Adjustment of Cell-Type Composition Minimizes Systematic Bias in Blood DNA Methylation Profiles Derived by DNA Collection Protocols

Methodological and Biological Factors Influencing Global DNA Methylation Results Measured by LINE-1 Pyrosequencing Assay in Colorectal Tissue and Liquid Biopsy Samples

Long interspersed nuclear element 1 (LINE-1) bisulfite pyrosequencing is a widely used technique for genome-wide methylation analyses. We aimed to investigate the effects of experimental and biological factors on its results to improve the comparability. LINE-1 bisulfite pyrosequencing was performed on colorectal tissue (n = 222), buffy coat (n = 39), and plasma samples (n = 9) of healthy individuals and patients with colorectal tumors. Significantly altered methylation was observed between investigated LINE-1 CpG positions of non-tumorous tissues (p ≤ 0.01). Formalin-fixed, paraffin-embedded biopsies (73.0 ± 5.3%) resulted in lower methylation than fresh frozen samples (76.1 ± 2.8%) (p ≤ 0.01). DNA specimens after long-term storage showed higher methylation levels (+3.2%, p ≤ 0.01). In blood collection tubes with preservatives, cfDNA and buffy coat methylation significantly changed compared to K3EDTA tubes (p ≤ 0.05). Lower methylation was detected in older (>40 years, 76.8 ± 1.7%) vs. younger (78.1 ± 1.0%) female patients (p ≤ 0.05), and also in adenomatous tissues with MTHFR 677CT, or 1298AC mutations vs. wild-type (p ≤ 0.05) comparisons. Based on our findings, it is highly recommended to consider the application of standard DNA samples in the case of a possible clinical screening approach, as well as in experimental research studies.

The influence of blood sample processing on blood-based DNA methylation signatures

Stability is crucial for the clinical applicable biomarker such as DNA methylation profiles. However, the influence of various blood processing on the DNA methylation signatures have been barely studied. Here, we systematically evaluated the impact of temporary storage and frozen and thaw on the levels of DNA methylation. The methylation intensities of 13 CpG loci from 53 individuals (42 healthy participants and 11 lung cancer patients) whose blood samples were processed by up to 14 various protocols were quantitatively determined by the mass spectrometry, obtaining more than 8,000 quantitative data. We disclosed a trend of accumulatively increased DNA methylation along with time when the blood from healthy people were stored for up to 96 hours at room temperature (RT), whereas the storage at 4℃ had much weaker effects or no impact. On the contrary, the methylation patterns in the blood of lung cancer patients were more stable at both RT and 4℃ even for 96 hours. Multiple cycles of frozen and thaw could result in demethylation, but was more significant to the blood than to the extracted DNA. Our study indicated that the blood processing in vitro could influence the DNA methylation signatures and introduce unexpected biases.

Autoimmune gastritis induces aberrant DNA methylation reflecting its carcinogenic potential

BACKGROUND

Autoimmune gastritis (AIG) is a chronic inflammatory condition in gastric mucosa and is associated with increased cancer risk, though not as high as that by Helicobacter pylori (H. pylori)-associated gastritis (HPG). Although aberrant DNA methylation is induced by HPG and the level correlates with the risk of gastric cancer, DNA methylation induction by AIG is unknown.

METHODS

Gastric mucosa samples from the corpus were collected from 12 people with AIG without H. pylori infection, 10 people with HPG, and eight healthy volunteers. Genome-wide DNA methylation analysis was conducted using Infinium Methylation EPIC array. Gene expression was analyzed by quantitative RT-PCR.

RESULTS

The AIG samples had extensive aberrant DNA methylation but presented unique methylation profiles against the HPG samples after correction of leucocyte fractions. Comparison between the AIG and HPG samples showed that AIG induced methylation, but less than HPG, in overall CpG sites and also in promoter CpG islands. Promoter CpG islands of tumor-suppressor genes in the pathway of cell cycle, cell adhesion, p53, and WNT were highly methylated in the AIG samples, but more so in the HPG samples. The expression levels of IL1B and IL8, secreted by macrophage, were significantly lower in the AIG samples than in the HPG samples, suggesting that a difference in inflammatory response affected the degree and patterns of aberrant DNA methylation.

