scholarly journals THU0005 VARIABILITY OF DNA METHYLATION IS A DRIVER OF LYMPHOCYTE DYSREGULATION IN EARLY RHEUMATOID ARTHRITIS.

2020 ◽  
Vol 79 (Suppl 1) ◽  
pp. 215.2-215
Author(s):  
A. Clark ◽  
N. Naamane ◽  
N. Nair ◽  
A. Anderson ◽  
N. Thalayasingam ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Systemic Inflammation ◽  
Cell Subset ◽  
Hypergeometric Test ◽  
Cell Type ◽  
Multiple Test Correction ◽  
Multiple Test ◽  
Methylation Patterns ◽  
The Impact ◽  
Cd4 Lymphocytes

Background:DNA methylation patterns differ between leukocyte subsets and mediate the impact of environmental exposures on the molecular and functional phenotype of immune cells. Besides differences in mean methylation of CpG positions amongst patients with immune mediated diseases, recent evidence indicates variability of site-specific DNA methylation also contributes to pathogenesis1,2.Objectives:To seek evidence of altered DNA methylation patterns in RA, controlling for systemic inflammation and immunotherapy use.Methods:Patients with confirmed clinical diagnoses were enrolled from the Northeast Early Arthritis Cohort (NEAC). CD4+and CD19+lymphocytes were isolated from fresh blood by positive selection prior to therapeutic immune modulation. Methylation was quantified in cell subset-specific DNA (Infinium MethylationEPIC BeadChip, Illumina)3. Differentially methylated positions and regions (DMPs, DMRs) between RA and non-RA patients were identified (linear modelling, filtering on 5% pairwise difference in mean DNA methylation, and DMRcate package). Next, to identify instances where methylation variance differed between comparator groups, Bartlett’s test was performed using the iEVORA package, which accounts for outlier values4. Findings were controlled for technical confounders and subject to multiple test correction (FDR). A validated hypergeometric test was used to annotate enriched pathways.Results:After sample- and probe-level quality control, CD4+ and B lymphocyte specific data were respectively available for 45 and 49 RA patients, and 64 and 81 disease controls matched for systemic inflammation (CRP, ESR). No DMPs were identified in either cell type at FDR < 0.05 and Δβ ≥0.05. Only following relaxation of multiple test correction was it possible to identify DMRs in either cell type, most notably encapsulating 10 CpGs relatively hypomethylated at the promoter of the endosome protein-encodingRUFY1gene in CD4+ lymphocytes of RA patients (Δβ = 0.076). By contrast, striking evidence for differential variation in DNA methylation was observed at 291 and 601 CpGs of CD4+ and B lymphocytes, respectively (exemplars depicted in Figure 1). Only 15 of these differentially variable positions (DVPs) were common to both cell types. Pathway analysis highlighted potential functional consequences of DVP associations; for example, RA-specific hypervariability implicates prostaglandinsignalling in CD4+ lymphocytes.Conclusion:We highlight a role for altered variability in DNA methylation during the molecular pathogenesis of RA, and emphasise the importance of its study in relevant cell subsets.References:[1]Paul DSet al. Nature Communications 7, 13555 doi: 10.1038/ncomms13555 (2016).[2]Webster AP et al. Genome Medicine 10, 64 (2018)doi:10.1186/s13073-018-0575-9.[3]Clark AD et al. Journal of Allergy and Clinical Immunology 2019; doi: 10.1016/j.jaci.2019.12.910[4]Teschendorff AE et al. Nature Communications 2016; 7:12.Disclosure of Interests:Alexander Clark: None declared, Najib Naamane: None declared, Nisha Nair: None declared, Amy Anderson: None declared, Nishanthi Thalayasingam: None declared, Julie Diboll: None declared, Anne Barton Consultant of: AbbVie, Stephen Eyre: None declared, John D Isaacs Consultant of: AbbVie, Bristol-Myers Squibb, Eli Lilly, Gilead, Janssen, Merck, Pfizer, Roche, Louise Reynard: None declared, Arthur Pratt Grant/research support from: Pfizer, GlaxoSmithKlein

scholarly journals Differences in DNA methylation of white blood cell types at birth and in adulthood reflect postnatal immune maturation and influence accuracy of cell type prediction

2018 ◽  
Author(s):  
Meaghan J Jones ◽  
Louie Dinh ◽  
Hamid Reza Razzaghian ◽  
Olivia de Goede ◽  
Julia L MacIsaac ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Immune System ◽  
Blood Cell ◽  
Cord Blood ◽  
White Blood Cell ◽  
Blood Cells ◽  
Cell Types ◽  
Cell Type ◽  
Cell Type Specific ◽  
The Impact

