Heterogeneity in White Blood Cells Has Potential to Confound DNA Methylation Measurements

Epigenetic studies are commonly conducted on DNA from tissue samples. However, tissues are ensembles of cells that may each have their own epigenetic profile, and therefore inter-individual cellular heterogeneity may compromise these studies. Here, we explore the potential for such confounding on DNA methylation measurement outcomes when using DNA from whole blood. DNA methylation was measured using pyrosequencing-based methodology in whole blood (n = 50–179) and in two white blood cell fractions (n = 20), isolated using density gradient centrifugation, in four CGIs (CpG Islands) located in genes HHEX (10 CpG sites assayed), KCNJ11 (8 CpGs), KCNQ1 (4 CpGs) and PM20D1 (7 CpGs). Cellular heterogeneity (variation in proportional white blood cell counts of neutrophils, lymphocytes, monocytes, eosinophils and basophils, counted by an automated cell counter) explained up to 40% (p<0.0001) of the inter-individual variation in whole blood DNA methylation levels in the HHEX CGI, but not a significant proportion of the variation in the other three CGIs tested. DNA methylation levels in the two cell fractions, polymorphonuclear and mononuclear cells, differed significantly in the HHEX CGI; specifically the average absolute difference ranged between 3.4–15.7 percentage points per CpG site. In the other three CGIs tested, methylation levels in the two fractions did not differ significantly, and/or the difference was more moderate. In the examined CGIs, methylation levels were highly correlated between cell fractions. In summary, our analysis detects region-specific differential DNA methylation between white blood cell subtypes, which can confound the outcome of whole blood DNA methylation measurements. Finally, by demonstrating the high correlation between methylation levels in cell fractions, our results suggest a possibility to use a proportional number of a single white blood cell type to correct for this confounding effect in analyses.     

Functional annotation of the human brain methylome identifies tissue-specific epigenetic variation across brain and blood

Background

Dynamic changes to the epigenome play a critical role in establishing and maintaining cellular phenotype during differentiation, but little is known about the normal methylomic differences that occur between functionally distinct areas of the brain. We characterized intra- and inter-individual methylomic variation across whole blood and multiple regions of the brain from multiple donors.

Results

Distinct tissue-specific patterns of DNA methylation were identified, with a highly significant over-representation of tissue-specific differentially methylated regions (TS-DMRs) observed at intragenic CpG islands and low CG density promoters. A large proportion of TS-DMRs were located near genes that are differentially expressed across brain regions. TS-DMRs were significantly enriched near genes involved in functional pathways related to neurodevelopment and neuronal differentiation, including BDNF, BMP4, CACNA1A, CACA1AF, EOMES, NGFR, NUMBL, PCDH9, SLIT1, SLITRK1 and SHANK3. Although between-tissue variation in DNA methylation was found to greatly exceed between-individual differences within any one tissue, we found that some inter-individual variation was reflected across brain and blood, indicating that peripheral tissues may have some utility in epidemiological studies of complex neurobiological phenotypes.

Conclusions

This study reinforces the importance of DNA methylation in regulating cellular phenotype across tissues, and highlights genomic patterns of epigenetic variation across functionally distinct regions of the brain, providing a resource for the epigenetics and neuroscience research communities.     

Deep Bisulfite Sequencing of Aberrantly Methylated Loci in a Patient with Multiple Methylation Defects

NLRP7 is a maternal effect gene as maternal mutations in this gene cause recurrent hydatidiform moles, spontaneous abortions and stillbirths, whereas live births are very rare. We have studied a patient with multiple anomalies born to a mother with a heterozygous NLRP7 mutation. By array-based CpG methylation analysis of blood DNA from the patient, his parents and 18 normal controls on Illumina Infinium HumanMethylation27 BeadChips we found that the patient had methylation changes (delta ß ≥ 0.3) at many imprinted loci as well as at 87 CpGs associated with 85 genes of unknown imprinting status. Using a pseudoproband (permutation) approach, we found methylation changes at only 7-24 CpGs (mean 15; standard deviation 4.84) in the controls. Thus, the number of abberantly methylated CpGs in the patient is more than 14 standard deviations higher. In order to identify novel imprinted genes among the 85 conspicuous genes in the patient, we selected 19 (mainly hypomethylated) genes for deep bisulfite amplicon sequencing on the ROCHE/454 Genome Sequencer in the patient and at least two additional controls. These controls had not been included in the array analysis and were heterozygous for a single nucleotide polymorphism at the test locus, so that allele-specific DNA methylation patterns could be determined. Apart from FAM50B, which we proved to be imprinted in blood, we did not observe allele-specific DNA methylation at the other 18 loci. We conclude that the patient does not only have methylation defects at imprinted loci but (at least in blood) also an excess of methylation changes at apparently non-imprinted loci.     

