MATERIALS & METHODS: Here, we examined the potential of DNA methylation changes in 910 prediagnostic peripheral blood samples as a marker of exposure to tobacco smoke in a large multinational cohort.
RESULTS: We identified 748 CpG sites that were differentially methylated between smokers and nonsmokers, among which we identified novel regionally clustered CpGs associated with active smoking. Importantly, we found a marked reversibility of methylation changes after smoking cessation, although specific genes remained differentially methylated up to 22 years after cessation.
CONCLUSION: Our study has comprehensively cataloged the smoking-associated DNA methylation alterations and showed that these alterations are reversible after smoking cessation.
METHODS: Data on highest education attained were gathered for 459,170 participants (70% women) from 10 European countries. A relative index of inequality (RII) based on adult education was calculated for comparability across countries and generations. Cox regression models were applied to estimate relative inequality in pancreatic cancer risk, stratifying by age, gender, and center, and adjusting for known pancreatic cancer risk factors.
RESULTS: A total of 1,223 incident pancreatic cancer cases were included after a mean follow-up of 13.9 (±4.0) years. An inverse social trend was found in models adjusted for age, sex, and center for both sexes [HR of RII, 1.27; 95% confidence interval (CI), 1.02-1.59], which was also significant among women (HR, 1.42; 95% CI, 1.05-1.92). Further adjusting by smoking intensity, alcohol consumption, body mass index, prevalent diabetes, and physical activity led to an attenuation of the RII risk and loss of statistical significance.
CONCLUSIONS: The present reanalysis does not sustain the existence of an independent social inequality influence on pancreatic cancer risk in Western European women and men, using an index based on adult education, the most relevant social indicator linked to individual lifestyles, in a context of very low pancreatic cancer survival from (quasi) universal public health systems.
IMPACT: The results do not support an association between education and risk of pancreatic cancer.
METHODS: Relative mortality and mortality rate advancement periods (RAPs) were estimated by Cox proportional hazards models for the population-based prospective cohort studies from Europe and the U.S. (CHANCES [Consortium on Health and Ageing: Network of Cohorts in Europe and the U.S.]), and subsequently pooled by individual participant meta-analysis. Statistical analyses were performed from June 2013 to March 2014.
RESULTS: A total of 489,056 participants aged ≥60 years at baseline from 22 population-based cohort studies were included. Overall, 99,298 deaths were recorded. Current smokers had 2-fold and former smokers had 1.3-fold increased mortality compared with never smokers. These increases in mortality translated to RAPs of 6.4 (95% CI=4.8, 7.9) and 2.4 (95% CI=1.5, 3.4) years, respectively. A clear positive dose-response relationship was observed between number of currently smoked cigarettes and mortality. For former smokers, excess mortality and RAPs decreased with time since cessation, with RAPs of 3.9 (95% CI=3.0, 4.7), 2.7 (95% CI=1.8, 3.6), and 0.7 (95% CI=0.2, 1.1) for those who had quit <10, 10 to 19, and ≥20 years ago, respectively.
CONCLUSIONS: Smoking remains as a strong risk factor for premature mortality in older individuals and cessation remains beneficial even at advanced ages. Efforts to support smoking abstinence at all ages should be a public health priority.
METHODS: We built two models, for ER+ (ModelER+) and ER- tumors (ModelER-), respectively, in 281,330 women (51% postmenopausal at recruitment) from the European Prospective Investigation into Cancer and Nutrition cohort. Discrimination (C-statistic) and calibration (the agreement between predicted and observed tumor risks) were assessed both internally and externally in 82,319 postmenopausal women from the Women's Health Initiative study. We performed decision curve analysis to compare ModelER+ and the Gail model (ModelGail) regarding their applicability in risk assessment for chemoprevention.
