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Background: Postmenopausal women with cancer experience an accelerated physical dysfunction beyond what is expected through aging alone due to cancer and its treatments. The aim of this study was to determine whether declines in physical function after cancer diagnosis are associated with all-cause mortality and cancer-specific mortality., Methods: This prospective cohort study included 8068 postmenopausal women enrolled in the Women's Health Initiative with a cancer diagnosis and who had physical function assessed within 1 year of that diagnosis. Self-reported physical function was measured using the 10-item physical function subscale of the 36-Item Short Form Health Survey. Cause of death was determined by medical record review, with central adjudication and linkage to the National Death Index. Death was adjudicated through February 2022., Results: Over a median follow-up of 7.7 years from cancer diagnosis, 3316 (41.1%) women died. Our results showed that for every 10% difference in the physical function score after cancer diagnosis versus pre-diagnosis, all-cause mortality and cancer-specific mortality were reduced by 12% (hazard ratio [HR] = 0.88, 95% confidence interval  [95% CI] = 0.87 to 0.89 and HR = 0.88, 95% CI = 0.86 to 0.91, respectively). Further categorical analyses showed a significant dose-response relationship between postdiagnosis physical function categories and mortality outcomes (P < .001 for trend), where the median survival time for women in the lowest physical function quartile was 9.1 years (Interquartile range [IQR] = 8.6-10.6 years) compared with 18.4 years (IQR = 15.8-22.0 years) for women in the highest physical function quartile., Conclusion: Postmenopausal women with low physical function after cancer diagnosis may be at higher risk of mortality from all causes and cancer-related mortality., (© The Author(s) 2024. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

We investigated relations of depressive symptoms, antidepressant use, and epigenetic age acceleration with all-cause mortality risk among postmenopausal women. Data were analyzed from ≤1,900 participants in the Women's Health Initiative study testing four-way decomposition models. After a median 20.4y follow-up, 1,161 deaths occurred. Approximately 11% had elevated depressive symptoms (EDS + ), 7% were taking antidepressant medication at baseline (ANTIDEP + ), while 16.5% fell into either category (EDS&#95;ANTIDEP + ). Baseline ANTIDEP + , longitudinal transition into ANTIDEP + and accelerated epigenetic aging directly predicted increased mortality risk. GrimAge DNA methylation age acceleration (AgeAccelGrim) partially mediated total effects of baseline ANTIDEP + and EDS&#95;ANTIDEP + on all-cause mortality risk in socio-demographic factors-adjusted models (Pure Indirect Effect >0, P < 0.05; Total Effect >0, P < 0.05). Thus, higher AgeAccelGrim partially explained the relationship between antidepressant use and increased all-cause mortality risk, though only prior to controlling for lifestyle and health-related factors. Antidepressant use and epigenetic age acceleration independently predicted increased all-cause mortality risk. Further studies are needed in varying populations.

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., (©2018 American Association for Cancer Research.)

Purpose: Genetic 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., Methods: We 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., Results: Seven 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., Conclusions: Our 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.

Background: Impaired 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., Method: Using 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., Results: Several 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., Conclusions: Our findings suggest that glucose metabolism genetic variants interact with obesity, resulting in altered cancer risk through pathways other than those mediated by glucose metabolism traits.

