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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.

BackgroundInsulin resistance (IR) is a well-established factor for breast cancer (BC) risk in postmenopausal women, but the interrelated molecular pathways on the methylome are not explicitly described. We conducted a population-level epigenome-wide association (EWA) study for DNA methylation (DNAm) probes that are associated with IR and prospectively correlated with BC development, both overall and in BC subtypes among postmenopausal women.MethodsWe used data from Women's Health Initiative (WHI) ancillary studies for our EWA analyses and evaluated the associations of site-specific DNAm across the genome with IR phenotypes by multiple regressions adjusting for age and leukocyte heterogeneities. For our analysis of the top 20 IR-CpGs with BC risk, we used the WHI and the Cancer Genomic Atlas (TCGA), using multiple Cox proportional hazards and logit regressions, respectively, accounting for age, diabetes, obesity, leukocyte heterogeneities, and tumor purity (for TCGA). We further conducted a Gene Set Enrichment Analysis.ResultsWe detected several EWA-CpGs in TXNIP, CPT1A, PHGDH, and ABCG1. In particular, cg19693031 in TXNIP was replicated in all IR phenotypes, measured by fasting levels of glucose, insulin, and homeostatic model assessment-IR. Of those replicated IR-genes, 3 genes (CPT1A, PHGDH, and ABCG1) were further correlated with BC risk; and 1 individual CpG (cg01676795 in POR) was commonly detected across the 2 cohorts.ConclusionsOur study contributes to better understanding of the interconnected molecular pathways on the methylome between IR and BC carcinogenesis and suggests potential use of DNAm markers in the peripheral blood cells as preventive targets to detect an at-risk group for IR and BC in postmenopausal women.

Tumor subtype and menopausal status are strong predictors of breast cancer (BC) prognosis. We aimed to find and validate subtype- or menopausal-status-specific changes in tumor DNA methylation (DNAm) associated with all-cause mortality or BC progression. Associations between site-specific tumor DNAm and BC prognosis were estimated among The Cancer Genome Atlas participants (n = 692) with Illumina Infinium HumanMethylation450 BeadChip array data. All-cause mortality and BC progression were modeled using Cox proportional hazards models stratified by tumor subtypes, adjusting for age, race, stage, menopausal status, tumor purity, and cell type proportion. Effect measure modification by subtype and menopausal status were evaluated by incorporating a product term with DNAm. Site-specific inference was used to identify subtype- or menopausal-status-specific differentially methylated regions (DMRs) and functional pathways. The validation of the results was carried out on an independent dataset (GSE72308; n = 180). We identified a total of fifteen unique CpG probes that were significantly associated ( P≤1×10-7 with survival outcomes in subtype- or menopausal-status-specific manner. Seven probes were associated with overall survival (OS) or progression-free interval (PFI) for women with luminal A subtype, and four probes were associated with PFI for women with luminal B subtype. Five probes were associated with PFI for post-menopausal women. A majority of significant probes showed a lower risk of OS or BC progression with higher DNAm. We identified subtype- or menopausal-status-specific DMRs and functional pathways of which top associated pathways differed across subtypes or menopausal status. None of significant probes from site-specific analyses met genome-wide significant level in validation analyses while directions and magnitudes of coefficients showed consistent pattern. We have identified subtype- or menopausal-status-specific DNAm biomarkers, DMRs and functional path

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.

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.

IntroductionInsulin resistance (IR)/glucose intolerance is a critical biologic mechanism for the development of colorectal cancer (CRC) in postmenopausal women. Whereas IR and excessive adiposity are more prevalent in African American (AA) women than in White women, AA women are underrepresented in genome-wide studies for systemic regulation of IR and the association with CRC risk.MethodsWith 780 genome-wide IR single-nucleotide polymorphisms (SNPs) among 4,692 AA women, we tested for a causal inference between genetically elevated IR and CRC risk. Furthermore, by incorporating CRC-associated lifestyle factors, we established a prediction model on the basis of gene-environment interactions to generate risk profiles for CRC with the most influential genetic and lifestyle factors.ResutlsIn the pooled Mendelian randomization analysis, the genetically elevated IR was associated with 9 times increased risk of CRC, but with lack of analytic power. By addressing the variation of individual SNPs in CRC in the prediction model, we detected 4 fasting glucose-specific SNPs in GCK, PCSK1, and MTNR1B and 4 lifestyles, including smoking, aging, prolonged lifetime exposure to endogenous estrogen, and high fat intake, as the most predictive markers of CRC risk. Our joint test for those risk genotypes and lifestyles with smoking revealed the synergistically increased CRC risk, more substantially in women with longer-term exposure to cigarette smoking.DiscussionOur findings may improve CRC prediction ability among medically underrepresented AA women and highlight genetically informed preventive interventions (e.g., smoking cessation; CRC screening to longer-term smokers) for those women at high risk with risk genotypes and behavioral patterns.