RESULTS: Parity, number of full-term pregnancies, age at first full-term pregnancy and body height were only associated with ER+ tumors. Menopausal status, age at menarche and at menopause, hormone replacement therapy, postmenopausal body mass index, and alcohol intake were homogeneously associated with ER+ and ER- tumors. Internal validation yielded a C-statistic of 0.64 for ModelER+ and 0.59 for ModelER-. External validation reduced the C-statistic of ModelER+ (0.59) and ModelGail (0.57). In external evaluation of calibration, ModelER+ outperformed the ModelGail: the former led to a 9% overestimation of the risk of ER+ tumors, while the latter yielded a 22% underestimation of the overall BC risk. Compared with the treat-all strategy, ModelER+ produced equal or higher net benefits irrespective of the benefit-to-harm ratio of chemoprevention, while ModelGail did not produce higher net benefits unless the benefit-to-harm ratio was below 50. The clinical applicability, i.e. the area defined by the net benefit curve and the treat-all and treat-none strategies, was 12.7 × 10- 6 for ModelER+ and 3.0 × 10- 6 for ModelGail.
CONCLUSIONS: Modeling heterogeneous epidemiological risk factors might yield little improvement in BC risk prediction. Nevertheless, a model specifically predictive of ER+ tumor risk could be more applicable than an omnibus model in risk assessment for chemoprevention.
METHODS: Associations between prediagnostic plasma levels of 17 primary, secondary, and tertiary bile acid metabolites (conjugated and unconjugated) and colon cancer risk were evaluated in a nested case-control study within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. Bile acid levels were quantified by tandem mass spectrometry in samples from 569 incident colon cancer cases and 569 matched controls. Multivariable logistic regression analyses were used to estimate odds ratios (ORs) for colon cancer risk across quartiles of bile acid concentrations.
RESULTS: Positive associations were observed between colon cancer risk and plasma levels of seven conjugated bile acid metabolites: the primary bile acids glycocholic acid (ORquartile 4 vs quartile 1= 2.22, 95% confidence interval [CI] = 1.52 to 3.26), taurocholic acid (OR = 1.78, 95% CI = 1.23 to 2.58), glycochenodeoxycholic acid (OR = 1.68, 95% CI = 1.13 to 2.48), taurochenodeoxycholic acid (OR = 1.62, 95% CI = 1.11 to 2.36), and glycohyocholic acid (OR = 1.65, 95% CI = 1.13 to 2.40), and the secondary bile acids glycodeoxycholic acid (OR = 1.68, 95% CI = 1.12 to 2.54) and taurodeoxycholic acid (OR = 1.54, 95% CI = 1.02 to 2.31). By contrast, unconjugated bile acids and tertiary bile acids were not associated with risk.
CONCLUSIONS: This prospective study showed that prediagnostic levels of certain conjugated primary and secondary bile acids were positively associated with risk of colon cancer. Our findings support experimental data to suggest that a high bile acid load is colon cancer promotive.
METHODS: Baseline plasma fatty acid concentrations were determined in a representative EPIC sample from the 23 participating EPIC centers. A total of 1,945 individuals were followed for a median of 4.9 years to monitor weight change. The association between elaidic acid level and percent change of weight was investigated using a multinomial logistic regression model, adjusted by length of follow-up, age, energy, alcohol, smoking status, physical activity, and region.
RESULTS: In women, doubling elaidic acid was associated with a decreased risk of weight loss (odds ratio (OR) = 0.69, 95% confidence interval (CI) = 0.55-0.88, p = 0.002) and a trend was observed with an increased risk of weight gain during the 5-year follow-up (OR = 1.23, 95% CI = 0.97-1.56, p = 0.082) (p-trend
METHODS: We conducted a nested case-control study in a cohort of 519 978 men and women aged 25 to 70 years followed from 1992 to 2003. A total of 713 incident colon cancer cases were matched, using risk-set sampling, to 713 controls on age, sex, study centre, fasting status and hormonal therapy use. The amount of total physical activity during the past year was expressed in metabolic equivalent of task [MET]-h/week. Anthropometric measurements and blood samples were collected at study baseline.
