Search

Background: Current epidemiologic evidence indicates that smoking is associated with a lower endometrial cancer risk. However, it is unknown if this association is causal or confounded. To further elucidate the role of smoking in endometrial cancer risk, we conducted complementary observational and Mendelian randomization (MR) analyses. Methods: The observational analyses included 286,415 participants enrolled in the European Prospective Investigation into Cancer and Nutrition and 179,271 participants in the UK Biobank, and multivariable Cox proportional hazards models were used. In twosampleMR analyses, genetic variants robustly associated with lifetime amount of smoking (n ¼ 126 variants) and ever having smoked regularly (n ¼ 112 variants) were selected and their association with endometrial cancer risk (12,906 cancer/108,979 controls from the Endometrial Cancer Association Consortium) was examined. Results: In the observational analysis, lifetime amount of smoking and ever having smoked regularly were associated with a lower endometrial cancer risk. In the MR analysis accounting for body mass index, a genetic predisposition to a higher lifetime amount of smoking was not associated with endometrial cancer risk (OR per 1-SD increment: 1.15; 95% confidence interval: 0.91–1.44). Genetic predisposition to ever having smoked regularly was not associated with risk of endometrial cancer. Conclusions: Smoking was inversely associated with endometrial cancer in the observational analyses, although unsupported by the MR. Additional studies are required to better understand the possible confounders and mechanisms underlying the observed associations between smoking and endometrial cancer. Impact: The results from this analysis indicate that smoking is unlikely to be causally linked with endometrial cancer risk., World Health Organization, Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, NIHR Imperial Biomedical Research Centre (BRC), Danish Cancer Society, Ligue Contre le Cancer (France) Institut Gustave Roussy (France) MutuelleGenerale de l'Education Nationale (France), Institut National de la Sante et de la Recherche Medicale (Inserm), Deutsche Krebshilfe German Cancer Research Center (DKFZ) (Germany) German Institute of Human Nutrition Potsdam-Rehbruecke (DIfE) (Germany) Federal Ministry of Education & Research (BMBF), Fondazione AIRC per la ricerca sul cancro Compagnia di San Paolo Consiglio Nazionale delle Ricerche (CNR), Netherlands Government Netherlands Government, World Cancer Research Fund International (WCRF), Netherlands Government, Health Research Fund (FIS) - Instituto de Salud Carlos III (ISCIII) (Spain), Junta de Andalucia, Principality of Asturias Regional Government of Basque Country (Spain) Regional Government of Murcia (Spain) Regional Government of Navarra (Spain) Catalan Institute of Oncology - ICO (Spain), Swedish Cancer Society Swedish Research Council County Council of Skane (Sweden) County Council of Vasterbotten (Sweden), Cancer Research UK 14136 C8221/A29017, UK Research & Innovation (UKRI), Medical Research Council UK (MRC) 1000143 MR/M012190/1 MR/N003284/1 MC-UU_12015/1 MC_UU_00006/ 1, Cancer Research UK C864/A14136 C18281/A29019

Pooling metabolomics data across studies is often desirable to increase the statistical power of the analysis. However, this can raise methodological challenges as several preanalytical and analytical factors could introduce differences in measured concentrations and variability between datasets. Specifically, different studies may use variable sample types (e.g., serum versus plasma) collected, treated, and stored according to different protocols, and assayed in different laboratories using different instruments. To address these issues, a new pipeline was developed to normalize and pool metabolomics data through a set of sequential steps: (i) exclusions of the least informative observations and metabolites and removal of outliers, imputation of missing data, (ii) identification of the main sources of variability through principal component partial R-square (PC-PR2) analysis, (iii) application of linear mixed models to remove unwanted variability, including samples’ originating study and batch, and preserve biological variations while accounting for potential differences in the residual variances across studies. This pipeline was applied to targeted metabolomics data acquired using Biocrates AbsoluteIDQ kits in eight case-control studies nested within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. Comprehensive examination of metabolomics measurements indicated that the pipeline improved the comparability of data across the studies. Our pipeline can be adapted to normalize other molecular data, including biomarkers as well as proteomics data, and could be used for pooling molecular datasets, for example in international consortia, to limit biases introduced by inter-study variability. This versatility of the pipeline makes our work of potential interest to molecular epidemiologists.

