A comparison of complementary measures of vitamin B6 status, function, and metabolism in the European Prospective Investigation into Cancer and Nutrition (EPIC) study

Background: Vitamin B6 insufficiency has been linked to increased risk of cancer and other chronic diseases. The circulating concentration of pyridoxal 5'-phosphate (PLP) is a commonly used measure of vitamin B6 status. Ratios of substrates indicating PLP coenzymatic function and metabolism may be useful complementary measures to further explore the role of vitamin B6 in health. Objectives: We explored the sensitivity of 5 outcomes, namely PLP concentration, homocysteine:cysteine (Hcy:Cys), cystathionine:cysteine (Cysta:Cys), the 3´-hydroxykynurenine ratio (HKr), and the 4-pyridoxic acid ratio (PAr) to vitamin B6 intake as well as personal and lifestyle characteristics. Medthods: Dietary intake and biomarker data were collected from participants from 3 nested case-control studies within the European Prospective Investigation into Cancer and Nutrition (EPIC). Bayesian regression models assessed the associations of the 5 biomarker outcomes with vitamin B6 intake and personal and lifestyle covariates. Analogous models examined the relations of Hcy:Cys, Cysta:Cys, and HKr with PLP. Results: In total, 4608 participants were included in the analyses. Vitamin B6 intake was most strongly associated with PLP, moderately associated with Hcy:Cys, Cysta:Cys, and HKr, and not associated with PAr (fold change in marker given a doubling of vitamin B6 intake: PLP 1.60 [95% credible interval (CrI): 1.50, 1.71]; Hcy:Cys 0.87 [95% CrI: 0.84, 0.90]; Cysta:Cys 0.89 [95% CrI: 0.84, 0.94]; HKr 0.88 [95% CrI: 0.85, 0.91]; PAr 1.00 [95% CrI: 0.95, 1.05]). PAr was most sensitive to age, and HKr was least sensitive to BMI and alcohol intake. Sex and menopause status were strongly associated with all 5 markers. Conclusions: We found that 5 different markers, capturing different aspects of vitamin B6-related biological processes, varied in their associations with vitamin B6 intake and personal and lifestyle predictors

Genome-Wide Interactions with Dairy Intake for Body Mass Index in Adults of European Descent

Scope: Body weight responds variably to the intake of dairy foods. Genetic variation may contribute to inter‐individual variability in associations between body weight and dairy consumption. Methods and results: A genome‐wide interaction study to discover genetic variants that account for variation in BMI in the context of low‐fat, high‐fat and total dairy intake in cross‐sectional analysis was conducted. Data from nine discovery studies (up to 25 513 European descent individuals) were meta‐analyzed. Twenty‐six genetic variants reached the selected significance threshold (p‐interaction \u3c10−7), and six independent variants (LINC01512‐rs7751666, PALM2/AKAP2‐rs914359, ACTA2‐rs1388, PPP1R12A‐rs7961195, LINC00333‐rs9635058, AC098847.1‐rs1791355) were evaluated meta‐analytically for replication of interaction in up to 17 675 individuals. Variant rs9635058 (128 kb 3’ of LINC00333) was replicated (p‐interaction = 0.004). In the discovery cohorts, rs9635058 interacted with dairy (p‐interaction = 7.36 × 10−8) such that each serving of low‐fat dairy was associated with 0.225 kg m−2 lower BMI per each additional copy of the effect allele (A). A second genetic variant (ACTA2‐rs1388) approached interaction replication significance for low‐fat dairy exposure. Conclusion: Body weight responses to dairy intake may be modified by genotype, in that greater dairy intake may protect a genetic subgroup from higher body weight

Timing of eating across ten European countries - results from the European Prospective Investigation into Cancer and Nutrition (EPIC) calibration study