Aging effects on DNA methylation modules in human brain and blood tissue

Background

Several recent studies reported aging effects on DNA methylation levels of individual CpG dinucleotides. But it is not yet known whether aging-related consensus modules, in the form of clusters of correlated CpG markers, can be found that are present in multiple human tissues. Such a module could facilitate the understanding of aging effects on multiple tissues.

Results

We therefore employed weighted correlation network analysis of 2,442 Illumina DNA methylation arrays from brain and blood tissues, which enabled the identification of an age-related co-methylation module. Module preservation analysis confirmed that this module can also be found in diverse independent data sets. Biological evaluation showed that module membership is associated with Polycomb group target occupancy counts, CpG island status and autosomal chromosome location. Functional enrichment analysis revealed that the aging-related consensus module comprises genes that are involved in nervous system development, neuron differentiation and neurogenesis, and that it contains promoter CpGs of genes known to be down-regulated in early Alzheimer's disease. A comparison with a standard, non-module based meta-analysis revealed that selecting CpGs based on module membership leads to significantly increased gene ontology enrichment, thus demonstrating that studying aging effects via consensus network analysis enhances the biological insights gained.

Conclusions

Overall, our analysis revealed a robustly defined age-related co-methylation module that is present in multiple human tissues, including blood and brain. We conclude that blood is a promising surrogate for brain tissue when studying the effects of age on DNA methylation profiles.     

Influence of DNMT Genotype on Global and Site Specific DNA Methylation Patterns in Neonates and Pregnant Women

This study examines the relationship between common genetic variation within DNA methyltransferase genes and inter-individual variation in DNA methylation. Eleven polymorphisms spanning DNMT1 and DNMT3B were genotyped. Global and gene specific (IGF2, IGFBP3, ZNT5) DNA methylation was quantified by LUMA and bisulfite Pyrosequencing assays, respectively, in neonatal cord blood and in maternal peripheral blood. Associations between maternal genotype and maternal methylation (n ^≈ 333), neonatal genotype and neonatal methylation (n ^≈ 454), and maternal genotype and neonatal methylation (n ^≈ 137) were assessed. The findings of this study provide some support to the hypothesis that genetic variation in DNA methylating enzymes influence DNA methylation at global and gene-specific levels; however observations were not robust to correction for multiple testing. More comprehensive analysis of the influence of genetic variation on global and site specific DNA methylation is warranted.     

Global Analysis of DNA Methylation Variation in Adipose Tissue from Twins Reveals Links to Disease-Associated Variants in Distal Regulatory Elements

Epigenetic modifications such as DNA methylation play a key role in gene regulation and disease susceptibility. However, little is known about the genome-wide frequency, localization, and function of methylation variation and how it is regulated by genetic and environmental factors. We utilized the Multiple Tissue Human Expression Resource (MuTHER) and generated Illumina 450K adipose methylome data from 648 twins. We found that individual CpGs had low variance and that variability was suppressed in promoters. We noted that DNA methylation variation was highly heritable (h²_median = 0.34) and that shared environmental effects correlated with metabolic phenotype-associated CpGs. Analysis of methylation quantitative-trait loci (metQTL) revealed that 28% of CpGs were associated with nearby SNPs, and when overlapping them with adipose expression quantitative-trait loci (eQTL) from the same individuals, we found that 6% of the loci played a role in regulating both gene expression and DNA methylation. These associations were bidirectional, but there were pronounced negative associations for promoter CpGs. Integration of metQTL with adipose reference epigenomes and disease associations revealed significant enrichment of metQTL overlapping metabolic-trait or disease loci in enhancers (the strongest effects were for high-density lipoprotein cholesterol and body mass index [BMI]). We followed up with the BMI SNP rs713586, a cg01884057 metQTL that overlaps an enhancer upstream of ADCY3, and used bisulphite sequencing to refine this region. Our results showed widespread population invariability yet sequence dependence on adipose DNA methylation but that incorporating maps of regulatory elements aid in linking CpG variation to gene regulation and disease risk in a tissue-dependent manner.     

