Simulating ComBat: how batch correction can lead to the systematic introduction of false positive results in DNA methylation microarray studies.

BACKGROUND: Systematic technical effects-also called batch effects-are a considerable challenge when analyzing DNA methylation (DNAm) microarray data, because they can lead to false results when confounded with the variable of interest. Methods to correct these batch effects are error-prone, as previous findings have shown. RESULTS: Here, we demonstrate how using the R function ComBat to correct simulated Infinium HumanMethylation450 BeadChip (450 K) and Infinium MethylationEPIC BeadChip Kit (EPIC) DNAm data can lead to a large number of false positive results under certain conditions. We further provide a detailed assessment of the consequences for the highly relevant problem of p-value inflation with subsequent false positive findings after application of the frequently used ComBat method. Using ComBat to correct for batch effects in randomly generated samples produced alarming numbers of false discovery rate (FDR) and Bonferroni-corrected (BF) false positive results in unbalanced as well as in balanced sample distributions in terms of the relation between the outcome of interest variable and the technical position of the sample during the probe measurement. Both sample size and number of batch factors (e.g. number of chips) were systematically simulated to assess the probability of false positive findings. The effect of sample size was simulated using n = 48 up to n = 768 randomly generated samples. Increasing the number of corrected factors led to an exponential increase in the number of false positive signals. Increasing the number of samples reduced, but did not completely prevent, this effect. CONCLUSIONS: Using the approach described, we demonstrate, that using ComBat for batch correction in DNAm data can lead to false positive results under certain conditions and sample distributions. Our results are thus contrary to previous publications, considering a balanced sample distribution as unproblematic when using ComBat. We do not claim completeness in terms of reporting all technical conditions and possible solutions of the occurring problems as we approach the problem from a clinician's perspective and not from that of a computer scientist. With our approach of simulating data, we provide readers with a simple method to assess the probability of false positive findings in DNAm microarray data analysis pipelines.

Elevated DNA methylation across a 48-kb region spanning the HOXA gene cluster is associated with Alzheimer's disease neuropathology.

INTRODUCTION: Alzheimer's disease is a neurodegenerative disorder that is hypothesized to involve epigenetic dysregulation of gene expression in the brain. METHODS: We performed an epigenome-wide association study to identify differential DNA methylation associated with neuropathology in prefrontal cortex and superior temporal gyrus samples from 147 individuals, replicating our findings in two independent data sets (N = 117 and 740). RESULTS: We identify elevated DNA methylation associated with neuropathology across a 48-kb region spanning 208 CpG sites within the HOXA gene cluster. A meta-analysis of the top-ranked probe within the HOXA3 gene (cg22962123) highlighted significant hypermethylation across all three cohorts (P = 3.11 × 10-18). DISCUSSION: We present robust evidence for elevated DNA methylation associated with Alzheimer's disease neuropathology spanning the HOXA gene cluster on chromosome 7. These data add to the growing evidence highlighting a role for epigenetic variation in Alzheimer's disease, implicating the HOX gene family as a target for future investigation.

Genome-Wide Measures of Peripheral Blood Dna Methylation and Prostate Cancer Risk in a Prospective Nested Case-Control Study.