Objective To examine timing of eating across ten European countries. Design Cross-sectional analysis of the European Prospective Investigation into Cancer and Nutrition (EPIC) calibration study using standardized 24 h diet recalls collected during 1995-2000. Eleven predefined food consumption occasions were assessed during the recall interview. We present time of consumption of meals and snacks as well as the later:earlier energy intake ratio, with earlier and later intakes defined as 06.00-14.00 and 15.00-24.00 hours, respectively. Type III tests were used to examine associations of sociodemographic, lifestyle and health variables with timing of energy intake. Setting Ten Western European countries. Subjects In total, 22 985 women and 13 035 men aged 35-74 years (n 36 020). Results A south-north gradient was observed for timing of eating, with later consumption of meals and snacks in Mediterranean countries compared with Central and Northern European countries. However, the energy load was reversed, with the later:earlier energy intake ratio ranging from 0 center dot 68 (France) to 1 center dot 39 (Norway) among women, and from 0 center dot 71 (Greece) to 1 center dot 35 (the Netherlands) among men. Among women, country, age, education, marital status, smoking, day of recall and season were all independently associated with timing of energy intake (all PPeer reviewe

Intake estimation of total and individual flavan-3-ols, proanthocyanidins and theaflavins, their food sources and determinants in the European Prospective Investigation into Cancer and Nutrition (EPIC) study

Epidemiological studies suggest health-protective effects of flavan-3-ols and their derived compounds on chronic diseases. The present study aimed to estimate dietary flavan-3-ol, proanthocyanidin (PA) and theaflavin intakes, their food sources and potential determinants in the European Prospective Investigation into Cancer and Nutrition (EPIC) calibration cohort. Dietary data were collected using a standardised 24 h dietary recall software administered to 36 037 subjects aged 35-74 years. Dietary data were linked with a flavanoid food composition database compiled from the latest US Department of Agriculture and Phenol-Explorer databases and expanded to include recipes, estimations and retention factors. Total flavan-3-ol intake was the highest in UK Health-conscious men (453·6 mg/d) and women of UK General population (377·6 mg/d), while the intake was the lowest in Greece (men: 160·5 mg/d; women: 124·8 mg/d). Monomer intake was the highest in UK General population (men: 213·5 mg/d; women: 178·6 mg/d) and the lowest in Greece (men: 26·6 mg/d in men; women: 20·7 mg/d). Theaflavin intake was the highest in UK General population (men: 29·3 mg/d; women: 25·3 mg/d) and close to zero in Greece and Spain. PA intake was the highest in Asturias (men: 455·2 mg/d) and San Sebastian (women: 253 mg/d), while being the lowest in Greece (men: 134·6 mg/d; women: 101·0 mg/d). Except for the UK, non-citrus fruits (apples/pears) were the highest contributors to the total flavan-3-ol intake. Tea was the main contributor of total flavan-3-ols in the UK. Flavan-3-ol, PA and theaflavin intakes were significantly different among all assessed groups. This study showed heterogeneity in flavan-3-ol, PA and theaflavin intake throughout the EPIC countries

A Nested Case-Control Study of Metabolically Defined Body Size Phenotypes and Risk of Colorectal Cancer in the European Prospective Investigation into Cancer and Nutrition (EPIC).

