10 research outputs found

    Tobacco smoking is associated with DNA methylation of diabetes susceptibility genes.

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    AIMS/HYPOTHESIS: Tobacco smoking, a risk factor for diabetes, is an established modifier of DNA methylation. We hypothesised that tobacco smoking modifies DNA methylation of genes previously identified for diabetes. METHODS: We annotated CpG sites available on the Illumina Human Methylation 450K array to diabetes genes previously identified by genome-wide association studies (GWAS), and investigated them for an association with smoking by comparing current to never smokers. The discovery study consisted of 630 individuals (Bonferroni-corrected p = 1.4 × 10(-5)), and we sought replication in an independent sample of 674 individuals. The replicated sites were tested for association with nearby genetic variants and gene expression and fasting glucose and insulin levels. RESULTS: We annotated 3,620 CpG sites to the genes identified in the GWAS on type 2 diabetes. Comparing current smokers to never smokers, we found 12 differentially methylated CpG sites, of which five replicated: cg23161492 within ANPEP (p = 1.3 × 10(-12)); cg26963277 (p = 1.2 × 10(-9)), cg01744331 (p = 8.0 × 10(-6)) and cg16556677 (p = 1.2 × 10(-5)) within KCNQ1 and cg03450842 (p = 3.1 × 10(-8)) within ZMIZ1. The effect of smoking on DNA methylation at the replicated CpG sites attenuated after smoking cessation. Increased DNA methylation at cg23161492 was associated with decreased gene expression levels of ANPEP (p = 8.9 × 10(-5)). rs231356-T, which was associated with hypomethylation of cg26963277 (KCNQ1), was associated with a higher odds of diabetes (OR 1.06, p = 1.3 × 10(-5)). Additionally, hypomethylation of cg26963277 was associated with lower fasting insulin levels (p = 0.04). CONCLUSIONS/INTERPRETATION: Tobacco smoking is associated with differential DNA methylation of the diabetes risk genes ANPEP, KCNQ1 and ZMIZ1. Our study highlights potential biological mechanisms connecting tobacco smoking to excess risk of type 2 diabetes

    The Rotterdam Study: 2016 objectives and design update

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    A systematic analysis highlights multiple long non-coding RNAs associated with cardiometabolic disorders

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    Genome-wide association studies (GWAS) have identified many susceptibility loci for cardiometabolic disorders. Most of the associated variants reside in non-coding regions of the genome including long non-coding RNAs (lncRNAs), which are thought to play critical roles in diverse biological processes. Here, we leveraged data from the available GWAS meta-analyses on lipid and obesity-related traits, blood pressure, type 2 diabetes, and coronary artery disease and identified 179 associated single-nucleotide polymorphisms (SNPs) in 102 lncRNAs (p-value < 2.3 × 10-7). Of these, 55 SNPs, either the lead SNP or in strong linkage disequilibrium with the lead SNP in the related loci, were selected for further investigations. Our in silico predictions and functional annotations of the SNPs as well as expression and DNA methylation analysis of their lncRNAs demonstrated several lncRNAs that fulfilled predefined criteria for being potential functional targets. In particular, we found evidence suggesting that LOC157273 (at 8p23.1) is involved in regulating serum lipid-cholesterol. Our results showed that rs4841132 in the second exon and cg17371580 in the promoter region of LOC157273 are associated with lipids; the lncRNA is expressed in liver and associates with the expression of its nearby coding gene, PPP1R3B. Collectively, we highlight a number of loci associated with cardiometabolic disorders for which the association may act through lncRNAs

    From forensic epigenetics to forensic epigenomics: broadening DNA investigative intelligence

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