BACKGROUND: Global measures of peripheral blood DNA methylation have been associated with risk of some malignancies, including breast, bladder, and gastric cancer. Here, we examined genome-wide measures of peripheral blood DNA methylation in prostate cancer and its non-aggressive and aggressive disease forms. METHODS: We used a matched, case-control study of 687 incident prostate cancer samples, nested within a larger prospective cohort study. DNA methylation was measured in pre-diagnostic, peripheral blood samples using the Illumina Infinium HM450K BeadChip. Genome-wide measures of DNA methylation were computed as the median M-value of all CpG sites and according to CpG site location and regulatory function. We used conditional logistic regression to test for associations between genome-wide measures of DNA methylation and risk of prostate cancer and its subtypes, and by time between blood draw and diagnosis. RESULTS: We observed no associations between the genome-wide measure of DNA methylation based on all CpG sites and risk of prostate cancer or aggressive disease. Risk of non-aggressive disease was associated with higher methylation of CpG islands (OR = 0.80; 95%CI = 0.68-0.94), promoter regions (OR = 0.79; 95%CI = 0.66-0.93), and high density CpG regions (OR = 0.80; 95%CI = 0.68-0.94). Additionally, higher methylation of all CpGs (OR = 0.66; 95%CI = 0.48-0.89), CpG shores (OR = 0.62; 95%CI = 0.45-0.84), and regulatory regions (OR = 0.68; 95% CI = 0.51-0.91) was associated with a reduced risk of overall prostate cancer within 5 years of blood draw but not thereafter. CONCLUSIONS: A reduced risk of overall prostate cancer within 5 years of blood draw and non-aggressive prostate cancer was associated with higher genome-wide methylation of peripheral blood DNA. While these data have no immediate clinical utility, with further work they may provide insight into the early events of prostate carcinogenesis. Prostate 77:471-478, 2017. © 2017 Wiley Periodicals, Inc.

Predicting CpG methylation levels by integrating Infinium HumanMethylation450 BeadChip array data.

The Infinium HumanMethylation450 BeadChip array, referred as 450K array hereinafter, has been widely adopted as an affordable technique to determine DNA methylation. Tens of thousands of data have been generated on diverse cell types and patient tissues, which have provided great insight into understanding the crucial roles of epigenetic modifications in many biological processes and diseases. The limitation of this technique is its coverage, which measures methylation levels of about 450,000 CpGs, accounting for about 1.6% of all CpGs in the human genome. In the present study we developed and compared computational models to significantly expand the coverage of Illumina 450K (~11 folds). Using the whole genome bisulfite sequencing and Illumina 450K data in the human H1 embryonic stem cell, we showed that the predicted and measured methylation levels were well correlated. Our proposed model showed superior prediction accuracies compared to the existing methods on the same dataset. When applied to predict the DNA methylome on other cells, our proposed model achieved comparable performance in cross-validations, which indicates the generalizibility of the method. Our method would thus be invaluable to maximize the usage of the existing data.

Type 2 diabetes and leucocyte DNA methylation: an epigenome-wide association study in over 1,500 older adults.

AIMS/HYPOTHESIS: Development of type 2 diabetes depends on environmental and genetic factors. We investigated the epigenome-wide association of prevalent diabetes with DNA methylation (DNAm) in peripheral blood. METHODS: DNAm was measured in whole blood with the Illumina Infinium HumanMethylation450 BeadChip in two subsamples of participants from the ESTHER cohort study. Cohort 1 included 988 participants, who were consecutively recruited between July and October 2000 and cohort 2 included 527 randomly selected participants. The association of DNAm with prevalent type 2 diabetes at recruitment was estimated using median regression analysis adjusting for sex, age, BMI, smoking behaviour, cell composition and batch at 361,922 CpG sites. RESULTS: Type 2 diabetes was prevalent in 16% of the participants, and diabetes was poorly controlled in 45% of the diabetic patients. In cohort 1 (discovery) DNAm at 39 CpGs was significantly associated with prevalent diabetes after correction for multiple testing. In cohort 2 (replication) at one of these CpGs, DNAm was still significantly associated. Decreasing methylation levels at cg19693031 with increasing fasting glucose and HbA1c concentrations were observed using restricted cubic spline analysis. In diabetic patients with poorly controlled diabetes, the decrease in estimated DNAm levels was approximately 5% in comparison with participants free of diagnosed diabetes. CONCLUSIONS/INTERPRETATION: Cg19693031, which is located within the 3'-untranslated region of TXNIP, might play a role in the pathophysiology of type 2 diabetes. This result appears biologically plausible given that thioredoxin-interacting protein is overexpressed in diabetic animals and humans and 3'-untranslated regions are known to play a regulatory role in gene expression.

