Association between Common Variation in 120 Candidate Genes and Breast Cancer Risk
Association studies in candidate genes have been widely used to search for common low penetrance susceptibility alleles, but few definite associations have been established. We have conducted association studies in breast cancer using an empirical single nucleotide polymorphism (SNP) tagging approac...
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| Vydáno v: | PLoS genetics Ročník 3; číslo 3; s. e42 |
|---|---|
| Hlavní autoři: | , , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
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United States
Public Library of Science
01.03.2007
Public Library of Science (PLoS) |
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| ISSN: | 1553-7404, 1553-7390, 1553-7404 |
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| Abstract | Association studies in candidate genes have been widely used to search for common low penetrance susceptibility alleles, but few definite associations have been established. We have conducted association studies in breast cancer using an empirical single nucleotide polymorphism (SNP) tagging approach to capture common genetic variation in genes that are candidates for breast cancer based on their known function. We genotyped 710 SNPs in 120 candidate genes in up to 4,400 breast cancer cases and 4,400 controls using a staged design. Correction for population stratification was done using the genomic control method, on the basis of data from 280 genomic control SNPs. Evidence for association with each SNP was assessed using a Cochran-Armitage trend test (p-trend) and a two-degrees of freedom chi(2) test for heterogeneity (p-het). The most significant single SNP (p-trend = 8 x 10(-5)) was not significant at a nominal 5% level after adjusting for population stratification and multiple testing. To evaluate the overall evidence for an excess of positive associations over the proportion expected by chance, we applied two global tests: the admixture maximum likelihood (AML) test and the rank truncated product (RTP) test corrected for population stratification. The admixture maximum likelihood experiment-wise test for association was significant for both the heterogeneity test (p = 0.0031) and the trend test (p = 0.017), but no association was observed using the rank truncated product method for either the heterogeneity test or the trend test (p = 0.12 and p = 0.24, respectively). Genes in the cell-cycle control pathway and genes involved in steroid hormone metabolism and signalling were the main contributors to the association. These results suggest that a proportion of SNPs in these candidate genes are associated with breast cancer risk, but that the effects of individual SNPs is likely to be small. Large sample sizes from multicentre collaboration will be needed to identify associated SNPs with certainty. |
|---|---|
| AbstractList | Association studies in candidate genes have been widely used to search for common low penetrance susceptibility alleles, but few definite associations have been established. We have conducted association studies in breast cancer using an empirical single nucleotide polymorphism (SNP) tagging approach to capture common genetic variation in genes that are candidates for breast cancer based on their known function. We genotyped 710 SNPs in 120 candidate genes in up to 4,400 breast cancer cases and 4,400 controls using a staged design. Correction for population stratification was done using the genomic control method, on the basis of data from 280 genomic control SNPs. Evidence for association with each SNP was assessed using a Cochran–Armitage trend test (p-trend) and a two-degrees of freedom χ2 test for heterogeneity (p-het). The most significant single SNP (p-trend = 8 × 10−5) was not significant at a nominal 5% level after adjusting for population stratification and multiple testing. To evaluate the overall evidence for an excess of positive associations over the proportion expected by chance, we applied two global tests: the admixture maximum likelihood (AML) test and the rank truncated product (RTP) test corrected for population stratification. The admixture maximum likelihood experiment-wise test for association was significant for both the heterogeneity test (p = 0.0031) and the trend test (p = 0.017), but no association was observed using the rank truncated product method for either the heterogeneity test or the trend test (p = 0.12 and p = 0.24, respectively). Genes in the cell-cycle control pathway and genes involved in steroid hormone metabolism and signalling were the main contributors to the association. These results suggest that a proportion of SNPs in these candidate genes are associated with breast cancer risk, but that the effects of individual SNPs is likely to be small. Large sample sizes from multicentre collaboration will be needed to identify associated SNPs with certainty. Association studies in candidate genes have been widely used to search for common low penetrance