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Epigenome-wide <t>DNA</t> <t>methylation</t> analysis reveals MIR-21 as the top hypermethylated region in CD4 T cells from FAE-treated patients. CD4 T cell DNA from 47 treatment-naïve, 35 FAE-treated and 16 GA-treated multiple sclerosis patients was analysed by using the Infinium MethylationEPIC BeadChip array. To identify differentially methylated regions between treated and untreated patients, we utilized a linear regression model at each individual CpG site to identify the contribution of treatment status in DNA methylation changes after controlling for age, gender, race, disease duration, the total CD4 T cell percentage as well as the percentage of CCR6−CCR4+, CCR6+CCR4+ and CCR6+CCR4− CD4 T cells in each sample. We then used a 1-kb sliding window to define genomic regions with closely located CpG sites, and then combined each CpG specific P-value from our previous linear regression model within a single region with the Stouffer’s method. This was followed by the Bonferroni correction for multiple hypothesis testing. DMRs were defined as regions with more than four CpG sites that have an absolute median β-value change > 0.02 and an adjusted combined P-value of < 0.01. Based on this analysis we uncovered 202 hypermethylated DMRs (containing 1545 CpGs) and only 13 hypomethylated DMRs (containing 158 CpGs) in FAE-treated patients compared to controls. (A and B) The CpGs distribution of these hypermethylated (hyperCpGs) and hypomethylated (hypoCpGs) DMRs was compared to that of the CpG distribution in the Illumina Infinium MethylationEPIC BeadChip (allCpGs). (C) Circos plot showing (from inside out); innermost first circle: chromosomal colors, numbers and size; second circle: a scatter plot with each point representing the genomic location and mean change in β-value of hypomethylated (in blue) and hypermethylated (in red) CpG sites; third circle: dark red perpendicular lines represent the genomic location of significantly hypermethylated DMRs; fourth circle: dark red scatter plot with each point representing the genomic location and mean beta change of significantly hypermethylated DMRs spanning more than 10 CpGs; outermost fifth circle: contains the names of genes whose promoters are located in these large DMRs (MIR-21 is shown in red). (D) Manhattan plot of the discovery cohort analysis showing mean beta change of significantly hypermethylated DMRs spanning more than 10 CpGs, where MIR-21 was the top differentially methylated locus. (E) Manhattan plot from the pair-wise longitudinal analysis showing that MIR-21 was the hypermethylated DMR with the most consistent and greatest methylation change in the validation cohort.
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agena bioscience epityper methylation analysis
Epigenome-wide <t>DNA</t> <t>methylation</t> analysis reveals MIR-21 as the top hypermethylated region in CD4 T cells from FAE-treated patients. CD4 T cell DNA from 47 treatment-naïve, 35 FAE-treated and 16 GA-treated multiple sclerosis patients was analysed by using the Infinium MethylationEPIC BeadChip array. To identify differentially methylated regions between treated and untreated patients, we utilized a linear regression model at each individual CpG site to identify the contribution of treatment status in DNA methylation changes after controlling for age, gender, race, disease duration, the total CD4 T cell percentage as well as the percentage of CCR6−CCR4+, CCR6+CCR4+ and CCR6+CCR4− CD4 T cells in each sample. We then used a 1-kb sliding window to define genomic regions with closely located CpG sites, and then combined each CpG specific P-value from our previous linear regression model within a single region with the Stouffer’s method. This was followed by the Bonferroni correction for multiple hypothesis testing. DMRs were defined as regions with more than four CpG sites that have an absolute median β-value change > 0.02 and an adjusted combined P-value of < 0.01. Based on this analysis we uncovered 202 hypermethylated DMRs (containing 1545 CpGs) and only 13 hypomethylated DMRs (containing 158 CpGs) in FAE-treated patients compared to controls. (A and B) The CpGs distribution of these hypermethylated (hyperCpGs) and hypomethylated (hypoCpGs) DMRs was compared to that of the CpG distribution in the Illumina Infinium MethylationEPIC BeadChip (allCpGs). (C) Circos plot showing (from inside out); innermost first circle: chromosomal colors, numbers and size; second circle: a scatter plot with each point representing the genomic location and mean change in β-value of hypomethylated (in blue) and hypermethylated (in red) CpG sites; third circle: dark red perpendicular lines represent the genomic location of significantly hypermethylated DMRs; fourth circle: dark red scatter plot with each point representing the genomic location and mean beta change of significantly hypermethylated DMRs spanning more than 10 CpGs; outermost fifth circle: contains the names of genes whose promoters are located in these large DMRs (MIR-21 is shown in red). (D) Manhattan plot of the discovery cohort analysis showing mean beta change of significantly hypermethylated DMRs spanning more than 10 CpGs, where MIR-21 was the top differentially methylated locus. (E) Manhattan plot from the pair-wise longitudinal analysis showing that MIR-21 was the hypermethylated DMR with the most consistent and greatest methylation change in the validation cohort.
Epityper Methylation Analysis, supplied by agena bioscience, used in various techniques. Bioz Stars score: 96/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Methods for estimating age by DNA methylation analysis. Each workflow begins with bisulfite conversion as the initial step. Created with BioRender.com .