CONCLUSIONS

AIG induced aberrant DNA methylation in gastric mucosa. However, the degree of DNA methylation was less than that by HPG, which reflected carcinogenic risk.

DNA methylation analysis of cord blood samples in neonates born to gestational diabetes mothers diagnosed before 24 gestational weeks

INTRODUCTION

Genome-wide methylation analyses of gestational diabetes mellitus (GDM) diagnosed after 24 gestational weeks (late GDM (L-GDM)) using cord blood have been reported. However, epigenetic changes in neonates born to mothers with GDM diagnosed before 24 gestational weeks (early GDM (E-GDM)) have not been reported. We investigated DNA methylation in neonates born to mothers with E-GDM using cord blood samples.

RESEARCH DESIGN AND METHODS

Genome-wide DNA methylation analysis was performed using an Illumina EPIC array to compare methylation rates of 754 255 autosomal sites in cord blood samples from term neonates born to 162 mothers with GDM (E-GDM: n=84, L-GDM: n=78) and 60 normal glucose tolerance (normal OGTT) pregnancies. GDM was diagnosed based on Japan Society of Obstetrics and Gynecology criteria modified with International Association of Diabetes in Pregnancy Study Group criteria. In this study, all GDM mothers underwent dietary management, while self-monitoring of blood glucose and insulin administration was initiated when dietary modification did not achieve glycemic control.

RESULTS

There were no significant differences in genome-wide DNA methylation of cord blood samples between the GDM (E-GDM and L-GDM) groups and normal OGTT group or between the E-GDM and normal OGTT groups, L-GDM and normal OGTT groups, and E-GDM and L-GDM groups.

CONCLUSIONS

This is the first report to determine the DNA methylation patterns in neonates born to mothers with E-GDM. Neonates born to mothers with GDM, who were diagnosed based on Japan Society of Obstetrics and Gynecology criteria, may not differ in DNA methylation compared with those born to normal OGTT mothers.

Guidelines for pre-analytical conditions for assessing the methylation of circulating cell-free DNA

Methylation analysis of circulating cell-free DNA (cirDNA), as a liquid biopsy, has a significant potential to advance the detection, prognosis, and treatment of cancer, as well as many genetic disorders. The role of epigenetics in disease development has been reported in several hereditary disorders, and epigenetic modifications are regarded as one of the earliest and most significant genomic aberrations that arise during carcinogenesis. Liquid biopsy can be employed for the detection of these epigenetic biomarkers. It consists of isolation (pre-analytical) and detection (analytical) phases. The choice of pre-analytical variables comprising cirDNA extraction and bisulfite conversion methods can affect the identification of cirDNA methylation. Indeed, different techniques give a different return of cirDNA, which confirms the importance of pre-analytical procedures in clinical diagnostics. Although novel techniques have been developed for the simplification of methylation analysis, the process remains complex, as the steps of DNA extraction, bisulfite treatment, and methylation detection are each carried out separately. Recent studies have noted the absence of any standard method for the pre-analytical processing of methylated cirDNA. We have therefore conducted a comprehensive and systematic review of the important pre-analytical and analytical variables and the patient-related factors which form the basis of our guidelines for analyzing methylated cirDNA in liquid biopsy.

A likelihood-based deconvolution of bulk gene expression data using single-cell references

Direct comparison of bulk gene expression profiles is complicated by distinct cell type mixtures in each sample which obscure whether observed differences are actually due to changes in expression levels themselves or simply due to differing cell type compositions. Single-cell technology has made it possible to measure gene expression in individual cells, achieving higher resolution at the expense of increased noise. If carefully incorporated, such single-cell data can be used to deconvolve bulk samples to yield accurate estimates of the true cell type proportions, thus enabling one to disentangle the effects of differential expression and cell type mixtures. Here, we propose a generative model and a likelihood-based inference method that uses asymptotic statistical theory and a novel optimization procedure to perform deconvolution of bulk RNA-seq data to produce accurate cell type proportion estimates. We demonstrate the effectiveness of our method, called RNA-Sieve, across a diverse array of scenarios involving real data and discuss extensions made uniquely possible by our probabilistic framework, including a demonstration of well-calibrated confidence intervals.

