MATERIALS & METHODS: Here, we examined the potential of DNA methylation changes in 910 prediagnostic peripheral blood samples as a marker of exposure to tobacco smoke in a large multinational cohort.
RESULTS: We identified 748 CpG sites that were differentially methylated between smokers and nonsmokers, among which we identified novel regionally clustered CpGs associated with active smoking. Importantly, we found a marked reversibility of methylation changes after smoking cessation, although specific genes remained differentially methylated up to 22 years after cessation.
CONCLUSION: Our study has comprehensively cataloged the smoking-associated DNA methylation alterations and showed that these alterations are reversible after smoking cessation.
METHODS: Biomarkers of internal exposure were measured in red blood cells (collected at baseline) by high-performance liquid chromatography/tandem mass spectrometry (HPLC/MS/MS) . In this cross-sectional analysis, four dependent variables were evaluated: HbAA, HbGA, sum of total adducts (HbAA + HbGA), and their ratio (HbGA/HbAA). Simple and multiple regression analyses were used to identify determinants of the four outcome variables. All dependent variables (except HbGA/HbAA) and all independent variables were log-transformed (log2) to improve normality. Median (25th-75th percentile) HbAA and HbGA adduct levels were 41.3 (32.8-53.1) pmol/g Hb and 34.2 (25.4-46.9) pmol/g Hb, respectively.
RESULTS: The main food group determinants of HbAA, HbGA, and HbAA + HbGA were biscuits, crackers, and dry cakes. Alcohol intake and body mass index were identified as the principal determinants of HbGA/HbAA. The total percent variation in HbAA, HbGA, HbAA + HbGA, and HbGA/HbAA explained in this study was 30, 26, 29, and 13 %, respectively.
CONCLUSIONS: Dietary and lifestyle factors explain a moderate proportion of acrylamide adduct variation in non-smoking postmenopausal women from the EPIC cohort.
METHODS: A case-control study was nested in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. A total of 2008 incident invasive breast cancer cases (estrogen receptor (ER)+, n = 1622; ER-, n = 386), matched 1:1 to controls, were included in the analysis. Women were predominantly postmenopausal at blood collection (77%); postmenopausal women included users and non-users of postmenopausal hormone therapy (HT). Serum OPG was quantified with an electrochemiluminescence assay. Relative risks (RRs) and 95% confidence intervals (CIs) were calculated using conditional logistic regression.
RESULTS: The associations between OPG and ER+ and ER- breast cancer differed significantly. Higher concentrations of OPG were associated with increased risk of ER- breast cancer (top vs. bottom tertile RR = 1.93 [95% CI 1.24-3.02]; p trend = 0.03). We observed a suggestive inverse association for ER+ disease overall and among women premenopausal at blood collection. Results for ER- disease did not differ by menopausal status at blood collection (p het = 0.97), and we observed no heterogeneity by HT use at blood collection (p het ≥ 0.43) or age at breast cancer diagnosis (p het ≥ 0.30).
CONCLUSIONS: This study provides the first prospective data on OPG and breast cancer risk by hormone receptor subtype. High circulating OPG may represent a novel risk factor for ER- breast cancer.
METHODS: Baseline plasma fatty acid concentrations were determined in a representative EPIC sample from the 23 participating EPIC centers. A total of 1,945 individuals were followed for a median of 4.9 years to monitor weight change. The association between elaidic acid level and percent change of weight was investigated using a multinomial logistic regression model, adjusted by length of follow-up, age, energy, alcohol, smoking status, physical activity, and region.
RESULTS: In women, doubling elaidic acid was associated with a decreased risk of weight loss (odds ratio (OR) = 0.69, 95% confidence interval (CI) = 0.55-0.88, p = 0.002) and a trend was observed with an increased risk of weight gain during the 5-year follow-up (OR = 1.23, 95% CI = 0.97-1.56, p = 0.082) (p-trend
METHODS: This study includes 373,293 men and women, 25-70 years old, recruited between 1992 and 2000 from 10 European countries in the European Prospective Investigation into Cancer and Nutrition (EPIC) study. Habitual intake of nuts including peanuts, together defined as nut intake, was estimated from country-specific validated dietary questionnaires. Body weight was measured at recruitment and self-reported 5 years later. The association between nut intake and body weight change was estimated using multilevel mixed linear regression models with center/country as random effect and nut intake and relevant confounders as fixed effects. The relative risk (RR) of becoming overweight or obese after 5 years was investigated using multivariate Poisson regressions stratified according to baseline body mass index (BMI).
RESULTS: On average, study participants gained 2.1 kg (SD 5.0 kg) over 5 years. Compared to non-consumers, subjects in the highest quartile of nut intake had less weight gain over 5 years (-0.07 kg; 95% CI -0.12 to -0.02) (P trend = 0.025) and had 5% lower risk of becoming overweight (RR 0.95; 95% CI 0.92-0.98) or obese (RR 0.95; 95% CI 0.90-0.99) (both P trend <0.008).
CONCLUSIONS: Higher intake of nuts is associated with reduced weight gain and a lower risk of becoming overweight or obese.
METHODS: Among 477 312 participants, intakes of 23 nutrients were estimated from validated dietary questionnaires. Using results from a previous principal component (PC) analysis, four major nutrient patterns were identified. Hazard ratios (HRs) and 95% confidence intervals (CIs) were computed for the association of each of the four patterns and CRC incidence using multivariate Cox proportional hazards models with adjustment for established CRC risk factors.
RESULTS: During an average of 11 years of follow-up, 4517 incident cases of CRC were documented. A nutrient pattern characterised by high intakes of vitamins and minerals was inversely associated with CRC (HR per 1 s.d.=0.94, 95% CI: 0.92-0.98) as was a pattern characterised by total protein, riboflavin, phosphorus and calcium (HR (1 s.d.)=0.96, 95% CI: 0.93-0.99). The remaining two patterns were not significantly associated with CRC risk.
CONCLUSIONS: Analysing nutrient patterns may improve our understanding of how groups of nutrients relate to CRC.
METHODS: This study includes 235,880 participants, 25-70 years old, recruited between 1992 and 2000 in 10 European countries. Intakes of 23 nutrients were estimated from country-specific validated dietary questionnaires using the harmonized EPIC Nutrient DataBase. Four nutrient patterns, explaining 67 % of the total variance of nutrient intakes, were previously identified from principal component analysis. Body weight was measured at recruitment and self-reported 5 years later. The relationship between nutrient patterns and annual weight change was examined separately for men and women using linear mixed models with random effect according to center controlling for confounders.
RESULTS: Mean weight gain was 460 g/year (SD 950) and 420 g/year (SD 940) for men and women, respectively. The annual differences in weight gain per one SD increase in the pattern scores were as follows: principal component (PC) 1, characterized by nutrients from plant food sources, was inversely associated with weight gain in men (-22 g/year; 95 % CI -33 to -10) and women (-18 g/year; 95 % CI -26 to -11). In contrast, PC4, characterized by protein, vitamin B2, phosphorus, and calcium, was associated with a weight gain of +41 g/year (95 % CI +2 to +80) and +88 g/year (95 % CI +36 to +140) in men and women, respectively. Associations with PC2, a pattern driven by many micro-nutrients, and with PC3, a pattern driven by vitamin D, were less consistent and/or non-significant.
CONCLUSIONS: We identified two main nutrient patterns that are associated with moderate but significant long-term differences in weight gain in adults.