Journal: International Journal of Molecular Sciences

Article Title: Uncovering Forensic Evidence: A Path to Age Estimation through DNA Methylation

doi: 10.3390/ijms25094917

Figure Lengend Snippet: Methods for estimating age by DNA methylation analysis. Each workflow begins with bisulfite conversion as the initial step. Created with BioRender.com .

Article Snippet: First, public datasets from Illumina BeadChip arrays were analyzed, followed by the utilization of EpiTYPER DNA methylation analysis system to identify six loci (KCNAB3, EDARADD, ELOVL2, CCDC102B, MIR29B2CHG, CR_23_CpG_3) associated with age.

Techniques: DNA Methylation Assay

Description of sample types, methods, and associated accuracies in recent publications. The numbers in the sample types correspond to the evidence markers in <xref ref-type= Figure 3 ." width="100%" height="100%">

Journal: International Journal of Molecular Sciences

Article Title: Uncovering Forensic Evidence: A Path to Age Estimation through DNA Methylation

doi: 10.3390/ijms25094917

Figure Lengend Snippet: Description of sample types, methods, and associated accuracies in recent publications. The numbers in the sample types correspond to the evidence markers in Figure 3 .

Article Snippet: First, public datasets from Illumina BeadChip arrays were analyzed, followed by the utilization of EpiTYPER DNA methylation analysis system to identify six loci (KCNAB3, EDARADD, ELOVL2, CCDC102B, MIR29B2CHG, CR_23_CpG_3) associated with age.

Techniques: Next-Generation Sequencing, Sequencing

Epigenome-wide DNA methylation analysis reveals MIR-21 as the top hypermethylated region in CD4 T cells from FAE-treated patients. CD4 T cell DNA from 47 treatment-naïve, 35 FAE-treated and 16 GA-treated multiple sclerosis patients was analysed by using the Infinium MethylationEPIC BeadChip array. To identify differentially methylated regions between treated and untreated patients, we utilized a linear regression model at each individual CpG site to identify the contribution of treatment status in DNA methylation changes after controlling for age, gender, race, disease duration, the total CD4 T cell percentage as well as the percentage of CCR6−CCR4+, CCR6+CCR4+ and CCR6+CCR4− CD4 T cells in each sample. We then used a 1-kb sliding window to define genomic regions with closely located CpG sites, and then combined each CpG specific P-value from our previous linear regression model within a single region with the Stouffer’s method. This was followed by the Bonferroni correction for multiple hypothesis testing. DMRs were defined as regions with more than four CpG sites that have an absolute median β-value change > 0.02 and an adjusted combined P-value of < 0.01. Based on this analysis we uncovered 202 hypermethylated DMRs (containing 1545 CpGs) and only 13 hypomethylated DMRs (containing 158 CpGs) in FAE-treated patients compared to controls. (A and B) The CpGs distribution of these hypermethylated (hyperCpGs) and hypomethylated (hypoCpGs) DMRs was compared to that of the CpG distribution in the Illumina Infinium MethylationEPIC BeadChip (allCpGs). (C) Circos plot showing (from inside out); innermost first circle: chromosomal colors, numbers and size; second circle: a scatter plot with each point representing the genomic location and mean change in β-value of hypomethylated (in blue) and hypermethylated (in red) CpG sites; third circle: dark red perpendicular lines represent the genomic location of significantly hypermethylated DMRs; fourth circle: dark red scatter plot with each point representing the genomic location and mean beta change of significantly hypermethylated DMRs spanning more than 10 CpGs; outermost fifth circle: contains the names of genes whose promoters are located in these large DMRs (MIR-21 is shown in red). (D) Manhattan plot of the discovery cohort analysis showing mean beta change of significantly hypermethylated DMRs spanning more than 10 CpGs, where MIR-21 was the top differentially methylated locus. (E) Manhattan plot from the pair-wise longitudinal analysis showing that MIR-21 was the hypermethylated DMR with the most consistent and greatest methylation change in the validation cohort.

