An updated validation of the Dietary Quality Score: associations with risk factors for cardiometabolic diseases in a Danish population.

PURPOSE: This study assessed the validity of the Dietary Quality Score (DQS) and investigated the association between the DQS and risk factors for cardiometabolic diseases. METHODS: The DQS was calculated based on an updated 23-item FFQ and validated against a 376-item FFQ. A sub-sample of 450 men and women aged 18-73 years, from the Danish Diet, Cancer and Health-Next generations (DCH-NG) cohort, completed the updated 23-item FFQ. We investigated the associations between the DQS and risk factors for cardiometabolic diseases (lipids, haemoglobin A1c (HbA1c), high-sensitive C-reactive protein (hs-CRP), blood pressure (BP), waist circumference (WC), visceral and total fat mass) using linear regression models. RESULTS: A high DQS, i.e. healthy dietary habits, was significantly associated with a higher intake of fruits, vegetables, fish, fibre, several vitamins and minerals and a lower intake of saturated fat. Moreover, a high DQS was significantly associated with lower levels of LDL cholesterol (P = 0.0133), Hs-CRP (P = 0.0449), WC (P = 0.0161), visceral fat (P = 0.0003), total fat mass (P = 0.0106) and total fat percentage (P = 0.0030) and significantly associated with a higher HDL cholesterol (P = 0.0379) level, when adjusting for education, smoking habits and physical activity. There was no association with total cholesterol, triglycerides, HbA1c, BP and BMI. CONCLUSION: The DQS, based on the updated 23-item FFQ, is a valid tool to classify individuals into groups with low, average and high dietary quality in the Danish population. Furthermore, a high DQS is significantly associated with lower levels of several risk factors for cardiometabolic diseases.

Descriptive analysis of dietary (poly)phenol intake in the subcohort MAX from DCH-NG: "Diet, Cancer and Health-Next Generations cohort".

PURPOSE: (Poly)phenols are bioactive compounds widely distributed in plant-based foods. Currently, limited data exist on the intake distribution of (poly)phenols across meals. This study aimed to estimate dietary intakes of all individual (poly)phenols and total intake per class and subclass by meal event, and to identify their main food sources in the subcohort MAX from the Diet, Cancer and Health-Next Generations cohort (DCH-NG). METHODS: Dietary data were collected using three web-based 24-h dietary recalls over 1 year. In total, 676 participants completed at least one recall. The dietary data were linked to Phenol-Explorer database using standardized procedures and an in-house software. We categorized foods/drinks into five options of meal events selected by the participant: 'Breakfast', 'Lunch', 'Evening', 'Snack', and 'Drink'. RESULTS: Adjusted total (poly)phenols mean intake by meal was the highest in the drink event (563 mg/day in men and 423 mg/day in women) and the lowest in the evening event (146 mg/day in men and 137 mg/day in women). The main overall (poly)phenol class contributor was phenolic acids (55.7-79.0%), except for evening and snack events where it was flavonoids (45.5-60%). The most consumed (poly)phenol subclasses were hydroxycinnamic acids and proanthocyanidins. Nonalcoholic beverages (coffee accounted for 66.4%), cocoa products, and cereals were the main food sources of total (poly)phenols. CONCLUSION: This study provides data on the variability in the intake of classes and subclasses of (poly)phenols and their main food sources by meal event according to lifestyle data, age, and gender in a Danish population.

Dietary polyphenols, metabolic syndrome and cardiometabolic risk factors: An observational study based on the DCH-NG subcohort.

