DNA Methylation in Whole Blood: Uses and Challenges

Association of Neighborhood Deprivation With Epigenetic Aging Using 4 Clock Metrics

IMPORTANCE

Neighborhood deprivation is associated with age-related disease, mortality, and reduced life expectancy. However, biological pathways underlying these associations are not well understood.

OBJECTIVE

To evaluate the association between neighborhood deprivation and epigenetic measures of age acceleration and genome-wide methylation.

DESIGN, SETTING, AND PARTICIPANTS

This cross-sectional study used data from the Sister Study, a prospective cohort study comprising 50 884 women living in the US and Puerto Rico aged 35 to 74 years at enrollment who had a sister with breast cancer but had not had breast cancer themselves. Cohort enrollment occurred between July 2003 and March 2009. Participants completed a computer-assisted telephone interview on demographic, socioeconomic, lifestyle, and residential factors and provided anthropometric measures and peripheral blood samples at a home examination. DNA methylation data obtained for 2630 non-Hispanic White women selected for a case-cohort study in 2014 were used in this cross-sectional analysis. DNA methylation was measured using the HumanMethylation450 BeadChips in whole blood samples collected at baseline. Data analysis for this study was performed from October 17, 2019, to August 27, 2020.

EXPOSURES

Each participants' primary address was linked to an established index of neighborhood deprivation.

MAIN OUTCOMES AND MEASURES

Epigenetic age was estimated using 4 epigenetic clocks (Horvath, Hannum, PhenoAge, and GrimAge). Age acceleration was determined using residuals from regressing chronologic age on each of the 4 epigenetic age metrics. Linear regression was used to estimate associations between neighborhood deprivation and epigenetic age acceleration as well as DNA methylation at individual cytosine-guanine sites across the genome.

RESULTS

Mean (SD) age of the 2630 participants was 56.9 (8.7) years. Those with the greatest (>75th percentile) vs least (≤25th percentile) neighborhood deprivation had higher epigenetic age acceleration estimated by Hannum (β = 0.23; 95% CI, 0.01-0.45), PhenoAge (β = 0.28; 95% CI, 0.06-.50), and GrimAge (β = 0.37; 95% CI, 0.12-0.62). Increasing US quartiles of neighborhood deprivation exhibited a trend with Hannum, PhenoAge, and GrimAge. For example, GrimAge showed a significant dose-response (P test for trend <.001) as follows: level 2 vs level 1 (β = 0.30; 95% CI, 0.17-0.42), level 3 vs level 1 (β = 0.35; 95% CI, 0.19-0.50), and level 4 vs level 1 (β = 0.37; 95% CI, 0.12-0.62). Neighborhood deprivation was found to be associated with 3 cytosine-phosphate-guanine sites, with 1 of these annotated to a known gene MAOB (P = 9.71 × 10-08).

CONCLUSIONS AND RELEVANCE

The findings of this study suggest that residing in a neighborhood with a higher deprivation index appears to be reflected by methylation-based markers of aging.

DNA methylation biomarkers of future health outcomes in children

Biomarkers which predict future health outcomes are key to the goals of precision health. Such biomarkers do not have to be involved in the causal pathway of a disease, and their performance is best assessed using statistical tests of clinical performance and evaluation of net health impact. DNA methylation is the most commonly studied epigenetic process and represents a potential biomarker of future health outcomes. We review 25 studies in non-oncological paediatric conditions where DNA methylation biomarkers of future health outcomes are assessed. Whilst a number of positive findings have been described, the body of evidence is severely limited by issues with outcome measures, tissue-specific samples, accounting for sample cell type heterogeneity, lack of appropriate statistical testing, small effect sizes, limited validation, and no assessment of net health impact. Future studies should concentrate on careful study design to overcome these issues, and integration of DNA methylation data with other 'omic', clinical, and environmental data to generate the most clinically useful biomarkers of paediatric disease.

Reliability and correlation of mixture cell correction in methylomic and transcriptomic blood data

Objectives

The number of DNA methylome and RNA transcriptome studies is growing, but investigators have to consider the cell type composition of tissues used. In blood samples, the data reflect the picture of a mixture of different cells. Specialized algorithms can address the cell-type heterogeneity issue. We tested if these corrections are correlated between two heterogeneous datasets.

Results

We used methylome and transcriptome datasets derived from a cohort of ten individuals whose blood was sampled at two different timepoints. We examined how the cell composition derived from these omics correlated with each other using “CIBERSORT” for the transcriptome and “estimateCellCounts function” in R for the methylome. The correlation coefficients between the two omic datasets ranged from 0.45 to 0.81 but correlations were minimal between two different timepoints. Our results suggest that a posteriori correction of a mixture of cells present in blood samples is reliable. Using an omic dataset to correct a second dataset for relative fractions of cells appears to be applicable, but only when the samples are simultaneously collected. This could be beneficial when there are difficulties to control the cell types in the second dataset, even when the sample size is limited.

A Tissue Comparison of DNA Methylation of the Glucocorticoid Receptor Gene (Nr3c1) in European Starlings

Negative feedback of the vertebrate stress response via the hypothalamic-pituitary-adrenal (HPA) axis is regulated by glucocorticoid receptors in the brain. Epigenetic modification of the glucocorticoid receptor gene (Nr3c1), including DNA methylation of the promoter region, can influence expression of these receptors, impacting behavior, physiology, and fitness. However, we still know little about the long-term effects of these modifications on fitness. To better understand these fitness effects, we must first develop a non-lethal method to assess DNA methylation in the brain that allows for multiple measurements throughout an organism's lifetime. In this study, we aimed to determine if blood is a viable biomarker for Nr3c1 DNA methylation in two brain regions (hippocampus and hypothalamus) in adult European starlings (Sturnus vulgaris). We found that DNA methylation of CpG sites in the complete Nr3c1 putative promoter varied among tissue types and was lowest in blood. Although we identified a similar cluster of correlated Nr3c1 putative promoter CpG sites within each tissue, this cluster did not show any correlation in DNA methylation among tissues. Additional studies should consider the role of the developmental environment in producing epigenetic modifications in different tissues.

Immunomethylomics: A Novel Cancer Risk Prediction Tool

There is emerging evidence that the immune biology associated with lung and other solid tumors, as well as patient immune genetic traits, contributes to individual survival. At this time, dramatic advances in immunologic approaches to the study and management of human cancers are taking place, including lung and head and neck squamous cell carcinoma. However, major obstacles for therapies are the profound immune alterations in blood and in the tumor microenvironment that arise in tandem with the cancer. Although there is a significant current effort underway across the cancer research community to probe the tumor environment to uncover the dynamics of the immune response, little similar work is being done to understand the dynamics of immune alterations in peripheral blood, despite evidence showing the prognostic relevance of the neutrophil/lymphocyte ratio for these cancers. A prominent feature of cancer-associated inflammation is the generation of myeloid-derived suppressor cells, which arise centrally in bone marrow myelopoiesis and peripherally in response to tumor factors. Two classes of myeloid-derived suppressor cells are recognized: granulocytic and monocytic. To date, such immune factors have not been integrated into molecular classification or prognostication. Here, we advocate for a more complete characterization of patient immune profiles, using DNA from archival peripheral blood after application of methylation profiling (immunomethylomics). At the heart of this technology are cell libraries of differentially methylated regions that provide the "fingerprints" of immune cell subtypes. Going forward, opportunities exist to explore aberrant immune profiles in the context of cancer-associated inflammation, potentially adding significantly to prognostic and mechanistic information for solid tumors.

