Epigenetics In Autoimmune Disease

2018 ◽  
Author(s):  
Matlock A Jeffries
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Autoimmune Disease ◽  
Noncoding Rna ◽  
Specific Treatment ◽  
Cell Types ◽  
Response To Therapy ◽  
Human Immune System ◽  
Treatment Regimens ◽  
New Research

Autoimmunity refers to a pathologic state of immunologic dysregulation in which the human immune system turns inward, attacking healthy tissues. The key step in this process is a break of self-immune tolerance. Recent studies have implicated dysregulation of gene expression via altered epigenetic control as a key mechanism in the development and promotion of autoimmunity. Epigenetics is defined as heritable changes in gene expression as a result of modification of DNA methylation, histone side chains, and noncoding RNA. Studies examining identical twins discordant for lupus, for example, were among the first to identify alterations in DNA methylation leading to lupus. Histone side-chain changes have been studied extensively in rheumatoid arthritis (RA), and many pathogenic cell types in RA exhibit a hyperacetylation phenotype. Finally, new research in the noncoding RNA field has not only uncovered potentially targetable pathways (e.g., miR-155) but may lead to the development of new diagnostic and prognostic biomarkers, helping physicians better tailor specific treatment regimens to improve response to therapy in autoimmune disease.   This review contains 4 figures, 1 table and 47 references Key Words: autoimmunity, big data, biomarkers, computational biology, DNA methylation, epigenetics, histone acetylation, histone methylation, microRNA, noncoding RNA

scholarly journals Insights Into the Role of DNA Methylation in Immune Cell Development and Autoimmune Disease

2021 ◽  
Vol 9 ◽  
Author(s):  
Jiaqi Li ◽  
Lifang Li ◽  
Yimeng Wang ◽  
Gan Huang ◽  
Xia Li ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Autoimmune Disease ◽  
Autoimmune Diseases ◽  
Immune Cell ◽  
Gene Expression Regulation ◽  
Cell Types ◽  
Basic Function ◽  
Detailed Knowledge ◽  
Disease Pathogenesis

To date, nearly 100 autoimmune diseases have been an area of focus, and these diseases bring health challenges to approximately 5% of the population worldwide. As a type of disease caused by tolerance breakdown, both environmental and genetic risk factors contribute to autoimmune disease development. However, in most cases, there are still gaps in our understanding of disease pathogenesis, diagnosis, and treatment. Therefore, more detailed knowledge of disease pathogenesis and potential therapies is indispensable. DNA methylation, which does not affect the DNA sequence, is one of the key epigenetic silencing mechanisms and has been indicated to play a key role in gene expression regulation and to participate in the development of certain autoimmune diseases. Potential epigenetic regulation via DNA methylation has garnered more attention as a disease biomarker in recent years. In this review, we clarify the basic function and distribution of DNA methylation, evaluate its effects on gene expression and discuss related key enzymes. In addition, we summarize recent aberrant DNA methylation modifications identified in the most important cell types related to several autoimmune diseases and then provide potential directions for better diagnosing and monitoring disease progression driven by epigenetic control, which may broaden our understanding and contribute to further epigenetic research in autoimmune diseases.

scholarly journals GSDMA drives the most replicated association with asthma in naïve CD4+ T cells

2019 ◽  
Author(s):  
Anne-Marie Madore ◽  
Lucile Pain ◽  
Anne-Marie Boucher-Lafleur ◽  
Jolyane Meloche ◽  
Andréanne Morin ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
T Cells ◽  
Genetic Variants ◽  
Immune Cell ◽  
Cell Types ◽  
Sequencing Data ◽  
Opposite Pattern ◽  
Genetic Mechanisms ◽  
New Gene

AbstractBackgroundThe 17q12-21 locus is the most replicated association with asthma. However, no study had described the genetic mechanisms underlying this association considering all genes of the locus in immune cell samples isolated from asthmatic and non-asthmatic individuals.ObjectiveThis study takes benefit of samples from naïve CD4+ T cells and eosinophils isolated from the same 200 individuals to describe specific interactions between genetic variants, gene expression and DNA methylation levels for the 17q12-21 asthma locus.Methods and ResultsAfter isolation of naïve CD4+ T cells and eosinophils from blood samples, next generation sequencing was used to measure DNA methylation levels and gene expression counts. Genetic interactions were then evaluated considering genetic variants from imputed genotype data. In naïve CD4+ T cells but not eosinophils, 20 SNPs in the fourth and fifth haplotype blocks modulated both GSDMA expression and methylation levels, showing an opposite pattern of allele frequencies and expression counts in asthmatics compared to controls. Moreover, negative correlations have been measured between methylation levels of CpG sites located within the 1.5 kb region from the transcription start site of GSDMA and its expression counts.ConclusionAvailability of sequencing data from two key cell types isolated from asthmatic and non-asthmatic individuals allowed identifying a new gene in naïve CD4+ T cells that drives the association with the 17q12-21 locus, leading to a better understanding of the genetic mechanisms taking place in it.

