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Genetic variants in the MRPS30 region and postmenopausal breast cancer risk

Ying Huang1, Dennis G Ballinger2, James Y Dai1, Ulrike Peters1, David A Hinds3, David R Cox2, Erica Beilharz2, Rowan T Chlebowski4, Jacques E Rossouw5, Anne McTiernan1, Thomas Rohan6 and Ross L Prentice1*

Author Affiliations

1 Fred Hutchinson Cancer Research Center, Divisions of Public Health Sciences, and Vaccine and Infectious Diseases, 1100 Fairview Avenue North, Seattle, WA 98109-1024, USA

2 Perlegen Sciences Inc., 2021 Stierlin Court, Mountain View, CA 94043, USA

3 23andMe, Inc., 1390 Shorebird Way, Mountain View, CA 94043, USA

4 Harbor-UCLA Research and Education Institute, Division of Medical Oncology/Hematology, 1124 W. Carson Street, Bldg J-3, Torrance, CA 90502-2064, USA

5 National Institutes of Health, National Heart, Lung and Blood Institute, Prevention and Population Sciences Program, 6701 Rockledge Drive, Bethesda, MD 20892-7935, USA

6 Albert Einstein College of Medicine, Department of Epidemiology and Population Health, 1300 Morris Park Avenue, Bronx, NY 10461, USA

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Genome Medicine 2011, 3:42  doi:10.1186/gm258

Published: 24 June 2011



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.


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 (r2) 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.


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.


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.