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epityper massarray analysis dna methylation analysis  (agena bioscience)


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    agena bioscience epityper massarray analysis dna 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 Massarray Analysis Dna Methylation Analysis, supplied by agena bioscience, used in various techniques. Bioz Stars score: 96/100, based on 2219 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/dna+methylation+analysis+by+massarray/Methylation/pmc06821213-67-0-20
    Average 96 stars, based on 2219 article reviews
    epityper massarray analysis dna methylation analysis - by Bioz Stars, 2026-09
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    Images

    1) Product Images from "Fumarates target the metabolic-epigenetic interplay of brain-homing T cells in multiple sclerosis"

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

    Journal: Brain

    doi: 10.1093/brain/awy344

    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.
    Figure Legend 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.

    Techniques Used: 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.
    Figure Legend 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.

    Techniques Used: 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.
    Figure Legend 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.

    Techniques Used: DNA Methylation Assay, Expressing

    Related Articles

    Mass Spectrometry:

    Article Title: TXNIP hypomethylation and its interaction with obesity and hypertriglyceridemia increase type 2 diabetes mellitus risk: A nested case-control study.
    Article Snippet: .. Aims: To estimate the T2DM incidence with DNA methylation of thioredoxin-interacting protein gene (TXNIP) and its interaction with environmental factors.. Materials and Methods: This case–control study included 286 incident T2DM cases and 286 non-T2DM controls matched by sex, age, marital status, race, and residence village nested in the Rural Chinese Cohort Study.. A conditional logistic regression This article is protected by copyright. ..

    Article Title: Association of FTO gene methylation with incident type 2 diabetes mellitus: A nested case-control study.
    Article Snippet: .. Objectives: This study aimed to investigate the association of FTO methylation level with type 2 diabetes mellitus (T2DM) in a nested case–control study.. Methods: This nested case–control study included 287 pairs of T2DM cases and controls identified from a rural Chinese cohort study with a 6-year follow-up.. Controls were matched to the cases on a 1:1 basis by age, sex, ethnicity, marital status, and residence. ..

    Article Title: Integrated analysis of probability of type 2 diabetes mellitus with polymorphisms and methylation of KCNQ1 gene: A nested case-control study.
    Article Snippet: Funding information Medical Research Foundation of Guangdong Province, Grant/Award Number: A2017181; National Natural Science Foundation of China, Grant/ Award Numbers: 81373074, 81402752, 81673260; Natural Science Foundation of Guangdong Province, Grant/Award Number: 2017A030313452; the Science and Technology Development Foundation of Shenzhen, Grant/Award Numbers: JCYJ20140418091413562, JCYJ20160307155707264, JCYJ Abstract Background: To estimate the associations between single-nucleotide polymorphisms (SNPs) and methylation of KCNQ1 gene and type 2 diabetes mellitus (T2DM) risk and the interactions among SNPs, methylation, and environmental factors on T2DM risk.. Methods: We genotyped five SNPs and tested methylation at 39 CpG loci of KCNQ1 in 290 T2DM cases and 290 matched controls nested in the Rural Chinese Cohort Study.. Conditional logistic regression model was used to estimate the associations between SNPs and KCNQ1 methylation and T2DM risk.

    DNA Methylation Assay:

    Article Title: TXNIP hypomethylation and its interaction with obesity and hypertriglyceridemia increase type 2 diabetes mellitus risk: A nested case-control study.
    Article Snippet: .. Aims: To estimate the T2DM incidence with DNA methylation of thioredoxin-interacting protein gene (TXNIP) and its interaction with environmental factors.. Materials and Methods: This case–control study included 286 incident T2DM cases and 286 non-T2DM controls matched by sex, age, marital status, race, and residence village nested in the Rural Chinese Cohort Study.. A conditional logistic regression This article is protected by copyright. ..

    Article Title: Association of FTO gene methylation with incident type 2 diabetes mellitus: A nested case-control study.
    Article Snippet: .. Objectives: This study aimed to investigate the association of FTO methylation level with type 2 diabetes mellitus (T2DM) in a nested case–control study.. Methods: This nested case–control study included 287 pairs of T2DM cases and controls identified from a rural Chinese cohort study with a 6-year follow-up.. Controls were matched to the cases on a 1:1 basis by age, sex, ethnicity, marital status, and residence. ..

    Article Title: Integrated analysis of probability of type 2 diabetes mellitus with polymorphisms and methylation of KCNQ1 gene: A nested case-control study.
    Article Snippet: Funding information Medical Research Foundation of Guangdong Province, Grant/Award Number: A2017181; National Natural Science Foundation of China, Grant/ Award Numbers: 81373074, 81402752, 81673260; Natural Science Foundation of Guangdong Province, Grant/Award Number: 2017A030313452; the Science and Technology Development Foundation of Shenzhen, Grant/Award Numbers: JCYJ20140418091413562, JCYJ20160307155707264, JCYJ Abstract Background: To estimate the associations between single-nucleotide polymorphisms (SNPs) and methylation of KCNQ1 gene and type 2 diabetes mellitus (T2DM) risk and the interactions among SNPs, methylation, and environmental factors on T2DM risk.. Methods: We genotyped five SNPs and tested methylation at 39 CpG loci of KCNQ1 in 290 T2DM cases and 290 matched controls nested in the Rural Chinese Cohort Study.. Conditional logistic regression model was used to estimate the associations between SNPs and KCNQ1 methylation and T2DM risk.