Identification of epigenetic memory candidates associated with gestational age at birth through analysis of methylome and transcriptional data

Preterm birth is known to be associated with chronic disease risk in adulthood whereby epigenetic memory may play a mechanistic role in disease susceptibility. Gestational age (GA) is the most important prognostic factor for preterm infants, and numerous DNA methylation alterations associated with GA have been revealed by epigenome-wide association studies. However, in human preterm infants, whether the methylation changes relate to transcription in the fetal state and persist after birth remains to be elucidated. Here, we identified 461 transcripts associated with GA (range 23-41 weeks) and 2093 candidate CpG sites for GA-involved epigenetic memory through analysis of methylome (110 cord blood and 47 postnatal blood) and transcriptional data (55 cord blood). Moreover, we discovered the trends of chromatin state, such as polycomb-binding, among these candidate sites. Fifty-four memory candidate sites showed correlation between methylation and transcription, and the representative corresponding gene was UCN, which encodes urocortin.

An epigenome-wide association study identifies multiple DNA methylation markers of exposure to endocrine disruptors

BACKGROUND

Exposure to environmental endocrine disrupting chemicals (EDCs) may play an important role in the epidemic of metabolic diseases. Epigenetic alterations may functionally link EDCs with gene expression and metabolic traits.

OBJECTIVES

We aimed to evaluate metabolic-related effects of the exposure to endocrine disruptors including five parabens, three bisphenols, and 13 metabolites of nine phthalates as measured in 24-hour urine on epigenome-wide DNA methylation.

METHODS

A blood-based epigenome-wide association study was performed in 622 participants from the Lifelines DEEP cohort using Illumina Infinium HumanMethylation450 methylation data and EDC excretions in 24-hour urine. Out of the 21 EDCs, 13 compounds were detected in >75% of the samples and, together with bisphenol F, were included in these analyses. Furthermore, we explored the putative function of identified methylation markers and their correlations with metabolic traits.

RESULTS

We found 20 differentially methylated cytosine-phosphate-guanines (CpGs) associated with 10 EDCs at suggestive p-value < 1 × 10^-6, of which four, associated with MEHP and MEHHP, were genome-wide significant (Bonferroni-corrected p-value < 1.19 × 10^-7). Nine out of 20 CpGs were significantly associated with at least one of the tested metabolic traits, such as fasting glucose, glycated hemoglobin, blood lipids, and/or blood pressure. 18 out of 20 EDC-associated CpGs were annotated to genes functionally related to metabolic syndrome, hypertension, obesity, type 2 diabetes, insulin resistance and glycemic traits.

CONCLUSIONS

The identified DNA methylation markers for exposure to the most common EDCs provide suggestive mechanism underlying the contributions of EDCs to metabolic health. Follow-up studies are needed to unravel the causality of EDC-induced methylation changes in metabolic alterations.

DNA Methylation Analysis Identifies Differentially Methylated Sites Associated with Early-Onset Intracranial Atherosclerotic Stenosis

Aim: Studies have suggested that genetic and environmental factors do not account for all risks and mechanisms of intracranial atherosclerotic stenosis (ICAS). DNA methylation may play a role in the progression of ICAS.

Methods: DNA methylation profiles of peripheral blood leucocytes from 7 patients with early-onset ICAS and 7 perfectly matched controls were interrogated for the first time using the Illumina Infinium Human MethylationEPIC BeadChip. Afterward, functional analysis for differentially methylated genes was conducted. In addition, pyrosequencing verification was performed in an independent cohort comprising 21 patients with earlyonset ICAS and 21 age- and gender-matched controls.

Results: A total of 318 cytosine-phosphate-guanine sites were found to be differentially methylated based on the established standards. Functional analysis annotated differentially methylated sites to atherosclerosis-related processes and pathways, such as the negative regulation of hydrolase activity (GO 0051346), type II diabetes mellitus (KEGG hsa04930), and the insulin signaling pathway (KEGG hsa04910). In addition, a differentially methylated site was also validated, cg22443212 in gene Rnf213, which showed significant hypermethylation in patients with early-onset ICAS compared with controls 59.56% (49.77%, 88.55%) vs. 44.65% (25.07%, 53.21%), respectively; P = 0.010). Receiver operating characteristic curve analysis showed that the area under the curve value of cg22443212 was 0.744 (95% confidence interval, 0.586–0.866; P = 0.002).