IntroductionInsulin resistance (IR)/glucose intolerance is a critical biologic mechanism for the development of colorectal cancer (CRC) in postmenopausal women. Whereas IR and excessive adiposity are more prevalent in African American (AA) women than in White women, AA women are underrepresented in genome-wide studies for systemic regulation of IR and the association with CRC risk.MethodsWith 780 genome-wide IR single-nucleotide polymorphisms (SNPs) among 4,692 AA women, we tested for a causal inference between genetically elevated IR and CRC risk. Furthermore, by incorporating CRC-associated lifestyle factors, we established a prediction model on the basis of gene-environment interactions to generate risk profiles for CRC with the most influential genetic and lifestyle factors.ResutlsIn the pooled Mendelian randomization analysis, the genetically elevated IR was associated with 9 times increased risk of CRC, but with lack of analytic power. By addressing the variation of individual SNPs in CRC in the prediction model, we detected 4 fasting glucose-specific SNPs in GCK, PCSK1, and MTNR1B and 4 lifestyles, including smoking, aging, prolonged lifetime exposure to endogenous estrogen, and high fat intake, as the most predictive markers of CRC risk. Our joint test for those risk genotypes and lifestyles with smoking revealed the synergistically increased CRC risk, more substantially in women with longer-term exposure to cigarette smoking.DiscussionOur findings may improve CRC prediction ability among medically underrepresented AA women and highlight genetically informed preventive interventions (e.g., smoking cessation; CRC screening to longer-term smokers) for those women at high risk with risk genotypes and behavioral patterns.

As key inflammatory biomarkers C-reactive protein (CRP) and interleukin-6 (IL6) play an important role in the pathogenesis of non-inflammatory diseases, including specific cancers, such as breast cancer (BC). Previous genome-wide association studies (GWASs) have neither explained the large proportion of genetic heritability nor provided comprehensive understanding of the underlying regulatory mechanisms. We adopted an integrative genomic network approach by incorporating our previous GWAS data for CRP and IL6 with multi-omics datasets, such as whole-blood expression quantitative loci, molecular biologic pathways, and gene regulatory networks to capture the full range of genetic functionalities associated with CRP/IL6 and tissue-specific key drivers (KDs) in gene subnetworks. We applied another systematic genomics approach for BC development to detect shared gene sets in enriched subnetworks across BC and CRP/IL6. We detected the topmost significant common pathways across CRP/IL6 (e.g., immune regulatory; chemokines and their receptors; interferon γ, JAK-STAT, and ERBB4 signaling), several of which overlapped with BC pathways. Further, in gene-gene interaction networks enriched by those topmost pathways, we identified KDs-both well-established (e.g., JAK1/2/3, STAT3) and novel (e.g., CXCR3, CD3D, CD3G, STAT6)-in a tissue-specific manner, for mechanisms shared in regulating CRP/IL6 and BC risk. Our study may provide robust, comprehensive insights into the mechanisms of CRP/IL6 regulation and highlight potential novel genetic targets as preventive and therapeutic strategies for associated disorders, such as BC.

BackgroundDisparities 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.MethodsWith 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.ResultsIn 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.ConclusionsOur 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.

Systemic inflammation-related etiologic pathways via inflammatory cytokines in the development of colorectal cancer (CRC) have not been convincingly determined and may be confounded by lifestyle factors or reverse causality. We investigated the genetically predicted C-reactive protein (CRP) phenotype in the potential causal pathway of primary CRC risk in postmenopausal women in a Mendelian randomization (MR) framework. We employed individual-level data of the Women's Health Initiative Database for Genotypes and Phenotypes Study, which consists of 5 genome-wide association (GWA) studies, including 10,142 women, 737 of whom developed primary CRC. We examined 61 GWA single-nucleotide polymorphisms (SNPs) associated with CRP by using weighted/penalized MR weighted-medians and MR gene-environment interactions that allow some relaxation of the strict variable requirements and attenuate the heterogeneous estimates of outlying SNPs. In lifestyle-stratification analyses, genetically determined CRP exhibited its effects on the decreased CRC risk in non-viscerally obese and high-fat diet subgroups. In contrast, genetically driven CRP was associated with an increased risk for CRC in women who smoked ≥ 15 cigarettes/day, with significant interaction of the gene-smoking relationship. Further, a substantially increased risk of CRC induced by CRP was observed in relatively short-term users (< 5 years) of estrogen (E)-only and also longer-term users (5 to > 10 years) of E plus progestin. Our findings may provide novel evidence on immune-related etiologic pathways connected to CRC risk and suggest the possible use of CRP as a CRC-predictive biomarker in women with particular behaviors and CRP marker-informed interventions to reduce CRC risk.

