scholarly journals High-resolution targeted bisulfite sequencing reveals blood cell type-specific DNA methylation patterns in IL13 and ORMDL3

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Cilla Söderhäll ◽  
Lovisa E. Reinius ◽  
Pertteli Salmenperä ◽  
Massimiliano Gentile ◽  
Nathalie Acevedo ◽  
...  
Keyword(s):  
Dna Methylation ◽  
High Resolution ◽  
Blood Cell ◽  
White Blood Cell ◽  
Disease Risk ◽  
Epigenetic Modification ◽  
Cell Types ◽  
Significant Information ◽  
Targeted Bisulfite Sequencing ◽  
Methylation Of Dna

Abstract Background Methylation of DNA at CpG sites is an epigenetic modification and a potential modifier of disease risk, possibly mediating environmental effects. Currently, DNA methylation is commonly assessed using specific microarrays that sample methylation at a few % of all methylated sites. Methods To understand if significant information on methylation can be added by a more comprehensive analysis of methylation, we set up a quantitative method, bisulfite oligonucleotide-selective sequencing (Bs-OS-seq), and compared the data with microarray-derived methylation data. We assessed methylation at two asthma-associated genes, IL13 and ORMDL3, in blood samples collected from children with and without asthma and fractionated white blood cell types from healthy adult controls. Results Our results show that Bs-OS-seq can uncover vast amounts of methylation variation not detected by commonly used array methods. We found that high-density methylation information from even one gene can delineate the main white blood cell lineages. Conclusions We conclude that high-resolution methylation studies can yield clinically important information at selected specific loci missed by array-based methods, with potential implications for future studies of methylation-disease associations.

scholarly journals Differences in DNA methylation of white blood cell types at birth and in adulthood reflect postnatal immune maturation and influence accuracy of cell type prediction

2018 ◽  
Author(s):  
Meaghan J Jones ◽  
Louie Dinh ◽  
Hamid Reza Razzaghian ◽  
Olivia de Goede ◽  
Julia L MacIsaac ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Immune System ◽  
Blood Cell ◽  
Cord Blood ◽  
White Blood Cell ◽  
Blood Cells ◽  
Cell Types ◽  
Cell Type ◽  
Cell Type Specific ◽  
The Impact

AbstractBackgroundDNA methylation profiling of peripheral blood leukocytes has many research applications, and characterizing the changes in DNA methylation of specific white blood cell types between newborn and adult could add insight into the maturation of the immune system. As a consequence of developmental changes, DNA methylation profiles derived from adult white blood cells are poor references for prediction of cord blood cell types from DNA methylation data. We thus examined cell-type specific differences in DNA methylation in leukocyte subsets between cord and adult blood, and assessed the impact of these differences on prediction of cell types in cord blood.ResultsThough all cell types showed differences between cord and adult blood, some specific patterns stood out that reflected how the immune system changes after birth. In cord blood, lymphoid cells showed less variability than in adult, potentially demonstrating their naïve status. In fact, cord CD4 and CD8 T cells were so similar that genetic effects on DNA methylation were greater than cell type effects in our analysis, and CD8 T cell frequencies remained difficult to predict, even after optimizing the library used for cord blood composition estimation. Myeloid cells showed fewer changes between cord and adult and also less variability, with monocytes showing the fewest sites of DNA methylation change between cord and adult. Finally, including nucleated red blood cells in the reference library was necessary for accurate cell type predictions in cord blood.ConclusionChanges in DNA methylation with age were highly cell type specific, and those differences paralleled what is known about the maturation of the postnatal immune system.

scholarly journals Accurate prediction of cell composition, age, smoking consumption and infection serostatus based on blood DNA methylation profiles

2018 ◽  
Author(s):  
Jacob Bergstedt ◽  
Alejandra Urrutia ◽  
Darragh Duffy ◽  
Matthew L. Albert ◽  
Lluís Quintana-Murci ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Blood Cell ◽  
Regression Models ◽  
Disease Risk ◽  
Association Studies ◽  
Cell Types ◽  
Cellular Heterogeneity ◽  
Cell Composition ◽  
Healthy Donors ◽  
Circulating Levels

DNA methylation is a stable epigenetic alteration that plays a key role in cellular differentiation and gene regulation, and that has been proposed to mediate environmental effects on disease risk. Epigenome-wide association studies have identified and replicated associations between methylation sites and several disease conditions, which could serve as biomarkers in predictive medicine and forensics. Nevertheless, heterogeneity in cellular proportions between the compared groups could complicate interpretation. Reference-based cell-type deconvolution methods have proven useful in correcting epigenomic studies for cellular heterogeneity, but they rely on reference libraries of sorted cells and only predict a limited number of cell populations. Here we leverage >850,000 methylation sites included in the MethylationEPIC array and use elastic net regularized and stability selected regression models to predict the circulating levels of 70 blood cell subsets, measured by standardized flow cytometry in 962 healthy donors of western European descent. We show that our predictions, based on a hundred of methylation sites or lower, are less error-prone than other existing methods, and extend the number of cell types that can be accurately predicted. Application of the same methods to age, smoking consumption and several serological responses to pathogen antigens also provide accurate estimations. Together, our study substantially improves predictions of blood cell composition based on methylation profiles, which will be critical in the emerging field of medical epigenomics.

