Genome-wide signatures of differential DNA methylation in pediatric acute lymphoblastic leukemia

Background

Although aberrant DNA methylation has been observed previously in acute lymphoblastic leukemia (ALL), the patterns of differential methylation have not been comprehensively determined in all subtypes of ALL on a genome-wide scale. The relationship between DNA methylation, cytogenetic background, drug resistance and relapse in ALL is poorly understood.

Results

We surveyed the DNA methylation levels of 435,941 CpG sites in samples from 764 children at diagnosis of ALL and from 27 children at relapse. This survey uncovered four characteristic methylation signatures. First, compared with control blood cells, the methylomes of ALL cells shared 9,406 predominantly hypermethylated CpG sites, independent of cytogenetic background. Second, each cytogenetic subtype of ALL displayed a unique set of hyper- and hypomethylated CpG sites. The CpG sites that constituted these two signatures differed in their functional genomic enrichment to regions with marks of active or repressed chromatin. Third, we identified subtype-specific differential methylation in promoter and enhancer regions that were strongly correlated with gene expression. Fourth, a set of 6,612 CpG sites was predominantly hypermethylated in ALL cells at relapse, compared with matched samples at diagnosis. Analysis of relapse-free survival identified CpG sites with subtype-specific differential methylation that divided the patients into different risk groups, depending on their methylation status.

Conclusions

Our results suggest an important biological role for DNA methylation in the differences between ALL subtypes and in their clinical outcome after treatment.     

Orthology between genomes of Brachypodium, wheat and rice

Background

Differential expression of perforin (PRF1), a gene with a pivotal role in immune surveillance, can be attributed to differential methylation of CpG sites in its promoter region. A reproducible method for quantitative and CpG site-specific determination of perforin methylation is required for molecular epidemiologic studies of chronic diseases with immune dysfunction.

Findings

We developed a pyrosequencing based method to quantify site-specific methylation levels in 32 out of 34 CpG sites in the PRF1 promoter, and also compared methylation pattern in DNAs extracted from whole blood drawn into PAXgene blood DNA tubes (whole blood DNA) or DNA extracted from peripheral blood mononuclear cells (PBMC DNA) from the same normal subjects. Sodium bisulfite treatment of DNA and touchdown PCR were highly reproducible (coefficient of variation 1.63 to 2.18%) to preserve methylation information. Application of optimized pyrosequencing protocol to whole blood DNA revealed that methylation level varied along the promoter in normal subjects with extremely high methylation (mean 86%; range 82–92%) in the distal enhancer region (CpG sites 1–10), a variable methylation (range 49%–83%) in the methylation sensitive region (CpG sites 11–17), and a progressively declining methylation level (range 12%–80%) in the proximal promoter region (CpG sites 18–32) of PRF1. This pattern of methylation remained the same between whole blood and PBMC DNAs, but the absolute values of methylation in 30 out of 32 CpG sites differed significantly, with higher values for all CpG sites in the whole blood DNA.

Conclusion

This reproducible, site-specific and quantitative method for methylation determination of PRF1 based on pyrosequencing without cloning is well suited for large-scale molecular epidemiologic studies of diseases with immune dysfunction. PBMC DNA may be better suited than whole blood DNA for examining methylation levels in genes associated with immune function.     

The prognostic significance of whole blood global and specific DNA methylation levels in gastric adenocarcinoma

Background

Epigenetics, particularly DNA methylation, has recently been elucidated as important in gastric cancer (GC) initiation and progression. We investigated the clinical and prognostic importance of whole blood global and site-specific DNA methylation in GC.

Methods

Genomic DNA was extracted from the peripheral blood of 105 Omani GC patients at diagnosis. DNA methylation was quantified by pyrosequencing of global DNA and specific gene promoter regions at 5 CpG sites for CDH1, 7 CpG sites for p16, 4 CpG sites for p53, and 3 CpG sites for RUNX3. DNA methylation levels in patients were categorized into low, medium, and high tertiles. Associations between methylation level category and clinicopathological features were evaluated using χ² tests. Survival analyses were carried out using the Kaplan-Meier method and log rank test. A backward conditional Cox proportional hazards regression model was used to identify independent predictors of survival.

