Genome-wide DNA methylation scan in major depressive disorder

While genome-wide association studies are ongoing to identify sequence variation influencing susceptibility to major depressive disorder (MDD), epigenetic marks, such as DNA methylation, which can be influenced by environment, might also play a role. Here we present the first genome-wide DNA methylation (DNAm) scan in MDD. We compared 39 postmortem frontal cortex MDD samples to 26 controls. DNA was hybridized to our Comprehensive High-throughput Arrays for Relative Methylation (CHARM) platform, covering 3.5 million CpGs. CHARM identified 224 candidate regions with DNAm differences >10%. These regions are highly enriched for neuronal growth and development genes. Ten of 17 regions for which validation was attempted showed true DNAm differences; the greatest were in PRIMA1, with 12-15% increased DNAm in MDD (p = 0.0002-0.0003), and a concomitant decrease in gene expression. These results must be considered pilot data, however, as we could only test replication in a small number of additional brain samples (n = 16), which showed no significant difference in PRIMA1. Because PRIMA1 anchors acetylcholinesterase in neuronal membranes, decreased expression could result in decreased enzyme function and increased cholinergic transmission, consistent with a role in MDD. We observed decreased immunoreactivity for acetylcholinesterase in MDD brain with increased PRIMA1 DNAm, non-significant at p = 0.08.While we cannot draw firm conclusions about PRIMA1 DNAm in MDD, the involvement of neuronal development genes across the set showing differential methylation suggests a role for epigenetics in the illness. Further studies using limbic system brain regions might shed additional light on this role.     

High density DNA methylation array with single CpG site resolution

We have developed a new generation of genome-wide DNA methylation BeadChip which allows high-throughput methylation profiling of the human genome. The new high density BeadChip can assay over 480K CpG sites and analyze twelve samples in parallel. The innovative content includes coverage of 99% of RefSeq genes with multiple probes per gene, 96% of CpG islands from the UCSC database, CpG island shores and additional content selected from whole-genome bisulfite sequencing data and input from DNA methylation experts. The well-characterized Infinium® Assay is used for analysis of CpG methylation using bisulfite-converted genomic DNA. We applied this technology to analyze DNA methylation in normal and tumor DNA samples and compared results with whole-genome bisulfite sequencing (WGBS) data obtained for the same samples. Highly comparable DNA methylation profiles were generated by the array and sequencing methods (average R² of 0.95). The ability to determine genome-wide methylation patterns will rapidly advance methylation research.     

DNA methylation-based biomarkers for ageing long-lived cetaceans

Epigenetic approaches for estimating the age of living organisms are revolutionizing studies of long-lived species. Molecular biomarkers that allow age estimates from small tissue biopsies promise to enhance studies of long-lived whales, addressing a fundamental and challenging parameter in wildlife management. DNA methylation (DNAm) can affect gene expression, and strong correlations between DNAm patterns and age have been documented in humans and nonhuman vertebrates and used to construct “epigenetic clocks”. We present several epigenetic clocks for skin samples from two of the longest-lived cetaceans, killer whales and bowhead whales. Applying the mammalian methylation array to genomic DNA from skin samples we validate four different clocks with median errors of 2.3–3.7 years. These epigenetic clocks demonstrate the validity of using cytosine methylation data to estimate the age of long-lived cetaceans and have broad applications supporting the conservation and management of long-lived cetaceans using genomic DNA from remote tissue biopsies.     

Differential DNA methylation in purified human blood cells: implications for cell lineage and studies on disease susceptibility

Methylation of cytosines at CpG sites is a common epigenetic DNA modification that can be measured by a large number of methods, now even in a genome-wide manner for hundreds of thousands of sites. The application of DNA methylation analysis is becoming widely popular in complex disorders, for example, to understand part of the "missing heritability". The DNA samples most readily available for methylation studies are derived from whole blood. However, blood consists of many functionally and developmentally distinct cell populations in varying proportions. We studied whether such variation might affect the interpretation of methylation studies based on whole blood DNA. We found in healthy male blood donors there is important variation in the methylation profiles of whole blood, mononuclear cells, granulocytes, and cells from seven selected purified lineages. CpG methylation between mononuclear cells and granulocytes differed for 22% of the 8252 probes covering the selected 343 genes implicated in immune-related disorders by genome-wide association studies, and at least one probe was differentially methylated for 85% of the genes, indicating that whole blood methylation results might be unintelligible. For individual genes, even if the overall methylation patterns might appear similar, a few CpG sites in the regulatory regions may have opposite methylation patterns (i.e., hypo/hyper) in the main blood cell types. We conclude that interpretation of whole blood methylation profiles should be performed with great caution and for any differences implicated in a disorder, the differences resulting from varying proportions of white blood cell types should be considered.     

