Single CpGs Research Articles

Predictive value of DNA methylation patterns in AML patients treated with an azacytidine containing induction regimen

BackgroundAcute myeloid leukemia (AML) is a heterogeneous disease with a poor prognosis. Dysregulation of the epigenetic machinery is a significant contributor to disease development. Some AML patients benefit from treatment with hypomethylating agents (HMAs), but no predictive biomarkers for therapy response exist. Here, we investigated whether unbiased genome-wide assessment of pre-treatment DNA-methylation profiles in AML bone marrow blasts can help to identify patients who will achieve a remission after an azacytidine-containing induction regimen.ResultsA total of n = 155 patients with newly diagnosed AML treated in the AMLSG 12-09 trial were randomly assigned to a screening and a refinement and validation cohort. The cohorts were divided according to azacytidine-containing induction regimens and response status. Methylation status was assessed for 664,227 500-bp-regions using methyl-CpG immunoprecipitation-seq, resulting in 1755 differentially methylated regions (DMRs). Top regions were distilled and included genes such as WNT10A and GATA3. 80% of regions identified as a hit were represented on HumanMethlyation 450k Bead Chips. Quantitative methylation analysis confirmed 90% of these regions (36 of 40 DMRs). A classifier was trained using penalized logistic regression and fivefold cross validation containing 17 CpGs. Validation based on mass spectra generated by MALDI-TOF failed (AUC 0.59). However, discriminative ability was maintained by adding neighboring CpGs. A recomposed classifier with 12 CpGs resulted in an AUC of 0.77. When evaluated in the non-azacytidine containing group, the AUC was 0.76.ConclusionsOur analysis evaluated the value of a whole genome methyl-CpG screening assay for the identification of informative methylation changes. We also compared the informative content and discriminatory power of regions and single CpGs for predicting response to therapy. The relevance of the identified DMRs is supported by their association with key regulatory processes of oncogenic transformation and support the idea of relevant DMRs being enriched at distinct loci rather than evenly distribution across the genome.Predictive response to therapy could be established but lacked specificity for treatment with azacytidine. Our results suggest that a predictive epigenotype carries its methylation information at a complex, genome-wide level, that is confined to regions, rather than to single CpGs. With increasing application of combinatorial regimens, response prediction may become even more complicated.

Implication of DNA methylation during lifestyle mediated weight loss.

Over the past 50 years, the number of overweight/obese people increased significantly, making obesity a global public health challenge. Apart from rare monogenic forms, obesity is a multifactorial disease, most likely resulting from a concerted interaction of genetic, epigenetic and environmental factors. Although recent studies opened new avenues in elucidating the complex genetics behind obesity, the biological mechanisms contributing to individual's risk to become obese are not yet fully understood. Non-genetic factors such as eating behaviour or physical activity are strong contributing factors for the onset of obesity. These factors may interact with genetic predispositions most likely via epigenetic mechanisms. Epigenome-wide association studies or methylome-wide association studies are measuring DNA methylation at single CpGs across thousands of genes and capture associations to obesity phenotypes such as BMI. However, they only represent a snapshot in the complex biological network and cannot distinguish between causes and consequences. Intervention studies are therefore a suitable method to control for confounding factors and to avoid possible sources of bias. In particular, intervention studies documenting changes in obesity-associated epigenetic markers during lifestyle driven weight loss, make an important contribution to a better understanding of epigenetic reprogramming in obesity. To investigate the impact of lifestyle in obesity state specific DNA methylation, especially concerning the development of new strategies for prevention and individual therapy, we reviewed 19 most recent human intervention studies. In summary, this review highlights the huge potential of targeted interventions to alter disease-associated epigenetic patterns. However, there is an urgent need for further robust and larger studies to identify the specific DNA methylation biomarkers which influence obesity.

Ambient air pollution during pregnancy and DNA methylation in umbilical cord blood, with potential mediation of associations with infant adiposity: The Healthy Start study