Association of season of birth with DNA methylation and allergic disease.

BACKGROUND: Season of birth influences allergy risk; however, the biological mechanisms underlying this observation are unclear. The environment affects DNA methylation, with potentially long-lasting effects on gene expression and disease. This study examined whether DNA methylation could underlie the association between season of birth and allergy. METHODS: In a subset of 18-year-old participants from the Isle of Wight (IoW) birth cohort (n = 367), the risks of birth season on allergic outcomes were estimated. Whole blood epigenome-wide DNA methylation was measured, and season-associated CpGs detected using a training-and-testing-based technique. Validation method examined the 8-year-old Prevention and Incidence of Asthma and Mite Allergy (PIAMA) cohort. The relationships between DNA methylation, season of birth and allergy were examined. CpGs were analysed in IoW third-generation cohort newborns. RESULTS: Autumn birth increased risk of eczema, relative to spring birth. Methylation at 92 CpGs showed association with season of birth in the epigenome-wide association study. In validation, significantly more CpGs had the same directionality than expected by chance, and four were statistically significant. Season-associated methylation was enriched among networks relating to development, the cell cycle and apoptosis. Twenty CpGs were nominally associated with allergic outcomes. Two CpGs were marginally on the causal pathway to allergy. Season-associated methylation was largely absent in newborns, suggesting it arises post-natally. CONCLUSIONS: This study demonstrates that DNA methylation in adulthood is associated with season of birth, supporting the hypothesis that DNA methylation could mechanistically underlie the effect of season of birth on allergy, although other mechanisms are also likely to be involved.

Preliminary assessment of pre-morbid DNA methylation in individuals at high genetic risk of mood disorders.

OBJECTIVES: Accumulating evidence implicates altered DNA methylation in psychiatric disorders, including bipolar disorder (BD) and major depressive disorder (MDD). It is not clear, however, whether these changes are causative or result from illness progression or treatment. To disentangle these possibilities we profiled genome-wide DNA methylation in well, unrelated individuals at high familial risk of mood disorder. DNA methylation was compared between individuals who subsequently developed BD or MDD [ill later (IL)] and those who remained well [well later (WL)]. METHODS: DNA methylation profiles were obtained from whole-blood samples from 22 IL and 23 WL individuals using the Infinium HumanMethylation450 BeadChip. Differential methylation was assessed on a single-locus and regional basis. Pathway analysis was performed to assess enrichment for particular biological processes amongst nominally significantly differentially methylated loci. RESULTS: Although no locus withstood correction for multiple testing, uncorrected P-values provided suggestive evidence for altered methylation at sites within genes previously implicated in neuropsychiatric conditions, such as Transcription Factor 4 (TCF4) and Interleukin 1 Receptor Accessory Protein-Like 1 ([IL1RAPL1]; P≤3.11×10(-5) ). Pathway analysis revealed significant enrichment for several neurologically relevant pathways and functions, including Nervous System Development and Function and Behavior; these findings withstood multiple testing correction (q≤0.05). Analysis of differentially methylated regions identified several within the major histocompatibility complex (P≤.000 479), a region previously implicated in schizophrenia and BD. CONCLUSIONS: Our data provide provisional evidence for the involvement of altered whole-blood DNA methylation in neurologically relevant genes in the aetiology of mood disorders. These findings are convergent with the findings of genome-wide association studies.

Widespread DNA hypomethylation at gene enhancer regions in placentas associated with early-onset pre-eclampsia.