Systemic inflammation-related etiologic pathways via inflammatory cytokines in the development of colorectal cancer (CRC) have not been convincingly determined and may be confounded by lifestyle factors or reverse causality. We investigated the genetically predicted C-reactive protein (CRP) phenotype in the potential causal pathway of primary CRC risk in postmenopausal women in a Mendelian randomization (MR) framework. We employed individual-level data of the Women's Health Initiative Database for Genotypes and Phenotypes Study, which consists of 5 genome-wide association (GWA) studies, including 10,142 women, 737 of whom developed primary CRC. We examined 61 GWA single-nucleotide polymorphisms (SNPs) associated with CRP by using weighted/penalized MR weighted-medians and MR gene-environment interactions that allow some relaxation of the strict variable requirements and attenuate the heterogeneous estimates of outlying SNPs. In lifestyle-stratification analyses, genetically determined CRP exhibited its effects on the decreased CRC risk in non-viscerally obese and high-fat diet subgroups. In contrast, genetically driven CRP was associated with an increased risk for CRC in women who smoked ≥ 15 cigarettes/day, with significant interaction of the gene-smoking relationship. Further, a substantially increased risk of CRC induced by CRP was observed in relatively short-term users (< 5 years) of estrogen (E)-only and also longer-term users (5 to > 10 years) of E plus progestin. Our findings may provide novel evidence on immune-related etiologic pathways connected to CRC risk and suggest the possible use of CRP as a CRC-predictive biomarker in women with particular behaviors and CRP marker-informed interventions to reduce CRC risk.

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.

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.

IntroductionInsulin resistance (IR)/glucose intolerance is a critical biologic mechanism for the development of colorectal cancer (CRC) in postmenopausal women. Whereas IR and excessive adiposity are more prevalent in African American (AA) women than in White women, AA women are underrepresented in genome-wide studies for systemic regulation of IR and the association with CRC risk.MethodsWith 780 genome-wide IR single-nucleotide polymorphisms (SNPs) among 4,692 AA women, we tested for a causal inference between genetically elevated IR and CRC risk. Furthermore, by incorporating CRC-associated lifestyle factors, we established a prediction model on the basis of gene-environment interactions to generate risk profiles for CRC with the most influential genetic and lifestyle factors.ResutlsIn the pooled Mendelian randomization analysis, the genetically elevated IR was associated with 9 times increased risk of CRC, but with lack of analytic power. By addressing the variation of individual SNPs in CRC in the prediction model, we detected 4 fasting glucose-specific SNPs in GCK, PCSK1, and MTNR1B and 4 lifestyles, including smoking, aging, prolonged lifetime exposure to endogenous estrogen, and high fat intake, as the most predictive markers of CRC risk. Our joint test for those risk genotypes and lifestyles with smoking revealed the synergistically increased CRC risk, more substantially in women with longer-term exposure to cigarette smoking.DiscussionOur findings may improve CRC prediction ability among medically underrepresented AA women and highlight genetically informed preventive interventions (e.g., smoking cessation; CRC screening to longer-term smokers) for those women at high risk with risk genotypes and behavioral patterns.

Immune-related etiologic pathways to influence invasive breast cancer risk may interact with lifestyle factors, but the interrelated molecular genetic pathways are incompletely characterized. We used data from the Women's Health Initiative Database for Genotypes and Phenotypes Study including 16,088 postmenopausal women, a population highly susceptible to inflammation, obesity, and increased risk for breast cancer. With 21,784,812 common autosomal single-nucleotide polymorphisms (SNP), we conducted a genome-wide association (GWA) gene-environment interaction (G × E) analysis in six independent GWA Studies for proinflammatory cytokines [IL6 and C-reactive protein (CRP)] and their gene-lifestyle interactions. Subsequently, we tested for the association of the GWA SNPs with breast cancer risk. In women overall and stratified by obesity status (body mass index, waist circumference, and waist-to-hip ratio) and obesity-related lifestyle factors (exercise and high-fat diet), 88 GWA SNPs in 10 loci were associated with proinflammatory cytokines: 3 associated with IL6 (1 index SNP in MAPK1 and 1 independent SNP in DEC1); 85 with CRP (3 index SNPs in CRPP1, CRP, RP11-419N10.5, HNF1A-AS1, HNF1A, and C1q2orf43; and two independent SNPs in APOE and APOC1). Of those, 27 in HNF1A-AS1, HNF1A, and C1q2orf43 displayed significantly increased risk for breast cancer. We found a number of novel top markers for CRP and IL6, which interacted with obesity factors. A substantial proportion of those SNPs' susceptibility influenced breast cancer risk. Our findings may contribute to better understanding of genetic associations between pro-inflammation and cancer and suggest intervention strategies for women who carry the risk genotypes, reducing breast cancer risk. PREVENTION RELEVANCE: The top GWA-SNPs associated with pro-inflammatory biomarkers have implications for breast carcinogenesis by interacting with obesity factors. Our findings may suggest interventions for women who carry the infla

BackgroundDisparities 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.MethodsWith 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.ResultsIn 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.ConclusionsOur 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.