BackgroundPrenatal exposure to ambient air pollution has been associated with adverse offspring health outcomes. Childhood health effects of prenatal exposures may be mediated through changes to DNA methylation detectable at birth. MethodsAmong 429 non-smoking women in a cohort study of mother-infant pairs in Colorado, USA, we estimated associations between prenatal exposure to ambient fine particulate matter (PM2.5) and ozone (O3), and epigenome-wide DNA methylation of umbilical cord blood cells at delivery (2010–2014). We calculated average PM2.5 and O3 in each trimester of pregnancy and the full pregnancy using inverse-distance-weighted interpolation. We fit linear regression models adjusted for potential confounders and cell proportions to estimate associations between air pollutants and methylation at each of 432,943 CpGs. Differentially methylated regions (DMRs) were identified using comb-p. Previously in this cohort, we reported positive associations between 3rd trimester O3 exposure and infant adiposity at 5 months of age. Here, we quantified the potential for mediation of that association by changes in DNA methylation in cord blood. ResultsWe identified several DMRs for each pollutant and period of pregnancy. The greatest number of significant DMRs were associated with third trimester PM2.5 (21 DMRs). No single CpGs were associated with air pollutants at a false discovery rate <0.05. We found that up to 8% of the effect of 3rd trimester O3 on 5-month adiposity may be mediated by locus-specific methylation changes, but mediation estimates were not statistically significant. ConclusionsDifferentially methylated regions in cord blood were identified in association with maternal exposure to PM2.5 and O3. Genes annotated to the significant sites played roles in cardiometabolic disease, immune function and inflammation, and neurologic disorders. We found limited evidence of mediation by DNA methylation of associations between third trimester O3 exposure and 5-month infant adiposity.

Strong Parallel Differential Gene Expression Induced by Hatchery Rearing Weakly Associated with Methylation Signals in Adult Coho Salmon (O. kisutch).

Human activities and resource exploitation led to a massive decline of wild salmonid populations, consequently, numerous conservation programs have been developed to supplement wild populations. However, many studies documented reduced fitness of hatchery-born relative to wild fish. Here, by using both RNA sequencing and Whole Genome Bisulfite Sequencing of hatchery and wild-born adult Coho salmon (Oncorhynchus kisutch) originating from two previously studied river systems, we show that early-life hatchery-rearing environment-induced significant and parallel gene expression differentiation is maintained until Coho come back to their natal river for reproduction. A total of 3,643 genes differentially expressed and 859 coexpressed genes were downregulated in parallel in hatchery-born fish from both rivers relative to their wild congeners. Among those genes, 26 displayed a significant relationship between gene expression and the median gene body methylation and 669 single CpGs displayed a significant correlation between methylation level and the associated gene expression. The link between methylation and gene expression was weak suggesting that DNA methylation is not the only player in mediating hatchery-related expression differences. Yet, significant gene expression differentiation was observed despite 18 months spent in a common environment (i.e., the sea). Finally, the differentiation is observed in parallel in two different river systems, highlighting the fact that early-life environment may account for at least some of the reduced fitness of the hatchery salmon in the wild. These results illustrate the relevance and importance of considering both epigenome and transcriptome to evaluate the costs and benefits of large-scale supplementation programs.

The Vista of Application of Specific Anaphylaxis Accurate Diagnosis Based on DNA Single-Nucleotide Methylation Sites.

Anaphylaxis has rapidly spread around the world in the last several decades. Environmental factors seem to play a major role, and epigenetic marks, especially DNA methylation, get more attention. We discussed several GEO opening data classifications with TOP 100 specific methylation region values (normalized M-values on line) by machine learning, which are remarkable to classify specific anaphylaxis after monoallergen exposure. Then, we sequenced the whole-genome DNA methylation of six people (3 wormwood monoallergen atopic rhinitis patients and 3 normal-immune people) during the pollen season and analyzed the difference of the single nucleotide and DNA region. The results' divergences were obvious (the differential single nucleotides were mostly distributed in nongene regions but the differential DNA regions of GWAS, on the other hand), which may have caused most single nucleotides to be concealed in the regions' sequences. Therefore, we suggest that we should conduct more “pragmatic” and directly find special single-nucleotide changes after exposure to atopic allergens instead of complex correlativity. It is possible to try to use DNA methylation marks to accurately diagnose anaphylaxis and form a machine learning classification based on the single methylated CpGs.

