scholarly journals Testing cell-type-specific mediation effects in genome-wide epigenetic studies

Author(s):  
Xiangyu Luo ◽  
Joel Schwartz ◽  
Andrea Baccarelli ◽  
Zhonghua Liu

Abstract Epigenome-wide mediation analysis aims to identify DNA methylation CpG sites that mediate the causal effects of genetic/environmental exposures on health outcomes. However, DNA methylations in the peripheral blood tissues are usually measured at the bulk level based on a heterogeneous population of white blood cells. Using the bulk level DNA methylation data in mediation analysis might cause confounding bias and reduce study power. Therefore, it is crucial to get fine-grained results by detecting mediation CpG sites in a cell-type-specific way. However, there is a lack of methods and software to achieve this goal. We propose a novel method (Mediation In a Cell-type-Specific fashion, MICS) to identify cell-type-specific mediation effects in genome-wide epigenetic studies using only the bulk-level DNA methylation data. MICS follows the standard mediation analysis paradigm and consists of three key steps. In step1, we assess the exposure-mediator association for each cell type; in step 2, we assess the mediator-outcome association for each cell type; in step 3, we combine the cell-type-specific exposure-mediator and mediator-outcome associations using a multiple testing procedure named MultiMed [Sampson JN, Boca SM, Moore SC, et al. FWER and FDR control when testing multiple mediators. Bioinformatics 2018;34:2418–24] to identify significant CpGs with cell-type-specific mediation effects. We conduct simulation studies to demonstrate that our method has correct FDR control. We also apply the MICS procedure to the Normative Aging Study and identify nine DNA methylation CpG sites in the lymphocytes that might mediate the effect of cigarette smoking on the lung function.

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Hanyu Zhang ◽  
Ruoyi Cai ◽  
James Dai ◽  
Wei Sun

AbstractWe introduce a new computational method named EMeth to estimate cell type proportions using DNA methylation data. EMeth is a reference-based method that requires cell type-specific DNA methylation data from relevant cell types. EMeth improves on the existing reference-based methods by detecting the CpGs whose DNA methylation are inconsistent with the deconvolution model and reducing their contributions to cell type decomposition. Another novel feature of EMeth is that it allows a cell type with known proportions but unknown reference and estimates its methylation. This is motivated by the case of studying methylation in tumor cells while bulk tumor samples include tumor cells as well as other cell types such as infiltrating immune cells, and tumor cell proportion can be estimated by copy number data. We demonstrate that EMeth delivers more accurate estimates of cell type proportions than several other methods using simulated data and in silico mixtures. Applications in cancer studies show that the proportions of T regulatory cells estimated by DNA methylation have expected associations with mutation load and survival time, while the estimates from gene expression miss such associations.


Circulation ◽  
2017 ◽  
Vol 135 (suppl_1) ◽  
Author(s):  
Xiaoling Wang ◽  
Yue Pan ◽  
Haidong Zhu ◽  
Guang Hao ◽  
Xin Wang ◽  
...  