Conclusions: We revealed that altered DNA methylation may play a role in the occurrence and development of ICAS. These results provided new epigenetic insights into ICAS.

Genome analyses for the Tohoku Medical Megabank Project towards establishment of personalized healthcare

Personalized healthcare (PHC) based on an individual's genetic make-up is one of the most advanced, yet feasible, forms of medical care. The Tohoku Medical Megabank (TMM) Project aims to combine population genomics, medical genetics and prospective cohort studies to develop a critical infrastructure for the establishment of PHC. To date, a TMM CommCohort (adult general population) and a TMM BirThree Cohort (birth+three-generation families) have conducted recruitments and baseline surveys. Genome analyses as part of the TMM Project will aid in the development of a high-fidelity whole-genome Japanese reference panel, in designing custom single-nucleotide polymorphism (SNP) arrays specific to Japanese, and in estimation of the biological significance of genetic variations through linked investigations of the cohorts. Whole-genome sequencing from >3,500 unrelated Japanese and establishment of a Japanese reference genome sequence from long-read data have been done. We next aim to obtain genotype data for all TMM cohort participants (>150,000) using our custom SNP arrays. These data will help identify disease-associated genomic signatures in the Japanese population, while genomic data from TMM BirThree Cohort participants will be used to improve the reference genome panel. Follow-up of the cohort participants will allow us to test the genetic markers and, consequently, contribute to the realization of PHC.

DNA methylome profiling of all-cause mortality in comparison with age-associated methylation patterns

Background

Multiple epigenome-wide association studies have been performed to identify DNA methylation patterns regulated by aging or correlated with risk of death. However, the inter-relatedness of the epigenetic basis of aging and mortality has not been well investigated.

Methods

Using genome-wide DNA methylation data from the Lothian Birth Cohorts, we conducted a genome-wide association analysis of all-cause mortality and compared this with age-associated methylation patterns reported on the same samples.

Results

Survival analysis using the Cox regression model identified 2552 CpG sites with genome-wide significance (false discovery rate < 0.05) for all-cause mortality. CpGs whose methylation levels are associated with increased mortality appear more distributed from the gene body to the intergenic regions whereas CpGs whose methylation levels are associated with decreased mortality is more concentrated at the promoter regions. In comparison with reported CpGs displaying significant age-dependent methylation patterns in the same samples, we observed a limited but highly significant overlap between mortality-associated and age-associated CpGs (p value 2.52e−06). Most importantly, the overlapping CpGs are dominated by those whose overall age-related methylation patterns reduce the risk of death.

Conclusion

All-cause mortality is significantly associated with altered methylation at multiple genomic sites with differential distribution in gene regions for CpGs correlated with increased or decreased risk of death. The age-dependent methylation changes could reflect an active response to the aging process that contributes to maintain individual survival.

Electronic supplementary material

The online version of this article (10.1186/s13148-019-0622-4) contains supplementary material, which is available to authorized users.

Exploring the influence from whole blood DNA extraction methods on Infinium 450K DNA methylation

Genome-wide DNA methylation studies are becoming increasingly important in unraveling the epigenetic basis of cell biology, aging and human conditions. The aim of the present study was to explore whether different methods for extracting DNA from whole blood can affect DNA methylation outcome, potentially confounding DNA methylation studies. DNA was isolated from healthy blood donors (n = 10) using three different extraction methods (i.e. two automatic extractions methods based on magnetic beads or isopropanol precipitation, and manual organic extraction). DNA methylation was analyzed using the Infinium HumanMethylation450 Bead Chip (Infinium 450K) (n = 30 samples in total), which is a frequently used method in genome-wide DNA methylation analyses. Overall, the different extraction methods did not have a significant impact on the global DNA methylation patterns. However, DNA methylation differences between organic extraction and each of the automated methods were in general larger than differences between the two automated extraction methods. No CpG sites or regions reached genome-wide significance when testing for differential methylation between extraction methods. Although this study is based on a small sample, these results suggest that extraction method is unlikely to confound Infinium 450K methylation analysis in whole blood.

