Differential Methylation Signatures in Severely Calcified Carotid Plaques by Genome-Wide Comprehensive Analysis

2020 ◽  
Vol 17 ◽  
Author(s):  
Hiroyuki Katano ◽  
Yusuke Nishikawa ◽  
Hiroshi Yamada ◽  
Tomoyasu Yamanaka ◽  
Mitsuhito Mase
Keyword(s):  
Dna Methylation ◽  
Cpg Island ◽  
Principal Component ◽  
Smooth Muscle Contraction ◽  
Differential Methylation ◽  
Promoter Regions ◽  
Tissue Specific ◽  
Carotid Plaques ◽  
Differentially Methylated Genes ◽  
Island Shore

Background: The precise cellular behaviors of calcification, including its molecular and genetic activities, have not yet been fully established for carotid plaques. Objective: We sought specific genes with tissue-specific differential methylation associated with carotid calcification status. Methods: We classified eight plaques from carotid endarterectomy patients as high- or low-calcified based on their Agatston calcium scores. We analyzed differential DNA methylation and performed bioinformatics data mining. Results: A high correlation of average methylation levels (b-values) in promoter regions between high- and low-calcified plaque groups was observed. A principal component analysis of DNA methylation values in promoters of specimens revealed two independent clusters for high- and low-calcified plaques. Volcano plots for methylation differences in promoter regions showed that significantly hypomethylated probes were more frequently found for high-calcified plaques than more methylated probes. Differential hypomethylation of receptor activity-modifying protein 1 (RAMP1) in high-calcified plaques was commonly extracted in both the promoter region and the cytosine-phosphate-guanine (CpG) island shore region, where differential methylation had been reported to be more tissue-specific. Kyoto Encyclopedia of Genes and Genomes pathway analysis annotated a pathway associated with vascular smooth muscle contraction in the differentially methylated genes of the promoter and CpG island shore regions in high-calcified plaques. Conclusion: Among the extracted differentially methylated genes, hypomethylated genes were more dominant than more methylated genes. The augmentation of RAMP1 by hypomethylation may contribute to the enhancement of antiatherosclerotic effects and hence stability in high-calcified plaques. These results contribute to our understanding of the genetic signatures associated with calcification status and cellular activity in carotid plaques.

Genome Wide Study of DNA Methylation In AML

Blood ◽  
2010 ◽  
Vol 116 (21) ◽  
pp. 3618-3618
Author(s):  
Marwa Saied ◽  
Sabah Khaled ◽  
Thomas Down ◽  
Jacek Marzec ◽  
Paul Smith ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Cpg Island ◽  
Cpg Islands ◽  
Differential Methylation ◽  
Methylation Analysis ◽  
Promoter Regions ◽  
Gene Body Methylation ◽  
Normal Bone ◽  
Genome Wide

Abstract Abstract 3618 DNA methylation is the most stable epigenetic modification and has a major role in cancer initiation and progression. The two main aims for this research were, firstly, to use the genome wide analysis of DNA methylation to better understand the development of acute myeloid leukemia (AML). The second aim was to detect differentially methylated genes/regions between certain subtypes of AML and normal bone marrow (NBM). We used the methylated DNA immunoprecipitation technique followed by high-throughput sequencing by Illumina Genome Analyser II (MeDIP -seq) for 9 AML samples for which ethical approval has been obtained. The selected leukemias included three with the t(8; 21), three with the t(15; 17) translocations and three with normal karyotypes (NK). The control samples were 3 normal bone marrows (NBMs) from healthy donors. The number of reads generated from Illumina ranged between 18– 20 million paired-end reads/lane with a good base quality from both ends (base quality > 30 represented 75%-85% of reads). The reads were aligned using 2 algorithms (Maq and Bowtie) and the methylation analysis was performed by Batman software (Bayesian Tool for Methylation Analysis). The creation of this genome-wide methylation map for AML permits the examination of the patterns for key genetic elements. Investigation of the 35,072 promoter regions identified 80 genes, which showed a significant differential methylation levels in leukemic cases in comparison to NBM; consistently high methylation levels in leukaemia were detected in the promoters of 70 genes e.g. DPP6, ID4, DCC, whereas high methylation levels in NBM, lost in leukaemia was observed in 10 genes e.g. ATF4. For each AML subtype, we also identified significant differentially methylated promoter regions e.g. PAX1 for t(8; 21), GRM7 for t(15; 17), NPM2 for NK. An analysis of gene body methylation identified 49 genes with significantly higher methylation in AML in comparison to NBM e.g. MYOD1 and 31 genes with a higher methylation in NBMs than AML e.g. GNG8. A similar analysis of 23,600 CpG islands identified 400 CpG islands with significant differential methylation levels between leukaemia and NBMs (212 CpG islands were found to have significantly increased methylation in leukaemia and 188 CpG islands had significantly higher methylation in NBMs). The pattern of methylation in CpG island “shores” (2 KB from either side of each CpG island) has been investigated and 312 CpG island shores showed a higher methylation in leukaemia and 88 CpG shores had a significant increase methylation levels in NBMs. This genome wide methylation map has been validated by using direct bisulfite sequencing of the regions identified above (Spearman r= 0.8, P <0.0001) and also by using Illumina Infinium assay (Spearman r= 0.7 P <0.0001) which interrogates regions at single representative CpGs. Comparison of previous array based gene expression data with this methylation map revealed a significant negative correlation between promoter methylation and gene expression (Pearson r= -0.9, P< 0.0001) while, gene body methylation showed a small negative correlation with gene expression, that was found in genes of CpG density >3% (Pearson r= -0.3, P< 0.0001). Conclusion: we have established a high-resolution (100bp) map of DNA methylation in AML and thus identified a novel list of genes, which have significantly differential methylation levels in AML. Disclosures: No relevant conflicts of interest to declare.