BACKGROUND AND AIMS: Polyphenol-rich foods have beneficial properties that may lower cardiometabolic risk. We aimed to prospectively investigate the relationship between intakes of dietary polyphenols, and metabolic syndrome (MetS) and its components, in 676 Danish residents from the MAX study, a subcohort of the Danish Diet, Cancer and Health-Next Generations (DCH-NG) cohort. METHODS AND RESULTS: Dietary data were collected using web-based 24-h dietary recalls over one year (at baseline, and at 6 and 12 months). The Phenol-Explorer database was used to estimate dietary polyphenol intake. Clinical variables were also collected at the same time point. Generalized linear mixed models were used to investigate relationships between polyphenol intake and MetS. Participants had a mean age of 43.9y, a mean total polyphenol intake of 1368 mg/day, and 75 (11.6%) had MetS at baseline. Compared to individuals with MetS in Q1 and after adjusting for age, sex, lifestyle and dietary confounders, those in Q4 - for total polyphenols, flavonoids and phenolic acids-had a 50% [OR (95% CI): 0.50 (0.27, 0.91)], 51% [0.49 (0.26, 0.91)] and 45% [0.55 (0.30, 1.00)] lower odds of MetS, respectively. Higher total polyphenols, flavonoids and phenolic acids intakes as continuous variable were associated with lower risk for elevated systolic blood pressure (SBP) and low high-density lipoprotein cholesterol (HDL-c) (p < 0.05). CONCLUSIONS: Total polyphenol, flavonoid and phenolic acid intakes were associated with lower odds of MetS. These intakes were also consistently and significantly associated with a lower risk for higher SBP and lower HDL-c concentrations.

Prospective evaluation of 92 serum protein biomarkers for early detection of ovarian cancer.

BACKGROUND: CA125 is the best available yet insufficiently sensitive biomarker for early detection of ovarian cancer. There is a need to identify novel biomarkers, which individually or in combination with CA125 can achieve adequate sensitivity and specificity for the detection of earlier-stage ovarian cancer. METHODS: In the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort, we measured serum levels of 92 preselected proteins for 91 women who had blood sampled ≤18 months prior to ovarian cancer diagnosis, and 182 matched controls. We evaluated the discriminatory performance of the proteins as potential early diagnostic biomarkers of ovarian cancer. RESULTS: Nine of the 92 markers; CA125, HE4, FOLR1, KLK11, WISP1, MDK, CXCL13, MSLN and ADAM8 showed an area under the ROC curve (AUC) of ≥0.70 for discriminating between women diagnosed with ovarian cancer and women who remained cancer-free. All, except ADAM8, had shown at least equal discrimination in previous case-control comparisons. The discrimination of the biomarkers, however, was low for the lag-time of >9-18 months and paired combinations of CA125 with any of the 8 markers did not improve discrimination compared to CA125 alone. CONCLUSION: Using pre-diagnostic serum samples, this study identified markers with good discrimination for the lag-time of 0-9 months. However, the discrimination was low in blood samples collected more than 9 months prior to diagnosis, and none of the markers showed major improvement in discrimination when added to CA125.

Impact of cumulative body mass index and cardiometabolic diseases on survival among patients with colorectal and breast cancer: a multi-centre cohort study.

BACKGROUND: Body mass index (BMI) and cardiometabolic comorbidities such as cardiovascular disease and type 2 diabetes have been studied as negative prognostic factors in cancer survival, but possible dependencies in the mechanisms underlying these associations remain largely unexplored. We analysed these associations in colorectal and breast cancer patients. METHODS: Based on repeated BMI assessments of cancer-free participants from four European countries in the European Prospective Investigation into Cancer and nutrition (EPIC) study, individual BMI-trajectories reflecting predicted mean BMI between ages 20 to 50 years were estimated using a growth curve model. Participants with incident colorectal or breast cancer after the age of 50 years were included in the survival analysis to study the prognostic effect of mean BMI and cardiometabolic diseases (CMD) prior to cancer. CMD were defined as one or more chronic conditions among stroke, myocardial infarction, and type 2 diabetes. Hazard ratios (HRs) and confidence intervals (CIs) of mean BMI and CMD were derived using multivariable-adjusted Cox proportional hazard regression for mean BMI and CMD separately and both exposures combined, in subgroups of localised and advanced disease. RESULTS: In the total cohort of 159,045 participants, there were 1,045 and 1,620 eligible patients of colorectal and breast cancer. In colorectal cancer patients, a higher BMI (by 1 kg/m2) was associated with a 6% increase in risk of death (95% CI of HR: 1.02-1.10). The HR for CMD was 1.25 (95% CI: 0.97-1.61). The associations for both exposures were stronger in patients with localised colorectal cancer. In breast cancer patients, a higher BMI was associated with a 4% increase in risk of death (95% CI: 1.00-1.08). CMDs were associated with a 46% increase in risk of death (95% CI: 1.01-2.09). The estimates and CIs for BMI remained similar after adjustment for CMD and vice versa. CONCLUSIONS: Our results suggest that cumulative exposure to higher BMI during early to mid-adulthood was associated with poorer survival in patients with breast and colorectal cancer, independent of CMD prior to cancer diagnosis. The association between a CMD diagnosis prior to cancer and survival in patients with breast and colorectal cancer was independent of BMI.