Journal: Brain

Article Title: Fumarates target the metabolic-epigenetic interplay of brain-homing T cells in multiple sclerosis

doi: 10.1093/brain/awy344

Figure Lengend Snippet: Epigenome-wide DNA methylation analysis reveals MIR-21 as the top hypermethylated region in CD4 T cells from FAE-treated patients. CD4 T cell DNA from 47 treatment-naïve, 35 FAE-treated and 16 GA-treated multiple sclerosis patients was analysed by using the Infinium MethylationEPIC BeadChip array. To identify differentially methylated regions between treated and untreated patients, we utilized a linear regression model at each individual CpG site to identify the contribution of treatment status in DNA methylation changes after controlling for age, gender, race, disease duration, the total CD4 T cell percentage as well as the percentage of CCR6−CCR4+, CCR6+CCR4+ and CCR6+CCR4− CD4 T cells in each sample. We then used a 1-kb sliding window to define genomic regions with closely located CpG sites, and then combined each CpG specific P-value from our previous linear regression model within a single region with the Stouffer’s method. This was followed by the Bonferroni correction for multiple hypothesis testing. DMRs were defined as regions with more than four CpG sites that have an absolute median β-value change > 0.02 and an adjusted combined P-value of < 0.01. Based on this analysis we uncovered 202 hypermethylated DMRs (containing 1545 CpGs) and only 13 hypomethylated DMRs (containing 158 CpGs) in FAE-treated patients compared to controls. (A and B) The CpGs distribution of these hypermethylated (hyperCpGs) and hypomethylated (hypoCpGs) DMRs was compared to that of the CpG distribution in the Illumina Infinium MethylationEPIC BeadChip (allCpGs). (C) Circos plot showing (from inside out); innermost first circle: chromosomal colors, numbers and size; second circle: a scatter plot with each point representing the genomic location and mean change in β-value of hypomethylated (in blue) and hypermethylated (in red) CpG sites; third circle: dark red perpendicular lines represent the genomic location of significantly hypermethylated DMRs; fourth circle: dark red scatter plot with each point representing the genomic location and mean beta change of significantly hypermethylated DMRs spanning more than 10 CpGs; outermost fifth circle: contains the names of genes whose promoters are located in these large DMRs (MIR-21 is shown in red). (D) Manhattan plot of the discovery cohort analysis showing mean beta change of significantly hypermethylated DMRs spanning more than 10 CpGs, where MIR-21 was the top differentially methylated locus. (E) Manhattan plot from the pair-wise longitudinal analysis showing that MIR-21 was the hypermethylated DMR with the most consistent and greatest methylation change in the validation cohort.

Article Snippet: EpiTYPER MassArray® analysis DNA methylation analysis of ex vivo and in vitro stimulated cells was performed with EpiTYPERTM MassARRAY® system (Agena Bioscience) as previously described ( Moyon et al. , 2016 ) at the Epigenetics Core facility at the CUNY Advanced Science Research Center (ASRC).

Techniques: DNA Methylation Assay, Methylation, Biomarker Discovery

FAEs inhibit DNA demethylation at the MIR-21 promoter in a specific and dose-dependent manner. Naïve (CD45RO−CCR7+) and memory (CD45RO+) CD4 T cells were isolated from human PBMCs by FACS. The baseline DNA methylation levels of naïve (NaïveBL) and memory CD4 T cells (MemoryBL) at the (A) MIR-21 and (B) TNF promoters were measured ex vivo by EpiTYPER™ MassARRAY®. Naïve and memory CD4 T cells were also cultured with or without MMF at the specified concentration and stimulated with anti-CD3 and anti-CD28 coated beads for 3 days either without polarization or under Th17 polarizing conditions, after which DNA methylation levels at the (A) MIR-21 and (B) TNF promoters were measured by EpiTYPER™ MassARRAY®. (A) MMF was able to inhibit DNA demethylation of the MIR-21 promoter in naïve CD4 T cells, but not in memory CD4 T cells, in a dose dependent manner. (B) DNA methylation at the TNF promoter was not significantly changed by MMF in either naïve or memory CD4 T cells. (C) MMF had an even greater hypermethylating effect on the MIR-21 locus of naïve CD4 T cells that were stimulated under Th17 polarizing conditions. (D) MMF was also able to inhibit the demethylation of the MIR-21 promoter of naïve (CD45RO−CCR7+) CD8 T cells after 3 days of activation with anti-CD3 and anti-CD28 coated beads in vitro under Tc17 polarizing conditions. MMF20 = 20 µM of MMF; MMF50 = 50 µM of MMF; Veh = vehicle.

