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 Assessing the co-variability of DNA methylation across peripheral cells and tissues: implications for the interpretation of findings in epigenetic epidemiology

2020 ◽  
Author(s):  
Eilis Hannon ◽  
Georgina Mansell ◽  
Joe Burrage ◽  
Agnieszka Kepa ◽  
Janis Best-Lane ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Blood Cell ◽  
Whole Blood ◽  
Cell Types ◽  
Sample Type ◽  
Cell Type ◽  
Peripheral Tissues ◽  
Multiple Loci ◽  
Blood Cell Type ◽  
Variance Explained

Summary/AbstractBackgroundMost epigenome-wide association studies (EWAS) quantify DNA methylation (DNAm) in peripheral tissues such as whole blood to identify positions in the genome where variation is statistically associated with a trait or exposure. As whole blood comprises a mix of cell types, it is unclear whether trait-associated variation is specific to an individual cellular population.MethodsWe collected three peripheral tissues (whole blood, buccal and nasal epithelial cells) from thirty individuals. Whole blood samples were subsequently processed using fluorescence-activated cell sorting (FACS) to purify five constituent cell-types (monocytes, granulocytes, CD4+ T cells, CD8+ T cells, and B cells). DNAm was profiled in all eight sample-types from each individual using the Illumina EPIC array.ResultsWe identified significant differences in both the level and variability of DNAm between different tissues and cell types, and DNAm data-derived estimates of age and smoking were found to differ dramatically across sample types from the same individual. We found that for the majority of loci variation in DNAm in individual blood cell types was only weakly predictive of variance in DNAm measured in whole blood, however, the proportion of variance explained was greater than that explained by either buccal or nasal tissues. Instead we observe that DNAm variation in whole blood is additively influenced by a combination of the major blood cell types. For a subset of sites variable DNAm detected in whole blood can be attributed to variation in a single blood cell type providing potential mechanistic insight.ConclusionsWe identified major differences in DNAm between blood cell types and peripheral tissues, with each sample type being characterized by a unique DNAm signature across multiple loci. Our results suggest that associations between whole blood DNAm and traits or exposures reflect differences in multiple cell types and provide important insights for the interpretation of EWAS performed in whole blood.Key MessagesWe identified major differences in DNA methylation between blood cell types and peripheral tissues, with each sample type being characterized by a unique DNA methylation signature across multiple loci.Estimates of DNAmAge and tobacco smoking from DNA methylation data can be highly variable across different sample types collected from the same individual at the same time.While individual blood cell types did predict more of the variation in whole blood compared to buccal epithelial and nasal epithelial cells, the percentage of variance explained was still small.Instead our data indicate that at the majority of sites, variation in multiple blood cell types additively combines to drive variation in DNA methylation in whole blood.There are subset of sites where variable DNA methylation detected in whole blood can be attributed to variation in a single blood cell type.

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 Hematopoietic Lineage Transcriptome Stability and Representation in PAXgene™ Collected Peripheral Blood Utilising SPIA Single-Stranded cDNA Probes for Microarray

2008 ◽  
Vol 3 ◽  
pp. BMI.S938 ◽  
Author(s):  
Laura Kennedy ◽  
J. Keith Vass ◽  
D. Ross Haggart ◽  
Steve Moore ◽  
Michael E. Burczynski ◽  
...  
Keyword(s):  
Gene Expression ◽  
Blood Cell ◽  
Whole Blood ◽  
Peripheral Blood ◽  
Expression Profiles ◽  
Cell Types ◽  
Great Promise ◽  
Microarray Probe ◽  
Blood Samples ◽  
Transcriptional Profiles

Peripheral blood as a surrogate tissue for transcriptome profiling holds great promise for the discovery of diagnostic and prognostic disease biomarkers, particularly when target tissues of disease are not readily available. To maximize the reliability of gene expression data generated from clinical blood samples, both the sample collection and the microarray probe generation methods should be optimized to provide stabilized, reproducible and representative gene expression profiles faithfully representing the transcriptional profiles of the constituent blood cell types present in the circulation. Given the increasing innovation in this field in recent years, we investigated a combination of methodological advances in both RNA stabilisation and microarray probe generation with the goal of achieving robust, reliable and representative transcriptional profiles from whole blood. To assess the whole blood profiles, the transcriptomes of purified blood cell types were measured and compared with the global transcriptomes measured in whole blood. The results demonstrate that a combination of PAXgene™ RNA stabilising technology and single-stranded cDNA probe generation afforded by the NuGEN Ovation RNA amplification system V2™ enables an approach that yields faithful representation of specific hematopoietic cell lineage transcriptomes in whole blood without the necessity for prior sample fractionation, cell enrichment or globin reduction. Storage stability assessments of the PAXgene™ blood samples also advocate a short, fixed room temperature storage time for all PAXgene™ blood samples collected for the purposes of global transcriptional profiling in clinical studies.