Epigenome-Wide Association Study of Acute Lymphoblastic Leukemia in Children with Down Syndrome

Background: Down syndrome (DS) is associated with an up to 30-fold increased risk of B-cell acute lymphoblastic leukemia (ALL), and DS-ALL patients have worse overall survival and increased long-term treatment-related health conditions compared with non-DS ALL patients. In a recent genome-wide association study of DS-ALL, established ALL genetic risk loci were associated with DS-ALL, with several single nucleotide polymorphisms (SNPs) conferring a larger effect on ALL risk in the context of DS than in euploidy. We performed an epigenome-wide association study (EWAS) to elucidate whether epigenetic differences at birth are associated with risk of subsequent DS-ALL.Methods: The DS-ALL Discovery Study included 147 DS-ALL cases and 198 DS controls from the International Study of Down Syndrome Acute Leukemia, with newborn dried bloodspots (DBS) obtained from California (n=326) and Washington state (n=19) biobanks. The DS-ALL Replication Study included 24 DS-ALL cases and 24 DS controls with newborn DBS from the Michigan Neonatal Biobank. DNA was isolated from DBS, bisulfite converted, and assayed using Illumina Infinium MethylationEPIC Beadchip genome-wide DNA methylation arrays. Raw data were processed using “minfi” and “noob” packages in R. Reference-based deconvolution of blood cell proportions was performed using the Identifying Optimal DNA methylation Libraries (IDOL) algorithm, using DNA methylation data from cord blood reference samples, to estimate proportions of B cells, T cells (CD4+ and CD8+), monocytes, granulocytes, natural killer cells, and nucleated red blood cells. We compared each cell type proportion between DS-ALL cases and DS controls using linear regression adjusting for sex, plate, and principal components (PCs) to account for genetic ancestry. To identify single CpG probes associated with DS-ALL risk, we performed a multiethnic EWAS of DS-ALL in each study using linear regression adjusting for sex, plate, and PCs related to: 1) cell-type proportions and 2) genetic ancestry. Differentially methylated regions (DMRs) were identified using DMRcate and comb-p methods. In the Discovery Study, genome-wide SNP array data were available for 131 cases and 130 controls, and data from targeted sequencing of somatic mutations in exons 2/3 of GATA1 were available for 184/198 DS controls.Results: Deconvolution of blood cell proportions in the DS-ALL Discovery Study showed significantly higher B cell proportions in newborns with DS who later developed ALL (mean=0.0128, sd=0.0151) compared with DS controls (mean=0.00826, sd=0.0115) (P=6.4x10 -4, coefficient=0.0052). A significantly higher B cell proportion at birth was also found in DS-ALL cases in the independent Replication Study (cases mean=0.048, sd=0.024; controls mean=0.039, sd=0.028; P=0.03, coefficient=0.015). In the Discovery Study, the B cell difference remained significant (P=5.8x10 -3) with a similar effect size (coefficient=0.0045) after removal of GATA1 mutation-positive DS controls (n=30). We also investigated whether DS-ALL risk SNPs at ARID5B, IKZF1, GATA3, and CDKN2A may confound the association, but the increased B cell proportions in DS-ALL remained significant and effect estimates slightly increased in SNP genotype-adjusted models (coefficient range:0.0055-0.0059). In the EWAS of DS-ALL, 9 CpGs reached epigenome-wide significance (P<7.67x10 -8), including 2 CpGs overlapping the promoter of the tumor suppressor gene TRIM13, frequently deleted in B-CLL, although none of these showed evidence of association (P<0.05) in the Replication Study. We identified 125 DMRs associated with DS-ALL in the Discovery Study. For 3 DMRs, overlapping genes HOPX, SMIM24, and PPP1R10, all implicated in normal and leukemic stem cell function, there were multiple significant CpGs in the Replication Study (P<0.05) all with effects in the same direction as the Discovery Study DMRs.Conclusions: Increased B cell proportions in newborns with DS may be a risk factor for development of DS-ALL in childhood. This finding, based on DNA methylation data, requires confirmation using conventional cell count measures, and should be explored as a novel biomarker for ALL risk in the non-DS population. Single CpGs and DMRs associated with DS-ALL risk in our Discovery Study require further investigation, including in additional ALL case-control studies in DS and non-DS populations. DisclosuresMa: Celgene/Bristol Myers Squibb: Consultancy, Research Funding.

DNA Methylation Changes in Fibromyalgia Suggest the Role of the Immune-Inflammatory Response and Central Sensitization.