Assessing the co-variability of DNA methylation across peripheral cells and tissues: Implications for the interpretation of findings in epigenetic epidemiology

Most epigenome-wide association studies (EWAS) quantify DNA methylation (DNAm) in peripheral tissues such as whole blood to identify positions in the genome where variation is statistically associated with a trait or exposure. As whole blood comprises a mix of cell types, it is unclear whether trait-associated DNAm variation is specific to an individual cellular population. We collected three peripheral tissues (whole blood, buccal epithelial and nasal epithelial cells) from thirty individuals. Whole blood samples were subsequently processed using fluorescence-activated cell sorting (FACS) to purify five constituent cell-types (monocytes, granulocytes, CD4⁺ T cells, CD8⁺ T cells, and B cells). DNAm was profiled in all eight sample-types from each individual using the Illumina EPIC array. We identified significant differences in both the level and variability of DNAm between different sample types, and DNAm data-derived estimates of age and smoking were found to differ dramatically across sample types from the same individual. We found that for the majority of loci variation in DNAm in individual blood cell types was only weakly predictive of variance in DNAm measured in whole blood, although the proportion of variance explained was greater than that explained by either buccal or nasal epithelial samples. Covariation across sample types was much higher for DNAm sites influenced by genetic factors. Overall, we observe that DNAm variation in whole blood is additively influenced by a combination of the major blood cell types. For a subset of sites, however, variable DNAm detected in whole blood can be attributed to variation in a single blood cell type providing potential mechanistic insight about EWAS findings. Our results suggest that associations between whole blood DNAm and traits or exposures reflect differences in multiple cell types and our data will facilitate the interpretation of findings in epigenetic epidemiology.     

Gene-Specific DNA Methylation Association with Serum Levels of C-Reactive Protein in African Americans

A more thorough understanding of the differences in DNA methylation (DNAm) profiles in populations may hold promise for identifying molecular mechanisms through which genetic and environmental factors jointly contribute to human diseases. Inflammation is a key molecular mechanism underlying several chronic diseases including cardiovascular disease, and it affects DNAm profile on both global and locus-specific levels. To understand the impact of inflammation on the DNAm of the human genome, we investigated DNAm profiles of peripheral blood leukocytes from 966 African American participants in the Genetic Epidemiology Network of Arteriopathy (GENOA) study. By testing the association of DNAm sites on CpG islands of over 14,000 genes with C-reactive protein (CRP), an inflammatory biomarker of cardiovascular disease, we identified 257 DNAm sites in 240 genes significantly associated with serum levels of CRP adjusted for age, sex, body mass index and smoking status, and corrected for multiple testing. Of the significantly associated DNAm sites, 80.5% were hypomethylated with higher CRP levels. The most significant Gene Ontology terms enriched in the genes associated with the CRP levels were immune system process, immune response, defense response, response to stimulus, and response to stress, which are all linked to the functions of leukocytes. While the CRP-associated DNAm may be cell-type specific, understanding the DNAm association with CRP in peripheral blood leukocytes of multi-ethnic populations can assist in unveiling the molecular mechanism of how the process of inflammation affects the risks of developing common disease through epigenetic modifications.     

Adaptation of the CHARM DNA methylation platform for the rat genome reveals novel brain region-specific differences

Comprehensive High-throughput Arrays for Relative Methylation (CHARM) was recently developed as an experimental platform and analytic approach to assess DNA methylation (DNAm) at a genome-wide level. Its initial implementation was for human and mouse. We adapted it for rat and sought to examine DNAm differences across tissues and brain regions in this model organism. We extracted DNA from liver, spleen, and three brain regions: cortex, hippocampus, and hypothalamus from adult Sprague Dawley rats. DNA was digested with McrBC, and the resulting methyl-depleted fraction was hybridized to the rat CHARM array along with a mock-treated fraction. Differentially methylated regions (DMRs) between tissue types were detected using normalized methylation log-ratios. In validating 24 of the most significant DMRs by bisulfite pyrosequencing, we detected large mean differences in DNAm, ranging from 33-59%, among the most significant DMRs in the across-tissue comparisons. The comparable figures for the hippocampus vs. hypothalamus DMRs were 14-40%, for the cortex vs. hippocampus DMRs, 12-29%, and for the cortex vs. hypothalamus DMRs, 5-35%, with a correlation of r² = 0.92 between the methylation differences in 24 DMRs predicted by CHARM and those validated by bisulfite pyrosequencing. Our adaptation of the CHARM array for the rat genome yielded highly robust results that demonstrate the value of this method in detecting substantial DNAm differences between tissues and across different brain regions. This platform should prove valuable in future studies aimed at examining DNAm differences in particular brain regions of rats exposed to environmental stimuli with potential epigenetic consequences.     

