Project description:The objective of the study was to utilize DNA methylation to quantify human leukocyte subsets in human blood. This file contains data from an Illumina custom VeraCode GGMA microarray for human leukocyte subtypes (purified from whole blood samples via magnetic activated cell sorting (MACS) and purity confirmed by flourescence activated cell sorting (FACS)) as well as for complex mixtures of DNA from those samples, and for human whole blood samples. Bisulphite converted DNA from the samples were hybridized to an Illumina Custom VeraCode GGMA microarray.
Project description:The objective of the study was to utilize DNA methylation to quantify human leukocyte subsets in human blood. This file contains data from an Illumina Infinium HumanMethlation450 for human whole blood samples as well as complex mixtures of DNA from purified human leukocyte subtypes in quantities that mimick human blood under different clinical conditions. Bisulphite converted DNA from the samples were hybridized to an Illumina Infinium HumanMethylation450 beadchip
Project description:The objective of the study was to identify differentially methylated regions of DNA (DMRs) that distinguish human leukocyte subtypes, and hence serve as biomarkers for those immune cell types. This file contains Illumina Infinium HumanMethylation27 BeadChip data for human leukocyte subtypes that were purified from whole blood samples via magnetic activated cell sorting (MACS) and purity confirmed by flourescence activated cell sorting (FACS). Bisulphite converted DNA from the 73 samples were hybridised to the Illumina Infinium 27k Human Methylation Beadchip v1.2
Project description:In short: Genome wide promoter DNA methylation profiling of 43 T-ALL samples and 5 T-cell controls (normal bone marrow and stimulated T-cells) . The Illumina Infinium 27k Human DNA methylation Beadchip v1.2 was used to obtain DNA methylation profiles across approximately 27,000 CpGs. Manuscript abstract: Background: Treatment of pediatric T-cell acute lymphoblastic leukemia (T-ALL) has improved, but there is a considerable fraction of patients experiencing a poor outcome. There is a need for better prognostic markers and aberrant DNA methylation is a candidate in other malignancies, but its potential prognostic significance in T-ALL is hitherto undecided. Design and Methods: Genome wide promoter DNA methylation analysis was performed in pediatric T-ALL samples (n=43) using arrays covering >27000 CpG sites. Clinical outcome was evaluated in relation to methylation status and compared with a contemporary T-ALL group not tested for methylation (n= 32). Results: Based on CpG island methylator phenotype (CIMP), T-ALL samples were subgrouped as CIMP+ (high methylation) and CIMP- (low methylation). CIMP- T-ALL patients had significantly worse overall and event free survival (p=0.02 and p=0.001, respectively) compared to CIMP+ cases. CIMP status was an independent factor for survival in multivariate analysis including age, gender and white blood cell count. Analysis of differently methylated genes in the CIMP subgroups showed an overrepresentation of transcription factors, ligands and polycomb target genes. Conclusions: We identified global promoter methylation profiling as being of relevance for subgrouping and prognostication of pediatric T-ALL. Bisulphite converted DNA from the 48 samples were hybridised to the Illumina Infinium 27k Human Methylation Beadchip v1.2
Project description:Confounding due to cellular heterogeneity represents one of the foremost challenges currently facing Epigenome-Wide Association Studies (EWAS). Statistical methods leveraging the tissue-specificity of DNA methylation for deconvoluting the cellular mixture of heterogeneous biospecimens such as whole blood, offer a promising solution. However, their performance depends entirely on the library of DNA methylation markers being used as the basis for deconvolution. The objective of this study was to train and validate an algorithm for the identification of optimal DNA methylation libraries for the deconvolution of adult human whole blood. Purified granulocytes, monocytes, CD4T, CD8T, natural killer cells, and B cells from normal human subjects were purchased from AllCells LLC (Emeryville, CA). DNA extracted from purified leukocyte subtypes were mixed in predetermined proportions to reconstruct two distinct sets of white blood cell (WBC) mixtures, each consisting of six samples. An additional six whole blood (WB) samples from disease-free adult donors with available immune cell profiling data from flow cytometry were purchased from All-Cells LLC and were included in this investigation. All DNA samples were bisulfite modified using the Zymo EZ DNA Methylation kit (Irvine, CA) and profiled for DNA methylation using the Illumina HumanMethylation450 array platform.
