Project description:DNA methylation profiles for whole blood, CD4 T cells, CD8 T cells, B cells, Monocytes, Granulocytes, nasal epithelial cells and buccal cells purified from 30 individuals
Project description:Methylation of cytosines at CpG sites is a common epigenetic DNA modification that can be measured by a large number of methods, now even in a genome-wide manner for hundreds of thousands of sites. The application of DNA methylation analysis is becoming widely popular in complex disorders, for example, to understand part of the “missing inheritance”. The DNA samples most readily available for methylation studies are derived from whole blood. However, blood consists of many functionally and developmentally distinct cell populations in varying proportions. We studied whether such variation might affect the interpretation of methylation studies based on whole blood DNA. We found in healthy male blood donors there is important variation in the methylation profiles of whole blood, mononuclear cells, granulocytes, and cells from seven selected purified lineages. CpG methylation between mononuclear cells and granulocytes differed for 22% of the 8252 probes covering the selected 343 genes implicated in immune-related disorders by genome-wide association studies, and at least one probe was differentially methylated for 85% of the genes, indicating that whole blood methylation results might be unintelligible. For individual genes, even if the overall methylation patterns might appear similar, a few CpG sites in the regulatory regions may have opposite methylation patterns (i.e., hypo/hyper) in the main blood cell types. We conclude that interpretation of whole blood methylation profiles should be performed with great caution and for any differences implicated in a disorder, the differences resulting from varying proportions of white blood cell types should be considered.
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).
Project description:Methylation of cytosines at CpG sites is a common epigenetic DNA modification that can be measured by a large number of methods, now even in a genome-wide manner for hundreds of thousands of sites. The application of DNA methylation analysis is becoming widely popular in complex disorders, for example, to understand part of the “missing inheritance”. The DNA samples most readily available for methylation studies are derived from whole blood. However, blood consists of many functionally and developmentally distinct cell populations in varying proportions. We studied whether such variation might affect the interpretation of methylation studies based on whole blood DNA. We found in healthy male blood donors there is important variation in the methylation profiles of whole blood, mononuclear cells, granulocytes, and cells from seven selected purified lineages. CpG methylation between mononuclear cells and granulocytes differed for 22% of the 8252 probes covering the selected 343 genes implicated in immune-related disorders by genome-wide association studies, and at least one probe was differentially methylated for 85% of the genes, indicating that whole blood methylation results might be unintelligible. For individual genes, even if the overall methylation patterns might appear similar, a few CpG sites in the regulatory regions may have opposite methylation patterns (i.e., hypo/hyper) in the main blood cell types. We conclude that interpretation of whole blood methylation profiles should be performed with great caution and for any differences implicated in a disorder, the differences resulting from varying proportions of white blood cell types should be considered. Six healthy male blood donors, age 38 ± 13.6 years, were included in the study. From each individual, global DNA methylation levels were analyzed in whole blood, peripheral blood mononuclear cells (PBMC) and granulocytes as well as for seven isolated cell populations (CD4+ T cells, CD8+ T cells, CD56+ NK cells, CD19+ B cells, CD14+ monocytes, neutrophils, and eosinophils), n=60 samples analyzed in total.
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:Tobacco smoking alters DNA methylation profiles of immune cells which may underpin some of the pathogenesis of smoking-associated diseases. However, approaches linking smoking-driven epigenetic effects in specific immune cell types with disease risk are limited. We isolated six leukocyte subtypes, CD14+ monocytes, CD15+ granulocytes, CD19+ B cells, CD4+ T cells, CD8+ T cells, and CD56+ natural killer cells, from whole blood of healthy adult smokers and nonsmokers for epigenome-wide association study (EWAS).
Project description:An optimized whole genome bisulfite sequencing protocol (µWGBS, Farlik et al. 2015 Cell Reports) was used to establish DNA methylation profiles of FACS-purified stem and progenitor cells types of the human blood lineage. Most cell types were sorted from the peripheral blood of three donors each (43 donors total) with eight pools of ten cells, two pools of 50 cells, and one pool of 1000 cells. Additionally, two cell types (HSC, MPP) were sorted from bone marrow, fetal liver, and cord blood; single-cell methylome sequencing (scWGBS, Farlik et al. 2015 Cell Reports) was done for selected cell types (HSC, MPP, CMP, GMP, CLP, MLP0); and gene expression profiling using the Smart-seq2 protocol (Picelli et al. 2013 Nature Methods) was done on all stem/progenitor cell types (HSC, MPP, CMP, MEP, GMP, CLP, MLP0, MLP1, MLP2, MLP3).
Project description:DNA methylation profiles were generating using Illumina HM450 microarrays in a prospective sample blood from the prenatal period of pregnant mood disorder patients who would and would not develop depression post partum.