The therapeutic management of obesity is challenging, hence further elucidating the underlying mechanisms of obesity development and identifying new diagnostic biomarkers and therapeutic targets are urgent and necessary. Here, we performed differential gene expression analysis and weighted gene co-expression network analysis (WGCNA) to identify significant genes and specific modules related to BMI based on gene expression profile data of 7 discordant monozygotic twins. In the differential gene expression analysis, it appeared that 32 differentially expressed genes (DEGs) were with a trend of up-regulation in twins with higher BMI when compared to their siblings. Categories of positive regulation of nitric-oxide synthase biosynthetic process, positive regulation of NF-kappa B import into nucleus, and peroxidase activity were significantly enriched within GO database and NF-kappa B signaling pathway within KEGG database. DEGs of NAMPT, TLR9, PTGS2, HBD, and PCSK1N might be associated with obesity. In the WGCNA, among the total 20 distinct co-expression modules identified, coral1 module (68 genes) had the strongest positive correlation with BMI (r = 0.56, P = 0.04) and disease status (r = 0.56, P = 0.04). Categories of positive regulation of phospholipase activity, high-density lipoprotein particle clearance, chylomicron remnant clearance, reverse cholesterol transport, intermediate-density lipoprotein particle, chylomicron, low-density lipoprotein particle, very-low-density lipoprotein particle, voltage-gated potassium channel complex, cholesterol transporter activity, and neuropeptide hormone activity were significantly enriched within GO database for this module. And alcoholism and cell adhesion molecules pathways were significantly enriched within KEGG database. Several hub genes, such as GAL, ASB9, NPPB, TBX2, IL17C, APOE, ABCG4, and APOC2 were also identified. The module eigengene of saddlebrown module (212 genes) was also significantly correlated with BMI (r = 0.56, P = 0.04), and hub genes of KCNN1 and AQP10 were differentially expressed. We identified significant genes and specific modules potentially related to BMI based on the gene expression profile data of monozygotic twins. The findings may help further elucidate the underlying mechanisms of obesity development and provide novel insights to research potential gene biomarkers and signaling pathways for obesity treatment. Further analysis and validation of the findings reported here are important and necessary when more sample size is acquired.

Objective: We conducted a meta-analysis to evaluate the relationship between vitamin E and age-related cataract (ARC).Design: The fixed- or random-effect model was selected based on heterogeneity. Meta-regression was used to explore potential sources of between-study heterogeneity. Publication bias was evaluated using Begg’s test. The dose–response relationship was assessed by a restricted cubic spline model.Setting: Relevant studies were identified by a search of PubMed and the Cochrane Library to May 2014, without language restrictions.Subjects: Studies involved samples of people of all ages.Results: Dietary vitamin E intake, dietary and supplemental vitamin E intake, and high serum tocopherol levels were significantly associated with decreased risk of ARC, the pooled relative risk was 0·73 (95 % CI 0·58, 0·92), 0·86 (95 % CI 0·75, 0·99) and 0·77 (95 % CI 0·66, 0·91), respectively. Supplemental vitamin E intake was non-significantly associated with ARC risk (relative risk=0·92; 95 % CI 0·78, 1·07). The findings from dose–response analysis showed evidence of a non-linear association between dietary vitamin E intake and ARC. The risk of ARC decreased with dietary vitamin E intake from 7 mg/d (relative risk=0·94; 95 % CI 0·90, 0·97).Conclusions: The findings of the meta-analysis indicated that dietary vitamin E intake, dietary and supplemental vitamin E intake, and high level of serum tocopherol might be significantly associated with reduced ARC risk.