Cell-specific DNA Methylation Research Articles

Abstract B033: Identification of cell-specific DNA methylation alterations in the breast tumor microenvironment

Abstract The tumor microenvironment (TME) comprises diverse cell types whose interactions are crucial for cancer progression. Traditional bulk tissue analyses mask cell-type-specific epigenetic changes that may drive disease progression. We used DNA methylation data and a reference- based cell-type deconvolution algorithm — hierarchical tumor immune microenvironment epigenetic deconvolution (HiTIMED) — to quantify cell types in the TME. Then, we employed CellDMC, a statistical interaction testing framework that can use cell type proportions in conjunction with differential methylation analysis to identify cell-specific differential methylation. Genome-scale DNA methylation profiles from breast cancer tissue (n=609) and normal breast tissue (n=230) samples were accessed in GEO and GTEx. Our novel approach leverages bulk DNA methylation data to infer cell-type-specific epigenetic landscapes, circumventing challenges and limitations associated with direct single-cell methylation profiling, such as high costs and technical variability. Reference-based computational tools allow us to dissect complex tissue compositions and reveal distinct methylation patterns and pathways that may be unique to individual cell types, providing insights that are not discernible from traditional bulk tumor analysis approaches. Compared with nontumor normal samples, we identified significant DNA methylation alterations (FDR≤0.05) across tumor, stromal, endothelial, epithelial, lymphocytes, and myeloid cells in breast tumors. Tumor cells exhibited the highest number, 8,510, differentially methylated cytosines (DMCs) with 1,966 of these unique to tumor cells. Stromal, endothelial, and epithelial cells also showed considerable methylation alterations, with a total of 530, 440, 339 DMCs, respectively, with 5 DMCs unique to epithelial cells. Despite lower immune cell proportions in our samples, we identified 104 lymphocyte specific DMCs and 185 myeloid specific DMCs, with 14 and 20 DMCs unique to these cell types respectively. The unique DMCs identified in each cell type suggest distinct epigenetic landscapes that may drive specific cellular functions and interactions within the TME. Importantly, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of the annotated cell-type-specific DMCs revealed distinct pathways that were not apparent in the pathway analysis of bulk tumor versus normal tissue, underscoring the value of examining epigenetic alterations at the cell-type level. Our findings highlight the opportunity to leverage DNA-based cell typing with DNA methylation data to discern cell-specific molecular alterations. By focusing on cell-type-specific alterations, we can better understand the epigenetic mechanisms driving TME crosstalk, such as the activation of stromal cells and the modulation of immune responses by tumor cells. Our findings underscore the need for targeted therapeutic strategies that consider the unique epigenetic landscapes of individual cell types within the TME, offering new avenues for improving cancer treatment outcomes. Citation Format: Barbara Karakyriakou, Brock C. Christensen, Lucas A. Salas. Identification of cell-specific DNA methylation alterations in the breast tumor microenvironment [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Tumor-body Interactions: The Roles of Micro- and Macroenvironment in Cancer; 2024 Nov 17-20; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(22_Suppl):Abstract nr B033.

Identification of cell-specific epigenetic patterns associated with chondroitin sulfate treatment response in an endemic arthritis, Kashin-Beck disease.

To assess the alterations in cell-specific DNA methylation associated with chondroitin sulphate response using peripheral blood collected from Kashin-Beck disease (KBD) patients before initiation of chondroitin sulphate treatment. Peripheral blood samples were collected from KBD patients at baseline of chondroitin sulphate treatment. Methylation profiles were generated using reduced representation bisulphite sequencing (RRBS) from peripheral blood. Differentially methylated regions (DMRs) were identified using MethylKit, while DMR-related genes were defined as those annotated to the gene body or 2.2-kilobase upstream regions of DMRs. Selected DMR-related genes were further validated by quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) to assess expression levels. Tensor composition analysis was performed to identify cell-specific differential DNA methylation from bulk tissue. This study revealed 21,060 hypermethylated and 44,472 hypomethylated DMRs, and 13,194 hypermethylated and 22,448 hypomethylated CpG islands for differential global methylation for chondroitin sulphate treatment response. A total of 12,666 DMR-related genes containing DMRs were identified in their promoter regions, such as CHL1 (false discovery rate (FDR) = 2.11 × 10-11), RIC8A (FDR = 7.05 × 10-4), and SOX12 (FDR = 1.43 × 10-3). Additionally, RIC8A and CHL1 were hypermethylated in responders, while SOX12 was hypomethylated in responders, all showing decreased gene expression. The patterns of cell-specific differential global methylation associated with chondroitin sulphate response were observed. Specifically, we found that DMRs located in TESPA1 and ATP11A exhibited differential DNA methylation between responders and non-responders in granulocytes, monocytes, and B cells. Our study identified cell-specific changes in DNA methylation associated with chondroitin sulphate response in KBD patients.

