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Background and aims: Emerging evidence suggests a role of amino acids (AAs) in the development of various diseases including renal failure, liver cirrhosis, diabetes and cancer. However, mechanistic pathways and the effects of dietary AA intakes on circulating levels and disease outcomes are unclear. We aimed to compare protein and AA intakes, with their respective blood concentrations in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. Methods: Dietary protein and AA intakes were assessed via the EPIC dietary questionnaires (DQ) and 24-h dietary recalls (24-HDR). A subsample of 3768 EPIC participants who were free of cancer had blood AA concentrations measured. To investigate how circulating levels relate to their respective intakes, dietary AA intake was examined in quintiles and ANOVA tests were run. Pearson correlations were examined for continous associations between intakes and blood concentrations. Results: Dietary AA intakes (assessed with the DQ) and blood AA concentrations were not strongly correlated (−0.15 ≤ r ≤ 0.17) and the direction of the correlations depended on AA class: weak positive correlations were found for most essential AAs (isoleucine, leucine, lysine, methionine, threonine, tryptophan, and valine) and conditionally essential AAs (arginine and tyrosine), while negative associations were found for non-essential AAs. Similar results were found when using the 24-HDR. When conducting ANOVA tests for essential AAs, higher intake quintiles were linked to higher blood AA concentrations, except for histidine and phenylalanine. For non-essential AAs and glycine, an inverse relationship was observed. Conditionally-essential AAs showed mixed results. Conclusions: Weak positive correlations and dose responses were found between most essential and conditionally essential AA intakes, and blood concentrations, but not for the non-essential AAs. These results suggest that intake of dietary AA might be related to physiological AA status, particularly for the essential AAs. However, these results should be further evaluated and confirmed in large-scale prospective studies.

Endometrial cancer risk prediction models including lifestyle, anthropometric and reproductive factors have limited discrimina-tion. Adding biomarker data to these models may improve predictive capacity; to our knowledge, this has not been investigat-ed for endometrial cancer. Using a nested case-control study within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort, we investigated the improvement in discrimination gained by adding serum biomarker concentrations to risk estimates derived from an existing risk prediction model based on epidemiologic factors. Serum concentrations of sex steroid hormones, metabolic markers, growth factors, adipokines and cytokines were evaluated in a step-wise backward selec-tion process; biomarkers were retained at p < 0.157 indicating improvement in the Akaike information criterion (AIC). Improvement in discrimination was assessed using the C-statistic for all biomarkers alone, and change in C-statistic from addition of biomarkers to preexisting absolute risk estimates. We used internal validation with bootstrapping (1000-fold) to adjust for over-fitting. Adiponectin, estrone, interleukin-1 receptor antagonist, tumor necrosis factor-alpha and triglycerides were select-ed into the model. After accounting for over-fitting, discrimination was improved by 2.0 percentage points when all evaluated biomarkers were included and 1.7 percentage points in the model including the selected biomarkers. Models including eti-ologic markers on independent pathways and genetic markers may further improve discrimination.

Background: Renal cell carcinoma (RCC) accounts for more than 80% of kidney cancers in adults, and obesity is a known risk factor. Regular consumption of sweetened beverages has been linked to obesity and several chronic diseases, including some types of cancer. It is uncertain whether soft drink and juice consumption is associated with risk of RCC. We investigated the associations of soft drink and juice consumption with RCC incidence and mortality in the European Prospective Investigation into Cancer and Nutrition (EPIC). Methods: A total of 389,220 EPIC participants with median age of 52 years at recruitment (1991–2000) were included. Cox regression yielded adjusted HRs and 95% confidence intervals (CI) for RCC incidence and mortality in relation to intakes of juices and total, sugar-sweetened, and artificially sweetened soft drinks. Results: A total of 888 incident RCCs and 356 RCC deaths were identified. In models including adjustment for body mass index and energy intake, there was no higher risk of incident RCC associated with consumption of juices (HR per 100 g/day increment = 1.03; 95% CI, 0.97–1.09), total soft drinks (HR = 1.01; 95% CI, 0.98–1.05), sugar-sweetened soft drinks (HR = 0.99; 95% CI, 0.94–1.05), or artificially sweetened soft drinks (HR = 1.02; 95% CI, 0.96–1.08). In these fully adjusted models, none of the beverages was associated with RCC mortality (HR, 95% CI per 100 g/day increment 1.06, 0.97–1.16; 1.03, 0.98–1.09; 0.97, 0.89–1.07; and 1.06, 0.99–1.14, respectively). Conclusions: Consumption of juices or soft drinks was not associated with RCC incidence or mortality after adjusting for obesity. Impact: Soft drink and juice intakes are unlikely to play an independent role in RCC development or mortality.

Existing evidence is inconclusive on whether socioeconomic status (SES) and educational inequalities influence colorectal cancer (CRC) risk, and whether low or high SES/educational level is associated with developing CRC. The aim of our study was to investigate the relationship between educational level and CRC. We studied data from 400,510 participants in the EPIC (European Prospective Investigation into Cancer and Nutrition) study, of whom 2,447 developed CRC (colon: 1,551, rectum: 896, mean follow-up 8.3 years). Cox proportional hazard regression analysis stratified by age, gender and center, and adjusted for potential confounders were used to estimate hazard ratios (HR) and 95% confidence intervals (95% CI). Relative indices of inequality (RII) for education were estimated using Cox regression models. We conducted separate analyses for tumor location, gender and geographical region. Compared with participants with college/university education, participants with vocational secondary education or less had a nonsignificantly lower risk of developing CRC. When further stratified for tumor location, adjusted risk estimates for the proximal colon were statistically significant for primary education or less (HR 0.73, 95% CI 0.57-0.94) and for vocational secondary education (HR 0.76, 95% CI 0.58-0.98). The inverse association between low education and CRC risk was particularly found in women and Southern Europe. These associations were statistically significant for CRC, for colon cancer and for proximal colon cancer. In conclusion, CRC risk, especially in the proximal colon, is lower in subjects with a lower educational level compared to those with a higher educational level. This association is most pronounced in women and Southern Europe

Menstrual and reproductive factors and exogenous hormone use have been investigated as pancreatic cancer risk factors in case-control and cohort studies, but results have been inconsistent. We conducted a prospective examination of menstrual and reproductive factors, exogenous hormone use and pancreatic cancer risk (based on 304 cases) in 328,610 women from the EPIC cohort. Then, in a case-control study nested within the EPIC cohort, we examined 12 single nucleotide polymorphisms (SNPs) in CYP17A1 (an essential gene in sex steroid metabolism) for association with pancreatic cancer in women and men (324 cases and 353 controls). Of all factors analyzed, only younger age at menarche (