Hepatocellular carcinoma (HCC) development entails changes in liver metabolism. Current knowledge on metabolic perturbations in HCC is derived mostly from case-control designs, with sparse information from prospective cohorts. Our objective was to apply comprehensive metabolite profiling to detect metabolites whose serum concentrations are associated with HCC development, using biological samples from within the prospective European Prospective Investigation into Cancer and Nutrition (EPIC) cohort (>520 000 participants), where we identified 129 HCC cases matched 1:1 to controls. We conducted high-resolution untargeted liquid chromatography-mass spectrometry-based metabolomics on serum samples collected at recruitment prior to cancer diagnosis. Multivariable conditional logistic regression was applied controlling for dietary habits, alcohol consumption, smoking, body size, hepatitis infection and liver dysfunction. Corrections for multiple comparisons were applied. Of 9206 molecular features detected, 220 discriminated HCC cases from controls. Detailed feature annotation revealed 92 metabolites associated with HCC risk, of which 14 were unambiguously identified using pure reference standards. Positive HCC-risk associations were observed for N1-acetylspermidine, isatin, p-hydroxyphenyllactic acid, tyrosine, sphingosine, l,l-cyclo(leucylprolyl), glycochenodeoxycholic acid, glycocholic acid and 7-methylguanine. Inverse risk associations were observed for retinol, dehydroepiandrosterone sulfate, glycerophosphocholine, γ-carboxyethyl hydroxychroman and creatine. Discernible differences for these metabolites were observed between cases and controls up to 10 years prior to diagnosis. Our observations highlight the diversity of metabolic perturbations involved in HCC development and replicate previous observations (metabolism of bile acids, amino acids and phospholipids) made in Asian and Scandinavian populations. These findings emphasize the role of metabolic pathways associated with steroid metabolism and immunity and specific dietary and environmental exposures in HCC development.

Aims/hypothesis: The gut microbiome is hypothesised to be related to insulin resistance and other metabolic variables. However, data from population-based studies are limited. We investigated associations between serologic measures of metabolic health and the gut microbiome in the Northern Finland Birth Cohort 1966 (NFBC1966) and the TwinsUK cohort. Methods: Among 506 individuals from the NFBC1966 with available faecal microbiome (16S rRNA gene sequence) data, we estimated associations between gut microbiome diversity metrics and serologic levels of HOMA for insulin resistance (HOMA-IR), HbA1c and C-reactive protein (CRP) using multivariable linear regression models adjusted for sex, smoking status and BMI. Associations between gut microbiome diversity measures and HOMA-IR and CRP were replicated in 1140 adult participants from TwinsUK, with available faecal microbiome (16S rRNA gene sequence) data. For both cohorts, we used general linear models with a quasi-Poisson distribution and Microbiome Regression-based Kernel Association Test (MiRKAT) to estimate associations of metabolic variables with alpha- and beta diversity metrics, respectively, and generalised additive models for location scale and shape (GAMLSS) fitted with the zero-inflated beta distribution to identify taxa associated with the metabolic markers. Results: In NFBC1966, alpha diversity was lower in individuals with higher HOMA-IR with a mean of 74.4 (95% CI 70.7, 78.3) amplicon sequence variants (ASVs) for the first quartile of HOMA-IR and 66.6 (95% CI 62.9, 70.4) for the fourth quartile of HOMA-IR. Alpha diversity was also lower with higher HbA1c (number of ASVs and Shannon’s diversity, p

Hepatocellular carcinoma (HCC) development entails changes in liver metabolism. Current knowledge on metabolic perturbations in HCC is derived mostly from case-control designs, with sparse information from prospective cohorts. Our objective was to apply comprehensive metabolite profiling to detect metabolites whose serum concentrations are associated with HCC development, using biological samples from within the prospective European Prospective Investigation into Cancer and Nutrition (EPIC) cohort (>520 000 participants), where we identified 129 HCC cases matched 1:1 to controls. We conducted high-resolution untargeted liquid chromatography-mass spectrometry-based metabolomics on serum samples collected at recruitment prior to cancer diagnosis. Multivariable conditional logistic regression was applied controlling for dietary habits, alcohol consumption, smoking, body size, hepatitis infection and liver dysfunction. Corrections for multiple comparisons were applied. Of 9206 molecular features detected, 220 discriminated HCC cases from controls. Detailed feature annotation revealed 92 metabolites associated with HCC risk, of which 14 were unambiguously identified using pure reference standards. Positive HCC-risk associations were observed for N1-acetylspermidine, isatin, p-hydroxyphenyllactic acid, tyrosine, sphingosine, l,l-cyclo(leucylprolyl), glycochenodeoxycholic acid, glycocholic acid and 7-methylguanine. Inverse risk associations were observed for retinol, dehydroepiandrosterone sulfate, glycerophosphocholine, γ-carboxyethyl hydroxychroman and creatine. Discernible differences for these metabolites were observed between cases and controls up to 10 years prior to diagnosis. Our observations highlight the diversity of metabolic perturbations involved in HCC development and replicate previous observations (metabolism of bile acids, amino acids and phospholipids) made in Asian and Scandinavian populations. These findings emphasize the role of metabolic pathways associated with steroid metabolism and immunity and specific dietary and environmental exposures in HCC development. © 2020 UICC

