CENPHER five year report 2009-2014: From a research project to a research center

Other than the influence of ionizing radiation and benign thyroid disease, little is known about the risk factors for differentiated thyroid cancer (TC) which is an increasing common cancer worldwide. Consistent evidence shows that body mass is positively associated with TC risk. As excess weight is a state of chronic inflammation, we investigated the relationship between concentrations of leptin, adiponectin, C-reactive protein, interleukin (IL)-6, IL-10 and tumor necrosis factor (TNF)-α and the risk of TC. A case-control study was nested within the European Prospective Investigation into Cancer and Nutrition (EPIC) study and included 475 first primary incident TC cases (399 women and 76 men) and 1,016 matched cancer-free cohort participants. Biomarkers were measured in serum samples using validated and highly sensitive commercially available immunoassays. Odds ratios (ORs) of TC by levels of each biomarker were estimated using conditional logistic regression models, adjusting for BMI and alcohol consumption. Adiponectin was inversely associated with TC risk among women (ORT3vs.T1 = 0.69, 95% CI: 0.49-0.98, Ptrend = 0.04) but not among men (ORT3vs.T1 = 1.36, 95% CI: 0.67-2.76, Ptrend = 0.37). Increasing levels of IL-10 were positively associated with TC risk in both genders and significantly so in women (ORT3vs.T1 = 1.59, 95% CI: 1.13-2.25, Ptrend = 0.01) but not in men (ORT3vs.T1 = 1.78, 95% CI: 0.80-3.98, Ptrend = 0.17). Leptin, CRP, IL-6 and TNF-α were not associated with TC risk in either gender. These results indicate a positive association of TC risk with IL-10 and a negative association with adiponectin that is probably restricted to women. Inflammation may play a role in TC in combination with or independently of excess weight

Plasma Elaidic Acid Level as Biomarker of Industrial Trans Fatty Acids and Risk of Weight Change: Report from the EPIC Study

Background Few epidemiological studies have examined the association between dietary trans fatty acids and weight gain, and the evidence remains inconsistent. The main objective of the study was to investigate the prospective association between biomarker of industrial trans fatty acids and change in weight within the large study European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. 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<.0001). In men, a trend was observed for doubling elaidic acid level and risk of weight loss (OR = 0.82, 95% CI = 0.66-1.01, p = 0.062) while no significant association was found with risk of weight gain during the 5-year follow-up (OR = 1.08, 95% CI = 0.88-1.33, p = 0.454). No association was found for saturated and cis-monounsaturated fatty acids. Conclusions These data suggest that a high intake of industrial trans fatty acids may decrease the risk of weight loss, particularly in women. Prevention of obesity should consider limiting the consumption of highly processed foods, the main source of industrially-produced trans fatty acids

Alcohol intake and breast cancer in the European prospective investigation into cancer and nutrition

Alcohol intake has been associated to breast cancer in pre and postmenopausal women; however results are inconclusive regarding tumor hormonal receptor status, and potential modifying factors like age at start drinking. Therefore, we investigated the relation between alcohol intake and the risk of breast cancer using prospective observational data from the European Prospective Investigation into Cancer and Nutrition (EPIC). Up to 334,850 women, aged 35-70 years at baseline, were recruited in ten European countries and followed up an average of 11 years. Alcohol intake at baseline and average lifetime alcohol intake were calculated from country-specific dietary and lifestyle questionnaires. The study outcomes were the Hazard ratios (HR) of developing breast cancer according to hormonal receptor status. During 3,670,439 person-years, 11,576 incident breast cancer cases were diagnosed. Alcohol intake was significantly related to breast cancer risk, for each 10 g/day increase in alcohol intake the HR increased by 4.2% (95% CI: 2.7-5.8%). Taking 0 to 5 g/day as reference, alcohol intake of >5 to 15 g/day was related to a 5.9% increase in breast cancer risk (95% CI: 1-11%). Significant increasing trends were observed between alcohol intake and ER+/PR+, ER-/PR-, HER2- and ER-/PR-HER2- tumors. Breast cancer risk was stronger among women who started drinking prior to first full-time pregnancy. Overall, our results confirm the association between alcohol intake and both hormone receptor positive and hormone receptor negative breast tumors, suggesting that timing of exposure to alcohol drinking may affect the risk. Therefore, women should be advised to control their alcohol consumption. What's new? Although it is now established that alcohol consumption increases breast cancer risk, many questions remain. Using a prospective study design with 11,576 incident breast cancer cases across 10 European countries, the authors confirmed the increased risk of alcohol on breast cancer development. They further show that women who started drinking before their first full-term pregnancy have a higher risk than women who started afterwards. These effects were observed in hormone-receptor positive and -negative tumors pointing to non-hormonal pathways that need to be further investigated