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 DNA methylation of cord blood cell types: Applications for mixed cell birth studies

Epigenetics ◽  
2016 ◽  
Vol 11 (5) ◽  
pp. 354-362 ◽  
Author(s):  
Kelly M. Bakulski ◽  
Jason I. Feinberg ◽  
Shan V. Andrews ◽  
Jack Yang ◽  
Shannon Brown ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Blood Cell ◽  
Cord Blood ◽  
Cell Types ◽  
Mixed Cell ◽  
Cord Blood Cell

scholarly journals The effect of smoking on chronic inflammation, immune function and blood cell composition

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Ingrid Elisia ◽  
Vivian Lam ◽  
Brandon Cho ◽  
Mariah Hay ◽  
Michael Yu Li ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Blood Cell ◽  
Whole Blood ◽  
Blood Samples ◽  
E Coli ◽  
Cell Composition ◽  
Adaptive Immune ◽  
Preventative Measures ◽  
Whole Blood Samples ◽  
Heavy Smokers

Abstract Smoking is the number one risk factor for cancer mortality but only 15–20% of heavy smokers develop lung cancer. It would, therefore, be of great benefit to identify those at high risk early on so that preventative measures can be initiated. To investigate this, we evaluated the effects of smoking on inflammatory markers, innate and adaptive immune responses to bacterial and viral challenges and blood cell composition. We found that plasma samples from 30 heavy smokers (16 men and 14 women) had significantly higher CRP, fibrinogen, IL-6 and CEA levels than 36 non-smoking controls. Whole blood samples from smokers, incubated for 7 h at 37 °C in the absence of any exogenous stimuli, secreted significantly higher levels of IL-8 and a number of other cytokines/chemokines than non-smokers. When challenged for 7 h with E. coli, whole blood samples from smokers secreted significantly lower levels of many inflammatory cytokines/chemokines. However, when stimulated with HSV-1, significantly higher levels of both PGE2 and many cytokines/chemokines were secreted from smokers’ blood samples than from controls. In terms of blood cell composition, red blood cells, hematocrits, hemoglobin levels, MCV, MCH, MCHC, Pct and RDW levels were all elevated in smokers, in keeping with their compromised lung capacity. As well, total leukocytes were significantly higher, driven by increases in granulocytes and monocytes. In addition, smokers had lower NK cells and higher Tregs than controls, suggesting that smoking may reduce the ability to kill nascent tumor cells. Importantly, there was substantial person-to person variation amongst smokers with some showing markedly different values from controls and others showing normal levels of many parameters measured, indicating the former may be at significantly higher risk of developing lung cancer.

scholarly journals Leukocyte Counts Based on DNA Methylation at Individual Cytosines

2018 ◽  
Vol 64 (3) ◽  
pp. 566-575 ◽  
Author(s):  
Joana Frobel ◽  
Tanja Božić ◽  
Michael Lenz ◽  
Peter Uciechowski ◽  
Yang Han ◽  
...  
Keyword(s):  
Dna Methylation ◽  
T Cells ◽  
Blood Cell ◽  
White Blood Cell ◽  
Absolute Quantification ◽  
Blood Samples ◽  
Cell Numbers ◽  
Cell Counts ◽  
Blood Cell Counts ◽  
White Blood Cell Counts

Abstract BACKGROUND White blood cell counts are routinely measured with automated hematology analyzers, by flow cytometry, or by manual counting. Here, we introduce an alternative approach based on DNA methylation (DNAm) at individual CG dinucleotides (CpGs). METHODS We identified candidate CpGs that were nonmethylated in specific leukocyte subsets. DNAm levels (ranging from 0% to 100%) were analyzed by pyrosequencing and implemented into deconvolution algorithms to determine the relative composition of leukocytes. For absolute quantification of cell numbers, samples were supplemented with a nonmethylated reference DNA. RESULTS Conventional blood counts correlated with DNAm at individual CpGs for granulocytes (r = −0.91), lymphocytes (r = −0.91), monocytes (r = −0.74), natural killer (NK) cells (r = −0.30), T cells (r = −0.73), CD4+ T cells (r = −0.41), CD8+ T cells (r = −0.88), and B cells (r = −0.66). Combination of these DNAm measurements into the “Epi-Blood-Count” provided similar precision as conventional methods in various independent validation sets. The method was also applicable to blood samples that were stored at 4 °C for 7 days or at −20 °C for 3 months. Furthermore, absolute cell numbers could be determined in frozen blood samples upon addition of a reference DNA, and the results correlated with measurements of automated analyzers in fresh aliquots (r = 0.84). CONCLUSIONS White blood cell counts can be reliably determined by site-specific DNAm analysis. This approach is applicable to very small blood volumes and frozen samples, and it allows for more standardized and cost-effective analysis in clinical application.