Results

Older GC patients had increased methylation levels at specific CpG sites within the CDH1, p53, and RUNX-3 promoters. Male gender was significantly associated with reduced global and increased site-specific DNA methylation levels in CDH1, p16, and p53 promoters. Global DNA low methylation level was associated with better survival on univariate analysis. Patients with high and medium methylation vs. low methylation levels across p16 promoter CpG sites, site 2 in particular, had better survival. Multivariate analysis showed that global DNA hypermethylation was a significant independent predictor of worse survival (hazard ratio (HR) = 2.0, 95% CI: 1.1–3.8; p = 0.02) and high methylation mean values across p16 promoter sites 1–7 were associated with better survival with HR of 0.3 (95% CI, 0.1–0.8; p = 0.02) respectively.

Conclusions

Analysis of global and site-specific DNA methylation in peripheral blood by pyrosequencing provides quantitative DNA methylation values that may serve as important prognostic indicators.     

Non-Steroidal Anti-Inflammatory Drug Use and Genomic DNA Methylation in Blood

Background

Non-steroidal anti-inflammatory drug (NSAID) use is associated with decreased risk of some cancers. NSAID use modulates the epigenetic profile of normal colonic epithelium and may reduce risk of colon cancer through this pathway; however, the effect of NSAID use on the DNA methylation profile of other tissues including whole blood has not yet been examined.

Findings

Using the Sister Study cohort, we examined the association between NSAID usage and whole genome methylation patterns in blood DNA. Blood DNA methylation status across 27,589 CpG sites was evaluated for 871 women using the Illumina Infinium HumanMethylation27 Beadchip, and in a non-overlapping replication sample of 187 women at 485,512 CpG sites using the Infinium HumanMethylation450 Beadchip. We identified a number of CpG sites that were differentially methylated in regular, long-term users of NSAIDs in the discovery group, but none of these sites were statistically significant in our replication group.

Conclusions

We found no replicable methylation differences in blood related to NSAID usage. If NSAID use does effect blood DNA methylation patterns, differences are likely small.     

Meta-analysis of human methylation data for evidence of sex-specific autosomal patterns

Background

Several individual studies have suggested that autosomal CpG methylation differs by sex both in terms of individual CpG sites and global autosomal CpG methylation. However, these findings have been inconsistent and plagued by spurious associations due to the cross reactivity of CpG probes on commercial microarrays. We collectively analysed 76 published studies (n = 6,795) for sex-associated differences in both autosomal and sex chromosome CpG sites.

Results

Overall autosomal methylation profiles varied substantially by study, and we encountered substantial batch effects. We accounted for these by conducting random effects meta-analysis for individual autosomal CpG methylation associations. After excluding non-specific probes, we found 184 autosomal CpG sites differentially methylated by sex after correction for multiple testing. In line with previous studies, average beta differences were small. Many of the most significantly associated CpG probes were new. Of note was differential CpG methylation in the promoters of genes thought to be involved in spermatogenesis and male fertility, such as SLC9A2, SPESP1, CRISP2, and NUPL1. Pathway analysis revealed overrepresentation of genes differentially methylated by sex in several broad Gene Ontology biological processes, including RNA splicing and DNA repair.

Conclusions

This study represents a comprehensive analysis of sex-specific methylation patterns. We demonstrate the existence of sex-specific methylation profiles and report a large number of novel DNA methylation differences in autosomal CpG sites between sexes.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-981) contains supplementary material, which is available to authorized users.     

BISMA - Fast and accurate bisulfite sequencing data analysis of individual clones from unique and repetitive sequences

Background  

Bisulfite sequencing is a popular method to analyze DNA methylation patterns at high resolution. A region of interest is targeted by PCR and about 20-50 subcloned DNA molecules are usually analyzed, to determine the methylation status at single CpG sites and molecule resolution.     

Incorporating methylation genome information improves prediction accuracy for drug treatment responses

Background

An accumulation of evidence has revealed the important role of epigenetic factors in explaining the etiopathogenesis of human diseases. Several empirical studies have successfully incorporated methylation data into models for disease prediction. However, it is still a challenge to integrate different types of omics data into prediction models, and the contribution of methylation information to prediction remains to be fully clarified.

