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Genome-wide association studies (GWAS) have identified more than 40 T1D loci associated with type 1 diabetes (T1D). How these polymorphisms interact with environmental factors to trigger T1D is unknown, but recent evidence suggests that epigenetic mechanisms could play a role. To begin to explore the contribution of epigenetics to T1D, we have examined DNA methylation in a pilot study of whole blood cells DNA from 10 young T1D patients and 10 young controls. Through the study of >900 000 CG loci across a diverse set of functionally relevant genomic regions using a custom DNA methylation array, we identified 250 T1D-differentially methylated region (DMR) at p < 0.05 and 1 DMR using next a permutation-based multiple testing correction method. This DMR is located in an imprinted region previously associated with T1D on the chromosome 14 that encompasses RTL1 gene and 2 miRNAs (miR136 and miR432). Using pyrosequencing-based bisulfite PCR, we replicated this association in a different and larger set of T1D patients and controls. DNA methylation at this DMR was inversely correlated with RTL1 gene expression and positively correlated with miR136 expression in human placentas. The DMR identified in this study presents suggestive evidence for altered methylation site in T1D and provide a promising new candidate gene. RTL1 is essential for placental permeability function in the mid-to-late fetal stages. We suggest that hypo-methylation could increase the fetal exposure to environmental factors in T1D susceptibility. [ABSTRACT FROM AUTHOR]

The insulin (INS) region is the second most important locus associated with Type 1 Diabetes (T1D). The study of the DNA methylation pattern of the 7 CpGs proximal to the TSS in the INS gene promoter revealed that T1D patients have a lower level of methylation of CpG -19, -135 and -234 (p = 2.10-16) and a higher methylation of CpG -180 than controls, while methylation was comparable for CpG -69, -102, -206. The magnitude of the hypomethylation relative to a control population was 8-15% of the corresponding levels in controls and was correlated in CpGs -19 and -135 (r = 0.77) and CpG - 135 and -234 (r = 0.65). 70/485 (14%) of T1D patients had a simultaneous decrease in methylation of CpG -19, -135, -234 versus none in 317 controls. CpG methylation did not correlate with glycated hemoglobin or with T1D duration. The methylation of CpG -69, -102, -180, -206, but not CpG -19, -135, -234 was strongly influenced by the cis-genotype at rs689, a SNP known to show a strong association with T1D. We hypothesize that part of this genetic association could in fact be mediated at the statistical and functional level by the underlying changes in neighboring CpG methylation. Our observation of a CpG-specific, locus-specific methylation pattern, although it can provide an epigenetic biomarker of a multifactorial disease, does not indicate whether the reported epigenetic pattern preexists or follows the establishment of T1D. To explore the effect of chronic hyperglycemia on CpG methylation, we studied non obese patients with type 2 diabetes (T2D) who were found to have decreased CpG-19 methylation versus age-matched controls, similar to T1D (p = 2.10-6) but increased CpG-234 methylation (p = 5.10-8), the opposite of T1D. The causality and natural history of the different epigenetic changes associated with T1D or T2D remain to be determined. [ABSTRACT FROM AUTHOR]

Epidemiologic study designs represent a major challenge for genome-wide association studies. Most such studies to date have selected controls from the pool of participants without the disease of interest at the end of the study time. These choices can lead to biased estimates of exposure effects. Using data from the Framingham Heart Study (Genetic Analysis Workshop 16 Problem 2), we evaluate the impact on genetic association estimates for designs with control selection based on status at the end of a study (case exclusion (CE) sampling) to control selection based on incidence density (ID) sampling, when controls are selected from the pool of participants who are disease-free at the time a case is diagnosed. Cases are defined as those diagnosed with type 2 diabetes (T2D). We estimated odds ratios for 18 previously confirmed T2D variants using 189 cases selected by ID sampling and using 231 cases selected by CE sampling. We found none of these single-nucleotide polymorphisms to be significantly associated with T2D using either design. Because these empirical analyses were based on a small number of cases and on single-nucleotide polymorphisms with likely small effect sizes, we supplemented this work with simulated data sets of 500 cases from each strategies across a variety of allele frequencies and effect sizes. In our simulated datasets, we show ID sampling to be less biased than CE, although CE shows apparent increased power due to the upward bias of point estimates. We conclude that ID sampling is an appropriate option for genome-wide association studies. [ABSTRACT FROM AUTHOR]

Long before reaching diagnostic cutoff levels for type 2 diabetes, fasting glucose can be a powerful risk marker for this disease. We conducted a genome-wide search for fasting glucose as a quantitative trait in 412 young European sib-pairs including obese children, with adjustment for sex, age, and BMI. We identified more quantitative trait loci specific to fasting glucose and more significant than would be found by simple chance estimated by permutation tests. The strongest linkage was on chromosome 2q (logarithm of odds [LOD] = 3.00) in a region previously linked to type 2 diabetes as a disease. We also found linkage signals of fasting glucose with 7q (LOD = 2.03), 8q (1.28), 17p (2.12), 17q (1.4), and 11p (1.33). These findings suggest that the quantitative genetics of fasting glucose could contribute to the search for type 2 diabetes genes. Diabetes 56:1742-1745, 2007 [ABSTRACT FROM AUTHOR]

Over recent decades, it has become clear that epigenetic abnormalities are involved in the hallmarks of cancer. Histone modifications, such as acetylation, play a crucial role in cancer development and progression, by regulating gene expression, such as for oncogenes or tumor suppressor genes. Therefore, histone deacetylase inhibitors (HDACi) have recently shown efficacy against both hematological and solid cancers. Designed to target histone deacetylases (HDAC), these drugs can modify the expression pattern of numerous genes including those coding for micro-RNAs (miRNA). miRNAs are small non-coding RNAs that regulate gene expression by targeting messenger RNA. Current research has found that miRNAs from a tumor can be investigated in the tumor itself, as well as in patient body fluids. In this review, we summarized current knowledge about HDAC and HDACi in several cancers, and described their impact on miRNA expression. We discuss briefly how circulating miRNAs may be used as biomarkers of HDACi response and used to investigate response to treatment. [ABSTRACT FROM AUTHOR]