Background

Inflammatory and insulin pathways have been linked to prostate cancer; postdiagnostic behaviors activating these pathways may lead to poor outcomes. The empirical dietary inflammatory pattern (EDIP), empirical dietary index for hyperinsulinemia (EDIH), and empirical dietary index for insulin resistance (EDIR), and associated lifestyle indices (ELIH, ELIR) predict biomarkers of inflammation (EDIP: IL6, TNFaR2, CRP) and insulin secretion (EDIH/ELIH: c-peptide; EDIR/ELIR: TAG:HDL) from whole foods and behaviors.

Methods

Associations of these indices with time to prostate cancer progression (primary, n = 2,056) and prostate cancer-specific mortality (PCSM; secondary, n = 2,447) were estimated among men diagnosed with nonmetastatic prostate cancer in the Cancer of the Prostate Strategic Urologic Research Endeavor cohort diet and lifestyle sub-study. Because the true (versus clinically documented) date of progression is unobserved, we used parametric (Weibull) survival models to accommodate interval-censoringand estimated adjusted HR and 95% confidence intervals (CI) for prostate cancer progression per 1-SD increase in index. Cox proportional hazards models were used to estimate PCSM associations.

Results

During a median [interquartile range (IQR)] 6.4 years (IQR, 1.3-12.7), 192 progression and 73 PCSM events were observed. Inflammatory (EDIP: HR, 1.27; CI, 1.17-1.37), hyperinsulinemic (EDIH: HR, 1.24; CI, 1.05-1.46. ELIH: HR, 1.34; CI, 1.17-1.54), and insulin-resistant (EDIR: HR, 1.22; CI, 1.00-1.48. ELIR: HR, 1.36; CI, 1.12-1.64) indices were positively associated with risk of prostate cancer progression. There was no evidence of associations between the indices and PCSM.

Conclusions

Both inflammatory and insulinemic dietary and lifestyle patterns are associated with risk of prostate cancer progression.

Impact

For men with prostate cancer, consuming dietary patterns that limit chronic systemic inflammation and insulin hypersecretion may improve survivorship, especially when coupled with active lifestyle and healthy body weight. See related commentary by Kucuk, p. 1673.

Though studies have observed inverse associations between use of analgesics (aspirin, NSAIDs, and acetaminophen) and the risk of several cancers, the potential biological mechanisms underlying these associations are unclear. We investigated the relationship between analgesic use and serum concentrations of estrogens, androgens, and their metabolites among postmenopausal women to provide insights on whether analgesic use might influence endogenous hormone levels, which could in turn influence hormone-related cancer risk. The study included 1,860 postmenopausal women from two case-control studies nested within the Women's Health Initiative Observational Study. Analgesic use was reported at study baseline. Fifteen estrogens and estrogen metabolites and 12 androgens and androgen metabolites were quantified in baseline serum by LC/MS-MS. Linear regression with inverse probability weighting, stratified by menopausal hormone therapy (MHT) use, was used to estimate adjusted geometric mean concentrations of each hormone by analgesic use. Among women not currently using MHT (n = 951), low-dose aspirin (<100 mg) use was associated with a higher serum concentration of estrone, estradiol, and 2, 4, and 16 hydroxylated metabolites. Use of regular-dose aspirin (≥100 mg), non-aspirin NSAIDs, and acetaminophen was not associated with serum concentrations of estrogens, androgens, or their metabolites. This study highlights the importance of examining aspirin use by dose and suggests that low-dose aspirin may influence endogenous estrogen concentrations.

Prevention relevance

This study explores a potential pathway by which analgesic medications such as aspirin may prevent hormone-related cancers. The findings support a positive association between low-dose aspirin use and endogenous estrogens, indicating that further elucidation of the interplay between low-dose aspirin, estrogen concentrations, and cancer risk is needed.

Purpose

Lifestyle factors such as smoking, alcohol, body weight, physical activity, and diet quality have been associated with the risk of pancreatic cancer. However, studies of their combined association in women are limited.