Estimation of Eosinophil Cells in Cord Blood with References Based on Blood in Adults via Bayesian Measurement Error Modeling

MOTIVATION

Eosinophils are phagocytic white blood cells with a variety of roles in the immune system. In situations where actual counts are not available, high quality approximations of their cell proportions using indirect markers are critical.

RESULTS

We develop a Bayesian measurement error model to estimate proportions of eosinophils in cord blood, using the cord blood DNA methylation profiles, based on markers of eosinophil cell heterogeneity in blood of adults. The proposed method can be directly extended to other cells across different reference panels. We demonstrate the method's estimation accuracy using B cells and show that the findings support the proposed approach. The method has been incorporated into the estimateCellCounts function in the minfi package to estimate eosinophil cells proportions in cord blood.

AVAILABILITY

estimateCellCounts function is implemented and available in Bioconductor package minfi.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

RNA sequencing of identical twins discordant for autism reveals blood-based signatures implicating immune and transcriptional dysregulation

Background

A gap exists in our mechanistic understanding of how genetic and environmental risk factors converge at the molecular level to result in the emergence of autism symptoms. We compared blood-based gene expression signatures in identical twins concordant and discordant for autism spectrum condition (ASC) to differentiate genetic and environmentally driven transcription differences, and establish convergent evidence for biological mechanisms involved in ASC.

Methods

Genome-wide gene expression data were generated using RNA-seq on whole blood samples taken from 16 pairs of monozygotic (MZ) twins and seven twin pair members (39 individuals in total), who had been assessed for ASC and autism traits at age 12. Differential expression (DE) analyses were performed between (a) affected and unaffected subjects (N = 36) and (b) within discordant ASC MZ twin pairs (total N = 11) to identify environmental-driven DE. Gene set enrichment and pathway testing was performed on DE gene lists. Finally, an integrative analysis using DNA methylation data aimed to identify genes with consistent evidence for altered regulation in cis.

Results

In the discordant twin analysis, three genes showed evidence for DE at FDR < 10%: IGHG4, EVI2A and SNORD15B. In the case-control analysis, four DE genes were identified at FDR < 10% including IGHG4, PRR13P5, DEPDC1B, and ZNF501. We find enrichment for DE of genes curated in the SFARI human gene database. Pathways showing evidence of enrichment included those related to immune cell signalling and immune response, transcriptional control and cell cycle/proliferation. Integrative methylomic and transcriptomic analysis identified a number of genes showing suggestive evidence for cis dysregulation.

Limitations

Identical twins stably discordant for ASC are rare, and as such the sample size was limited and constrained to the use of peripheral blood tissue for transcriptomic and methylomic profiling. Given these primary limitations, we focused on transcript-level analysis.

Conclusions

Using a cohort of ASC discordant and concordant MZ twins, we add to the growing body of transcriptomic-based evidence for an immune-based component in the molecular aetiology of ASC. Whilst the sample size was limited, the study demonstrates the utility of the discordant MZ twin design combined with multi-omics integration for maximising the potential to identify disease-associated molecular signals.

In Epigenomic Studies, Including Cell-Type Adjustments in Regression Models Can Introduce Multicollinearity, Resulting in Apparent Reversal of Direction of Association

Background: Association studies of epigenome-wide DNA methylation and disease can inform biological mechanisms. DNA methylation is often measured in peripheral blood, with heterogeneous cell types with different methylation profiles. Influences such as adiposity-associated inflammation can change cell-type proportions, altering measured blood methylation levels. To determine whether associations between loci-specific methylation and outcomes result from cellular heterogeneity, many studies adjust for estimated blood cell proportions, but high correlations between methylation and cell-type proportions could violate the statistical assumption of no multicollinearity. We examined these assumptions in a population-based study. Methods: CDKN2A promoter CpG methylation was measured in peripheral blood from 812 adolescents aged 17 years (Western Australian Pregnancy Cohort Study). Log_e adolescent BMI was used as the outcome in a regression analysis with DNA methylation as predictor, adjusting for age/sex. Further regression analyses additionally adjusted for estimated cell-type proportions using the reference-based Houseman method, and simulations modeled the effects of varying levels of correlation between cell proportions and methylation. Correlations between estimated cell proportions and CpG methylation from Illumina 450K were measured. Results: Lower DNA methylation was associated with higher BMI when cell-type adjustment was not included; for CpG4, β = -0.004 log_eBMI/%methylation (95% CI -0.0065, -0.001; p = 0.003). The direction of association reversed when adjustment for six cell types was made; for CpG4, β = 0.004 log_eBMI/%methylation (-0.0002, 0.0089; p = 0.06). Correlations between CpG methylation and cell-type proportions were high, and variance inflation factors (VIFs) were extremely high (25 to 113.7). Granulocyte count was correlated with BMI, and removing granulocytes from the regression model reduced all VIFs to <3.1, with persistence of a positive association between methylation and BMI [CpG4 β = 0.004 log_eBMI/%methylation (-0.0002, 0.0088; p = 0.06)]. Simulations supported major effects of multicollinearity on regression results. Conclusions: Where cell types are highly correlated with other covariates in regression models, the statistical assumption of no multicollinearity may be violated. This can result in reversal of direction of association, particularly when examining associations with phenotypes related to inflammation, as CpG methylation may associate with changes in cell-type proportions. Removing predictors with high correlations from regression models may remove the multicollinearity. However, this might hinder biological interpretability.

Particulate matter exposure shapes DNA methylation through the lifespan

Exposure to airborne particulate matter (PM) has been associated with detrimental health effects. DNA methylation represents the most well-studied epigenetic factor among the possible mechanisms underlying this association. Interestingly, changes of DNA methylation in response to environmental stimuli are being considered for their role in the pathogenic mechanism, but also as mediators of the body adaptation to air pollutants.Several studies have evaluated both global and gene-specific methylation in relation to PM exposure in different clinical conditions and life stages. The purpose of the present literature review is to evaluate the most relevant and recent studies in the field in order to analyze the available evidences on long- and short-term PM exposure and DNA methylation changes, with a particular focus on the different life stages when the alteration occurs. PM exposure modulates DNA methylation affecting several biological mechanisms with marked effects on health, especially during susceptible life stages such as pregnancy, childhood, and the older age.Although many cross-sectional investigations have been conducted so far, only a limited number of prospective studies have explored the potential role of DNA methylation. Future studies are needed in order to evaluate whether these changes might be reverted.

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

BACKGROUND

Umbilical 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.

RESULTS

We 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.

CONCLUSION

These 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.

Age prediction of children and adolescents aged 6-17 years: an epigenome-wide analysis of DNA methylation

The DNA methylation age, a good reflection of human aging process, has been used to predict chronological age of adults and newborns. However, the prediction model for children and adolescents was absent. In this study, we aimed to generate a prediction model of chronological age for children and adolescents aged 6-17 years by using age-specific DNA methylation patterns from 180 Chinese twin individuals. We identified 6,350 age-related CpGs from the epigenome-wide association analysis (N=179). 116 known age-related sites in children were confirmed. 83 novel CpGs were selected as predictors from all age-related loci by elastic net regression and they could accurately predict the chronological age of the pediatric population, with a correlation of 0.99 and the error of 0.23 years in the training dataset (N=90). The predictive accuracy in the testing dataset (N=89) was high (correlation=0.93, error=0.62 years). Among the 83 predictors, 49 sites were novel probes not existing on the Illumina 450K BeadChip. The top two predictors of age were on the PRKCB and REG4 genes, which are associated with diabetes and cancer, respectively. Our results suggest that the chronological age can be accurately predicted among children and adolescents aged 6-17 years by 83 newly identified CpG sites.