Project description:We analyzed 28 fresh frozen samples from pure SCLC patients and 13 noncancerous lung tissues, using the Illumina Infinium 27k Human DNA methylation Beadchip v1.2 Background: Small cell lung cancer (SCLC) accounts for 13-15% of new lung cancer cases in worldwide and has the poor therapeutic outcomes with a median survival of just over one year. A CpG island methylate phenotype (CIMP) is well known as a methylator phenotype with characteristic promoter DNA methylation alterations, in colorectal cancers, glioblastoma and breast cancers, although there has been no report about any CIMP of SCLC. We investigated whether DNA methylation profiles can provide useful molecular subtyping of SCLC in terms of etiology and prognosis of SCLC. Results: We selected a total of 1741 most differentially methylated CpG sites (s.d. > 0.20) across the 28 SCLC tumor tissues in each DNA methylation platform, after an elimination of the probes related with the X- and Y- chromosome. Unsupervised hierarchical clustering of methylation data from SCLC samples reveals two major subgroups with different prognosis: the 5 years disease-free interval (DFI) rate of patients in cluster 1 (11.1%) was lower than that of patients in cluster 2 (61.57%) (p = 0.001). By multivariate analysis for DFI, both postoperative chemotherapy and cluster 1 were a significant prognostic factor (p = 0.002 and 0.002; respectively). Next, among 1220 genes with methylation and expression data both available, the CpG sites were ranked on the basis of the spearman’s correlation coefficient between cluster 1 and cluster 2 into an ascending order. Finally, we identified that fifty-five CpG sites were nagetively correlated and found that apoptosis pathway was a most differentially expressed. Conclusion: By comprehensive DNA methylation profiling, two distinct subgroups with different molecular and clinical phenotype were identified to evoke a CIMP of SCLC. We found some promoter markers in the apoptosis pathway could make a difference between the two groups, and we hope that our data can contribute to provide a useful resource for the construction of therapeutic strategy and the development of a new chemotherapeutic agent. After genomic DNA was treated with sodium bisulfite, bisulfite-converted genomic DNA was analyzed using Illumina’s Infinium HumanMethylation27 BeadChip.
Project description:Genome wide DNA methylation profiling of peripheral blood samples. The Illumina Infinium 450k Human DNA methylation Beadchip was used to obtain DNA methylation profiles across approximately 450,000 CpGs. Samples included 63 of male samples,and 54 of female samples from peripheral leukocytes. All samples were healthy controls. Bisulphite converted DNA from the 117 samples were hybridised to the Illumina Infinium 450k Human Methylation Beadchip. Samples 1-93 were used in a pilot experiment and Samples 101-124 were used in a replicated experiment.
Project description:Gene expression is regulated by genetic variants and DNA methylation with evidence from molecular biology studies, as well as expression QTL (eQTL) mapping and methylation QTL (mQTL) mapping. In this study, we explored the interaction between genetic variants and DNA methylation for its influence on gene expression. We analyzed a postmortem brain data and identified 2,768 SNP-methylation interaction (SMI) that can survive Bonferroni correction for the number of tests in cis- region of each gene. Seven SNP-methylation pairs were significant after Bonferroni correction for all the tests, including number of gene expression traits, we performed in this study. Only a small proportion of the SMI had evidence from the exact same SNP-transcript pair in eQTL mapping or SNP-methylation pair in mQTL mapping. This suggested that the interaction analysis could uncover novel regulatory relationships, which would be missed by eQTL or mQTL analyses. Since methylation per se is regulated by both genetic and environmental factors, analysis indicates that the SMI detected in this study may involve both genetic and environmental regulation. A total of 155 postmortem cerebellum brains were used in this study, including 47 bipolar disorder, 46 schizophrenia, 15 depression patients and 47 normal controls. All were of European Ancestry. We also designed 13 random replicates in our experiment. Illumina Infinium HumanMethylation27 BeadChip was used for DNA methylation profiling. The assay was performed at the Genomics Core Facility at Northwestern University.
Project description:Background: A small number of recent reports have suggested that altered placental DNA methylation may be associated with early onset preeclampsia. It is important that further studies be undertaken to confirm and develop these findings. We therefore undertook a systematic analysis of DNA methylation patterns in placental tissue from 24 women with preeclampsia and 24 with uncomplicated pregnancy outcome. Methods: We analyzed the DNA methylation status of approximately 27,000 CpG sites in placental tissues in a massively parallel fashion using an oligonucleotide microarray. Follow up analysis of DNA methylation at specific CpG loci was performed using the Epityper MassArray approach and high-throughput bisulfite sequencing. Results: Preeclampsia-specific DNA methylation changes were identified in placental tissue samples irrespective of gestational age of delivery. In addition, we identified a group of CpG sites within specific gene sequences that were only altered in early onset-preeclampsia (EOPET) although these DNA methylation changes did not correlate with altered mRNA transcription. We found evidence that fetal gender influences DNA methylation at autosomal loci but could find no clear association between DNA methylation and gestational age. Conclusion: Preeclampsia is associated with altered placental DNA methylation. Fetal gender should be carefully considered during the design of future studies in which placental DNA is analyzed at the level of DNA methylation. Further large-scale analyses of preeclampsia-associated DNA methylation are necessary. Bisulphite converted DNA from the 48 samples were hybridized to the Illumina Infinium 27k Human Methylation Beadchip v1.2