Reliability Estimates For assessing Meal Timing Derived From Longitudinal Repeated 24-Hour Dietary Recalls

BACKGROUND: Regulating meal timing may have efficacy for improving metabolic health for preventing or managing chronic disease. However, the reliability of measuring meal timing with commonly used dietary assessment tools needs characterization prior to investigating meal timing and health outcomes in epidemiologic studies. OBJECTIVES: to evaluate the reliability of estimating meal timing parameters, including overnight fasting duration, the midpoint of overnight fasting time, the number of daily eating episodes, the period with the largest percentage of daily caloric intake, and late last eating episode (\u3e 09:00 pm) from repeated 24-h dietary recalls (24HRs). METHODS: Intraclass correlation coefficients (ICC), Light\u27s Kappa estimates, and 95% CIs were calculated from repeated 24HR administered in 3 epidemiologic studies: The United States-based Interactive Diet and Activity Tracking in AARP (IDATA) study (n = 996, 6 24HR collected over 12-mo), German EPIC-Potsdam Validation Study (European Prospective Investigation into Cancer and Nutrition Potsdam Germany cohort) (n = 134, 12 24HR collected over 12-mo) and EPIC-Potsdam BMBF-II Study (Federal Ministry of Education and Research, Bundesministerium für Bildung und Forschung ) (n = 725, 4 24HR collected over 36 mo). RESULTS: Measurement reliability of overnight fasting duration based on a single 24HR was poor in all studies [ICC range: 0.27; 95% CI: 0.23, 0.32 - 0.46; 95% CI: 0.43, 0.50]. Reliability was moderate with 3 24HR (ICC range: 0.53; 95% CI: 0.47, 0.58 in IDATA, 0.62; 95% CI: 0.52, 0.69 in the EPIC-Potsdam Validation Study, and 0.72; 95% CI: 0.70-0.75 in the EPIC-Potsdam BMBF-II Study). Results were similar for the midpoint of overnight fasting time and the number of eating episodes. Reliability of measuring late eating was fair in IDATA (Light\u27s Kappa: 0.30; 95% CI: 0.21, 0.39) and slight in the EPIC-Potsdam Validation study and the EPIC-Potsdam BMBF-II study (Light\u27s Kappa: 0.19; 95% CI: 0.15, 0.25 and 0.09; 95% CI: 0.06, 0.12, respectively). Reliability estimates differed by sex, BMI, weekday, and season of 24HR administration in some studies. CONCLUSIONS: Our results show that ≥ 3 24HR over a 1-3-y period are required for reliable estimates of meal timing variables

Characterization of the degree of food processing in the European Prospective Investigation into Cancer and Nutrition: Application of the Nova classification and validation using selected biomarkers of food processing