Plasticity of DNA methylation in a nerve injury model of pain

The response of the peripheral nervous system (PNS) to injury may go together with alterations in epigenetics, a conjecture that has not been subjected to a comprehensive, genome-wide test. Using reduced representation bisulfite sequencing, we report widespread remodeling of DNA methylation in the rat dorsal root ganglion (DRG) occurring within 24 h of peripheral nerve ligation, a neuropathy model of allodynia. Significant (P < 10⁻⁴) cytosine hyper- and hypo-methylation was found at thousands of CpG sites. Remodeling occurred outside of CpG islands. Changes affected genes with known roles in the PNS, yet methylome remodeling also involved genes that were not linked to neuroplasticity by prior evidence. Consistent with emerging models relying on genome-wide methylation and RNA-seq analysis of promoter regions and gene bodies, variation of methylation was not tightly linked with variation of gene expression. Furthermore, approximately 44% of the dynamically changed CpGs were located outside of genes. We compared their positions with the intergenic, tissue-specific differentially methylated CpGs (tDMCs) of an independent experimental set consisting of liver, spleen, L4 control DRG, and muscle. Dynamic changes affected those intergenic CpGs that were different between tissues (P < 10⁻¹⁵) and almost never the invariant portion of the methylome (those CpGs that were identical across all tissues). Our findings—obtained in mixed tissue—show that peripheral nerve injury leads to methylome remodeling in the DRG. Future studies may address which of the cell types found in the DRG, such as specific groups of neurons or non-neuronal cells are affected by which aspect of the observed methylome remodeling.     

Interaction between Oxytocin Genotypes and Early Experience Predicts Quality of Mothering and Postpartum Mood

Individual differences in maternal behavior are affected by both early life experiences and oxytocin, but little is known about genetic variation in oxytocin genes and its effects on mothering. We examined two polymorphisms in the oxytocin peptide gene OXT (rs2740210 and rs4813627) and one polymorphism in the oxytocin receptor gene OXTR (rs237885) in 187 Caucasian mothers at six months postpartum. For OXT, both rs2740210 and rs4813627 significantly associated with maternal vocalizing to the infant. These polymorphisms also interacted with the quality of care mothers experienced in early life, to predict variation in maternal instrumental care and postpartum depression. However, postpartum depression did not mediate the gene-environment effects of the OXT SNPs on instrumental care. In contrast, the OXTR SNP rs237885 did not associate with maternal behavior, but it did associate with pre-natal (but not post-natal) depression score. The findings illustrate the importance of variation in oxytocin genes, both alone and in interaction with early environment, as predictors of individual differences in human mothering. Furthermore, depression does not appear to have a causal role on the variation we report in instrumental care. This suggests that variation in instrumental care varies in association with a gene-early environment effect regardless of current depressive symptomatology. Finally, our findings highlight the importance of examining multiple dimensions of human maternal behavior in studies of genetic associations.     

DNA methylation profiles in African American prostate cancer patients in relation to disease progression

This study examined whether differential DNA methylation is associated with clinical features of more aggressive disease at diagnosis and prostate cancer recurrence in African American men, who are more likely to die from prostate cancer than other populations. Tumor tissues from 76 African Americans diagnosed with prostate cancer who had radical prostatectomy as their primary treatment were profiled for epigenome-wide DNA methylation levels. Long-term follow-up identified 19 patients with prostate cancer recurrence. Twenty-three CpGs were differentially methylated (FDR q ≤ 0.25, mean methylation difference ≥ 0.10) in patients with vs. without recurrence, including CpGs in GCK, CDKL2, PRDM13, and ZFR2. Methylation differences were also observed between men with metastatic-lethal prostate cancer vs. no recurrence (five CpGs), regional vs. local pathological stage (two CpGs), and higher vs. lower tumor aggressiveness (one CpG). These results indicate that differentially methylated CpG sites identified in tumor tissues of African American men may contribute to prostate cancer aggressiveness.     