Maternal anxiety and depression in pregnancy and DNA methylation of the NR3C1 glucocorticoid receptor gene

Epigenomics ◽  
2020 ◽  
Author(s):  
Alexandra E Dereix ◽  
Rachel Ledyard ◽  
Allyson M Redhunt ◽  
Tessa R Bloomquist ◽  
Kasey JM Brennan ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Depressive Symptoms ◽  
Trait Anxiety ◽  
Cpg Island ◽  
Depression Scale ◽  
Maternal Anxiety ◽  
Anxiety And Depression ◽  
Pregnancy Anxiety ◽  
Glucocorticoid Receptor Gene ◽  
Island Shore

Aim: To quantify associations of anxiety and depression during pregnancy with differential cord blood DNA methylation of the glucorticoid receptor ( NR3C1). Materials & methods: Pregnancy anxiety, trait anxiety and depressive symptoms were collected using the Pregnancy Related Anxiety Scale, State-Trait Anxiety Index and Edinburgh Postnatal Depression Scale, respectively. NR3C1 methylation was determined at four methylation sites. Results: DNA methylation of CpG 1 in the NR3C1 CpG island shore was higher in infants born to women with high pregnancy anxiety (β 2.54, 95% CI: 0.49–4.58) and trait anxiety (β 1.68, 95% CI: 0.14–3.22). No significant association was found between depressive symptoms and NR3C1 methylation. Conclusion: We found that maternal anxiety was associated with increased NR3C1 CpG island shore methylation.

scholarly journals Exploring Differentially Methylated Genes in Vulvar Squamous Cell Carcinoma

Cancers ◽  
2021 ◽  
Vol 13 (14) ◽  
pp. 3580
Author(s):  
Shatavisha Dasgupta ◽  
Patricia C. Ewing-Graham ◽  
Sigrid M. A. Swagemakers ◽  
Thierry P. P. van den Bosch ◽  
Peggy N. Atmodimedjo ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Dna Sequences ◽  
Cpg Island ◽  
Epigenetic Modification ◽  
Vulvar Squamous Cell Carcinoma ◽  
Differentially Methylated Genes ◽  
Methylation Profiling

DNA methylation is the most widely studied mechanism of epigenetic modification, which can influence gene expression without alterations in DNA sequences. Aberrations in DNA methylation are known to play a role in carcinogenesis, and methylation profiling has enabled the identification of biomarkers of potential clinical interest for several cancers. For vulvar squamous cell carcinoma (VSCC), however, methylation profiling remains an under-studied area. We sought to identify differentially methylated genes (DMGs) in VSCC, by performing Infinium MethylationEPIC BeadChip (Illumina) array sequencing, on a set of primary VSCC (n = 18), and normal vulvar tissue from women with no history of vulvar (pre)malignancies (n = 6). Using a false-discovery rate of 0.05, beta-difference (Δβ) of ± 0.5, and CpG-island probes as cut-offs, 199 DMGs (195 hyper-methylated, 4 hypo-methylated) were identified for VSCC. Most of the hyper-methylated genes were found to be involved in transcription regulator activity, indicating that disruption of this process plays a vital role in VSCC development. The majority of VSCCs harbored amplifications of chromosomes 3, 8, and 9. We identified a set of DMGs in this exploratory, hypothesis-generating study, which we hope will facilitate epigenetic profiling of VSCCs. Prognostic relevance of these DMGs deserves further exploration in larger cohorts of VSCC and its precursor lesions.