Background: Epidemiological studies have demonstrated an association between the degree of food processing in our diet and the risk of various chronic diseases. Much of this evidence is based on the international Nova classification system, which classifies food into four groups based on the type of processing: (1) Unprocessed and minimally processed foods, (2) Processed culinary ingredients, (3) Processed foods, and (4) “Ultra-processed” foods (UPF). The ability of the Nova classification to accurately characterise the degree of food processing across consumption patterns in various European populations has not been investigated so far. Therefore, we applied the Nova coding to data from the European Prospective Investigation into Cancer and Nutrition (EPIC) in order to characterize the degree of food processing in our diet across European populations with diverse cultural and socio-economic backgrounds and to validate this Nova classification through comparison with objective biomarker measurements. Methods: After grouping foods in the EPIC dataset according to the Nova classification, a total of 476,768 participants in the EPIC cohort (71.5% women; mean age 51 [standard deviation (SD) 9.93]; median age 52 [percentile (p)25–p75: 58–66] years) were included in the cross-sectional analysis that characterised consumption patterns based on the Nova classification. The consumption of food products classified as different Nova categories were compared to relevant circulating biomarkers denoting food processing, measured in various subsamples (N between 417 and 9,460) within the EPIC cohort via (partial) correlation analyses (unadjusted and adjusted by sex, age, BMI and country). These biomarkers included an industrial transfatty acid (ITFA) isomer (elaidic acid; exogenous fatty acid generated during oil hydrogenation and heating) and urinary 4-methyl syringol sulfate (an indicator for the consumption of smoked food and a component of liquid smoke used in UPF). Results: Contributions of UPF intake to the overall diet in % grams/day varied across countries from 7% (France) to 23% (Norway) and their contributions to overall % energy intake from 16% (Spain and Italy) to >45% (in the UK and Norway). Differences were also found between sociodemographic groups; participants in the highest fourth of UPF consumption tended to be younger, taller, less educated, current smokers, more physically active, have a higher reported intake of energy and lower reported intake of alcohol. The UPF pattern as defined based on the Nova classification (group 4;% kcal/day) was positively associated with blood levels of industrial elaidic acid (r = 0.54) and 4-methyl syringol sulfate (r = 0.43). Associations for the other 3 Nova groups with these food processing biomarkers were either inverse or non-significant (e.g., for unprocessed and minimally processed foods these correlations were –0.07 and –0.37 for elaidic acid and 4-methyl syringol sulfate, respectively). Conclusion: These results, based on a large pan-European cohort, demonstrate sociodemographic and geographical differences in the consumption of UPF. Furthermore, these results suggest that the Nova classification can accurately capture consumption of UPF, reflected by stronger correlations with circulating levels of industrial elaidic acid and a syringol metabolite compared to diets high in minimally processed foods

Prospective analysis of circulating metabolites and endometrial cancer risk

Background: Endometrial cancer is strongly associated with obesity and dysregulation of metabolic factors such as estrogen and insulin signaling are causal risk factors for this malignancy. To identify additional novel metabolic pathways associated with endometrial cancer we performed metabolomic analyses on pre-diagnostic plasma samples from 853 case-control pairs from the European Prospective Investigation into Cancer and Nutrition (EPIC). Methods: A total of 129 metabolites (acylcarnitines, amino acids, biogenic amines, glycerophospholipids, hexoses, and sphingolipids) were measured by liquid chromatography-mass spectrometry. Conditional logistic regression estimated the associations of metabolites with endometrial cancer risk. An analysis focusing on clusters of metabolites using the bootstrap lasso method was also employed. Results: After adjustment for body mass index, sphingomyelin [SM] C18:0 was positively (OR1SD: 1.18, 95% CI: 1.05-1.33), and glycine, serine, and free carnitine (C0) were inversely (OR1SD: 0.89, 95% CI: 0.80-0.99; OR1SD: 0.89, 95% CI: 0.79-1.00 and OR1SD: 0.91, 95% CI: 0.81-1.00, respectively) associated with endometrial cancer risk. Serine, C0 and two sphingomyelins were selected by the lasso method in >90% of the bootstrap samples. The ratio of esterified to free carnitine (OR1SD: 1.14, 95% CI: 1.02-1.28) and that of short chain to free acylcarnitines (OR1SD: 1.12, 95% CI: 1.00-1.25) were positively associated with endometrial cancer risk. Further adjustment for C-peptide or other endometrial cancer risk factors only minimally altered the results. Conclusion: These findings suggest that variation in levels of glycine, serine, SM C18:0 and free carnitine may represent specific pathways linked to endometrial cancer development. If causal, these pathways may offer novel targets for endometrial cancer prevention