Fibromyalgia (FM) has been explained as a result of gene-environment interactions. The present study aims to verify DNA methylation differences in eleven candidate genome regions previously associated to FM, evaluating DNA methylation patterns as potential disease biomarkers. DNA methylation was analyzed through bisulfite sequencing, comparing 42 FM women and their 42 healthy sisters. The associations between the level of methylation in these regions were further explored through a network analysis. Lastly, a logistic regression model investigated the regions potentially associated with FM, when controlling for sociodemographic variables and depressive symptoms. The analysis highlighted significant differences in the GCSAML region methylation between patients and controls. Moreover, seventeen single CpGs, belonging to other genes, were significantly different, however, only one cytosine related to GCSAML survived the correction for multiple comparisons. The network structure of methylation sites was different for each group; GRM2 methylation represented a central node only for FM patients. Logistic regression revealed that depressive symptoms and DNA methylation in the GRM2 region were significantly associated with FM risk. Our study encourages better exploration of GCSAML and GRM2 functions and their possible role in FM affecting immune, inflammatory response, and central sensitization of pain.

DNA methylation of Vesicular Glutamate Transporters in the mesocorticolimbic brain following early-life stress and adult ethanol exposure\u2014an explorative study

DNA methylation and gene expression can be altered by early life stress (ELS) and/or ethanol consumption. The present study aimed to investigate whether DNA methylation of the Vesicular Glutamate Transporters (Vglut)1-3 is related to previously observed Vglut1-3 transcriptional differences in the ventral tegmental area (VTA), nucleus accumbens (Acb), dorsal striatum (dStr) and medial prefrontal cortex (mPFC) of adult rats exposed to ELS, modelled by maternal separation, and voluntary ethanol consumption. Targeted next-generation bisulfite sequencing was performed to identify the methylation levels on 61 5′-cytosine-phosphate-guanosine-3′ sites (CpGs) in potential regulatory regions of Vglut1, 53 for Vglut2, and 51 for Vglut3. In the VTA, ELS in ethanol-drinking rats was associated with Vglut1-2 CpG-specific hypomethylation, whereas bidirectional Vglut2 methylation differences at single CpGs were associated with ELS alone. Exposure to both ELS and ethanol, in the Acb, was associated with lower promoter and higher intronic Vglut3 methylation; and in the dStr, with higher and lower methylation in 26% and 43% of the analyzed Vglut1 CpGs, respectively. In the mPFC, lower Vglut2 methylation was observed upon exposure to ELS or ethanol. The present findings suggest Vglut1-3 CpG-specific methylation signatures of ELS and ethanol drinking, underlying previously reported Vglut1-3 transcriptional differences in the mesocorticolimbic brain.

Rare genetic variation at transcription factor binding sites modulates local DNA methylation profiles.

Although DNA methylation is the best characterized epigenetic mark, the mechanism by which it is targeted to specific regions in the genome remains unclear. Recent studies have revealed that local DNA methylation profiles might be dictated by cis-regulatory DNA sequences that mainly operate via DNA-binding factors. Consistent with this finding, we have recently shown that disruption of CTCF-binding sites by rare single nucleotide variants (SNVs) can underlie cis-linked DNA methylation changes in patients with congenital anomalies. These data raise the hypothesis that rare genetic variation at transcription factor binding sites (TFBSs) might contribute to local DNA methylation patterning.In this work, by combining blood genome-wide DNA methylation profiles, whole genome sequencing-derived SNVs from 247 unrelated individuals along with 133 predicted TFBS motifs derived from ENCODE ChIP-Seq data, we observed an association between the disruption of binding sites for multiple TFs by rare SNVs and extreme DNA methylation values at both local and, to a lesser extent, distant CpGs. While the majority of these changes affected only single CpGs, 24% were associated with multiple outlier CpGs within ±1kb of the disrupted TFBS. Interestingly, disruption of functionally constrained sites within TF motifs lead to larger DNA methylation changes at nearby CpG sites. Altogether, these findings suggest that rare SNVs at TFBS negatively influence TF-DNA binding, which can lead to an altered local DNA methylation profile. Furthermore, subsequent integration of DNA methylation and RNA-Seq profiles from cardiac tissues enabled us to observe an association between rare SNV-directed DNA methylation and outlier expression of nearby genes.In conclusion, our findings not only provide insights into the effect of rare genetic variation at TFBS on shaping local DNA methylation and its consequences on genome regulation, but also provide a rationale to incorporate DNA methylation data to interpret the functional role of rare variants.

