Background: DNA methylation is an important type of epigenetic modification involved in gene regulation. Although strong DNA methylation at promoters is widely recognized to be associated with transcriptional repression, many aspects of DNA methylation remain not fully understood, including the quantitative relationships between DNA methylation and expression levels, and the individual roles of promoter and gene body methylation. Results: Here we present an integrated analysis of whole-genome bisulfite sequencing and RNA sequencing data from human samples and cell lines. We find that while promoter methylation inversely correlates with gene expression as generally observed, the repressive effect is clear only on genes with a very high DNA methylation level. By means of statistical modeling, we find that DNA methylation is indicative of the expression class of a gene in general, but gene body methylation is a better indicator than promoter methylation. These findings are general in that a model constructed from a sample or cell line could accurately fit the unseen data from another. We further find that promoter and gene body methylation have minimal redundancy, and either one is sufficient to signify low expression. Finally, we obtain increased modeling power by integrating histone modification data with the DNA methylation data, showing that neither type of information fully subsumes the other. Conclusion: Our results suggest that DNA methylation outside promoters also plays critical roles in gene regulation. Future studies on gene regulatory mechanisms and disease-associated differential methylation should pay more attention to DNA methylation at gene bodies and other non-promoter regions.

BackgroundDNA methylation is an important type of epigenetic modification involved in gene regulation. Although strong DNA methylation at promoters is widely recognized to be associated with transcriptional repression, many aspects of DNA methylation remain not fully understood, including the quantitative relationships between DNA methylation and expression levels, and the individual roles of promoter and gene body methylation.ResultsHere we present an integrated analysis of whole-genome bisulfite sequencing and RNA sequencing data from human samples and cell lines. We find that while promoter methylation inversely correlates with gene expression as generally observed, the repressive effect is clear only on genes with a very high DNA methylation level. By means of statistical modeling, we find that DNA methylation is indicative of the expression class of a gene in general, but gene body methylation is a better indicator than promoter methylation. These findings are general in that a model constructed from a sample or cell line could accurately fit the unseen data from another. We further find that promoter and gene body methylation have minimal redundancy, and either one is sufficient to signify low expression. Finally, we obtain increased modeling power by integrating histone modification data with the DNA methylation data, showing that neither type of information fully subsumes the other.ConclusionOur results suggest that DNA methylation outside promoters also plays critical roles in gene regulation. Future studies on gene regulatory mechanisms and disease-associated differential methylation should pay more attention to DNA methylation at gene bodies and other non-promoter regions.Electronic supplementary materialThe online version of this article (doi:10.1186/s13059-014-0408-0) contains supplementary material, which is available to authorized users.

BackgroundHyperglycemia is associated with increased risk of all-site cancer that may be mediated through activation of the renin-angiotensin-system (RAS) and 3-hydroxy-3-methyl-glutaryl-coenzyme-A-reductase (HMGCR) pathways. We examined the joint associations of optimal glycemic control (HbA1c <7%), RAS inhibitors and HMGCR inhibitors on cancer incidence in patients with type 2 diabetes.MethodsPatients with type 2 diabetes, with or without a history of cancer or prior exposure to RAS or HMGCR inhibitors at baseline were observed between 1996 and 2005. All patients underwent a comprehensive assessment at baseline and were followed until the censored date at 2005 or their death.ResultsAfter a median follow-up period of 4.91 years (interquartile range, 2.81 to 6.98), 271 out of 6,103 patients developed all-site cancer. At baseline, patients with incident cancers were older, had longer disease duration of diabetes, higher alcohol and tobacco use, and higher systolic blood pressure and albuminuria, but lower triglyceride levels and estimated glomerular filtration rate (P <0.05). Patients who developed cancers during follow-up were less likely to have started using statins (22.5% versus 38.6%, P <0.001), fibrates (5.9% versus 10.2%, P = 0.02), metformin (63.8% versus 74.5%, P <0.001) or thiazolidinedione (0.7% versus 6.8%, P <0.001) than those who remained cancer-free. After adjusting for co-variables, new treatment with metformin (hazard ratio: 0.39; 95% confidence interval: 0.25, 0.61; P <0.001), thiazolidinedione (0.18; 0.04, 0.72; P = 0.015), sulphonylurea (0.44; 0.27, 0.73; P = 0.014), insulin (0.58; 0.38, 0.89; P = 0.01), statins (0.47; 0.31, 0.70; P <0.001) and RAS inhibitors (0.55; 0.39, 0.78; P <0.001) were associated with reduced cancer risk. Patients with all three risk factors of HbA1c ≥7%, non-use of RAS inhibitors and non-use of statins had four-fold adjusted higher risk of cancer than those without any risk factors (incidence per 1,000-person-years for no risk factors: 3.40 (0.07, 6.72); one risk factor: 6.34 (4.19, 8.50); two risk factors: 8.40 (6.60, 10.20); three risk factors: 13.08 (9.82, 16.34); P <0.001).ConclusionsHyperglycemia may promote cancer growth that can be attenuated by optimal glycemic control and inhibition of the RAS and HMGCR pathways.

Aim Levels of branched‐chain amino acids (BCAAs, namely, isoleucine, leucine, and valine) are modulated by dietary intake and metabolic/genetic factors. BCAAs are associated with insulin resistance and increased risk of type 2 diabetes (T2D). Although insulin resistance predicts heart failure (HF), the relationship between BCAAs and HF in T2D remains unknown. Methods In this prospective observational study, we measured BCAAs in fasting serum samples collected at inception from 2139 T2D patients free of cardiovascular‐renal diseases. The study outcome was the first hospitalization for HF. Results During 29 103 person‐years of follow‐up, 115 primary events occurred (age: 54.8 ± 11.2 years, 48.2% men, median [interquartile range] diabetes duration: 5 years [1‐10]). Patients with incident HF had 5.6% higher serum BCAAs than those without HF (median 639.3 [561.3‐756.3] vs 605.2 [524.8‐708.7] μmol/L; P = .01). Serum BCAAs had a positive linear association with incident HF (per‐SD increase in logarithmically transformed BCAAs: hazard ratio [HR] 1.22 [95% CI 1.07‐1.39]), adjusting for age, sex, and diabetes duration. The HR remained significant after sequential adjustment of risk factors including incident coronary heart disease (1.24, 1.09‐1.41); blood pressure, low‐density lipoprotein cholesterol, and baseline use of related medications (1.31, 1.14‐1.50); HbA1c, waist circumference, triglyceride, and baseline use of related medications (1.28, 1.11‐1.48); albuminuria and estimated glomerular filtration rate (1.28, 1.11‐1.48). The competing risk of death analyses showed similar results. Conclusions Circulating levels of BCAAs are independently associated with incident HF in patients with T2D. Prospective cohort analysis and randomized trials are needed to evaluate the long‐term safety and efficacy of using different interventions to optimize BCAAs levels in these patients.