Association of body shape phenotypes and body fat distribution indexes with inflammatory biomarkers in the European Prospective Investigation into Cancer and Nutrition (EPIC) and UK Biobank

Background: The allometric body shape index (ABSI) and hip index (HI), as well as multi-trait body shape phenotypes, have not yet been compared in their associations with inflammatory markers. The aim of this study was to examine the relationship between novel and traditional anthropometric indexes with inflammation using data from the European Prospective Investigation into Cancer and Nutrition (EPIC) and UK Biobank cohorts. Methods: Participants from EPIC (n = 17,943, 69.1% women) and UK Biobank (n = 426,223, 53.2% women) with data on anthropometric indexes and C-reactive protein (CRP) were included in this cross-sectional analysis. A subset of women in EPIC also had at least one measurement for interleukins, tumour necrosis factor alpha, interferon gamma, leptin, and adiponectin. Four distinct body shape phenotypes were derived by a principal component (PC) analysis on height, weight, body mass index (BMI), waist (WC) and hip circumferences (HC), and waist-to-hip ratio (WHR). PC1 described overall adiposity, PC2 tall with low WHR, PC3 tall and centrally obese, and PC4 high BMI and weight with low WC and HC, suggesting an athletic phenotype. ABSI, HI, waist-to-height ratio and waist-to-hip index (WHI) were also calculated. Linear regression models were carried out separately in EPIC and UK Biobank stratified by sex and adjusted for age, smoking status, education, and physical activity. Results were additionally combined in a random-effects meta-analysis. Results: Traditional anthropometric indexes, particularly BMI, WC, and weight were positively associated with CRP levels, in men and women. Body shape phenotypes also showed distinct associations with CRP. Specifically, PC2 showed inverse associations with CRP in EPIC and UK Biobank in both sexes, similarly to height. PC3 was inversely associated with CRP among women, whereas positive associations were observed among men. Conclusions: Specific indexes of body size and body fat distribution showed differential associations with inflammation in adults. Notably, our results suggest that in women, height may mitigate the impact of a higher WC and HC on inflammation. This suggests that subtypes of adiposity exhibit substantial variation in their inflammatory potential, which may have implications for inflammation-related chronic diseases

Metabolically-Defined Body Size Phenotypes and Risk of Endometrial Cancer in the European Prospective Investigation into Cancer and Nutrition (EPIC)

Background: Obesity is a risk factor for endometrial cancer but whether metabolic dysfunction is associated with endometrial cancer independent of body size is not known. Methods: The association of metabolically defined body size phenotypes with endometrial cancer risk was investigated in a nested case-control study (817 cases/ 817 controls) within the European Prospective Investigation into Cancer and Nutrition (EPIC). Concentrations of C-peptide were used to define metabolically healthy (MH; _1st tertile) status among the control participants. These metabolic health definitions were combined with normal weight (NW); body mass index (BMI)_25 kg/m2 or WC >_80 cm or WHR >_0. 8) status, generating four phenotype groups for each anthropometric measure: (i) MH/NW, (ii) MH/OW, (iii) MU/ NW, and (iv) MU/OW. Results: In a multivariable-adjusted conditional logistic regression model, compared with MH/NW individuals, endometrial cancer risk was higher among those classified as MU/NW [ORWC, 1.48; 95% confidence interval (CI), 1.05-2.10 and ORWHR, 1.68; 95% CI, 1.21- 2.35] and MU/OW (ORBMI, 2.38; 95% CI, 1.73-3.27; ORWC, 2.69; 95% CI, 1.92-3.77 and ORWHR, 1.83; 95% CI, 1.32-2.54). MH/OW individuals were also at increased endometrial cancer risk compared with MH/NW individuals (ORWC, 1.94; 95% CI, 1.24-3.04). Conclusions: Women with metabolic dysfunction appear to have higher risk of endometrial cancer regardless of their body size. However, OW status raises endometrial cancer risk even among women with lower insulin levels, suggesting that obesity related pathways are relevant for the development of this cancer beyond insulin. Impact: Classifying women by metabolic health may be of greater utility in identifying those at higher risk for endometrial cancer than anthropometry per se