Background Acylcarnitines (ACs) play a major role in fatty acid metabolism and are potential markers of metabolic dysfunction with higher blood concentrations reported in obese and diabetic individuals. Diet, and in particular red and processed meat intake, has been shown to influence AC concentrations but data on the effect of meat consumption on AC concentrations is limited. Objectives To investigate the effect of red and processed meat intake on AC concentrations in plasma and urine using a randomized controlled trial with replication in an observational cohort. Methods In the randomized crossover trial, 12 volunteers successively consumed 2 different diets containing either pork or tofu for 3 d each. A panel of 44 ACs including several oxidized ACs was analyzed by LC-MS in plasma and urine samples collected after the 3-d period. ACs that were associated with pork intake were then measured in urine (n = 474) and serum samples (n = 451) from the European Prospective Investigation into Cancer and nutrition (EPIC) study and tested for associations with habitual red and processed meat intake derived from dietary questionnaires. Results In urine samples from the intervention study, pork intake was positively associated with concentrations of 18 short- and medium-chain ACs. Eleven of these were also positively associated with habitual red and processed meat intake in the EPIC cross-sectional study. In blood, C18:0 was positively associated with red meat intake in both the intervention study (q = 0.004, Student's t-test) and the cross-sectional study (q = 0.033, linear regression). Conclusions AC concentrations in urine and blood were associated with red meat intake in both a highly controlled intervention study and in subjects of a cross-sectional study. Our data on the role of meat intake on this important pathway of fatty acid and energy metabolism may help understanding the role of red meat consumption in the etiology of some chronic diseases. This trial was registered at Clinicaltrials.gov as NCT03354130.

Pancreatic cancer (PC) is a highly fatal cancer with currently limited opportunities for early detection and effective treatment. Modifiable factors may offer pathways for primary prevention. In this study, the association between the Healthy Lifestyle Index (HLI) and PC risk was examined. Within the European Prospective Investigation into Cancer and Nutrition cohort, 1113 incident PC (57% women) were diagnosed from 400,577 participants followed-up for 15 years (median). HLI scores combined smoking, alcohol intake, dietary exposure, physical activity and, in turn, overall and central adiposity using BMI (HLIBMI) and waist-to-hip ratio (WHR, HLIWHR), respectively. High values of HLI indicate adherence to healthy behaviors. Cox proportional hazard models with age as primary time variable were used to estimate PC hazard ratios (HR) and 95% confidence intervals (CI). Sensitivity analyses were performed by excluding, in turn, each factor from the HLI score. Population attributable fractions (PAF) were estimated assuming participants’ shift to healthier lifestyles. The HRs for a one-standard deviation increment of HLIBMI and HLIWHR were 0.84 (95% CI: 0.79, 0.89; ptrend = 4.3e−09) and 0.77 (0.72, 0.82; ptrend = 1.7e−15), respectively. Exclusions of smoking from HLIWHR resulted in HRs of 0.88 (0.82, 0.94; ptrend = 4.9e−04). The overall PAF estimate was 19% (95% CI: 11%, 26%), and 14% (6%, 21%) when smoking was removed from the score. Adherence to a healthy lifestyle was inversely associated with PC risk, beyond the beneficial role of smoking avoidance. Public health measures targeting compliance with healthy lifestyles may have an impact on PC incidence. © 2019, Springer Nature B.V.