Associations of maternal early-pregnancy blood glucose and insulin concentrations with DNA methylation in newborns

BackgroundIntrauterine exposure to a disturbed maternal glucose metabolism is associated with adverse offspring outcomes. DNA methylation is a potential mechanism underlying these associations. We examined whether maternal early-pregnancy glucose and insulin concentrations are associated with newborn DNA methylation. In a population-based prospective cohort study among 935 pregnant women, maternal plasma concentrations of non-fasting glucose and insulin were measured at a median of 13.1 weeks of gestation (95% range 9.4–17.4). DNA methylation was measured using the Infinium HumanMethylation450 BeadChip (Ilumina). We analyzed associations of maternal early-pregnancy glucose and insulin concentrations with single-CpG DNA methylation using robust linear regression models. Differentially methylated regions were analyzed using the dmrff package in R. We stratified the analyses on normal weight versus overweight or obese women. We also performed a look-up of CpGs and differently methylated regions from previous studies to be associated with maternal gestational diabetes, hyperglycemia or hyperinsulinemia, or with type 2 diabetes in adults.ResultsMaternal early-pregnancy glucose and insulin concentrations were not associated with DNA methylation at single CpGs nor with differentially methylated regions in the total group. In analyses stratified on maternal BMI, maternal early-pregnancy glucose concentrations were associated with DNA methylation at one CpG (cg03617420, XKR6) among normal weight women and at another (cg12081946, IL17D) among overweight or obese women. No stratum-specific associations were found for maternal early-pregnancy insulin concentrations. The two CpGs were not associated with birth weight or childhood glycemic measures (p values > 0.1). Maternal early-pregnancy insulin concentrations were associated with one CpG known to be related to adult type 2 diabetes. Enrichment among nominally significant findings in our maternal early-pregnancy glucose concentrations was found for CpGs identified in a previous study on adult type 2 diabetes.ConclusionsMaternal early-pregnancy glucose concentrations, but not insulin concentrations, were associated with DNA methylation at one CpG each in the subgroups of normal weight and of overweight or obese women. No associations were present in the full group. The role of these CpGs in mechanisms underlying offspring health outcomes needs further study. Future studies should replicate our results in larger samples with early-pregnancy information on maternal fasting glucose metabolism.

1568-P: One Methylation Risk Score Model, Two Racial Populations

Metabolic Syndrome (MetS) is a cluster of conditions that can increase the risk of chronic diseases like, type 2 diabetes. Multiple reports show alterations in DNA methylation patterns are associated with the condition. Using cross-sectional data from Hypertension Genetic Epidemiology Network (HyperGEN) (N=614 African Americans (AA)) and Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) (N=995 European Americans (EA)), we created a risk score model for MetS. First, we selected specific cytosine-guanine dinucleotides (CpG) sites measured on Illumina Methyl450 arrays previously found to be significantly associated to MetS (CPT1A cg00574958, PHOSPHO1 cg02650017, ABCG1 cg06500161, SREBF1 cg11024682, SOCS3 cg18181703, TXNIP cg19693031). Using the HyperGEN parameter estimates for the single CpGs as weights, we calculated a methylation risk score in HyperGEN which was validated in GOLDN. We then conducted an association analysis using a generalized linear mixed model to test the association between the methylation risk score (MetS-score) and MetS, adjusting for age, sex, study site, 4 ancestry principal components, and family structure. In HyperGEN we performed a 100,000-permutation test to determine statistical significance of the score with MetS. Results showed the risk score was significantly associated with MetS in both populations (HyperGEN p=6.36x-10; GOLDN p=2x-16), with a 1 standard deviation increase in the score being associated with 2.25 (95% CI, 1.79 - 2.86) higher odds of having MetS in HyperGEN and a 2.45 (CI 95%, 2.02 - 3.00) higher odds of having MetS in GOLDN. Lastly, we compared the model fitness of the GOLDN MetS model with and without the MetS-score. AIC criterion suggested the model including the score was a better fit (no score = 1173.99; with score = 1112.61). In conclusion, we created a methylation risk score strongly associated with MetS which should be further investigated for its ability to predict MetS risk in both AAs and EAs. Disclosure B.A. Minniefield: None. M. Irvin: None. B. Hidalgo: None. H.K. Tiwari: None. A. Patki: None. N. Chaudhary: None. Funding National Heart, Lung, and Blood Institute (3R01HL123782-02S1)

Genome-Wide DNA Methylation Patterns in Children Exposed to Nonpharmacologically Treated Prenatal Depressive Symptoms: Results From 2 Independent Cohorts.

