# Presentation: 030731

## Multi-IC Symposium on Application of Genomic Technologies to Population-Based Studies

- National Human Genome Research Institute

- National  Institutes of Health

- U.S. Department of Health and Human Services

**James Battey, NIDCR**
**Stephen Chanock, NCI****	**
**Katrina Gwinn-Hardy, NINDS**
**Teri Manolio, NHGRI**
**Rebekah Rasooly, NIDDK**
**Winifred Rossi, NIA**
**Gerald Sharp, NIAID**

## Opportunities and Challenges in Applying Genomic Techniques to Population Studies Teri Manolio, M.D., Ph.D.Senior Advisor to the Director for Population GenomicsJune 5, 2006

## Background and Opportunities

- Understanding of genome structure provides unprecedented opportunities to define genetic contributions to health and disease, particularly in relation to environmental effects
- Progress in application of genomic knowledge to health hampered by two separate worlds:
- Genomics
- Population-based research

## anonymized

## anonymized

- coding SNP

## anonymized

- coding SNP

- indel

## whole genome amplification

- phenocopy

- coding SNP

- silencer

- indel

- inversion

- linkage disequilibrium

## lambda

- ancestral markers

- anonymized

- phenocopy

- coding SNP

- whole genome amplification

- 5' UTR

- silencer

- shotgun sequencing

- indel

- inversion

- linkage disequilibrium

**lambda**

- admixture

## lambda

- ancestral markers

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**epigenetics**

- epistasis

- phenocopy

- population stratification

- coding SNP

- whole genome amplification

- genome wide association

- promoter

- 5' UTR

- selective sweep

- enhancer

- silencer

- shotgun sequencing

**minor allele frequency**

- indel

- inversion

- linkage disequilibrium

**lambda**

- gene-environment interaction

- admixture

## Gary Larson, The Far Side.

- Gary Larson, *The Far Side.*

## Basic Definitions

_**Locus**_: Place on a chromosome where a specific gene or set of markers reside
_**Gene**_: Contiguous piece of DNA that can contain information to make or modify ‘expression’ of specific protein(s)
_**Polymorphism**_: Variation in the sequence of DNA among individuals
_**Allele**_: A variant form of a DNA sequence at a particular locus on a chromosome
*Note: these terms were defined when we did not have access to complete DNA sequence*

- Courtesy S. Chanock, NCI

## What is a Classical Gene?

**What is a Classical Gene?**

- Exons

- 2Kb

- 2Kb

- Human/Mouse conserved regions
- > 200 bp ;  > 80% identity

- Promoter &
- 5’UTR

- 3’ UTR &
- downstream

- Start
- transcription

- Stop
- translation

- Gene region

- Intron

- 5, 10 or 20 kb

- “Regulators”

- Courtesy S. Chanock, NCI

## Mutations and Single Nucleotide Polymorphisms (SNPs)

- Mutation = change in bp sequence
- Point substitution: most frequent in genome
- Point mutations occur roughly once every 108 replication events
- "Common" SNPs are defined as >1% minor allele frequency (MAF) in at least one population
- Rare SNPs are hard to identify and validate (probably requires sequencing), but there are likely a large number per individual

- After S. Chanock, NCI

## SNPs and Function

- Majority are “silent” (excellent as markers)
- No known functional change
- Alter gene expression/regulation
- Promoter/enhancer/silencer
- mRNA stability, splice site variants
- Small RNAs
- Alter function of gene product
- Change sequence of protein

- After S. Chanock, NCI

## Coding SNPs (cSNPs)

**Synonymous**: no change in amino acid
- 	previously termed “silent” but.....
- 		*Can alter mRNA stability*
- 		*DRD2* (Duan et al 2002)
**Nonsynonymous**: changes amino acid,
- 	conservative and radical
**Nonsense**: change to stop codon
**Insertion/deletion (indel)**: disrupts codon sequence, rare but disruptive