scholarly journals Simultaneous enumeration of cancer and immune cell types from bulk tumor gene expression data

eLife ◽  
2017 ◽  
Vol 6 ◽  
Author(s):  
Julien Racle ◽  
Kaat de Jonge ◽  
Petra Baumgaertner ◽  
Daniel E Speiser ◽  
David Gfeller
Keyword(s):  
Gene Expression ◽  
Gene Expression Data ◽  
Immune Cell ◽  
Expression Profiles ◽  
Cell Types ◽  
Response To Therapy ◽  
Expression Data ◽  
Cell Type ◽  
Tumor Gene Expression ◽  
Tumor Gene

Immune cells infiltrating tumors can have important impact on tumor progression and response to therapy. We present an efficient algorithm to simultaneously estimate the fraction of cancer and immune cell types from bulk tumor gene expression data. Our method integrates novel gene expression profiles from each major non-malignant cell type found in tumors, renormalization based on cell-type-specific mRNA content, and the ability to consider uncharacterized and possibly highly variable cell types. Feasibility is demonstrated by validation with flow cytometry, immunohistochemistry and single-cell RNA-Seq analyses of human melanoma and colorectal tumor specimens. Altogether, our work not only improves accuracy but also broadens the scope of absolute cell fraction predictions from tumor gene expression data, and provides a unique novel experimental benchmark for immunogenomics analyses in cancer research (http://epic.gfellerlab.org).

scholarly journals Exosomal miRNA: Small Molecules, Big Impact in Colorectal Cancer

2019 ◽  
Vol 2019 ◽  
pp. 1-18 ◽  
Author(s):  
Valentin Vautrot ◽  
Gaëtan Chanteloup ◽  
Mohammed Elmallah ◽  
Marine Cordonnier ◽  
François Aubin ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Cancer Biology ◽  
Noncoding Rna ◽  
Cell Types ◽  
Response To Therapy ◽  
Bioactive Molecules ◽  
Premetastatic Niche ◽  
Rna Molecules ◽  
Small Noncoding Rna ◽  
Exosomal Mirna

Colorectal cancer (CRC) is one of the major causes of cancer-related deaths worldwide. Tumor microenvironment (TME) contains many cell types including stromal cells, immune cells, and endothelial cells. The TME modulation explains the heterogeneity of response to therapy observed in patients. In this context, exosomes are emerging as major contributors in cancer biology. Indeed, exosomes are implicated in tumor proliferation, angiogenesis, invasion, and premetastatic niche formation. They contain bioactive molecules such as proteins, lipids, and RNAs. More recently, many studies on exosomes have focused on miRNAs, small noncoding RNA molecules able to influence protein expression. In this review, we describe miRNAs transported by exosomes in the context of CRC and discuss their influence on TME and their potential as circulating biomarkers. This overview underlines emerging roles for exosomal miRNAs in cancer research for the near future.

scholarly journals Global Modulation in DNA Epigenetics during Pro-Inflammatory Macrophage Activation

2019 ◽  
Author(s):  
Nikhil Jain ◽  
Tamar Shahal ◽  
Tslil Gabrieli ◽  
Noa Gilat ◽  
Dmitry Torchinsky ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Single Molecule ◽  
Transcriptional Control ◽  
Excision Repair ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Cell Types ◽  
Inflammatory Activation ◽  
Methylation Patterns

AbstractDNA methylation patterns create distinct gene expression profiles. These patterns are maintained after cell division, thus enabling the differentiation and maintenance of multiple cell types from the same genome sequence. The advantage of this mechanism for transcriptional control is that chemical-encoding allows to rapidly establish new epigenetic patterns “on-demand” through enzymatic methylation and de-methylation of DNA. Here we show that this feature is associated with the fast response of macrophages during their pro-inflammatory activation. By using a combination of mass spectroscopy and single-molecule imaging to quantify global epigenetic changes in the genomes of primary macrophages, we followed three distinct DNA marks (methylated, hydroxymethylated and unmethylated), involved in establishing new DNA methylation patterns during pro-inflammatory activation. The observed epigenetic modulation together with gene expression data generated for the involved enzymatic machinery, may suggest that de-methylation upon LPS-activation starts with oxidation of methylated CpGs, followed by excision-repair of these oxidized bases and their replacement with unmodified cytosine.