Immune-related molecular and genetic pathways that are connected to colorectal cancer (CRC) and lifestyles in postmenopausal women are incompletely characterized. In this study, we examined the role of pro-inflammatory biomarkers such as C-reactive protein (CRP) and interleukin-6 (IL-6) in those pathways. Through selection of the best predictive single-nucleotide polymorphisms (SNPs) and lifestyles, our goal was to improve the prediction accuracy and ability for CRC risk. Using large cohort data of postmenopausal women from the Women's Health Initiative Database for Genotypes and Phenotypes Study, we previously conducted a genome-wide association (GWA) for a CRP and IL-6 gene-behavioral interaction study. For the present study, we added GWA-SNPs from outside GWA studies, resulting in a total of 152 SNPs. Together with 41 selected lifestyles, we performed a 2-stage multimodal random survival forest analysis with generalized multifactor dimensionality reduction approach to construct CRC risk profiles. Overall and in obesity strata (by body mass index, waist circumference, waist-to-hip ratio, exercise, and dietary fat intake), we identified the best predictive genetic markers in inflammatory cytokines and lifestyles. Across the strata, 2 SNPs (ONECUT2 rs4092465 and HNF4A rs1800961) and 1 lifestyle factor (relatively short-term past use of oral contraceptives) were the most common and strongest predictive markers for CRC risk. The risk profile that combined those variables exhibited synergistically increased risk for CRC; this pattern appeared more strongly in obese and inactive subgroups. Our results may contribute to improved predictability for CRC and suggest genetically targeted lifestyle interventions for women carrying the inflammatory-risk genotypes, reducing CRC 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.

BackgroundImmune-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.MethodsWe 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.ResultsIn 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.ConclusionsOur 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.

BackgroundCirculating glycemic traits (GTs) have been considered a risk factor for breast cancer, but studies using GT-associated genetic variants as an instrumental variable are limited and inconclusive.MethodsOur Mendelian Randomization analysis used the most recent genome-wide datasets focusing on European women.ResultsOf 44 single-nucleotide polymorphisms (SNPs) with GTs, 38 fasting-glucose and 6 fasting-insulin SNPs showed heterogeneous associations with breast cancer, without significant directional pleiotropy observed.ConclusionOur findings indicate a null association between genetically determined GTs and breast cancer risk among European women. Our findings may contribute to more complete characterizing of metabolic pathways in GTs and breast cancer.

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.

The authors have withdrawn this preprint due to erroneous posting.

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 10,170 women, including 537 who developed breast cancer, from the Women’s Health Initiative Database for Genotypes and Phenotypes Study, which consists of 5 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 pathways linking to breast cancer risk, and suggest potential clinical use of CRP to predict the specific cancer subtypes and CRP–inflammatory marker targeting interventions to reduce postmenopausal breast cancer risk.

Immune-related molecular and genetic pathways that are connected to colorectal cancer (CRC) and lifestyles in postmenopausal women are incompletely characterized. In this study, we examined the role of pro-inflammatory biomarkers such as C-reactive protein (CRP) and interleukin-6 (IL-6) in those pathways. Through selection of the best predictive single-nucleotide polymorphisms (SNPs) and lifestyles, our goal was to improve the prediction accuracy and ability for CRC risk. Using large cohort data of postmenopausal women from the Women's Health Initiative Database for Genotypes and Phenotypes Study, we previously conducted a genome-wide association (GWA) for a CRP and IL-6 gene-behavioral interaction study. For the present study, we added GWA-SNPs from outside GWA studies, resulting in a total of 152 SNPs. Together with 41 selected lifestyles, we performed a 2-stage multimodal random survival forest analysis with generalized multifactor dimensionality reduction approach to construct CRC risk profiles. Overall and in obesity strata (by body mass index, waist circumference, waist-to-hip ratio, exercise, and dietary fat intake), we identified the best predictive genetic markers in inflammatory cytokines and lifestyles. Across the strata, 2 SNPs (ONECUT2 rs4092465 and HNF4A rs1800961) and 1 lifestyle factor (relatively short-term past use of oral contraceptives) were the most common and strongest predictive markers for CRC risk. The risk profile that combined those variables exhibited synergistically increased risk for CRC; this pattern appeared more strongly in obese and inactive subgroups. Our results may contribute to improved predictability for CRC and suggest genetically targeted lifestyle interventions for women carrying the inflammatory-risk genotypes, reducing CRC risk.