Results

A stratified drug-response prediction model was built based on an artificial neural network to predict the change in the circulating triglyceride level after fenofibrate intervention. Associated single-nucleotide polymorphisms (SNPs), methylation of selected cytosine-phosphate-guanine (CpG) sites, age, sex, and smoking status, were included as predictors. The model with selected SNPs achieved a mean 5-fold cross-validation prediction error rate of 43.65%. After adding methylation information into the model, the error rate dropped to 41.92%. The combination of significant SNPs, CpG sites, age, sex, and smoking status, achieved the lowest prediction error rate of 41.54%.

Conclusions

Compared to using SNP data only, adding methylation data in prediction models slightly improved the error rate; further prediction error reduction is achieved by a combination of genome, methylation genome, and environmental factors.

     

DNA Methylation Profiles of Airway Epithelial Cells and PBMCs from Healthy, Atopic and Asthmatic Children

Background

Allergic inflammation is commonly observed in a number of conditions that are associated with atopy including asthma, eczema and rhinitis. However, the genetic, environmental or epigenetic factors involved in these conditions are likely to be different. Epigenetic modifications, such as DNA methylation, can be influenced by the environment and result in changes to gene expression.

Objectives

To characterize the DNA methylation pattern of airway epithelial cells (AECs) compared to peripheral blood mononuclear cells (PBMCs) and to discern differences in methylation within each cell type amongst healthy, atopic and asthmatic subjects.

Methods

PBMCs and AECs from bronchial brushings were obtained from children undergoing elective surgery for non-respiratory conditions. The children were categorized as atopic, atopic asthmatic, non-atopic asthmatic or healthy controls. Extracted DNA was bisulfite treated and 1505 CpG loci across 807 genes were analyzed using the Illumina GoldenGate Methylation Cancer Panel I. Gene expression for a subset of genes was performed using RT-PCR.

Results

We demonstrate a signature set of CpG sites that are differentially methylated in AECs as compared to PBMCs regardless of disease phenotype. Of these, 13 CpG sites were specific to healthy controls, 8 sites were only found in atopics, and 6 CpGs were unique to asthmatics. We found no differences in the methylation status of PBMCs between disease phenotypes. In AECs derived from asthmatics compared to atopics, 8 differentially methylated sites were identified including CpGs in STAT5A and CRIP1. We demonstrate STAT5A gene expression is decreased whereas CRIP1 gene expression is elevated in the AECs from asthmatic compared to both healthy and atopic subjects.

Discussion

We characterized a cell specific DNA methylation signature for AECs compared to PBMCs regardless of asthmatic or atopic status. Our data highlight the importance of understanding DNA methylation in the epithelium when studying the epithelial contribution to asthma.     

Evaluation of microarray-based DNA methylation measurement using technical replicates: the Atherosclerosis Risk In Communities (ARIC) Study

Background

DNA methylation is a widely studied epigenetic phenomenon; alterations in methylation patterns influence human phenotypes and risk of disease. As part of the Atherosclerosis Risk in Communities (ARIC) study, the Illumina Infinium HumanMethylation450 (HM450) BeadChip was used to measure DNA methylation in peripheral blood obtained from ~3000 African American study participants. Over 480,000 cytosine-guanine (CpG) dinucleotide sites were surveyed on the HM450 BeadChip. To evaluate the impact of technical variation, 265 technical replicates from 130 participants were included in the study.

Results

For each CpG site, we calculated the intraclass correlation coefficient (ICC) to compare variation of methylation levels within- and between-replicate pairs, ranging between 0 and 1. We modeled the distribution of ICC as a mixture of censored or truncated normal and normal distributions using an EM algorithm. The CpG sites were clustered into low- and high-reliability groups, according to the calculated posterior probabilities. We also demonstrated the performance of this clustering when applied to a study of association between methylation levels and smoking status of individuals. For the CpG sites showing genome-wide significant association with smoking status, most (~96%) were seen from sites in the high reliability cluster.

Conclusions

We suggest that CpG sites with low ICC may be excluded from subsequent association analyses, or extra caution needs to be taken for associations at such sites.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2105-15-312) contains supplementary material, which is available to authorized users.     