Enhanced exposure assessment and genome-wide DNA methylation in World Trade Center disaster responders

DNA methylation has emerged as a promising target linking environmental exposures and cancer. The World Trade Center (WTC) responders sustained exposures to potential carcinogens, resulting in an increased risk of cancer. Previous studies of cancer risk in WTC-exposed responders were limited by the deficiency in quantitative and individual information on exposure to carcinogens. The current study introduces a new exposure-ranking index (ERI) for estimating cancer-related acute and chronic exposures, which aimed to improve the ability of future analyses to estimate cancer risk. An epigenome-wide association study based on DNA methylation and a weighted gene co-expression network analysis were carried out to identify cytosine-phosphate-guanosine (CpG) sites, modules of correlated CpG sites, and biological pathways associated with the new ERI. Methylation was profiled on blood samples using Illumina 450K Beadchip. No significant epigenome-wide association was found for ERI at a false discovery rate of 0.05. Several cancer-related pathways emerged in pathway analyses for the top ranking genes from epigenome-wide association study as well as enriched module from the weighted gene co-expression network analysis. The current study was the first DNA methylation study that aimed to identify methylation signature for cancer-related exposure in the WTC population. No CpG sites survived multiple testings adjustment. However, enriched gene sets involved in cancer, were identified in both acute and chronic ERIs, supporting the view that multiple genes play a role in this complex exposure.

Biomarkers in Motor Neuron Disease: A State of the Art Review

Motor neuron disease can be viewed as an umbrella term describing a heterogeneous group of conditions, all of which are relentlessly progressive and ultimately fatal. The average life expectancy is 2 years, but with a broad range of months to decades. Biomarker research deepens disease understanding through exploration of pathophysiological mechanisms which, in turn, highlights targets for novel therapies. It also allows differentiation of the disease population into sub-groups, which serves two general purposes: (a) provides clinicians with information to better guide their patients in terms of disease progression, and (b) guides clinical trial design so that an intervention may be shown to be effective if population variation is controlled for. Biomarkers also have the potential to provide monitoring during clinical trials to ensure target engagement. This review highlights biomarkers that have emerged from the fields of systemic measurements including biochemistry (blood, cerebrospinal fluid, and urine analysis); imaging and electrophysiology, and gives examples of how a combinatorial approach may yield the best results. We emphasize the importance of systematic sample collection and analysis, and the need to correlate biomarker findings with detailed phenotype and genotype data.

Making Sense of the Epigenome Using Data Integration Approaches

Epigenetic research involves examining the mitotically heritable processes that regulate gene expression, independent of changes in the DNA sequence. Recent technical advances such as whole-genome bisulfite sequencing and affordable epigenomic array-based technologies, allow researchers to measure epigenetic profiles of large cohorts at a genome-wide level, generating comprehensive high-dimensional datasets that may contain important information for disease development and treatment opportunities. The epigenomic profile for a certain disease is often a result of the complex interplay between multiple genetic and environmental factors, which poses an enormous challenge to visualize and interpret these data. Furthermore, due to the dynamic nature of the epigenome, it is critical to determine causal relationships from the many correlated associations. In this review we provide an overview of recent data analysis approaches to integrate various omics layers to understand epigenetic mechanisms of complex diseases, such as obesity and cancer. We discuss the following topics: (i) advantages and limitations of major epigenetic profiling techniques, (ii) resources for standardization, annotation and harmonization of epigenetic data, and (iii) statistical methods and machine learning methods for establishing data-driven hypotheses of key regulatory mechanisms. Finally, we discuss the future directions for data integration that shall facilitate the discovery of epigenetic-based biomarkers and therapies.

Aberrant DNA methylation of M1-macrophage genes in coronary artery disease

M1 and M2 macrophage balance in atherosclerosis has attracted much interest. Though, it remains unknown how macrophage heterogeneity is regulated. Moreover, the regulation of macrophage polarization and activation also involve DNA methylation. However, it remains ambiguous which genes are under direct regulation by DNA methylation. Our aim was to evaluate the gene-specific promoter DNA methylation status of M1/M2 polarization markers in PBMCs of CAD patients. A case-control study was performed with 25 CAD patients and 25 controls to study the promoter DNA methylation status of STAT1, STAT6, MHC2, IL12b, iNOS, JAK1, JAK2 and SOCS5 using MS-HRM analysis. Our data indicates that there was a clear-cut difference in the pattern of gene-specific promoter DNA methylation of CAD patients in comparison to controls. A significant difference was observed between the percentage methylation of STAT1, IL12b, MHC2, iNOS, JAK1 and JAK2 in CAD patients and control subjects. In conclusion, our data show that MS-HRM assay is a rapid and inexpensive method for qualitatively identifying aberrant gene-specific promoter DNA methylation changes in CAD. Furthermore, we propose that gene-specific promoter DNA methylation based on monocyte/macrophage might aid as diagnostic marker for clinical application or DNA methylation-related drug interventions may offer novel possibilities for atherosclerotic disease management.

DNA Methylation in Healthy Older Adults With a History of Childhood Adversity-Findings From the Women 40+ Healthy Aging Study

Background: Adversity in early development seems to increase the risk of stress-related somatic disorders later in life. Physiologically, functioning of the hypothalamic-pituitary-adrenal and hypothalamic-pituitary-gonadal axes is often discussed as long-term mediators of risk. In particular, DNA methylation in the glucocorticoid receptor gene promoter (NR3C1) has been associated with type and strength of early life adversity and subsequent effects on HPA axis signaling in humans. Animal studies, moreover, suggest changes in DNA methylation in the estrogen receptor gene (ERα) upon early life adversity. We investigated the association of type and severity of childhood adversity with methylation in NR3C1 and ERα and additionally considered associations between methylation and steroid hormone secretion. Methods: The percentage of methylation within the NR3C1 promoter and the ERα shore was investigated using dried blood spot samples of 103 healthy women aged 40-73 years. Childhood adversity was examined with the Childhood Trauma Questionnaire. Linear regression analyses were performed with methylation as dependent variable and the experience of emotional abuse and neglect, physical abuse and neglect, and sexual abuse (compared to non-experience) as independent variables. All analyses were controlled for age, BMI, annual household income, and smoking status and were adjusted for multiple testing. Results: Overall, over 70% of the sample reported having experienced any kind of abuse or neglect of at least low intensity. There were no significant associations between childhood adversity and methylation in the NR3C1 promoter (all p > .10). Participants reporting emotional abuse showed significantly higher methylation in the ERα shore than those who did not (p = .001). Additionally, higher levels of adversity were associated with higher levels of ERα shore methylation (p = .001). Conclusion: In healthy women, early life adversity does not seem to result in NR3C1 promoter hypermethylation in midlife and older age. This is the first study in humans to suggest that childhood adversity might, however, epigenetically modify the ERα shore. Further studies are needed to gain a better understanding of why some individuals remain healthy and others develop psychopathologies in the face of childhood adversity.

Frequency of heavy vehicle traffic and association with DNA methylation at age 18 years in a subset of the Isle of Wight birth cohort

Assessment of changes in DNA methylation (DNA-m) has the potential to identify adverse environmental exposures. To examine DNA-m among a subset of participants (n = 369) in the Isle of Wight birth cohort who reported variable near resident traffic frequencies. We used self-reported frequencies of heavy vehicles passing by the homes of study subjects as a proxy measure for TRAP, which were: never, seldom, 10 per day, 1-9 per hour and >10 per hour. Methylation of cytosine-phosphate-guanine (CpG) dinucleotide sequences in the DNA was assessed from blood samples collected at age 18 years (n = 369) in the F1 generation. We conducted an epigenome wide association study to examine CpGs related to the frequency of heavy vehicles passing by subjects' homes, and employed multiple linear regression models to assess potential associations. We repeated some of these analysis in the F2 generation (n = 140). Thirty-five CpG sites were associated with heavy vehicular traffic. After adjusting for confounders, we found 23 CpGs that were more methylated, and 11 CpGs that were less methylated with increasing heavy vehicular traffic frequency among all subjects. In the F2 generation, 2 of 31 CpGs were associated with traffic frequencies and the direction of the effect was the same as in the F1 subset while differential methylation of 7 of 31 CpG sites correlated with gene expression. Our findings reveal differences in DNA-m in participants who reported higher heavy vehicular traffic frequencies when compared to participants who reported lower frequencies.