Pre-eclampsia is a serious complication of pregnancy that can affect both maternal and fetal outcomes. Early-onset pre-eclampsia (EOPET) is a severe form of pre-eclampsia that is associated with altered physiological characteristics and gene expression in the placenta. DNA methylation is a relatively stable epigenetic modification to DNA that can reflect gene expression, and can provide insight into the mechanisms underlying such expression changes. This case-control study focused on DNA methylation and gene expression of whole chorionic villi samples from 20 EOPET placentas and 20 gestational age-matched controls from pre-term births. DNA methylation was also assessed in placentas affected by late-onset pre-eclampsia (LOPET) and normotensive intrauterine growth restriction (nIUGR). The Illumina HumanMethylation450 BeadChip was used to assess DNA methylation at >480 000 cytosine-guanine dinucleotide (CpG) sites. The Illumina HT-12v4 Expression BeadChip was used to assess gene expression of >45 000 transcripts in a subset of cases and controls. DNA methylation analysis by pyrosequencing was used to follow-up the initial findings in four genes with a larger cohort of cases and controls, including nIUGR and LOPET placentas. Bioinformatic analysis was used to identify overrepresentation of gene ontology categories and transcription factor binding motifs. We identified 38 840 CpG sites with significant (false discovery rate <0.01) DNA methylation alterations in EOPET, of which 282 had >12.5% methylation difference compared with the controls. Significant sites were enriched at the enhancers and low CpG density regions of the associated genes and the majority (74.5%) of these sites were hypomethylated in EOPET. EOPET, but not associated clinical features, such as intrauterine growth restriction (IUGR), presented a distinct DNA methylation profile. CpG sites from four genes relevant to pre-eclampsia (INHBA, BHLHE40, SLC2A1 and ADAM12) showed different extent of changes in LOPET and nIUGR. Genome-wide expression in a subset of samples showed that some of the gene expression changes were negatively correlated with DNA methylation changes, particularly for genes that are responsible for angiogenesis (such as EPAS1 and FLT1). Results could be confounded by altered cell populations in abnormal placentas. Larger sample sizes are needed to fully address the possibility of sub-profiles of methylation within the EOPET cohort. Based on DNA methylation profiling, we conclude that there are widespread DNA methylation alterations in EOPET that may be associated with changes in placental function. This property may provide a useful tool for early screening of such placentas. This study identifies DNA methylation changes at many loci previously reported to have altered gene expression in EOPET placentas, as well as in novel biologically relevant genes we confirmed to be differentially expressed. These results may be useful for DNA- methylation-based non-invasive prenatal diagnosis of at-risk pregnancies.

Uncertainty quantification of reference-based cellular deconvolution algorithms.

The majority of epigenetic epidemiology studies to date have generated genome-wide profiles from bulk tissues (e.g., whole blood) however these are vulnerable to confounding from variation in cellular composition. Proxies for cellular composition can be mathematically derived from the bulk tissue profiles using a deconvolution algorithm; however, there is no method to assess the validity of these estimates for a dataset where the true cellular proportions are unknown. In this study, we describe, validate and characterize a sample level accuracy metric for derived cellular heterogeneity variables. The CETYGO score captures the deviation between a sample's DNA methylation profile and its expected profile given the estimated cellular proportions and cell type reference profiles. We demonstrate that the CETYGO score consistently distinguishes inaccurate and incomplete deconvolutions when applied to reconstructed whole blood profiles. By applying our novel metric to >6,300 empirical whole blood profiles, we find that estimating accurate cellular composition is influenced by both technical and biological variation. In particular, we show that when using a common reference panel for whole blood, less accurate estimates are generated for females, neonates, older individuals and smokers. Our results highlight the utility of a metric to assess the accuracy of cellular deconvolution, and describe how it can enhance studies of DNA methylation that are reliant on statistical proxies for cellular heterogeneity. To facilitate incorporating our methodology into existing pipelines, we have made it freely available as an R package (https://github.com/ds420/CETYGO).

Activation of hypermethylated P2RY1 mitigates gastric cancer by promoting apoptosis and inhibiting proliferation.

