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      The Relationship of DNA Methylation with Age, Gender and Genotype in Twins and Healthy Controls

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          Abstract

          Cytosine-5 methylation within CpG dinucleotides is a potentially important mechanism of epigenetic influence on human traits and disease. In addition to influences of age and gender, genetic control of DNA methylation levels has recently been described. We used whole blood genomic DNA in a twin set (23 MZ twin-pairs and 23 DZ twin-pairs, N = 92) as well as healthy controls (N = 96) to investigate heritability and relationship with age and gender of selected DNA methylation profiles using readily commercially available GoldenGate bead array technology. Despite the inability to detect meaningful methylation differences in the majority of CpG loci due to tissue type and locus selection issues, we found replicable significant associations of DNA methylation with age and gender. We identified associations of genetically heritable single nucleotide polymorphisms with large differences in DNA methylation levels near the polymorphism ( cis effects) as well as associations with much smaller differences in DNA methylation levels elsewhere in the human genome ( trans effects). Our results demonstrate the feasibility of array-based approaches in studies of DNA methylation and highlight the vast differences between individual loci. The identification of CpG loci of which DNA methylation levels are under genetic control or are related to age or gender will facilitate further studies into the role of DNA methylation and disease.

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          Most cited references34

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          A note on exact tests of Hardy-Weinberg equilibrium.

          Deviations from Hardy-Weinberg equilibrium (HWE) can indicate inbreeding, population stratification, and even problems in genotyping. In samples of affected individuals, these deviations can also provide evidence for association. Tests of HWE are commonly performed using a simple chi2 goodness-of-fit test. We show that this chi2 test can have inflated type I error rates, even in relatively large samples (e.g., samples of 1,000 individuals that include approximately 100 copies of the minor allele). On the basis of previous work, we describe exact tests of HWE together with efficient computational methods for their implementation. Our methods adequately control type I error in large and small samples and are computationally efficient. They have been implemented in freely available code that will be useful for quality assessment of genotype data and for the detection of genetic association or population stratification in very large data sets.
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            High-throughput DNA methylation profiling using universal bead arrays.

            We have developed a high-throughput method for analyzing the methylation status of hundreds of preselected genes simultaneously and have applied it to the discovery of methylation signatures that distinguish normal from cancer tissue samples. Through an adaptation of the GoldenGate genotyping assay implemented on a BeadArray platform, the methylation state of 1536 specific CpG sites in 371 genes (one to nine CpG sites per gene) was measured in a single reaction by multiplexed genotyping of 200 ng of bisulfite-treated genomic DNA. The assay was used to obtain a quantitative measure of the methylation level at each CpG site. After validating the assay in cell lines and normal tissues, we analyzed a panel of lung cancer biopsy samples (N = 22) and identified a panel of methylation markers that distinguished lung adenocarcinomas from normal lung tissues with high specificity. These markers were validated in a second sample set (N = 24). These results demonstrate the effectiveness of the method for reliably profiling many CpG sites in parallel for the discovery of informative methylation markers. The technology should prove useful for DNA methylation analyses in large populations, with potential application to the classification and diagnosis of a broad range of cancers and other diseases.
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              Maternal care effects on the hippocampal transcriptome and anxiety-mediated behaviors in the offspring that are reversible in adulthood.

              Early-life experience has long-term consequences on behavior and stress responsivity of the adult. We previously proposed that early-life experience results in stable epigenetic programming of glucocorticoid receptor gene expression in the hippocampus. The aim of this study was to examine the global effect of early-life experience on the hippocampal transcriptome and the development of stress-mediated behaviors in the offspring and whether such effects were reversible in adulthood. Adult offspring were centrally infused with saline vehicle, the histone deacetylase inhibitor trichostatin A (TSA), or the essential amino acid l-methionine. The animals were assessed in an unfamiliar open-field arena, and the hippocampal transcriptome of each animal was evaluated by microarray analysis. Here we report that TSA and methionine treatment reversed the effect of maternal care on open-field behavior. We identified >900 genes stably regulated by maternal care. A fraction of these differences in gene expression is reversible by either the histone deacetylase inhibitor TSA or the methyl donor l-methionine. These results suggest that early-life experience has a stable and broad effect on the hippocampal transcriptome and anxiety-mediated behavior, which is potentially reversible in adulthood.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2009
                26 August 2009
                : 4
                : 8
                : e6767
                Affiliations
                [1 ]Rudolf Magnus Institute of Neuroscience, Department of Psychiatry, University Medical Center Utrecht, Utrecht, The Netherlands
                [2 ]Julius Centre for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands
                [3 ]USC Epigenome Center and USC Norris Comprehensive Cancer Center Keck School of Medicine, University of Southern California Los Angeles, Los Angeles, California, United States of America
                [4 ]Department of Medical Genetics, University Medical Center Utrecht, Utrecht, The Netherlands
                [5 ]UCLA Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, Los Angeles, California, United States of America
                City of Hope Medical Center, United States of America
                Author notes

                Conceived and designed the experiments: MPB DJW RSK RAO. Performed the experiments: ES EJ. Analyzed the data: MPB. Contributed reagents/materials/analysis tools: MPB EMD RAO. Wrote the paper: MPB EMD DJW IES RSK RAO.

                Article
                09-PONE-RA-09156R2
                10.1371/journal.pone.0006767
                2747671
                19774229
                cb92c8b0-6e1c-45d2-85dc-dcbf02dee4c9
                Boks et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
                History
                : 11 March 2009
                : 10 July 2009
                Page count
                Pages: 8
                Categories
                Research Article
                Computational Biology/Genomics
                Developmental Biology/Aging
                Developmental Biology/Developmental Molecular Mechanisms
                Genetics and Genomics/Epigenetics
                Genetics and Genomics/Genomics
                Molecular Biology/DNA Methylation

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