AbstractBackgroundDNA methylation profiling of peripheral blood leukocytes has many research applications, and characterizing the changes in DNA methylation of specific white blood cell types between newborn and adult could add insight into the maturation of the immune system. As a consequence of developmental changes, DNA methylation profiles derived from adult white blood cells are poor references for prediction of cord blood cell types from DNA methylation data. We thus examined cell-type specific differences in DNA methylation in leukocyte subsets between cord and adult blood, and assessed the impact of these differences on prediction of cell types in cord blood.ResultsThough all cell types showed differences between cord and adult blood, some specific patterns stood out that reflected how the immune system changes after birth. In cord blood, lymphoid cells showed less variability than in adult, potentially demonstrating their naïve status. In fact, cord CD4 and CD8 T cells were so similar that genetic effects on DNA methylation were greater than cell type effects in our analysis, and CD8 T cell frequencies remained difficult to predict, even after optimizing the library used for cord blood composition estimation. Myeloid cells showed fewer changes between cord and adult and also less variability, with monocytes showing the fewest sites of DNA methylation change between cord and adult. Finally, including nucleated red blood cells in the reference library was necessary for accurate cell type predictions in cord blood.ConclusionChanges in DNA methylation with age were highly cell type specific, and those differences paralleled what is known about the maturation of the postnatal immune system.

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 The Impact of Natural Dietary Compounds and Food-Borne Mycotoxins on DNA Methylation and Cancer

Cells ◽  
2020 ◽  
Vol 9 (9) ◽  
pp. 2004 ◽  
Author(s):  
Terisha Ghazi ◽  
Thilona Arumugam ◽  
Ashmika Foolchand ◽  
Anil A. Chuturgoon
Keyword(s):  
Dna Methylation ◽  
Bioactive Compounds ◽  
Epigenetic Modification ◽  
Bioactive Molecules ◽  
Methyl Donors ◽  
Food Borne ◽  
One Carbon Metabolism ◽  
Aberrant Dna Methylation ◽  
Methylation Patterns ◽  
The Impact

Cancer initiation and progression is an accumulation of genetic and epigenetic modifications. DNA methylation is a common epigenetic modification that regulates gene expression, and aberrant DNA methylation patterns are considered a hallmark of cancer. The human diet is a source of micronutrients, bioactive molecules, and mycotoxins that have the ability to alter DNA methylation patterns and are thus a contributing factor for both the prevention and onset of cancer. Micronutrients such as betaine, choline, folate, and methionine serve as cofactors or methyl donors for one-carbon metabolism and other DNA methylation reactions. Dietary bioactive compounds such as curcumin, epigallocatechin-3-gallate, genistein, quercetin, resveratrol, and sulforaphane reactivate essential tumor suppressor genes by reversing aberrant DNA methylation patterns, and therefore, they have shown potential against various cancers. In contrast, fungi-contaminated agricultural foods are a source of potent mycotoxins that induce carcinogenesis. In this review, we summarize the existing literature on dietary micronutrients, bioactive compounds, and food-borne mycotoxins that affect DNA methylation patterns and identify their potential in the onset and treatment of cancer.

Neuronal cell‐type specific DNA methylation patterns of the Cacna1c gene

2012 ◽  
Vol 31 (2) ◽  
pp. 89-95 ◽  
Author(s):  
Masaki Nishioka ◽  
Takafumi Shimada ◽  
Miki Bundo ◽  
Wataru Ukai ◽  
Eri Hashimoto ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Neuronal Cell ◽  
Cell Type ◽  
Cell Type Specific ◽  
Methylation Patterns

Genome-Wide DNA Methylation Profiling of Hematopoietic Stem and Progenitor Cells Reveals Over-Representation of ETS Transcrition Factor Binding Sites

Blood ◽  
2011 ◽  
Vol 118 (21) ◽  
pp. 211-211
Author(s):  
Amber Hogart ◽  
Jens Lichtenberg ◽  
Subramanian Ajay ◽  
Elliott Margulies ◽  
David M. Bodine
Keyword(s):  
Dna Methylation ◽  
Transcription Factor ◽  
Cpg Islands ◽  
Hematopoietic Cells ◽  
Cell Type ◽  
Hematopoietic Stem ◽  
Genome Wide ◽  
Cell Type Specific ◽  
Methylation Patterns