Background: Several large-scale epigenome wide association studies on obesity-related DNA methylation changes have been published and in total identified 46 CpG sites. These studies were conducted in middle-aged and older adults of Caucasians and African Americans (AAs) using leukocytes. To what extend these signals are independent of cell compositions as well as to what extend they may influence gene expression have not been systematically investigated. Furthermore, the high prevalence of obesity comorbidities in middle-aged or older population may hide or bias obesity itself related DNA methylation changes. Methods: In this study of healthy AA youth and young adults, genome wide DNA methylation data from leukocytes were obtained from three independent studies: EpiGO study (96 obese cases vs. 92 lean controls, aged 14-21, 50% females, test of interest is obesity status), LACHY study (284 participants from general population, aged 14-18, 50% females, test of interest is BMI), and Georgia Stress and Heart study (298 participants from general population, aged 18-38, 52% females, test of interest is BMI) using the Infinium HumanMethylation450 BeadChip. Genome wide DNA methylation data from purified neutrophils as well as genome wide gene expression data from leukocytes using Illumina HT12 V4 array were also obtained for the EpiGO samples. Results: The meta-analysis on the 3 cohorts identified 76 obesity related CpG sites in leukocytes with p<1х10 -7 . Out of the 46 previously identified CpG sites, 36 can be replicated in this AA youth and young adult sample with same direction and p<0.05. Out of the 107 CpG sites including the 36 replicated ones and the 71 newly identified ones, 71 CpG sites (66%) had their relationship with obesity replicated in purified neutrophils (p<0.05). The analysis on the cis regulation of the 107 CpG sites on gene expression showed that 59 CpG sites had at least one gene within 250kb having expression difference between obese cases and lean controls. Furthermore, out of the 59 CpG sites, 6 showed significantly negative correlations and 1 showed significantly positive correlation with the differentially expressed genes. These CpG sites located in SOCS3, CISH, ABCG1, PIM3 and PTGDS genes. Conclusion: In this study of AA youth and young adults, we identified novel CpG sites associated with obesity and replicated majority of the CpG sites previously identified in middle-aged and older adults. For the first time, we showed that majority of the obesity related CpG sites identified from leukocytes are not driven by cell compositions and provided the direct link between DNA methylation-gene expression-obesity status for 7 CpG sites in 5 genes.


2019 ◽  
Author(s):  
Igor Mačinković ◽  
Ina Theofel ◽  
Tim Hundertmark ◽  
Kristina Kovač ◽  
Stephan Awe ◽  
...  

Abstract CoREST has been identified as a subunit of several protein complexes that generate transcriptionally repressive chromatin structures during development. However, a comprehensive analysis of the CoREST interactome has not been carried out. We use proteomic approaches to define the interactomes of two dCoREST isoforms, dCoREST-L and dCoREST-M, in Drosophila. We identify three distinct histone deacetylase complexes built around a common dCoREST/dRPD3 core: A dLSD1/dCoREST complex, the LINT complex and a dG9a/dCoREST complex. The latter two complexes can incorporate both dCoREST isoforms. By contrast, the dLSD1/dCoREST complex exclusively assembles with the dCoREST-L isoform. Genome-wide studies show that the three dCoREST complexes associate with chromatin predominantly at promoters. Transcriptome analyses in S2 cells and testes reveal that different cell lineages utilize distinct dCoREST complexes to maintain cell-type-specific gene expression programmes: In macrophage-like S2 cells, LINT represses germ line-related genes whereas other dCoREST complexes are largely dispensable. By contrast, in testes, the dLSD1/dCoREST complex prevents transcription of germ line-inappropriate genes and is essential for spermatogenesis and fertility, whereas depletion of other dCoREST complexes has no effect. Our study uncovers three distinct dCoREST complexes that function in a lineage-restricted fashion to repress specific sets of genes thereby maintaining cell-type-specific gene expression programmes.


Blood ◽  
2011 ◽  
Vol 118 (21) ◽  
pp. 211-211
Author(s):  
Amber Hogart ◽  
Jens Lichtenberg ◽  
Subramanian Ajay ◽  
Elliott Margulies ◽  
David M. Bodine