DNA Methylation Predicts the Response of Triple-Negative Breast Cancers to All-Trans Retinoic Acid

All-trans retinoic acid (atRA) regulates gene expression and is used to treat acute promyelocytic leukemia. Attempts to use atRA in breast cancer without a stratification strategy have resulted in limited overall effectiveness. To identify biomarkers for the treatment of triple-negative breast cancer (TNBC) with atRA, we characterized the effects of atRA on the tumor growth of 13 TNBC cell lines. This resulted in a range of effects that was not predictable based on previously hypothesized predictors of response, such as the levels of atRA nuclear shuttling proteins fatty acid binding protein 5 (FABP5) and cellular retinoic acid binding protein 2 (CRABP2). Transcriptional profiling revealed that atRA induced distinct gene expression changes in the sensitive versus resistant cell lines that were mostly independent of the presence of retinoic acid response elements (RAREs) or peroxisome proliferator response elements (PPREs). Given the importance of DNA methylation in regulating gene expression, we hypothesized that differential DNA methylation could predict the response of TNBCs to atRA. We identified over 1400 sites that were differentially methylated between atRA resistant and sensitive cell lines. These CpG sites predicted the response of four TNBC patient-derived xenografts to atRA, and we utilized these xenografts to refine the profile and identified that as many as 17% of TNBC patients could benefit from atRA treatment. These data illustrate that differential methylation of specific CpGs may be useful biomarkers for predicting the response of patient tumors to atRA treatment.

Letter to the editor: blood processing and sample storage have negligible effects on methylation

DNA methylation is a dynamic epigenetic mechanism. Researchers aiming to assess archived DNA samples are expressing concern about the effect of technical factors on methylation, as this may confound results. We reviewed recent reports examining this issue in blood samples and concluded that variation in collection, storage, and processing of blood DNA confers negligible effects on both global methylation and methylation status of specific genes. These results are concordant with studies that have investigated the effect of sample storage and processing on methylation in other tissues, such as tumour, sperm, and placenta samples.

DNA-Methylation and Body Composition in Preschool Children: Epigenome-Wide-Analysis in the European Childhood Obesity Project (CHOP)-Study

Adiposity and obesity result from the interaction of genetic variation and environmental factors from very early in life, possibly mediated by epigenetic processes. Few Epigenome-Wide-Association-Studies have identified DNA-methylation (DNAm) signatures associated with BMI and body composition in children. Body composition by Bio-Impedance-Analysis and genome-wide DNAm in whole blood were assessed in 374 pre-school children from four European countries. Associations were tested by linear regression adjusted for sex, age, centre, education, 6 WBC-proportions according to Houseman and 30 principal components derived from control probes. Specific DNAm variants were identified to be associated with BMI (212), fat-mass (230), fat-free-mass (120), fat-mass-index (24) and fat-free-mass-index (15). Probes in genes SNED1(IRE-BP1), KLHL6, WDR51A(POC1A), CYTH4-ELFN2, CFLAR, PRDM14, SOS1, ZNF643(ZFP69B), ST6GAL1, C3orf70, CILP2, MLLT4 and ncRNA LOC101929268 remained significantly associated after Bonferroni-correction of P-values. We provide novel evidence linking DNAm with (i) altered lipid and glucose metabolism, (ii) diabetes and (iii) body size and composition in children. Both common and specific epigenetic signatures among measures were also revealed. The causal direction with phenotypic measures and stability of DNAm variants throughout the life course remains unclear and longitudinal analysis in other populations is required. These findings give support for potential epigenetic programming of body composition and obesity.

Impact of Preanalytical Variations in Blood-Derived Biospecimens on Omics Studies: Toward Precision Biobanking?

Research data and outcomes do vary across populations and persons, but this is not always due to experimental or true biological variation. Preanalytical components of experiments, be they biospecimen acquisition, preparation, storage, or transportation to the laboratory, may all contribute to apparent variability in research data, outcomes, and interpretation. The present review article and biobanking innovation analysis offer new insights with a summary of such preanalytical variables, for example, the type of blood collection tube, centrifugation conditions, long-term sample storage temperature, and duration, on output of omics analyses of blood-derived biospecimens: whole blood, serum, plasma, buffy coat, and peripheral blood mononuclear cells. Furthermore, we draw parallels from the field of precision medicine in this study, with a view to the future of "precision biobanking" wherein such preanalytical variations are carefully taken into consideration so as to minimize their influence on outcomes of omics data, analyses, and sensemaking, particularly in clinical omics applications. We underscore the need for using broadly framed, critical, independent, social and political science, and humanities research so as to understand the multiple possible future trajectories of, and the motivations and values embedded in, precision biobanking that is increasingly relevant in the current age of Big Data.

