidemiologic Definitions

| P-Value | Probability of finding result as extreme or more extreme by chance alone (0.0001 or 1 x 10-4) |  |
| --- | --- | --- |
| Type I error (α) | Probability of finding a difference when in fact none exists (also called “spurious association”)  |  |
| Type II error (β) | Probability of failing to find a difference when in fact one does exist |  |
| Power | Probability of finding a difference when one in fact does exist, = 1 - β |  |
| Effect Size | Magnitude of risk associated with variant |  |
| Sample Size  |    P-value
   Effect size |   Allele frequency
  Variability of measure |

## 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?

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

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

## P-values for 8q24 SNPs Most Strongly Associated with Prostate Cancer 

**Haiman et al, *****Nat Genet*****  2007; 39:638-44.**

## P-values for Chromosome 11 SNPs Most Strongly Associated with Diabetes 

**Scott et al, *****Sciencexpress*****  26 April 2007.**

## Of 600 Gene-Disease Associations, Only 6 Significant in > 75% of Identified Studies

| Disease/Trait | Gene | Polymorphism | Frequency |
| --- | --- | --- | --- |
| DVT | F5 | Arg506Gln | 0.015 |
| Graves’ Disease | CTLA4 | Thr17Ala | 0.62 |
| Type 1 DM | INS | 5’ VNTR | 0.67 |
| HIV/AIDS | CCR5 | 32 bp Ins/Del | 0.05-0.07 |
| Alzheimer’s | APOE | Epsilon 2/3/4 | 0.16-0.24 |
| Creutzfeldt-Jakob Disease | PRNP | Met129Val | 0.37 |

**Hirschhorn J et al, *****Genet Med***** 2002; 4:45-61.**

## Aspects of GWA Studies that Make Data Sharing Crucial

- Expensive, generate many “false positives”
- Replication held as *sine qua non *of valid association
- Large sample sizes and multiple studies needed to replicate findings
- Massive data sets, analysis requires huge and specialized effort
- Better analytic methods needed
- Once genome is measured can be related to just about anything

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

## The revolution is here...

- Williard, AM.  *Spirit of ‘76*

## The revolution is here...

- Williard, AM.  *Spirit of ‘76*

- Extensive characterization of individual person’s genome now feasible
- Can be applied to unrelated individuals
- Many existing studies have carefully characterized thousands of persons
- New approaches to manipulating and interpreting data needed
- Responsible and widespread data sharing key to fully exploring GWA datasets
- Collaboration for replication and functional determination is crucial

## Slide 27

## Measures of Public Health Impact: Population Attributable Risk

- Measures the proportion of disease that would be eliminated if particular causal factor were eliminated
- Directly related to prevalence of risk factor and risk it conveys
- Almost always over-estimates proportion attributable to risk factor

| PAR =  | (Prevalence of exposure) x (Relative risk - 1) |
| --- | --- |
|  | 1 + (Prevalence of exposure) x (Relative risk - 1)  |

## GWA Genotyping Data, Chromosome 22, Parkinson’s Study

| Study ID | Case/
Control Status | rs5747620 |  | rs2236639  |  |  |
| --- | --- | --- | --- | --- | --- | --- |
|  |  | Allele 1 | Allele 2 |  | Allele 1 | Allele 2 |
| 14 | Case | T | T |  | G | G |
| 20 | Case | T | C |  | G | G |
| 41 | Case | T | C |  | G | G |
| 412  | Control | T | C |  | G | G |
| 592 | Control | C | C |  | G | G |
| 665 | Control | T | C |  | A | G |

**http://ccr.coriell.org/ninds/**

## GWA Genotyping Data, Chromosome 22, One Person

- 412 1 T C G G G G A A A A C C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T T T C C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T T T C C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T T T C C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T T T C C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T T T C C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T T T C C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T T T C C A A A A T C A G C C T C T T T  T C T T A G C C A G A A T T T C C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T T T C C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T T T C C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T T T C C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T T T C C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T T T C C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T T T C C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T T T C C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T T T C C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T T T C C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T T T C C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T T T C C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T T C C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T T T C C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T T T C C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T T T C C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T T T C C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T T T C C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T T T ...

## Chromosome 22, One Person, Continued

- ...G A A A A C C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T T T C C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T T T C C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T T T C C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T T T C C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T T T C C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T T T C C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T T T C C A A A A T C A G C C T C T T T  T C T T A G C C A G A A T T T C C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T T T C C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T T T C C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T T T C C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T T T C C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T T T C C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T T T C C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T T T C C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T T T C C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T T T C C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T T T C C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T T T C C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T T C C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T T T C C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T T T C C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T T T C C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T T T C C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T T T C C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T T TC C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T T T C C A A A A T C A G C C T C T T T C T C T T A G C C C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T ...

## Chromosome 22, One Person, Continued...

- ...A A T C A G C C T C T T T C T C T T A G C C A G A A T T T C C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T T T C C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T T T C C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T T T C C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T T T C C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T T T C C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T T T C C A A A A T C A G C C T C T T T  T C T T A G C C A G A A T T T C C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T T T C C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T T T C C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T T T C C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T T T C C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T T T C C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T T T C C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T T T C C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T T T C C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T T T C C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T T T C C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T T T C C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T T C C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T T T C C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T T T C C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T T T C C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T T T C C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T T T C C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T T TC C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T T T C C A A A A T C A G C C T C T T T C T C T T A G C C C A A A A T C A G C C T C T T T C T C T T A G C C A G A A T C C A A A A T C A G C C T C ...