Background Bilirubin, a byproduct of hemoglobin breakdown and purported anti-oxidant, is thought to be cancer preventive. We conducted complementary serological and Mendelian randomization (MR) analyses to investigate whether alterations in circulating levels of bilirubin are associated with risk of colorectal cancer (CRC). We decided a priori to perform analyses separately in men and women based on suggestive evidence that associations may differ by sex. Methods In a case-control study nested in the European Prospective Investigation into Cancer and Nutrition (EPIC), pre-diagnostic unconjugated bilirubin (UCB, the main component of total bilirubin) concentrations were measured by high-performance liquid chromatography in plasma samples of 1386 CRC cases and their individually matched controls. Additionally, 115 single-nucleotide polymorphisms (SNPs) robustly associated (P < 5 x 10(-8)) with circulating total bilirubin were instrumented in a 2-sample MR to test for a potential causal effect of bilirubin on CRC risk in 52,775 CRC cases and 45,940 matched controls in the Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO), the Colon Cancer Family Registry (CCFR), and the Colorectal Transdisciplinary (CORECT) study. Results The associations between circulating UCB levels and CRC risk differed by sex (P-heterogeneity = 0.008). Among men, higher levels of UCB were positively associated with CRC risk (odds ratio [OR] = 1.19, 95% confidence interval [CI] = 1.04-1.36; per 1-SD increment of log-UCB). In women, an inverse association was observed (OR = 0.86 (0.76-0.97)). In the MR analysis of the mainUGT1A1SNP (rs6431625), genetically predicted higher levels of total bilirubin were associated with a 7% increase in CRC risk in men (OR = 1.07 (1.02-1.12);P = 0.006; per 1-SD increment of total bilirubin), while there was no association in women (OR = 1.01 (0.96-1.06);P = 0.73). Raised bilirubin levels, predicted by instrumental variables excluding rs6431625, were suggestive of an inverse association with CRC in men, but not in women. These differences by sex did not reach formal statistical significance (P-heterogeneity >= 0.2). Conclusions Additional insight into the relationship between circulating bilirubin and CRC is needed in order to conclude on a potential causal role of bilirubin in CRC development.

Emerging evidence suggests that a metabolic profile associated with obesity may be a more relevant risk factor for some cancers than adiposity per se. Basal metabolic rate (BMR) is an indicator of overall body metabolism and may be a proxy for the impact of a specific metabolic profile on cancer risk. Therefore, we investigated the association of predicted BMR with incidence of 13 obesity-related cancers in the European Prospective Investigation into Cancer and Nutrition (EPIC). BMR at baseline was calculated using the WHO/FAO/UNU equations and the relationships between BMR and cancer risk were investigated using multivariable Cox proportional hazards regression models. A total of 141,295 men and 317,613 women, with a mean follow-up of 14 years were included in the analysis. Overall, higher BMR was associated with a greater risk for most cancers that have been linked with obesity. However, among normal weight participants, higher BMR was associated with elevated risks of esophageal adenocarcinoma (hazard ratio per 1-standard deviation change in BMR [HR1-SD]: 2.46; 95% CI 1.20; 5.03) and distal colon cancer (HR1-SD: 1.33; 95% CI 1.001; 1.77) among men and with proximal colon (HR1-SD: 1.16; 95% CI 1.01; 1.35), pancreatic (HR1-SD: 1.37; 95% CI 1.13; 1.66), thyroid (HR1-SD: 1.65; 95% CI 1.33; 2.05), postmenopausal breast (HR1-SD: 1.17; 95% CI 1.11; 1.22) and endometrial (HR1-SD: 1.20; 95% CI 1.03; 1.40) cancers in women. These results indicate that higher BMR may be an indicator of a metabolic phenotype associated with risk of certain cancer types, and may be a useful predictor of cancer risk independent of body fatness. © 2019 International Agency for Research on Cancer (IARC/WHO); licensed by UICC