Abstract A007: DNA methylation analysis comparing high-grade serous ovarian cancer to the normal ovary with adjustment for cell type variation identifies tumor-specific methylation alterations

Abstract A007: DNA methylation analysis comparing high-grade serous ovarian cancer to the normal ovary with adjustment for cell type variation identifies tumor-specific methylation alterations

Cell-free DNA methylation reveals cell-specific tissue injury and correlates with disease severity and patient outcomes in COVID-19

BackgroundThe recently identified methylation patterns specific to cell type allows the tracing of cell death dynamics at the cellular level in health and diseases. This study used COVID-19 as a disease model to investigate the efficacy of cell-specific cell-free DNA (cfDNA) methylation markers in reflecting or predicting disease severity or outcome.MethodsWhole genome methylation sequencing of cfDNA was performed for 20 healthy individuals, 20 cases with non-hospitalized COVID-19 and 12 cases with severe COVID-19 admitted to intensive care unit (ICU). Differentially methylated regions (DMRs) and gene ontology pathway enrichment analyses were performed to explore the locus-specific methylation difference between cohorts. The proportion of cfDNA derived from lung and immune cells to a given sample (i.e. tissue fraction) at cell-type resolution was estimated using a novel algorithm, which reflects lung injuries and immune response in COVID-19 patients and was further used to evaluate clinical severity and patient outcome.ResultsCOVID‑19 patients had globally reduced cfDNA methylation level compared with healthy controls. Compared with non-hospitalized COVID-19 patients, the cfDNA methylation pattern was significantly altered in severe patients with the identification of 11,156 DMRs, which were mainly enriched in pathways related to immune response. Markedly elevated levels of cfDNA derived from lung and more specifically alveolar epithelial cells, bronchial epithelial cells, and lung endothelial cells were observed in COVID-19 patients compared with healthy controls. Compared with non-hospitalized patients or healthy controls, severe COVID-19 had significantly higher cfDNA derived from B cells, T cells and granulocytes and lower cfDNA from natural killer cells. Moreover, cfDNA derived from alveolar epithelial cells had the optimal performance to differentiate COVID-19 with different severities, lung injury levels, SOFA scores and in-hospital deaths, with the area under the receiver operating characteristic curve of 0.958, 0.941, 0.919 and 0.955, respectively.ConclusionSevere COVID-19 has a distinct cfDNA methylation signature compared with non-hospitalized COVID-19 and healthy controls. Cell type-specific cfDNA methylation signature enables the tracing of COVID-19 related cell deaths in lung and immune cells at cell-type resolution, which is correlated with clinical severities and outcomes, and has extensive application prospects to evaluate tissue injuries in diseases with multi-organ dysfunction.

Evaluation of Cell-Specific Epigenetic Age Acceleration in People With Multiple Sclerosis.

