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Trends in Biomedical Science 02 Mapping of disease genes GWAS 1

Trends in Biomedical Science 02 Mapping of disease genes GWAS 1

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Trends in Biomedical Science

02 Mapping of disease genes GWAS

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Genome-wide association studies (GWAS) • recently developed research technique • used to identify the single nucleotide

polymorphisms (SNPs, pronounced "snips") – common to the human genome – find how SNPs are spread across different populations.

• help scientists associations between individual SNPs and disorders that are passed from one generation to the next

• can be used to determine an individual's risk of developing a particular disorder

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The most common type of genetic variation is a single nucleotide polymorphism (pronounced 'snip'), a difference in a single DNA base. There are approximately 10 million SNPs estimated to occur commonly in the human genome.

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Depends upon researchers' understanding of the interacting factors behind common genetic disorders.

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SNP(Single Nucleotide Polymorphism)단일염기변이 , 스니프스 (SNPs). 인종이나 개인별 염기의 차이를 말한다 .즉 세포핵 속에 염색체가 갖고 있는 30 억개의 염기 서열 가운데 개인 편차를 나타내는 한개 또는 수십개의 변이염기를 일컫는다 .500~1000 염기당 1 개꼴로 나타나며 , 인간지놈에는 약 300 만개의 SNP 가 존재하고 있다 .인간은 인종이나 민족과 상관없이 유전자가 99.9% 일치하지만 0.1% 의 SNP 때문에 키와 피부색이 달라지게 된다 .한국인이 서양인에 비해 위암과 간암이 잘 걸리는 것도 이런 차이에서 생기는 것으로 추정된다 .

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Other methods • quantitative trait locus (QTL) analysis – identify a QTL, or a chromosomal region associated

with a given phenotype – study the candidate genes within that region

• microsatellite DNA sequences – short stretches of chromosomal DNA – contain a two- to five-base-pair sequence (such as

CA) • repeated multiple times (e.g., CACACACACACACA).

– polymorphic, and the number of base-pair repeats often varies between individuals.

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SNPs: Variations in the Human Genome After Human Genome Project • find areas of the genome that varied

between individuals • discovered that the most common type of

DNA sequence variation found in the genome is the single nucleotide polymorphism; – an estimated 10 million SNPs that commonly

occur in the human genome. – HapMap Project

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HapMap Project • identify and localize these and other genetic

variants, • learn how the variants are distributed within

and among populations from different parts of the world.

• identified over 3.1 million SNPs that are common to individuals of African, Asian, and European ancestry.

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The HapMap information → the genome-wide association study (GWAS). • find distribution of SNPs in hundreds or even

thousands of people with and without a particular disease.

• find which SNPs co-occur with disease symptoms,

• → statistical estimate regarding the level of increased risk associated with each SNP.

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For instance, 2007 study in the United Kingdom: • Found people affected by seven common

disorders, – genotyped 2,000 people in each disease category

(for a total of 14,000 people) – compared to 3,000 genotyped controls who did

not have the disorders – identified new genetic markers that point to an

increased risk for multifactorial disorders such as heart disease and diabetes

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• July 2008 –study will be expanded to add 36,000

individuals –will examine the genetic contributions

to a total of 14 common disorders – individuals' responses to certain drugs.

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The Role of DNA Microarrays in GWAS DNA microarray (sometimes called a DNA chip) • a small glass slide with short DNA probes

attached to it in a specific pattern – a sample of fragmented DNA is washed over the

microarray, – pieces of this DNA hybridize to the chip – detected by scanning software.

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Affymetrix is one manufacturer of DNA microarrays • sells a chip containing approximately 1.8 million

different genetic markers • a fragment of DNA from a test sample hybridizes

to a probe on this microarray • the scanning software can document exactly

which genetic marker is present in that DNA sample

• allows a single sample to be searched for changes at almost 2 million known genetic variants.

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Microarray experimentsTwo color experiment (panel a) DNA from individuals or different tissue from a single individual (e.g., normal and diseased cells) is extracted and differentially labeled with compatible fluorophores (e.g., Cy3, Cy5). Equal amounts of labeled DNA is hybridized to the microarray. At most probes, equal amounts of the two samples will hybridize (yellow features on the array), so most loci in the two genomes are present in equal amounts (for example region 3). One-color experiments (panel b in the figure). DNA is labeled with a single color and hybridized to a microarray without a reference sample. The difference between two-color and one-color experiments is that in the former case two samples are compared within an experiment, whereas in the latter case two separate experiments are required to compare the samples.