DNA methylation analysis from saliva samples for epidemiological studies

Saliva is a non-invasive, easily accessible tissue, which is regularly collected in large epidemiological studies to examine genetic questions. Recently, it is becoming more common to use saliva to assess DNA methylation. However, DNA extracted from saliva is a mixture of both bacterial and human DNA derived from epithelial and immune cells in the mouth. Thus, there are unique challenges to using salivary DNA in methylation studies that can influence data quality. This study assesses: (1) quantification of human DNA after extraction; (2) delineation of human and bacterial DNA; (3) bisulfite conversion (BSC); (4) quantification of BSC DNA; (5) PCR amplification of BSC DNA from saliva and; (6) quantitation of DNA methylation with a targeted assay. The framework proposed will allow saliva samples to be more widely used in targeted epigenetic studies.

An optimized library for reference-based deconvolution of whole-blood biospecimens assayed using the Illumina HumanMethylationEPIC BeadArray

Genome-wide methylation arrays are powerful tools for assessing cell composition of complex mixtures. We compare three approaches to select reference libraries for deconvoluting neutrophil, monocyte, B-lymphocyte, natural killer, and CD4+ and CD8+ T-cell fractions based on blood-derived DNA methylation signatures assayed using the Illumina HumanMethylationEPIC array. The IDOL algorithm identifies a library of 450 CpGs, resulting in an average R2 = 99.2 across cell types when applied to EPIC methylation data collected on artificial mixtures constructed from the above cell types. Of the 450 CpGs, 69% are unique to EPIC. This library has the potential to reduce unintended technical differences across array platforms.

Polyunsaturated Fatty Acid Biosynthesis Involving Δ8 Desaturation and Differential DNA Methylation of FADS2 Regulates Proliferation of Human Peripheral Blood Mononuclear Cells

Polyunsaturated fatty acids (PUFAs) are important for immune function. Limited evidence indicates that immune cell activation involves endogenous PUFA synthesis, but this has not been characterised. To address this, we measured metabolism of 18:3n-3 in quiescent and activated peripheral blood mononuclear cells (PBMCs), and in Jurkat T cell leukaemia. PBMCs from men and women (n = 34) were incubated with [1-¹³C]18:3n-3 with or without Concanavalin A (Con. A). 18:3n-3 conversion was undetectable in unstimulated PBMCs, but up-regulated when stimulated. The main products were 20:3n-3 and 20:4n-3, while 18:4n-3 was undetectable, suggesting initial elongation and Δ8 desaturation. PUFA synthesis was 17.4-fold greater in Jurkat cells than PBMCs. The major products of 18:3n-3 conversion in Jurkat cells were 20:4n-3, 20:5n-3, and 22:5n-3. ¹³C Enrichment of 18:4n-3 and 20:3n-3 suggests parallel initial elongation and Δ6 desaturation. The FADS2 inhibitor SC26196 reduced PBMC, but not Jurkat cell, proliferation suggesting PUFA synthesis is involved in regulating mitosis in PBMCs. Con. A stimulation increased FADS2, FADS1, ELOVL5 and ELOVL4 mRNA expression in PBMCs. A single transcript corresponding to the major isoform of FADS2, FADS20001, was detected in PBMCs and Jurkat cells. PBMC activation induced hypermethylation of a 470bp region in the FADS2 5'-regulatory sequence. This region was hypomethylated in Jurkat cells compared to quiescent PBMCs. These findings show that PUFA synthesis involving initial elongation and Δ8 desaturation is involved in regulating PBMC proliferation and is regulated via transcription possibly by altered DNA methylation. These processes were dysregulated in Jurkat cells. This has implications for understanding the regulation of mitosis in normal and transformed lymphocytes.

Elevated Global DNA Methylation Is Not Exclusive to Amyotrophic Lateral Sclerosis and Is Also Observed in Spinocerebellar Ataxia Types 1 and 2

Adult-onset neurological disorders are caused and influenced by a multitude of different factors, including epigenetic modifications. Here, using an ELISA kit selected upon careful testing, we investigated global 5-methylcytosine (5-mC) levels in sporadic and familial amyotrophic lateral sclerosis (sALS and fALS), spinocerebellar ataxia types 1 and 2 (SCA1 and SCA2), Huntington's disease, Friedreich's ataxia, and myotonic dystrophy type 1. We report a significant elevation in global 5-mC levels of about 2-7% on average for sALS (p < 0.01 [F(1, 243) = 9.159, p = 0.0027]) and various forms of fALS along with SCA1 (p < 0.01 [F(1, 83) = 11.285], p = 0.0012) and SCA2 (p < 0.001 [F(1, 122) = 29.996, p = 0.0001]) when compared to age- and sex-matched healthy controls. C9orf72 expansion carrier ALS patients exhibit the highest global 5-mC levels along with C9orf72 promoter hypermethylation. We failed to measure global 5-hydroxymethylcytosine (5-hmC) levels in blood, probably due to the very low levels of 5-hmC and the limitations of the commercially available ELISA kits. Our results point towards a role for epigenetics modification in ALS, SCA1, and SCA2, and help conclude a dispute on the global 5-mC levels in sALS blood.

DNA methylation markers associated with type 2 diabetes, fasting glucose and HbA1c levels: a systematic review and replication in a case-control sample of the Lifelines study

AIMS/HYPOTHESIS

Epigenetic mechanisms may play an important role in the aetiology of type 2 diabetes. Recent epigenome-wide association studies (EWASs) identified several DNA methylation markers associated with type 2 diabetes, fasting glucose and HbA_1c levels. Here we present a systematic review of these studies and attempt to replicate the CpG sites (CpGs) with the most significant associations from these EWASs in a case-control sample of the Lifelines study.

METHODS

We performed a systematic literature search in PubMed and EMBASE for EWASs to test the association between DNA methylation and type 2 diabetes and/or glycaemic traits and reviewed the search results. For replication purposes we selected 100 unique CpGs identified in peripheral blood, pancreas, adipose tissue and liver from 15 EWASs, using study-specific Bonferroni-corrected significance thresholds. Methylation data (Illumina 450K array) in whole blood from 100 type 2 diabetic individuals and 100 control individuals from the Lifelines study were available. Multivariate linear models were used to examine the associations of the specific CpGs with type 2 diabetes and glycaemic traits.

RESULTS

From the 52 CpGs identified in blood and selected for replication, 15 CpGs showed nominally significant associations with type 2 diabetes in the Lifelines sample (p < 0.05). The results for five CpGs (in ABCG1, LOXL2, TXNIP, SLC1A5 and SREBF1) remained significant after a stringent multiple-testing correction (changes in methylation from -3% up to 3.6%, p < 0.0009). All associations were directionally consistent with the original EWAS results. None of the selected CpGs from the tissue-specific EWASs were replicated in our methylation data from whole blood. We were also unable to replicate any of the CpGs associated with HbA_1c levels in the healthy control individuals of our sample, while two CpGs (in ABCG1 and CCDC57) for fasting glucose were replicated at a nominal significance level (p < 0.05).

