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AIM:To investigate whether nicotinamide overload plays a role in type 2 diabetes. METHODS:Nicotinamide metabolic patterns of 14 diabetic and 14 non-diabetic subjects were compared using HPLC. Cumulative effects of nicotinamide and N 1 -methylnicotinamide on glucose metabolism, plasma H2O2 levels and tissue nicotinamide adenine dinucleotide (NAD) contents of adult Sprague-Dawley rats were observed. The role of human sweat glands and rat skin in nicotinamide metabolism was investigated using sauna and burn injury, respectively. RESULTS:Diabetic subjects had significantly higher plasma N 1 -methylnicotinamide levels 5 h after a 100-mg nicotinamide load than the non-diabetic subjects (0.89 ± 0.13 μmol/L vs 0.6 ± 0.13 μmol/L, P < 0.001). Cumulative doses of nicotinamide (2 g/kg) significantly increased rat plasma N 1 -methylnicotinamide concentrations associated with severe insulin resistance, which was mimicked by N 1 -methylnicotinamide. Moreover, cumulative exposure to N 1 -methylnicotinamide (2 g/kg) markedly reduced rat muscle and liver NAD contents and erythrocyte NAD/ NADH ratio, and increased plasma H2O2 levels. Decrease in NAD/NADH ratio and increase in H2O2 generation were also observed in human erythrocytes after exposure to N 1 -methylnicotinamide in vitro . Sweating eliminated excessive nicotinamide (5.3-fold increase in sweat nicotinamide concentration 1 h after a 100-mg nicotinamide load). Skin damage or aldehyde oxidase inhibition with tamoxifen or olanzapine, both being notorious for impairing glucose tolerance, delayed N 1 -methylnicotinamide clearance. CONCLUSION:These findings suggest that nicotinamide overload, which induced an increase in plasma N 1 -methylnicotinamide, associated with oxidative stress and insulin resistance, plays a role in type 2 diabetes.

The appetite-stimulating effect of nicotinamide appears to involve oxidative stress. Excess niacin consumption may be a major factor in the increased obesity prevalence in US children.

The early diagnosis and accurate prognosis prediction of esophageal cancer is an essential part of improving survival. However, these diseases lack effective and specific markers. A total of 1,744 samples of HumanMethylation450 data were integrated to identify and validate specific methylation markers for esophageal adenocarcinoma (EAC) and esophageal squamous cell carcinoma (ESCC) as well as for Barrett’s esophagus (BE) using The Cancer Genome Atlas and the Gene Expression Omnibus. The diagnostic and prognostic methylation classifiers were constructed by moderated t-statistics and the least absolute shrinkage and selection operator method. The diagnostic methylation classifier using 12 CpG sites was constructed in training set (377 samples) that could effectively discriminate samples of BE, EAC, and ESCC from normal tissue (AUC = 0.992), which achieved highly predictive ability in both internal (187 samples, AUC = 0.990) and external validation (184 samples, AUC = 0.978). The prognostic methylation classifier with 3 CpG and 2 CpG sites for EAC and ESCC respectively, could accurately estimate the prognosis of an individual patient and improved the predictive ability of the tumor node metastasis staging system. Overall, our study systematically analyzed large-scale methylation data and provided promising markers for the diagnosis and prognosis of esophageal cancer.