Similar Datasets
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
2021-02-19 | GSE166844 | GEO
Project description:Genome-wide DNA methylation was measured using the Illumina 450K array in T cells, monocytes, granulocytes and nucleated red blood cells (nRBCs) isolated from cord blood of term and extreme preterm (<31 weeks gestational age) individuals. 36 samples in total: 5 each of T cells, monocytes, granulocytes and nRBCs from term births; and 5 T cells, 4 monocytes, 4 nRBCs and 3 granulocytes from preterm births.
2017-04-21 | GSE82084 | GEO
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).
2023-06-20 | GSE224807 | GEO
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.
2012-08-02 | E-GEOD-35069 | biostudies-arrayexpress
Project description:DNA methylation profiles of Purified Blood Cell types
| PRJNA702111 | ENA
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.
2016-02-12 | E-GEOD-77797 | biostudies-arrayexpress
Project description:miR-Blood is a high-quality, small RNA expression atlas for the major components of human peripheral blood (plasma, erythrocytes, thrombocytes, monocytes, neutrophils, eosinophils, basophils, natural killer cells, CD4+ T cells, CD8+ T cells, and B cells). *** The data provided in this GEO dataset is licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). ***
2024-01-16 | GSE225872 | GEO
Project description:Expression data from purified mouse CD4+ T cells
| PRJNA429803 | ENA
Project description:The objective of this study is to: 1) Characterize the cellular origin of transciptional signatures observed on day 1 after vaccination with 2009/10 seasonal influenza and pneumococcal vaccine discovered by transcriptional profiling of whole blood samples in data set “WholeBlood_SysVax”. 2) Discover potential biomarkers for immune-responsiveness to non-live vaccines. In this Series, a total of 72 samples of leukocyte subsets (neutrophils, monocytes, CD4+ T and CD8+ T lymphocytes) were isolated before and 24 hours after vaccination from 6 healthy adult individuals receiving seasonal influenza and 4 healthy adult individuals receiving pneumococcal vaccine. From each subject, neutrophils and peripheral blood mononuclear cells were obtained by Ficoll gradient separation and then CD14+ monocytes, CD4+ T and CD8+ T cells were purified by sequential positive bead selection. Cells were transferred into RLT buffer and stored at -80ºC until mRNA extraction.
2013-07-10 | E-GEOD-30059 | biostudies-arrayexpress
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.
2012-08-03 | GSE35069 | GEO