Dataset Information

Genetic Variants in Metabolic Signaling Pathways and Their Interaction with Lifestyle Factors on Breast Cancer Risk: A Random Survival Forest Analysis.

ABSTRACT: Genetic variants in the insulin-like growth factor-I (IGF-I)/insulin resistance axis may interact with lifestyle factors, influencing postmenopausal breast cancer risk, but these interrelated pathways are not fully understood. In this study, we examined 54 single-nucleotide polymorphisms (SNP) in genes related to IGF-I/insulin phenotypes and signaling pathways and lifestyle factors in relation to postmenopausal breast cancer, using data from 6,567 postmenopausal women in the Women's Health Initiative Harmonized and Imputed Genome-Wide Association Studies. We used a machine-learning method, two-stage random survival forest analysis. We identified three genetic variants (AKT1 rs2494740, AKT1 rs2494744, and AKT1 rs2498789) and two lifestyle factors [body mass index (BMI) and dietary alcohol intake] as the top five most influential predictors for breast cancer risk. The combination of the three SNPs, BMI, and alcohol consumption (?1 g/day) significantly increased the risk of breast cancer in a gene and lifestyle dose-dependent manner. Our findings provide insight into gene-lifestyle interactions and will enable researchers to focus on individuals with risk genotypes to promote intervention strategies. These data also suggest potential genetic targets in future intervention/clinical trials for cancer prevention in order to reduce the risk for breast cancer in postmenopausal women. Cancer Prev Res; 11(1); 44-51. ©2017 AACR.

SUBMITTER: Jung SY

PROVIDER: S-EPMC5754228 | biostudies-literature | 2018 Jan

REPOSITORIES: biostudies-literature

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Genetic Variants in Metabolic Signaling Pathways and Their Interaction with Lifestyle Factors on Breast Cancer Risk: A Random Survival Forest Analysis.

Jung Su Yon SY Papp Jeanette C JC Sobel Eric M EM Zhang Zuo-Feng ZF

Cancer prevention research (Philadelphia, Pa.) 20171026 1

Genetic variants in the insulin-like growth factor-I (IGF-I)/insulin resistance axis may interact with lifestyle factors, influencing postmenopausal breast cancer risk, but these interrelated pathways are not fully understood. In this study, we examined 54 single-nucleotide polymorphisms (SNP) in genes related to IGF-I/insulin phenotypes and signaling pathways and lifestyle factors in relation to postmenopausal breast cancer, using data from 6,567 postmenopausal women in the Women's Health Initi ...[more]

PMID: 29074537

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Project description:Obesity-insulin connections have been considered potential risk factors for postmenopausal breast cancer, and the association between insulin resistance (IR) genotypes and phenotypes can be modified by obesity-lifestyle factors, affecting breast cancer risk. In this study, we explored the role of IR in those pathways at the genome-wide level. We identified IR-genetic factors and selected lifestyles to generate risk profiles for postmenopausal breast cancer. Using large-scale cohort data from postmenopausal women in the Women's Health Initiative Database for Genotypes and Phenotypes Study, our previous genome-wide association gene-behavior interaction study identified 58 loci for associations with IR phenotypes (homeostatic model assessment-IR, hyperglycemia, and hyperinsulinemia). We evaluated those single-nucleotide polymorphisms (SNP) and additional 31 lifestyles in relation to breast cancer risk by conducting a two-stage multimodal random survival forest analysis. We identified the most predictive genetic and lifestyle variables in overall and subgroup analyses [stratified by body mass index (BMI), exercise, and dietary fat intake]. Two SNPs (LINC00460 rs17254590 and MKLN1 rs117911989), exogenous factors related to lifetime cumulative exposure to estrogen, BMI, and dietary alcohol consumption were the most common influential factors across the analyses. Individual SNPs did not have significant associations with breast cancer, but SNPs and lifestyles combined synergistically increased the risk of breast cancer in a gene-behavior, dose-dependent manner. These findings may contribute to more accurate predictions of breast cancer and suggest potential intervention strategies for women with specific genetic and lifestyle factors to reduce their breast cancer risk. SIGNIFICANCE: These findings identify insulin resistance SNPs in combination with lifestyle as synergistic factors for breast cancer risk, suggesting lifestyle changes can prevent breast cancer in women who carry the risk genotypes.

Project description:BACKGROUND:Lifestyle factors such as diet and physical activity have been shown to modify the association between fat mass and obesity-associated (FTO) gene variants and metabolic traits in several populations; however, there are no gene-lifestyle interaction studies, to date, among Asian Indians living in India. In this study, we examined whether dietary factors and physical activity modified the association between two FTO single nucleotide polymorphisms (rs8050136 and rs11076023) (SNPs) and obesity traits and type 2 diabetes (T2D). METHODS:The study included 734 unrelated T2D and 884 normal glucose-tolerant (NGT) participants randomly selected from the urban component of the Chennai Urban Rural Epidemiology Study (CURES). Dietary intakes were assessed using a validated interviewer administered semi-quantitative food frequency questionnaire (FFQ). Physical activity was based upon the self-report. Interaction analyses were performed by including the interaction terms in the linear/logistic regression model. RESULTS:There was a significant interaction between SNP rs8050136 and carbohydrate intake (% energy) (Pinteraction?=?0.04), where the 'A' allele carriers had 2.46 times increased risk of obesity than those with 'CC' genotype (P?=?3.0 × 10(-5)) among individuals in the highest tertile of carbohydrate intake (% energy, 71 %). A significant interaction was also observed between SNP rs11076023 and dietary fibre intake (Pinteraction?=?0.0008), where individuals with AA genotype who are in the 3(rd) tertile of dietary fibre intake had 1.62 cm lower waist circumference than those with 'T' allele carriers (P?=?0.02). Furthermore, among those who were physically inactive, the 'A' allele carriers of the SNP rs8050136 had 1.89 times increased risk of obesity than those with 'CC' genotype (P?=?4.0 × 10(-5)). CONCLUSIONS:This is the first study to provide evidence for a gene-diet and gene-physical activity interaction on obesity and T2D in an Asian Indian population. Our findings suggest that the association between FTO SNPs and obesity might be influenced by carbohydrate and dietary fibre intake and physical inactivity. Further understanding of how FTO gene influences obesity and T2D through dietary and exercise interventions is warranted to advance the development of behavioral intervention and personalised lifestyle strategies, which could reduce the risk of metabolic diseases in this Asian Indian population.

Dataset Information

Genetic Variants in Metabolic Signaling Pathways and Their Interaction with Lifestyle Factors on Breast Cancer Risk: A Random Survival Forest Analysis.

Publications

Genetic Variants in Metabolic Signaling Pathways and Their Interaction with Lifestyle Factors on Breast Cancer Risk: A Random Survival Forest Analysis.

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