Postnatal stability,tissue, and time specific effects of AHRR methylation change in response to maternal smoking in pregnancy

The intrauterine environment has the potential to “program” the developing fetus in a way that can be potentially deleterious to later health. While in utero environmental/stochastic factors are known to influence DNA methylation profile at birth, it has been difficult to assign specific examples of epigenetic variation to specific environmental exposures. Recently, several studies have linked exposure to smoking with DNA methylation change in the aryl hydrocarbon receptor repressor (AHRR) gene in blood. This includes hypomethylation of AHRR in neonatal blood in response to maternal smoking in pregnancy. The role of AHRR as a negative regulator of pathways involved in pleiotropic responses to environmental contaminants raises the possibility that smoking-induced hypomethylation is an adaptive response to an adverse in utero environmental exposure. However, the tissue specificity of the response to maternal smoking, and the stability of the methylation changes early in life remain to be determined. In this study we analyzed AHRR methylation in three cell types—cord blood mononuclear cells (CBMCs), buccal epithelium, and placenta tissue—from newborn twins of mothers who smoked throughout pregnancy and matched controls. Further, we explored the postnatal stability of this change at 18 months. Our results confirm the previous association between maternal smoking and AHRR methylation in neonatal blood. In addition, this study expands the region of AHRR methylation altered in response to maternal smoking during pregnancy and reveals the tissue-specific nature of epigenetic responses to environmental exposures in utero. Further, the evidence for postnatal stability of smoking-induced epigenetic change supports a role for epigenetics as a mediator of long-term effects of specific in utero exposures in humans. Longitudinal analysis of further specific exposures in larger cohorts is required to examine the extent of this phenomenon in humans.     

Ancestry Dependent DNA Methylation and Influence of Maternal Nutrition

There is extensive variation in DNA methylation between individuals and ethnic groups. These differences arise from a combination of genetic and non-genetic influences and potential modifiers include nutritional cues, early life experience, and social and physical environments. Here we compare genome-wide DNA methylation in neonatal cord blood from African American (AA; N = 112) and European American (EA; N = 91) participants of the CANDLE Study (Conditions Affecting Neurocognitive Development and Learning in Early Childhood). Our goal is to determine if there are replicable ancestry-specific methylation patterns that may implicate risk factors for diseases that have differential prevalence between populations. To identify the most robust ancestry-specific CpG sites, we replicate our results in lymphoblastoid cell lines from Yoruba African and CEPH European panels of HapMap. We also evaluate the influence of maternal nutrition—specifically, plasma levels of vitamin D and folate during pregnancy—on methylation in newborns. We define stable ancestry-dependent methylation of genes that include tumor suppressors and cell cycle regulators (e.g., APC, BRCA1, MCC). Overall, there is lower global methylation in African ancestral groups. Plasma levels of 25-hydroxy vitamin D are also considerably lower among AA mothers and about 60% of AA and 40% of EA mothers have concentrations below 20 ng/ml. Using a weighted correlation analysis, we define a network of CpG sites that is jointly modulated by ancestry and maternal vitamin D. Our results show that differences in DNA methylation patterns are remarkably stable and maternal micronutrients can exert an influence on the child epigenome.     

Maternal genome-wide DNA methylation profiling in gestational diabetes shows distinctive disease-associated changes relative to matched healthy pregnancies

Several recent reports have described associations between gestational diabetes (GDM) and changes to the epigenomic landscape where the DNA samples were derived from either cord or placental sources. We employed genome-wide 450K array analysis to determine changes to the epigenome in a unique cohort of maternal blood DNA from 11 pregnant women prior to GDM development relative to matched controls. Hierarchical clustering segregated the samples into 2 distinct clusters comprising GDM and healthy pregnancies. Screening identified 100 CpGs with a mean β-value difference of ≥0.2 between cases and controls. Using stringent criteria, 5 CpGs (within COPS8, PIK3R5, HAAO, CCDC124, and C5orf34 genes) demonstrated potentials to be clinical biomarkers as revealed by differential methylation in 8 of 11 women who developed GDM relative to matched controls. We identified, for the first time, maternal methylation changes prior to the onset of GDM that may prove useful as biomarkers for early therapeutic intervention.     

Differential DNA methylation with age displays both common and dynamic features across human tissues that are influenced by CpG landscape

Background

DNA methylation is an epigenetic modification that changes with age in human tissues, although the mechanisms and specificity of this process are still poorly understood. We compared CpG methylation changes with age across 283 human blood, brain, kidney, and skeletal muscle samples using methylation arrays to identify tissue-specific age effects.