Abstract Abstract 211 The hematopoietic system is ideal for the study of epigenetic changes in primary cells because hematopoietic cells representing distinct stages of hematopoiesis can be enriched and isolated by differences in surface marker expression. DNA methylation is an essential epigenetic mark that is required for normal development. Conditional knockout of the DNA methyltransferase enzymes in the mouse hematopoietic compartment have revealed that methylation is critical for long-term renewal and lineage differentiation of hematopoietic stem cells (Broske et al 2009, Trowbridge el al 2009). To better understand the role of DNA methylation in self-renewal and differentiation of hematopoietic cells, we characterized genome-wide DNA methylation in primary cells representing three distinct stages of hematopoiesis. We isolated mouse hematopoietic stem cells (HSC; Lin- Sca-1+ c-kit+), common myeloid progenitor cells (CMP; Lin- Sca-1- c-kit+), and erythroblasts (ERY; CD71+ Ter119+). Methyl Binding Domain Protein 2 (MBD2) is an endogenous reader of DNA methylation that recognizes DNA with a high concentration of methylated CpG residues. Recombinant MBD2 enrichment of DNA followed by massively-parallel sequencing was used to map and compare genome-wide DNA methylation patterns in HSC, CMP and ERY. Two biological replicates were sequenced for each cell type with total read counts ranging from 32,309,435–46,763,977. Model-based analysis of ChIP Seq (MACS) with a significance cutoff of p<10−5 was used to determine statistically significant peaks of methylation in each replicate. Globally, the number of methylation peaks was highest in HSC (85,797peaks), lower in CMP (50,638 peaks), and lowest in ERY (27,839 peaks). Comparison of the peaks in HSC, CMP and ERY revealed that only 2% of the peaks in CMP or ERY are absent in HSC indicating that the vast majority of methylation in HSC is lost during differentiation. Comparison of methylation with genomic features revealed that CpG islands associated with promoters are hypomethylated, while many non-promoter CpG islands are methylated. Furthermore, methylation of non-promoter associated CpG islands occurs infrequently in cell-type specific peaks but is more abundant in common methylation peaks. When the DNA methylation patterns were compared to mRNA expression, we found that as expected, proximal promoter sequences of expressed genes were hypomethylated in all three cell types, while methylation in the gene body positively correlated with gene expression in HSC and CMP. Utilizing de novo motif discovery we found a subset of transcription factor consensus binding motifs that were overrepresented in methylated sequences. Motifs for several ETS transcription factors, including GABPalpha and ELF1 were found to be overrepresented in cell-type specific as well as common methylated regions. Other transcription factor consensus sites, such as the NFAT factors involved in T-cell activation, were specifically overrepresented in the methylated promoter regions of CMP and ERY. Comparison of our methylation data with the occupancy of hematopoietic transcription factors in the HPC7 cell line, which is similar to CMP (Wilson et al 2010), revealed a significant anti-correlation between DNA methylation and the binding of Fli1, Lmo2, Lyl1, Runx1, and Scl. Our genome-wide survey provides new insights into the role of DNA methylation in hematopoiesis. Firstly, the methylation of CpG islands is associated with the most primitive hematopoietic cells and is unlikely to drive hematopoietic differentiation. We feel that the elevated genome-wide DNA methylation in HSC compared to CMP and ERY, combined with the positive association between gene body methylation and gene expression demonstrates that DNA methylation is a mark of cellular plasticity in HSC. Finally, the finding that transcription factor binding sites are over represented in the methylated sequences of the genome leads us to conclude that DNA methylation modulates key hematopoietic transcription factor programs that regulate hematopoiesis. Disclosures: No relevant conflicts of interest to declare.

scholarly journals DNA Methylation Changes Induced by Redox-Active Compounds—Choosing the Right PCR-Based Method

Proceedings ◽  
2019 ◽  
Vol 11 (1) ◽  
pp. 20
Author(s):  
Patrycja Jakubek ◽  
Jovana Rajić ◽  
Monika Baranowska ◽  
Melita Vidaković ◽  
Agnieszka Bartoszek ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Ht29 Cell ◽  
Pcr Array ◽  
Down Regulation ◽  
Redox Active ◽  
The Right ◽  
Methylation Patterns ◽  
The Impact ◽  
Proper Strategy ◽  
Ht29 Cell Line

The impact of catechins on the expression profile of redox-related genes in HT29 cell line has been studied recently by our group using Oxidative Stress RT2 Profiler PCR Array. Within the examined panel of 84 genes, the down-regulation of SRXN1 gene was unique among other up-regulated genes. We hypothesized that the observed down-regulation resulted from DNA methylation and have exploited this observation to choose the proper strategy to monitor the changes in DNA methylation patterns incurred by dietary antioxidants. The current study verified two PCR-based approaches.

