The effect of genetic variants on the relationship between statins and breast cancer in postmenopausal women in the Women's Health Initiative observational study.

MedStar author(s):
Citation: Breast Cancer Research & Treatment. 167(3):741-749, 2018 02.PMID: 29063981Institution: MedStar Health Research InstituteForm of publication: Journal ArticleMedline article type(s): Journal ArticleSubject headings: *Breast Neoplasms/dt [Drug Therapy] | *Cholesterol/ge [Genetics] | *Genetic Predisposition to Disease | *Hydroxymethylglutaryl-CoA Reductase Inhibitors/ad [Administration & Dosage] | Aged | Anticholesteremic Agents/ad [Administration & Dosage] | Anticholesteremic Agents/ae [Adverse Effects] | Breast Neoplasms/ge [Genetics] | Breast Neoplasms/pa [Pathology] | Cholesterol/me [Metabolism] | Female | Genome-Wide Association Study | Humans | Hydroxymethylglutaryl-CoA Reductase Inhibitors/ae [Adverse Effects] | Middle Aged | Polymorphism, Single Nucleotide/ge [Genetics] | Postmenopause | Risk Assessment | Risk Factors | Women's HealthYear: 2018Local holdings: Available online from MWHC library: 1997 - presentISSN:
  • 0167-6806
Name of journal: Breast cancer research and treatmentAbstract: CONCLUSIONS: We found no evidence of SNP interactions with statin usage for breast cancer risk in a population of 3374 individuals. These results suggest that genome-wide common genetic variants do not moderate the association between statin usage and breast cancer in the population of women in the Women's Health Initiative.METHODS: To identify candidate gene-statin interactions, we tested interactions between 22 SNPS in nine candidate genes implicated in the effect of statins on lipid metabolism in 1687 cases and 1687 controls. We then evaluated statin use interaction with the remaining 30,380 SNPs available in this sample from the CGEMS GWAS study.PURPOSE: Statins have been postulated to have chemopreventive activity against breast cancer. We evaluated whether germline genetic polymorphisms modified the relationship between statins and breast cancer risk using data from the Women's Health Initiative. We evaluated these interactions using both candidate gene and agnostic genome-wide approaches.RESULTS: After adjusting for multiple comparisons, no SNP interactions with statin usage and risk of breast cancer were statistically significant in either the candidate genes or genome-wide approaches.All authors: Beebe-Dimmer JL, Bock CH, Cote ML, Desai P, Dyson G, Hou L, Howard BV, Jay AM, Prentice R, Purrington K, Simon MSOriginally published: Breast Cancer Research & Treatment. , 2017 Oct 24Fiscal year: FY2018Digital Object Identifier: Date added to catalog: 2017-11-10
Holdings
Item type Current library Collection Call number Status Date due Barcode
Journal Article MedStar Authors Catalog Article 29063981 Available 29063981

Available online from MWHC library: 1997 - present

CONCLUSIONS: We found no evidence of SNP interactions with statin usage for breast cancer risk in a population of 3374 individuals. These results suggest that genome-wide common genetic variants do not moderate the association between statin usage and breast cancer in the population of women in the Women's Health Initiative.

METHODS: To identify candidate gene-statin interactions, we tested interactions between 22 SNPS in nine candidate genes implicated in the effect of statins on lipid metabolism in 1687 cases and 1687 controls. We then evaluated statin use interaction with the remaining 30,380 SNPs available in this sample from the CGEMS GWAS study.

PURPOSE: Statins have been postulated to have chemopreventive activity against breast cancer. We evaluated whether germline genetic polymorphisms modified the relationship between statins and breast cancer risk using data from the Women's Health Initiative. We evaluated these interactions using both candidate gene and agnostic genome-wide approaches.

RESULTS: After adjusting for multiple comparisons, no SNP interactions with statin usage and risk of breast cancer were statistically significant in either the candidate genes or genome-wide approaches.

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