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Genetic variants in the MRPS30 region and postmenopausal breast cancer risk

BACKGROUND: Genome-wide association studies have identified several genomic regions that are associated with breast cancer risk, but these provide an explanation for only a small fraction of familial breast cancer aggregation. Genotype by environment interactions may contribute further to such expla...

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Autores principales: Huang, Ying, Ballinger, Dennis G, Dai, James Y, Peters, Ulrike, Hinds, David A, Cox, David R, Beilharz, Erica, Chlebowski, Rowan T, Rossouw, Jacques E, McTiernan, Anne, Rohan, Thomas, Prentice, Ross L
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2011
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Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3218816/
https://www.ncbi.nlm.nih.gov/pubmed/21702935
http://dx.doi.org/10.1186/gm258
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author Huang, Ying
Ballinger, Dennis G
Dai, James Y
Peters, Ulrike
Hinds, David A
Cox, David R
Beilharz, Erica
Chlebowski, Rowan T
Rossouw, Jacques E
McTiernan, Anne
Rohan, Thomas
Prentice, Ross L
author_facet Huang, Ying
Ballinger, Dennis G
Dai, James Y
Peters, Ulrike
Hinds, David A
Cox, David R
Beilharz, Erica
Chlebowski, Rowan T
Rossouw, Jacques E
McTiernan, Anne
Rohan, Thomas
Prentice, Ross L
author_sort Huang, Ying
collection PubMed
description BACKGROUND: Genome-wide association studies have identified several genomic regions that are associated with breast cancer risk, but these provide an explanation for only a small fraction of familial breast cancer aggregation. Genotype by environment interactions may contribute further to such explanation, and may help to refine the genomic regions of interest. METHODS: We examined genotypes for 4,988 SNPs, selected from recent genome-wide studies, and four randomized hormonal and dietary interventions among 2,166 women who developed invasive breast cancer during the intervention phase of the Women's Health Initiative (WHI) clinical trial (1993 to 2005), and one-to-one matched controls. These SNPs derive from 3,224 genomic regions having pairwise squared correlation (r(2)) between adjacent regions less than 0.2. Breast cancer and SNP associations were identified using a test statistic that combined evidence of overall association with evidence for SNPs by intervention interaction. RESULTS: The combined 'main effect' and interaction test led to a focus on two genomic regions, the fibroblast growth factor receptor two (FGFR2) and the mitochondrial ribosomal protein S30 (MRPS30) regions. The ranking of SNPs by significance level, based on this combined test, was rather different from that based on the main effect alone, and drew attention to the vicinities of rs3750817 in FGFR2 and rs7705343 in MRPS30. Specifically, rs7705343 was included with several FGFR2 SNPs in a group of SNPs having an estimated false discovery rate < 0.05. In further analyses, there were suggestions (nominal P < 0.05) that hormonal and dietary intervention hazard ratios varied with the number of minor alleles of rs7705343. CONCLUSIONS: Genotype by environment interaction information may help to define genomic regions relevant to disease risk. Combined main effect and intervention interaction analyses raise novel hypotheses concerning the MRPS30 genomic region and the effects of hormonal and dietary exposures on postmenopausal breast cancer risk.
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spelling pubmed-32188162011-11-18 Genetic variants in the MRPS30 region and postmenopausal breast cancer risk Huang, Ying Ballinger, Dennis G Dai, James Y Peters, Ulrike Hinds, David A Cox, David R Beilharz, Erica Chlebowski, Rowan T Rossouw, Jacques E McTiernan, Anne Rohan, Thomas Prentice, Ross L Genome Med Research BACKGROUND: Genome-wide association studies have identified several genomic regions that are associated with breast cancer risk, but these provide an explanation for only a small fraction of familial breast cancer aggregation. Genotype by environment interactions may contribute further to such explanation, and may help to refine the genomic regions of interest. METHODS: We examined genotypes for 4,988 SNPs, selected from recent genome-wide studies, and four randomized hormonal and dietary interventions among 2,166 women who developed invasive breast cancer during the intervention phase of the Women's Health Initiative (WHI) clinical trial (1993 to 2005), and one-to-one matched controls. These SNPs derive from 3,224 genomic regions having pairwise squared correlation (r(2)) between adjacent regions less than 0.2. Breast cancer and SNP associations were identified using a test statistic that combined evidence of overall association with evidence for SNPs by intervention interaction. RESULTS: The combined 'main effect' and interaction test led to a focus on two genomic regions, the fibroblast growth factor receptor two (FGFR2) and the mitochondrial ribosomal protein S30 (MRPS30) regions. The ranking of SNPs by significance level, based on this combined test, was rather different from that based on the main effect alone, and drew attention to the vicinities of rs3750817 in FGFR2 and rs7705343 in MRPS30. Specifically, rs7705343 was included with several FGFR2 SNPs in a group of SNPs having an estimated false discovery rate < 0.05. In further analyses, there were suggestions (nominal P < 0.05) that hormonal and dietary intervention hazard ratios varied with the number of minor alleles of rs7705343. CONCLUSIONS: Genotype by environment interaction information may help to define genomic regions relevant to disease risk. Combined main effect and intervention interaction analyses raise novel hypotheses concerning the MRPS30 genomic region and the effects of hormonal and dietary exposures on postmenopausal breast cancer risk. BioMed Central 2011-06-24 /pmc/articles/PMC3218816/ /pubmed/21702935 http://dx.doi.org/10.1186/gm258 Text en Copyright ©2011 Huang et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research
Huang, Ying
Ballinger, Dennis G
Dai, James Y
Peters, Ulrike
Hinds, David A
Cox, David R
Beilharz, Erica
Chlebowski, Rowan T
Rossouw, Jacques E
McTiernan, Anne
Rohan, Thomas
Prentice, Ross L
Genetic variants in the MRPS30 region and postmenopausal breast cancer risk
title Genetic variants in the MRPS30 region and postmenopausal breast cancer risk
title_full Genetic variants in the MRPS30 region and postmenopausal breast cancer risk
title_fullStr Genetic variants in the MRPS30 region and postmenopausal breast cancer risk
title_full_unstemmed Genetic variants in the MRPS30 region and postmenopausal breast cancer risk
title_short Genetic variants in the MRPS30 region and postmenopausal breast cancer risk
title_sort genetic variants in the mrps30 region and postmenopausal breast cancer risk
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3218816/
https://www.ncbi.nlm.nih.gov/pubmed/21702935
http://dx.doi.org/10.1186/gm258
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