Analysis of DNA Methylation and Transcription During Granulopoiesis Reveals Timed Methylation Changes in Low CpG Areas That Correlate with Changed Transcriptional Activity.

Blood ◽  
2012 ◽  
Vol 120 (21) ◽  
pp. 2334-2334
Author(s):  
Rönnerblad Michelle ◽  
Olofsson Tor ◽  
Iyadh Douagi ◽  
Sören Lehmann ◽  
Karl Ekwall ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Conflicts Of Interest ◽  
Cell Types ◽  
Cpg Methylation ◽  
Epigenetic Mechanism ◽  
450K Array ◽  
Chi Square ◽  
Heterochromatin Formation ◽  
Chi Square Test

Abstract Abstract 2334 Accumulating evidence demonstrates that epigenetic changes, including DNA methylation play a central role in differentiation, providing cellular memory and stabilizing lineage choice in hematopoiesis1–3. DNA methylation is an important epigenetic mechanism involved in transcriptional regulation, heterochromatin formation and the normal development of many organisms. In this study we investigated the DNA methylome and transcriptome of human cells in four separate differentiation stages in granulopoiesis, ranging from the multipotent Common Myeloid progenitor (CMP) to terminally differentiated bone marrow neutrophils (PMN). To this end we employed HumanMethylation 450 BeadChip (450K array) from Illumina with extensive genomic coverage and mRNA expression arrays (Illumina). Temporally distinct methylation changes during granulopoiesis Differential methylation between two cell stages was defined as an average difference in β value of at least 0.17 (p ≤ 0.05). We detected 12132 DMSs during granulopoiesis. Of these the majority showed decreased methylation during granulopoeisis (10771 CpGs) and a smaller set gained methylation (1658 CpGs). Strikingly, increases in methylation predominantly occur between CMP and GMP, the two least mature cell types. Some CpGs also show increased methylation in the GMP-PMC transition, while very few CpG sites increase at the final stage of differentiation from PMC to PMN. Although reduction of methylation occurs at all stages of granulopoiesis, the greatest change is between GMP and PMC. It is striking that the DNA methylation patterns preferentially change at points of lineage restriction, and that the greatest change occurs upon loss of oligopotency between GMP and PMC. DMSs within CGIs were greatly underrepresented (p<0.001 with chi-square test), while DMSs were overrepresented in shelves (p<0.001) and open sea (p<0.001). Thus, methylation appears to be more dynamic outside of CGIs during granulocytic development. For all regions the variation within enhancers was greater than outside of enhancers indicating greater methylation changes in enhancers compared to non-enhancers. In addition, CpGs in enhancer regions are significantly enriched in the list of DMSs (p<0.001, chi-square test) further supporting the observation that enhancer regions display dynamic DNA methylation changes during granulopoiesis. Changes in gene expression correlate with DNA methylation changes There was a significant overlap between genes showing decreased methylation and genes with increased expression as well as for the reverse comparison between genes with increased methylation and decreased expression. Thus, support a general anticorrelation between DNA methylation and gene expression. Azurophilic granule proteins showed increased expression peaking in PMC and a rapid decrease toward PMN. CpG methylation levels for those genes decreased concomitantly with the peak in expression. We report cell population specific changes of DNA methylation levels. The main reduction of CpG methylation coincides with the loss of oligopotency at the transition from GMP-PMC. This suggests a role of DNA methylation in regulating cell plasticity and lineage choice. Disclosures: No relevant conflicts of interest to declare.

scholarly journals Hormonal regulation of H19 gene expression in prostate epithelial cells

