Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

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DNA methylation profiling of whole blood and reconstructed mixtures of purified leukocytes isolated from human adult blood

ABSTRACT: 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.

ORGANISM(S): Homo sapiens

SUBMITTER: Devin Koestler

PROVIDER: E-GEOD-77797 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Project description:Background: Maternal smoking during pregnancy is a major risk factor for adverse health outcomes. The main objective of the study was to assess the impact of in utero tobacco exposure on DNA methylation in children born at term with appropriate weight at birth. Methods: Twenty mother-newborn dyads, after uncomplicated pregnancies, in the absence of perinatal illness were included. All mothers were healthy with no cardiovascular risk factors, except for the associated risks among those mothers who smoked. Umbilical cord blood (for methylation arrays) and maternal peripheral venous blood (for cotine level measurement) were collected and an epigenome-wide association study was performed using a 450K epigenome-wide scan (Illumina Infinium HumanMethylation 450BeadChip) with adjustment to normalize the DNA methylation for data cell variability in whole blood. Results: The maternal plasmatic cotinine levels ranged from 10.70-115.40 ng/ml in the exposed group to 0-0.59 ng/ml in the non-exposed group. After adjusting for multiple comparisons in 427102 probes, statistically significant differences for 31 CpG sites, associated to 25 genes were observed. There was a greater than expected proportion of statistically-significant loci located in CpG islands (FisherM-bM-^@M-^Ys exact test, p=0.029) and of those CpG islands, 90.3% exhibit higher methylation levels in the exposed group. The most striking and significant CpG site, cg05727225, is located in the chromosome 11p15.4, within the adrenomedullin gene. Conclusions: In utero tobacco exposure, even in the absence of fetal growth restriction, may alter the epigenome, contributing to global DNA hypomethylation. Therefore, DNA status can be used as a biomarker of prenatal insults. Considering the possibility to reverse epigenetic modifications, a window of opportunity exists to change the programmed chronic disease. Twenty mother-newborn dyads, after uncomplicated pregnancies, in the absence of perinatal illness were included. All mothers were healthy with no cardiovascular risk factors, except for the associated risks among those mothers who smoked. Umbilical cord blood were collected and an epigenome-wide association study was performed using a 450K epigenome-wide scan (Illumina Infinium HumanMethylation 450BeadChip) with adjustment to normalize the DNA methylation for data cell variability in whole blood.

Project description:Aging is a progressive process that results in the accumulation of intra- and extracellular alterations that in turn contribute to a reduction in health. Age-related changes in DNA methylation have been reported before and may be responsible for aging-induced changes in gene expression, although a causal relationship has yet to be shown. Using genome-wide assays, we analyzed age-induced changes in DNA methylation and their effect on gene expression with and without transient induction with the synthetic transcription modulating agent WY14,643. To demonstrate feasibility of the approach, we isolated peripheral blood mononucleated cells (PBMCs) from five young and five old healthy male volunteers and cultured them with or without WY14,643. Infinium 450K BeadChip and Affymetrix Human Gene 1.1 ST expression array analysis revealed significant differential methylation of at least 5 % (M-NM-^TYOM-bM-^@M-^I>M-bM-^@M-^I5 %) at 10,625 CpG sites between young and old subjects, but only a subset of the associated genes were also differentially expressed. Age-related differential methylation of previously reported epigenetic biomarkers of aging including ELOVL2, FHL2, PENK, and KLF14 was confirmed in our study, but these genes did not display an age-related change in gene expression in PBMCs. Bioinformatic analysis revealed that differentially methylated genes that lack an age-related expression change predominantly represent genes involved in carcinogenesis and developmental processes, and expression of most of these genes were silenced in PBMCs. No changes in DNA methylation were found in genes displaying transiently induced changes in gene expression. In conclusion, aging-induced differential methylation often targets developmental genes and occurs mostly without change in gene expression. Peripheral blood mononuclear cells were isolated from 10 volunteers (5 young 5 old), treated with the synthetic PPARalpha agonists WY14,643 or control for 13 hrs, and subjected to genome-wide DNA methylation and gene expression analysis. This entry contains the DNA methylation data.

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DNA methylation profiling of whole blood and reconstructed mixtures of purified leukocytes isolated from human adult blood

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