BACKGROUND: Obesity is positively associated with colorectal cancer. Recently, body size subtypes categorised by the prevalence of hyperinsulinaemia have been defined, and metabolically healthy overweight/obese individuals (without hyperinsulinaemia) have been suggested to be at lower risk of cardiovascular disease than their metabolically unhealthy (hyperinsulinaemic) overweight/obese counterparts. Whether similarly variable relationships exist for metabolically defined body size phenotypes and colorectal cancer risk is unknown. METHODS AND FINDINGS: The association of metabolically defined body size phenotypes with colorectal cancer was investigated in a case-control study nested within the European Prospective Investigation into Cancer and Nutrition (EPIC) study. Metabolic health/body size phenotypes were defined according to hyperinsulinaemia status using serum concentrations of C-peptide, a marker of insulin secretion. A total of 737 incident colorectal cancer cases and 737 matched controls were divided into tertiles based on the distribution of C-peptide concentration amongst the control population, and participants were classified as metabolically healthy if below the first tertile of C-peptide and metabolically unhealthy if above the first tertile. These metabolic health definitions were then combined with body mass index (BMI) measurements to create four metabolic health/body size phenotype categories: (1) metabolically healthy/normal weight (BMI < 25 kg/m2), (2) metabolically healthy/overweight (BMI ≥ 25 kg/m2), (3) metabolically unhealthy/normal weight (BMI < 25 kg/m2), and (4) metabolically unhealthy/overweight (BMI ≥ 25 kg/m2). Additionally, in separate models, waist circumference measurements (using the International Diabetes Federation cut-points [≥80 cm for women and ≥94 cm for men]) were used (instead of BMI) to create the four metabolic health/body size phenotype categories. Statistical tests used in the analysis were all two-sided, and a p-value of <0.05 was considered statistically significant. In multivariable-adjusted conditional logistic regression models with BMI used to define adiposity, compared with metabolically healthy/normal weight individuals, we observed a higher colorectal cancer risk among metabolically unhealthy/normal weight (odds ratio [OR] = 1.59, 95% CI 1.10-2.28) and metabolically unhealthy/overweight (OR = 1.40, 95% CI 1.01-1.94) participants, but not among metabolically healthy/overweight individuals (OR = 0.96, 95% CI 0.65-1.42). Among the overweight individuals, lower colorectal cancer risk was observed for metabolically healthy/overweight individuals compared with metabolically unhealthy/overweight individuals (OR = 0.69, 95% CI 0.49-0.96). These associations were generally consistent when waist circumference was used as the measure of adiposity. To our knowledge, there is no universally accepted clinical definition for using C-peptide level as an indication of hyperinsulinaemia. Therefore, a possible limitation of our analysis was that the classification of individuals as being hyperinsulinaemic-based on their C-peptide level-was arbitrary. However, when we used quartiles or the median of C-peptide, instead of tertiles, as the cut-point of hyperinsulinaemia, a similar pattern of associations was observed. CONCLUSIONS: These results support the idea that individuals with the metabolically healthy/overweight phenotype (with normal insulin levels) are at lower colorectal cancer risk than those with hyperinsulinaemia. The combination of anthropometric measures with metabolic parameters, such as C-peptide, may be useful for defining strata of the population at greater risk of colorectal cancer

Estimation of the intake of anthocyanidins and their food sources in the European prospective investigation into cancer and nutrition (EPIC) study

Anthocyanidins are bioactive flavonoids with potential health-promoting effects. These may vary among single anthocyanidins considering differences in their bioavailability and some of the mechanisms involved. The aim of the present study was to estimate the dietary intake of anthocyanidins, their food sources and the lifestyle factors (sex, age, BMI, smoking status, educational level and physisical activity) involved among twenty-seven centres in ten European countries participating in the European Prospective Investigation into Cancer and Nutrition (EPIC) study. Anthocyanidin intake and their food sources for 36 037 subjects, aged between 35 and 74 years, in twenty-seven redefined centres were obtained using standardised 24 h dietary recall software (EPIC-SOFT). An ad hoc food composition database on anthocyanidins (cyanidin, delphinidin, malvidin, pelargonidin, peonidin, petunidin) was compiled using data from the US Department of Agriculture and Phenol-Explorer databases and was expanded by adding recipes, estimated values and cooking factors. For men, the total anthocyanidin mean intake ranged from 19·83 (se 1·53) mg/d (Bilthoven, The Netherlands) to 64·88 (se 1·86) mg/d (Turin, Italy), whereas for women the range was 18·73 (se 2·80) mg/d (Granada, Spain) to 44·08 (se 2·45) mg/d (Turin, Italy). A clear south to north gradient intake was observed. Cyanidins and malvidins were the main anthocynidin contributors depending on the region and sex. Anthocyanidin intake was higher in non-obese older females, non-smokers, and increased with educational level and physical activity. The major food sources were fruits, wine, non-alcoholic beverages and some vegetables. The present study shows differences in both total and individual anthocyanidin intakes and various lifestyle factors throughout Europe, with some geographical variability in their food sources