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 10,170 women, including 537 who developed breast cancer, from the Women’s Health Initiative Database for Genotypes and Phenotypes Study, which consists of 5 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 pathways linking to breast cancer risk, and suggest potential clinical use of CRP to predict the specific cancer subtypes and CRP–inflammatory marker targeting interventions to reduce postmenopausal breast cancer risk.

The authors have withdrawn this preprint due to erroneous posting.

BackgroundCirculating glycemic traits (GTs) have been considered a risk factor for breast cancer, but studies using GT-associated genetic variants as an instrumental variable are limited and inconclusive.MethodsOur Mendelian Randomization analysis used the most recent genome-wide datasets focusing on European women.ResultsOf 44 single-nucleotide polymorphisms (SNPs) with GTs, 38 fasting-glucose and 6 fasting-insulin SNPs showed heterogeneous associations with breast cancer, without significant directional pleiotropy observed.ConclusionOur findings indicate a null association between genetically determined GTs and breast cancer risk among European women. Our findings may contribute to more complete characterizing of metabolic pathways in GTs and breast cancer.

BackgroundImmune-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.MethodsWe 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.ResultsIn 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.ConclusionsOur 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.

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.

BackgroundConcurrent variation in adiposity and inflammation suggests potential shared functional pathways and pleiotropic disease underpinning. Yet, exploration of pleiotropy in the context of adiposity-inflammation has been scarce, and none has included self-identified Hispanic/Latino populations. Given the high level of ancestral diversity in Hispanic American population, genetic studies may reveal variants that are infrequent/monomorphic in more homogeneous populations.MethodsUsing multi-trait Adaptive Sum of Powered Score (aSPU) method, we examined individual and shared genetic effects underlying inflammatory (CRP) and adiposity-related traits (Body Mass Index [BMI]), and central adiposity (Waist to Hip Ratio [WHR]) in HLA participating in the Population Architecture Using Genomics and Epidemiology (PAGE) cohort (N = 35,871) with replication of effects in the Cameron County Hispanic Cohort (CCHC) which consists of Mexican American individuals.ResultsOf the > 16 million SNPs tested, variants representing 7 independent loci were found to illustrate significant association with multiple traits. Two out of 7 variants were replicated at statistically significant level in multi-trait analyses in CCHC. The lead variant on APOE (rs439401) and rs11208712 were found to harbor multi-trait associations with adiposity and inflammation.ConclusionsResults from this study demonstrate the importance of considering pleiotropy for improving our understanding of the etiology of the various metabolic pathways that regulate cardiovascular disease development.

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

PurposeThe 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.MethodsWe 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.ResultsNo 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).ConclusionsWe 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.

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.

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.

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

PurposeThe 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.MethodsWe 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.ResultsNo 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).ConclusionsWe 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.

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.

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.

ObjectivesGenetic variants in metabolic signaling pathways may interact with lifestyle factors, such as dietary fatty acids, influencing postmenopausal colorectal cancer (CRC) risk, but these interrelated pathways are not fully understood.MethodsIn this study, we examined 54 single-nucleotide polymorphisms (SNPs) in genes related to insulin-like growth factor-I/insulin traits and their signaling pathways and lifestyle factors in relation to postmenopausal CRC, using data from 6,539 postmenopausal women in the Women's Health Initiative Harmonized and Imputed Genome-Wide Association Studies. By employing a two-stage random survival forest analysis, we evaluated the SNPs and lifestyle factors by ranking them according to their predictive value and accuracy for CRC.ResultsWe identified four SNPs (IRS1 rs1801123, IRS1 rs1801278, AKT2 rs3730256, and AKT2 rs7247515) and two lifestyle factors (age and percentage calories from saturated fatty acids) as the top six most influential predictors for CRC risk. We further examined interactive effects of those factors on cancer risk. In the individual SNP analysis, no significant association was observed, but the combination of the four SNPs, age, and percentage calories from saturated fatty acid (≥11% per day) significantly increased the risk of CRC in a gene and lifestyle dose-dependent manner.ConclusionsOur findings provide insight into gene-lifestyle interactions and will enable researchers to focus on individuals with risk genotypes to promote intervention strategies. Our study suggests the careful use of data on potential genetic targets in clinical trials for cancer prevention to reduce the risk for CRC in postmenopausal women.

