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Pluripotent cells appear to be in a transient state during early development. These cells have the capability to transition into embryonic stem cells (ESCs). It has been reported that mouse pluripotent cells cultivated in chemically defined media sustain the ground state of pluripotency. Because the epigenetic pattern of pluripotent cells reflects their environment, culture under different conditions causes epigenetic changes, which could lead to genomic instability. This study focused on the DNA methylation pattern of repetitive elements (REs) and their activation levels under two ground-state conditions and assessed the genomic integrity of ESCs. We measured the methylation and expression level of REs in different media. The results indicated that although the ground-state conditions show higher REs activity, they did not lead to DNA damage; therefore, the level of genomic instability is lower under the ground-state compared with the conventional condition. Our results indicated that when choosing an optimum condition, different features of the condition must be considered to have epigenetically and genomically stable stem cells., (© 2018 Wiley Periodicals, Inc.)

DNA methylation is an epigenetic regulator of gene transcription, which has been found to be both metastable and variable within human cohort studies. Currently, few studies have been done to identify metastable DNA methylation biomarkers associated with longitudinal lung function decline in humans. The identification of such biomarkers is important for screening vulnerable populations. We hypothesized that quantifiable blood-based DNA methylation alterations would serve as metastable biomarkers of lung function decline and aging, which may help to discover new pathways and/or mechanisms related to pulmonary pathogenesis. Using linear mixed models, we performed an Epigenome Wide Association Study (EWAS) between DNA methylation at CpG dinucleotides and longitudinal lung function (FVC, FEV 1 , FEF 25-75% ) decline and aging with initial discovery in the Normative Aging Study, and replication in the Cooperative Health Research in the Region of Augsburg cohort. We identified two metastable epigenetic loci associated with either poor lung function and aging, cg05575921 (AHRR gene), or lung function independently of aging, cg06126421 (IER3 gene). These loci may inform basic mechanisms associated with pulmonary function, pathogenesis, and aging. Human epigenomic variation, may help explain features of lung function decline and related pathophysiology not attributable to DNA sequence alone, such as accelerated pulmonary decline in smokers, former smokers, and perhaps non-smokers. Our EWAS across two cohorts, therefore, will likely have implications for the human population, not just the elderly.

DNA methylation (DNAm) has been found to show robust and widespread age-related changes across the genome. DNAm profiles from whole blood can be used to predict human aging rates with great accuracy. We sought to test whether DNAm-based predictions of age are related to phenotypes associated with type 2 diabetes (T2D), with the goal of identifying risk factors potentially mediated by DNAm. Our participants were 43 women enrolled in the Women's Health Initiative. We obtained methylation data via the Illumina 450K Methylation array on whole blood samples from participants at three timepoints, covering on average 16 years per participant. We employed the method and software of Horvath, which uses DNAm at 353 CpGs to form a DNAm-based estimate of chronological age. We then calculated the epigenetic age acceleration, or Δ age , at each timepoint. We fit linear mixed models to characterize how Δ age contributed to a longitudinal model of aging and diabetes-related phenotypes and risk factors. For most participants, Δ age remained constant, indicating that age acceleration is generally stable over time. We found that Δ age associated with body mass index (p = 0.0012), waist circumference (p = 0.033), and fasting glucose (p = 0.0073), with the relationship with BMI maintaining significance after correction for multiple testing. Replication in a larger cohort of 157 WHI participants spanning 3 years was unsuccessful, possibly due to the shorter time frame covered. Our results suggest that DNAm has the potential to act as a mediator between aging and diabetes-related phenotypes, or alternatively, may serve as a biomarker of these phenotypes.

Biological measures of aging are important for understanding the health of an aging population, with epigenetics particularly promising. Previous studies found that tumor tissue is epigenetically older than its donors are chronologically. We examined whether blood Δage (the discrepancy between epigenetic and chronological ages) can predict cancer incidence or mortality, thus assessing its potential as a cancer biomarker. In a prospective cohort, Δage and its rate of change over time were calculated in 834 blood leukocyte samples collected from 442 participants free of cancer at blood draw. About 3-5 years before cancer onset or death, Δage was associated with cancer risks in a dose-responsive manner (P = 0.02) and a one-year increase in Δage was associated with cancer incidence (HR: 1.06, 95% CI: 1.02-1.10) and mortality (HR: 1.17, 95% CI: 1.07-1.28). Participants with smaller Δage and decelerated epigenetic aging over time had the lowest risks of cancer incidence (P = 0.003) and mortality (P = 0.02). Δage was associated with cancer incidence in a 'J-shaped' manner for subjects examined pre-2003, and with cancer mortality in a time-varying manner. We conclude that blood epigenetic age may mirror epigenetic abnormalities related to cancer development, potentially serving as a minimally invasive biomarker for cancer early detection.

Summary: The development of the Infinium HumanMethylation450 BeadChip enables epigenome-wide association studies at a reduced cost. One observation of the 450K data is that many CpG sites the beadchip interrogates have very large measurement errors. Including these noisy CpGs will decrease the statistical power of detecting relevant associations due to multiple testing correction. We propose to use intra-class correlation coefficient (ICC), which characterizes the relative contribution of the biological variability to the total variability, to filter CpGs when technical replicates are available. We estimate the ICC based on a linear mixed effects model by pooling all the samples instead of using the technical replicates only. An ultra-fast algorithm has been developed to address the computational complexity and CpG filtering can be completed in minutes on a desktop computer for a 450K data set of over 1000 samples. Our method is very flexible and can accommodate any replicate design. Simulations and a real data application demonstrate that our whole-sample ICC method performs better than replicate-sample ICC or variance-based method., Availability and Implementation: CpGFilter is implemented in R and publicly available under CRAN via the R package 'CpGFilter'., Contact: chen.jun2@mayo.edu or xlin@hsph.harvard.edu, Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.)