In multiple sclerosis (MS), accelerated aging of the immune system (immunosenescence) may be associated with disease onset or drive progression. DNA methylation (DNAm) is an epigenetic factor that varies among lymphocyte subtypes, and cell-specific DNAm is associated with MS. DNAm varies across the life span and can be used to accurately estimate biological age acceleration, which has been linked to a range of morbidities. The objective of this study was to test for cell-specific epigenetic age acceleration (EAA) in people with MS. This was a case-control study of EAA using existing DNAm data from several independent previously published studies. Data were included if .idat files from Illumina 450K or EPIC arrays were available for both a case with MS and an age-matched and sex-matched control, from the same study. Multifactor statistical modeling was performed to assess the primary outcome of EAA. We explored the relationship of EAA and MS, including interaction terms to identify immune cell-specific effects. Cell-sorted DNA methylation data from 3 independent datasets were used to validate findings. We used whole blood DNA methylation data from 583 cases with MS and 643 non-MS controls to calculate EAA using the GrimAge algorithm. The MS group exhibited an increased EAA compared with controls (approximately 9 mths, 95% CI 3.6-14.4), p = 0.001). Statistical deconvolution showed that EAA is associated with MS in a B cell-dependent manner (β int = 1.7, 95% CI 0.3-2.8), p = 0.002), irrespective of B-cell proportions. Validation analysis using 3 independent datasets enriched for B cells showed an EAA increase of 5.1 years in cases with MS compared with that in controls (95% CI 2.8-7.4, p = 5.5 × 10-5). By comparison, there was no EAA difference in MS in a T cell-enriched dataset. We found that EAA was attributed to the DNAm surrogates for Beta-2-microglobulin (difference = 47,546, 95% CI 10,067-85,026; p = 7.2 × 10-5), and smoking pack-years (difference = 8.1, 95% CI 1.9-14.2, p = 0.002). This study provides compelling evidence that B cells exhibit marked EAA in MS and supports the hypothesis that premature B-cell immune senescence plays a role in MS. Future MS studies should focus on age-related molecular mechanisms in B cells.

Interferon beta treatment is a potent and targeted epigenetic modifier in multiple sclerosis.

Multiple Sclerosis (MS) has a complex pathophysiology that involves genetic and environmental factors. DNA methylation (DNAm) is one epigenetic mechanism that can reversibly modulate gene expression. Cell specific DNAm changes have been associated with MS, and some MS therapies such as dimethyl fumarate can influence DNAm. Interferon Beta (IFNβ), was one of the first disease modifying therapies in multiple sclerosis (MS). However, how IFNβ reduces disease burden in MS is not fully understood and little is known about the precise effect of IFNβ treatment on methylation. The objective of this study was to determine the changes in DNAm associated with INFβ use, using methylation arrays and statistical deconvolutions on two separate datasets (total ntreated = 64, nuntreated = 285). We show that IFNβ treatment in people with MS modifies the methylation profile of interferon response genes in a strong, targeted, and reproducible manner. Using these identified methylation differences, we constructed a methylation treatment score (MTS) that is an accurate discriminator between untreated and treated patients (Area under the curve = 0.83). This MTS is time-sensitive and in consistent with previously identified IFNβ treatment therapeutic lag. This suggests that methylation changes are required for treatment efficacy. Overrepresentation analysis found that IFNβ treatment recruits the endogenous anti-viral molecular machinery. Finally, statistical deconvolution revealed that dendritic cells and regulatory CD4+ T cells were most affected by IFNβ induced methylation changes. In conclusion, our study shows that IFNβ treatment is a potent and targeted epigenetic modifier in multiple sclerosis.

Identification of Cell-Specific Differential DNA Methylation Associated With Methotrexate Treatment Response in Rheumatoid Arthritis.

We undertook this study to estimate changes in cell-specific DNA methylation (DNAm) associated with methotrexate (MTX) response using whole blood samples collected from rheumatoid arthritis (RA) patients before and after initiation of MTX treatment. Patients included in this study were from the Rheumatoid Arthritis Medication Study (n=66) and the University of California San Francisco Rheumatoid Arthritis study (n=11). All patients met the American College of Rheumatology RA classification criteria. Blood samples were collected at baseline and following treatment. Disease Activity Scores in 28 joints using the C-reactive protein level were collected at baseline and after 3-6 months of treatment with MTX. Methylation profiles were generated using the Illumina Infinium HumanMethylation450 and MethylationEPIC v1.0 BeadChip arrays using DNA from whole blood. MTX response was defined using the EULAR response criteria (responders showed good/moderate response; nonresponders showed no response). Differentially methylated positions were identified using the Limma software package and Tensor Composition Analysis, which is a method for identifying cell-specific differential DNAm at the CpG level from tissue-level ("bulk") data. Differentially methylated regions were identified using Comb-p software. We found evidence of differential global methylation between treatment response groups. Further, we found patterns of cell-specific differential global methylation associated with MTX response. After correction for multiple testing, 1 differentially methylated position was associated with differential DNAm between responders and nonresponders at baseline in CD4+ T cells, CD8+ T cells, and natural killer cells. Thirty-nine cell-specific differentially methylated regions associated with MTX treatment response were identified. There were no significant findings in analyses of whole blood samples. We identified cell-specific changes in DNAm that were associated with MTX treatment response in RA patients. Future studies of DNAm and MTX treatment response should include measurements of DNAm from sorted cells.

