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

Synergistic Effects of Genetic Variants of Glucose Homeostasis and Lifelong Exposures to Cigarette Smoking, Female Hormones, and Dietary Fat Intake on Primary Colorectal Cancer Development in African and Hispanic/Latino American Women

BACKGROUND

Disparities in cancer genomic science exist among racial/ethnic minorities. Particularly, African American (AA) and Hispanic/Latino American (HA) women, the 2 largest minorities, are underrepresented in genetic/genome-wide studies for cancers and their risk factors. We conducted on AA and HA postmenopausal women a genomic study for insulin resistance (IR), the main biologic mechanism underlying colorectal cancer (CRC) carcinogenesis owing to obesity.

METHODS

With 780 genome-wide IR-specific single-nucleotide polymorphisms (SNPs) among 4,692 AA and 1,986 HA women, we constructed a CRC-risk prediction model. Along with these SNPs, we incorporated CRC-associated lifestyles in the model of each group and detected the topmost influential genetic and lifestyle factors. Further, we estimated the attributable risk of the topmost risk factors shared by the groups to explore potential factors that differentiate CRC risk between these groups.

RESULTS

In both groups, we detected IR-SNPs in PCSK1 (in AA) and IFT172, GCKR, and NRBP1 (in HA) and risk lifestyles, including long lifetime exposures to cigarette smoking and endogenous female hormones and daily intake of polyunsaturated fatty acids (PFA), as the topmost predictive variables for CRC risk. Combinations of those top genetic- and lifestyle-markers synergistically increased CRC risk. Of those risk factors, dietary PFA intake and long lifetime exposure to female hormones may play a key role in mediating racial disparity of CRC incidence between AA and HA women.

CONCLUSIONS

Our results may improve CRC risk prediction performance in those medically/scientifically underrepresented groups and lead to the development of genetically informed interventions for cancer prevention and therapeutic effort, thus contributing to reduced cancer disparities in those minority subpopulations.

Identification of genetic variants for blood insulin level in sex-stratified Korean population and evaluation of the causal relationship between blood insulin level and polycystic ovary syndrome

BACKGROUND

Blood insulin level is an important risk factor for numerous disorders. Individual blood insulin level is known to be substantially influenced by genetic factors. Several genetic association studies identified a number of genetic variants for blood insulin level, but none of them was from a sex-stratified population.

OBJECTIVE

This study aimed to identify male- and female-specific genetic variants related to blood insulin level and to evaluate the causal relationship between blood insulin level and polycystic ovary syndrome (PCOS) that is likely caused by high insulin in Korean women.

METHODS

A genome-wide association study was conducted to identify genetic variants influencing blood insulin level in males (N = 4183) and females (N = 4659) in the Korean population. Two-sample Mendelian randomization (MR) analysis was used to investigate the causal effects of the insulin variants identified from GWAS on PCOS in Korean women. Genetic association data for PCOS were obtained from a PCOS study cohort (946 cases, 976 controls) in Ewha Womans University Hospital.

RESULTS

GWAS linear regression analysis identified 13 female-specific SNPs and 13 male-specific SNPs showing suggestive associations (P < 10^-5) with blood insulin level. The results from two-sample MR analysis using the GWAS variants for PCOS indicated that genetically determined insulin level was not associated with the risk of PCOS in Korean women.

CONCLUSION

This study identified sex-specific genetic variants showing associations with insulin for the first time in East Asian populations. In addition, MR analysis using variants discovered from Korean women revealed that genetically determined high level of insulin is not the cause of PCOS.

Multi-Omics Data Analysis Uncovers Molecular Networks and Gene Regulators for Metabolic Biomarkers

The insulin-like growth factors (IGFs)/insulin resistance (IR) axis is the major metabolic hormonal pathway mediating the biologic mechanism of several complex human diseases, including type 2 diabetes (T2DM) and cancers. The genomewide association study (GWAS)-based approach has neither fully characterized the phenotype variation nor provided a comprehensive understanding of the regulatory biologic mechanisms. We applied systematic genomics to integrate our previous GWAS data for IGF-I and IR with multi-omics datasets, e.g., whole-blood expression quantitative loci, molecular pathways, and gene network, to capture the full range of genetic functionalities associated with IGF-I/IR and key drivers (KDs) in gene-regulatory networks. We identified both shared (e.g., T2DM, lipid metabolism, and estimated glomerular filtration signaling) and IR-specific (e.g., mechanistic target of rapamycin, phosphoinositide 3-kinases, and erb-b2 receptor tyrosine kinase 4 signaling) molecular biologic processes of IGF-I/IR axis regulation. Next, by using tissue-specific gene–gene interaction networks, we identified both well-established (e.g., IRS1 and IGF1R) and novel (e.g., AKT1, HRAS, and JAK1) KDs in the IGF-I/IR-associated subnetworks. Our results, if validated in additional genomic studies, may provide robust, comprehensive insights into the mechanisms of IGF-I/IR regulation and highlight potential novel genetic targets as preventive and therapeutic strategies for the associated diseases, e.g., T2DM and cancers.