The P2RY1 receptor is known to cause cancer by activating the ERK signal pathway, and its DNA methylation status and corresponding regulatory mechanism remain unknown. This study used the DNA methylation chip to profile the genome-wide DNA methylation level in gastric cancer tissues. The proliferation and apoptosis of the SGC7901 gastric cancer cell line were determined after treatment with a selective P2RY1 receptor agonist, MRS2365. The promoter region of P2RY1 was found to be highly methylated with four hypermethylated sites (|Δß value| > 0.2) in diffuse gastric cancer and was validated by bioinformatics analysis in the TCGA database. Also, immunohistochemical staining data obtained from the HPA database demonstrated the downregulated expression of proteins encoded by P2RY1 in stomach cancer tissue. The analysis of MRS2365-treated cells by annexin V/propidium iodide staining and caspase-3 activity assays indicated the induction of apoptosis in SGC7901 cells. The P2RY1 receptor activation in human SGC7901 gastric cancer cells via the MRS2365 agonist induced apoptosis and reduced cell growth. High DNA methylation in the promoter region of P2RY1 might have contributed to the reduced expression of P2RY1's mRNA, which was likely responsible for the "aggressive" nature of the diffuse gastric cancer.

Liquid Biopsy in Alzheimer's Disease Patients Reveals Epigenetic Changes in the PRLHR Gene.

In recent years, new DNA methylation variants have been reported in genes biologically relevant to Alzheimer's disease (AD) in human brain tissue. However, this AD-specific epigenetic information remains brain-locked and unreachable during patients' lifetimes. In a previous methylome performed in the hippocampus of 26 AD patients and 12 controls, we found higher methylation levels in AD patients in the promoter region of PRLHR, a gene involved in energy balance regulation. Our aim was to further characterize PRLHR's role in AD and to evaluate if the liquid biopsy technique would provide life access to this brain information in a non-invasive way. First, we extended the methylation mapping of PRLHR and validated previous methylome results via bisulfite cloning sequencing. Next, we observed a positive correlation between PRLHR methylation levels and AD-related neuropathological changes and a decreased expression of PRLHR in AD hippocampus. Then, we managed to replicate the hippocampal methylation differences in plasma cfDNA from an additional cohort of 35 AD patients and 35 controls. The isolation of cfDNA from the plasma of AD patients may constitute a source of potential epigenetic biomarkers to aid AD clinical management.

Epigenetic Signatures of Centrosomes Are Novel Targets in Cancer Diagnosis: Insights from an Analysis of the Cancer Genome Atlas.

The centrosome plays a central role for cellular signaling and is critical for several fundamental cellular processes in human cells. Centrosome abnormalities have been linked to multiple solid tumors and hematological malignancies. We sought to explore the potential role of the DNA methylation, a critical epigenetic modification, of centrosome-related genes in different cancers. The 450K array DNA methylation data and RNA-seq data were downloaded for ~4000 tumor samples and ~500 normal controls from The Cancer Genome Atlas (TCGA) project, covering 11 major cancer types. Cancers with more than 30 normal controls were retained for analysis. Differentially modified CpGs of centrosome genes were identified, and cancer-specific epigenetic models were developed using a machine-learning algorithm for each cancer type. The association between the methylation level of differential CpGs and the corresponding gene expression, as well as the co-localization of the differential CpGs and cis-regulatory elements were evaluated. In total, 2761 CpGs located on 160 centrosome genes for 6 cancers were included in the analysis. Cancer-specific models demonstrated a high accuracy in terms of the area under the receiver operating characteristic (ROC) curve (AUC > 0.9) in five cancers and showed tissue specificity. This study enhanced our understanding of the epigenetic mechanisms underlying the DNA methylation of centrosome-related genes in cancers, and showed the potential of these epigenetic modifications as novel cancer biomarkers.

DNA Methylation Signatures Predict Cytogenetic Subtype and Outcome in Pediatric Acute Myeloid Leukemia (AML).

