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| In ], a '''genome-wide association study''' (GWA study) - also known as '''whole genome association study''' (WGA study) - is an examination of genetic variation across the human genome, designed to identify genetic associations with observable traits, such as blood pressure or weight, or why some people get a disease or condition.<ref name="Pearson">{{Cite journal| doi = 10.1001/jama.299.11.1335| volume = 299| issue = 11| pages = |
In ], a '''genome-wide association study''' (GWA study) - also known as '''whole genome association study''' (WGA study) - is an examination of genetic variation across the human genome, designed to identify genetic associations with observable traits, such as blood pressure or weight, or why some people get a disease or condition.<ref name="Pearson">{{Cite journal| doi = 10.1001/jama.299.11.1335| volume = 299| issue = 11| pages = 1335–44 |author= Pearson TA, Manolio TA | title = How to interpret a genome-wide association study| journal = JAMA| date = 2008 |doi=10.1001/jama.299.11.1335 |pmid=18349094 | url = http://jama.ama-assn.org/cgi/content/full/299/11/1335}}</ref> | ||
| The completion of the ] in 2003 made it possible to find the genetic contributions to common diseases and analyze whole-genome samples for genetic variations that contribute to their onset. | The completion of the ] in 2003 made it possible to find the genetic contributions to common diseases and analyze whole-genome samples for genetic variations that contribute to their onset. | ||
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| If genetic variations are more frequent in people with the disease, the variations are said to be "associated" with the disease. The associated genetic variations are then considered pointers to the region of the human genome where the disease-causing problem resides. Since the entire genome is analysed for the genetic associations of a particular disease, this technique allows the genetics of a disease to be investigated in a non-hypothesis-driven manner.<ref name="Pearson" /> | If genetic variations are more frequent in people with the disease, the variations are said to be "associated" with the disease. The associated genetic variations are then considered pointers to the region of the human genome where the disease-causing problem resides. Since the entire genome is analysed for the genetic associations of a particular disease, this technique allows the genetics of a disease to be investigated in a non-hypothesis-driven manner.<ref name="Pearson" /> | ||
| ==Background== | |||
| ==Why are these a good idea?== | |||
| Humans differ in genetic makeup by only 0.1%, but that small part of the genome contains the key differences that can determine a person’s susceptibility to disease. GWA |
Humans differ in genetic makeup by only 0.1%, but that small part of the genome contains the key differences that can determine a person’s susceptibility to disease. GWA studies allow researchers to identify factors in many areas, including asthma, cancer, diabetes, heart disease and mental illness research and clinical care. | ||
| ⚫ | As people have migrated and married over generations, it has become more difficult to limit studies to biological data; for example, people with tuberculosis moving to Colorado might lead to conclusions that Colorado people are biologically inclined to Tuberculosis if correction for population stratification is not properly factored in.<ref>{{cite press release |url=http://www.broad.mit.edu/cgi-bin/news/display_news.cgi?id=1841 |title= Taking geography out of genetics |publisher= Broad Institute |date=2006-07-31 |accessdate=2008-06-19}}</ref> | ||
| ==What are the challenges?== | |||
| ==Successes== | |||
| ⚫ | As people have migrated and married over generations, it has become more difficult to limit studies to biological data; for example, people with tuberculosis moving to Colorado might lead to conclusions that Colorado people are biologically inclined to Tuberculosis if correction for population stratification is not properly factored in. | ||
| ==What is an example of a successful GWA Study?== | |||
| In 2005 it was learned through a small scale GWA Studies that age-related macular degeneration is associated with variation in the gene for complement factor H, which produces a protein that regulates inflammation. | In 2005 it was learned through a small scale GWA Studies that age-related macular degeneration is associated with variation in the gene for complement factor H, which produces a protein that regulates inflammation. | ||
| The first major GWA was published in ] in February 2007 by |
The first major GWA was published in ] in February 2007 by Robert Sladek ''et al.'' in a study searching for type II diabetes variants.<ref>{{cite journal |author= Sladek R, Rocheleau G, Rung J, ''et al.'' |title= A genome-wide association study identifies novel risk loci for type 2 diabetes |journal=Nature |volume=445 |issue=7130 |pages=881–5 |date=2007 |pmid=17293876 |doi=10.1038/nature05616}}</ref> | ||
| | author = ], Ghislain Rocheleau, Johan Rung, Christian Dina, Lishuang Shen, David Serre, Philippe Boutin, Daniel Vincent, Alexandre Belisle, Samy Hadjadj, Beverley Balkau, Barbara Heude, Guillaume Charpentier, Thomas J. Hudson, Alexandre Montpetit, Alexey V. Pshezhetsky, Marc Prentki, Barry I. Posner, David J. Balding, David Meyre, Constantin Polychronakos and Philippe Froguel | |||
| | title = A genome-wide association study identifies novel risk loci for type 2 diabetes | |||
| | journal = ] | |||
| | volume = 445 | |||
| | pages = 881–885 | |||
| | month = February | |||
| | year = 2007 | |||
| | doi = 10.1038/nature05616 | |||
| | url = http://www.nature.com/nature/journal/v445/n7130/abs/nature05616.html | |||
| }}</ref> | |||
| The work was mainly carried out the Genome Quebec centre in McGill University although it included collaboration with scientists at ] and other research institutions. | The work was mainly carried out the Genome Quebec centre in McGill University although it included collaboration with scientists at ] and other research institutions. | ||
| The group tested 392'935 single-nucleotide polymorphisms and identified several associations, among others in the genes called ] and ]. | The group tested 392'935 single-nucleotide polymorphisms and identified several associations, among others in the genes called ] and ]. | ||
| In 2007 the Wellcome Trust Case |