scholarly journals Stable DNMT3L overexpression in SH-SY5Y neurons recreates a facet of the genome-wide Down syndrome DNA methylation signature

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Benjamin I. Laufer ◽  
J. Antonio Gomez ◽  
Julia M. Jianu ◽  
Janine M. LaSalle
Keyword(s):  
Dna Methylation ◽  
Down Syndrome ◽  
Neuronal Differentiation ◽  
Molecular Mechanisms ◽  
Cpg Island ◽  
Differential Methylation ◽  
Chromosome 21 ◽  
Pairwise Comparisons ◽  
Genome Wide ◽  
A Genome

Abstract Background Down syndrome (DS) is characterized by a genome-wide profile of differential DNA methylation that is skewed towards hypermethylation in most tissues, including brain, and includes pan-tissue differential methylation. The molecular mechanisms involve the overexpression of genes related to DNA methylation on chromosome 21. Here, we stably overexpressed the chromosome 21 gene DNA methyltransferase 3L (DNMT3L) in the human SH-SY5Y neuroblastoma cell line and assayed DNA methylation at over 26 million CpGs by whole genome bisulfite sequencing (WGBS) at three different developmental phases (undifferentiated, differentiating, and differentiated). Results DNMT3L overexpression resulted in global CpG and CpG island hypermethylation as well as thousands of differentially methylated regions (DMRs). The DNMT3L DMRs were skewed towards hypermethylation and mapped to genes involved in neurodevelopment, cellular signaling, and gene regulation. Consensus DNMT3L DMRs showed that cell lines clustered by genotype and then differentiation phase, demonstrating sets of common genes affected across neuronal differentiation. The hypermethylated DNMT3L DMRs from all pairwise comparisons were enriched for regions of bivalent chromatin marked by H3K4me3 as well as differentially methylated sites from previous DS studies of diverse tissues. In contrast, the hypomethylated DNMT3L DMRs from all pairwise comparisons displayed a tissue-specific profile enriched for regions of heterochromatin marked by H3K9me3 during embryonic development. Conclusions Taken together, these results support a mechanism whereby regions of bivalent chromatin that lose H3K4me3 during neuronal differentiation are targeted by excess DNMT3L and become hypermethylated. Overall, these findings demonstrate that DNMT3L overexpression during neurodevelopment recreates a facet of the genome-wide DS DNA methylation signature by targeting known genes and gene clusters that display pan-tissue differential methylation in DS.

scholarly journals Atlas of Age- and Tissue-specific DNA Methylation during Early Development of Barley (Hordeum vulgare)

2018 ◽  
Author(s):  
Moumouni Konate ◽  
Michael J. Wilkinson ◽  
Banjamin Mayne ◽  
Eileen Scott ◽  
Bettina Berger ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Hordeum Vulgare ◽  
Organ Function ◽  
Tissue Specific ◽  
Organ Differentiation ◽  
Differentiated Cells ◽  
Differentially Methylated Genes ◽  
Organ Specific ◽  
Development And Differentiation ◽  
Methylation Patterns

The barley (Hordeum vulgare) genome comprises over 32,000 genes, with differentiated cells expressing only a subset of genes; the remainder being silent. Mechanisms by which tissue-specific genes are regulated are not entirely understood, although DNA methylation is likely to be involved. DNA methylation patterns are not static during plant development, but it is still unclear whether different organs possess distinct methylation profiles. Methylation-sensitive GBS was used to generate DNA methylation profiles for roots, leaf-blades and leaf-sheaths from five barley varieties, using seedlings at the three-leaf stage. Differentially Methylated Markers (DMMs) were characterised by pairwise comparisons of roots, leaf-blades and leaf-sheaths of three different ages. While very many DMMs were found between roots and leaf parts, only a few existed between leaf-blades and leaf-sheaths, with differences decreasing with leaf rank. Organ-specific DMMs appeared to target mainly repeat regions, implying that organ differentiation partially relies on the spreading of DNA methylation from repeats to promoters of adjacent genes. Furthermore, the biological functions of differentially methylated genes in the different organs correlated with functional specialisation. Our results indicate that different organs do possess diagnostic methylation profiles and suggest that DNA methylation is important for both tissue development and differentiation and organ function.