Results

We found age-associated CpGs (ageCGs) that are both tissue-specific and common across tissues. Tissue-specific ageCGs are frequently located outside CpG islands with decreased methylation, and common ageCGs show the opposite trend. AgeCGs are significantly associated with poorly expressed genes, but those with decreasing methylation are linked with higher tissue-specific expression levels compared with increasing methylation. Therefore, tissue-specific gene expression may protect against common age-dependent methylation. Distinguished from other tissues, skeletal muscle ageCGs are more associated with expression, enriched near genes related to myofiber contraction, and closer to muscle-specific CTCF binding sites. Kidney-specific ageCGs are more increasingly methylated compared to other tissues as measured by affiliation with kidney-specific expressed genes. Underlying chromatin features also mark common and tissue-specific age effects reflective of poised and active chromatin states, respectively. In contrast with decreasingly methylated ageCGs, increasingly methylated ageCGs are also generally further from CTCF binding sites and enriched within lamina associated domains.

Conclusions

Our data identified common and tissue-specific DNA methylation changes with age that are reflective of CpG landscape and suggests both common and unique alterations within human tissues. Our findings also indicate that a simple epigenetic drift model is insufficient to explain all age-related changes in DNA methylation.     

Predicting DNA methylation level across human tissues

Differences in methylation across tissues are critical to cell differentiation and are key to understanding the role of epigenetics in complex diseases. In this investigation, we found that locus-specific methylation differences between tissues are highly consistent across individuals. We developed a novel statistical model to predict locus-specific methylation in target tissue based on methylation in surrogate tissue. The method was evaluated in publicly available data and in two studies using the latest IlluminaBeadChips: a childhood asthma study with methylation measured in both peripheral blood leukocytes (PBL) and lymphoblastoid cell lines; and a study of postoperative atrial fibrillation with methylation in PBL, atrium and artery. We found that our method can greatly improve accuracy of cross-tissue prediction at CpG sites that are variable in the target tissue [R² increases from 0.38 (original R² between tissues) to 0.89 for PBL-to-artery prediction; from 0.39 to 0.95 for PBL-to-atrium; and from 0.81 to 0.98 for lymphoblastoid cell line-to-PBL based on cross-validation, and confirmed using cross-study prediction]. An extended model with multiple CpGs further improved performance. Our results suggest that large-scale epidemiology studies using easy-to-access surrogate tissues (e.g. blood) could be recalibrated to improve understanding of epigenetics in hard-to-access tissues (e.g. atrium) and might enable non-invasive disease screening using epigenetic profiles.     

Tissue-specific patterns of allelically-skewed DNA methylation

While DNA methylation is usually thought to be symmetrical across both alleles, there are some notable exceptions. Genomic imprinting and X chromosome inactivation are two well-studied sources of allele-specific methylation (ASM), but recent research has indicated a more complex pattern in which genotypic variation can be associated with allelically-skewed DNA methylation in cis. Given the known heterogeneity of DNA methylation across tissues and cell types we explored inter- and intra-individual variation in ASM across several regions of the human brain and whole blood from multiple individuals. Consistent with previous studies, we find widespread ASM with > 4% of the ～220,000 loci interrogated showing evidence of allelically-skewed DNA methylation. We identify ASM flanking known imprinted regions, and show that ASM sites are enriched in DNase I hypersensitivity sites and often located in an extended genomic context of intermediate DNA methylation. We also detect examples of genotype-driven ASM, some of which are tissue-specific. These findings contribute to our understanding of the nature of differential DNA methylation across tissues and have important implications for genetic studies of complex disease. As a resource to the community, ASM patterns across each of the tissues studied are available in a searchable online database: http://epigenetics.essex.ac.uk/ASMBrainBlood.     

Epigenetic divergence of key genes associated with water temperature and salinity in a highly invasive model ascidian

Invasive species offer good models for studying mechanisms of response to rapid changing environments in the wild. DNA methylation is considered to be one of crucial drivers for rapid local adaptation. However, the extent of epigenetic variation and the factors driving such variation remain largely unexplored in biological invasions. Here we used direct bisulfite sequencing to investigate DNA methylation patterns of five key genes corresponding to two important environmental factors in marine ecosystems, water temperature and salinity, in a model invasive ascidian Ciona robusta (=C. intestinalis spA). Our results clearly showed that DNA methylation mainly occurred in gene bodies, rather than promoters, at regions with low values of CpG O/E. We detected significant variation of DNA methylation among populations in two genes (heat shock protein 90 and Na⁺-K⁺-2Cl^? cotransporter). Interestingly, significant correlation was detected between methylation levels and the two environmental factors at some CpGs in these two genes. When the data of all CpGs was subjected to principal component analysis, individuals were assigned back to their population orgins. All the results suggest that environmental factors likely contribute, at least partially, to the observed DNA methylation variation. Such variation, either by some loci alone or through gene networks, might be involved in rapid local adaptation during biological invasions.