Metabolic perturbations prior to hepatocellular carcinoma diagnosis: Findings from a prospective observational cohort study.

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.

Intake of whole grain and associations with lifestyle and demographics: a cross-sectional study based on the Danish Diet, Cancer and Health-Next Generations cohort.

PURPOSE: The aim was to analyze the intake of whole grain (WG) and associations with lifestyle and demographics in a newly established cohort of Danish adults. METHODS: Between 2015 and 2019, Danes were enrolled into The Diet, Cancer and Health-Next Generations cohort. A total of 38,553 persons were included in the current cross-sectional study, where all completed a 376-item food frequency questionnaire, a lifestyle questionnaire, and a physical examination in a study center where physical measurements and biological samples were collected. RESULTS: The median intake of WG was 79 g/10 mega joule (MJ) and 54% of the participants consumed the amount of WG recommended in Denmark, which is 75 g/10 MJ. The probability of consuming the recommended amount of WG was highest among men, persons < 30 years, students, persons with body mass index (BMI) < 25 kg/m2, persons participating in sports, who did not exceed the recommended maximum intake of alcohol and did not smoke. The probability of having a low intake of WG defined as < 25 g/10 MJ was highest among persons with short education, BMI ≥ 25 kg/m2, persons not participating in sports, persons having an alcohol intake above the recommended maximum level and persons being active smokers. CONCLUSION: The median intake of WG was 79 g/10 MJ. The probability of consuming at least 75 g WG/10 MJ was highest among persons who also adhered to healthy lifestyle measured by other factors. Only 6% of the cohort participants consumed < 25 g WG/10 MJ, these persons were more likely to have a general less healthy lifestyle.

Metabolic Mediators of the Association Between Adult Weight Gain and Colorectal Cancer: Data From the European Prospective Investigation into Cancer and Nutrition (EPIC) Cohort.

Evidence indicates that gaining weight in adult life is associated with an elevated risk of colorectal cancer; however, biological mechanisms that may explain this association remain unclear. We evaluated the mediation effect of 20 different biomarkers on the relationship between adult weight gain and colorectal cancer, using data from a prospective nested case-control study of 452 incident cases diagnosed between 1992 and 2003 and matched within risk sets to 452 controls within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. The proportions of mediated effects (%) were estimated on the basis of differences in percent effect changes in conditional logistic regression models with and without additional adjustment for individual biomarkers. Greater adult weight gain (≥300 g/year vs. <300 g/year) was associated with a higher risk of colon cancer (multivariable-adjusted relative risk = 1.54, 95% confidence interval: 1.07, 2.24) but not rectal cancer (relative risk = 1.07, 95% confidence interval: 0.68, 1.66). This association was accounted for mostly by attained waist circumference (reduction of 61%) and by the biomarkers soluble leptin receptor (reduction of 43%) and glycated hemoglobin (reduction of 28%). These novel data suggest that the observed association between adult weight gain and colon cancer could be primarily explained by attained abdominal fatness and biomarkers of metabolic dysfunction.

Energy and macronutrient intake and risk of differentiated thyroid carcinoma in the European Prospective Investigation into Cancer and Nutrition study.