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Using GWAS to Estimate Disease Risk

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Finding a correlation between a genetic change and the incidence of a complex disease • limited to statistical estimation of increased

risk for developing the disorder • rather than a hard-and-fast prediction • significant number of genetic and

environmental variables interact to cause the onset of a complex disease

• any genetic variant, such as a SNP, makes only a small contribution to an individual's overall risk.

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Findings from a GWAS: • usually cannot be directly applied to the

prevention or treatment of disease. before doctors are able to recommend medicinal, behavioral, and environmental interventions

• the full pathway of disease development must be understood

• the involvement of all variables must be understood.

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• Eg., a SNP may not be located within an exon of a gene –Maybe the SNP lies in a promoter or

enhancer region – somehow affects regulation of the causal

gene.

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Sometimes results of a GWAS can be directly applied; • often when a gene contains a variant that

gives susceptibility to a multifactorial disorder • the effect of that variant or other alleles of the

gene is one of many factors influencing disease risk

• the predictive power of the various alleles is not absolute

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eg. certain alleles of the apolipoprotein E (ApoE) gene found on chromosome 19 • linked to the development of Alzheimer's disease. • ApoE codes for a protein that helps carry

cholesterol in the bloodstream, – three common alleles: e2, e3, and e4. – having one or two copies of the ApoE e4 allele

significantly increases a person's risk for developing Alzheimer's disease,

– does not guarantee development of this disorder. • Not clear how certain forms of ApoE influence

cerebral plaque formation, - Alzheimer's disease

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Personal SNP Profiles

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Very large amounts of information derived from the use of genome-wide association studies. • most SNPs are only partial contributors to an

individual's risk for developing a disease, • researchers must be cautious about giving too much

weight to SNP profiles. • entrepreneurs capitalizing on existing GWAS research – eg., consumer genomics companies such as 23andMe,

deCODE genetics, Navigenics, and Knome – used to offer a range of personal genotyping and

sequencing services to clients – regulated so much → cannot offer services

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Summary

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• genome-wide association studies have played an important role in research to identify possible connections between SNPs and various disorders.

• knowledge of the genetic risk factors for disease has increased → apply GWAS research to risk assessments for various disorders.

• GWASs are not absolute predictors of disease due to the role of environmental factors in complex disease development

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Genome-Wide Association Studies and Human Disease Networks Adapted from Pray,L.(2008)Genome-wide association studies and human disease networks.NatureEducation1(1):220

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Organizing Gene Association Data Research institutions in the United States and Korea • developed what they call the "human disease

network," • a visual map of all human diseases with

known underlying genetic associations; • details the genetic connections between these

diseases

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Map made of nodes and branches • node

•a disease, •size - number of genes known to be

associated with that disorder. • thickness of the branches

•the number of genes shared by the connected diseases.

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Most diseases with known genetic associations share most of their genes with other diseases. • such as type 2 diabetes and

prostate cancer– appear to be influenced by variation in the

JAZF1 gene

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Genetic connections among diseases Show the molecular pathways that

cause disease aid in the design and development of

new ways of treating or curing disease. eg. a treatment that works well for one

of the diseases may work for the other

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Benefits of Gene Association Mapping

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Gene-disease networking first step toward making GWAS data

useful for health care, changes how physicians think about

disease

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• eg. how doctors categorize various illnesses. –Stop thinking of human sickness in

terms of the tissue involved (e.g., cancer of the breast), –Start thinking in terms of the molecular

pathways involved.

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• Eg. invasive breast cancer, – categorized as being either Her2/neu-

positive or Her2/neu-negative. Her2/neu is a receptor on the surface of breast cancer cells that is coded for by the Her2/neu gene. –Her2/neu-positive have many more of these

receptors –Benefit more from certain forms of

treatment than are Her2/neu-negative patients

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Example Database - http://www.ebi.ac.uk/fgpt/gwas/

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