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Rare Variants Create Synthetic Genome-Wide Associations
Genome-wide association studies (GWAS) have now identified at least 2,000 common variants that appear associated with common diseases or related traits (http://www.genome.gov/gwastudies), hundreds of which have been convincingly replicated. It is generally thought that the associated markers reflect...
Autores principales: | , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2010
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2811148/ https://www.ncbi.nlm.nih.gov/pubmed/20126254 http://dx.doi.org/10.1371/journal.pbio.1000294 |
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author | Dickson, Samuel P. Wang, Kai Krantz, Ian Hakonarson, Hakon Goldstein, David B. |
author_facet | Dickson, Samuel P. Wang, Kai Krantz, Ian Hakonarson, Hakon Goldstein, David B. |
author_sort | Dickson, Samuel P. |
collection | PubMed |
description | Genome-wide association studies (GWAS) have now identified at least 2,000 common variants that appear associated with common diseases or related traits (http://www.genome.gov/gwastudies), hundreds of which have been convincingly replicated. It is generally thought that the associated markers reflect the effect of a nearby common (minor allele frequency >0.05) causal site, which is associated with the marker, leading to extensive resequencing efforts to find causal sites. We propose as an alternative explanation that variants much less common than the associated one may create “synthetic associations” by occurring, stochastically, more often in association with one of the alleles at the common site versus the other allele. Although synthetic associations are an obvious theoretical possibility, they have never been systematically explored as a possible explanation for GWAS findings. Here, we use simple computer simulations to show the conditions under which such synthetic associations will arise and how they may be recognized. We show that they are not only possible, but inevitable, and that under simple but reasonable genetic models, they are likely to account for or contribute to many of the recently identified signals reported in genome-wide association studies. We also illustrate the behavior of synthetic associations in real datasets by showing that rare causal mutations responsible for both hearing loss and sickle cell anemia create genome-wide significant synthetic associations, in the latter case extending over a 2.5-Mb interval encompassing scores of “blocks” of associated variants. In conclusion, uncommon or rare genetic variants can easily create synthetic associations that are credited to common variants, and this possibility requires careful consideration in the interpretation and follow up of GWAS signals. |
format | Text |
id | pubmed-2811148 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2010 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-28111482010-02-02 Rare Variants Create Synthetic Genome-Wide Associations Dickson, Samuel P. Wang, Kai Krantz, Ian Hakonarson, Hakon Goldstein, David B. PLoS Biol Research Article Genome-wide association studies (GWAS) have now identified at least 2,000 common variants that appear associated with common diseases or related traits (http://www.genome.gov/gwastudies), hundreds of which have been convincingly replicated. It is generally thought that the associated markers reflect the effect of a nearby common (minor allele frequency >0.05) causal site, which is associated with the marker, leading to extensive resequencing efforts to find causal sites. We propose as an alternative explanation that variants much less common than the associated one may create “synthetic associations” by occurring, stochastically, more often in association with one of the alleles at the common site versus the other allele. Although synthetic associations are an obvious theoretical possibility, they have never been systematically explored as a possible explanation for GWAS findings. Here, we use simple computer simulations to show the conditions under which such synthetic associations will arise and how they may be recognized. We show that they are not only possible, but inevitable, and that under simple but reasonable genetic models, they are likely to account for or contribute to many of the recently identified signals reported in genome-wide association studies. We also illustrate the behavior of synthetic associations in real datasets by showing that rare causal mutations responsible for both hearing loss and sickle cell anemia create genome-wide significant synthetic associations, in the latter case extending over a 2.5-Mb interval encompassing scores of “blocks” of associated variants. In conclusion, uncommon or rare genetic variants can easily create synthetic associations that are credited to common variants, and this possibility requires careful consideration in the interpretation and follow up of GWAS signals. Public Library of Science 2010-01-26 /pmc/articles/PMC2811148/ /pubmed/20126254 http://dx.doi.org/10.1371/journal.pbio.1000294 Text en Dickson et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Dickson, Samuel P. Wang, Kai Krantz, Ian Hakonarson, Hakon Goldstein, David B. Rare Variants Create Synthetic Genome-Wide Associations |
title | Rare Variants Create Synthetic Genome-Wide Associations |
title_full | Rare Variants Create Synthetic Genome-Wide Associations |
title_fullStr | Rare Variants Create Synthetic Genome-Wide Associations |
title_full_unstemmed | Rare Variants Create Synthetic Genome-Wide Associations |
title_short | Rare Variants Create Synthetic Genome-Wide Associations |
title_sort | rare variants create synthetic genome-wide associations |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2811148/ https://www.ncbi.nlm.nih.gov/pubmed/20126254 http://dx.doi.org/10.1371/journal.pbio.1000294 |
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