Epigenome-wide association of myocardial infarction with DNA methylation sites at loci related to cardiovascular disease

Background

Development of cardiovascular disease (CVD), including coronary artery disease, arrhythmia, and ischemic stroke, depends on environmental and genetic factors. To investigate the epigenetic basis of myocardial infarction (MI), we performed an epigenome-wide association study for this condition in elderly Japanese subjects. A total of 192 case subjects with MI and 192 control subjects were recruited from hospital attendees and the general population, respectively. Genome-wide DNA methylation (DNAm) profiles for DNA isolated from whole blood were obtained by analysis with an Infinium HumanMethylation450 BeadChip. The relation of DNAm sites found to be significantly associated with MI to nearby single nucleotide polymorphisms (SNPs) previously shown to be associated with CVD was assessed in the control group.

Findings

Three DNAm sites (cg06642177, cg07786668, cg17218495) showed genome-wide significant associations with MI (p = 4.33 × 10⁻⁸, 3.96 × 10⁻¹⁰, and 3.77 × 10⁻⁸, respectively). Two of these sites (cg07786668, cg17218495) still showed such associations after adjustment for classical risk factors of MI (p = 1.04 × 10⁻⁷ and 6.60 × 10⁻⁸, respectively). The DNAm sites cg07786668 and cg17218495 are located in ZFHX3 (zinc finger homeobox 3) and SMARCA4 (SWI/SNF-related, matrix-associated, actin-dependent regulator of chromatin, subfamily a, member 4) genes, respectively. SNPs in ZFHX3 or SMARCA4 that were previously found to be associated with CVD were not significantly associated with these DNAm sites in our control subjects.

Conclusions

We identified two DNAm sites—cg07786668 in ZFHX3 and cg17218495 in SMARCA4— that are independently and significantly associated with MI. Our results suggest that the development of MI might be influenced by changes in DNAm at these sites via a pathway that differs from that affected by CVD-associated SNPs in these genes.

The Kita-Nagoya Genomic Epidemiology (KING) study, which was the source of control samples in the present study, was registered in ClinicalTrials.gov (NCT00262691) on 6 December 2005.

Genome-wide identification of inter-individually variable DNA methylation sites improves the efficacy of epigenetic association studies

Epigenome-wide association studies, which searches for blood-based DNA methylation signatures associated with environmental exposures and/or disease susceptibilities, is a promising approach to a better understanding of the molecular aetiology of common diseases. To carry out large-scale epigenome-wide association studies while avoiding false negative detection, an efficient strategy to determine target CpG sites for microarray-based or sequencing-based DNA methylation profiling is essentially needed. Here, we propose and validate a hypothesis that a strategy focusing on CpG sites with high DNA methylation level variability may attain an improved efficacy. Through whole-genome bisulfite sequencing of purified blood cells collected from > 100 apparently healthy subjects, we identified ~2.0 million inter-individually variable CpG sites as potential targets. The efficacy of our strategy was estimated to be 3.7-fold higher than that of the most frequently used strategy. Our catalogue of inter-individually variable CpG sites will accelerate the discovery of clinically relevant DNA methylation biomarkers in future epigenome-wide association studies.

Intraindividual dynamics of transcriptome and genome-wide stability of DNA methylation

Cytosine methylation at CpG dinucleotides is an epigenetic mechanism that affects the gene expression profiles responsible for the functional differences in various cells and tissues. Although gene expression patterns are dynamically altered in response to various stimuli, the intraindividual dynamics of DNA methylation in human cells are yet to be fully understood. Here, we investigated the extent to which DNA methylation contributes to the dynamics of gene expression by collecting 24 blood samples from two individuals over a period of 3 months. Transcriptome and methylome association analyses revealed that only ~2% of dynamic changes in gene expression could be explained by the intraindividual variation of DNA methylation levels in peripheral blood mononuclear cells and purified monocytes. These results showed that DNA methylation levels remain stable for at least several months, suggesting that disease-associated DNA methylation markers are useful for estimating the risk of disease manifestation.