Background:Maternal depressive symptoms are a common phenomenon during pregnancy and are related to negative outcomes for child development and health. Modifications in child DNA methylation are discussed as an underlying mechanism for the association between prenatal depressive symptoms and alterations in child outcomes. However, formerly reported genome-wide associations have yet to be replicated.Methods:In an epigenome-wide association study (EWAS), alterations of DNA methylation related to maternal prenatal depressive symptoms were investigated in buccal cell samples from 174 children (n = 52 exposed to prenatal depressive symptoms; 6-9 years old) of the German longitudinal study FRAMES-FRANCES. Whole blood samples from the independent, age-comparable ARIES subsample of the ARIES/ALSPAC study (n = 641; n = 159 exposed to prenatal depressive symptoms; 7-8 years old) were examined as a confirmation sample. Depressive symptoms were assessed with the Edinburgh Postnatal Depression Scale. DNA methylation was analyzed with the Infinium Human Methylation 450k BeadChip. Modifications in single CpGs, regions, and biological pathways were investigated. Results were adjusted for age and birth outcomes as well as postnatal and current maternal depressive symptoms. Analyses were performed for the whole sample as well as separated for sex.Results:The EWAS yielded no differentially methylated CpG or region as well as no accordance between samples withstanding correction for multiple testing. In pathway analyses, no overlapping functional domain was found to be enriched for either sample. A comparison of current and former findings suggests some overlapping methylation modifications from infancy to childhood. Results suggest that there might be sex-specific differential methylation, which should be further investigated in additional studies.Conclusions:The current, mainly nonsignificant, results challenge the assumption of consistent modifications of DNA methylation in children exposed to prenatal depressive symptoms. Despite the relatively small sample size used in this study, this lack of significant results may reflect diverse issues of environmental epigenetic studies, which need to be addressed in future research.

Newborn and childhood differential DNA methylation and liver fat in school-age children

BackgroundNon-alcoholic fatty liver disease is the most common chronic liver disease in children in western countries. Adverse early-life exposures are associated with higher liver fat percentages in children. Differential DNA methylation may underlie these associations. We aimed to identify differential DNA methylation in newborns and children associated with liver fat accumulation in childhood. We also examined whether DNA methylation at 22 cytosine-phosphate-guanine sites (CpGs) associated with adult non-alcoholic fatty liver disease is associated with liver fat in children. Within a population-based prospective cohort study, we analyzed epigenome-wide DNA methylation data of 785 newborns and 344 10-year-old children in relation to liver fat fraction at 10 years. DNA methylation was measured using the Infinium HumanMethylation450 BeadChip (Illumina). We measured liver fat fraction by Magnetic Resonance Imaging. Associations of single CpG DNA methylation at the two-time points with liver fat accumulation were analyzed using robust linear regression models. We also analyzed differentially methylation regions using the dmrff package. We looked-up associations of 22 known adult CpGs at both ages with liver fat at 10 years.ResultsThe median liver fat fraction was 2.0% (95% range 1.3, 5.1). No single CpGs and no differentially methylated regions were associated with liver fat accumulation. None of the 22 known adult CpGs were associated with liver fat in children.ConclusionsDNA methylation at birth and in childhood was not associated with liver fat accumulation in 10-year-old children in this study. This may be due to modest sample sizes or DNA methylation changes being a consequence rather than a determinant of liver fat.

Human aging DNA methylation signatures are conserved but accelerated in cultured fibroblasts

ABSTRACTAging is associated with progressive and site-specific changes in DNA methylation (DNAm). These global changes are captured by DNAm clocks that accurately predict chronological age in humans but relatively little is known about how clocks perform in vitro. Here we culture primary human fibroblasts across the cellular lifespan (~6 months) and use four different DNAm clocks to show that age-related DNAm signatures are conserved and accelerated in vitro. The Skin & Blood clock shows the best linear correlation with chronological time (r = 0.90), including during replicative senescence. Although similar in nature, the rate of epigenetic aging is approximately 62x times faster in cultured cells than in the human body. Consistent with in vivo data, cells aged under hyperglycemic conditions exhibit an approximately three years elevation in baseline DNAm age. Moreover, candidate gene-based analyses further corroborate the conserved but accelerated biological aging process in cultured fibroblasts. Fibroblasts mirror the established DNAm topology of the age-related ELOVL2 gene in human blood and the rapid hypermethylation of its promoter cg16867657, which correlates with a linear decrease in ELOVL2 mRNA levels across the lifespan. Using generalized additive modeling on twelve timepoints across the lifespan, we also show how single CpGs exhibit loci-specific, linear and nonlinear trajectories that reach rates up to −47% (hypomethylation) to +23% (hypermethylation) per month. Together, these high-temporal resolution global, gene-specific, and single CpG data highlight the conserved and accelerated nature of epigenetic aging in cultured fibroblasts, which may constitute a system to evaluate age-modifying interventions across the lifespan.