Assessment of immune cell profiles among post-menopausal women in the Women’s Health Initiative using DNA methylation-based methods

BackgroundOver the past decade, DNA methylation (DNAm)-based deconvolution methods that leverage cell-specific DNAm markers of immune cell types have been developed to provide accurate estimates of the proportions of leukocytes in peripheral blood. Immune cell phenotyping using DNAm markers, termed immunomethylomics or methylation cytometry, offers a solution for determining the body’s immune cell landscape that does not require fresh blood and is scalable to large sample sizes. Despite significant advances in DNAm-based deconvolution, references at the population level are needed for clinical and research interpretation of these additional immune layers. Here we aim to provide some references for immune populations in a group of multi-ethnic post-menopausal American women.ResultsWe applied DNAm-based deconvolution to a large sample of post-menopausal women enrolled in the Women’s Health Initiative (baseline, N = 58) or the ancillary Long Life Study (WHI-LLS, N = 1237) to determine the reference ranges of 58 immune parameters, including proportions and absolute counts for 19 leukocyte subsets and 20 derived cell ratios. Participants were 50–94 years old at the time of blood draw, and N = 898 (69.3%) self-identified as White. Using linear regression models, we observed significant associations between age at blood draw and absolute counts and proportions of naïve B, memory CD4+, naïve CD4+, naïve CD8+, memory CD8+ memory, neutrophils, and natural killer cells. We also assessed the same immune profiles in a subset of paired longitudinal samples collected 14–18 years apart across N = 52 participants. Our results demonstrate high inter-individual variability in rates of change of leukocyte subsets over this time. And, when conducting paired t tests to test the difference in counts and proportions between the baseline visit and LLS visit, there were significant changes in naïve B, memory CD4+, naïve CD4+, naïve CD8+, memory CD8+ cells and neutrophils, similar to the results seen when analyzing the association with age in the entire cohort.ConclusionsHere, we show that derived cell counts largely reflect the immune profile associated with proportions and that these novel methods replicate the known immune profiles associated with age. Further, we demonstrate the value this methylation cytometry approach can add as a potential application in epidemiological studies.

Longitudinal DNA methylation profiling of the rectal mucosa identifies cell-specific signatures of disease status, severity and clinical outcomes in ulcerative colitis cell-specific DNA methylation signatures of UC

BackgroundIn peripheral blood, DNA methylation (DNAm) patterns in inflammatory bowel disease patients reflect inflammatory status rather than disease status. Here, we examined DNAm in diseased rectal mucosa from ulcerative colitis (UC) patients, focusing on constituent cell types with the goal of identifying therapeutic targets for UC other than the immune system. We profiled DNAm of rectal mucosal biopsies of pediatric UC at diagnosis (n = 211) and non-IBD control (n = 85) patients and performed epigenome-wide association studies (EWAS) of specific cell types to understand DNAm changes in epithelial, immune and fibroblast cells across disease states, course, and clinical outcomes. We also examined longitudinal analysis on follow-up samples (n = 73), and comparisons were made among patients with clinical outcomes including those undergoing colectomy versus those who did not. Additionally, we included RNA-seq from the same subjects to assess the impact of CpG sites on the transcription of nearby genes during the disease course.ResultsAt diagnosis, UC rectal mucosa exhibited a lower proportion of epithelial cells and fibroblasts, and higher proportion of immune cells, in conjunction with variation in the DNAm pattern. While treatment had significant effects on the methylation signature of immune cells, its effects on fibroblasts and epithelial cells were attenuated. Individuals who required colectomy exhibited cell composition and DNAm patterns at follow-up more similar to disease onset than patients who did not require colectomy. Combining these results with gene expression profiles, we identify CpG sites whose methylation patterns are most consistent with a contribution to poor disease outcomes and could thus be potential therapeutic targets.ConclusionsCell-specific epigenetic changes in the rectal mucosa in UC are associated with disease severity and outcome. Current therapeutics may more effectively target the immune than the epithelial and fibroblast compartments.Graphical abstract