Circulating hormones and risk of gastric cancer by subsite in three cohort studies

Background Obesity has been positively associated with gastric cancer. Excess fat impacts hormones, which have been implicated in carcinogenesis. We investigated obesity-related hormones and cardia gastric cancer (CGC) and non-cardia gastric cancer (NCGC) risk. Methods Nested case–control studies were conducted within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort (61 CGCs, and 172 NCGCs and matched controls) and the Alpha-Tocopherol, Beta-Carotene Cancer Prevention (ATBC) study (100 CGCs and 65 NCGCs and matched controls); serum hormones were measured. In UK-Biobank (n = 458,713), we included 137 CGCs and 92 NCGCs. Sex-specific analyses were conducted. For EPIC and ATBC, odds ratios (ORs), and for UK-Biobank hazard ratios (HRs), were estimated using conditional logistic regression and Cox regression, respectively. Results Insulin-like growth-factor-1 was positively associated with CGC and NCGC in EPIC men (ORper 1-SD increase 1.94, 95% CI 1.03–3.63; ORper 1-SD increase 1.63, 95% CI 1.05–2.53, respectively), with similar findings for CGC in UK-Biobank women (HRper 1-SD increase 1.76, 95% CI 1.08–2.88). Leptin in EPIC men and C-peptide in EPIC women were positively associated with NCGC (ORT3 vs. T1 2.72, 95% CI 1.01–7.34 and ORper 1-SD increase 2.17, 95% CI 1.19–3.97, respectively). Sex hormone-binding globulin was positively associated with CGC in UK-Biobank men (HRper 1-SD increase 1.29, 95% CI 1.02–1.64). Conversely, ghrelin was inversely associated with NCGC among EPIC and ATBC men (ORper 1-SD increase 0.53, 95% CI 0.34–0.84; ORper 1-SD increase 0.22, 95% CI 0.10–0.50, respectively). In addition, dehydroepiandrosterone was inversely associated with CGC in EPIC and ATBC men combined. Conclusions Some obesity-related hormones influence CGC and NCGC risk

Prediagnostic selenium status, selenoprotein gene variants and association with breast cancer risk in a European cohort study

Selenium (Se) may help prevent breast cancer (BC) development. Owing to limited observational evidence, we investigated whether prediagnostic Se status and/or variants in the selenoprotein genes are associated with BC risk in a large European cohort. Se status was assessed by plasma measures of Se and its major circulating proteins, selenoprotein P (SELENOP) and glutathione peroxidase 3 (GPX3), in matched BC case-control pairs (2208 for SELENOP; 1785 for GPX3 and Se) nested within the European Prospective Investigation into Cancer and Nutrition (EPIC). Single nucleotide polymorphisms (SNPs, n = 452) in 55 selenoprotein and Se metabolic pathway genes and an additional 18 variants previously associated with Se concentrations were extracted from existing genotyping data within EPIC for 1564 case-control pairs. Multivariable-adjusted logistic regression models were used to calculate the odds ratios (ORs) and 95 % confidence intervals (CIs) of the association between Se status markers, SNP variants and BC risk. Overall, there was no statistically significant association of Se status with BC risk. However, higher GPX3 activity was associated with lower risk of premenopausal BC (4th versus 1st quartile, OR = 0.54, 95 % CI: 0.30–0.98, Ptrend = 0.013). While none of the genetic variant associations (P ≤ 0.05) retained significance after multiple testing correction, rs1004243 in the SELENOM selenoprotein gene and two SNPs in the related antioxidant TXN2 gene (rs4821494 and rs5750261) were associated with respective lower and higher risks of BC at a significance threshold of P ≤ 0.01. Fourteen SNPs in twelve Se pathway genes (P ≤ 0.01) in interaction with Se status were also associated with BC risk. Higher Se status does not appear to be associated with BC risk, although activity of the selenoenzyme GPX3 may be inversely associated with premenopausal BC risk, and SNPs in the Se pathway alone or in combination with suboptimal Se status may influence BC risk