susceptibility alleles, but few definite associations have been established. We have conducted association studies in breast cancer using an empirical single nucleotide polymorphism (SNP) tagging approach to capture common genetic variation in genes that are candidates for breast cancer based on their known function. We genotyped 710 SNPs in 120 candidate genes in up to 4,400 breast cancer cases and 4,400 controls using a staged design. Correction for population stratification was done using the genomic control method, on the basis of data from 280 genomic control SNPs. Evidence for association with each SNP was assessed using a Cochran-Armitage trend test (p-trend) and a two-degrees of freedom chi(2) test for heterogeneity (p-het). The most significant single SNP (p-trend = 8 x 10(-5)) was not significant at a nominal 5% level after adjusting for population stratification and multiple testing. To evaluate the overall evidence for an excess of positive associations over the proportion expected by chance, we applied two global tests: the admixture maximum likelihood (AML) test and the rank truncated product (RTP) test corrected for population stratification. The admixture maximum likelihood experiment-wise test for association was significant for both the heterogeneity test (p = 0.0031) and the trend test (p = 0.017), but no association was observed using the rank truncated product method for either the heterogeneity test or the trend test (p = 0.12 and p = 0.24, respectively). Genes in the cell-cycle control pathway and genes involved in steroid hormone metabolism and signalling were the main contributors to the association. These results suggest that a proportion of SNPs in these candidate genes are associated with breast cancer risk, but that the effects of individual SNPs is likely to be small. Large sample sizes from multicentre collaboration will be needed to identify associated SNPs with certainty. Association studies in candidate genes have been widely used to search for common low penetrance susceptibility alleles, but few definite associations have been established. We have conducted association studies in breast cancer using an empirical single nucleotide polymorphism (SNP) tagging approach to capture common genetic variation in genes that are candidates for breast cancer based on their known function. We genotyped 710 SNPs in 120 candidate genes in up to 4,400 breast cancer cases and 4,400 controls using a staged design. Correction for population stratification was done using the genomic control method, on the basis of data from 280 genomic control SNPs. Evidence for association with each SNP was assessed using a Cochran-Armitage trend test (p-trend) and a two-degrees of freedom χ2 test for heterogeneity (p-het). The most significant single SNP (p-trend = 8 × 10-5) was not significant at a nominal 5% level after adjusting for population stratification and multiple testing. To evaluate the overall evidence for an excess of positive associations over the proportion expected by chance, we applied two global tests: the admixture maximum likelihood (AML) test and the rank truncated product (RTP) test corrected for population stratification. The admixture maximum likelihood experiment-wise test for association was significant for both the heterogeneity test (p = 0.0031) and the trend test (p = 0.017), but no association was observed using the rank truncated product method for either the heterogeneity test or the trend test (p = 0.12 and p = 0.24, respectively). Genes in the cell-cycle control pathway and genes involved in steroid hormone metabolism and signalling were the main contributors to the association. These results suggest that a proportion of SNPs in these candidate genes are associated with breast cancer risk, but that the effects of individual SNPs is likely to be small. Large sample sizes from multicentre collaboration will be needed to identify associated SNPs with certainty. Association studies in candidate genes have been widely used to search for common low penetrance susceptibility alleles, but few definite associations have been established. We have conducted association studies in breast cancer using an empirical single nucleotide polymorphism (SNP) tagging approach to capture common genetic variation in genes that are candidates for breast cancer based on their known function. We genotyped 710 SNPs in 120 candidate genes in up to 4,400 breast cancer cases and 4,400 controls using a staged design. Correction for population stratification was done using the genomic control method, on the basis of data from 280 genomic control SNPs. Evidence for association with each SNP was assessed using a Cochran-Armitage trend test (p-trend) and a two-degrees of freedom χ2 test for heterogeneity (p-het). The most significant single SNP (p-trend = 8 × 10-5) was not significant at a nominal 5% level after adjusting for population stratification and multiple testing. To evaluate the overall evidence for an excess of positive associations over the proportion expected by chance, we