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 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 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.

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 Heritability enrichment implicates microglia in Parkinson’s disease pathogenesis

2020 ◽  
Author(s):  
Maren Stolp Andersen ◽  
Sara Bandres-Ciga ◽  
Regina H. Reynolds ◽  
John Hardy ◽  
Mina Ryten ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Disease Risk ◽  
Association Studies ◽  
Cell Types ◽  
Polygenic Risk Score ◽  
Open Chromatin ◽  
Specific Cell ◽  
Genome Wide Association Studies ◽  
Therapeutic Implications

AbstractObjectiveUnderstanding how different parts of the immune system contribute to pathogenesis in Parkinson’s disease is a burning challenge with important therapeutic implications. We studied enrichment of common variant heritability for Parkinson’s disease stratified by immune and brain cell types.MethodsWe used summary statistics from the most recent meta-analysis of genome-wide association studies in Parkinson’s disease and partitioned heritability using linkage disequilibrium score regression, stratified for specific cell types as defined by open chromatin regions. We also validated enrichment results using a polygenic risk score approach and intersected disease-associated variants with epigenetic data and expression quantitative loci to nominate and explore a putative microglial locus.ResultsWe found significant enrichment of Parkinson’s disease risk heritability in open chromatin regions of microglia and monocytes. Genomic annotations overlapped substantially between these two cell types, and only the enrichment signal for microglia remained significant in a joint model. We present evidence suggesting P2RY12, a key microglial gene and target for the anti-thrombotic agent clopidogrel, as the likely driver of a significant Parkinson’s disease association signal on chromosome 3.InterpretationOur results provide further support for the importance of immune mechanisms in PD pathogenesis, highlight microglial dysregulation as a contributing etiological factor and nominate a targetable microglial gene candidate as a pathogenic player. Immune processes can be modulated by therapy, with potentially important clinical implications for future treatment in Parkinson’s disease.

scholarly journals Reference-free deconvolution of DNA methylation data and mediation by cell composition effects

2016 ◽  
Author(s):  
E. Andres Houseman ◽  
Molly L. Kile ◽  
David C. Christiani ◽  
Tan A. Ince ◽  
Karl T. Kelsey ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Reference Data ◽  
Cell Types ◽  
Data Sets ◽  
Phenotypic Data ◽  
Simple Method ◽  
Cell Composition ◽  
Composition Effects ◽  
Heterogeneous Tissues ◽  
Cell Proportion

AbstractWe propose a simple method for reference-free deconvolution that provides both proportions of putative cell types defined by their underlying methylomes, the number of these constituent cell types, as well as a method for evaluating the extent to which the underlying methylomes reflect specific types of cells. We have demonstrated these methods in an analysis of 23 Infinium data sets from 13 distinct data collection efforts; these empirical evaluations show that our algorithm can reasonably estimate the number of constituent types, return cell proportion estimates that demonstrate anticipated associations with underlying phenotypic data; and methylomes that reflect the underlying biology of constituent cell types. Thus the methodology permits an explicit quantitation of the mediation of phenotypic associations with DNA methylation by cell composition effects. Although more work is needed to investigate functional information related to estimated methylomes, our proposed method provides a novel and useful foundation for conducting DNA methylation studies on heterogeneous tissues lacking reference data.

scholarly journals DNA Methylation Profiles of Purified Cell Types in Bronchoalveolar Lavage: Applications for Mixed Cell Paediatric Pulmonary Studies

2021 ◽  
Vol 12 ◽  
Author(s):  
Shivanthan Shanthikumar ◽  
Melanie R. Neeland ◽  
Richard Saffery ◽  
Sarath C. Ranganathan ◽  
Alicia Oshlack ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Bronchoalveolar Lavage ◽  
Association Studies ◽  
Cell Types ◽  
Alveolar Epithelial Cells ◽  
Cell Type ◽  
Mixed Cell ◽  
Alveolar Epithelial ◽  
Cell Type Composition ◽  
Type Composition