Parity is associated with long-term differences in DNA methylation at genes related to neural plasticity in multiple sclerosis

BackgroundPregnancy in women with multiple sclerosis (wwMS) is associated with a reduction of long-term disability progression. The mechanism that drives this effect is unknown, but converging evidence suggests a role for epigenetic mechanisms altering immune and/or central nervous system function. In this study, we aimed to identify whole blood and immune cell-specific DNA methylation patterns associated with parity in relapse-onset MS.ResultsWe investigated the association between whole blood and immune cell-type-specific genome-wide methylation patterns and parity in 192 women with relapse-onset MS, matched for age and disease severity. The median time from last pregnancy to blood collection was 16.7 years (range = 1.5–44.4 years). We identified 2965 differentially methylated positions in whole blood, 68.5% of which were hypermethylated in parous women; together with two differentially methylated regions on Chromosomes 17 and 19 which mapped to TMC8 and ZNF577, respectively. Our findings validated 22 DMPs and 366 differentially methylated genes from existing literature on epigenetic changes associated with parity in wwMS. Differentially methylated genes in whole blood were enriched in neuronal structure and growth-related pathways. Immune cell-type-specific analysis using cell-type proportion estimates from statistical deconvolution of whole blood revealed further differential methylation in T cells specifically (four in CD4+ and eight in CD8+ T cells). We further identified reduced methylation age acceleration in parous women, demonstrating slower biological aging compared to nulligravida women.ConclusionDifferential methylation at genes related to neural plasticity offers a potential molecular mechanism driving the long-term effect of pregnancy on MS outcomes. Our results point to a potential ‘CNS signature’ of methylation in peripheral immune cells, as previously described in relation to MS progression, induced by parity. As the first epigenome-wide association study of parity in wwMS reported, validation studies are needed to confirm our findings.

A Novel Framework for the Identification of Reference DNA Methylation Libraries for Reference-Based Deconvolution of Cellular Mixtures.

Reference-based deconvolution methods use reference libraries of cell-specific DNA methylation (DNAm) measurements as a means toward deconvoluting cell proportions in heterogeneous biospecimens (e.g., whole-blood). As the accuracy of such methods depends highly on the CpG loci comprising the reference library, recent research efforts have focused on the selection of libraries to optimize deconvolution accuracy. While existing approaches for library selection work extremely well, the best performing approaches require a training data set consisting of both DNAm profiles over a heterogeneous cell population and gold-standard measurements of cell composition (e.g., flow cytometry) in the same samples. Here, we present a framework for reference library selection without a training dataset (RESET) and benchmark it against the Legacy method (minfi:pickCompProbes), where libraries are constructed based on a pre-specified number of cell-specific differentially methylated loci (DML). RESET uses a modified version of the Dispersion Separability Criteria (DSC) for comparing different libraries and has four main steps: 1) identify a candidate set of cell-specific DMLs, 2) randomly sample DMLs from the candidate set, 3) compute the Modified DSC of the selected DMLs, and 4) update the selection probabilities of DMLs based on their contribution to the Modified DSC. Steps 2–4 are repeated many times and the library with the largest Modified DSC is selected for subsequent reference-based deconvolution. We evaluated RESET using several publicly available datasets consisting of whole-blood DNAm measurements with corresponding measurements of cell composition. We computed the RMSE and R 2 between the predicted cell proportions and their measured values. RESET outperformed the Legacy approach in selecting libraries that improve the accuracy of deconvolution estimates. Additionally, reference libraries constructed using RESET resulted in cellular composition estimates that explained more variation in DNAm as compared to the Legacy approach when evaluated in the context of epigenome-wide association studies (EWAS) of several publicly available data sets. This finding has implications for the statistical power of EWAS. RESET combats potential challenges associated with existing approaches for reference library assembly and thus, may serve as a viable strategy for library construction in the absence of a training data set.

DNA Methylation Patterning and the Regulation of Beta Cell Homeostasis.