BackgroundA decreased level of serum adiponectin is associated with obesity and an increased risk of breast cancer among postmenopausal women. Yet, the interplay between genetic variants associated with adiponectin phenotype, obesity, and breast cancer risk is unclear in African American (AA) women.MethodsWe examined 32 single-nucleotide polymorphisms (SNPs) previously identified in genome-wide association and replication studies of serum adiponectin levels using data from 7,991 AA postmenopausal women in the Women's Health Initiative SNP Health Association Resource.ResultsStratifying by obesity status, we identified 18 adiponectin-related SNPs that were associated with breast cancer risk. Among women with BMI ≥ 30 kg/m2, the minor TT genotype of FER rs10447248 had an elevated breast cancer risk. Interaction was observed between obesity and the CT genotype of ADIPOQ rs6773957 on the additive scale for breast cancer risk (relative excess risk due to interaction, 0.62; 95% CI, 0.32-0.92). The joint effect of BMI ≥ 30 kg/m2 and the TC genotype of OR8S1 rs11168618 was larger than the sum of the independent effects on breast cancer risk.ConclusionsWe demonstrated that obesity plays a significant role as an effect modifier in an increased effect of the SNPs on breast cancer risk using one of the most extensive data on postmenopausal AA women.ImpactThe results suggest the potential use of adiponectin genetic variants as obesity-associated biomarkers for informing AA women who are at greater risk for breast cancer and also for promoting behavioral interventions, such as weight control, to those with risk genotypes.

BackgroundA decreased level of serum adiponectin is associated with obesity and an increased risk of breast cancer among postmenopausal women. Yet, the interplay between genetic variants associated with adiponectin phenotype, obesity, and breast cancer risk is unclear in African American (AA) women.MethodsWe examined 32 single-nucleotide polymorphisms (SNPs) previously identified in genome-wide association and replication studies of serum adiponectin levels using data from 7,991 AA postmenopausal women in the Women's Health Initiative SNP Health Association Resource.ResultsStratifying by obesity status, we identified 18 adiponectin-related SNPs that were associated with breast cancer risk. Among women with BMI ≥ 30 kg/m2, the minor TT genotype of FER rs10447248 had an elevated breast cancer risk. Interaction was observed between obesity and the CT genotype of ADIPOQ rs6773957 on the additive scale for breast cancer risk (relative excess risk due to interaction, 0.62; 95% CI, 0.32-0.92). The joint effect of BMI ≥ 30 kg/m2 and the TC genotype of OR8S1 rs11168618 was larger than the sum of the independent effects on breast cancer risk.ConclusionsWe demonstrated that obesity plays a significant role as an effect modifier in an increased effect of the SNPs on breast cancer risk using one of the most extensive data on postmenopausal AA women.ImpactThe results suggest the potential use of adiponectin genetic variants as obesity-associated biomarkers for informing AA women who are at greater risk for breast cancer and also for promoting behavioral interventions, such as weight control, to those with risk genotypes.

ObjectivesDietary factors are of importance in the development of stomach cancer. This study aims to examine index-based dietary patterns associated with stomach cancer in a Chinese population.MethodsUsing data from a population-based case-control study conducted in Jiangsu Province, China, we included a total of 8432 participants (1900 stomach cancer cases and 6532 controls). Dietary data collected by food frequency questionnaire was evaluated by modified Chinese Healthy Eating Index-2016 (mCHEI-2016) and the US Healthy Eating Index-2015 (HEI-2015). Multiple logistic regression analyses were applied to examine the association of mCHEI-2016 and HEI-2015 with stomach cancer while adjusting for potential confounders. The possible interactions between mCHEI-2016 or HEI-2015 and established risk factors were explored.ResultsAmong nonproxy interviews, after adjusting for potential confounding factors, a higher score of sodium, reflecting lower intake per day, was inversely associated with stomach cancer [odds ratio (OR), 0.95; 95% CI, 0.91-0.99 for mCHEI-2016; OR, 0.97; 95% CI, 0.94-0.99 for HEI-2015]. No clear associations with stomach cancer were identified for total scores of HEI-2015 (OR, 0.98; 95% CI, 0.87-1.10 with a 10-point increase, P trend = 0.98) and mCHEI-2016 (OR, 1.05; 95% CI, 0.94-1.17 with a 10-point increase, P trend = 0.22). However, the relation between stomach cancer and the mCHEI-2016 was modified by BMI, with a possible inverse association in normal-weight subjects.ConclusionsOur findings highlight that reduced intake of dietary sodium would prevent the development of stomach cancer. The data indicate a heterogeneity between normal weight and overweight's dietary factors in relation to stomach cancer.

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.

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.