Methods

Data on smoking habits, alcohol intake, diet composition, recreational physical activity, body weight, and waist circumference, obtained at recruitment for 136,945 postmenopausal women (aged 50-79 years) participating in the Women's Health Initiative study, were categorized separately, with higher scores for each variable assigned to the categories representing healthier behaviors. The combined healthy lifestyle index (HLI) score, created by summing the scores for each risk factor, was grouped into quartiles. We used multivariable-adjusted Cox regression to estimate hazard ratios (HR) and 95% confidence intervals (CI) for pancreatic cancer risk in association with the HLI.

Results

Over an average follow-up period of approximately 16.0 years, 1,119 incident cases of pancreatic cancer were ascertained. Compared to women in the lowest HLI quartile, those in the upper quartiles (qt) had a reduced risk of pancreatic cancer (multivariable-adjusted HRqt₃^rd 0.83, 95% CI 0.74-0.99; and HRqt₄^th 0.74, 95% CI 0.62-0.88, respectively, p trend = 0.001). Use of waist circumference instead of BMI in the HLI score yielded similar results. Among women who were either non-diabetic or non-smokers, high HLI was also associated with reduced risk (HRqt₄^th 0.78, 95% CI 0.65-0.85 and HRqt₄^th 0.80, 95% CI 0.66-0.97, respectively). Stratification by BMI categories (18.5- < 25.0, 25.0- < 30.0 and > 30.0 kg/m²) showed similar results in all groups.

Conclusions

Our findings suggest that in postmenopausal women, a healthy lifestyle is associated with reduced risk of pancreatic cancer.

BACKGROUND: Low diet quality, diabetes, and chronic inflammation are risk factors of liver cancer and chronic liver disease (CLD), but the extent to which insulinemic and inflammatory diets are independently associated with risk of liver cancer and CLD mortality is unknown. METHODS: We conducted a prospective cohort analysis among 78,356 postmenopausal women in the Womens Health Initiative Observational Study. Two validated dietary indices, the empirical dietary index for hyperinsulinemia (EDIH) and the empirical dietary inflammation pattern (EDIP), were estimated from a food-frequency questionnaire. Incident cases of liver cancer and CLD mortality were adjudicated via review of medical records and linkage to National Death Index. Multivariable hazard ratios (HRs) with 95% confidence intervals (CIs) were calculated using Cox proportional hazards models, adjusted for age, diabetes, body mass index, and other covariates. RESULTS: During a median 22.1 y of follow-up, we documented 176 primary liver cancer cases and 156 CLD mortality cases. EDIH was positively associated with incident liver cancer (HRQuartile 4 vs. Quartile 1 = 1.68; 95% CI: 1.00, 2.83; P-trend = 0.05) and CLD mortality (HRQ4 vs. Q1 = 2.28; 95% CI: 1.25, 4.15; P-trend = 0.02) in the multivariable model. EDIP was also positively associated with liver cancer (HRQ4 vs. Q1 = 1.88; 95% CI: 1.17, 3.03; P-trend = 0.009) and CLD mortality (HRQ4 vs. Q1 = 1.85; 95% CI: 1.09, 3.15; P-trend = 0.007). Estimates remained significant and robust in sensitivity analyses. Further analyses indicated positive associations for refined grains, processed meat, sugary beverages, and eggs, and inverse associations for coffee/tea and poultry. CONCLUSIONS: Dietary insulinemic and inflammatory potentials were independently associated with higher risk of liver cancer and CLD mortality in U.S. postmenopausal women. These findings suggest a potential role for diet modification to reduce risk of liver cancer and CLD.