2004 ◽  
Vol 183 (1) ◽  
pp. 69-78 ◽  
Author(s):  
N Berteaux ◽  
S Lottin ◽  
E Adriaenssens ◽  
F Van Coppenolle ◽  
X Leroy ◽  
...  
Keyword(s):  
Gene Expression ◽  
Hormonal Regulation ◽  
Noncoding Rna ◽  
Steroid Hormone ◽  
Calf Serum ◽  
Cancer Cell Line ◽  
Cell Types ◽  
Culture Conditions ◽  
Androgen Independence

The H19 gene is transcribed in an mRNA-like noncoding RNA. When tumors of various organs or cell types are considered, H19 oncogene or tumor-suppressor status remains controversial. To address the potential regulation of H19 gene expression by an androgen steroid hormone (DHT: dihydrotestosterone) or by a peptidic hormone (PRL: prolactin), we performed experiments in rats systemically treated with chemical mediators. This range of in vivo experiments demonstrated that chronic hyperprol-actinemia upregulated the H19 expression in epithelial and stromal cells whereas DHT downregulated the gene. PRL and DHT appeared to be opposite mediators in the H19 RNA synthesis. We investigated these hormonal effects in three human prostate epithelial cell lines. In LNCaP cancer cells, the opposite effect of PRL and DHT was corroborated. However, in normal cells (PNT1A), H19 remained insensitive to the hormones in fetal calf serum (FCS) medium but became responsive in a serum-stripped medium. In the DU-145 cancer cell line, tested for its androgen-independence and aggressiveness, the hormones had no effect on H19 expression whatever the culture conditions. Finally, we demonstrated that PRL upregulated the H19 expression in LNCaP cells by the JAK2–STAT5 transduction pathway. We conclude that H19 expression is regulated by both a peptidic and a male steroid hormone.

scholarly journals Integrative transcriptomic analysis of SLE reveals IFN-driven cross-talk between immune cells

2020 ◽  
Author(s):  
Bharat Panwar ◽  
Benjamin J. Schmiedel ◽  
Shu Liang ◽  
Brandie White ◽  
Enrique Rodriguez ◽  
...  
Keyword(s):  
Gene Expression ◽  
T Cells ◽  
Autoimmune Disease ◽  
Cross Talk ◽  
Immune Cell ◽  
Cell Types ◽  
Cell Populations ◽  
Multiple Cell ◽  
Classical Monocytes ◽  
Multiple Immune Cell

ABSTRACTThe systemic lupus erythematosus (SLE) is an incurable autoimmune disease disproportionately affecting women and may lead to damage in multiple different organs. The marked heterogeneity in its clinical manifestations is a major obstacle in finding targeted treatments and involvement of multiple immune cell types further increases this complexity. Thus, identifying molecular subtypes that best correlate with disease heterogeneity and severity as well as deducing molecular cross-talk among major immune cell types that lead to disease progression are critical steps in the development of more informed therapies for SLE. Here we profile and analyze gene expression of six major circulating immune cell types from patients with well-characterized SLE (classical monocytes (n=64), T cells (n=24), neutrophils (n=24), B cells (n=20), conventional (n=20) and plasmacytoid (n=22) dendritic cells) and from healthy control subjects. Our results show that the interferon (IFN) response signature was the major molecular feature that classified SLE patients into two distinct groups: IFN-signature negative (IFNneg) and positive (IFNpos). We show that the gene expression signature of IFN response was consistent (i) across all immune cell types, (ii) all single cells profiled from three IFNpos donors using single-cell RNA-seq, and (iii) longitudinal samples of the same patient. For a better understanding of molecular differences of IFNpos versus IFNneg patients, we combined differential gene expression analysis with differential Weighted Gene Co-expression Network Analysis (WGCNA), which revealed a relatively small list of genes from classical monocytes including two known immune modulators, one the target of an approved therapeutic for SLE (TNFSF13B/BAFF: belimumab) and one itself a therapeutic for Rheumatoid Arthritis (IL1RN: anakinra). For a more integrative understanding of the cross-talk among different cell types and to identify potentially novel gene or pathway connections, we also developed a novel gene co-expression analysis method for joint analysis of multiple cell types named integrated WGNCA (iWGCNA). This method revealed an interesting cross-talk between T and B cells highlighted by a significant enrichment in the expression of known markers of T follicular helper cells (Tfh), which also correlate with disease severity in the context of IFNpos patients. Interestingly, higher expression of BAFF from all myeloid cells also shows a strong correlation with enrichment in the expression of genes in T cells that may mark circulating Tfh cells or related memory cell populations. These cell types have been shown to promote B cell class-switching and antibody production, which are well-characterized in SLE patients. In summary, we generated a large-scale gene expression dataset from sorted immune cell populations and present a novel computational approach to analyze such data in an integrative fashion in the context of an autoimmune disease. Our results reveal the power of a hypothesis-free and data-driven approach to discover drug targets and reveal novel cross-talk among multiple immune cell types specific to a subset of SLE patients. This approach is immediately useful for studying autoimmune diseases and is applicable in other contexts where gene expression profiling is possible from multiple cell types within the same tissue compartment.

