A DNA methylation biomarker of alcohol consumption.

The lack of reliable measures of alcohol intake is a major obstacle to the diagnosis and treatment of alcohol-related diseases. Epigenetic modifications such as DNA methylation may provide novel biomarkers of alcohol use. To examine this possibility, we performed an epigenome-wide association study of methylation of cytosine-phosphate-guanine dinucleotide (CpG) sites in relation to alcohol intake in 13 population-based cohorts (ntotal=13 317; 54% women; mean age across cohorts 42-76 years) using whole blood (9643 European and 2423 African ancestries) or monocyte-derived DNA (588 European, 263 African and 400 Hispanic ancestry) samples. We performed meta-analysis and variable selection in whole-blood samples of people of European ancestry (n=6926) and identified 144 CpGs that provided substantial discrimination (area under the curve=0.90-0.99) for current heavy alcohol intake (⩾42 g per day in men and ⩾28 g per day in women) in four replication cohorts. The ancestry-stratified meta-analysis in whole blood identified 328 (9643 European ancestry samples) and 165 (2423 African ancestry samples) alcohol-related CpGs at Bonferroni-adjusted P<1 × 10-7. Analysis of the monocyte-derived DNA (n=1251) identified 62 alcohol-related CpGs at P<1 × 10-7. In whole-blood samples of people of European ancestry, we detected differential methylation in two neurotransmitter receptor genes, the γ-Aminobutyric acid-A receptor delta and γ-aminobutyric acid B receptor subunit 1; their differential methylation was associated with expression levels of a number of genes involved in immune function. In conclusion, we have identified a robust alcohol-related DNA methylation signature and shown the potential utility of DNA methylation as a clinically useful diagnostic test to detect current heavy alcohol consumption.

Modification of genetic influences on adiposity between 36 and 63 years of age by physical activity and smoking in the 1946 British Birth Cohort Study.

BACKGROUND: Previous studies reporting on the interaction between physical activity and genetic susceptibility on obesity have been cross-sectional and have not considered the potential influences of other lifestyle behaviours. The aim of this study was to examine modification of genetic influences on changes across age in adiposity during mid-adulthood by physical activity and smoking. METHODS: The sample comprised 2444 participants who were genotyped for 11 obesity variants and had body mass index (BMI), waist circumference-to-height ratio (WHtR), physical activity and smoking measures at 36, 43, 53 and 60-64 years of age. A genetic risk score (GRS) comprising the sum of risk alleles was computed. Structural equation models investigated modification of the longitudinal GRS associations by physical activity (active versus inactive) and smoking (non-smoker versus smoker), using a latent linear spline to summarise BMI or WHtR (multiplied by 100) at the age of 36 years and their subsequent rates of change over age. RESULTS: Physical activity at the age of 36 years attenuated the GRS associations with BMI and WHtR at the same age (P-interaction 0.009 and 0.004, respectively). Further, physical activity at the age of 53 years attenuated the GRS association with rate of change in BMI between 53 and 63 years of age (by 0.012 kg m(-2) per year (95% confidence interval (CI): 0.001, 0.024), P-interaction 0.004). Conversely, smoking at the age of 43 years showed a trend towards augmenting the GRS association with rate of change in WHtR between 43 and 63 years of age (by 0.012 (95% CI: 0.001, 0.026), P-interaction 0.07). Estimated GRS effect sizes were lowest at all ages in the healthiest group (e.g., active non-smokers). CONCLUSIONS: Healthy lifestyle behaviours appeared to attenuate the genetic influence on changes across age in BMI and central adiposity during mid-adulthood. An active lifestyle and not smoking may have additive effects on reducing the genetic susceptibility to obesity in adults.

Association between childhood obesity and subsequent Type 1 diabetes: a systematic review and meta-analysis.

AIMS: To review and synthesize the published evidence on the possible association between childhood obesity and the subsequent risk of Type 1 diabetes. METHODS: The PubMed database was systematically searched for studies using childhood obesity, BMI or %weight-for-height as the exposure variable and subsequent Type 1 diabetes as the outcome. Studies were only included if assessment of obesity preceded the diagnosis of Type 1 diabetes. RESULTS: Eight case-control studies and one cohort study were included, comprising a total of 2658 cases. Of these nine studies, seven reported a significant association between childhood obesity, BMI or %weight-for-height and increased risk for Type 1 diabetes. Meta-analysis of the four studies that reported childhood obesity as a categorical exposure produced a pooled odds ratio of 2.03 (95% CI 1.46-2.80) for subsequent Type 1 diabetes; however, in those studies, age at obesity assessment varied from age 1 to 12 years. A dose-response relationship was supported by a continuous association between childhood BMI and subsequent Type 1 diabetes in a meta-analysis of five studies (pooled odds ratio 1.25 (95%CI 1.04-1.51) per 1 sd higher BMI). CONCLUSION: There is overall evidence for an association between childhood obesity, or higher BMI, and increased risk of subsequent Type 1 diabetes. Several theories have been proposed for a causal relationship. Reduction in Type 1 diabetes should be considered as a potential additional benefit of preventing childhood obesity.