The Influence of Smoking and Occupational Risk Factors on DNA Methylation in the AHRR and F2RL3 Genes.

BACKGROUND: AHRR and F2RL3 hypomethylation has been associated with lung cancer. In this study, we investigated the cross-sectional association between smoking and occupational exposures, and AHRR and F2RL3 methylation. METHODS: A case-control study was nested in CARTaGENE to examine the association between AHRR and F2RL3 methylation and lung cancer risk (200 cases; 400 controls). A secondary analysis was conducted using the data collected from this nested study; namely, baseline information on participants' smoking behavior and longest-held job was obtained. A cumulative smoking index summarized information on the number of cigarettes smoked, duration of smoking, and time since cessation. Exposure to 13 occupational agents was estimated using the Canadian Job Exposure Matrix. In baseline blood samples, methylation ratios of 40 CpG sites in the AHRR and F2RL3 genes were measured using Sequenom EpiTYPER. Separate least squares regression models were used to estimate the associations between smoking and occupational exposures, and average AHRR and F2RL3 methylation levels, while adjusting for confounders identified from directed acyclic graphs. RESULTS: In both genes, smoking was associated with lower average methylation levels. Occupational exposure to aromatic amines, cadmium, and formaldehyde were associated with lower AHRR methylation while, only benzene was associated with F2RL3 hypomethylation; these associations were stronger among ever smokers. CONCLUSIONS: Our findings support that smoking and occupational exposures to some agents are associated with AHRR and F2RL3 hypomethylation. IMPACT: Our results inform on mechanisms underlying environmental exposures in lung cancer etiology; future studies should prioritize studying joint exposures.

Genotoxic effect of meat consumption: A mini review.

In 2015, the International Agency for Research on Cancer classified the consumption of processed meat as carcinogenic to humans (Group 1) and red meat as probably carcinogenic to humans (Group 2A) based on sufficient data from animal models and epidemiological studies. However, research characterising the mechanisms underlying this carcinogenic process in humans are limited, particularly with respect to measures of direct DNA damage. The current review sought to evaluate and summarize the recent literature, published since 2000, regarding the associations of meat consumption and three biomarkers of genotoxicity in humans: DNA strand breaks (measured using the comet assay), DNA adducts, and micronucleus formation. After screening 230 potential articles, 35 were included, and then were classified as experimental or observational in design, the latter of which were further categorized according to their dietary assessment approach. Among the 30 observational studies, 4 of which used two different assays, 3 of 5 comet assay studies, 13 of 20 DNA adduct studies, and 7 of 9 micronucleus studies reported a positive association between meat consumption and DNA damage. Among the 5 experimental studies, 1 of 1 using the comet assay, 3 of 3 measuring DNA adducts and 0 of 1 measuring micronuclei reported significant positive associations with meat consumption. Nevertheless, common limitations among the selected publications included small sample size, and poor methodological reporting of both exposure and outcome measures. Moreover, the vast majority of studies only measured DNA damage in one biological sample using a single assay and we cannot exclude the possibility of publication bias. Ultimately, our review of the literature, published since 2000, revealed a preponderance of studies that support mechanisms of genotoxicity in playing an important role in the meat-cancer association.

Associations of sleep duration, sedentary behaviours and energy expenditure with maternal glycemia in pregnancy.

BACKGROUND: Women with high levels of physical activity (PA) are less likely to develop gestational diabetes mellitus (GDM), but the relations with sleep and sedentary behaviours (SB) are more controversial. We aimed to investigate all three components (sleep, PA, and SB) and their association with maternal glucose in pregnancy. METHODS: We included 766 pregnant women recruited at first trimester and that we followed at second trimester. We collected blood samples, anthropometry and standardized questionnaires about lifestyle including PA, SB, and sleep duration at both visits. Women completed a 50 g glucose challenge test at first trimester and 75-g oral glucose tolerance test (OGTT) at second trimester. We conducted regression analyses to test cross-sectional associations between sleep, PA, and SB with maternal glucose levels while taking into account potential confounders (maternal age, pre-pregnancy body mass index (BMI), gravidity, and smoking). We considered linear and quadratic relationships. RESULTS: At first trimester, we observed a linear relationship between shorter sleep duration and higher glucose levels, which was attenuated after adjustments for confounders. At second trimester, we found a quadratic relationship between sleep and glucose showing lowest levels at fasting and 1 h-post OGTT for women who slept 6-10 h/night. This association remained significant after adjusting for confounders and taking into account PA and/or SB. Greater amount of SB was associated with higher 1 h-glucose after adjustment for confounders (ß = 0.132; SE = 0.047; P = 0.005). CONCLUSIONS: Sleep duration is associated with glucose regulation in pregnancy, independently of PA and SB, and this association varies according to the period of gestation.