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American Association for Cancer Research, Cancer Prevention Research, 1(12), p. 31-42, 2019

DOI: 10.1158/1940-6207.capr-18-0180

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Genome-Wide Meta-analysis of Gene–Environmental Interaction for Insulin Resistance Phenotypes and Breast Cancer Risk in Postmenopausal Women

This paper was not found in any repository, but could be made available legally by the author.
This paper was not found in any repository, but could be made available legally by the author.

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Abstract

Abstract Insulin resistance (IR)–related genetic variants are possibly associated with breast cancer, and the gene–phenotype–cancer association could be modified by lifestyle factors including obesity, physical inactivity, and high-fat diet. Using data from postmenopausal women, a population highly susceptible to obesity, IR, and increased risk of breast cancer, we implemented a genome-wide association study (GWAS) in two steps: (1) GWAS meta-analysis of gene–environmental (i.e., behavioral) interaction (G*E) for IR phenotypes (hyperglycemia, hyperinsulinemia, and homeostatic model assessment–insulin resistance) and (2) after the G*E GWAS meta-analysis, the identified SNPs were tested for their associations with breast cancer risk in overall or subgroup population, where the SNPs were identified at genome-wide significance. We found 58 loci (55 novel SNPs; 5 index SNPs and 6 SNPs, independent of each other) that are associated with IR phenotypes in women overall or women stratified by obesity, physical activity, and high-fat diet; among those 58 loci, 29 (26 new loci; 2 index SNPs and 2 SNPs, independently) were associated with postmenopausal breast cancer. Our study suggests that a number of newly identified SNPs may have their effects on glucose intolerance by interplaying with obesity and other lifestyle factors, and a substantial proportion of these SNPs’ susceptibility can also interact with the lifestyle factors to ultimately influence breast cancer risk. These findings may contribute to improved prediction accuracy for cancer and suggest potential intervention strategies for those women carrying genetic risk that will reduce their breast cancer risk.