EBV transformation and cell culturing destabilizes DNA methylation in human lymphoblastoid cell lines

Recent research suggests that epigenetic alterations involving DNA methylation can be causative for neurodevelopmental, growth and metabolic disorders. Although lymphoblastoid cell lines have been an invaluable resource for the study of both genetic and epigenetic disorders, the impact of EBV transformation, cell culturing and freezing on epigenetic patterns is unknown. We compared genome-wide DNA methylation patterns of four white blood cell samples, four low-passage lymphoblastoid cell lines pre and post freezing and four high-passage lymphobastoid cell lines, using two microarray platforms: Illumina HumanMethylation27 platform containing 27,578 CpG sites and Agilent Human CpG island Array containing 27,800 CpG islands. Comparison of genome-wide methylation profiles between white blood cells and lymphoblastoid cell lines demonstrated methylation alterations in lymphoblastoid cell lines occurring at random genomic locations. These changes were more profound in high-passage cells. Freezing at low-passages did not have a significant effect on DNA methylation. Methylation changes were observed in several imprinted differentially methylated regions, including DIRAS3, NNAT, H19, MEG3, NDN and MKRN3, but not in known imprinting centers. Our results suggest that lymphoblastoid cell lines should be used with caution for the identification of disease-associated DNA methylation changes or for discovery of new imprinted genes, as the methylation patterns seen in these cell lines may not always be representative of DNA methylation present in the original B-lymphocytes of the patient.     

Maternal weight affects placental DNA methylation of genes involved in metabolic pathways in the common marmoset monkey (Callithrix jacchus)

Accumulating evidence suggests that dysregulation of placental DNA methylation (DNAm) is a mechanism linking maternal weight during pregnancy to metabolic programming outcomes. The common marmoset, Callithrix jaccus, is a platyrrhine primate species that has provided much insight into studies of the primate placenta, maternal condition, and metabolic programming, yet the relationships between maternal weight and placental DNAm are unknown. Here, we report genome-wide DNAm from term marmoset placentas using reduced representation bisulfite sequencing. We identified 74 genes whose DNAm pattern is associated with maternal weight during gestation. These genes are predominantly involved in energy metabolism and homeostasis, including the regulation of glycolytic and lipid metabolic processes pathways.     

Adaptation of the CHARM DNA methylation platform for the rat genome reveals novel brain region-specific differences

Comprehensive High-throughput Arrays for Relative Methylation (CHARM) was recently developed as an experimental platform and analytic approach to assess DNA methylation (DNAm) at a genome-wide level. Its initial implementation was for human and mouse. We adapted it for rat and sought to examine DNAm differences across tissues and brain regions in this model organism. We extracted DNA from liver, spleen, and three brain regions: cortex, hippocampus, and hypothalamus from adult Sprague Dawley rats. DNA was digested with McrBC, and the resulting methyl-depleted fraction was hybridized to the rat CHARM array along with a mock-treated fraction. Differentially methylated regions (DMRs) between tissue types were detected using normalized methylation log-ratios. In validating 24 of the most significant DMRs by bisulfite pyrosequencing, we detected large mean differences in DNAm, ranging from 33-59%, among the most significant DMRs in the across-tissue comparisons. The comparable figures for the hippocampus vs. hypothalamus DMRs were 14-40%, for the cortex vs. hippocampus DMRs, 12-29%, and for the cortex vs. hypothalamus DMRs, 5-35%, with a correlation of r(2) = 0.92 between the methylation differences in 24 DMRs predicted by CHARM and those validated by bisulfite pyrosequencing. Our adaptation of the CHARM array for the rat genome yielded highly robust results that demonstrate the value of this method in detecting substantial DNAm differences between tissues and across different brain regions. This platform should prove valuable in future studies aimed at examining DNAm differences in particular brain regions of rats exposed to environmental stimuli with potential epigenetic consequences.     