Objective: Bioavailable insulin-like growth factor-I (IGF-I) interacts with obesity and exogenous estrogen (E) in a racial disparity in obesity-related cancer risk, yet their interconnected pathways are not fully characterized. We investigated whether circulating bioavailable IGF-I acted as a mediator of the racial disparity in obesity-related cancers such as breast and colorectal (CR) cancers and how obesity and E use regulate this relationship., Methods: A total of 2,425 white and 164 African American (AA) postmenopausal women from the Women's Health Initiative Observational Study were followed from October 1, 1993 through August 29, 2014. To assess bioactive IGF-I as a mediator of race-cancer relationship, we used the Baron-Kenny method and quantitative estimation of the mediation effect., Results: Compared with white women, AA women had higher IGF-I levels; their higher risk of CR cancer, after accounting for IGF-I, was no longer significant. IGF-I was associated with breast and CR cancers even after controlling for race. Among viscerally obese (waist/hip ratio >0.85) and overall nonobese women (body mass index <30), IGF-I was a strong mediator, reducing the racial disparity in both cancers by 30% and 60%, respectively. In E-only users and nonusers, IGF-I explained the racial disparity in CR cancer only modestly., Conclusions: Bioavailable IGF-I is potentially important in racial disparities in obesity-related breast and CR cancer risk between postmenopausal AA and white women. Body fat distribution and E use may be part of the interconnected hormonal pathways related to racial difference in IGF-I levels and obesity-related cancer risk.

Background: The role of exogenous estrogen use in racial differences in insulin-like growth factor-I (IGF-I) levels which affect cancer risk is unclear. We investigated whether the relationship between race and circulating bioactive IGF-I proteins was mediated by exogenous estrogen and the extent to which exogenous estrogen influenced the race-IGF-I relationship in postmenopausal women., Methods: This cross-sectional study included 636 white and 133 African American postmenopausal women enrolled in an ancillary study of the Women's Health Initiative Observational Study. To assess exogenous estrogen use (nonusers [n = 262] vs users [n = 507]) as a mediator of the race-IGF-I relationship, we used the Baron-Kenny method and an estimation of the proportional change in the odd ratios for IGF-I levels on race plus a bootstrapping test for the significance of the mediation effect., Results: Compared with white women, African American women were more likely to have high IGF-I levels and less likely to use exogenous estrogen. After accounting for race, estrogen nonusers had higher IGF-I levels than estrogen users did. Among oral contraceptive ever users, exogenous estrogen had a strong mediation effect (67%; p = .018) in the race-IGF-I relationship. In the women with a history of hypertension, exogenous estrogen explained racial differences in IGF-I levels to a modest degree (23%; p = .029)., Conclusions: Exogenous estrogen use has a potentially important role in disparities in IGF-I bioactivity between postmenopausal African American and white women. A history of oral contraceptive use and hypertension may be part of the interconnected hormonal pathways related to racial differences in IGF-I levels., (© The Author 2014. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Purpose: Risk factors for obesity and weight gain are typically evaluated individually while "adjusting for" the influence of other confounding factors, and few studies, if any, have created risk profiles by clustering risk factors. We identified subgroups of postmenopausal women homogeneous in their clustered modifiable and non-modifiable risk factors for gaining ≥ 3% weight., Methods: This study included 612 postmenopausal women 50-79 years old, enrolled in an ancillary study of the Women's Health Initiative Observational Study between February 1995 and July 1998. Classification and regression tree and stepwise regression models were built and compared., Results: Of 27 selected variables, the factors significantly related to ≥ 3% weight gain were weight change in the past 2 years, age at menopause, dietary fiber, fat, alcohol intake, and smoking. In women younger than 65 years, less than 4 kg weight change in the past 2 years sufficiently reduced risk of ≥ 3% weight gain. Different combinations of risk factors related to weight gain were reported for subgroups of women: women 65 years or older (essential factor: < 9.8 g/day dietary factor), African Americans (essential factor: currently smoking), and white women (essential factor: ≥ 5 kg weight change for the past 2 years)., Conclusions: Our findings suggest specific characteristics for particular subgroups of postmenopausal women that may be useful for identifying those at risk for weight gain. The study results may be useful for targeting efforts to promote strategies to reduce the risk of obesity and weight gain in subgroups of postmenopausal women and maximize the effect of weight control by decreasing obesity-relevant adverse health outcomes.