Genetically Predicted C-Reactive Protein Associated With Postmenopausal Breast Cancer Risk: Interrelation With Estrogen and Cancer Molecular Subtypes Using Mendelian Randomization

Background

Immune-related etiologic pathways that influence breast cancer risk are incompletely understood and may be confounded by lifestyles or reverse causality. Using a Mendelian randomization (MR) approach, we investigated the potential causal relationship between genetically elevated C-reactive protein (CRP) concentrations and primary invasive breast cancer risk in postmenopausal women.

Methods

We used individual-level data obtained from 10,179 women, including 537 who developed breast cancer, from the Women’s Health Initiative Database for Genotypes and Phenotypes Study, which consists of five genome-wide association (GWA) studies. We examined 61 GWA single-nucleotide polymorphisms (SNPs) previously associated with CRP. We employed weighted/penalized weighted–medians and MR gene–environment interactions that allow instruments’ invalidity to some extent and attenuate the heterogeneous estimates of outlying SNPs.

Results

In lifestyle-stratification analyses, genetically elevated CRP decreased risk for breast cancer in exogenous estrogen-only, estrogen + progestin, and past oral contraceptive (OC) users, but only among relatively short-term users (<5 years). Estrogen-only users for ≥5 years had more profound CRP-decreased breast cancer risk in dose–response fashion, whereas past OC users for ≥5 years had CRP-increased cancer risk. Also, genetically predicted CRP was strongly associated with increased risk for hormone-receptor positive or human epidermal growth factor receptor-2 negative breast cancer.

Conclusions

Our findings may provide novel evidence on the immune-related molecular pathways linking to breast cancer risk and suggest potential clinical use of CRP to predict the specific cancer subtypes. Our findings suggest potential interventions targeting CRP–inflammatory markers to reduce breast cancer risk.

Pro-inflammatory cytokine polymorphisms and interactions with dietary alcohol and estrogen, risk factors for invasive breast cancer using a post genome-wide analysis for gene-gene and gene-lifestyle interaction

Molecular and genetic immune-related pathways connected to breast cancer and lifestyles in postmenopausal women are not fully characterized. In this study, we explored the role of pro-inflammatory cytokines such as C-reactive protein (CRP) and interleukin-6 (IL-6) in those pathways at the genome-wide level. With single-nucleotide polymorphisms (SNPs) in the biomarkers and lifestyles together, we further constructed risk profiles to improve predictability for breast cancer. Our earlier genome-wide association gene-environment interaction study used large cohort data from the Women's Health Initiative Database for Genotypes and Phenotypes Study and identified 88 SNPs associated with CRP and IL-6. For this study, we added an additional 68 SNPs from previous GWA studies, and together with 48 selected lifestyles, evaluated for the association with breast cancer risk via a 2-stage multimodal random survival forest and generalized multifactor dimensionality reduction methods. Overall and in obesity strata (by body mass index, waist, waist-to-hip ratio, exercise, and dietary fat intake), we identified the most predictive genetic and lifestyle variables. Two SNPs (SALL1 rs10521222 and HLA-DQA1 rs9271608) and lifestyles, including alcohol intake, lifetime cumulative exposure to estrogen, and overall and visceral obesity, are the most common and strongest predictive markers for breast cancer across the analyses. The risk profile that combined those variables presented their synergistic effect on the increased breast cancer risk in a gene-lifestyle dose-dependent manner. Our study may contribute to improved predictability for breast cancer and suggest potential interventions for the women with the risk genotypes and lifestyles to reduce their breast cancer risk.

Genetic Variation and Hot Flashes: A Systematic Review

CONTEXT

Approximately 70% of women report experiencing vasomotor symptoms (VMS, hot flashes and/or night sweats). The etiology of VMS is not clearly understood but may include genetic factors.

EVIDENCE ACQUISITION

We searched PubMed and Embase in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidance. We included studies on associations between genetic variation and VMS. We excluded studies focused on medication interventions or prevention or treatment of breast cancer.

EVIDENCE SYNTHESIS

Of 202 unique citations, 18 citations met the inclusion criteria. Study sample sizes ranged from 51 to 17 695. Eleven of the 18 studies had fewer than 500 participants; 2 studies had 1000 or more. Overall, statistically significant associations with VMS were found for variants in 14 of the 26 genes assessed in candidate gene studies. The cytochrome P450 family 1 subfamily A member 1 (CYP1B1) gene was the focus of the largest number (n = 7) of studies, but strength and statistical significance of associations of CYP1B1 variants with VMS were inconsistent. A genome-wide association study reported statistically significant associations between 14 single-nucleotide variants in the tachykinin receptor 3 gene and VMS. Heterogeneity across trials regarding VMS measurement methods and effect measures precluded quantitative meta-analysis; there were few studies of each specific genetic variant.

CONCLUSIONS

Genetic variants are associated with VMS. The associations are not limited to variations in sex-steroid metabolism genes. However, studies were few and future studies are needed to confirm and extend these findings.