Abstract Abstract 211 The hematopoietic system is ideal for the study of epigenetic changes in primary cells because hematopoietic cells representing distinct stages of hematopoiesis can be enriched and isolated by differences in surface marker expression. DNA methylation is an essential epigenetic mark that is required for normal development. Conditional knockout of the DNA methyltransferase enzymes in the mouse hematopoietic compartment have revealed that methylation is critical for long-term renewal and lineage differentiation of hematopoietic stem cells (Broske et al 2009, Trowbridge el al 2009). To better understand the role of DNA methylation in self-renewal and differentiation of hematopoietic cells, we characterized genome-wide DNA methylation in primary cells representing three distinct stages of hematopoiesis. We isolated mouse hematopoietic stem cells (HSC; Lin- Sca-1+ c-kit+), common myeloid progenitor cells (CMP; Lin- Sca-1- c-kit+), and erythroblasts (ERY; CD71+ Ter119+). Methyl Binding Domain Protein 2 (MBD2) is an endogenous reader of DNA methylation that recognizes DNA with a high concentration of methylated CpG residues. Recombinant MBD2 enrichment of DNA followed by massively-parallel sequencing was used to map and compare genome-wide DNA methylation patterns in HSC, CMP and ERY. Two biological replicates were sequenced for each cell type with total read counts ranging from 32,309,435–46,763,977. Model-based analysis of ChIP Seq (MACS) with a significance cutoff of p<10−5 was used to determine statistically significant peaks of methylation in each replicate. Globally, the number of methylation peaks was highest in HSC (85,797peaks), lower in CMP (50,638 peaks), and lowest in ERY (27,839 peaks). Comparison of the peaks in HSC, CMP and ERY revealed that only 2% of the peaks in CMP or ERY are absent in HSC indicating that the vast majority of methylation in HSC is lost during differentiation. Comparison of methylation with genomic features revealed that CpG islands associated with promoters are hypomethylated, while many non-promoter CpG islands are methylated. Furthermore, methylation of non-promoter associated CpG islands occurs infrequently in cell-type specific peaks but is more abundant in common methylation peaks. When the DNA methylation patterns were compared to mRNA expression, we found that as expected, proximal promoter sequences of expressed genes were hypomethylated in all three cell types, while methylation in the gene body positively correlated with gene expression in HSC and CMP. Utilizing de novo motif discovery we found a subset of transcription factor consensus binding motifs that were overrepresented in methylated sequences. Motifs for several ETS transcription factors, including GABPalpha and ELF1 were found to be overrepresented in cell-type specific as well as common methylated regions. Other transcription factor consensus sites, such as the NFAT factors involved in T-cell activation, were specifically overrepresented in the methylated promoter regions of CMP and ERY. Comparison of our methylation data with the occupancy of hematopoietic transcription factors in the HPC7 cell line, which is similar to CMP (Wilson et al 2010), revealed a significant anti-correlation between DNA methylation and the binding of Fli1, Lmo2, Lyl1, Runx1, and Scl. Our genome-wide survey provides new insights into the role of DNA methylation in hematopoiesis. Firstly, the methylation of CpG islands is associated with the most primitive hematopoietic cells and is unlikely to drive hematopoietic differentiation. We feel that the elevated genome-wide DNA methylation in HSC compared to CMP and ERY, combined with the positive association between gene body methylation and gene expression demonstrates that DNA methylation is a mark of cellular plasticity in HSC. Finally, the finding that transcription factor binding sites are over represented in the methylated sequences of the genome leads us to conclude that DNA methylation modulates key hematopoietic transcription factor programs that regulate hematopoiesis. Disclosures: No relevant conflicts of interest to declare.


Blood ◽  
2021 ◽  
Vol 138 (Supplement 1) ◽  
pp. 214-214
Author(s):  
Shaobo Li ◽  
Pagna Sok ◽  
Keren Xu ◽  
Ivo S Muskens ◽  
Natalina Elliott ◽  
...  