Pancreatic beta cells play a central role in regulating glucose homeostasis by secreting the hormone insulin. Failure of beta cells due to reduced function and mass and the resulting insulin insufficiency can drive the dysregulation of glycemic control, causing diabetes. Epigenetic regulation by DNA methylation is central to shaping the gene expression patterns that define the fully functional beta cell phenotype and regulate beta cell growth. Establishment of stage-specific DNA methylation guides beta cell differentiation during fetal development, while faithful restoration of these signatures during DNA replication ensures the maintenance of beta cell identity and function in postnatal life. Lineage-specific transcription factor networks interact with methylated DNA at specific genomic regions to enhance the regulatory specificity and ensure the stability of gene expression patterns. Recent genome-wide DNA methylation profiling studies comparing islets from diabetic and non-diabetic human subjects demonstrate the perturbation of beta cell DNA methylation patterns, corresponding to the dysregulation of gene expression associated with mature beta cell state in diabetes. This article will discuss the molecular underpinnings of shaping the islet DNA methylation landscape, its mechanistic role in the specification and maintenance of the functional beta cell phenotype, and its dysregulation in diabetes. We will also review recent advances in utilizing beta cell specific DNA methylation patterns for the development of biomarkers for diabetes, and targeting DNA methylation to develop translational approaches for supplementing the functional beta cell mass deficit in diabetes.

RETRACTED ARTICLE: Aging-associated distinctive DNA methylation changes of LINE-1 retrotransposons in pure cell-free DNA from human blood

LINE-1 hypomethylation of cell-free DNA has been described as an epigenetic biomarker of human aging. However, in the past, insufficient differentiation between cellular and cell-free DNA may have confounded analyses of genome-wide methylation levels in aging cells. Here we present a new methodological strategy to properly and unambiguously extract DNA methylation patterns of repetitive, as well as single genetic loci from pure cell-free DNA from peripheral blood. Since this nucleic acid fraction originates mainly in apoptotic, senescent and cancerous cells, this approach allows efficient analysis of aged and cancerous cell-specific DNA methylation patterns for diagnostic and prognostic purposes. Using this methodology, we observe a significant age-associated erosion of LINE-1 methylation in cfDNA suggesting that the threshold of hypomethylation sufficient for relevant LINE-1 activation and consequential harmful retrotransposition might be reached at higher age. We speculate that this process might contribute to making aging the main risk factor for many cancers.

EPID-08. PRE-SURGERY IMMUNE PROFILES OF ADULT GLIOMA PATIENTS

Abstract Changes in glioma patients’ immune profiles over the course of disease may predict outcomes. DNA based immunomethylomics quantifies blood immune cells based on cell specific DNA methylation signatures. To assess changes in immune profiles, we are longitudinally collecting blood samples from glioma patients pre-surgery and at other clinically relevant time points. Here we report patients’ pre-surgery immune profiles. All patients underwent biopsy or resection of a presumed new glioma or recurrent lower grade glioma. Blood DNA methylation was assessed with Illumina EPIC methylation arrays. Relative cell fractions of CD4, CD8, B-cells, natural killer cells, monocytes, and neutrophils, were estimated via our validated deconvolution algorithm. Total nucleated cell counts from Nexcelom cytometry were used to compute absolute cell counts. Other measures include total lymphocytes, CD4/CD8 ratio, neutrophil to lymphocyte ratio (NLR), and lymphocyte to monocyte ratio (LMR)). The first 125 participants includes 56 newly diagnosed glioblastomas (GBM), 28 newly diagnosed grade II-III gliomas, and 41 recurrent grade II-III gliomas. Median patient age is 49 years. 53 (43%) had recent dexamethasone exposure. In overall non-parametric analyses, most cell subsets, especially CD4, differed across grade, diagnosis group, WHO classification and dexamethasone exposure. In post-hoc pairwise analyses, immune profiles of IDH wildtype GBM patients who had taken dexamethasone differed from patients with GBM or grade II-III glioma who had not taken dexamethasone; they had clinically relevant and statistically significantly lower absolute CD4 counts, total white cell counts, and percent of total lymphocytes, and higher absolute neutrophil counts, NLR and LMR. However, some dexamethasone naïve GBM patients also had altered immune profiles. Comparisons of relative immune cell fractions with those from 454 non-glioma controls from the UCSF Adult Glioma Study showed that across grade and WHO classification, for the most part, immune profiles of glioma patients not exposed to dexamethasone did not differ from controls.