Incidence rates of differentiated thyroid carcinoma (TC) have increased in many countries. Adiposity and dietary risk factors may play a role, but little is known on the influence of energy intake and macronutrient composition. The aim of this study was to investigate the associations between TC and the intake of energy, macronutrients, glycemic index (GI) and glycemic load in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. The study included 477,274 middle-age participants (70.2% women) from ten European countries. Dietary data were collected using country-specific validated dietary questionnaires. Total carbohydrates, proteins, fats, saturated, monounsaturated and polyunsaturated fats (PUFA), starch, sugar, and fiber were computed as g/1,000 kcal. Multivariable Cox regression was used to calculate multivariable adjusted hazard ratios (HR) and 95% confidence interval (CI) by intake quartile (Q). After a mean follow-up time of 11 years, differentiated TC was diagnosed in 556 participants (90% women). Overall, we found significant associations only with total energy (HRQ4 vs .Q1 , 1.29; 95% CI, 1.00-1.68) and PUFA intakes (HRQ4 vs .Q1 , 0.74; 95% CI, 0.57-0.95). However, the associations with starch and sugar intake and GI were significantly heterogeneous across body mass index (BMI) groups, i.e., positive associations with starch and GI were found in participants with a BMI ≥ 25 and with sugar intake in those with BMI < 25. Moreover, inverse associations with starch and GI were observed in subjects with BMI < 25. In conclusion, our results suggest that high total energy and low PUFA intakes may increase the risk of differentiated TC. Positive associations with starch intake and GI in participants with BMI ≥ 25 suggest that those persons may have a greater insulin response to high starch intake and GI than lean people.

Metabolome biomarkers linking dietary fibre intake with cardiometabolic effects: results from the Danish Diet, Cancer and Health-Next Generations MAX study.

Biomarkers associated with dietary fibre intake, as complements to traditional dietary assessment tools, may improve the understanding of its role in human health. Our aim was to discover metabolite biomarkers related to dietary fibre intake and investigate their association with cardiometabolic risk factors. We used data and samples from the Danish Diet Cancer and Health Next Generation (DCH-NG) MAX-study, a one-year observational study with evaluations at baseline, six and 12 months (n = 624, 55% female, mean age: 43 years, 1353 observations). Direct associations between fibre intake and plasma concentrations of 2,6-dihydroxybenzoic acid (2,6-DHBA) and indolepropionic acid were observed at the three time-points. Both metabolites showed an intraclass-correlation coefficient (ICC) > 0.50 and were associated with the self-reported intake of wholegrain cereals, and of fruits and vegetables, respectively. Other metabolites associated with dietary fibre intake were linolenoyl carnitine, 2-aminophenol, 3,4-DHBA, and proline betaine. Based on the metabolites associated with dietary fibre intake we calculated predicted values of fibre intake using a multivariate, machine-learning algorithm. Metabolomics-based predicted fibre, but not self-reported fibre values, showed negative associations with cardiometabolic risk factors (i.e. high sensitivity C-reactive protein, systolic and diastolic blood pressure, all FDR-adjusted p-values <0.05). Furthermore, different correlations with gut microbiota composition were observed. In conclusion, 2,6-DHBA and indolepropionic acid in plasma may better link dietary fibre intake with its metabolic effects than self-reported values. These metabolites may represent a novel class of biomarkers reflecting both dietary exposure and host and/or gut microbiota characteristics providing a read-out that is differentially related to cardiometabolic risk.

Relative Validity and Reproducibility of a Web-Based Semi-Quantitative Food Frequency Questionnaire in the Danish Diet, Cancer, and Health-Next Generations MAX Study.