BACKGROUND: Previous attempts to identify low-carbohydrate diets (LCDs) in epidemiological studies relied on the LCD Score, which is unable to identify ketogenic dieters. Ketogenic ratios of macronutrients are clinical equations proposed to predict ketogenic diets; however, their utility in epidemiological studies is unknown. OBJECTIVE: To determine the number of participants consuming a ketogenic diet, compare ketogenic ratios to the LCD Score, and evaluate their association with type 2 diabetes mellitus (T2DM). DESIGN: Secondary analysis of the Womens Health Initiative with 17.9 ± 6.03 years of follow-up. Baseline food frequency questionnaires were used to calculate the ketogenic ratio as follows: (0.9 × grams fat + 0.46 × grams protein) / (0.1 × grams fat + 0.58 × grams protein + grams net carbohydrate), a value ≥1.5 is the minimum threshold for a ketogenic diet. PARTICIPANTS/SETTING: One hundred twenty-five nine hundred eighty-two postmenopausal women without diabetes (aged 50 to 79 years) enrolled in the multicenter Womens Health Initiative observational study and clinical trials were included. MAIN OUTCOME MEASURES: Risk of self-reported incident T2DM. STATISTICAL ANALYSES PERFORMED: Cox proportional hazards models, adjusted for age, race, ethnicity, education, income, health insurance, relationship status, geographic region, Womens Health Initiative study component, female hormone use, smoking status, alcohol use, recreational physical activity, total energy intake, diet quality, body mass index, hyperlipidemia, and hypertension, were used to compare hazard ratios and 95% CIs for T2DM among quintiles of the ketogenic ratio. RESULTS: A total of 18,775 incident cases of T2DM occurred. The median ketogenic ratio was 0.35 (interquartile range 0.28 to 0.42) and 15 individuals (0.01%) exceeded the threshold for a ketogenic diet. Higher ketogenic ratio quintiles were associated with increased risk of T2DM in a dose-dependent manner. Comparing extreme quintiles of the ketogenic ratio, the hazard ratio for diabetes was 1.24 (95% CI 1.18 to 1.31; Ptrend < 0.001) in fully adjusted models. Similarly, comparing extreme quintiles, the hazard ratio for diabetes was 1.36 (95% CI 1.29 to 1.43; Ptrend < 0.001) for the LCD Score and 1.13 (95% CI 1.07 to 1.19; Ptrend < 0.001) for the simplified ketogenic ratio in fully adjusted models. CONCLUSIONS: Increasing ketogenic ratio values are associated with increased risk of T2DM and align well with LCD Scores; however, too few participants consumed a ketogenic diet to determine its association with T2DM.

Background

Pancreatic cancer risk is increasing in countries with high consumption of Western dietary patterns and rising obesity rates. We examined the hypothesis that specific dietary patterns reflecting hyperinsulinemia (empirical dietary index for hyperinsulinemia; EDIH), systemic inflammation (empirical dietary inflammatory pattern; EDIP), and postprandial glycemia [glycemic index (GI); glycemic load (GL)] are associated with pancreatic cancer risk, including the potential modifying role of type 2 diabetes (T2D) and body mass index (BMI).

Methods

We calculated dietary scores from baseline (1993-1998) food frequency questionnaires among 129,241 women, 50-79 years-old in the Women's Health Initiative. We used multivariable-adjusted Cox regression to estimate HRs and 95% confidence intervals (95% CI) for pancreatic cancer risk.

Results

During a median 19.9 years of follow-up, 850 pancreatic cancer cases were diagnosed. We observed no association between dietary scores and pancreatic cancer risk overall. However, risk was elevated among participants with longstanding T2D (present >3 years before pancreatic cancer diagnosis) for EDIH. For each 1 SD increment in dietary score, the HRs (95% CIs) were: EDIH, 1.33 (1.06-1.66); EDIP, 1.26 (0.98-1.63); GI, 1.26 (0.96-1.67); and GL, 1.23 (0.96-1.57); although interactions were not significant (all P _interaction >0.05). Separately, we observed inverse associations between GI [0.86 (0.76-0.96), P _interaction = 0.0068] and GL [0.83 (0.73-0.93), P _interaction = 0.0075], with pancreatic cancer risk among normal-weight women.

