The raw IDAT files of Illumina 450K Beadchip data including CHB patients (n = 10) and Barcelona clinic liver cancer staging system (BCLC) 0 (n = 10), BCLC-A (n = 10), BCLC-B (n = 10), and BCLC-C (n = 9) were obtained from Gene Expression Omnibus (accession number: GSE67170) (9 (link)), which was prepared to obtain differentially methylated CpGs between CHB and each HCC stage. Forty-four paired PBMC samples were taken from 22 patients before and again after diagnosis of HCC. The 22 patients were diagnosed as LC prior to HCC, and then 5 were diagnosed as HCC BCLC-0 and 17 were BCLC-A. Twenty-two LC and 22 early HCC PBMC samples were subjected to genome-wide DNA methylation assay by using Illumina EPIC Beadchip (data did not published). The R package ChAMP was applied for methylation raw data processing and the paired t tests were used to analyze the differentially methylated CpGs between LC and HCC BCLC-0 and -A. The differentially methylated CpGs with |delta beta|≥ 0.2 and remaining significant after Bonferroni-corrected p value < 0.05 were selected.
Epic beadchip
Manufactured by Illumina
Sourced in United States
The EPIC BeadChip is a high-throughput microarray platform designed for genome-wide genotyping and methylation analysis. It provides comprehensive coverage of common and rare genetic variants, as well as comprehensive coverage of CpG sites across the genome.
Automatically generated - may contain errors
Lab products found in correlation
Ez dna methylation kit, by Zymo Research (6 mentions)
450k beadchip, by Illumina (3 mentions)
Iscan system, by Illumina (3 mentions)
450k methylation beadchip, by Illumina (2 mentions)
Ez dna methylation gold kit, by Zymo Research (2 mentions)
Infinium human methylation 450k, by Illumina (2 mentions)
Hiscan system, by Illumina (1 mentions)
Bioanalyzer, by Agilent Technologies (1 mentions)
Infinium humanmethylation450k beadchip, by Illumina (1 mentions)
450k platform, by Illumina (1 mentions)
Pyromark q24, by Qiagen (1 mentions)
Infinium humanmethylation450, by Illumina (1 mentions)
Gentra puregene blood kit, by Qiagen (1 mentions)
Genomestudio software, by Illumina (1 mentions)
Ez 96 dna methylation kit, by Zymo Research (1 mentions)
Epic beadchip array, by Illumina (1 mentions)
Humanmethylation450 beadchip 450k, by Illumina (1 mentions)
Infinium methylationepic beadchip kit, by Illumina (1 mentions)
Rna dna purification plus kit, by Norgen Biotek (1 mentions)
27 protocols using epic beadchip
1
Hepatocellular Carcinoma Methylome Analysis
2
Epigenetic Age Estimation from Blood
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The generation, preprocessing, and normalization of the DNAm data were described in our previous paper (19 (link)). Briefly, genome-wide DNAm from blood samples was determined on Illumina EPIC BeadChip, and the data were preprocessed with R package minfi. Detection p values comparing the total signal for each probe to the background signal level were calculated to evaluate the quality of the samples (20 (link)). Further analysis excluded samples of poor quality (mean detection p > .01). The single-sample Noob normalization method was used to normalize the data (21 (link)). The epigenetic age estimates, including Horvath’s (6 (link)) and Hannum’s (22 (link)) DNAmAge, DNAm PhenoAge (7 (link)), and GrimAge (8 (link)), were produced using an online calculator with default settings (https://dnamage.genetics.ucla.edu/new ). Epigenetic age acceleration, which describes the difference between the chronological age and the epigenetic age estimate, was calculated as the residual from a linear regression model of epigenetic age estimates of chronological age. DNA collection and the assessment of DNAm age acceleration were conducted only at baseline.
3
DNA Methylation Analysis of Bladder Cancer
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DNA methylation analysis was performed using DNA from 29 patients based on the UROMOL2016 classification with 10–11 samples from each class. After re-classification, we had 10 samples in class 1, 12 in class 2a/2b with a majority in class 2b and 6 in class 3. All tumors were selected to have a high silhouette score, and all were Ta high-grade tumors. We used 500 ng genomic DNA for bisulfite conversion followed by whole-genome amplification prior to hybridization to EPIC BeadChip (Illumina, San Diego, CA) overnight as described by the manufacturer and then scanned with the Illumina iSCAN system. Data was imported and processed using the RnBeads v2.2R package pipeline. For the preprocessing of the data, the normalization method was set to “illumina” and the background correction method to “methylumi.noob”.