The food frequency questionnaire (FFQ) is designed to capture an individual's habitual dietary intake and is the most applied method in nutritional epidemiology. Our aim was to assess the relative validity and reproducibility of the FFQ used in the Diet, Cancer, and Health-Next Generations cohort (DCH-NG). We included 415 Danish women and men aged 18-67 years. Spearman's correlations coefficients, Bland-Altman limits of agreement and cross-classification between dietary intakes estimated from the FFQ administered at baseline (FFQbaseline), and the mean of three 24-h dietary recalls (24-HDRs) and the FFQ administered after 12 months (FFQ12 months) were determined. Nutrient intakes were energy-adjusted by Nutrient Density and Residual methods. Correlation coefficients ranged from 0.18-0.58 for energy and energy-adjusted nutrient intakes, and the percentage of participants classified into the same quartile ranged from 28-47% between the FFQbaseline and the 24-HDRs. For the FFQ12 months compared with FFQbaseline, correlation coefficients ranged from 0.52-0.88 for intakes of energy, energy-adjusted nutrients, and food groups, and the proportion of participants classified into the same quartiles ranged from 43-69%. Overall, the FFQ provided a satisfactory ranking of individuals according to energy, nutrient, and food group intakes, making the FFQ suitable for use in epidemiological studies investigating diet in relation to disease outcomes.

Plasma metabolomic profiles of plant-based dietary indices reveal potential pathways for metabolic syndrome associations.

BACKGROUND AND AIMS: Plant-based dietary patterns have been associated with improved health outcomes. This study aims to describe the metabolomic fingerprints of plant-based diet indices (PDI) and examine their association with metabolic syndrome (MetS) and its components in a Danish population. METHODS: The MAX study comprised 676 participants (55% women, aged 18-67 y) from Copenhagen. Sociodemographic and dietary data were collected using questionnaires and three 24-h dietary recalls over one year (at baseline, and at 6 and 12 months). Mean dietary intakes were computed, as well as overall PDI, healthful (hPDI) and unhealthful (uPDI) scores, according to food groups for each plant-based index. Clinical variables were also collected at the same time points in a health examination that included complete blood tests. MetS was defined according to the International Diabetes Federation criteria. Plasma metabolites were measured using a targeted metabolomics approach. Metabolites associated with PDI were selected using random forest models and their relationships with PDIs and MetS were analyzed using generalized linear mixed models. RESULTS: The mean prevalence of MetS was 10.8%. High, compared to low, hPDI and uPDI scores were associated with a lower and higher odd of MetS, respectively [odds ratio (95%CI); hPDI: 0.56 (0.43-0.74); uPDI: 1.61 (1.26-2.05)]. Out of 411 quantified plasma metabolites, machine-learning metabolomics fingerprinting revealed 13 metabolites, including food and food-related microbial metabolites, like hypaphorine, indolepropionic acid and lignan-derived enterolactones. These metabolites were associated with all PDIs and were inversely correlated with MetS components (p < 0.05). Furthermore, they had an explainable contribution of 12% and 14% for the association between hPDI or uPDI, respectively, and MetS only among participants with overweight/obesity. CONCLUSIONS: Metabolites associated with PDIs were inversely associated with MetS and its components, and may partially explain the effects of plant-based diets on cardiometabolic risk factors.

Dietary Sources of Anthocyanins and Their Association with Metabolome Biomarkers and Cardiometabolic Risk Factors in an Observational Study.

Anthocyanins (ACNs) are (poly)phenols associated with reduced cardiometabolic risk. Associations between dietary intake, microbial metabolism, and cardiometabolic health benefits of ACNs have not been fully characterized. Our aims were to study the association between ACN intake, considering its dietary sources, and plasma metabolites, and to relate them with cardiometabolic risk factors in an observational study. A total of 1351 samples from 624 participants (55% female, mean age: 45 ± 12 years old) enrolled in the DCH-NG MAX study were studied using a targeted metabolomic analysis. Twenty-four-hour dietary recalls were used to collect dietary data at baseline, six, and twelve months. ACN content of foods was calculated using Phenol Explorer and foods were categorized into food groups. The median intake of total ACNs was 1.6mg/day. Using mixed graphical models, ACNs from different foods showed specific associations with plasma metabolome biomarkers. Combining these results with censored regression analysis, metabolites associated with ACNs intake were: salsolinol sulfate, 4-methylcatechol sulfate, linoleoyl carnitine, 3,4-dihydroxyphenylacetic acid, and one valerolactone. Salsolinol sulfate and 4-methylcatechol sulfate, both related to the intake of ACNs mainly from berries, were inversely associated with visceral adipose tissue. In conclusion, plasma metabolome biomarkers of dietary ACNs depended on the dietary source and some of them, such as salsolinol sulfate and 4-methylcatechol sulfate may link berry intake with cardiometabolic health benefits.