Abstract Background: Down syndrome (DS) is associated with an up to 30-fold increased risk of B-cell acute lymphoblastic leukemia (ALL), and DS-ALL patients have worse overall survival and increased long-term treatment-related health conditions compared with non-DS ALL patients. In a recent genome-wide association study of DS-ALL, established ALL genetic risk loci were associated with DS-ALL, with several single nucleotide polymorphisms (SNPs) conferring a larger effect on ALL risk in the context of DS than in euploidy. We performed an epigenome-wide association study (EWAS) to elucidate whether epigenetic differences at birth are associated with risk of subsequent DS-ALL. Methods: The DS-ALL Discovery Study included 147 DS-ALL cases and 198 DS controls from the International Study of Down Syndrome Acute Leukemia, with newborn dried bloodspots (DBS) obtained from California (n=326) and Washington state (n=19) biobanks. The DS-ALL Replication Study included 24 DS-ALL cases and 24 DS controls with newborn DBS from the Michigan Neonatal Biobank. DNA was isolated from DBS, bisulfite converted, and assayed using Illumina Infinium MethylationEPIC Beadchip genome-wide DNA methylation arrays. Raw data were processed using "minfi" and "noob" packages in R. Reference-based deconvolution of blood cell proportions was performed using the Identifying Optimal DNA methylation Libraries (IDOL) algorithm, using DNA methylation data from cord blood reference samples, to estimate proportions of B cells, T cells (CD4+ and CD8+), monocytes, granulocytes, natural killer cells, and nucleated red blood cells. We compared each cell type proportion between DS-ALL cases and DS controls using linear regression adjusting for sex, plate, and principal components (PCs) to account for genetic ancestry. To identify single CpG probes associated with DS-ALL risk, we performed a multiethnic EWAS of DS-ALL in each study using linear regression adjusting for sex, plate, and PCs related to: 1) cell-type proportions and 2) genetic ancestry. Differentially methylated regions (DMRs) were identified using DMRcate and comb-p methods. In the Discovery Study, genome-wide SNP array data were available for 131 cases and 130 controls, and data from targeted sequencing of somatic mutations in exons 2/3 of GATA1 were available for 184/198 DS controls. Results: Deconvolution of blood cell proportions in the DS-ALL Discovery Study showed significantly higher B cell proportions in newborns with DS who later developed ALL (mean=0.0128, sd=0.0151) compared with DS controls (mean=0.00826, sd=0.0115) (P=6.4x10 -4, coefficient=0.0052). A significantly higher B cell proportion at birth was also found in DS-ALL cases in the independent Replication Study (cases mean=0.048, sd=0.024; controls mean=0.039, sd=0.028; P=0.03, coefficient=0.015). In the Discovery Study, the B cell difference remained significant (P=5.8x10 -3) with a similar effect size (coefficient=0.0045) after removal of GATA1 mutation-positive DS controls (n=30). We also investigated whether DS-ALL risk SNPs at ARID5B, IKZF1, GATA3, and CDKN2A may confound the association, but the increased B cell proportions in DS-ALL remained significant and effect estimates slightly increased in SNP genotype-adjusted models (coefficient range:0.0055-0.0059). In the EWAS of DS-ALL, 9 CpGs reached epigenome-wide significance (P&lt;7.67x10 -8), including 2 CpGs overlapping the promoter of the tumor suppressor gene TRIM13, frequently deleted in B-CLL, although none of these showed evidence of association (P&lt;0.05) in the Replication Study. We identified 125 DMRs associated with DS-ALL in the Discovery Study. For 3 DMRs, overlapping genes HOPX, SMIM24, and PPP1R10, all implicated in normal and leukemic stem cell function, there were multiple significant CpGs in the Replication Study (P&lt;0.05) all with effects in the same direction as the Discovery Study DMRs. Conclusions: Increased B cell proportions in newborns with DS may be a risk factor for development of DS-ALL in childhood. This finding, based on DNA methylation data, requires confirmation using conventional cell count measures, and should be explored as a novel biomarker for ALL risk in the non-DS population. Single CpGs and DMRs associated with DS-ALL risk in our Discovery Study require further investigation, including in additional ALL case-control studies in DS and non-DS populations. Disclosures Ma: Celgene/Bristol Myers Squibb: Consultancy, Research Funding.


2019 ◽  
Vol 104 (12) ◽  
pp. 6155-6170 ◽  
Author(s):  
Danielle Hiam ◽  
David Simar ◽  
Rhianna Laker ◽  
Ali Altıntaş ◽  
Melanie Gibson-Helm ◽  
...  