applied two global tests: the admixture maximum likelihood (AML) test and the rank truncated product (RTP) test corrected for population stratification. The admixture maximum likelihood experiment-wise test for association was significant for both the heterogeneity test (p = 0.0031) and the trend test (p = 0.017), but no association was observed using the rank truncated product method for either the heterogeneity test or the trend test (p = 0.12 and p = 0.24, respectively). Genes in the cell-cycle control pathway and genes involved in steroid hormone metabolism and signalling were the main contributors to the association. These results suggest that a proportion of SNPs in these candidate genes are associated with breast cancer risk, but that the effects of individual SNPs is likely to be small. Large sample sizes from multicentre collaboration will be needed to identify associated SNPs with certainty. Association studies in candidate genes have been widely used to search for common low penetrance susceptibility alleles, but few definite associations have been established. We have conducted association studies in breast cancer using an empirical single nucleotide polymorphism (SNP) tagging approach to capture common genetic variation in genes that are candidates for breast cancer based on their known function. We genotyped 710 SNPs in 120 candidate genes in up to 4,400 breast cancer cases and 4,400 controls using a staged design. Correction for population stratification was done using the genomic control method, on the basis of data from 280 genomic control SNPs. Evidence for association with each SNP was assessed using a Cochran-Armitage trend test (p-trend) and a two-degrees of freedom [chi] super(2) test for heterogeneity (p-het). The most significant single SNP (p-trend = 8 x 10 super(-5)) was not significant at a nominal 5% level after adjusting for population stratification and multiple testing. To evaluate the overall evidence for an excess of positive associations over the proportion expected by chance, we applied two global tests: the admixture maximum likelihood (AML) test and the rank truncated product (RTP) test corrected for population stratification. The admixture maximum likelihood experiment-wise test for association was significant for both the heterogeneity test (p = 0.0031) and the trend test (p = 0.017), but no association was observed using the rank truncated product method for either the heterogeneity test or the trend test (p = 0.12 and p = 0.24, respectively). Genes in the cell-cycle control pathway and genes involved in steroid hormone metabolism and signalling were the main contributors to the association. These results suggest that a proportion of SNPs in these candidate genes are associated with breast cancer risk, but that the effects of individual SNPs is likely to be small. Large sample sizes from multicentre collaboration will be needed to identify associated SNPs with certainty. Association studies in candidate genes have been widely used to search for common low penetrance susceptibility alleles, but few definite associations have been established. We have conducted association studies in breast cancer using an empirical single nucleotide polymorphism (SNP) tagging approach to capture common genetic variation in genes that are candidates for breast cancer based on their known function. We genotyped 710 SNPs in 120 candidate genes in up to 4,400 breast cancer cases and 4,400 controls using a staged design. Correction for population stratification was done using the genomic control method, on the basis of data from 280 genomic control SNPs. Evidence for association with each SNP was assessed using a Cochran-Armitage trend test (p-trend) and a two-degrees of freedom chi(2) test for heterogeneity (p-het). The most significant single SNP (p-trend = 8 x 10(-5)) was not significant at a nominal 5% level after adjusting for population stratification and multiple testing. To evaluate the overall evidence for an excess of positive associations over the proportion expected by chance, we applied two global tests: the admixture maximum likelihood (AML) test and the rank truncated product (RTP) test corrected for population stratification. The admixture maximum likelihood experiment-wise test for association was significant for both the heterogeneity test (p = 0.0031) and the trend test (p = 0.017), but no association was observed using the rank truncated product method for either the heterogeneity test or the trend test (p = 0.12 and p = 0.24, respectively). Genes in the cell-cycle control pathway and genes involved in steroid hormone metabolism and signalling were the main contributors to the association. These results suggest that a proportion of SNPs in these candidate genes are associated with breast cancer risk, but that the effects of individual SNPs is likely to be small. Large sample sizes from multicentre collaboration will be needed to identify associated SNPs with certainty.Association studies in candidate genes have been widely used to search for common