Obesity Partially Mediates the Diabetogenic Effect of Lowering LDL Cholesterol

OBJECTIVE LDL cholesterol (LDLc)-lowering drugs modestly increase body weight and type 2 diabetes risk, but the extent to which the diabetogenic effect of lowering LDLc is mediated through increased BMI is unknown. RESEARCH DESIGN AND METHODS We conducted summary-level univariable and multivariable Mendelian randomization (MR) analyses in 921,908 participants to investigate the effect of lowering LDLc on type 2 diabetes risk and the proportion of this effect mediated through BMI. We used data from 92,532 participants from 14 observational studies to replicate findings in individual-level MR analyses. RESULTS A 1-SD decrease in genetically predicted LDLc was associated with increased type 2 diabetes odds (odds ratio [OR] 1.12 [95% CI 1.01, 1.24]) and BMI (b 5 0.07 SD units [95% CI 0.02, 0.12]) in univariable MR analyses. The multivariable MR analysis showed evidence of an indirect effect of lowering LDLc on type 2 diabetes through BMI (OR 1.04 [95% CI 1.01, 1.08]) with a proportion mediated of 38% of the total effect (P 5 0.03). Total and indirect effect estimates were similar across a number of sensitivity analyses. Individual-level MR analyses confirmed the indirect effect of lowering LDLc on type 2 diabetes through BMI with an estimated proportion mediated of 8% (P 5 0.04). CONCLUSIONS These findings suggest that the diabetogenic effect attributed to lowering LDLc is partially mediated through increased BMI. Our results could help advance understanding of adipose tissue and lipids in type 2 diabetes pathophysiology and inform strategies to reduce diabetes risk among individuals taking LDLc-lowering medications

Dietary Intake of Total, Heme and Non-Heme Iron and the Risk of Colorectal Cancer in a European Prospective Cohort Study

BACKGROUND: Iron is an essential micronutrient with differing intake patterns and metabolism between men and women. Epidemiologic evidence on the association of dietary iron and its heme and non-heme components with colorectal cancer (CRC) development is inconclusive. METHODS: We examined baseline dietary questionnaire-assessed intakes of total, heme, and non-heme iron and CRC risk in the EPIC cohort. Sex-specific multivariable-adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) were computed using Cox regression. We modelled substitution of a 1 mg/day of heme iron intake with non-heme iron using the leave one-out method. RESULTS: Of 450,105 participants (318,680 women) followed for 14.2 ± 4.0 years, 6162 (3511 women) developed CRC. In men, total iron intake was not associated with CRC risk (highest vs. lowest quintile, HR CONCLUSIONS: Our findings suggest potential sex-specific CRC risk associations for higher iron consumption that may differ by dietary sources

Five meal patterns are differently associated with nutrient intakes, lifestyle factors and energy misreporting in a sub-sample of the Malmö Diet and Cancer cohort

OBJECTIVE: Examine how meal patterns are associated with nutrient intakes, lifestyle and socioeconomic factors, and energy misreporting. DESIGN: A cross-sectional study within the Malmö Diet and Cancer (MDC) cohort. Participants reported on the overall types and frequency of meals consumed, and completed a modified dietary history, a lifestyle and socioeconomic questionnaire, and anthropometric measurements. Based on the reported intake of six different meal types, meal pattern groups were distinguished using Ward's cluster analysis. Associations between meal patterns and nutrient intakes, anthropometric, lifestyle and socioeconomic variables were examined using the chi(2)-method and analysis of variance. SUBJECTS: A sub-sample of the MDC study cohort (n=28,098), consisting of 1,355 men and 1,654 women. RESULTS: Cluster analysis identified five groups of subjects with different meal patterns in both men and women. These meal pattern groups differed regarding nutrient intakes, lifestyle and socioeconomic factors. Subjects reporting frequent coffee meals were more likely to report an 'unhealthy' lifestyle, e.g. smoking, high alcohol consumption and low physical activity, while those with a fruit pattern reported a more 'healthy' lifestyle. Women were more likely to underreport their energy intake than men, and the degree of underreporting varied between the meal pattern groups. CONCLUSIONS: The meal pattern groups showed significant differences in dietary quality and socioeconomic and lifestyle variables. This supports previous research suggesting that diet is part of a multifaceted phenomenon. Incorporation of aspects on how foods are combined and eaten into public health advices might improve their efficiency