Abstract Context Polycystic ovary syndrome (PCOS) is a chronic disease affecting reproductive function and whole-body metabolism. Although the etiology is unclear, emerging evidence indicates that the epigenetics may be a contributing factor. Objective To determine the role of global and genome-wide epigenetic modifications in specific immune cells in PCOS compared with controls and whether these could be related to clinical features of PCOS. Design Cross-sectional study. Participants Women with (n = 17) or without PCOS (n = 17). Setting Recruited from the general community. Main Outcome Measures Isolated peripheral blood mononuclear cells were analyzed using multicolor flow cytometry methods to determine global DNA methylation levels in a cell-specific fashion. Transcriptomic and genome-wide DNA methylation analyses were performed on T helper cells using RNA sequencing and reduced representation bisulfite sequencing. Results Women with PCOS had lower global DNA methylation in monocytes (P = 0.006) and in T helper (P = 0.004), T cytotoxic (P = 0.004), and B cells (P = 0.03). Specific genome-wide DNA methylation analysis of T helper cells from women with PCOS identified 5581 differentially methylated CpG sites. Functional gene ontology enrichment analysis showed that genes located at the proximity of differentially methylated CpG sites belong to pathways related to reproductive function and immune cell function. However, these genes were not altered at the transcriptomic level. Conclusions It was shown that PCOS is associated with global and gene-specific DNA methylation remodeling in a cell type–specific manner. Further investigation is warranted to determine whether epigenetic reprogramming of immune cells is important in determining the different phenotypes of PCOS.


2021 ◽  
Vol 15 ◽  
Author(s):  
Jeffrey Gu ◽  
Julio Barrera ◽  
Young Yun ◽  
Susan K. Murphy ◽  
Thomas G. Beach ◽  
...  

Parkinson’s disease (PD) and dementia with Lewy body (DLB) are the most common synucleinopathies. SNCA gene is a major genetic risk factor for these diseases group, and dysregulation of its expression has been implicated in the genetic etiologies of several synucleinopathies. DNA methylation at CpG island (CGI) within SNCA intron 1 has been suggested as a regulatory mechanism of SNCA expression, and changes in methylation levels at this region were associated with PD and DLB. However, the role of DNA methylation in the regulation of SNCA expression in a cell-type specific manner and its contribution to the pathogenesis of PD and DLB remain poorly understood, and the data are conflicting. Here, we employed a bisulfite pyrosequencing technique to profile the DNA methylation across SNCA intron 1 CGI in PD and DLB compared to age- and sex-matched normal control subjects. We analyzed homogenates of bulk post-mortem frozen frontal cortex samples and a subset of neuronal and glia nuclei sorted by the fluorescence-activated nuclei sorting (FANS) method. Bulk brain tissues showed no significant difference in the overall DNA methylation across SNCA intron 1 CGI region between the neuropathological groups. Sorted neuronal nuclei from PD frontal cortex showed significant lower levels of DNA methylation at this region compared to normal controls, but no differences between DLB and control, while sorted glia nuclei exhibited trends of decreased overall DNA methylation in DLB only. In conclusion, our data suggested disease-dependent cell-type specific differential DNA methylation within SNCA intron 1 CGI. These changes may affect SNCA dysregulation that presumably mediates disease-specific risk. Our results can be translated into the development of the SNCA intron 1 CGI region as an attractive therapeutics target for gene therapy in patients who suffer from synucleinopathies due to SNCA dysregulation.


2020 ◽  
Author(s):  
Marco Schmidt ◽  
Tiago Maié ◽  
Edgar Dahl ◽  
Ivan G. Costa ◽  
Wolfgang Wagner