Conclusions

We observed no overall association between the dietary patterns evaluated and pancreatic cancer risk, although women with T2D appeared to have greater cancer risk.

Impact

The elevated risk for hyperinsulinemic diets among women with longstanding T2D and the inverse association among normal-weight women warrant further examination.

We utilized the dietary inflammatory index (DII) to investigate associations between patterns of change in, and history of the inflammatory potential of diet and risk of breast cancer in the Women's Health Initiative (WHI). We included 70,998 postmenopausal women aged 50-79 years recruited from 1993 to 1998 into the WHI Observational Study and Dietary Modification trial control group and followed through August 29, 2014. We utilized data from food frequency questionnaires administered at baseline and Year 3, to calculate average DII scores, patterns of change in DII, and used these measures in multivariable-adjusted Cox regression models to estimate hazards ratios (HR) and 95 % confidence intervals (CI) for incident invasive breast cancer and its subtypes. After 1,093,947 person-years of follow-up, 3471 cases of invasive breast cancer were identified. There was no substantial association between average DII scores or patterns of change in DII and risk of overall invasive breast cancer (HR, 1.03; 95 % CI, 0.90, 1.17; P-trend = 0.79; comparing extreme average DII quintiles). However, there was a significant nonlinear association between average DII scores and the ER-, PR-, HER2+, subtype (HR, 2.37; 95 % CI, 1.08, 5.20; P-trend = 0.18; comparing extreme quintiles). For patterns of change in DII, the age-adjusted association with ER-, PR-, HER2+ subtype comparing women in the proinflammatory stable to those in the anti-inflammatory stable categories (HR, 1.82; 95 % CI, 1.06, 3.13) persisted in the multivariable-adjusted model but was less precise (HR, 1.85; 95 % CI, 0.96, 3.55; P = 0.06). Dietary inflammatory potential may differentially influence the development of specific breast cancer phenotypes.

Purpose

Many dietary factors have either proinflammatory or anti-inflammatory properties. We previously developed a dietary inflammatory index (DII) to assess the inflammatory potential of diet. In this study, we conducted a construct validation of the DII based on data from a food frequency questionnaire and three inflammatory biomarkers in a subsample of 2567 postmenopausal women in the Women's Health Initiative Observational Study.

Methods

We used multiple linear and logistic regression models, controlling for potential confounders, to test whether baseline DII predicted concentrations of interleukin-6, high-sensitivity C-reactive protein (hs-CRP), tumor necrosis factor alpha receptor 2, or an overall biomarker score combining all three inflammatory biomarkers.

Results

The DII was associated with the four biomarkers with beta estimates (95% confidence interval) comparing the highest with lowest DII quintiles as follows: interleukin-6: 1.26 (1.15-1.38), Ptrend < .0001; tumor necrosis factor alpha receptor 2: 81.43 (19.15-143.71), Ptrend = .004; dichotomized hs-CRP (odds ratio for higher vs. lower hs-CRP): 1.30 (0.97-1.67), Ptrend = .34; and the combined inflammatory biomarker score: 0.26 (0.12-0.40), Ptrend = .0001.

Conclusions

The DII was significantly associated with inflammatory biomarkers. Construct validity of the DII indicates its utility for assessing the inflammatory potential of diet and for expanding its use to include associations with common chronic diseases in future studies.

Objective

The empirical dietary index for hyperinsulinemia (EDIH) and empirical dietary inflammatory pattern (EDIP) scores assess the insulinemic and inflammatory potentials of habitual dietary patterns, irrespective of the macronutrient content, and are based on plasma insulin response or inflammatory biomarkers, respectively. The glycemic index (GI) and glycemic load (GL) assess postprandial glycemic potential based on dietary carbohydrate content. We tested the hypothesis that dietary patterns promoting hyperinsulinemia, chronic inflammation, or hyperglycemia may influence type 2 diabetes risk.