Comprehensive DNA methylation analysis of human peripheral blood leukocytes and lymphoblastoid cell lines

DNA methylation is involved in development and in human diseases. Genomic DNA derived from lymphoblastoid cell lines (LCLs) is commonly used to study DNA methylation. There are potential confounding factors regarding the use of LCL-derived DNA, however, such as Epstein-Barr (EB) viral infection and artifacts induced during cell culture. Recently, several groups compared the DNA methylation status of peripheral blood leukocytes (PBLs) and LCLs and concluded that the DNA methylation profiles between them might be consistent. To confirm and extend theses results, we performed a comprehensive DNA methylation analysis using both PBLs and LCLs derived from the same individuals. Using the luminometric methylation assay, we revealed that the global DNA methylation level was different between PBLs and LCLs. Furthermore, the direction of change was not consistent. Comparisons of genome-wide DNA methylation patterns of promoter regions revealed that methylation profiles were largely conserved between PBLs and LCLs. A preliminary analysis in a small number of samples suggested that the methylation status of an LCL may be better correlated with PBLs from the same individual than with LCLs from other individuals. Expectedly, DNA methylation in promoter regions overlapping with CpG islands was associated with gene silencing in both PBLs and LCLs. With regard to methylation differences, we found that hypermethylation was more predominant than hypomethylation in LCLs compared with PBLs. These findings suggest that LCLs should be used for DNA methylation studies with caution as the methylation patterns of promoter regions in LCLs are not always the same as those in PBLs.     

Epigenomic association analysis identifies smoking-related DNA methylation sites in African Americans

Cigarette smoking is an environmental risk factor for many chronic diseases, and disease risk can often be managed by smoking control. Smoking can induce cellular and molecular changes, including epigenetic modification, but the short- and long-term epigenetic modifications caused by cigarette smoking at the gene level have not been well understood. Recent studies have identified smoking-related DNA methylation (DNAm) sites in Caucasians. To determine whether the same DNAm sites associate with smoking in African Americans, and to identify novel smoking-related DNAm sites, we conducted a methylome-wide association study of cigarette smoking using a discovery sample of 972 African Americans, and a replication sample of 239 African Americans with two array-based methods. Among 15 DNAm sites significantly associated with smoking after correction for multiple testing in our discovery sample, 5 DNAm sites are replicated in an independent cohort, and 14 sites in the replication sample have effects in the same direction as in the discovery sample. The top two smoking-related DNAm sites in F2RL3 (factor II receptor-like 3) and GPR15 (G-protein-coupled receptor 15) observed in African Americans are consistent with previous findings in Caucasians. The associations between the replicated DNAm sites and smoking remain significant after adjusting for genetic background. Despite the distinct genetic background between African Americans and Caucasians, the DNAm from the two ethnic groups shares common associations with cigarette smoking, which suggests a common molecular mechanism of epigenetic modification influenced by environmental exposure.     

Comprehensive DNA methylation analysis of human peripheral blood leukocytes and lymphoblastoid cell lines

DNA methylation is involved in development and in human diseases. Genomic DNA derived from lymphoblastoid cell lines (LCLs) is commonly used to study DNA methylation. There are potential confounding factors regarding the use of LCL-derived DNA, however, such as Epstein-Barr (EB) viral infection and artifacts induced during cell culture. Recently, several groups compared the DNA methylation status of peripheral blood leukocytes (PBLs) and LCLs and concluded that the DNA methylation profiles between them might be consistent. To confirm and extend theses results, we performed a comprehensive DNA methylation analysis using both PBLs and LCLs derived from the same individuals. Using the luminometric methylation assay, we revealed that the global DNA methylation level was different between PBLs and LCLs. Furthermore, the direction of change was not consistent. Comparisons of genome-wide DNA methylation patterns of promoter regions revealed that methylation profiles were largely conserved between PBLs and LCLs. A preliminary analysis in a small number of samples suggested that the methylation status of an LCL may be better correlated with PBLs from the same individual than with LCLs from other individuals. Expectedly, DNA methylation in promoter regions overlapping with CpG islands was associated with gene silencing in both PBLs and LCLs. With regard to methylation differences, we found that hypermethylation was more predominant than hypomethylation in LCLs compared with PBLs. These findings suggest that LCLs should be used for DNA methylation studies with caution as the methylation patterns of promoter regions in LCLs are not always the same as those in PBLs.Key words: DNA methylation, lymphoblastoid cell lines, peripheral blood leukocytes, LUMA, promoter tiling array, gene expression     