Endometriosis is a gynecological disease defined by the extrauterine growth of endometrial-like cells that cause chronic pain and infertility. The disease is limited to primates that exhibit spontaneous decidualization, and diseased cells are characterized by significant defects in the steroid-dependent genetic pathways that typify this process. Altered DNA methylation may underlie these defects, but few regions with differential methylation have been implicated in the disease. We mapped genome-wide differences in DNA methylation between healthy human endometrial and endometriotic stromal cells and correlated this with gene expression using an interaction analysis strategy. We identified 42,248 differentially methylated CpGs in endometriosis compared to healthy cells. These extensive differences were not unidirectional, but were focused intragenically and at sites distal to classic CpG islands where methylation status was typically negatively correlated with gene expression. Significant differences in methylation were mapped to 403 genes, which included a disproportionally large number of transcription factors. Furthermore, many of these genes are implicated in the pathology of endometriosis and decidualization. Our results tremendously improve the scope and resolution of differential methylation affecting the HOX gene clusters, nuclear receptor genes, and intriguingly the GATA family of transcription factors. Functional analysis of the GATA family revealed that GATA2 regulates key genes necessary for the hormone-driven differentiation of healthy stromal cells, but is hypermethylated and repressed in endometriotic cells. GATA6, which is hypomethylated and abundant in endometriotic cells, potently blocked hormone sensitivity, repressed GATA2, and induced markers of endometriosis when expressed in healthy endometrial cells. The unique epigenetic fingerprint in endometriosis suggests DNA methylation is an integral component of the disease, and identifies a novel role for the GATA family as key regulators of uterine physiology-aberrant DNA methylation in endometriotic cells correlates with a shift in GATA isoform expression that facilitates progesterone resistance and disease progression.

Pesticide exposure has repeatedly been associated with cancers. However, molecular mechanisms are largely undetermined. In this study, we examined whether exposure to diazinon, a common organophosphate that has been associated with cancers, could induce DNA methylation alterations. We conducted genome-wide DNA methylation analyses on DNA samples obtained from human hematopoietic K562 cell exposed to diazinon and ethanol using the Illumina Infinium HumanMethylation27 BeadChip. Bayesian-adjusted t-tests were used to identify differentially methylated gene promoter CpG sites. We identified 1069 CpG sites in 984 genes with significant methylation changes in diazinon-treated cells. Gene ontology analysis demonstrated that some genes are tumor suppressor genes, such as TP53INP1 (3.0-fold, q-value <0.001) and PTEN (2.6-fold, q-value <0.001), some genes are in cancer-related pathways, such as HDAC3 (2.2-fold, q-value=0.002), and some remain functionally unknown. Our results provided direct experimental evidence that diazinon may modify gene promoter DNA methylation levels, which may play a pathological role in cancer development., (Copyright © 2012 Elsevier B.V. All rights reserved.)

Although pesticides are subject to extensive carcinogenicity testing before regulatory approval, pesticide exposure has repeatedly been associated with various cancers. This suggests that pesticides may cause cancer via nonmutagenicity mechanisms. The present study provides evidence to support the hypothesis that pesticide-induced cancer may be mediated in part by epigenetic mechanisms. We examined whether exposure to seven commonly used pesticides (i.e., fonofos, parathion, terbufos, chlorpyrifos, diazinon, malathion, and phorate) induces DNA methylation alterations in vitro. We conducted genome-wide DNA methylation analyses on DNA samples obtained from the human hematopoietic K562 cell line exposed to ethanol (control) and several organophosphate pesticides (OPs) using the Illumina Infinium HumanMethylation27 BeadChip. Bayesian-adjusted t-tests were used to identify differentially methylated gene promoter CpG sites. In this report, we present our results on three pesticides (fonofos, parathion, and terbufos) that clustered together based on principle component analysis and hierarchical clustering. These three pesticides induced similar methylation changes in the promoter regions of 712 genes, while also exhibiting their own OP-specific methylation alterations. Functional analysis of methylation changes specific to each OP, or common to all three OPs, revealed that differential methylation was associated with numerous genes that are involved in carcinogenesis-related processes. Our results provide experimental evidence that pesticides may modify gene promoter DNA methylation levels, suggesting that epigenetic mechanisms may contribute to pesticide-induced carcinogenesis. Further studies in other cell types and human samples are required, as well as determining the impact of these methylation changes on gene expression., (Copyright © 2012 Wiley Periodicals, Inc.)

Background: High-throughput profiling of DNA methylation status of CpG islands is crucial to understand the epigenetic regulation of genes. The microarray-based Infinium methylation assay by Illumina is one platform for low-cost high-throughput methylation profiling. Both Beta-value and M-value statistics have been used as metrics to measure methylation levels. However, there are no detailed studies of their relations and their strengths and limitations., Results: We demonstrate that the relationship between the Beta-value and M-value methods is a Logit transformation, and show that the Beta-value method has severe heteroscedasticity for highly methylated or unmethylated CpG sites. In order to evaluate the performance of the Beta-value and M-value methods for identifying differentially methylated CpG sites, we designed a methylation titration experiment. The evaluation results show that the M-value method provides much better performance in terms of Detection Rate (DR) and True Positive Rate (TPR) for both highly methylated and unmethylated CpG sites. Imposing a minimum threshold of difference can improve the performance of the M-value method but not the Beta-value method. We also provide guidance for how to select the threshold of methylation differences., Conclusions: The Beta-value has a more intuitive biological interpretation, but the M-value is more statistically valid for the differential analysis of methylation levels. Therefore, we recommend using the M-value method for conducting differential methylation analysis and including the Beta-value statistics when reporting the results to investigators.