CONCLUSIONS/INTERPRETATION

A number of differentially methylated CpGs reported to be associated with type 2 diabetes in the EWAS literature were replicated in blood and show promise for clinical use as disease biomarkers. However, more prospective studies are needed to support the robustness of these findings.

Genomic 5-mC contents in peripheral blood leukocytes were independent protective factors for coronary artery disease with a specific profile in different leukocyte subtypes

Background

Alterations in DNA methylation are demonstrated in atherosclerosis pathogenesis. However, changing rules of global DNA methylation and hydroxymethylation in peripheral blood leukocytes (PBLs) and different blood cell subtypes of coronary artery disease (CAD) patients are still inconclusive, and much less is known about mechanisms underlying.

Results

We recruited 265 CAD patients and 270 healthy controls with genomic DNA from PBLs, of which 50 patients and 50 controls were randomly chosen with DNA from isolated neutrophils, lymphocytes and monocytes, and RNA from PBLs. Genomic 5-methylcytosine (5-mC) and 5-hydroxymethylcytosine (5-hmC) contents were quantified by liquid chromatography-electrospray ionization-tandem mass spectrometry (LC-ESI-MS/MS) assay. Genomic 5-mC contents were negatively associated with the serum total cholesterol (TC) level (P = 0.010), age (P = 0.016), and PBL classifications (P = 0.023), explaining 6.8% individual variation in controls. Furthermore, genomic 5-mC contents were inversely associated with an increased risk of CAD (odds ratio (OR) = 0.325, 95% confidence interval (CI) = 0.237~0.445, P = 2.62 × 10^− 12), independent of PBL counts and classifications, age, sex, histories of hyperlipidemia, hypertension, and diabetes. Within-individual analysis showed a general 5-mC decrease in PBL subtypes, but significant difference was found in monocytes only (P = 0.001), accompanied by increased 5-hmC (P = 3.212 × 10^− 4). In addition, coincident to the reduced DNMT1 expression in patients’ PBLs, the expression level of DNMT1 was significantly lower (P = 0.022) in oxidized low-density lipoprotein (ox-LDL) stimulated THP-1-derived foam cells compared to THP-1 monocytes, with decreased genomic 5-mdC content (P = 0.038).

Conclusions

Global hypomethylation of blood cells defined dominantly by the monocyte DNA hypomethylation is independently associated with the risk of CAD in Chinese Han population. The importance of monocytes in atherosclerosis pathophysiology may demonstrate via an epigenetic pathway, but prospective studies are still needed to test the causality.

Electronic supplementary material

The online version of this article (10.1186/s13148-018-0443-x) contains supplementary material, which is available to authorized users.

Longitudinal study of surrogate aging measures during human immunodeficiency virus seroconversion

Persons living with human immunodeficiency virus (HIV) harbor an increased risk of age-related conditions. We measured changes in telomere length and DNA methylation in the peripheral blood of 31 intravenous drug users, who were followed longitudinally with blood samples pre-HIV (T1), immediately post-HIV (T2; 1.9±1 year from T1), and at a later follow-up time (T3; 2.2±1 year from T2). Absolute telomere length measurements were performed using polymerase chain reaction methods. Methylation profiles were obtained using the Illumina Human Methylation450 platform. Methylation aging was assessed using the Horvath method. Telomere length significantly decreased between T1 and T2 (227±46 at T1 vs. 201±48 kbp/genome at T2, p=0.045), while no differences were observed between T2 and T3 (201±48 at T2 vs. 186±27 kbp/genome at T3, p=0.244). Methylation aging as measured by the age acceleration residual increased over the time course of HIV infection (p=0.035). CpG sites corresponding to PCBP2 and CSRNP1 were differentially methylated between T1 and T2 at a q-value <0.05. Telomere shortening and methylation changes can therefore be observed in the short-term period immediately following HIV seroconversion. Further studies to confirm these results in larger sample sizes and to compare these results to non-HIV and non-injection drug users are warranted.

Leukocyte Counts Based on DNA Methylation at Individual Cytosines

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.

The Intersection of Aging Biology and the Pathobiology of Lung Diseases: A Joint NHLBI/NIA Workshop

Death from chronic lung disease is increasing and chronic obstructive pulmonary disease has become the third leading cause of death in the United States in the past decade. Both chronic and acute lung diseases disproportionately affect elderly individuals, making it likely that these diseases will become more frequent and severe as the worldwide population ages. Chronic lung diseases are associated with substantial morbidity, frequently resulting in exercise limiting dyspnea, immobilization, and isolation. Therefore, effective strategies to prevent or treat lung disease are likely to increase healthspan as well as life span. This review summarizes the findings of a joint workshop sponsored by the NIA and NHLBI that brought together investigators focused on aging and lung biology. These investigators encouraged the use of genetic systems and aged animals in the study of lung disease and the development of integrative systems-based platforms that can dynamically incorporate data sets that describe the genomics, transcriptomics, epigenomics, metabolomics, and proteomics of the aging lung in health and disease. Further research was recommended to integrate benchmark biological hallmarks of aging in the lung with the pathobiology of acute and chronic lung diseases with divergent pathologies for which advanced age is the most important risk factor.

Accounting for cell lineage and sex effects in the identification of cell-specific DNA methylation using a Bayesian model selection algorithm

Cell- and sex-specific differences in DNA methylation are major sources of epigenetic variation in whole blood. Heterogeneity attributable to cell type has motivated the identification of cell-specific methylation at the CpG level, however statistical methods for this purpose have been limited to pairwise comparisons between cell types or between the cell type of interest and whole blood. We developed a Bayesian model selection algorithm for the identification of cell-specific methylation profiles that incorporates knowledge of shared cell lineage and allows for the identification of differential methylation profiles in one or more cell types simultaneously. Under the proposed methodology, sex-specific differences in methylation by cell type are also assessed. Using publicly available, cell-sorted methylation data, we show that 51.3% of female CpG markers and 61.4% of male CpG markers identified were associated with differential methylation in more than one cell type. The impact of cell lineage on differential methylation was also highlighted. An evaluation of sex-specific differences revealed differences in CD56⁺NK methylation, within both single and multi- cell dependent methylation patterns. Our findings demonstrate the need to account for cell lineage in studies of differential methylation and associated sex effects.

mIDH-associated DNA hypermethylation in acute myeloid leukemia reflects differentiation blockage rather than inhibition of TET-mediated demethylation

Isocitrate dehydrogenases 1 and 2 (IDH1/2) are recurrently mutated in acute myeloid leukemia (AML), but their mechanistic role in leukemogenesis is poorly understood. The inhibition of TET enzymes by D-2-hydroxyglutarate (D-2-HG), which is produced by mutant IDH1/2 (mIDH1/2), has been suggested to promote epigenetic deregulation during tumorigenesis. In addition, mIDH also induces a differentiation block in various cell culture and mouse models. Here we analyze the genomic methylation patterns of AML patients with mIDH using Infinium 450K data from a large AML cohort and found that mIDH is associated with pronounced DNA hypermethylation at tens of thousands of CpGs. Interestingly, however, myeloid leukemia cells overexpressing mIDH, cells that were cultured in the presence of D-2-HG or TET2 mutant AML patients did not show similar methylation changes. In further analyses, we also characterized the methylation landscapes of myeloid progenitor cells and analyzed their relationship to mIDH-associated hypermethylation. Our findings identify the differentiation state of myeloid cells, rather than inhibition of TET-mediated DNA demethylation, as a major factor of mIDH-associated hypermethylation in AML. Furthermore, our results are also important for understanding the mode of action of currently developed mIDH inhibitors.