Comparison of Flavonoid Intake Assessment Methods Using USDA and Phenol Explorer Databases: Subcohort Diet, Cancer and Health-Next Generations-MAX Study.

Flavonoids are bioactive plant compounds that are widely present in the human diet. Estimating flavonoid intake with a high degree of certainty is challenging due to the inherent limitations of dietary questionnaires and food composition databases. This study aimed to evaluate the degree of reliability among flavonoid intakes estimated using four different approaches based on the two most comprehensive flavonoid databases, namely, United States Department of Agriculture (USDA) and Phenol Explorer (PE). In 678 individuals from the MAX study, a subcohort of the Diet, Cancer and Health-Next Generations cohort, dietary data were collected using three 24-h diet recalls over 1 year. Estimates of flavonoid intake were compared using flavonoid food content from PE as (1) aglycones (chromatography with hydrolysis), (2) aglycones transformed (converted from glycosides by chromatography without hydrolysis), (3) as they are in nature (glycosides, aglycones, and esters), and 4) using flavonoid content from USDA as aglycones (converted). Spearman's intra-class correlation (ICC) coefficient and weighted kappa (K) coefficient were calculated for the reliability analysis. When comparing PE total aglycones to USDA total aglycones, there was a moderate reliability when a continuous variable was used [ICC: 0.73, 95% confidence interval (CI): 0.70-0.76] and an excellent reliability when flavonoid intake was modeled as a categorical variable (K: 0.89, 95% CI: 0.88-0.90). The degree of reliability among all methods of estimated flavonoid intakes was very similar, especially between database pairs, for the flavanol subclass, while larger differences were observed for flavone, flavonol, and isoflavone subclasses. Our findings indicate that caution should be taken when comparing the results of the associations between flavonoid intakes and health outcomes from studies, when flavonoid intakes were estimated using different methods, particularly for some subclasses.

Pepper Alkaloids and Processed Meat Intake: Results from a Randomized Trial and the European Prospective Investigation into Cancer and Nutrition (EPIC) Cohort.

SCOPE: Processed meat intake has been associated with adverse health outcomes. However, little is known about the type of processed meat more particularly responsible for these effects. This study aims to identify novel biomarkers for processed meat intake. METHODS AND RESULTS: In a controlled randomized cross-over dietary intervention study, 12 healthy volunteers consume different processed and non-processed meats for 3 consecutive days each. Metabolomics analyses are applied on post-intervention fasting blood and urine samples to identify discriminating molecular features of processed meat intake. Nine and five pepper alkaloid metabolites, including piperine, are identified as major discriminants of salami intake in urine and plasma, respectively. The associations with processed meat intake are tested for replication in a cross-sectional study (n = 418) embedded within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. Three of the serum metabolites including piperine are associated with habitual intake of sausages and to a lesser extent of total processed meat. CONCLUSION: Pepper alkaloids are major discriminants of intake for sausages that contain high levels of pepper used as ingredient. Further work is needed to assess if pepper alkaloids in combination with other metabolites may serve as biomarkers of processed meat intake.

Associations between dietary amino acid intakes and blood concentration levels.

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.

A New Pipeline for the Normalization and Pooling of Metabolomics Data.

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.

A metabolomic study of red and processed meat intake and acylcarnitine concentrations in human urine and blood.

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.

Association between nutritional profiles of foods underlying Nutri-Score front-of-pack labels and mortality: EPIC cohort study in 10 European countries.