scholarly journals Assessing the co-variability of DNA methylation across peripheral cells and tissues: Implications for the interpretation of findings in epigenetic epidemiology

PLoS Genetics ◽  
2021 ◽  
Vol 17 (3) ◽  
pp. e1009443
Author(s):  
Eilis Hannon ◽  
Georgina Mansell ◽  
Emma Walker ◽  
Marta F. Nabais ◽  
Joe Burrage ◽  
...  
Keyword(s):  
Dna Methylation ◽  
T Cells ◽  
Blood Cell ◽  
Whole Blood ◽  
Association Studies ◽  
Cell Types ◽  
Peripheral Tissues ◽  
Epigenetic Epidemiology ◽  
Blood Cell Type ◽  
Multiple Cell

Most epigenome-wide association studies (EWAS) quantify DNA methylation (DNAm) in peripheral tissues such as whole blood to identify positions in the genome where variation is statistically associated with a trait or exposure. As whole blood comprises a mix of cell types, it is unclear whether trait-associated DNAm variation is specific to an individual cellular population. We collected three peripheral tissues (whole blood, buccal epithelial and nasal epithelial cells) from thirty individuals. Whole blood samples were subsequently processed using fluorescence-activated cell sorting (FACS) to purify five constituent cell-types (monocytes, granulocytes, CD4+ T cells, CD8+ T cells, and B cells). DNAm was profiled in all eight sample-types from each individual using the Illumina EPIC array. We identified significant differences in both the level and variability of DNAm between different sample types, and DNAm data-derived estimates of age and smoking were found to differ dramatically across sample types from the same individual. We found that for the majority of loci variation in DNAm in individual blood cell types was only weakly predictive of variance in DNAm measured in whole blood, although the proportion of variance explained was greater than that explained by either buccal or nasal epithelial samples. Covariation across sample types was much higher for DNAm sites influenced by genetic factors. Overall, we observe that DNAm variation in whole blood is additively influenced by a combination of the major blood cell types. For a subset of sites, however, variable DNAm detected in whole blood can be attributed to variation in a single blood cell type providing potential mechanistic insight about EWAS findings. Our results suggest that associations between whole blood DNAm and traits or exposures reflect differences in multiple cell types and our data will facilitate the interpretation of findings in epigenetic epidemiology.

scholarly journals Accelerated hematopoietic mitotic aging measured by DNA methylation, blood cell lineage, and Parkinson’s disease

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Kimberly C Paul ◽  
Alexandra M Binder ◽  
Steve Horvath ◽  
Cynthia Kusters ◽  
Qi Yan ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Dna Methylation ◽  
Parkinson's Disease ◽  
Blood Cell ◽  
Cell Lineage ◽  
Cell Types ◽  
Lymphoid Cells ◽  
Cell Composition ◽  
Epigenetic Age ◽  
Epigenetic Age Acceleration

Abstract Background Aging and inflammation are important components of Parkinson’s disease (PD) pathogenesis and both are associated with changes in hematopoiesis and blood cell composition. DNA methylation (DNAm) presents a mechanism to investigate inflammation, aging, and hematopoiesis in PD, using epigenetic mitotic aging and aging clocks. Here, we aimed to define the influence of blood cell lineage on epigenetic mitotic age and then investigate mitotic age acceleration with PD, while considering epigenetic age acceleration biomarkers. Results We estimated epigenetic mitotic age using the “epiTOC” epigenetic mitotic clock in 10 different blood cell populations and in a population-based study of PD with whole-blood. Within subject analysis of the flow-sorted purified blood cell types DNAm showed a clear separation of epigenetic mitotic age by cell lineage, with the mitotic age significantly lower in myeloid versus lymphoid cells (p = 2.1e-11). PD status was strongly associated with accelerated epigenetic mitotic aging (AccelEpiTOC) after controlling for cell composition (OR = 2.11, 95 % CI = 1.56, 2.86, p = 1.6e-6). AccelEpiTOC was also positively correlated with extrinsic epigenetic age acceleration, a DNAm aging biomarker related to immune system aging (with cell composition adjustment: R = 0.27, p = 6.5e-14), and both were independently associated with PD. Among PD patients, AccelEpiTOC measured at baseline was also associated with longitudinal motor and cognitive symptom decline. Conclusions The current study presents a first look at epigenetic mitotic aging in PD and our findings suggest accelerated hematopoietic cell mitosis, possibly reflecting immune pathway imbalances, in early PD that may also be related to motor and cognitive progression.

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