Background: Weight gain, insulin-like growth factor-I (IGF-I) levels, and excess exogenous steroid hormone use are putative cancer risk factors, yet their interconnected pathways have not been fully characterized. This cross-sectional study investigated the relationship between plasma IGF-I levels and weight gain according to body mass index (BMI), leptin levels, and exogenous estrogen use among postmenopausal women., Methods: This study included 794 postmenopausal women who enrolled in an ancillary study of the Women's Health Initiative Observational Study between February 1995 and July 1998. The relationship between IGF-I levels and weight gain was analyzed using ordinal logistic regression. We used the molar ratio of IGF-I to IGF binding protein-3 (IGF-I/IGFBP-3) or circulating IGF-I levels adjusting for IGFBP-3 as a proxy of bioavailable IGF-I. The plasma concentrations were expressed as quartiles., Results: Among the obese group, women in the third quartile (Q3) of IGF-I and highest quartile of IGF-I/IGFBP-3 were less likely to gain weight (>3% from baseline) than were women in the first quartiles (Q1). Among the normal-weight group, women in Q2 and Q3 of IGF-I/IGFBP-3 were 70% less likely than those in Q1 to gain weight. Among current estrogen users, Q3 of IGF-I/IGFBP-3 had 0.5 times the odds of gaining weight than Q1., Conclusions: Bioavailable IGF-I levels were inversely related to weight gain overall., Impact: Although weight gain was not consistent with increases in IGF-I levels among postmenopausal women in this report, avoidance of weight gain as a strategy to reduce cancer risk may be recommended., (©2013 AACR.)

BACKGROUND & AIMS: Systematic reviews, meta-analyses and Mendelian randomization studies suggest that cardiometabolic diseases may be associated with COVID-19 risk and prognosis, with evidence implicating insulin resistance (IR) as a common biological mechanism. As driving factors for IR, we examined body mass index (BMI) and waist circumference (WC) among postmenopausal women in association with COVID-19 outcomes (positivity and hospitalization), and the role of glucose homeostasis as a mediator of this relationship. METHODS: Associations of BMI and WC at baseline (1993-1998) with COVID-19 outcomes collected at Survey 1 (June-December, 2020) and/or Survey 2 (September-December, 2021) were evaluated among 42,770 Womens Health Initiative (WHI) participants (baseline age: 59.36 years) of whom 16,526 self-reported having taken ≥1 COVID-19 test, with 1242 reporting ≥1 positive COVID-19 test and 362 reporting ≥1 COVID-19 hospitalization. We applied logistic regression and causal mediation analyses to sub-samples with available fasting biomarkers of glucose homeostasis (glucose, insulin, Homeostatic Model Assessment for Insulin Resistance, Homeostasis Model Assessment for β-cell function, Quantitative Insulin-sensitivity Check Index, Triglyceride-Glucose index (TyG)) at baseline, whereby 57 of 759 reported COVID-19 test positivity and 23 of 1896 reported COVID-19 hospitalization. RESULTS: In fully adjusted models, higher BMI, WC and TyG were associated with COVID-19 test positivity and hospitalization. Glucose concentrations mediated associations of BMI and WC with COVID-19 positivity, whereas TyG mediated BMI and WCs associations with COVID-19 hospitalization. CONCLUSIONS: Obesity and central obesity markers collected an average of 24 years prior were associated with COVID-19 outcomes among postmenopausal women. Glucose concentration and TyG partly mediated these associations.

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 inflammatory-risk genotypes to reduce 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.

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.

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.

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.

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.

ObjectiveBioavailable insulin-like growth factor-I (IGF-I) interacts with obesity and exogenous estrogen (E) in a racial disparity in obesity-related cancer risk, yet their interconnected pathways are not fully characterized. We investigated whether circulating bioavailable IGF-I acted as a mediator of the racial disparity in obesity-related cancers such as breast and colorectal (CR) cancers and how obesity and E use regulate this relationship.MethodsA total of 2,425 white and 164 African American (AA) postmenopausal women from the Women's Health Initiative Observational Study were followed from October 1, 1993 through August 29, 2014. To assess bioactive IGF-I as a mediator of race-cancer relationship, we used the Baron-Kenny method and quantitative estimation of the mediation effect.ResultsCompared with white women, AA women had higher IGF-I levels; their higher risk of CR cancer, after accounting for IGF-I, was no longer significant. IGF-I was associated with breast and CR cancers even after controlling for race. Among viscerally obese (waist/hip ratio >0.85) and overall nonobese women (body mass index

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.