Stage-differentiated modelling of DNA methylation landscapes uncovers salient biomarkers and prognostic signatures in colorectal cancer progression

2021 ◽  
Author(s):  
Sangeetha Muthamilselvan ◽  
Abirami Raghavendran ◽  
Ashok Palaniappan
Keyword(s):  
Colorectal Cancer ◽  
Dna Methylation ◽  
Cpg Island ◽  
Early Stage ◽  
P Value ◽  
Consensus Analysis ◽  
One Stage ◽  
Differentially Methylated Genes ◽  
Methylation Patterns ◽  
The Impact

Abstract Background: Aberrant DNA methylation acts epigenetically to skew the gene transcription rate up or down, with causative roles in the etiology of cancers. However research on the role of DNA methylation in driving the progression of cancers is limited. In this study, we have developed a comprehensive computational framework for the stage-differentiated modelling of DNA methylation landscapes in colorectal cancer (CRC), and unravelled significant stagewise signposts of CRC progression. Methods: The methylation β - matrix was derived from the public-domain TCGA data, converted into M-value matrix, annotated with AJCC stages, and analysed for stage-salient genes using multiple approaches involving stage-differentiated linear modelling of methylation patterns and/or expression patterns. Differentially methylated genes (DMGs) were identified using a contrast against controls (adjusted p-value <0.001 and |log fold-change of M-value| >2). These results were filtered using a series of all possible pairwise stage contrasts (p-value <0.05) to obtain stage-salient DMGs. These were then subjected to a consensus analysis, followed by Kaplan–Meier survival analysis to evaluate the impact of methylation patterns of consensus stage-salient biomarkers on disease prognosis.Results: We found significant genome-wide changes in methylation patterns in cancer cases relative to controls agnostic of stage. Our stage-differentiated analysis yielded the following stage-salient genes: one stage-I gene (FBN1), one stage-II gene (FOXG1), one stage-III gene (HCN1) and four stage-IV genes (NELL1, ZNF135, FAM123A, LAMA1). All the biomarkers were hypermethylated, indicating down-regulation and signifying a CpG island Methylator Phenotype (CIMP) manifestation. A significant prognostic signature consisting of FBN1 and FOXG1 survived all the steps of our analysis pipeline, and represents a novel early-stage biomarker. Conclusions: We have designed a workflow for stage-differentiated consensus analysis, and identified stage-salient diagnostic biomarkers and an early-stage prognostic biomarker panel. Our studies further yield a novel CIMP-like signature of potential clinical import underlying CRC progression.

scholarly journals DNA Methylation of Endoglin Pathway Genes in Pregnant Women With and Without Preeclampsia

2020 ◽  
Vol 13 ◽  
pp. 251686572095968
Author(s):  
Allison H Rietze ◽  
Yvette P Conley ◽  
Dianxu Ren ◽  
Cindy M Anderson ◽  
James M Roberts ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Transforming Growth Factor Beta ◽  
Transforming Growth Factor ◽  
Cpg Island ◽  
Methylation Status ◽  
Cpg Islands ◽  
Control Participant ◽  
Sample Collection ◽  
Promoter Regions ◽  
Participant Group

Objective: We compared blood-based DNA methylation levels of endoglin ( ENG) and transforming growth factor beta receptor 2 ( TGFβR2) gene promoter regions between women with clinically-overt preeclampsia and women with uncomplicated, normotensive pregnancies. Methods: We used EpiTect Methyl II PCR Assays to evaluate DNA methylation of CpG islands located in promoter regions of ENG (CpG Island 114642) and TGFβR2 (CpG Island 110111). Preeclampsia was diagnosed based on blood pressure, protein, and uric acid criteria. N = 21 nulliparous preeclampsia case participants were 1:1 frequency matched to N = 21 nulliparous normotensive control participants on gestational age at sample collection (±2 weeks), smoking status, and labor status at sample collection. Methylation values were compared between case and control participant groups [( ENG subset: n = 20 (9 cases, 11 controls); TGFβR2 subset: n = 28 (15 cases, 13 controls)]. Results: The majority of the preeclampsia cases delivered at ⩾34 weeks’ gestation (83%). Average methylation levels for ENG ([M ± (SD)]; Case Participant Group = 6.54% ± 4.57 versus Control Participant group = 4.81% ± 5.08; P = .102) and TGFβR2 (Case Participant Group = 1.50% ± 1.37 vs Control Participant Group = 1.70% ± 1.40; P = .695) promoter CpG islands did not differ significantly between the participant groups. Removal of 2 extreme outliers in the ENG analytic subset revealed a trend between levels of ENG methylation and pregnancy outcome (Case Participant Group = 5.17% ± 2.16 vs Control Participant Group = 3.36% ± 1.73; P = .062). Conclusion: Additional epigenetic studies that include larger sample sizes, investigate preeclampsia subtypes, and capture methylation status of CpG island shores and shelves are needed to further inform us of the potential role that ENG and TGFβR2 DNA methylation plays in preeclampsia pathophysiology.