scholarly journals Cord blood buffy coat DNA methylation is comparable to whole cord blood methylation

2017 ◽  
Author(s):  
John Dou ◽  
Rebecca J. Schmidt ◽  
Kelly S. Benke ◽  
Craig Newschaffer ◽  
Irva Hertz-Picciotto ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Blood Cell ◽  
Cord Blood ◽  
Whole Blood ◽  
Cell Types ◽  
Buffy Coat ◽  
Sample Type ◽  
Blood Samples ◽  
Cell Composition ◽  
Cell Counts

AbstractBackgroundCord blood DNA methylation is associated with numerous health outcomes and environmental exposures. Whole cord blood DNA reflects all nucleated blood cell types, while centrifuging whole blood separates red blood cells by generating a white blood cell buffy coat. Both sample types are used in DNA methylation studies. Cell types have unique methylation patterns and processing can impact cell distributions, which may influence comparability.ObjectivesTo evaluate differences in cell composition and DNA methylation between buffy coat and whole cord blood samples.MethodsCord blood DNA methylation was measured with the Infinium EPIC BeadChip (Illumina) in 8 individuals, each contributing buffy coat and whole blood samples. We analyzed principal components (PC) of methylation, performed hierarchical clustering, and computed correlations of mean-centered methylation between pairs. We conducted moderated t-tests on single sites and estimated cell composition.ResultsDNA methylation PCs were associated with individual (PPC1=1.4x10-9; PPC2=2.9x10-5; PPC3=3.8x10-5; PPC4=4.2x10-6; PPC5=9.9x10-13), and not with sample type (PPC1-5>0.7). Samples hierarchically clustered by individual. Pearson correlations of mean-centered methylation between paired individual samples ranged from r=0.66 to r=0.87. No individual site significantly differed between buffy coat and whole cord blood when adjusting for multiple comparisons (5 sites had unadjusted P<10-5). Estimated cell type proportions did not differ by sample type (P=0.86), and estimated cell counts were highly correlated between paired samples (r=0.99).ConclusionsDifferences in methylation and cell composition between buffy coat and whole cord blood are much lower than inter-individual variation, demonstrating that both sample preparation types can be analytically combined and compared.

scholarly journals Klasifikasi Sel Darah Putih dan Sel Limfoblas Menggunakan Metode Multilayer Perceptron Backpropagation

2019 ◽  
Vol 9 (2) ◽  
pp. 173
Author(s):  
Apri Nur Liyantoko ◽  
Ika Candradewi ◽  
Agus Harjoko
Keyword(s):  
Blood Cell ◽  
White Blood Cell ◽  
Blood Cells ◽  
White Blood Cells ◽  
Back Propagation ◽  
Cell Types ◽  
Diagnostic Process ◽  
The Subject ◽  
Processing Techniques

 Leukemia is a type of cancer that is on white blood cell. This disease are characterized by abundance of abnormal white blood cell called lymphoblast in the bone marrow. Classification of blood cell types, calculation of the ratio of cell types and comparison with normal blood cells can be the subject of diagnosing this disease. The diagnostic process is carried out manually by hematologists through microscopic image. This method is likely to provide a subjective result and time-consuming.The application of digital image processing techniques and machine learning in the process of classifying white blood cells can provide more objective results. This research used thresholding method as segmentation and  multilayer method of back propagation perceptron with variations in the extraction of textural features, geometry, and colors. The results of segmentation testing in this study amounted to 68.70%. Whereas the classification test shows that the combination of feature extraction of GLCM features, geometry features, and color features gives the best results. This test produces an accuration value 91.43%, precision value of 50.63%, sensitivity 56.67%, F1Score 51.95%, and specitifity 94.16%.

scholarly journals Utilization of Epigenome-wide DNA Methylation for Longitudinal Comparison of White Blood Cell Proportions Across Preeclamptic and Normotensive Pregnancy by Self-Reported Race

2020 ◽  
Author(s):  
Mitali Ray ◽  
Lacey W. Heinsberg ◽  
Yvette P. Conley ◽  
James M. Roberts ◽  
Arun Jeyabalan ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Blood Cell ◽  
B Cell ◽  
White Blood Cell ◽  
Nk Cell ◽  
Calibration Method ◽  
Small Sample ◽  
Methylation Data ◽  
Longitudinal Comparison ◽  
The Relationship

