Genetic variants of glucose metabolism and exposure to smoking in African American breast cancer

in Endocrine-Related Cancer
Authors:
Su Yon JungTranslational Sciences Section, School of Nursing, University of California Los Angeles, Los Angeles, California, USA
Jonsson Comprehensive Cancer Center, University of California Los Angeles, Los Angeles, California, USA

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Jeanette C PappJonsson Comprehensive Cancer Center, University of California Los Angeles, Los Angeles, California, USA
Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA

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Eric M SobelDepartment of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
Department of Computational Medicine, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA

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Matteo PellegriniDepartment of Molecular, Cell and Developmental Biology, Life Sciences Division, University of California Los Angeles, Los Angeles, California, USA

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Herbert YuCancer Epidemiology Program, University of Hawaii Cancer Center, Honolulu, Hawaii, USA

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Correspondence should be addressed to S Jung: sjung@sonnet.ucla.edu
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Insulin resistance (IR) is a well-established risk factor for breast cancer (BC) development in African American (AA) postmenopausal women. While obesity and IR are more prevalent in AA than in white women, they are under-represented in genome-wide studies for systemic regulation of IR. By examining 780 genome-wide IR single-nucleotide polymorphisms (SNPs) available in our data, we tested 4689 AA women in a Random Survival Forest framework. With 37 BC-associated lifestyle factors, we conducted a gene–environment interaction analysis to estimate risk prediction for BC with the most influential genetic and behavioral factors and evaluated their combined and joint effects on BC risk. By accounting for variations of individual SNPs in BC in the prediction model, we detected four fasting glucose–associated SNPs in PCSK1, SPC25, ADCY5, and MTNR1B and three lifestyle factors (smoking, oral contraceptive use, and age at menopause) as the most predictive markers for BC risk. Our joint analysis of risk genotypes and lifestyle with smoking revealed a synergistic effect on the increased risk of BC, particularly estrogen/progesterone positive (ER/PR+) BC, in a gene–lifestyle dose-dependent manner. The joint effect of smoking was more substantial in women with prolonged exposure to cigarette smoking and female hormones. The top genome-wide association-SNPs associated with metabolic biomarkers in combination with lifestyles synergistically increase the predictability of invasive ER/PR+ BC risk among AA women. Our findings highlight generically targeted preventive interventions for women who carry particular risk genotypes and lifestyles.

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