In epigenome-wide association studies analysing DNA methylation from samples containing multiple cell types, it is essential to adjust the analysis for cell type composition. One well established strategy for achieving this is reference-based cell type deconvolution, which relies on knowledge of the DNA methylation profiles of purified constituent cell types. These are then used to estimate the cell type proportions of each sample, which can then be incorporated to adjust the association analysis. Bronchoalveolar lavage is commonly used to sample the lung in clinical practice and contains a mixture of different cell types that can vary in proportion across samples, affecting the overall methylation profile. A current barrier to the use of bronchoalveolar lavage in DNA methylation-based research is the lack of reference DNA methylation profiles for each of the constituent cell types, thus making reference-based cell composition estimation difficult. Herein, we use bronchoalveolar lavage samples collected from children with cystic fibrosis to define DNA methylation profiles for the four most common and clinically relevant cell types: alveolar macrophages, granulocytes, lymphocytes and alveolar epithelial cells. We then demonstrate the use of these methylation profiles in conjunction with an established reference-based methylation deconvolution method to estimate the cell type composition of two different tissue types; a publicly available dataset derived from artificial blood-based cell mixtures and further bronchoalveolar lavage samples. The reference DNA methylation profiles developed in this work can be used for future reference-based cell type composition estimation of bronchoalveolar lavage. This will facilitate the use of this tissue in studies examining the role of DNA methylation in lung health and disease.

scholarly journals Differential DNA methylation and changing cell-type proportions as fibrotic stage progresses in NAFLD

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Nicholas D. Johnson ◽  
Xiumei Wu ◽  
Christopher D. Still ◽  
Xin Chu ◽  
Anthony T. Petrick ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Cell Types ◽  
Disease Stage ◽  
Rna Seq ◽  
Cell Type ◽  
Alcoholic Fatty Liver ◽  
Cell Composition ◽  
Cpg Sites ◽  
Plausible Mechanism ◽  
The Relationship

Abstract Background Non-alcoholic fatty liver disease (NAFLD) is characterized by changes in cell composition that occur throughout disease pathogenesis, which includes the development of fibrosis in a subset of patients. DNA methylation (DNAm) is a plausible mechanism underlying these shifts, considering that DNAm profiles differ across tissues and cell types, and DNAm may play a role in cell-type differentiation. Previous work investigating the relationship between DNAm and fibrosis in NAFLD has been limited by sample size and the number of CpG sites interrogated. Results Here, we performed an epigenome-wide analysis using Infinium MethylationEPIC array data from 325 individuals with NAFLD, including 119 with severe fibrosis and 206 with no histological evidence of fibrosis. After adjustment for latent confounders, we identified 7 CpG sites whose DNAm associated with fibrosis (p < 5.96 × 10–8). Analysis of RNA-seq data collected from a subset of individuals (N = 56) revealed that gene expression at 288 genes associated with DNAm at one or more of the 7 fibrosis-related CpGs. DNAm-based estimates of cell-type proportions showed that estimated proportions of natural killer cells increased, while epithelial cell proportions decreased with disease stage. Finally, we used an elastic net regression model to assess DNAm as a biomarker of fibrotic stage and found that our model predicted fibrosis with a sensitivity of 0.93 and provided information beyond a model based solely on cell-type proportions. Conclusion These findings are consistent with DNAm as a mechanism underpinning or marking fibrosis-related shifts in cell composition and demonstrate the potential of DNAm as a possible biomarker of NAFLD fibrosis.

It’s in the Bloody Genes!

2020 ◽  
Vol 23 (2) ◽  
pp. 96-97
Author(s):  
David M. Evans
Keyword(s):  
Blood Cell ◽  
Association Studies ◽  
Cell Types ◽  
Linkage Studies ◽  
Genetic Loci ◽  
Twin Registry ◽  
Cell Concentrations ◽  
Genomewide Association

AbstractBlood cell concentrations for most cell types are highly heritable. Data from Nick Martin’s twin registry provided much of the data for the early heritability and linkage studies of blood cell related traits and have contributed significantly to more recent genomewide association studies that have successfully identified individual genetic loci.

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