Purpose: Advanced glycation end products (AGEs) can be formed in foods by the reaction of reducing sugars with proteins, and have been shown to induce insulin resistance and obesity in experimental studies. We examined the association between dietary AGEs intake and changes in body weight in adults over an average of 5 years of follow-up. Methods: A total of 255,170 participants aged 25–70 years were recruited in ten European countries (1992–2000) in the PANACEA study (Physical Activity, Nutrition, Alcohol, Cessation of smoking, Eating out of home in relation to Anthropometry), a sub-cohort of the EPIC (European Prospective Investigation into Cancer and Nutrition). Body weight was measured at recruitment and self-reported between 2 and 11 years later depending on the study center. A reference database for AGEs was used containing UPLC–MS/MS-measured Nε-(carboxymethyl)-lysine (CML), Nε-(1-carboxyethyl)-lysine (CEL), and Nδ-(5-hydro-5-methyl-4-imidazolon-2-yl)-ornithine (MG-H1) in 200 common European foods. This reference database was matched to foods and decomposed recipes obtained from country-specific validated dietary questionnaires in EPIC and intake levels of CEL, CML, and MG-H1 were estimated. Associations between dietary AGEs intake and body weight change were estimated separately for each of the three AGEs using multilevel mixed linear regression models with center as random effect and dietary AGEs intake and relevant confounders as fixed effects. Results: A one-SD increment in CEL intake was associated with 0.111 kg (95% CI 0.087–0.135) additional weight gain over 5 years. The corresponding additional weight gain for CML and MG-H1 was 0.065 kg (0.041–0.089) and 0.034 kg (0.012, 0.057), respectively. The top six food groups contributing to AGEs intake, with varying proportions across the AGEs, were cereals/cereal products, meat/processed meat, cakes/biscuits, dairy, sugar and confectionary, and fish/shellfish. Conclusion: In this study of European adults, higher intakes of AGEs were associated with marginally greater weight gain over an average of 5 years of follow-up. © 2019, Springer-Verlag GmbH Germany, part of Springer Nature.

Background: Although lifestyle factors have been studied in relation to individual non-communicable diseases (NCDs), their association with development of a subsequent NCD, defined as multimorbidity, has been scarcely investigated. The aim of this study was to investigate associations between five lifestyle factors and incident multimorbidity of cancer and cardiometabolic diseases. Methods: In this prospective cohort study, 291,778 participants (64% women) from seven European countries, mostly aged 43 to 58 years and free of cancer, cardiovascular disease (CVD), and type 2 diabetes (T2D) at recruitment, were included. Incident multimorbidity of cancer and cardiometabolic diseases was defined as developing subsequently two diseases including first cancer at any site, CVD, and T2D in an individual. Multi-state modelling based on Cox regression was used to compute hazard ratios (HR) and 95% confidence intervals (95% CI) of developing cancer, CVD, or T2D, and subsequent transitions to multimorbidity, in relation to body mass index (BMI), smoking status, alcohol intake, physical activity, adherence to the Mediterranean diet, and their combination as a healthy lifestyle index (HLI) score. Cumulative incidence functions (CIFs) were estimated to compute 10-year absolute risks for transitions from healthy to cancer at any site, CVD (both fatal and non-fatal), or T2D, and to subsequent multimorbidity after each of the three NCDs. Results: During a median follow-up of 11 years, 1910 men and 1334 women developed multimorbidity of cancer and cardiometabolic diseases. A higher HLI, reflecting healthy lifestyles, was strongly inversely associated with multimorbidity, with hazard ratios per 3-unit increment of 0.75 (95% CI, 0.71 to 0.81), 0.84 (0.79 to 0.90), and 0.82 (0.77 to 0.88) after cancer, CVD, and T2D, respectively. After T2D, the 10-year absolute risks of multimorbidity were 40% and 25% for men and women, respectively, with unhealthy lifestyle, and 30% and 18% for men and women with healthy lifestyles. Conclusion: Pre-diagnostic healthy lifestyle behaviours were strongly inversely associated with the risk of cancer and cardiometabolic diseases, and with the prognosis of these diseases by reducing risk of multimorbidity. © 2020 The Author(s).