OBJECTIVE: To determine if the Food Standards Agency nutrient profiling system (FSAm-NPS), which grades the nutritional quality of food products and is used to derive the Nutri-Score front-of-packet label to guide consumers towards healthier food choices, is associated with mortality. DESIGN: Population based cohort study. SETTING: European Prospective Investigation into Cancer and Nutrition (EPIC) cohort from 23 centres in 10 European countries. PARTICIPANTS: 521 324 adults; at recruitment, country specific and validated dietary questionnaires were used to assess their usual dietary intakes. A FSAm-NPS score was calculated for each food item per 100 g content of energy, sugars, saturated fatty acids, sodium, fibre, and protein, and of fruit, vegetables, legumes, and nuts. The FSAm-NPS dietary index was calculated for each participant as an energy weighted mean of the FSAm-NPS score of all foods consumed. The higher the score the lower the overall nutritional quality of the diet. MAIN OUTCOME MEASURE: Associations between the FSAm-NPS dietary index score and mortality, assessed using multivariable adjusted Cox proportional hazards regression models. RESULTS: After exclusions, 501 594 adults (median follow-up 17.2 years, 8 162 730 person years) were included in the analyses. Those with a higher FSAm-NPS dietary index score (highest versus lowest fifth) showed an increased risk of all cause mortality (n=53 112 events from non-external causes; hazard ratio 1.07, 95% confidence interval 1.03 to 1.10, P<0.001 for trend) and mortality from cancer (1.08, 1.03 to 1.13, P<0.001 for trend) and diseases of the circulatory (1.04, 0.98 to 1.11, P=0.06 for trend), respiratory (1.39, 1.22 to 1.59, P<0.001), and digestive (1.22, 1.02 to 1.45, P=0.03 for trend) systems. The age standardised absolute rates for all cause mortality per 10 000 persons over 10 years were 760 (men=1237; women=563) for those in the highest fifth of the FSAm-NPS dietary index score and 661 (men=1008; women=518) for those in the lowest fifth. CONCLUSIONS: In this large multinational European cohort, consuming foods with a higher FSAm-NPS score (lower nutritional quality) was associated with a higher mortality for all causes and for cancer and diseases of the circulatory, respiratory, and digestive systems, supporting the relevance of FSAm-NPS to characterise healthier food choices in the context of public health policies (eg, the Nutri-Score) for European populations. This is important considering ongoing discussions about the potential implementation of a unique nutrition labelling system at the European Union level.

Circulating Metabolites Associated with Alcohol Intake in the European Prospective Investigation into Cancer and Nutrition Cohort.

Identifying the metabolites associated with alcohol consumption may provide insights into the metabolic pathways through which alcohol may affect human health. We studied associations of alcohol consumption with circulating concentrations of 123 metabolites among 2974 healthy participants from the European Prospective Investigation into Cancer and Nutrition (EPIC) study. Alcohol consumption at recruitment was self-reported through dietary questionnaires. Metabolite concentrations were measured by tandem mass spectrometry (BIOCRATES AbsoluteIDQTM p180 kit). Data were randomly divided into discovery (2/3) and replication (1/3) sets. Multivariable linear regression models were used to evaluate confounder-adjusted associations of alcohol consumption with metabolite concentrations. Metabolites significantly related to alcohol intake in the discovery set (FDR q-value < 0.05) were further tested in the replication set (Bonferroni-corrected p-value < 0.05). Of the 72 metabolites significantly related to alcohol intake in the discovery set, 34 were also significant in the replication analysis, including three acylcarnitines, the amino acid citrulline, four lysophosphatidylcholines, 13 diacylphosphatidylcholines, seven acyl-alkylphosphatidylcholines, and six sphingomyelins. Our results confirmed earlier findings that alcohol consumption was associated with several lipid metabolites, and possibly also with specific acylcarnitines and amino acids. This provides further leads for future research studies aiming at elucidating the mechanisms underlying the effects of alcohol in relation to morbid conditions.