Methylated site display (MSD)-AFLP,a sensitive and affordable method for analysis of CpG methylation profiles

Background

It has been pointed out that environmental factors or chemicals can cause diseases that are developmental in origin. To detect abnormal epigenetic alterations in DNA methylation, convenient and cost-effective methods are required for such research, in which multiple samples are processed simultaneously. We here present methylated site display (MSD), a unique technique for the preparation of DNA libraries. By combining it with amplified fragment length polymorphism (AFLP) analysis, we developed a new method, MSD-AFLP.

Results

Methylated site display libraries consist of only DNAs derived from DNA fragments that are CpG methylated at the 5′ end in the original genomic DNA sample. To test the effectiveness of this method, CpG methylation levels in liver, kidney, and hippocampal tissues of mice were compared to examine if MSD-AFLP can detect subtle differences in the levels of tissue-specific differentially methylated CpGs. As a result, many CpG sites suspected to be tissue-specific differentially methylated were detected. Nucleotide sequences adjacent to these methyl-CpG sites were identified and we determined the methylation level by methylation-sensitive restriction endonuclease (MSRE)-PCR analysis to confirm the accuracy of AFLP analysis. The differences of the methylation level among tissues were almost identical among these methods. By MSD-AFLP analysis, we detected many CpGs showing less than 5% statistically significant tissue-specific difference and less than 10% degree of variability. Additionally, MSD-AFLP analysis could be used to identify CpG methylation sites in other organisms including humans.

Conclusion

MSD-AFLP analysis can potentially be used to measure slight changes in CpG methylation level. Regarding the remarkable precision, sensitivity, and throughput of MSD-AFLP analysis studies, this method will be advantageous in a variety of epigenetics-based research.

     

A comparative analysis of DNA methylation across human embryonic stem cell lines

Background  

We performed a comparative analysis of the genome-wide DNA methylation profiles from three human embryonic stem cell (HESC) lines. It had previously been shown that HESC lines had significantly higher non-CG methylation than differentiated cells, and we therefore asked whether these sites were conserved across cell lines.     

Kidney Dysfunction in Adult Offspring Exposed In Utero to Type 1 Diabetes Is Associated with Alterations in Genome-Wide DNA Methylation

Background

Fetal exposure to hyperglycemia impacts negatively kidney development and function.

Objective

Our objective was to determine whether fetal exposure to moderate hyperglycemia is associated with epigenetic alterations in DNA methylation in peripheral blood cells and whether those alterations are related to impaired kidney function in adult offspring.

Design

Twenty nine adult, non-diabetic offspring of mothers with type 1 diabetes (T1D) (case group) were matched with 28 offspring of T1D fathers (control group) for the study of their leukocyte genome-wide DNA methylation profile (27,578 CpG sites, Human Methylation 27 BeadChip, Illumina Infinium). In a subset of 19 cases and 18 controls, we assessed renal vascular development by measuring Glomerular Filtration Rate (GFR) and Effective Renal Plasma Flow (ERPF) at baseline and during vasodilatation produced by amino acid infusion.

Results

Globally, DNA was under-methylated in cases vs. controls. Among the 87 CpG sites differently methylated, 74 sites were less methylated and 13 sites more methylated in cases vs. controls. None of these CpG sites were located on a gene known to be directly involved in kidney development and/or function. However, the gene encoding DNA methyltransferase 1 (DNMT1)—a key enzyme involved in gene expression during early development–was under-methylated in cases. The average methylation of the 74 under-methylated sites differently correlated with GFR in cases and controls.

Conclusion

Alterations in methylation profile imprinted by the hyperglycemic milieu of T1D mothers during fetal development may impact kidney function in adult offspring. The involved pathways seem to be a nonspecific imprinting process rather than specific to kidney development or function.     

Substitution rate variation at human CpG sites correlates with non-CpG divergence,methylation level and GC content

Background  

A major goal in the study of molecular evolution is to unravel the mechanisms that induce variation in the germ line mutation rate and in the genome-wide mutation profile. The rate of germ line mutation is considerably higher for cytosines at CpG sites than for any other nucleotide in the human genome, an increase commonly attributed to cytosine methylation at CpG sites. The CpG mutation rate, however, is not uniform across the genome and, as methylation levels have recently been shown to vary throughout the genome, it has been hypothesized that methylation status may govern variation in the rate of CpG mutation.     