4
Epigenome-Wide DNA Methylation Profiling
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DNAm profiling was conducted in the Kobor Lab from whole-blood DNA stored at −80°C. After quality controls and normalization, DNAm data sets were generated for n = 595 samples from 214 individuals (142 CR, 72 AL; Figure 1B , Table 1 ). Briefly, 750 ng of DNA was extracted from whole blood and bisulfite was converted using the EZ DNA Methylation kit (Zymo Research, Irvine, CA). Methylation was measured from 160 ng of bisulfite-converted DNA using the Illumina EPIC Beadchip (Illumina, Inc., San Diego, CA). Quality control (QC) and normalization were performed using methylumi (v. 2.32.0) (24 ) and the Bioconductor (v 2.46.0) (25 (link)) packages from the R statistical programming environment (v 3.6.3). Probes with detection p-values > .05 were coded as missing; probes missing in > 5% of samples were removed from the dataset (final probe n = 828,613 CpGs). Normalization to eliminate systematic dye bias in the 2-channel probes was carried out using the methylumi default method. We conducted a principal component analysis of EPIC-array control-probe beta values to compute controls for technical variability across the samples (26 (link)).
5
DNA Methylation Profiling of Cardiac Tissue
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LV apical myocardial tissue samples were washed in ice-cold saline (0.9% NaCl) and stored in liquid nitrogen until DNA and RNA were extracted. DNA was extracted using a DNA Kit (Qiagen). Purity and concentration were determined using a Bioanalyzer (Agilent Technologies). For DNA methylation profiling, DNA was bisulfite converted using a commercially available kit (Zymo Research). Illumina Infinium Human Methylation 450K Bead Chip and EPIC Bead Chip were used for genome-wide profiling of DNA methylation (58 (link)). The EPIC chip measures over 850,000 methylation sites, with high reproducibility compared with the previous 450k chip (59 (link)). After whole genome DNA amplification, the samples were applied following the Illumina Infinium Human Methylation DNA chip manufacturer protocols (Illumina). Chips were analyzed using the Illumina Hi-Scan system at the McDonnell Genome Institute (MGI) at Washington University.
6
Methylation Profiling of HPA-Axis Genes
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More than 90% of the probes on the Illumina 450K methylation Beadchip are also present on the Illumina EPIC BeadChip (Pidsley et al., 2016 (link)). Therefore we used the expanded annotation produced by Price et al., originally designed for the 450K array, to define, for each CpG site, the distance to the closest transcriptional start site (TSS) and the associated gene (Price et al., 2013 (link)). As such, only CpG-sites present on both the EPIC array and Illumina 450K methylation Beadchip were considered for further analysis. In addition, we only considered CpG sites located within 2000 base pairs (bp) up and downstream of the TSS. Wagner et al. demonstrated that DNA methylation and gene expression are closely related within this region (Wagner et al., 2014 (link)).
Based on the hypothesis that HPA-axis is associated with severity of suicidal behavior, we considered the following HPA-axis coupled genes: Corticotropin releasing hormone (CRH), corticotropin releasing hormone binding protein (CRHBP), corticotropin releasing hormone receptor 1 and 2 (CRHR1), (CRHR2), FK506-binding protein 51 (FKBP5) and the glucocorticoid receptor (NR3C1). After the preprocessing steps outlined above, all CpG sites annotated to any of the aforementioned genes were included in the study, resulting in 72 CpG sites investigated in the subsequent analysis.
Based on the hypothesis that HPA-axis is associated with severity of suicidal behavior, we considered the following HPA-axis coupled genes: Corticotropin releasing hormone (CRH), corticotropin releasing hormone binding protein (CRHBP), corticotropin releasing hormone receptor 1 and 2 (CRHR1), (CRHR2), FK506-binding protein 51 (FKBP5) and the glucocorticoid receptor (NR3C1). After the preprocessing steps outlined above, all CpG sites annotated to any of the aforementioned genes were included in the study, resulting in 72 CpG sites investigated in the subsequent analysis.
7
Methylation Profiling of Cell Lines and Tumor Biopsies
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A total of 250 ng of DNA was bisulfite converted using EZ DNA Methylation Kit (Zymo, catalog no. D5001), following the Illumina manufacturer’s protocol. The purified bisulfite converted DNA was then used as starting material for the Infinium MethylationEPIC bead chip, carried out by the Princess Margaret Genomics Centre, following manufacturer’s protocol. IDAT files for Illumina EPIC BeadChip data were processed using minfi R-package.36 (link) Single sample Noob normalization was performed to yield normalized beta values that were used for further analysis. Limma R-package was used for statistical comparisons.37 (link)
Processed data were obtained from EBI array express for a previously published dataset of cell lines that were grown in the presence of azacitidine and profiled at multiple time-points on the Illumina 450 k platform.13 (link) We computed beta-values for samples that had been grown in the presence of azacitidine for 7 days (beta-value >0.3, false discovery rate (FDR) <0.01). On the tumor biopsies, we identified all probes that were highly methylated (beta-value >0.8) at baseline and estimated beta-values for the same probes post-CC-486 treatment on the tumor biopsies.