Genetic variants and traits in metabolic signaling pathways may interact with lifestyle factors such as obesity, physical activity, and exogenous estrogen (E), influencing postmenopausal colorectal cancer (CRC) risk, but these interrelated pathways are not fully understood. In this case-cohort study, we examined 33 single-nucleotide polymorphisms (SNPs) in genes related to insulin-like growth factor-I (IGF-I)/ insulin resistance (IR) traits and signaling pathways, using data from 704 postmenopausal women in Women's Health Initiative Observation ancillary studies. Stratifying by the lifestyle modifiers, we assessed the effects of IGF-I/IR traits (fasting total and free IGF-I, IGF binding protein-3, insulin, glucose, and homeostatic model assessment-insulin resistance) on CRC risk as a mediator or influencing factor. Six SNPs in the INS, IGF-I, and IGFBP3 genes were associated with CRC risk, and those associations differed between non-obese/active and obese/inactive women and between E nonusers and users. Roughly 30% of the cancer risk due to the SNP was mediated by IGF-I/IR traits. Likewise, carriers of 11 SNPs in the IRS1 and AKT1/2 genes (signaling pathway-related genetic variants) had different associations with CRC risk between strata, and the proportion of the SNP-cancer association explained by traits varied from 30% to 50%. Our findings suggest that IGF-I/IR genetic variants interact with obesity, physical activity, and exogenous E, altering postmenopausal CRC risk, through IGF-I/IR traits, but also through different pathways. Unraveling gene-phenotype-lifestyle interactions will provide data on potential genetic targets in clinical trials for cancer prevention and intervention strategies to reduce CRC risk.

BackgroundImpaired glucose metabolism-related genetic variants and traits likely interact with obesity and related lifestyle factors, influencing postmenopausal breast and colorectal cancer (CRC), but their interconnected pathways are not fully understood. By stratifying via obesity and lifestyles, we partitioned the total effect of glucose metabolism genetic variants on cancer risk into two putative mechanisms: 1) indirect (risk-associated glucose metabolism genetic variants mediated by glucose metabolism traits) and 2) direct (risk-associated glucose metabolism genetic variants through pathways other than glucose metabolism traits) effects.MethodUsing 16 single-nucleotide polymorphisms (SNPs) associated with glucose metabolism and data from 5379 postmenopausal women in the Women's Health Initiative Harmonized and Imputed Genome-Wide Association Studies, we retrospectively assessed the indirect and direct effects of glucose metabolism-traits (fasting glucose, insulin, and homeostatic model assessment-insulin resistance [HOMA-IR]) using two quantitative tests.ResultsSeveral SNPs were associated with breast cancer and CRC risk, and these SNP-cancer associations differed between non-obese and obese women. In both strata, the direct effect of cancer risk associated with the SNP accounted for the majority of the total effect for most SNPs, with roughly 10% of cancer risk due to the SNP that was from an indirect effect mediated by glucose metabolism traits. No apparent differences in the indirect (glucose metabolism-mediated) effects were seen between non-obese and obese women. It is notable that among obese women, 50% of cancer risk was mediated via glucose metabolism trait, owing to two SNPs: in breast cancer, in relation to GCKR through glucose, and in CRC, in relation to DGKB/TMEM195 through HOMA-IR.ConclusionsOur findings suggest that glucose metabolism genetic variants interact with obesity, resulting in altered cancer risk through pathways other than those mediate

PurposeGenetic variants and traits in metabolic signaling pathways may interact with obesity, physical activity, and exogenous estrogen (E), influencing postmenopausal breast cancer risk, but these inter-related pathways are incompletely understood.MethodsWe used 75 single-nucleotide polymorphisms (SNPs) in genes related to insulin-like growth factor-I (IGF-I)/insulin resistance (IR) traits and signaling pathways, and data from 1003 postmenopausal women in Women's Health Initiative Observation ancillary studies. Stratifying via obesity and lifestyle modifiers, we assessed the role of IGF-I/IR traits (fasting IGF-I, IGF-binding protein 3, insulin, glucose, and homeostatic model assessment-insulin resistance) in breast cancer risk as a mediator or influencing factor.ResultsSeven SNPs in IGF-I and INS genes were associated with breast cancer risk. These associations differed between non-obese/active and obese/inactive women and between exogenous E non-users and users. The mediation effects of IGF-I/IR traits on the relationship between these SNPs and cancer differed between strata, but only roughly 35% of the cancer risk due to the SNPs was mediated by traits. Similarly, carriers of 20 SNPs in PIK3R1, AKT1/2, and MAPK1 genes (signaling pathways-genetic variants) had different associations with breast cancer between strata, and the proportion of the SNP-cancer relationship explained by traits varied 45-50% between the strata.ConclusionsOur findings suggest that IGF-I/IR genetic variants interact with obesity and lifestyle factors, altering cancer risk partially through pathways other than IGF-I/IR traits. Unraveling gene-phenotype-lifestyle interactions will provide data on potential genetic targets in clinical trials for cancer prevention and intervention strategies to reduce breast cancer risk.