Objective: We utilized epigenome-wide DNA methylation data to estimate/compare white blood cell (WBC) proportions in plasma across preeclamptic (case) and uncomplicated, normotensive (control) pregnancy. Methods: We previously collected methylation data using Infinium MethylationEPIC Beadchips during the three trimesters in 28 cases and 28 controls (21 Black, 7 White participants/group). We employed the Houseman regression calibration method to estimate and compare neutrophil, monocyte, B cell, NK cell, CD4+ T and CD8+ T cell proportions across pregnancy and between cases and controls. Results: We observed changes in WBC proportions across pregnancy within cases and controls that varied by cell type and race. Neutrophils represented the largest WBC mean proportion in all three trimesters for cases (Mean+/-SD: 67.2+/-9.6% to 74.4+/-12%) and controls (64.2+/-11% to 74.0+/-7.9%). Mean B cell proportions were significantly lower in cases than controls in Trimester 1 (5.25+/-0.02% versus 6.30+/-0.02%, p=0.02). The remaining mean cell proportions did not significantly differ in the overall sample. Stratified analyses revealed race-specific differences. In White participants (n=14): (1) neutrophil proportions were significantly higher in cases in Trimester 1 (p=0.04), but significantly lower in Trimester 2 (p=0.02), (2) B cell proportions were significantly lower in cases in Trimester 1 (p=0.001). No significant differences were detected among Black participants (n=42). Conclusions: Although chronic inflammation characterizes preeclampsia, few studies have investigated WBCs across pregnancy. We report differences between cases and controls across pregnancy. Our findings in a small sample demonstrate the need for additional studies investigating the relationship between race and WBCs in pregnancy, which could provide insight into preeclampsia pathophysiology.

scholarly journals Postprandial alterations in whole-blood DNA methylation are mediated by changes in white blood cell composition

2016 ◽  
Vol 104 (2) ◽  
pp. 518-525 ◽  
Author(s):  
Mathias Rask-Andersen ◽  
Nathalie Bringeland ◽  
Emil K Nilsson ◽  
Marcus Bandstein ◽  
Marcela Olaya Búcaro ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Blood Cell ◽  
White Blood Cell ◽  
Whole Blood ◽  
Cell Composition

scholarly journals Temporal Stability and Determinants of White Blood Cell DNA Methylation in the Breakthrough Generations Study

2014 ◽  
Vol 24 (1) ◽  
pp. 221-229 ◽  
Author(s):  
James M. Flanagan ◽  
Mark N. Brook ◽  
Nick Orr ◽  
Katarzyna Tomczyk ◽  
Penny Coulson ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Blood Cell ◽  
White Blood Cell ◽  
Temporal Stability

scholarly journals Global DNA methylation levels in white blood cell DNA from sisters discordant for breast cancer from the New York site of the Breast Cancer Family Registry

Epigenetics ◽  
2012 ◽  
Vol 7 (8) ◽  
pp. 868-874 ◽  
Author(s):  
Lissette Delgado-Cruzata ◽  
Hui-Chen Wu ◽  
Mary Perrin ◽  
Yuyan Liao ◽  
Maya A. Kappil ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Dna Methylation ◽  
New York ◽  
Blood Cell ◽  
White Blood Cell ◽  
Global Dna Methylation ◽  
Breast Cancer Family ◽  
Cancer Family

scholarly journals Reference-Based Versus Reference-Free Cell Type Estimation In DNA Methylation Studies Using Human Placental Tissue

2021 ◽  
Author(s):  
Linda Dieckmann ◽  
Cristiana Cruceanu ◽  
Marius Lahti-Pulkkinen ◽  
Jari Lahti ◽  
Tuomas Kvist ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Human Placenta ◽  
Disease Risk ◽  
Placental Tissue ◽  
Predictive Performance ◽  
Cell Types ◽  
Free Cell ◽  
Estimation Methods ◽  
Cell Type ◽  
Chorion Villus

Abstract The placenta is a central organ during early development, influencing trajectories of health and disease. DNA methylation (DNAm) studies of human placenta improve our understanding of how its function relates to disease risk. However, DNAm studies can be biased by cell type heterogeneity, so it is essential to control for this in order to reduce confounding and increase precision. Computational cell type deconvolution approaches have proven to be very useful for this purpose. For human placenta, however, an assessment of the performance of these estimation methods is still lacking. Here, we compare the predictive performance of reference-based versus reference-free estimated proportions of cell types from genome-wide DNAm in placental samples taken at birth and from chorion villus biopsies early in pregnancy using three independent studies comprising over 1,000 samples. We found both reference-free and reference-based estimated cell type proportions to have predictive value for DNAm, however, reference-based cell type estimation outperformed reference-free estimation for the majority of data sets. Reference-based cell type estimations mirror previous histological knowledge on changes in cell type proportions through gestation. Further, CpGs whose variation in DNAm was largely explained by reference-based estimated cell type proportions were in the proximity of genes that are highly tissue-specific for placenta. This was not the case for reference-free estimated cell type proportions. We provide a list of these CpGs as a resource to help researchers to interpret results of existing studies and improve future DNAm studies of human placenta.

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