Human monocyte-to-macrophage differentiation involves highly localized gain and loss of DNA methylation at transcription factor binding sites

BackgroundMacrophages and their precursors monocytes play a key role in inflammation and chronic inflammatory disorders. Monocyte-to-macrophage differentiation and activation programs are accompanied by significant epigenetic remodeling where DNA methylation associates with cell identity. Here we show that DNA methylation changes characteristic for monocyte-to-macrophage differentiation occur at transcription factor binding sites, and, in contrast to what was previously described, are generally highly localized and encompass both losses and gains of DNA methylation.ResultsWe compared genome-wide DNA methylation across 440,292 CpG sites between human monocytes, naïve macrophages and macrophages further activated toward a pro-inflammatory state (using LPS/IFNγ), an anti-inflammatory state (IL-4) or foam cells (oxLDL and acLDL). Moreover, we integrated these data with public whole-genome sequencing data on monocytes and macrophages to demarcate differentially methylated regions. Our analysis showed that differential DNA methylation was most pronounced during monocyte-to-macrophage differentiation, was typically restricted to single CpGs or very short regions, and co-localized with lineage-specific enhancers irrespective of whether it concerns gain or loss of methylation. Furthermore, differentially methylated CpGs were located at sites characterized by increased binding of transcription factors known to be involved in monocyte-to-macrophage differentiation including C/EBP and ETS for gain and AP-1 for loss of methylation.ConclusionOur study highlights the involvement of subtle, yet highly localized remodeling of DNA methylation at regulatory regions in cell differentiation.

Novel Assay for Quantitative Analysis of DNA Methylation at Single-Base Resolution.

The DNA methylation profile provides valuable biological information with potential clinical utility. Several methods, such as quantitative methylation-specific PCR (qMSP), have been developed to examine methylation of specific CpG sites. Existing qMSP-based techniques fail to examine the genomic methylation at a single-base resolution, particularly for loci in gene bodies or extensive CpG open seas lacking flanking CpGs. Therefore, we established a novel assay for quantitative analysis of single-base methylation. To achieve a robust single-base specificity, we developed a PCR-based method using paired probes following bisulfite treatment. The 6-carboxyfluorescein- and 2'-chloro-7'phenyl-1,4-dichloro-6-carboxy-fluorescein-labeled probes conjugated with minor groove binder were designed to specifically bind to the methylated and unmethylated allele of targeted single CpGs at their 3' half regions, respectively. The methylation percentage was calculated by values of methylation / (methylation + unmethylation). In the detection of single CpGs within promoters or bodies of 4 human genes, the quantitative analysis of the single-base methylation assay showed a detection capability in the 1 to 1:10000 dilution experiments with linearity over 4 orders of magnitude (R 2 = 0.989-0.994; all P < 0.001). In a cohort of 10 colorectal cancer samples, the assay showed a comparable detection performance with bisulfite pyrosequencing (R 2 = 0.875-0.990; all P < 0.001), which was better than conventional qMSP methods normalized by input control reaction (R 2 = 0.841 vs 0.769; P = 0.002 vs 0.009). This assay is highly specific and sensitive for determining single-base methylation and, thus, is potentially useful for methylation-based panels in diagnostic and prognostic applications.

DNA Methylation and All-Cause Mortality in Middle-Aged and Elderly Danish Twins.

Several studies have linked DNA methylation at individual CpG sites to aging and various diseases. Recent studies have also identified single CpGs whose methylation levels are associated with all-cause mortality. In this study, we perform an epigenome-wide study of the association between CpG methylation and mortality in a population of 435 monozygotic twin pairs from three Danish twin studies. The participants were aged 55–90 at the time of blood sampling and were followed for up to 20 years. We validated our results by comparison with results from a British and a Swedish cohort, as well as results from the literature. We identified 2806 CpG sites associated with mortality (false discovery rate (), of which 24 had an association p-value below . This was confirmed by intra-pair comparison controlling for confounding effects. Eight of the 24 top sites could be validated in independent datasets or confirmed by previous studies. For all these eight sites, hypomethylation was associated with poor survival prognosis, and seven showed monozygotic correlations above 35%, indicating a potential moderate to strong heritability, but leaving room for substantial shared or unique environmental effects. We also set up a predictor for mortality using least absolute shrinkage and selection operator (LASSO) regression. The predictor showed good performance on the Danish data under cross-validation, but did not perform very well in independent samples.