AbstractBackgroundThe complex composition of different cell types within a tissue can be estimated by deconvolution of omics datasets. For example, DNA methylation (DNAm) profiles have been used to establish an atlas for multiple human tissues and cell types. In this study, we investigated if deconvolution is also feasible with individual cell-type-specific CG dinucleotides (CpG sites), which can be addressed by targeted analysis, such as pyrosequencing.ResultsWe compiled and curated a dataset of 579 samples from Illumina 450k BeadChip technology that comprised 14 different purified and characterized human cell types. A training and validation strategy was applied to identify and test cell-type-specific CpGs. Initially, the amount of fibroblasts was estimated using two CpGs that were either hypermethylated or hypomethylated in fibroblasts. This FibroScore correlated with the state of fibrosis and was associated with overall survival in various types of cancer. Furthermore, we identified hypomethylated CpGs for leukocytes, endothelial cells, epithelial cells, hepatocytes, glia, neurons, fibroblasts and induced pluripotent stem cells. Using previously published BeadChip datasets with cell mixtures the accuracy of this eight CpG signature was comparable to previously published signatures based on several thousand CpGs. Finally, we established and validated pyrosequencing assays for the relevant CpGs that can be utilized for classification and deconvolution of cell types.ConclusionThis proof of concept study demonstrates that DNAm analysis at individual CpGs reflects the cellular composition of cellular mixtures and different tissues. Targeted analysis of these genomic regions facilitates robust methods for application in basic research and clinical settings.


BMC Biology ◽  
2020 ◽  
Vol 18 (1) ◽  
Author(s):  
Marco Schmidt ◽  
Tiago Maié ◽  
Edgar Dahl ◽  
Ivan G. Costa ◽  
Wolfgang Wagner

Abstract Background The complex composition of different cell types within a tissue can be estimated by deconvolution of bulk gene expression profiles or with various single-cell sequencing approaches. Alternatively, DNA methylation (DNAm) profiles have been used to establish an atlas for multiple human tissues and cell types. DNAm is particularly suitable for deconvolution of cell types because each CG dinucleotide (CpG site) has only two states per DNA strand—methylated or non-methylated—and these epigenetic modifications are very consistent during cellular differentiation. So far, deconvolution of DNAm profiles implies complex signatures of many CpGs that are often measured by genome-wide analysis with Illumina BeadChip microarrays. In this study, we investigated if the characterization of cell types in tissue is also feasible with individual cell type-specific CpG sites, which can be addressed by targeted analysis, such as pyrosequencing. Results We compiled and curated 579 Illumina 450k BeadChip DNAm profiles of 14 different non-malignant human cell types. A training and validation strategy was applied to identify and test for cell type-specific CpGs. We initially focused on estimating the relative amount of fibroblasts using two CpGs that were either hypermethylated or hypomethylated in fibroblasts. The combination of these two DNAm levels into a “FibroScore” correlated with the state of fibrosis and was associated with overall survival in various types of cancer. Furthermore, we identified hypomethylated CpGs for leukocytes, endothelial cells, epithelial cells, hepatocytes, glia, neurons, fibroblasts, and induced pluripotent stem cells. The accuracy of this eight CpG signature was tested in additional BeadChip datasets of defined cell mixtures and the results were comparable to previously published signatures based on several thousand CpGs. Finally, we established and validated pyrosequencing assays for the relevant CpGs that can be utilized for classification and deconvolution of cell types. Conclusion This proof of concept study demonstrates that DNAm analysis at individual CpGs reflects the cellular composition of cellular mixtures and different tissues. Targeted analysis of these genomic regions facilitates robust methods for application in basic research and clinical settings.


2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Chenglong You ◽  
Sijie Wu ◽  
Shijie C. Zheng ◽  
Tianyu Zhu ◽  
Han Jing ◽  
...  

Abstract Highly reproducible smoking-associated DNA methylation changes in whole blood have been reported by many Epigenome-Wide-Association Studies (EWAS). These epigenetic alterations could have important implications for understanding and predicting the risk of smoking-related diseases. To this end, it is important to establish if these DNA methylation changes happen in all blood cell subtypes or if they are cell-type specific. Here, we apply a cell-type deconvolution algorithm to identify cell-type specific DNA methylation signals in seven large EWAS. We find that most of the highly reproducible smoking-associated hypomethylation signatures are more prominent in the myeloid lineage. A meta-analysis further identifies a myeloid-specific smoking-associated hypermethylation signature enriched for DNase Hypersensitive Sites in acute myeloid leukemia. These results may guide the design of future smoking EWAS and have important implications for our understanding of how smoking affects immune-cell subtypes and how this may influence the risk of smoking related diseases.


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