Mendelian Randomization Study: The Association Between Metabolic Pathways and Colorectal Cancer Risk

Background: The roles of obesity-related biomarkers and their molecular pathways in the development of postmenopausal colorectal cancer (CRC) have been inconclusive. We examined insulin resistance (IR) as a major hormonal pathway mediating the association between obesity and CRC risk in a Mendelian randomization (MR) framework.

Methods: We performed MR analysis using individual-level data of 11,078 non-Hispanic white postmenopausal women from our earlier genome-wide association study. We identified four independent single-nucleotide polymorphisms associated with fasting glucose (FG), three with fasting insulin (FI), and six with homeostatic model assessment–IR (HOMA-IR), which were not associated with obesity. We estimated hazard ratios (HRs) for CRC by adjusting for potential confounding factors plus genetic principal components.

Results: Overall, we observed no direct association between combined 13 IR genetic instruments and CRC risk (HR = 0.96, 95% confidence interval [CI]: 0.78–1.17). In phenotypic analysis, genetically raised HOMA-IR exhibited its effects on the increased risk and FG and FI on the reduced risk for CRC, but with a lack of statistical power. Subgroup analyses by physical activity level and dietary fat intake with combined phenotypes showed that genetically determined IR was associated with reduced CRC risk in both physical activity-stratified (single contributor: MTRR rs722025; HR = 0.12, 95% CI: 0.02–0.62) and high-fat diet subgroups (main contributor: G6PC2 rs560887; HR = 0.59, 95% CI: 0.37–0.94).

Conclusions: Complex evidence was observed for a potential causal association between IR and CRC risk. Our findings may provide an additional value of intervention trials to lower IR and reduce CRC risk.

Post Genome-Wide Gene-Environment Interaction Study Using Random Survival Forest: Insulin Resistance, Lifestyle Factors, and Colorectal Cancer Risk

Molecular and genetic pathways of insulin resistance (IR) connecting colorectal cancer and obesity factors in postmenopausal women remain inconclusive. We examined the IR pathways on both genetic and phenotypic perspectives at the genome-wide level. We further constructed colorectal cancer risk profiles with the most predictive IR SNPs and lifestyle factors. In our earlier genome-wide association gene-environmental interaction study, we used data from a large cohort of postmenopausal women in the Women's Health Initiative Database for Genotypes and Phenotypes Study and identified 58 SNPs in relation to IR phenotypes. In this study, we evaluated the identified IR SNPs and selected 34 lifestyles for their association with colorectal cancer risk in a total of 11,078 women (including 736 women with colorectal cancer) using a 2-stage multimodal random survival forest analysis. In overall and subgroup (defined via body mass index, exercise, and dietary-fat intake) analyses, we identified 2 SNPs (LINC00460 rs1725459 and MTRR rs722025) and lifetime cumulative exposure to estrogen (oral contraceptive use) and cigarette smoking as the most common and strongest predictive markers for colorectal cancer risk across the analyses. The combinations of genetic and lifestyle factors had much greater impact on colorectal cancer risk than any individual risk factors, and a possible synergism existed to increase colorectal cancer risk in a gene-behavior dose-dependent manner. Our findings may inform research on the role of IR in the etiology of colorectal cancer and contribute to more accurate prediction of colorectal cancer risk, suggesting potential intervention strategies for women with specific genotypes and lifestyles to reduce their colorectal cancer risk.

Post genome-wide gene-environment interaction study: The effect of genetically driven insulin resistance on breast cancer risk using Mendelian randomization

PURPOSE

The role of insulin resistance (IR) in developing postmenopausal breast cancer has not been thoroughly resolved and may be confounded by lifestyle factors such as obesity. We examined whether genetically determined IR is causally associated with breast cancer risk.

METHODS

We conducted Mendelian randomization (MR) analyses using individual-level data from our previous meta-analysis of a genome-wide association study (GWAS) (n = 11,109 non-Hispanic white postmenopausal women). Four single-nucleotide polymorphisms were associated with fasting glucose (FG), 2 with fasting insulin (FI), and 6 with homeostatic model assessment-IR (HOMA-IR) but were not associated with obesity. We used this GWAS to employ hazard ratios (HRs) for breast cancer risk by adjusting for potential confounding factors.

RESULTS

No direct association was observed between comprising 12 IR genetic instruments and breast cancer risk (HR = 0.93, 95% CI: 0.76-1.14). In phenotype-specific analysis, genetically elevated FG was associated with reduced risk for breast cancer (main contributor of this MR-effect estimate: G6PC2 rs13431652; HR = 0.59, 95% CI: 0.35-0.99). Genetically driven FI and HOMA-IR were not significantly associated. Stratification analyses by body mass index, exercise, and dietary fat intake with combined phenotypes showed that genetically elevated IR was associated with greater breast cancer risk in overall obesity and inactive subgroups (single contributor: MTRR/LOC729506 rs13188458; HR = 2.21, 95% CI: 1.03-4.75).

CONCLUSIONS

We found complex evidence for causal association between IR and risk of breast cancer, which may support the potential value of intervention trials to lower IR and reduce breast cancer risk.

Breast Cancer Risk and Insulin Resistance: Post Genome-Wide Gene-Environment Interaction Study Using a Random Survival Forest

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.