Rules governing the mechanism of epigenetic reprogramming memory.

Disclosing the mechanisms that regulate reprogramming memory. We established computational procedure to find DNA methylation somatic memory sites (SMSs) at single CpGs and integrated them with genomics, epigenomics, transcriptomics and imprinting information. Reprogramming memory persists at late passages in low methylated regions. Contrarily to hypomethylated, hypermethylated SMSs occur at evolutionary conserved sites overlapping active transcription loci in dynamic chromatin regions. The epigenetic-memory molecular origin is the expression of source-cell transcription factors protecting hypomethylated SMSs in euchromatin from de novomethylation, keeping source-cell lineage-specific loci in induced pluripotent stem (iPS) cells incompletely silenced. Sites in lineage-specific genes of different-from-those-of-the-source-cell lineages remain hypermethylated in heterochromatin regions becoming permanently silenced. SMSs cause differential expression between iPS cells and embryonic stem cells through two mechanisms: 'epigenetic/expression memory rule', the DNA unreprogramming methylation status coupled with chromatin states induces differentially expressed genes. 'Imprinting control', the change of DNA methylation status in imprinting control regions induces differential expression of imprinted genes.

DNA methylation imprinting errors in spermatogenic cells from maturation arrest azoospermic patients.

Imprinting errors have been described in spermatozoa from infertile patients with oligozoospermia and azoospermia. However, little is known about methylation of imprinted genes in other spermatogenic cells from azoospermic patients. Therefore, we aimed to evaluate the methylation status of single CpGs located in the differentially methylated regions (DMRs) of two imprinted genes, one paternally (H19) and one maternally (MEST) methylated, in primary spermatocytes of azoospermic patients presenting complete (MAc, n=7) and incomplete (MAi, n=8) maturation arrest, as well as in other spermatogenic cells from MAi patients that presented focus of complete spermatogenesis in some seminiferous tubules. We observed H19 imprinting errors in primary spermatocytes from one MAi patient and MEST imprinting errors in one MAi and two MAc patients. Additionally, H19 imprinting errors were observed in elongated spermatids/spermatozoa from one MAi patient. Nevertheless, no statistical differences were found for H19 and MEST global methylation levels (percentage of methylated and unmethylated CpGs, respectively) between patients with complete and incomplete MA and also between MA groups and a control group. These results provide further evidence that imprinting errors occur in spermatogenic cells from patients presenting impaired spermatogenesis, as we and others have previously described in ejaculated and testicular spermatozoa. As paternal imprinting errors can be transmitted to the embryo by the sperm cell, they can provide a possible explanation for poor embryo development and/or low pregnancy rates as correct expression of imprinted genes is crucial for embryo and placental development and function. Therefore, in cases with male factor infertility where unsuccessful invitro fertilization (IVF) treatments are recurrent, analysis of imprinting marks in spermatozoa might be a useful diagnostic tool.

Teratozoospermia and asthenozoospermia are associated with specific epigenetic signatures.

Semen analysis is commonly used as a tool to assess the fertility potential of a male, despite its relatively low predictive power. In this study, we have assessed associations between semen analysis findings (low count, low motility, low viability, poor sperm penetration assay results, poor morphology, and increased DNA damage) and DNA methylation patterns in mature spermatozoa. DNA methylation patterns in the mature spermatozoa are thought to be indicative of patterns in the adult germline stem cells and may offer insight into potential perturbations to cellular pathways involved in spermatogenesis. In this study, sperm DNA methylation at >480,000 CpGs was assessed in 94 men using the Illumina 450k HumanMethylation Array and compared to standard measures of sperm quality. We did not identify any global changes to methylation profiles that were associated with reduced semen parameters. Similarly, we found no significant difference in methylation variability that was associated with any abnormal semen analysis parameter, although sperm displaying abnormal parameters tended to have an increased coefficient of variability, suggesting that, in some samples, this may be a contributing factor. Analysis of methylation at single CpGs and genomic regions did identify associations for low viability and low motility, and to a smaller extent, low count. Interestingly, based on GO Term analysis, differentially methylated regions associated with low viability were over-represented in regions important in meiosis, spermatogenesis, and genomic imprinting. These results suggest that while there are not global alterations to the sperm methylome associated with semen abnormalites, some viability associated regional alterations do exist that may be indicative of perturbed cellular pathways during spermatogenesis.