Background: Bilirubin, a byproduct of hemoglobin breakdown and purported anti-oxidant, is thought to be cancer preventive. We conducted complementary serological and Mendelian randomization (MR) analyses to investigate whether alterations in circulating levels of bilirubin are associated with risk of colorectal cancer (CRC). We decided a priori to perform analyses separately in men and women based on suggestive evidence that associations may differ by sex. Methods: In a case-control study nested in the European Prospective Investigation into Cancer and Nutrition (EPIC), pre-diagnostic unconjugated bilirubin (UCB, the main component of total bilirubin) concentrations were measured by high-performance liquid chromatography in plasma samples of 1386 CRC cases and their individually matched controls. Additionally, 115 single-nucleotide polymorphisms (SNPs) robustly associated (P < 5 × 10-8) with circulating total bilirubin were instrumented in a 2-sample MR to test for a potential causal effect of bilirubin on CRC risk in 52,775 CRC cases and 45,940 matched controls in the Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO), the Colon Cancer Family Registry (CCFR), and the Colorectal Transdisciplinary (CORECT) study. Results: The associations between circulating UCB levels and CRC risk differed by sex (P heterogeneity = 0.008). Among men, higher levels of UCB were positively associated with CRC risk (odds ratio [OR] = 1.19, 95% confidence interval [CI] = 1.04-1.36; per 1-SD increment of log-UCB). In women, an inverse association was observed (OR = 0.86 (0.76-0.97)). In the MR analysis of the main UGT1A1 SNP (rs6431625), genetically predicted higher levels of total bilirubin were associated with a 7% increase in CRC risk in men (OR = 1.07 (1.02-1.12); P = 0.006; per 1-SD increment of total bilirubin), while there was no association in women (OR = 1.01 (0.96-1.06); P = 0.73). Raised bilirubin levels, predicted by instrumental variables excluding rs6431625, were suggestive of an inverse association with CRC in men, but not in women. These differences by sex did not reach formal statistical significance (P heterogeneity ≥ 0.2). Conclusions: Additional insight into the relationship between circulating bilirubin and CRC is needed in order to conclude on a potential causal role of bilirubin in CRC development. © 2020 The Author(s).

National audience

Importance: Soft drinks are frequently consumed, but whether this consumption is associated with mortality risk is unknown and has been understudied in European populations to date. Objective: To examine the association between total, sugar-sweetened, and artificially sweetened soft drink consumption and subsequent total and cause-specific mortality. Design, Setting, and Participants: This population-based cohort study involved participants (n = 451743 of the full cohort) in the European Prospective Investigation into Cancer and Nutrition (EPIC), an ongoing, large multinational cohort of people from 10 European countries (Denmark, France, Germany, Greece, Italy, the Netherlands, Norway, Spain, Sweden, and the United Kingdom), with participants recruited between January 1, 1992, and December 31, 2000. Excluded participants were those who reported cancer, heart disease, stroke, or diabetes at baseline; those with implausible dietary intake data; and those with missing soft drink consumption or follow-up information. Data analyses were performed from February 1, 2018, to October 1, 2018. Exposure: Consumption of total, sugar-sweetened, and artificially sweetened soft drinks. Main Outcomes and Measures: Total mortality and cause-specific mortality. Hazard ratios (HRs) and 95% CIs were estimated using multivariable Cox proportional hazards regression models adjusted for other mortality risk factors. Results: In total, 521 330 individuals were enrolled. Of this total, 451743 (86.7%) were included in the study, with a mean (SD) age of 50.8 (9.8) years and with 321081 women (71.1%). During a mean (range) follow-up of 16.4 (11.1 in Greece to 19.2 in France) years, 41693 deaths occurred. Higher all-cause mortality was found among participants who consumed 2 or more glasses per day (vs consumers of

Background: Metabolomics is a promising molecular tool to identify novel etiologic pathways leading to cancer. Using a targeted approach, we prospectively investigated the associations between metabolite concentrations in plasma and breast cancer risk. Methods: A nested case-control study was established within the European Prospective Investigation into Cancer cohort, which included 1624 first primary incident invasive breast cancer cases (with known estrogen and progesterone receptor and HER2 status) and 1624 matched controls. Metabolites (n = 127, acylcarnitines, amino acids, biogenic amines, glycerophospholipids, hexose, sphingolipids) were measured by mass spectrometry in pre-diagnostic plasma samples and tested for associations with breast cancer incidence using multivariable conditional logistic regression. Results: Among women not using hormones at baseline (n = 2248), and after control for multiple tests, concentrations of arginine (odds ratio [OR] per SD = 0.79, 95% confidence interval [CI] = 0.70-0.90), asparagine (OR = 0.83 (0.74-0.92)), and phosphatidylcholines (PCs) ae C36:3 (OR = 0.83 (0.76-0.90)), aa C36:3 (OR = 0.84 (0.77-0.93)), ae C34:2 (OR = 0.85 (0.78-0.94)), ae C36:2 (OR = 0.85 (0.78-0.88)), and ae C38:2 (OR = 0.84 (0.76-0.93)) were inversely associated with breast cancer risk, while the acylcarnitine C2 (OR = 1.23 (1.11-1.35)) was positively associated with disease risk. In the overall population, C2 (OR = 1.15 (1.06-1.24)) and PC ae C36:3 (OR = 0.88 (0.82-0.95)) were associated with risk of breast cancer, and these relationships did not differ by breast cancer subtype, age at diagnosis, fasting status, menopausal status, or adiposity. Conclusions: These findings point to potentially novel pathways and biomarkers of breast cancer development. Results warrant replication in other epidemiological studies. © 2019 The Author(s).