- After S. Chanock, NCI

## Other Types of Polymorphisms (Structural Variation)

- Duplication/expansion/repeat:
- Minisatellites (VNTRs), 25 – 100s of bp
- Microsatellites (STRs), 2 – 7 bp
- Copy number variants: gains and losses of large chunks of DNA sequence, 10K – 5M bp
- Inversion: segment of DNA reversed end to end, recombination suppressed across that segment
- Translocation: segment of DNA moved to another position, especially another chromosome

- After S. Chanock, NCI

## Sidney Harris, http://www.sciencecartoonsplus.com/gallery.htm.

## Public Health and Genomics

- _Primary goal_:
- 	Improve health and prevent disease
- _Progress in_:
- 	Defining genome structure and function
- _But_:
- 	Not ready for direct clinical or public health application in detection, treatment, and prevention of disease
- _Need_:
- 	Concerted effort to stimulate steps from gene identification to public health implementation

## Identifying Risk-Related Genetic Variants on a Population Basis

- Determine prevalence of variants in diverse groups
- Examine associations identified in family studies, assess magnitude and independence
- 	common risk factors are not strong
- 	strong risk factors are not common
- Define associations with variety of phenotypes
- Identify factors modifying genotype-phenotype relationships (gene-environment interactions)

*“**Genes are merely risk factors passed on from parents to children....”*

## Genetic Studies in Unrelated Individuals (pre-2004)

- Goal: to characterize candidate genes and variants identified as related to disease
- Most effective if begun *after* disease-related genes and variants identified
- Not typically intended to “find genes”

**Notes:**
Co-seg with trait (inherited with trait)
“co-segregating”  or demonstrating “linkage,” has been suggested to be the stron
gest statistical evidence for an underlying genetic mechanism
anonymous markers: polymorphic markers of no known functional significance but

## Genetic Studies in Unrelated Individuals (pre-2004)

- Assess generalizability of family-based observations in population-based studies (genetic heterogeneity)
- Assess importance of allelic variation at population level (population attributable risk)
- Allele frequency
- Size of effect
- Identify modification of genetic association by  environmental factors (GxE interaction)

**Notes:**
Co-seg with trait (inherited with trait)
“co-segregating”  or demonstrating “linkage,” has been suggested to be the stron
gest statistical evidence for an underlying genetic mechanism
anonymous markers: polymorphic markers of no known functional significance but

## Age-Adjusted Odds on Hypertension by ACE ID/DD Genotype and Sex

|  | DD |   ID | II | P-value |
| --- | --- | --- | --- | --- |
| Men: % HTN |     53.1 |    45.8 |    44.4 |  |
| Men: OR  |     1.67 |    1.19 |    1.00 |   0.004 |
| Women: % HTN |     43.3 |    41.8 |    44.4 |  |
| Women: OR |     1.01 |    0.80 |    1.00 | 0.15 |

- after O’Donnell C et al, *Circulation* 1998; 97:1766-1772.

## www.hapmap.org

**Notes:**
Co-seg with trait (inherited with trait)
“co-segregating”  or demonstrating “linkage,” has been suggested to be the stron
gest statistical evidence for an underlying genetic mechanism
anonymous markers: polymorphic markers of no known functional significance but

## A HapMap for More Efficient Association Studies

- Use just the density of SNPs needed to find associations between SNPs and diseases.
- Do not miss chromosomal regions with disease association.
- Produce a tool to assist in finding genes affecting health and disease.

- Courtesy L. Brooks, NHGRI

## Genetic Studies in Unrelated Individuals post-2004 : Whole Genome Association Studies (WGAS, WGS, GWAS...)

- Identify genes related to complex diseases
- Complex diseases: caused by multiple genes of small effect, not amenable to family studies
- Whole genome: interrogate all variation throughout genome, two main approaches
- 	1. 	Family linkage study with 400 microsatellite 	markers, assumes ~10mb regions of LD
- 	2.	Unrelated case-control study with 300-500K 	SNPs, assumes ~10kb regions of LD

## Value of WGA Studies in Unrelated Individuals

- Unrelated individuals tend to be easier to study
- Many existing collections of population samples
- Often extremely well-characterized
- Often followed for long periods
- Often diverse in origin, exposures
- Large families with common diseases remain very valuable for gene-finding
- Not so common anymore
- Families tend to share environmental factors more than do unrelated individuals