Improved reduced representation bisulfite sequencing for epigenomic profiling of clinical samples

Background

DNA methylation plays crucial roles in epigenetic gene regulation in normal development and disease pathogenesis. Efficient and accurate quantification of DNA methylation at single base resolution can greatly advance the knowledge of disease mechanisms and be used to identify potential biomarkers. We developed an improved pipeline based on reduced representation bisulfite sequencing (RRBS) for cost-effective genome-wide quantification of DNA methylation at single base resolution. A selection of two restriction enzymes (Taq^αI and MspI) enables a more unbiased coverage of genomic regions of different CpG densities. We further developed a highly automated software package to analyze bisulfite sequencing results from the Solexa GAIIx system.

Results

With two sequencing lanes, we were able to quantify ~1.8 million individual CpG sites at a minimum sequencing depth of 10. Overall, about 76.7% of CpG islands, 54.9% of CpG island shores and 52.2% of core promoters in the human genome were covered with at least 3 CpG sites per region.

Conclusions

With this new pipeline, it is now possible to perform whole-genome DNA methylation analysis at single base resolution for a large number of samples for understanding how DNA methylation and its changes are involved in development, differentiation, and disease pathogenesis.     

Quality control for Illumina 450K methylation data in the absence of iDat files using correlation structure in pedigrees and repeated measures

Background

An important feature in many genomic studies is quality control and normalization. This is particularly important when analyzing epigenetic data, where the process of obtaining measurements can be bias prone. The GAW20 data was from the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN), a study with multigeneration families, where DNA cytosine-phosphate-guanine (CpG) methylation was measured pre- and posttreatment with fenofibrate. We performed quality control assessment of the GAW20 DNA methylation data, including normalization, assessment of batch effects and detection of sample swaps.

Results

We show that even after normalization, the GOLDN methylation data has systematic differences pre- and posttreatment. Through investigation of (a) CpGs sites containing a single nucleotide polymorphism, (b) the stability of breeding values for methylation across time points, and (c) autosomal gender-associated CpGs, 13 sample swaps were detected, 11 of which were posttreatment.

Conclusions

This paper demonstrates several ways to perform quality control of methylation data in the absence of raw data files and highlights the importance of normalization and quality control of the GAW20 methylation data from the GOLDN study.

     

Performance of Different Analytical Software Packages in Quantification of DNA Methylation by Pyrosequencing

Background

Pyrosequencing has emerged as an alternative method of nucleic acid sequencing, well suited for many applications which aim to characterize single nucleotide polymorphisms, mutations, microbial types and CpG methylation in the target DNA. The commercially available pyrosequencing systems can harbor two different types of software which allow analysis in AQ or CpG mode, respectively, both widely employed for DNA methylation analysis.

Objective

Aim of the study was to assess the performance for DNA methylation analysis at CpG sites of the two pyrosequencing software which allow analysis in AQ or CpG mode, respectively. Despite CpG mode having been specifically generated for CpG methylation quantification, many investigations on this topic have been carried out with AQ mode. As proof of equivalent performance of the two software for this type of analysis is not available, the focus of this paper was to evaluate if the two modes currently used for CpG methylation assessment by pyrosequencing may give overlapping results.

Methods

We compared the performance of the two software in quantifying DNA methylation in the promoter of selected genes (GSTP1, MGMT, LINE-1) by testing two case series which include DNA from paraffin embedded prostate cancer tissues (PC study, N = 36) and DNA from blood fractions of healthy people (DD study, N = 28), respectively.

Results

We found discrepancy in the two pyrosequencing software-based quality assignment of DNA methylation assays. Compared to the software for analysis in the AQ mode, less permissive criteria are supported by the Pyro Q-CpG software, which enables analysis in CpG mode. CpG mode warns the operators about potential unsatisfactory performance of the assay and ensures a more accurate quantitative evaluation of DNA methylation at CpG sites.

Conclusion

The implementation of CpG mode is strongly advisable in order to improve the reliability of the methylation analysis results achievable by pyrosequencing.