Epigenetic regulation of inflammation in localized aggressive periodontitis

Background

We have previously demonstrated a Toll-like receptor (TLR)-mediated hyper-responsive phenotype in our cohort of localized aggressive periodontitis (LAP) individuals. However, mechanisms related to this phenotype are still not clear in the literature. The objective of this cross-sectional study is to examine the role of epigenetic regulation, specifically DNA methylation status of genes in the TLR pathway in this cohort. Peripheral blood was collected from 20 LAP patients and 20 healthy unrelated controls. Whole blood was stimulated with 1 μl (100 ng/μl) of purified Escherichia coli lipopolysaccharide (LPS) for 24 h and cyto/chemokines in the supernatants analyzed by Luminex multiplex assays. Genomic DNA extracted from buffy coats prepared from a second tube of whole blood was used for DNA methylation analysis by pyrosequencing of seven TLR signaling genes (FADD, MAP3K7, MYD88, IL6R, PPARA, IRAK1BP1, RIPK2).

Results

Significant differences in the methylation status were observed at specific CpG positions in LAP patients compared to healthy controls and interestingly also between severe and moderate LAP. Specifically, subjects with moderate LAP presented hypermethylation of both the upregulating (MAP3K7, MYD88, IL6R, and RIPK2) and downregulating (FADD, IRAK, and PPARA) genes, while severe LAP presented hypomethylation of these genes. Further analysis on CpG sites with significant differences in methylation status correlates with an increased pro-inflammatory cytokine profile for LAP patients.

Conclusions

Our findings suggest that epigenetic modifications of genes in the TLR pathway may orchestrate the thresholds for balancing induction and prevention of tissue destruction during the course of disease, and thus differ significantly at different stages of the disease, where moderate LAP shows hypermethylation and severe LAP shows hypomethylation of several genes.

Trial registration

https://clinicaltrials.gov, NCT01330719

The Epigenomic Analysis of Human Obesity

OBJECTIVE

Analysis of the epigenome-the chemical modifications and packaging of the genome that can influence or indicate its activity-enables molecular insight into cell type-specific machinery. It can, therefore, reveal the pathophysiological mechanisms at work in disease. Detected changes can also represent physiological responses to adverse environmental exposures, thus enabling the epigenetic mark of DNA methylation to act as an epidemiological biomarker, even in surrogate tissue. This makes epigenomic analysis an attractive prospect to further understand the pathobiology and epidemiological aspects of obesity. Furthermore, integrating epigenomic data with known obesity-associated common genetic variation can aid in deciphering their molecular mechanisms.

METHODS AND CONCLUSIONS

This review primarily examines epidemiological or population-based studies of epigenetic modifications in relation to adiposity traits, as opposed to animal or cell models. It discusses recent work exploring the epigenome with respect to human obesity, which to date has predominately consisted of array-based studies of DNA methylation in peripheral blood. It is of note that highly replicated BMI DNA methylation associations are not causal, but strongly driven by coassociations for more precisely measured intertwined outcomes and factors, such as hyperlipidemia, hyperglycemia, and inflammation. Finally, the potential for the future exploration of the epigenome in obesity and related disorders is considered.

Prenatal phthalate exposure and altered patterns of DNA methylation in cord blood

Epigenetic changes such as DNA methylation may be a molecular mechanism through which environmental exposures affect health. Phthalates are known endocrine disruptors with ubiquitous exposures in the general population including pregnant women, and they have been linked with a number of adverse health outcomes. We examined the association between in utero phthalate exposure and altered patterns of cord blood DNA methylation in 336 Mexican-American newborns. Concentrations of 11 phthalate metabolites were analyzed in maternal urine samples collected at 13 and 26 weeks gestation as a measure of fetal exposure. DNA methylation was assessed using the Infinium HumanMethylation 450K BeadChip adjusting for cord blood cell composition. To identify differentially methylated regions (DMRs) that may be more informative than individual CpG sites, we used two different approaches, DMRcate and comb-p. Regional assessment by both methods identified 27 distinct DMRs, the majority of which were in relation to multiple phthalate metabolites. Most of the significant DMRs (67%) were observed for later pregnancy (26 weeks gestation). Further, 51% of the significant DMRs were associated with the di-(2-ethylhexyl) phthalate metabolites. Five individual CpG sites were associated with phthalate metabolite concentrations after multiple comparisons adjustment (FDR), all showing hypermethylation. Genes with DMRs were involved in inflammatory response (IRAK4 and ESM1), cancer (BRCA1 and LASP1), endocrine function (CNPY1), and male fertility (IFT140, TESC, and PRDM8). These results on differential DNA methylation in newborns with prenatal phthalate exposure provide new insights and targets to explore mechanism of adverse effects of phthalates on human health. Environ. Mol. Mutagen. 58:398-410, 2017. © 2017 Wiley Periodicals, Inc.

An epigenome-wide DNA methylation study of PTSD and depression in World Trade Center responders

Previous epigenome-wide association studies (EWAS) of posttraumatic stress disorder (PTSD) and major depressive disorder (MDD) have been inconsistent. This may be due to small sample sizes, and measurement and tissue differences. The current two EWA analyses of 473 World Trade Center responders are the largest to date for both PTSD and MDD. These analyses investigated DNA methylation patterns and biological pathways influenced by differentially methylated genes associated with each disorder. Methylation was profiled on blood samples using Illumina 450 K Beadchip. Two EWA analyses compared current versus never PTSD, and current versus never MDD, adjusting for cell types and demographic confounders. Pathway and gene set enrichment analyses were performed to understand the complex biological systems of PTSD and MDD. No significant epigenome-wide associations were found for PTSD or MDD at an FDR P<0.05. The majority of genes with differential methylation at a suggestive threshold did not overlap between the two disorders. Pathways significant in PTSD included a regulator of synaptic plasticity, oxytocin signaling, cholinergic synapse and inflammatory disease pathways, while only phosphatidylinositol signaling and cell cycle pathways emerged in MDD. The failure of the current EWA analyses to detect significant epigenome-wide associations is in contrast with disparate findings from previous, smaller EWA and candidate gene studies of PTSD and MDD. Enriched gene sets involved in several biological pathways, including stress response, inflammation and physical health, were identified in PTSD, supporting the view that multiple genes play a role in this complex disorder.

Systematic review of lung function and COPD with peripheral blood DNA methylation in population based studies

BACKGROUND

Epigenetic variations in peripheral blood have potential as biomarkers for disease. This systematic review assesses the association of lung function and chronic obstructive pulmonary disease (COPD) with DNA methylation profiles in peripheral blood from population-based studies.

METHODS

Online databases Medline, Embase, and Web of Science were searched. Google Scholar was searched to identify grey literature. After removing duplicate articles, 1155 articles were independently screened by two investigators. Peer reviewed reports on population-based studies that examined peripheral blood DNA methylation in participants with measured lung function (FEV1, FEV1/FVC ratio) or known COPD status were selected for full-text review. Six articles were suitable for inclusion. Information regarding study characteristics, designs, methodologies and conclusions was extracted. A narrative synthesis was performed based on published results.

RESULTS

Three of the six articles assessed the association of COPD with DNA methylation, and two of these also included associations with lung function. Overall, five reports examined the association of lung function with DNA methylation profiles. Five of the six articles reported 'significant' results. However, no consistent CpG sites were identified across studies for COPD status or lung function values.

CONCLUSIONS

DNA methylation patterns in peripheral blood from individuals with reduced lung function or COPD may be different to those in people with normal lung function. However, this systematic review did not find any consistent associations of lung function or COPD with differentially methylated CpG sites. Large studies with a longitudinal design to address reverse causality may prove a more fruitful area of research.

TRIAL REGISTRATION

PROSPERO 2016: CRD42016037352 .