RESULTS: High physical activity was associated with a lower risk of colon cancer: relative risk ≥91 MET-h/week vs <91 MET-h/week = 0.75 [95% confidence interval (CI): 0.57 to 0.96]. In mediation analyses, this association was accounted for by waist circumference: proportion explained effect (PEE) = 17%; CI: 4% to 52%; and the biomarkers soluble leptin receptor (sOB-R): PEE = 15%; 95% CI: 1% to 50% and 5-hydroxyvitamin D (25[OH]D): PEE = 30%; 95% CI: 12% to 88%. In combination, these factors explained 45% (95% CI: 20% to 125%) of the association. Beyond waist circumference, sOB-R and 25[OH]D additionally explained 10% (95% CI: 1%; 56%) and 23% (95% CI: 6%; 111%) of the association, respectively.
CONCLUSIONS: Promoting physical activity, particularly outdoors, and maintaining metabolic health and adequate vitamin D levels could represent a promising strategy for colon cancer prevention.
METHODS: We examined associations of body mass index (BMI), waist circumference (WC), and waist-hip ratio (WHR) with lung cancer risk among 1.6 million Americans, Europeans, and Asians. Cox proportional hazard regression was used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) with adjustment for potential confounders. Analyses for WC/WHR were further adjusted for BMI. The joint effect of BMI and WC/WHR was also evaluated.
RESULTS: During an average 12-year follow-up, 23 732 incident lung cancer cases were identified. While BMI was generally associated with a decreased risk, WC and WHR were associated with increased risk after controlling for BMI. These associations were seen 10 years before diagnosis in smokers and never smokers, were strongest among blacks, and varied by histological type. After excluding the first five years of follow-up, hazard ratios per 5 kg/m2 increase in BMI were 0.95 (95% CI = 0.90 to 1.00), 0.92 (95% CI = 0.89 to 0.95), and 0.89 (95% CI = 0.86 to 0.91) in never, former, and current smokers, and 0.86 (95% CI = 0.84 to 0.89), 0.94 (95% CI = 0.90 to 0.99), and 1.09 (95% CI = 1.03 to 1.15) for adenocarcinoma, squamous cell, and small cell carcinoma, respectively. Hazard ratios per 10 cm increase in WC were 1.09 (95% CI = 1.00 to 1.18), 1.12 (95% CI = 1.07 to 1.17), and 1.11 (95% CI = 1.07 to 1.16) in never, former, and current smokers, and 1.06 (95% CI = 1.01 to 1.12), 1.20 (95% CI = 1.12 to 1.29), and 1.13 (95% CI = 1.04 to 1.23) for adenocarcinoma, squamous cell, and small cell carcinoma, respectively. Participants with BMIs of less than 25 kg/m2 but high WC had a 40% higher risk (HR = 1.40, 95% CI = 1.26 to 1.56) than those with BMIs of 25 kg/m2 or greater but normal/moderate WC.
CONCLUSIONS: The inverse BMI-lung cancer association is not entirely due to smoking and reverse causation. Central obesity, particularly concurrent with low BMI, may help identify high-risk populations for lung cancer.
METHODS AND FINDINGS: This prospective analysis included 471,495 adults from the European Prospective Investigation into Cancer and Nutrition (EPIC, 1992-2014, median follow-up: 15.3 y), among whom there were 49,794 incident cancer cases (main locations: breast, n = 12,063; prostate, n = 6,745; colon-rectum, n = 5,806). Usual food intakes were assessed with standardized country-specific diet assessment methods. The FSAm-NPS was calculated for each food/beverage using their 100-g content in energy, sugar, saturated fatty acid, sodium, fibres, proteins, and fruits/vegetables/legumes/nuts. The FSAm-NPS scores of all food items usually consumed by a participant were averaged to obtain the individual FSAm-NPS Dietary Index (DI) scores. Multi-adjusted Cox proportional hazards models were computed. A higher FSAm-NPS DI score, reflecting a lower nutritional quality of the food consumed, was associated with a higher risk of total cancer (HRQ5 versus Q1 = 1.07; 95% CI 1.03-1.10, P-trend < 0.001). Absolute cancer rates in those with high and low (quintiles 5 and 1) FSAm-NPS DI scores were 81.4 and 69.5 cases/10,000 person-years, respectively. Higher FSAm-NPS DI scores were specifically associated with higher risks of cancers of the colon-rectum, upper aerodigestive tract and stomach, lung for men, and liver and postmenopausal breast for women (all P < 0.05). The main study limitation is that it was based on an observational cohort using self-reported dietary data obtained through a single baseline food frequency questionnaire; thus, exposure misclassification and residual confounding cannot be ruled out.