Genome-Wide DNA Methylation Analysis Shows Enrichment of Differential Methylation in “Open Seas” and Enhancers and Reveals Hypomethylation in DNMT3A Mutated Cytogenetically Normal AML (CN-AML)

Blood ◽  
2012 ◽  
Vol 120 (21) ◽  
pp. 653-653 ◽  
Author(s):  
Ying Qu ◽  
Andreas Lennartsson ◽  
Verena I. Gaidzik ◽  
Stefan Deneberg ◽  
Sofia Bengtzén ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Cpg Island ◽  
Cpg Islands ◽  
Differential Methylation ◽  
Methylation Analysis ◽  
Cpg Sites ◽  
Genome Wide ◽  
Genomic Regions ◽  
Methylation Patterns

Abstract Abstract 653 DNA methylation is involved in multiple biologic processes including normal cell differentiation and tumorigenesis. In AML, methylation patterns have been shown to differ significantly from normal hematopoietic cells. Most studies of DNA methylation in AML have previously focused on CpG islands within the promoter of genes, representing only a very small proportion of the DNA methylome. In this study, we performed genome-wide methylation analysis of 62 AML patients with CN-AML and CD34 positive cells from healthy controls by Illumina HumanMethylation450K Array covering 450.000 CpG sites in CpG islands as well as genomic regions far from CpG islands. Differentially methylated CpG sites (DMS) between CN-AML and normal hematopoietic cells were calculated and the most significant enrichment of DMS was found in regions more than 4kb from CpG Islands, in the so called open sea where hypomethylation was the dominant form of aberrant methylation. In contrast, CpG islands were not enriched for DMS and DMS in CpG islands were dominated by hypermethylation. DMS successively further away from CpG islands in CpG island shores (up to 2kb from CpG Island) and shelves (from 2kb to 4kb from Island) showed increasing degree of hypomethylation in AML cells. Among regions defined by their relation to gene structures, CpG dinucleotide located in theoretic enhancers were found to be the most enriched for DMS (Chi χ2<0.0001) with the majority of DMS showing decreased methylation compared to CD34 normal controls. To address the relation to gene expression, GEP (gene expression profiling) by microarray was carried out on 32 of the CN-AML patients. Totally, 339723 CpG sites covering 18879 genes were addressed on both platforms. CpG methylation in CpG islands showed the most pronounced anti-correlation (spearman ρ =-0.4145) with gene expression level, followed by CpG island shores (mean spearman rho for both sides' shore ρ=-0.2350). As transcription factors (TFs) have shown to be crucial for AML development, we especially studied differential methylation of an unbiased selection of 1638 TFs. The most enriched differential methylation between CN-AML and normal CD34 positive cells were found in TFs known to be involved in hematopoiesis and with Wilms tumor protein-1 (WT1), activator protein 1 (AP-1) and runt-related transcription factor 1 (RUNX1) being the most differentially methylated TFs. The differential methylation in WT 1 and RUNX1 was located in intragenic regions which were confirmed by pyro-sequencing. AML cases were characterized with respect to mutations in FLT3, NPM1, IDH1, IDH2 and DNMT3A. Correlation analysis between genome wide methylation patterns and mutational status showed statistically significant hypomethylation of CpG Island (p<0.0001) and to a lesser extent CpG island shores (p<0.001) and the presence of DNMT3A mutations. This links DNMT3A mutations for the first time to a hypomethylated phenotype. Further analyses correlating methylation patterns to other clinical data such as clinical outcome are ongoing. In conclusion, our study revealed that non-CpG island regions and in particular enhancers are the most aberrantly methylated genomic regions in AML and that WT 1 and RUNX1 are the most differentially methylated TFs. Furthermore, our data suggests a hypomethylated phenotype in DNMT3A mutated AML. Disclosures: No relevant conflicts of interest to declare.

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