Methylation pattern of urinary DNA as a marker of kidney function decline in diabetes

IntroductionRenal tubular injury contributes to the decline in kidney function in patients with diabetes. Cell type-specific DNA methylation patterns have been used to calculate proportions of particular cell types. In...

Multiplexing DNA methylation markers to detect circulating cell-free DNA derived from human pancreatic β cells.

It has been proposed that unmethylated insulin promoter fragments in plasma derive exclusively from β cells, reflect their recent demise, and can be used to assess β cell damage in type 1 diabetes. Herein we describe an ultrasensitive assay for detection of a β cell-specific DNA methylation signature, by simultaneous assessment of 6 DNA methylation markers, that identifies β cell DNA in mixtures containing as little as 0.03% β cell DNA (less than 1 β cell genome equivalent). Based on this assay, plasma from nondiabetic individuals (N = 218, aged 4-78 years) contained on average only 1 β cell genome equivalent/mL. As expected, cell-free DNA (cfDNA) from β cells was significantly elevated in islet transplant recipients shortly after transplantation. We also detected β cell cfDNA in a patient with KATP congenital hyperinsulinism, in which substantial β cell turnover is thought to occur. Strikingly, in contrast to previous reports, we observed no elevation of β cell-derived cfDNA in autoantibody-positive subjects at risk for type 1 diabetes (N = 32), individuals with recent-onset type 1 diabetes (<4 months, N = 92), or those with long-standing disease (>4 months, N = 38). We discuss the utility of sensitive β cell cfDNA analysis and potential explanations for the lack of a β cell cfDNA signal in type 1 diabetes.

The sperm epigenome does not display recurrent epimutations in patients with severely impaired spermatogenesis

BackgroundIn the past 15 years, numerous studies have described aberrant DNA methylation of imprinted genes (e.g. MEST and H19) in sperm of oligozoospermic men, but the prevalence and genomic extent of abnormal methylation patterns have remained unknown.ResultsUsing deep bisulfite sequencing (DBS), we screened swim-up sperm samples from 40 normozoospermic and 93 patients diagnosed as oligoasthenoteratozoospermic, oligoteratozoospermic or oligozoospermic, which are termed OATs throughout the manuscript, for H19 and MEST methylation. Based on this screening, we defined three patient groups: normal controls (NC), abnormally methylated oligozoospermic (AMO; n = 7) and normally methylated oligozoospermic (NMO; n = 86). Whole-genome bisulfite sequencing (WGBS) of five NC and five AMO samples revealed abnormal methylation levels of all 50 imprinting control regions in each AMO sample. To investigate whether this finding reflected epigenetic germline mosaicism or the presence of residual somatic DNA, we made a genome-wide inventory of soma-germ cell-specific DNA methylation. We found that > 2000 germ cell-specific genes are promoter-methylated in blood and that AMO samples had abnormal methylation levels at these genes, consistent with the presence of somatic cell DNA. The comparison between the five NC and six NMO samples revealed 19 differentially methylated regions (DMRs), none of which could be validated in an independent cohort of 40 men. Previous studies reported a higher incidence of epimutations at single CpG sites in the CTCF-binding region 6 of H19 in infertile patients. DBS analysis of this locus, however, revealed an association between DNA methylation levels and genotype (rs2071094), but not fertility phenotype.ConclusionsOur results suggest that somatic DNA contamination and genetic variation confound methylation studies in sperm of infertile men. While we cannot exclude the existence of rare patients with slightly abnormal sperm methylation at non-recurrent CpG sites, the prevalence of aberrant methylation in swim-up purified sperm of infertile men has likely been overestimated, which is reassuring for patients undergoing assisted reproduction.

Cell-Specific DNA Methylation Signatures in Asthma.