CONCLUSIONS: In this large multinational European cohort, the consumption of food products with a higher FSAm-NPS score (lower nutritional quality) was associated with a higher risk of cancer. This supports the relevance of the FSAm-NPS as underlying nutrient profiling system for front-of-pack nutrition labels, as well as for other public health nutritional measures.
METHODS: Using data from 272,098 women participating in the European Prospective Investigation into Cancer and Nutrition (EPIC) study, we assessed dietary intake of 92 foods and nutrients estimated by dietary questionnaires. Cox regression was used to quantify the association between each food/nutrient and risk of breast cancer. A false discovery rate (FDR) of 0.05 was used to select the set of foods and nutrients to be replicated in the independent Netherlands Cohort Study (NLCS).
RESULTS: Six foods and nutrients were identified as associated with risk of breast cancer in the EPIC study (10,979 cases). Higher intake of alcohol overall was associated with a higher risk of breast cancer (hazard ratio (HR) for a 1 SD increment in intake = 1.05, 95% CI 1.03-1.07), as was beer/cider intake and wine intake (HRs per 1 SD increment = 1.05, 95% CI 1.03-1.06 and 1.04, 95% CI 1.02-1.06, respectively), whereas higher intakes of fibre, apple/pear, and carbohydrates were associated with a lower risk of breast cancer (HRs per 1 SD increment = 0.96, 95% CI 0.94-0.98; 0.96, 95% CI 0.94-0.99; and 0.96, 95% CI 0.95-0.98, respectively). When evaluated in the NLCS (2368 cases), estimates for each of these foods and nutrients were similar in magnitude and direction, with the exception of beer/cider intake, which was not associated with risk in the NLCS.
CONCLUSIONS: Our findings confirm a positive association of alcohol consumption and suggest an inverse association of dietary fibre and possibly fruit intake with breast cancer risk.
SUBJECTS/METHODS: Nested within the European Prospective Investigation into Cancer and Nutrition (EPIC-IBD), incident UC and CD cases and matched controls where included. At recruitment, participants completed validated food frequency and lifestyle questionnaires. Alcohol consumption was classified as either: non-use, former, light (⩽0.5 and 1 drink per week), below the recommended limits (BRL) (⩽1 and 2 drinks per day), moderate (⩽2.5 and 5 drinks per day), or heavy use (>2.5 and >5 drinks per day) for women and men, respectively; and was expressed as consumption at enrolment and during lifetime. Conditional logistic regression was applied adjusting for smoking and education, taking light users as the reference.
RESULTS: Out of 262 451 participants in six countries, 198 UC incident cases/792 controls and 84 CD cases/336 controls were included. At enrolment, 8%/27%/32%/23%/11% UC cases and 7%/29%/40%/19%/5% CD cases were: non-users, light, BRL, moderate and heavy users, respectively. The corresponding figures for lifetime non-use, former, light, BRL, moderate and heavy use were: 3%/5%/23%/44%/19%/6% and 5%/2%/25%/44%/23%/1% for UC and CD cases, respectively. There were no associations between any categories of alcohol consumption and risk of UC or CD in the unadjusted and adjusted odds ratios.
CONCLUSION: There was no evidence of associations between alcohol use and the odds of developing either UC or CD.