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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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    ZNF582-AS1 expression was regulated by DNA methylation in ccRCC. a Detection of CpG islands in ZNF582-AS1 promoter and design of MSP primers. The horizontal axis of the curved lines represents the input sequence of ZNF582-AS1, and the vertical axis of the curved lines represents GC percentage. TSS: Transcription Start Sites. b MSP analysis of ZNF582-AS1 promoter DNA methylation status in ccRCC cell lines. c MSP analysis of ZNF582-AS1 promoter DNA methylation status in ccRCC tissues. d Detection of 38 CpG sites in ZNF582-AS1 promoter. e Quantitative detection of DNA methylation level of 38 CpG sites in ZNF582-AS1 promoter using Sequenom MassARRAY quantitative DNA methylation analysis. f and g Comparison of the DNA methylation levels of 38 CpG sites in ccRCC and adjacent normal renal tissues. h Treatment with 5-aza-dC and TSA demethylated ZNF582-AS1 promoter and increased ZNF582-AS1 expression in OSRC2 and Caki-1 cells. T refers to Tumor tissue of ccRCC, N refers to Adjacent normal kidney tissue. M = Methylated, U = Unmethylated

    Journal: Journal of Experimental & Clinical Cancer Research : CR

    Article Title: Downregulation of lncRNA ZNF582-AS1 due to DNA hypermethylation promotes clear cell renal cell carcinoma growth and metastasis by regulating the N(6)-methyladenosine modification of MT-RNR1

    doi: 10.1186/s13046-021-01889-8

    Figure Lengend Snippet: ZNF582-AS1 expression was regulated by DNA methylation in ccRCC. a Detection of CpG islands in ZNF582-AS1 promoter and design of MSP primers. The horizontal axis of the curved lines represents the input sequence of ZNF582-AS1, and the vertical axis of the curved lines represents GC percentage. TSS: Transcription Start Sites. b MSP analysis of ZNF582-AS1 promoter DNA methylation status in ccRCC cell lines. c MSP analysis of ZNF582-AS1 promoter DNA methylation status in ccRCC tissues. d Detection of 38 CpG sites in ZNF582-AS1 promoter. e Quantitative detection of DNA methylation level of 38 CpG sites in ZNF582-AS1 promoter using Sequenom MassARRAY quantitative DNA methylation analysis. f and g Comparison of the DNA methylation levels of 38 CpG sites in ccRCC and adjacent normal renal tissues. h Treatment with 5-aza-dC and TSA demethylated ZNF582-AS1 promoter and increased ZNF582-AS1 expression in OSRC2 and Caki-1 cells. T refers to Tumor tissue of ccRCC, N refers to Adjacent normal kidney tissue. M = Methylated, U = Unmethylated

    Article Snippet: TSS: Transcription Start Sites. b MSP analysis of ZNF582-AS1 promoter DNA methylation status in ccRCC cell lines. c MSP analysis of ZNF582-AS1 promoter DNA methylation status in ccRCC tissues. d Detection of 38 CpG sites in ZNF582-AS1 promoter. e Quantitative detection of DNA methylation level of 38 CpG sites in ZNF582-AS1 promoter using Sequenom MassARRAY quantitative DNA methylation analysis. f and g Comparison of the DNA methylation levels of 38 CpG sites in ccRCC and adjacent normal renal tissues. h Treatment with 5-aza-dC and TSA demethylated ZNF582-AS1 promoter and increased ZNF582-AS1 expression in OSRC2 and Caki-1 cells.

    Techniques: Expressing, DNA Methylation Assay, Sequencing, Comparison, Methylation

    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

    Summary of main projects in the PANINI network

    Journal: Aging Clinical and Experimental Research

    Article Title: Physical Activity and Nutrition INfluences In ageing (PANINI): consortium mission statement

    doi: 10.1007/s40520-017-0823-7

    Figure Lengend Snippet: Summary of main projects in the PANINI network

    Article Snippet: 10. University of Bologna , Epigenetics of nutrition in ageing , DNA methylation analysis (gene-targeted) by Sequenom ® MassARRAY EpiTYPER platform , NU-AGE samples and new PANINI data , Changes in DNA methylation patterns induced by dietary and physical interventions. Development of a gene-targeted epigenetic clock.

    Techniques: Battery, Activity Assay, Modification, DNA Methylation Assay, Variant Assay