In 2007 the Wellcome Trust Case Control Consortium carried out genome-wide association studies for the diseases coronary heart disease, ], ], ], ], ] and ]. This study was successful in uncovering many new disease genes underlying these diseases.<ref>{{cite press release |url=http://www.wtccc.org.uk/info/070606.shtml |title= Largest ever study of genetics of common diseases published today |publisher= Wellcome Trust Case Control Consortium |date=2007-06-06 |accessdate=2008-06-19}}</ref> | ||
| == |
==Problems== | ||
| Some critics of GWA studies regard them as extremely expensive "factory science". Alternatives such as ] have advantages over GWAs such as robustness to allelic heterogeneity. | Some critics of GWA studies regard them as extremely expensive "factory science". Alternatives such as ] have advantages over GWAs such as robustness to allelic heterogeneity. | ||
| Robert Elston is a prominent proponent of linkage, although he does accept association may occasionally be useful. | |||
| According to Pearson and Manolio's assessment of the technique, "the GWA approach can also be problematic because the massive number of statistical tests performed presents an unprecedented potential for ] results".<ref name="Pearson" /> | According to Pearson and Manolio's assessment of the technique, "the GWA approach can also be problematic because the massive number of statistical tests performed presents an unprecedented potential for ] results".<ref name="Pearson" /> | ||
| ⚫ | ==References== | ||
| ⚫ | {{reflist|2}} | ||
| == External links == | == External links == | ||
| * entry in the public domain NCI Dictionary of Cancer Terms. | * entry in the public domain NCI Dictionary of Cancer Terms. | ||
| * |
* (NIH release) | ||
| ⚫ | * (NIH fact sheet) | ||
| ⚫ | ==References== | ||
| ⚫ | {{reflist}} | ||
| * http://www.nature.com/nature/journal/v445/n7130/full/nature05616.html | |||
| * | |||
| * | |||
| ⚫ | * | ||
| ] | ] | ||
Revision as of 16:39, 19 June 2008
In genetic epidemiology, a genome-wide association study (GWA study) - also known as whole genome association study (WGA study) - is an examination of genetic variation across the human genome, designed to identify genetic associations with observable traits, such as blood pressure or weight, or why some people get a disease or condition.
The completion of the Human Genome Project in 2003 made it possible to find the genetic contributions to common diseases and analyze whole-genome samples for genetic variations that contribute to their onset.
These studies require two groups of participants: people with the disease and similar people without. After obtaining samples from each participant, the set of markers such as SNPs are scanned into computers. The computers survey each participant's genome for markers of genetic variation.
If genetic variations are more frequent in people with the disease, the variations are said to be "associated" with the disease. The associated genetic variations are then considered pointers to the region of the human genome where the disease-causing problem resides. Since the entire genome is analysed for the genetic associations of a particular disease, this technique allows the genetics of a disease to be investigated in a non-hypothesis-driven manner.
Background
Humans differ in genetic makeup by only 0.1%, but that small part of the genome contains the key differences that can determine a person’s susceptibility to disease. GWA studies allow researchers to identify factors in many areas, including asthma, cancer, diabetes, heart disease and mental illness research and clinical care.
As people have migrated and married over generations, it has become more difficult to limit studies to biological data; for example, people with tuberculosis moving to Colorado might lead to conclusions that Colorado people are biologically inclined to Tuberculosis if correction for population stratification is not properly factored in.
Successes
In 2005 it was learned through a small scale GWA Studies that age-related macular degeneration is associated with variation in the gene for complement factor H, which produces a protein that regulates inflammation.
The first major GWA was published in Nature in February 2007 by Robert Sladek et al. in a study searching for type II diabetes variants. The work was mainly carried out the Genome Quebec centre in McGill University although it included collaboration with scientists at Imperial College London and other research institutions. The group tested 392'935 single-nucleotide polymorphisms and identified several associations, among others in the genes called TCF7L2 and SLC30A8.
In 2007 the Wellcome Trust Case Control Consortium carried out genome-wide association studies for the diseases coronary heart disease, type 1 diabetes, type 2 diabetes, rheumatoid arthritis, Crohn's disease, bipolar disorder and hypertension. This study was successful in uncovering many new disease genes underlying these diseases.
Problems
Some critics of GWA studies regard them as extremely expensive "factory science". Alternatives such as linkage analysis have advantages over GWAs such as robustness to allelic heterogeneity.
Robert Elston is a prominent proponent of linkage, although he does accept association may occasionally be useful.
According to Pearson and Manolio's assessment of the technique, "the GWA approach can also be problematic because the massive number of statistical tests performed presents an unprecedented potential for false-positive results".
References
- ^ Pearson TA, Manolio TA (2008). "How to interpret a genome-wide association study". JAMA. 299 (11): 1335–44. doi:10.1001/jama.299.11.1335. PMID 18349094.
- "Taking geography out of genetics" (Press release). Broad Institute. 2006-07-31. Retrieved 2008-06-19.
- Sladek R, Rocheleau G, Rung J; et al. (2007). "A genome-wide association study identifies novel risk loci for type 2 diabetes". Nature. 445 (7130): 881–5. doi:10.1038/nature05616. PMID 17293876.
{{cite journal}}: Explicit use of et al. in:|author=(help)CS1 maint: multiple names: authors list (link) - "Largest ever study of genetics of common diseases published today" (Press release). Wellcome Trust Case Control Consortium. 2007-06-06. Retrieved 2008-06-19.
External links
- Whole genome association study entry in the public domain NCI Dictionary of Cancer Terms.
- Whole genome association studies (NIH release)
- Genome-wide association studies (NIH fact sheet)