Genetic variants and traits in metabolic signaling pathways may interact with lifestyle factors such as obesity, physical activity, and exogenous estrogen (E), influencing postmenopausal colorectal cancer (CRC) risk, but these interrelated pathways are not fully understood. In this case-cohort study, we examined 33 single-nucleotide polymorphisms (SNPs) in genes related to insulin-like growth factor-I (IGF-I)/ insulin resistance (IR) traits and signaling pathways, using data from 704 postmenopausal women in Women's Health Initiative Observation ancillary studies. Stratifying by the lifestyle modifiers, we assessed the effects of IGF-I/IR traits (fasting total and free IGF-I, IGF binding protein-3, insulin, glucose, and homeostatic model assessment-insulin resistance) on CRC risk as a mediator or influencing factor. Six SNPs in the INS, IGF-I, and IGFBP3 genes were associated with CRC risk, and those associations differed between non-obese/active and obese/inactive women and between E nonusers and users. Roughly 30% of the cancer risk due to the SNP was mediated by IGF-I/IR traits. Likewise, carriers of 11 SNPs in the IRS1 and AKT1/2 genes (signaling pathway-related genetic variants) had different associations with CRC risk between strata, and the proportion of the SNP-cancer association explained by traits varied from 30% to 50%. Our findings suggest that IGF-I/IR genetic variants interact with obesity, physical activity, and exogenous E, altering postmenopausal CRC risk, through IGF-I/IR traits, but also through different pathways. Unraveling gene-phenotype-lifestyle interactions will provide data on potential genetic targets in clinical trials for cancer prevention and intervention strategies to reduce CRC risk.

PurposeGenetic variants and traits in metabolic signaling pathways may interact with obesity, physical activity, and exogenous estrogen (E), influencing postmenopausal breast cancer risk, but these inter-related pathways are incompletely understood.MethodsWe used 75 single-nucleotide polymorphisms (SNPs) in genes related to insulin-like growth factor-I (IGF-I)/insulin resistance (IR) traits and signaling pathways, and data from 1003 postmenopausal women in Women's Health Initiative Observation ancillary studies. Stratifying via obesity and lifestyle modifiers, we assessed the role of IGF-I/IR traits (fasting IGF-I, IGF-binding protein 3, insulin, glucose, and homeostatic model assessment-insulin resistance) in breast cancer risk as a mediator or influencing factor.ResultsSeven SNPs in IGF-I and INS genes were associated with breast cancer risk. These associations differed between non-obese/active and obese/inactive women and between exogenous E non-users and users. The mediation effects of IGF-I/IR traits on the relationship between these SNPs and cancer differed between strata, but only roughly 35% of the cancer risk due to the SNPs was mediated by traits. Similarly, carriers of 20 SNPs in PIK3R1, AKT1/2, and MAPK1 genes (signaling pathways-genetic variants) had different associations with breast cancer between strata, and the proportion of the SNP-cancer relationship explained by traits varied 45-50% between the strata.ConclusionsOur findings suggest that IGF-I/IR genetic variants interact with obesity and lifestyle factors, altering cancer risk partially through pathways other than IGF-I/IR traits. Unraveling gene-phenotype-lifestyle interactions will provide data on potential genetic targets in clinical trials for cancer prevention and intervention strategies to reduce breast cancer risk.

BackgroundImpaired glucose metabolism-related genetic variants and traits likely interact with obesity and related lifestyle factors, influencing postmenopausal breast and colorectal cancer (CRC), but their interconnected pathways are not fully understood. By stratifying via obesity and lifestyles, we partitioned the total effect of glucose metabolism genetic variants on cancer risk into two putative mechanisms: 1) indirect (risk-associated glucose metabolism genetic variants mediated by glucose metabolism traits) and 2) direct (risk-associated glucose metabolism genetic variants through pathways other than glucose metabolism traits) effects.MethodUsing 16 single-nucleotide polymorphisms (SNPs) associated with glucose metabolism and data from 5379 postmenopausal women in the Women's Health Initiative Harmonized and Imputed Genome-Wide Association Studies, we retrospectively assessed the indirect and direct effects of glucose metabolism-traits (fasting glucose, insulin, and homeostatic model assessment-insulin resistance [HOMA-IR]) using two quantitative tests.ResultsSeveral SNPs were associated with breast cancer and CRC risk, and these SNP-cancer associations differed between non-obese and obese women. In both strata, the direct effect of cancer risk associated with the SNP accounted for the majority of the total effect for most SNPs, with roughly 10% of cancer risk due to the SNP that was from an indirect effect mediated by glucose metabolism traits. No apparent differences in the indirect (glucose metabolism-mediated) effects were seen between non-obese and obese women. It is notable that among obese women, 50% of cancer risk was mediated via glucose metabolism trait, owing to two SNPs: in breast cancer, in relation to GCKR through glucose, and in CRC, in relation to DGKB/TMEM195 through HOMA-IR.ConclusionsOur findings suggest that glucose metabolism genetic variants interact with obesity, resulting in altered cancer risk through pathways other than those mediate