Immunomethylomic approach to explore the blood neutrophil lymphocyte ratio (NLR) in glioma survival

Background

Differentially methylated regions (DMRs) within DNA isolated from whole blood can be used to estimate the proportions of circulating leukocyte subtypes. We use the term “immunomethylomics” to describe the application of these immune lineage DMRs to studying leukocyte profiles. Here, we applied this approach to peripheral blood DNA from 72 glioma patients with molecularly defined brain tumors, representing common patient groups with defined characteristic survival times and risk factors. We first estimated the proportions of leukocyte subtypes in samples using deconvolution algorithms with reference DMR libraries from isolated leukocyte populations and Illumina 450K DNA methylation data. Then, we calculated the neutrophil to lymphocyte ratio (NLR) using methylation-derived cell composition estimates (mdNLR). The NLR is considered an indicator of immunosuppressive cells in cancer patients.

Results

Elevated mdNLR scores were observed in glioma patients compared to mdNLR values of published controls. Significantly decreased survival times were associated with mdNLR ≥ 4.0 in Cox proportional hazards models adjusted for age, gender, tumor grade, and molecular subtype (HR 2.02, 95% CI, 1.11–3.69). We also identified five myeloid-related CpGs that were highly correlated with the mdNLR (adjusted R² ≥ 0.80). Each of the five myeloid CpG loci was associated with survival when adjusted for the above covariates and offer a simplified approach for utilizing fresh or archived peripheral blood samples for interrogating a very small number of methylation markers to estimate myeloid immune influences in glioma survival.

Conclusions

The mdNLR (based on DNA methylation) is a novel candidate methylation biomarker that represents immunosuppressive myeloid cells within the blood of glioma patients with potential application in clinical trials and future epidemiologic studies of glioma risk and survival.

Electronic supplementary material

The online version of this article (doi:10.1186/s13148-017-0316-8) contains supplementary material, which is available to authorized users.

Potential epigenetic biomarkers of obesity-related insulin resistance in human whole-blood

Obesity can increase the risk of complex metabolic diseases, including insulin resistance. Moreover, obesity can be caused by environmental and genetic factors. However, the epigenetic mechanisms of obesity are not well defined. Therefore, the identification of novel epigenetic biomarkers of obesity allows for a more complete understanding of the disease and its underlying insulin resistance. The aim of our study was to identify DNA methylation changes in whole-blood that were strongly associated with obesity and insulin resistance. Whole-blood was obtained from lean (n = 10; BMI = 23.6 ± 0.7 kg/m²) and obese (n = 10; BMI = 34.4 ± 1.3 kg/m²) participants in combination with euglycemic hyperinsulinemic clamps to assess insulin sensitivity. We performed reduced representation bisulfite sequencing on genomic DNA isolated from the blood. We identified 49 differentially methylated cytosines (DMCs; q < 0.05) that were altered in obese compared with lean participants. We identified 2 sites (Chr.21:46,957,981 and Chr.21:46,957,915) in the 5' untranslated region of solute carrier family 19 member 1 (SLC19A1) with decreased methylation in obese participants (lean 0.73 ± 0.11 vs. obese 0.09 ± 0.05; lean 0.68 ± 0.10 vs. obese 0.09 ± 0.05, respectively). These 2 DMCs identified by obesity were also significantly predicted by insulin sensitivity (r = 0.68, P = 0.003; r = 0.66; P = 0.004). In addition, we performed a differentially methylated region (DMR) analysis and demonstrated a decrease in methylation of Chr.21:46,957,915-46,958,001 in SLC19A1 of -34.9% (70.4% lean vs. 35.5% obese). The decrease in whole-blood SLC19A1 methylation in our obese participants was similar to the change observed in skeletal muscle (Chr.21:46,957,981, lean 0.70 ± 0.09 vs. obese 0.31 ± 0.11 and Chr.21:46,957,915, lean 0.72 ± 0.11 vs. obese 0.31 ± 0.13). Pyrosequencing analysis further demonstrated a decrease in methylation at Chr.21:46,957,915 in both whole-blood (lean 0.71 ± 0.10 vs. obese 0.18 ± 0.06) and skeletal muscle (lean 0.71 ± 0.10 vs. obese 0.30 ± 0.11). Our findings demonstrate a new potential epigenetic biomarker, SLC19A1, for obesity and its underlying insulin resistance.

miRNAs differentially expressed by next-generation sequencing in cord blood buffy coat samples of boys and girls

AIM

Differences in children's development and susceptibility to diseases and exposures have been observed by sex, yet human studies of sex differences in miRNAs are limited.

MATERIALS & METHODS

The genome-wide miRNA expression was characterized by sequencing-based EdgeSeq assay in cord blood buffy coats from 89 newborns, and 564 miRNAs were further analyzed.

RESULTS

Differential expression of most miRNAs was higher in boys. Neurodevelopment, RNA metabolism and metabolic ontology terms were enriched among miRNA targets. The majority of upregulated miRNAs (86%) validated by nCounter maintained positive-fold change values; however, only 21% reached statistical significance by false discovery rate.

CONCLUSION

Accounting for host factors like sex may improve the sensitivity of epigenetic analyses for epidemiological studies in early childhood.

Enlarged leukocyte referent libraries can explain additional variance in blood-based epigenome-wide association studies

AIM

We examined whether variation in blood-based epigenome-wide association studies could be more completely explained by augmenting existing reference DNA methylation libraries.

MATERIALS & METHODS

We compared existing and enhanced libraries in predicting variability in three publicly available 450K methylation datasets that collected whole-blood samples. Models were fit separately to each CpG site and used to estimate the additional variability when adjustments for cell composition were made with each library.

RESULTS

Calculation of the mean difference in the CpG-specific residual sums of squares error between models for an arthritis, aging and metabolic syndrome dataset, indicated that an enhanced library explained significantly more variation across all three datasets (p < 10(-3)).

CONCLUSION

Pathologically important immune cell subtypes can explain important variability in epigenome-wide association studies done in blood.

Epigenetic Research in Neuropsychiatric Disorders: the "Tissue Issue"

PURPOSE OF REVIEW

Evidence has linked neuropsychiatric disorders with epigenetic marks as either a biomarker of disease, biomarker of exposure, or mechanism of disease processes. Neuropsychiatric epidemiologic studies using either target brain tissue or surrogate blood tissue each have methodological challenges and distinct advantages.

RECENT FINDINGS

Brain tissue studies are challenged by small sample sizes of cases and controls, incomplete phenotyping, post-mortem timing, and cellular heterogeneity, but the use of a primary disease relevant tissue is critical. Blood-based studies have access to much larger sample sizes and more replication opportunities, as well as the potential for longitudinal measurements, both prior to onset and during the course of treatments. Yet, blood studies also are challenged by cell-type heterogeneity, and many question the validity of using peripheral tissues as a brain biomarker. Emerging evidence suggests that these limitations to blood-based epigenetic studies are surmountable, but confirmation in target tissue remains important.

SUMMARY

Epigenetic mechanisms have the potential to help elucidate biology connecting experiential risk factors with neuropsychiatric disease manifestation. Cross-tissue studies as well as advanced epidemiologic methods should be employed to more effectively conduct neuropsychiatric epigenetic research.

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

Background

Recent interest in reference-free deconvolution of DNA methylation data has led to several supervised methods, but these methods do not easily permit the interpretation of underlying cell types.

Results

We 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 demonstrate 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.

Conclusions

Our 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.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-016-1140-4) contains supplementary material, which is available to authorized users.