Asthma is a complex trait, often associated with atopy. The genetic contribution has been evidenced by familial occurrence. Genome-wide association studies allowed for associating numerous genes with asthma, as well as identifying new loci that have a minor contribution to its phenotype. Considering the role of environmental exposure on asthma development, an increasing amount of literature has been published on epigenetic modifications associated with this pathology and especially on DNA methylation, in an attempt to better understand its missing heritability. These studies have been conducted in different tissues, but mainly in blood or its peripheral mononuclear cells. However, there is growing evidence that epigenetic changes that occur in one cell type cannot be directly translated into another one. In this review, we compare alterations in DNA methylation from different cells of the immune system and of the respiratory tract. The cell types in which data are obtained influences the global status of alteration of DNA methylation in asthmatic individuals compared to control (an increased or a decreased DNA methylation). Given that several genes were cell-type-specific, there is a great need for comparative studies on DNA methylation from different cells, but from the same individuals in order to better understand the role of epigenetics in asthma pathophysiology.

Systematic evaluation and validation of reference and library selection methods for deconvolution of cord blood DNA methylation data

BackgroundUmbilical cord blood (UCB) is commonly used in epigenome-wide association studies of prenatal exposures. Accounting for cell type composition is critical in such studies as it reduces confounding due to the cell specificity of DNA methylation (DNAm). In the absence of cell sorting information, statistical methods can be applied to deconvolve heterogeneous cell mixtures. Among these methods, reference-based approaches leverage age-appropriate cell-specific DNAm profiles to estimate cellular composition. In UCB, four reference datasets comprising DNAm signatures profiled in purified cell populations have been published using the Illumina 450 K and EPIC arrays. These datasets are biologically and technically different, and currently, there is no consensus on how to best apply them. Here, we systematically evaluate and compare these datasets and provide recommendations for reference-based UCB deconvolution.ResultsWe first evaluated the four reference datasets to ascertain both the purity of the samples and the potential cell cross-contamination. We filtered samples and combined datasets to obtain a joint UCB reference. We selected deconvolution libraries using two different approaches: automatic selection using the top differentially methylated probes from the function pickCompProbes in minfi and a standardized library selected using the IDOL (Identifying Optimal Libraries) iterative algorithm. We compared the performance of each reference separately and in combination, using the two approaches for reference library selection, and validated the results in an independent cohort (Generation R Study, n = 191) with matched Fluorescence-Activated Cell Sorting measured cell counts. Strict filtering and combination of the references significantly improved the accuracy and efficiency of cell type estimates. Ultimately, the IDOL library outperformed the library from the automatic selection method implemented in pickCompProbes.ConclusionThese results have important implications for epigenetic studies in UCB as implementing this method will optimally reduce confounding due to cellular heterogeneity. This work provides guidelines for future reference-based UCB deconvolution and establishes a framework for combining reference datasets in other tissues.

Epigenetic mediated immune exhaustion persists after successful Tuberculosis therapy

Abstract BACKGROUND Chronic antigen stimulation from HIV, HPV, LCMV and schistosomiasis induce epigenetic-mediated immune exhaustion. Individuals with successful anti-TB therapy (ATT) have a thirteen-fold increased risk of developing recurrent TB. METHODS From a cohort of HIV infected and uninfected individuals with TB and their asymptomatic household contacts (n=32), genome-wide DNA methylation (DNA MethylEPIC) and epigenetic deconvolution (EDEC) identified cell-specific DNA methylation. Cell-specific results were validated with MSRE-PCR, gene expression and flow cytometry-based Mtb-specific multi-dimensional immune profiling. RESULTS Participants with TB had DNA hypermethylation in the IL-2, TCR and IFN-γ signalling pathways. The IFN-γ signalling pathway was affected in both innate (NK cells and monocytes) as well as adaptive (CD4 and CD8 T cells) lineages. Select DNA hyper-methylated differences were validated using MSRE-PCR. Pioneer and Transcription factors critical for cell-mediated immunity were also significantly differentially methylated with enrichment scores compatible with previous epigenetic-mediated immune exhaustion. After overnight stimulation with IFN-γ, TB patients have decreased IFN-γ-inducible gene expression. Six months after the completion of successful ATT, participants with TB have persistent DNA hypermethylation. DISCUSSION Persistent DNA hypermethylation may be a potential mechanism by which individuals with TB are at increased risk of recurrent disease. This may also assist in identifying potential new targets for host-directed therapy.