Background: There is increasing evidence that folate, an important component of one-carbon metabolism, modulates the epigenome. Alcohol, which can disrupt folate absorption, is also known to affect the epigenome. We investigated the association of dietary folate and alcohol intake on leukocyte DNA methylation levels in the European Prospective Investigation into Cancer and Nutrition (EPIC) study. Leukocyte genome-wide DNA methylation profiles on approximately 450,000 CpG sites were acquired with Illumina HumanMethylation 450K BeadChip measured among 450 women control participants of a case-control study on breast cancer nested within the EPIC cohort. After data preprocessing using surrogate variable analysis to reduce systematic variation, associations of DNA methylation with dietary folate and alcohol intake, assessed with dietary questionnaires, were investigated using CpG site-specific linear models. Specific regions of the methylome were explored using differentially methylated region (DMR) analysis and fused lasso (FL) regressions. The DMR analysis combined results from the feature-specific analysis for a specific chromosome and using distances between features as weights whereas FL regression combined two penalties to encourage sparsity of single features and the difference between two consecutive features. Results: After correction for multiple testing, intake of dietary folate was not associated with methylation level at any DNA methylation site, while weak associations were observed between alcohol intake and methylation level at CpG sites cg03199996 and cg07382687, with q val = 0.029 and q val = 0.048, respectively. Interestingly, the DMR analysis revealed a total of 24 and 90 regions associated with dietary folate and alcohol, respectively. For alcohol intake, 6 of the 15 most significant DMRs were identified through FL. Conclusions: Alcohol intake was associated with methylation levels at two CpG sites. Evidence from DMR and FL analyses indicated that dietary folate and alcohol intake may be associated with genomic regions with tumor suppressor activity such as the GSDMD and HOXA5 genes. These results were in line with the hypothesis that epigenetic mechanisms play a role in the association between folate and alcohol, although further studies are warranted to clarify the importance of these mechanisms in cancer. © 2019 The Author(s).

Background: Processed meat intake is associated with a higher risk of colorectal and stomach cancers, coronary artery disease, and type 2 diabetes and with higher mortality, but the estimation of intake of different processed meat products in this heterogeneous food group in epidemiological studies remains challenging. Objective: This work aimed at identifying novel biomarkers for processed meat intake using metabolomics. Methods: An untargeted, multi-tiered metabolomics approach based on LC-MS was applied to 33 meat products digested in vitro and secondly to urine and plasma samples from a randomized crossover dietary intervention in which 12 volunteers consumed successively 3 processed meat products (bacon, salami, and hot dog) and 2 other foods used as controls, over 3 consecutive days. The putative biomarkers were then measured in urine from 474 subjects from the European Prospective Investigation into Cancer and Nutrition (EPIC) cross-sectional study for which detailed 24-h dietary recalls and FFQs were available. Results: Syringol and 4 derivatives of syringol were found to be characteristic of in vitro digests of smoked meat products. The same compounds present as sulfate esters in urine increased at 2 and 12 h after consumption of smoked meat products (hot dog, bacon) in the intervention study. The same syringol sulfates were also positively associated with recent or habitual consumption of smoked meat products in urine samples from participants of the EPIC cross-sectional study. These compounds showed good discriminative ability for smoked meat intake with receiver operator characteristic areas under the curve ranging from 0.78 to 0.86 and 0.74 to 0.79 for short-term and habitual intake, respectively. Conclusions: Four novel syringol sulfates were identified as potential biomarkers of smoked meat intake and may be used to improve assessment of smoked meat intake in epidemiological studies. This trial was registered at clinicaltrials.gov as NCT03354130. © American Society for Nutrition 2019.

Background: Few published breast cancer (BC) risk prediction models consider the heterogeneity of predictor variables between estrogen-receptor positive (ER+) and negative (ER-) tumors. Using data from two large cohorts, we examined whether modeling this heterogeneity could improve prediction. 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. © 2018 The Author(s).