Journal: Brain

Article Title: Fumarates target the metabolic-epigenetic interplay of brain-homing T cells in multiple sclerosis

doi: 10.1093/brain/awy344

Figure Lengend Snippet: FAEs inhibit DNA demethylation at the MIR-21 promoter in a specific and dose-dependent manner. Naïve (CD45RO−CCR7+) and memory (CD45RO+) CD4 T cells were isolated from human PBMCs by FACS. The baseline DNA methylation levels of naïve (NaïveBL) and memory CD4 T cells (MemoryBL) at the (A) MIR-21 and (B) TNF promoters were measured ex vivo by EpiTYPER™ MassARRAY®. Naïve and memory CD4 T cells were also cultured with or without MMF at the specified concentration and stimulated with anti-CD3 and anti-CD28 coated beads for 3 days either without polarization or under Th17 polarizing conditions, after which DNA methylation levels at the (A) MIR-21 and (B) TNF promoters were measured by EpiTYPER™ MassARRAY®. (A) MMF was able to inhibit DNA demethylation of the MIR-21 promoter in naïve CD4 T cells, but not in memory CD4 T cells, in a dose dependent manner. (B) DNA methylation at the TNF promoter was not significantly changed by MMF in either naïve or memory CD4 T cells. (C) MMF had an even greater hypermethylating effect on the MIR-21 locus of naïve CD4 T cells that were stimulated under Th17 polarizing conditions. (D) MMF was also able to inhibit the demethylation of the MIR-21 promoter of naïve (CD45RO−CCR7+) CD8 T cells after 3 days of activation with anti-CD3 and anti-CD28 coated beads in vitro under Tc17 polarizing conditions. MMF20 = 20 µM of MMF; MMF50 = 50 µM of MMF; Veh = vehicle.

Article Snippet: EpiTYPER MassArray® analysis DNA methylation analysis of ex vivo and in vitro stimulated cells was performed with EpiTYPERTM MassARRAY® system (Agena Bioscience) as previously described ( Moyon et al. , 2016 ) at the Epigenetics Core facility at the CUNY Advanced Science Research Center (ASRC).

Techniques: Isolation, DNA Methylation Assay, Ex Vivo, Cell Culture, Concentration Assay, Activation Assay, In Vitro

FAE therapy modifies the metabolic-epigenetic interplay in multiple sclerosis to reduce pathogenic CCR6+ CD4 and CD8 T cells. (A) CD4 T cells from treatment naïve patients with multiple sclerosis exhibit low DNA methylation levels at the MIR-21 locus and high expression of CCR6. CD8 T cells from treatment naïve multiple sclerosis patients also exhibit high levels of CCR6. (B) FAE therapy epigenetically modulates the MIR-21 locus in CD4 and CD8 T cells, which results in hypermethylation and downregulation of miR-21 expression in FAE-treated Th17 and Tc17 cells. This in turn allows for the upregulation of SMAD7 in both CD4 and CD8 T cells, a miR-21-5p and miR-21-3p target with inhibitory feedback on the TGF-b signalling pathway. Finally, FAEs reduce CCR6 expression and lower this potentially pathogenic brain-homing CCR6+ CD4 and CD8 T cell population in FAE-treated multiple sclerosis patients.

Journal: Brain

Article Title: Fumarates target the metabolic-epigenetic interplay of brain-homing T cells in multiple sclerosis

doi: 10.1093/brain/awy344

Figure Lengend Snippet: FAE therapy modifies the metabolic-epigenetic interplay in multiple sclerosis to reduce pathogenic CCR6+ CD4 and CD8 T cells. (A) CD4 T cells from treatment naïve patients with multiple sclerosis exhibit low DNA methylation levels at the MIR-21 locus and high expression of CCR6. CD8 T cells from treatment naïve multiple sclerosis patients also exhibit high levels of CCR6. (B) FAE therapy epigenetically modulates the MIR-21 locus in CD4 and CD8 T cells, which results in hypermethylation and downregulation of miR-21 expression in FAE-treated Th17 and Tc17 cells. This in turn allows for the upregulation of SMAD7 in both CD4 and CD8 T cells, a miR-21-5p and miR-21-3p target with inhibitory feedback on the TGF-b signalling pathway. Finally, FAEs reduce CCR6 expression and lower this potentially pathogenic brain-homing CCR6+ CD4 and CD8 T cell population in FAE-treated multiple sclerosis patients.

Article Snippet: EpiTYPER MassArray® analysis DNA methylation analysis of ex vivo and in vitro stimulated cells was performed with EpiTYPERTM MassARRAY® system (Agena Bioscience) as previously described ( Moyon et al. , 2016 ) at the Epigenetics Core facility at the CUNY Advanced Science Research Center (ASRC).

Techniques: DNA Methylation Assay, Expressing