low penetrance susceptibility alleles, but few definite associations have been established. We have conducted association studies in breast cancer using an empirical single nucleotide polymorphism (SNP) tagging approach to capture common genetic variation in genes that are candidates for breast cancer based on their known function. We genotyped 710 SNPs in 120 candidate genes in up to 4,400 breast cancer cases and 4,400 controls using a staged design. Correction for population stratification was done using the genomic control method, on the basis of data from 280 genomic control SNPs. Evidence for association with each SNP was assessed using a Cochran-Armitage trend test (p-trend) and a two-degrees of freedom chi(2) test for heterogeneity (p-het). The most significant single SNP (p-trend = 8 x 10(-5)) was not significant at a nominal 5% level after adjusting for population stratification and multiple testing. To evaluate the overall evidence for an excess of positive associations over the proportion expected by chance, we applied two global tests: the admixture maximum likelihood (AML) test and the rank truncated product (RTP) test corrected for population stratification. The admixture maximum likelihood experiment-wise test for association was significant for both the heterogeneity test (p = 0.0031) and the trend test (p = 0.017), but no association was observed using the rank truncated product method for either the heterogeneity test or the trend test (p = 0.12 and p = 0.24, respectively). Genes in the cell-cycle control pathway and genes involved in steroid hormone metabolism and signalling were the main contributors to the association. These results suggest that a proportion of SNPs in these candidate genes are associated with breast cancer risk, but that the effects of individual SNPs is likely to be small. Large sample sizes from multicentre collaboration will be needed to identify associated SNPs with certainty. |
| Audience | Academic |
| Author | Ponder, Bruce A. J Dunning, Alison M Tyrer, Jonathan Easton, Douglas F Pharoah, Paul D. P |
| AuthorAffiliation | 1 Department of Oncology, University of Cambridge, Cambridge, United Kingdom University of Michigan, United States of America 2 Strangeways Research Laboratory, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom |
| AuthorAffiliation_xml | – name: University of Michigan, United States of America – name: 2 Strangeways Research Laboratory, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom – name: 1 Department of Oncology, University of Cambridge, Cambridge, United Kingdom |
| Author_xml | – sequence: 1 givenname: Paul D. P surname: Pharoah fullname: Pharoah, Paul D. P – sequence: 2 givenname: Jonathan surname: Tyrer fullname: Tyrer, Jonathan – sequence: 3 givenname: Alison M surname: Dunning fullname: Dunning, Alison M – sequence: 4 givenname: Douglas F surname: Easton fullname: Easton, Douglas F – sequence: 5 givenname: Bruce A. J surname: Ponder fullname: Ponder, Bruce A. J |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/17367212$$D View this record in MEDLINE/PubMed |
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| ContentType | Journal Article |
| Copyright | COPYRIGHT 2007 Public Library of Science 2007 Pharoah et al. 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 credited: Pharoah PDP, Tyrer J, Dunning AM, Easton DF, Ponder BAJ, et al. (2007) Association between Common Variation in 120 Candidate Genes and Breast Cancer Risk. PLoS Genet 3(3): e42. doi:10.1371/journal.pgen.0030042 2007 Pharoah et al. 2007 |
| Copyright_xml | – notice: COPYRIGHT 2007 Public Library of Science – notice: 2007 Pharoah et al. 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 credited: Pharoah PDP, Tyrer J, Dunning AM, Easton DF, Ponder BAJ, et al. (2007) Association between Common Variation in 120 Candidate Genes and Breast Cancer Risk. PLoS Genet 3(3): e42. doi:10.1371/journal.pgen.0030042 – notice: 2007 Pharoah et al. 2007 |
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| Snippet | Association studies in candidate genes have been widely used to search for common low penetrance susceptibility alleles, but few definite associations have... Association studies in candidate genes have been widely used to search for common low penetrance susceptibility alleles, but few definite associations have... |
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| SubjectTerms | Aged Breast cancer Breast Neoplasms - genetics Cancer Case-Control Studies Female Gene Frequency Genes Genes, Neoplasm - genetics Genetic aspects Genetic Predisposition to Disease - genetics Genetic variation Genetics Genetics and Genomics Genome, Human - genetics Health risk assessment Homo (Human) Humans Medical research Middle Aged Neoplasm Staging Polymorphism, Single Nucleotide - genetics Public Health and Epidemiology Risk factors |
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| Title | Association between Common Variation in 120 Candidate Genes and Breast Cancer Risk |
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