The importance of detailed epigenomic profiling of different cell types within organs

The human body consists of hundreds of kinds of cells specified from a single genome overlaid with cell type-specific epigenetic information. Comprehensively profiling the body's distinct epigenetic landscapes will allow researchers to verify cell types used in regenerative medicine and to determine the epigenetic effects of disease, environmental exposures and genetic variation. Key marks/factors that should be investigated include regions of nucleosome-free DNA accessible to regulatory factors, histone marks defining active enhancers and promoters, DNA methylation levels, regulatory RNAs, and factors controlling the three-dimensional conformation of the genome. Here we use the lung to illustrate the importance of investigating an organ's purified cell epigenomes, and outline the challenges and promise of realizing a comprehensive catalog of primary cell epigenomes.

Disagreement between two common biomarkers of global DNA methylation

BACKGROUND

The quantification of global DNA methylation has been established in epigenetic screening. As more practicable alternatives to the HPLC-based gold standard, the methylation analysis of CpG islands in repeatable elements (LINE-1) and the luminometric methylation assay (LUMA) of overall 5-methylcytosine content in "CCGG" recognition sites are most widely used. Both methods are applied as virtually equivalent, despite the hints that their results only partly agree. This triggered the present agreement assessments.

RESULTS

Three different human cell types (cultured MCF7 and SHSY5Y cell lines treated with different chemical modulators of DNA methylation and whole blood drawn from pain patients and healthy volunteers) were submitted to the global DNA methylation assays employing LINE-1 or LUMA-based pyrosequencing measurements. The agreement between the two bioassays was assessed using generally accepted approaches to the statistics for laboratory method comparison studies. Although global DNA methylation levels measured by the two methods correlated, five different lines of statistical evidence consistently rejected the assumption of complete agreement. Specifically, a bias was observed between the two methods. In addition, both the magnitude and direction of bias were tissue-dependent. Interassay differences could be grouped based on Bayesian statistics, and these groups allowed in turn to re-identify the originating tissue.

CONCLUSIONS

Although providing partly correlated measurements of DNA methylation, interchangeability of the quantitative results obtained with LINE-1 and LUMA was jeopardized by a consistent bias between the results. Moreover, the present analyses strongly indicate a tissue specificity of the differences between the two methods.

How to interpret epigenetic association studies: a guide for clinicians

Epigenetic mechanisms are able to alter gene expression, without altering DNA sequence, in a stable manner through cell divisions. They include, among others, the methylation of DNA cytosines and microRNAs and allow the cells to adapt to changing environmental conditions. In recent years, epigenetic association studies are providing new insights into the pathogenesis of complex disorders including prevalent skeletal disorders. Unlike the genome, the epigenome is cell and tissue specific and may change with age and a number of acquired factors. This poses particular difficulties for the design and interpretation of epigenetic studies, particularly those exploring the association of genome-wide epigenetic marks with disease phenotypes. In this report, we propose a framework to help in the critical appraisal of epigenetic association studies. In line with previous suggestions, we focus on the questions critical to appraise the validity of the study, to interpret the results and to assess the generalizability and relevance of the information.

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

Epigenome-wide association studies of disease widely use DNA methylation measured in blood as a surrogate tissue. Cell proportions can vary between people and confound associations of exposure or outcome. An adequate reference panel for estimating cell proportions from adult whole blood for DNA methylation studies is available, but an analogous cord blood cell reference panel is not yet available. Cord blood has unique cell types and the epigenetic signatures of standard cell types may not be consistent throughout the life course. Using magnetic bead sorting, we isolated cord blood cell types (nucleated red blood cells, granulocytes, monocytes, natural killer cells, B cells, CD4(+)T cells, and CD8(+)T cells) from 17 live births at Johns Hopkins Hospital. We confirmed enrichment of the cell types using fluorescence assisted cell sorting and ran DNA from the separated cell types on the Illumina Infinium HumanMethylation450 BeadChip array. After filtering, the final analysis was on 104 samples at 429,794 probes. We compared cell type specific signatures in cord to each other and methylation at 49.2% of CpG sites on the array differed by cell type (F-test P < 10(-8)). Differences between nucleated red blood cells and the remainder of the cell types were most pronounced (36.9% of CpG sites at P < 10(-8)) and 99.5% of these sites were hypomethylated relative to the other cell types. We also compared the mean-centered sorted cord profiles to the available adult reference panel and observed high correlation between the overlapping cell types for granulocytes and monocytes (both r=0.74), and poor correlation for CD8(+)T cells and NK cells (both r=0.08). We further provide an algorithm for estimating cell proportions in cord blood using the newly developed cord reference panel, which estimates biologically plausible cell proportions in whole cord blood samples.

Improving cell mixture deconvolution by identifying optimal DNA methylation libraries (IDOL)

Background

Confounding due to cellular heterogeneity represents one of the foremost challenges currently facing Epigenome-Wide Association Studies (EWAS). Statistical methods leveraging the tissue-specificity of DNA methylation for deconvoluting the cellular mixture of heterogenous biospecimens offer a promising solution, however the performance of such methods depends entirely on the library of methylation markers being used for deconvolution. Here, we introduce a novel algorithm for Identifying Optimal Libraries (IDOL) that dynamically scans a candidate set of cell-specific methylation markers to find libraries that optimize the accuracy of cell fraction estimates obtained from cell mixture deconvolution.

Results

Application of IDOL to training set consisting of samples with both whole-blood DNA methylation data (Illumina HumanMethylation450 BeadArray (HM450)) and flow cytometry measurements of cell composition revealed an optimized library comprised of 300 CpG sites. When compared existing libraries, the library identified by IDOL demonstrated significantly better overall discrimination of the entire immune cell landscape (p = 0.038), and resulted in improved discrimination of 14 out of the 15 pairs of leukocyte subtypes. Estimates of cell composition across the samples in the training set using the IDOL library were highly correlated with their respective flow cytometry measurements, with all cell-specific R²>0.99 and root mean square errors (RMSEs) ranging from [0.97 % to 1.33 %] across leukocyte subtypes. Independent validation of the optimized IDOL library using two additional HM450 data sets showed similarly strong prediction performance, with all cell-specific R²>0.90 and RMSE<4.00 %. In simulation studies, adjustments for cell composition using the IDOL library resulted in uniformly lower false positive rates compared to competing libraries, while also demonstrating an improved capacity to explain epigenome-wide variation in DNA methylation within two large publicly available HM450 data sets.

Conclusions

Despite consisting of half as many CpGs compared to existing libraries for whole blood mixture deconvolution, the optimized IDOL library identified herein resulted in outstanding prediction performance across all considered data sets and demonstrated potential to improve the operating characteristics of EWAS involving adjustments for cell distribution. In addition to providing the EWAS community with an optimized library for whole blood mixture deconvolution, our work establishes a systematic and generalizable framework for the assembly of libraries that improve the accuracy of cell mixture deconvolution.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-016-0943-7) contains supplementary material, which is available to authorized users.

DNA methylation signatures of mood stabilizers and antipsychotics in bipolar disorder

Aim: In view of the potential effects of psychiatric drugs on DNA methylation, we investigated whether medication use in bipolar disorder is associated with DNA methylation signatures. Experimental procedures: Blood-based DNA methylation patterns of six frequently used psychotropic drugs (lithium, quetiapine, olanzapine, lamotrigine, carbamazepine, and valproic acid) were examined in 172 bipolar disorder patients. After adjustment for cell type composition, we investigated gene networks, principal components, hypothesis-driven genes and epigenome-wide individual loci. Results: Valproic acid and quetiapine were significantly associated with altered methylation signatures after adjustment for drug-related changes on celltype composition. Conclusion: Psychiatric drugs influence DNA methylation patterns over and above cell type composition in bipolar disorder. Drug-related changes in DNA methylation are therefore not only an important confounder in psychiatric epigenetics but may also inform on the biological mechanisms underlying drug efficacy.