Research design and methods

We calculated dietary scores from baseline (1993-1998) food frequency questionnaires among 73,495 postmenopausal women in the Women's Health Initiative, followed through March 2019. We used multivariable-adjusted Cox regression to estimate hazard ratios (HRs) and 95% CIs for type 2 diabetes risk. We also estimated multivariable-adjusted absolute risk of type 2 diabetes.

Results

During a median 13.3 years of follow-up, 11,009 incident cases of type 2 diabetes were diagnosed. Participants consuming the most hyperinsulinemic or proinflammatory dietary patterns experienced greater risk of type 2 diabetes; HRs (95% CI) comparing highest to lowest dietary index quintiles were EDIH 1.49 (1.32-1.68; P _trend < 0.0001) and EDIP 1.45 (1.29-1.63; P _trend < 0.0001). The absolute excess incidence for the same comparison was 220 (EDIH) and 271 (EDIP) cases per 100,000 person-years. GI and GL were not associated with type 2 diabetes risk: GI 0.99 (0.88-1.12; P _trend = 0.46) and GL 1.01 (0.89-1.16; P _trend = 0.30).

Conclusions

Our findings in this diverse cohort of postmenopausal women suggest that lowering the insulinemic and inflammatory potentials of the diet may be more effective in preventing type 2 diabetes than focusing on glycemic foods.

The prevalence of obesity, defined as the body mass index (BMI) ≥ 30 kg/m2, has reached epidemic levels. Obesity is associated with an increased risk of various cancers, including gastrointestinal ones. Recent evidence has suggested that obesity disproportionately impacts males and females with cancer, resulting in varied transcriptional and metabolic dysregulation. This study aimed to elucidate the differences in the metabolic milieu of adenocarcinomas of the gastrointestinal (GI) tract both related and unrelated to sex in obesity. To demonstrate these obesity and sex-related effects, we utilized three primary data sources: serum metabolomics from obese and non-obese patients assessed via the Biocrates MxP Quant 500 mass spectrometry-based kit, the ORIEN tumor RNA-sequencing data for all adenocarcinoma cases to assess the impacts of obesity, and publicly available TCGA transcriptional analysis to assess GI cancers and sex-related differences in GI cancers specifically. We applied and integrated our unique transcriptional metabolic pipeline in combination with our metabolomics data to reveal how obesity and sex can dictate differential metabolism in patients. Differentially expressed genes (DEG) analysis of ORIEN obese adenocarcinoma as compared to normal-weight adenocarcinoma patients resulted in large-scale transcriptional reprogramming (4029 DEGs, adj. p < 0.05 and |logFC| > 0.58). Gene Set Enrichment and metabolic pipeline analysis showed genes enriched for pathways relating to immunity (inflammation, and CD40 signaling, among others) and metabolism. Specifically, we found alterations to steroid metabolism and tryptophan/kynurenine metabolism in obese patients, both of which are highly associated with disease severity and immune cell dysfunction. These findings were further confirmed using the TCGA colorectal adenocarcinoma (CRC) and esophageal adenocarcinoma (ESCA) data, which showed similar patterns of increased tryptophan catabolism for kynurenine production in obese patients. These patients further showed disparate alterations between males and females when comparing obese to non-obese patient populations. Alterations to immune and metabolic pathways were validated in six patients (two obese and four normal weight) via CD8+/CD4+ peripheral blood mononuclear cell RNA-sequencing and paired serum metabolomics, which showed differential kynurenine and lipid metabolism, which corresponded with altered T-cell transcriptome in obese populations. Overall, obesity is associated with differential transcriptional and metabolic programs in various disease sites. Further, these alterations, such as kynurenine and tryptophan metabolism, which impact both metabolism and immune phenotype, vary with sex and obesity together. This study warrants further in-depth investigation into obesity and sex-related alterations in cancers that may better define biomarkers of response to immunotherapy.