Background Postmenopausal women with cancer experience an accelerated physical dysfunction beyond what is expected through aging alone due to cancer and its treatments. The aim of this study was to determine whether declines in physical function after cancer diagnosis are associated with all-cause mortality and cancer-specific mortality. Methods This prospective cohort study included 8068 postmenopausal women enrolled in the Women's Health Initiative with a cancer diagnosis and who had physical function assessed within 1 year of that diagnosis. Self-reported physical function was measured using the 10-item physical function subscale of the 36-Item Short Form Health Survey. Cause of death was determined by medical record review, with central adjudication and linkage to the National Death Index. Death was adjudicated through February 2022. Results Over a median follow-up of 7.7 years from cancer diagnosis, 3316 (41.1%) women died. Our results showed that for every 10% difference in the physical function score after cancer diagnosis versus pre-diagnosis, all-cause mortality and cancer-specific mortality were reduced by 12% (hazard ratio [HR] = 0.88, 95% confidence interval  [95% CI] = 0.87 to 0.89 and HR = 0.88, 95% CI = 0.86 to 0.91, respectively). Further categorical analyses showed a significant dose-response relationship between postdiagnosis physical function categories and mortality outcomes (P  < .001 for trend), where the median survival time for women in the lowest physical function quartile was 9.1 years (Interquartile range [IQR] = 8.6-10.6 years) compared with 18.4 years (IQR = 15.8-22.0 years) for women in the highest physical function quartile. Conclusion Postmenopausal women with low physical function after cancer diagnosis may be at higher risk of mortality from all causes and cancer-related mortality. [ABSTRACT FROM AUTHOR]

PurposeImpaired glucose metabolism-related genetic variants likely interact with obesity-modifiable factors in response to glucose intolerance, yet their interconnected pathways have not been fully characterized.MethodsWith data from 1,027 postmenopausal participants of the Genomics and Randomized Trials Network study and 15 single-nucleotide polymorphisms (SNPs) associated with glucose homeostasis, we assessed whether obesity, physical activity, and high dietary fat intake interact with the SNP-glucose variations. We used regression analysis plus stratification and graphic approaches.ResultsAcross carriers of the 15 SNPs, fasting levels of glucose, insulin, and homeostatic model assessment-insulin resistance (HOMA-IR) were higher in obese, inactive, and high fat-diet women than in their respective counterparts. Carriers within subgroups differently demonstrated the direction and/or magnitude of the variants' effect on glucose-relevant traits. Variants in GCKR, GCK, DGKB/TMEM195 (P for interactions = 0.02, 0.02, and 0.01), especially, showed interactions with obesity: obese, inactive, and high fat-diet women had greater increases in fasting glucose, insulin, and HOMA-IR levels. Obese carriers at TCF7L2 variant had greater increases in fasting glucose levels than nonobese carriers (P for interaction = 0.04), whereas active women had greater decreases in insulin and HOMA-IR levels than inactive women (P for interaction = 0.02 in both levels).ConclusionsOur data support the important role of obesity in modifying glucose homeostasis in response to glucose metabolism-relevant variants. These findings may inform research on the role of glucose homeostasis in the etiology of chronic disease and the development of intervention strategies to reduce risk in postmenopausal women.

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. [ABSTRACT FROM AUTHOR]

Background: Impaired 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.Method: Using 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.Results: Several 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.Conclusions: Our findings suggest that glucose metabolism genetic variants interact with obesity, resulting in altered cancer risk through pathways other than those mediated by glucose metabolism traits. [ABSTRACT FROM AUTHOR]