## Whole Genome Scans (AKA Association Studies)

- Public Health Impact
- Primary Goal(s)
- Etiology
- Survival
- Pharmacogenomics
- Value-added Analyses
- Covariates
- Biomarkers
- Gene-environment interactions

## What WGA Studies Will and Won't Do

**WILL:**
- Identify lots of common SNPs with statistical association to disease or trait
- Identify a blizzard of spurious associations
- Provide clues to causative genetic variants
- Provide clues to environmental modifiers
- Generate terabytes of data
**WON'T**:
- Identify rare SNPs associated with disease/trait
- Identify causative genetic variants
- Explain biology or function

## What Sequencing Studies Will and Won't Do

**WILL:**
- Identify rare SNPs in persons with disease/trait
- Suggest clues to causative genetic variants
- Generate terabytes of data
**WON'T**:
- Identify causative genetic variants
- Explain biology or function
- Define importance of variants in population

## Environmental and behavioral changes interacting with genetic predisposition have likely produced most of the recent epidemics of  chronic diseases
GxE may be key in reversing their course, by suggesting approaches for modifying effects of deleterious genes 
Future public health measures may focus on avoiding deleterious environmental exposure, especially in genetically susceptible persons

- GxE may be key in reversing their course, by suggesting approaches for modifying effects of deleterious genes
- Future public health measures may focus on avoiding deleterious environmental exposure, especially in genetically susceptible persons

**Why are Gene-Environment Interactions so Important to Public Health?**

**Notes:**
Both genetic variant and exposure needed to produce disease

## Why are Gene-Environment Interactions so Important to Research?

- Can mask detection of genetic (or environmental) effect if they are not identified and controlled for
- Can lead to inconsistencies in disease associations in different populations with:
- Different environmental exposures that modify the effect of a genetic variant
- Different prevalences of genetic variants that modify the effect of an environmental exposure

## Is LIPC Genotype Related to HDL-C?

- TT

- CC

- CT

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

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

- TT

- CC

- CT

## Is LIPC Genotype Related to HDL-C?

- TT

- CC

- CT

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

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

- TT

- CC

- CT

## Is LIPC Genotype Related to HDL-C?

- TT

- CC

- CT

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

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

- TT

- CC

- CT

## Is LIPC Genotype Related to HDL-C?

- TT

- CC

- CT

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

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

- TT

- CC

- CT

## Is LIPC Genotype Related to HDL-C?

- TT

- CC

- CT

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

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

- TT

- CC

- CT

## Gary Larson, The Far Side.

- Gary Larson, *The Far Side.*

## Challenges in Applying Genomic Technologies to Population Studies

- Which technologies?  How to evaluate ever-changing technologies and ensure most reliable and cost-effective applied to your IC's studies?
- How to manage data?  How to increase access and usefulness to outside groups, and enhance comparability across studies?
- How to ensure adequate consent and human subjects approval for future studies?  How to protect participant confidentiality?

**Notes:**
don't have to spend millions to characterize
don't have to wait years for outcomes
often extensive characterization of environmental exposure permits identification of potential GxE

## Challenges in Applying Genomic Technologies to Population Studies (2)

- Which population studies?  How to facilitate use of large-scale studies for multiple ICs' needs?
- Which WGA or sequencing studies?  How to select and prioritize appropriate population samples and follow-up studies?
- How to fund and coordinate addition of genomic technologies to ongoing studies?  What issues related to consent, confidentiality, and IP need to be addressed in existing vs *de novo* studies?

**Notes:**
don't have to spend millions to characterize
don't have to wait years for outcomes
often extensive characterization of environmental exposure permits identification of potential GxE

## Symposium Website

- http://genome.gov/pages/extranets/PopulationGenomicsTraining/
- Username: 	**training**
- Password: 		**summer06**
- Stay tuned for migration, updates...

**Notes:**
don't have to spend millions to characterize
don't have to wait years for outcomes
often extensive characterization of environmental exposure permits identification of potential GxE

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