scholarly journals ARIC: Accurate and robust inference of cell type proportions from bulk gene expression or DNA methylation data

2021 ◽  
Author(s):  
Wei Zhang ◽  
Hanwen Xu ◽  
Rong Qiao ◽  
Bixi Zhong ◽  
Xianglin Zhang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Cell Types ◽  
Selection Strategy ◽  
Support Vector ◽  
Methylation Data ◽  
Cell Type ◽  
Promising Tool ◽  
Marker Selection ◽  
Bulk Data

Quantifying the cell proportions, especially for rare cell types in some scenarios, is of great value to track signals related to certain phenotypes or diseases. Although some methods have been pro-posed to infer cell proportions from multi-component bulk data, they are substantially less effective for estimating rare cell type proportions since they are highly sensitive against feature outliers and collinearity. Here we proposed a new deconvolution algorithm named ARIC to estimate cell type proportions from bulk gene expression or DNA methylation data. ARIC utilizes a novel two-step marker selection strategy, including component-wise condition number-based feature collinearity elimination and adaptive outlier markers removal. This strategy can systematically obtain effective markers that ensure a robust and precise weighted υ-support vector regression-based proportion prediction. We showed that ARIC can estimate fractions accurately in both DNA methylation and gene expression data from different experiments. Taken together, ARIC is a promising tool to solve the deconvolution problem of bulk data where rare components are of vital importance.

EPCO-04. RADIOTHERAPY IS ASSOCIATED WITH GLOBAL METHYLATION ALTERATIONS IN PATIENT DERIVED GLIOBLASTOMA CELL LINES

2021 ◽  
Vol 23 (Supplement_6) ◽  
pp. vi2-vi2
Author(s):  
Aram Modrek ◽  
David Byun ◽  
Ravesanker Ezhilarasan ◽  
Matija Snuderl ◽  
Erik Sulman
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Dna Damage ◽  
Radiation Treatment ◽  
Cpg Islands ◽  
Dna Damage Repair ◽  
Differential Methylation ◽  
Response To Therapy ◽  
Damage Repair ◽  
Genomic Regions

Abstract PURPOSE/OBJECTIVE(S) In glioblastoma, DNA methylation states are the most predictive marker of overall survival and response to therapy. Our understanding of how epigenetic states, such as DNA methylation, are “mis-repaired” after DNA damage repair is scant, hampering our ability to understand how treatment associated DNA methylation alterations may drive tumor resistance and growth. MATERIALS AND METHODS Three different patient derived IDH wild-type glioma stem cell (GSC) lines, in duplicates, were treated with radiation (20 Gray in 10 fractions vs. sham control) and allowed to recover prior to DNA methylation analysis with 850K methylation arrays. To analyze the methylation array data via bioinformatic methods we used RnBeads (version 2.4.0) and R (version 3.6.1) packages. We further focused our analysis to specific genomic regions, including CpG islands, promoters, gene bodies and CTCF motifs to understand how methylation alterations may differ between these and other genomic contexts following radiation. RESULTS There were widespread differential methylation (pre-treatment vs. radiation treatment) changes among the genomic regions examined. Interestingly, we found differential methylation changes at CTCF motifs, which play important DNA-methylation dependent roles in gene expression and chromatin architecture regulation. Hierarchical clustering, PCA and MDS analysis of DNA methylation status amongst CpG islands, promoters, gene bodies and CTCF domains revealed strong intra-sample differences, but not inter-sample differences (between GSC lines), suggesting radiation associated methylation alterations maybe loci and context dependent. CONCLUSION Radiation treatment is associated with wide-spread alterations of DNA methylation states in this patient derived glioblastoma model. Such alterations may drive gene expression changes or genomic architecture alterations that lead to treatment resistance, warranting further mechanistic investigation of the interplay between radiation induced DNA damage and local epigenetic state restoration following DNA damage repair.

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