Processed data were obtained from EBI array express for a previously published dataset of cell lines that were grown in the presence of azacitidine and profiled at multiple time-points on the Illumina 450 k platform.13 (link) We computed beta-values for samples that had been grown in the presence of azacitidine for 7 days (beta-value >0.3, false discovery rate (FDR) <0.01). On the tumor biopsies, we identified all probes that were highly methylated (beta-value >0.8) at baseline and estimated beta-values for the same probes post-CC-486 treatment on the tumor biopsies.
8
Multi-Omics Profiling of Biological Samples
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Genome-wide DNA methylation was profiled using the Illumina Infinium HumanMethylation450 and EPIC BeadChip platforms (Illumina, Cambridge, UK; Accession Number: E-MTAB-5463). Sample numbers are provided in Supplementary Table S3 . Expression profiling was performed using RNA-sequencing (RNA-seq) at the University of Kiel, Germany using an established pipeline as described previously.10 (link) (Project accession number: E-MTAB-5464). Patient genotyping was performed using the Illumina OmniExpressExome-8 BeadChip Kit. 16S rRNA gene profiling of the adjacent microbiota was performed at the Wellcome Trust Sanger Centre (Hinxton, Cambridge). The 16S microbiota data can be found under EBI study ID PRJEB6663. For further details of the arrays and sequencing, please see the Supplementary Methods .
Locus-specific validation of DNA methylation profiles was performed on bisulfite-converted DNA after polymerase chain reaction amplification using the Pyromark Q24 (Qiagen) pyrosequencing system as described previously.16 (link)
Locus-specific validation of DNA methylation profiles was performed on bisulfite-converted DNA after polymerase chain reaction amplification using the Pyromark Q24 (Qiagen) pyrosequencing system as described previously.16 (link)
9
Epigenetic Age Acceleration Analysis
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In our previous paper, we described the generation, preprocessing, and normalization of the DNAm data [13 (link)]. Briefly, genome-wide DNAm from blood samples was determined using an Illumina EPIC BeadChip, and the data were preprocessed with the R package minfi. Detection p-values comparing the total signal for each probe to the background signal level were calculated to evaluate the quality of the samples [33 ]. Further analysis excluded samples of poor quality (mean detection p > 0.01). A single-sample Noob normalization method was used to normalize the data [34 (link)]. The epigenetic age estimates, including Horvath’s DNAmAge [8 (link)] and DNAm GrimAge [10 (link)], were produced by an online calculator (https://dnamage.genetics.ucla.edu/new ). Horvath’s DNAmAge is a multi-tissue predictor of biological aging that has been developed to predict chronological age [8 (link)], while DNAm GrimAge was developed to predict lifespan [10 (link)]. Epigenetic age acceleration (the difference between chronological age and epigenetic age estimate) was calculated as the residuals from a linear regression model of epigenetic age estimate on chronological age for Horvath’s DNAmAge and DNAm GrimAge separately (AAHorvath, AAGrimAge, respectively).
10
Epigenetic Age and Biological Aging Estimation
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In our previous paper, we described the generation, preprocessing, and normalization of the DNAm data (27 (link)). Briefly, we determined genome-wide DNAm from blood samples using an Illumina EPIC BeadChip, and the data were preprocessed with the R package minfi. Detection p values comparing the total signal for each probe to the background signal level were calculated to evaluate the quality of the samples (28 (link)). Further analysis excluded samples of poor quality (mean detection p > .01). To normalize the data, a single-sample Noob normalization method was used (29 (link)).
The epigenetic age estimate, DNAm GrimAge, was calculated using an online calculator (https://dnamage.genetics.ucla.edu/new ). For this measure, in the analysis, we used the age acceleration measure, which describes the difference between chronological age and epigenetic age estimates. Age acceleration was defined as the residual from regressing the estimated epigenetic age on the chronological age. The DunedinPACE estimator gives an estimate for the pace of biological aging in years per calendar year (12 (link),13 (link)). It was calculated using a publicly available R package (https://github.com/danbelsky/DunedinPACE ).
The epigenetic age estimate, DNAm GrimAge, was calculated using an online calculator (
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