scholarly journals Differential DNA methylation patterns of homeobox genes in proximal and distal colon epithelial cells

2016 ◽  
Vol 48 (4) ◽  
pp. 257-273 ◽  
Author(s):  
Alan Barnicle ◽  
Cathal Seoighe ◽  
Aaron Golden ◽  
John M. Greally ◽  
Laurence J. Egan
Keyword(s):  
Colorectal Cancer ◽  
Dna Methylation ◽  
Epithelial Cells ◽  
Distal Colon ◽  
Human Colon ◽  
Differential Methylation ◽  
Cell Type ◽  
Cell Type Specific ◽  
Inflammatory Bowel ◽  
Methylation Patterns

Region and cell-type specific differences in the molecular make up of colon epithelial cells have been reported. Those differences may underlie the region-specific characteristics of common colon epithelial diseases such as colorectal cancer and inflammatory bowel disease. DNA methylation is a cell-type specific epigenetic mark, essential for transcriptional regulation, silencing of repetitive DNA and genomic imprinting. Little is known about any region-specific variations in methylation patterns in human colon epithelial cells. Using purified epithelial cells and whole biopsies ( n = 19) from human subjects, we generated epigenome-wide DNA methylation data (using the HELP-tagging assay), comparing the methylation signatures of the proximal and distal colon. We identified a total of 125 differentially methylated sites (DMS) mapping to transcription start sites of protein-coding genes, most notably several members of the homeobox ( HOX) family of genes. Patterns of differential methylation were validated with MassArray EpiTYPER. We also examined DNA methylation in whole biopsies, applying a computational technique to deconvolve variation in methylation within cell types and variation in cell-type composition across biopsies. Including inferred epithelial proportions as a covariate in differential methylation analysis applied to the whole biopsies resulted in greater overlap with the results obtained from purified epithelial cells compared with when the covariate was not included. Results obtained from both approaches highlight region-specific methylation patterns of HOX genes in colonic epithelium. Regional variation in methylation patterns has implications for the study of diseases that exhibit regional expression patterns in the human colon, such as inflammatory bowel disease and colorectal cancer.

scholarly journals Developmental subtypes assessed by DNA methylation-iPLEX forecast the natural history of chronic lymphocytic leukemia

Blood ◽  
2019 ◽  
Vol 134 (8) ◽  
pp. 688-698 ◽  
Author(s):  
Brian Giacopelli ◽  
Qiuhong Zhao ◽  
Amy S. Ruppert ◽  
Akwasi Agyeman ◽  
Christoph Weigel ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Chronic Lymphocytic Leukemia ◽  
Risk Stratification ◽  
Kinase Inhibitor ◽  
Lymphocytic Leukemia ◽  
Biological Traits ◽  
Elegant Method ◽  
Mutational Status ◽  
Methylation Patterns ◽  
The Impact

Abstract Alterations in global DNA methylation patterns are a major hallmark of cancer and represent attractive biomarkers for personalized risk stratification. Chronic lymphocytic leukemia (CLL) risk stratification studies typically focus on time to first treatment (TTFT), time to progression (TTP) after treatment, and overall survival (OS). Whereas TTFT risk stratification remains similar over time, TTP and OS have changed dramatically with the introduction of targeted therapies, such as the Bruton tyrosine kinase inhibitor ibrutinib. We have shown that genome-wide DNA methylation patterns in CLL are strongly associated with phenotypic differentiation and patient outcomes. Here, we developed a novel assay, termed methylation-iPLEX (Me-iPLEX), for high-throughput quantification of targeted panels of single cytosine guanine dinucleotides from multiple independent loci. Me-iPLEX was used to classify CLL samples into 1 of 3 known epigenetic subtypes (epitypes). We examined the impact of epitype in 1286 CLL patients from 4 independent cohorts representing a comprehensive view of CLL disease course and therapies. We found that epitype significantly predicted TTFT and OS among newly diagnosed CLL patients. Additionally, epitype predicted TTP and OS with 2 common CLL therapies: chemoimmunotherapy and ibrutinib. Epitype retained significance after stratifying by biologically related biomarkers, immunoglobulin heavy chain mutational status, and ZAP70 expression, as well as other common prognostic markers. Furthermore, among several biological traits enriched between epitypes, we found highly biased immunogenetic features, including IGLV3-21 usage in the poorly characterized intermediate-programmed CLL epitype. In summary, Me-iPLEX is an elegant method to assess epigenetic signatures, including robust classification of CLL epitypes that independently stratify patient risk at diagnosis and time of treatment.

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