Autosomal sex-associated co-methylated regions predict biological sex from DNA methylation

Sex is a modulator of health that has been historically overlooked in biomedical research. Recognizing this knowledge gap, funding agencies now mandate the inclusion of sex as a biological variable with the goal of stimulating efforts to illuminate the molecular underpinnings of sex biases in health and disease. DNA methylation (DNAm) is a strong molecular candidate for mediating such sex biases; however, a robust and well characterized annotation of sex differences in DNAm is yet to emerge. Beginning with a large (n = 3795) dataset of DNAm profiles from normative adult whole blood samples, we identified, validated and characterized autosomal sex-associated co-methylated genomic regions (sCMRs). Strikingly, sCMRs showed consistent sex differences in DNAm over the life course and a subset were also consistent across cell, tissue and cancer types. sCMRs included sites with known sex differences in DNAm and links to health conditions with sex biased effects. The robustness of sCMRs enabled the generation of an autosomal DNAm-based predictor of sex with 96% accuracy. Testing this tool on blood DNAm profiles from individuals with sex chromosome aneuploidies (Klinefelter [47,XXY], Turner [45,X] and 47,XXX syndrome) revealed an intimate relationship between sex chromosomes and sex-biased autosomal DNAm.     

A systematic study of normalization methods for Infinium 450K methylation data using whole-genome bisulfite sequencing data

DNA methylation plays an important role in disease etiology. The Illumina Infinium HumanMethylation450 (450K) BeadChip is a widely used platform in large-scale epidemiologic studies. This platform can efficiently and simultaneously measure methylation levels at ∼480,000 CpG sites in the human genome in multiple study samples. Due to the intrinsic chip design of 2 types of chemistry probes, data normalization or preprocessing is a critical step to consider before data analysis. To date, numerous methods and pipelines have been developed for this purpose, and some studies have been conducted to evaluate different methods. However, validation studies have often been limited to a small number of CpG sites to reduce the variability in technical replicates. In this study, we measured methylation on a set of samples using both whole-genome bisulfite sequencing (WGBS) and 450K chips. We used WGBS data as a gold standard of true methylation states in cells to compare the performances of 8 normalization methods for 450K data on a genome-wide scale. Analyses on our dataset indicate that the most effective methods are peak-based correction (PBC) and quantile normalization plus β-mixture quantile normalization (QN.BMIQ). To our knowledge, this is the first study to systematically compare existing normalization methods for Illumina 450K data using novel WGBS data. Our results provide a benchmark reference for the analysis of DNA methylation chip data, particularly in white blood cells.     

Genome-scale analysis of DNA methylation in colorectal cancer using Infinium HumanMethylation450 BeadChips

Illumina’s Infinium HumanMethylation450 BeadChip arrays were used to examine genome-wide DNA methylation profiles in 22 sample pairs from colorectal cancer (CRC) and adjacent tissues and 19 colon tissue samples from cancer-free donors. We show that the methylation profiles of tumors and healthy tissue samples can be clearly distinguished from one another and that the main source of methylation variability is associated with disease status. We used different statistical approaches to evaluate the methylation data. In general, at the CpG-site level, we found that common CRC-specific methylation patterns consist of at least 15,667 CpG sites that were significantly different from either adjacent healthy tissue or tissue from cancer-free subjects. Of these sites, 10,342 were hypermethylated in CRC, and 5,325 were hypomethylated. Hypermethylated sites were common in the maximum number of sample pairs and were mostly located in CpG islands, where they were significantly enriched for differentially methylated regions known to be cancer-specific. In contrast, hypomethylated sites were mostly located in CpG shores and were generally sample-specific. Despite the considerable variability in methylation data, we selected a panel of 14 highly robust candidates showing methylation marks in genes SND1, ADHFE1, OPLAH, TLX2, C1orf70, ZFP64, NR5A2, and COL4A. This set was successfully cross-validated using methylation data from 209 CRC samples and 38 healthy tissue samples from The Cancer Genome Atlas consortium (AUC = 0.981 [95% CI: 0.9677–0.9939], sensitivity = 100% and specificity = 82%). In summary, this study reports a large number of loci with novel differential methylation statuses, some of which may serve as candidate markers for diagnostic purposes.