Pediatric acute myeloid leukemia (AML) is a heterogeneous disease composed of clinically relevant subtypes defined by recurrent cytogenetic aberrations. The majority of the aberrations used in risk grouping for treatment decisions are extensively studied, but still a large proportion of pediatric AML patients remain cytogenetically undefined and would therefore benefit from additional molecular investigation. As aberrant epigenetic regulation has been widely observed during leukemogenesis, we hypothesized that DNA methylation signatures could be used to predict molecular subtypes and identify signatures with prognostic impact in AML. To study genome-wide DNA methylation, we analyzed 123 diagnostic and 19 relapse AML samples on Illumina 450k DNA methylation arrays. We designed and validated DNA methylation-based classifiers for AML cytogenetic subtype, resulting in an overall test accuracy of 91%. Furthermore, we identified methylation signatures associated with outcome in t(8;21)/RUNX1-RUNX1T1, normal karyotype, and MLL/KMT2A-rearranged subgroups (p < 0.01). Overall, these results further underscore the clinical value of DNA methylation analysis in AML.

A cross-cohort analysis of autosomal DNA methylation sex differences in the term placenta.

BACKGROUND: Human placental DNA methylation (DNAme) data is a valuable resource for studying sex differences during gestation, as DNAme profiles after delivery reflect the cumulative effects of gene expression patterns and exposures across gestation. Here, we present an analysis of sex differences in autosomal DNAme in the uncomplicated term placenta (n = 343) using the Illumina 450K array. RESULTS: At a false discovery rate < 0.05 and a mean sex difference in DNAme beta value of > 0.10, we identified 162 autosomal CpG sites that were differentially methylated by sex and replicated in an independent cohort of samples (n = 293). Several of these differentially methylated CpG sites were part of larger correlated regions of sex differential DNAme. Although global DNAme levels did not differ by sex, the majority of significantly differentially methylated CpGs were more highly methylated in male placentae, the opposite of what is seen in differential methylation analyses of somatic tissues. Patterns of autosomal DNAme at these 162 CpGs were significantly associated with maternal age (in males) and newborn birthweight standard deviation (in females). CONCLUSIONS: Our results provide a comprehensive analysis of sex differences in autosomal DNAme in the term human placenta. We report a list of high-confidence autosomal sex-associated differentially methylated CpGs and identify several key features of these loci that suggest their relevance to sex differences observed in normative and complicated pregnancies.

Differential CpG DNA methylation in peripheral naïve CD4+ T-cells in early rheumatoid arthritis patients.

BACKGROUND: The genetic risk associated with rheumatoid arthritis (RA) includes genes regulating DNA methylation, one of the hallmarks of epigenetic re-programing, as well as many T-cell genes, with a strong MHC association, pointing to immunogenetic mechanisms as disease triggers leading to chronicity. The aim of our study was to explore DNA methylation in early, drug-naïve RA patients, towards a better understanding of early events in pathogenesis. RESULT: Monocytes, naïve and memory CD4+ T-cells were sorted from 6 healthy controls and 10 RA patients. DNA methylation was assessed using a genome-wide Illumina 450K CpG promoter array. Differential methylation was confirmed using bisulfite sequencing for a specific gene promoter, ELISA for several cytokines and flow cytometry for cell surface markers. Differentially methylated (DM) CpGs were observed in 1047 genes in naïve CD4+ T-cells, 913 in memory cells and was minimal in monocytes with only 177 genes. Naive CD4+ T-cells were further investigated as presenting differential methylation in the promoter of > 500 genes associated with several disease-relevant pathways, including many cytokines and their receptors. We confirmed hypomethylation of a region of the TNF-alpha gene in early RA and differential expression of 3 cytokines (IL21, IL34 and RANKL). Using a bioinformatics package (DMRcate) and an in-house analysis based on differences in ß values, we established lists of DM genes between health and RA. Publicly available gene expression data were interrogated to confirm differential expression of over 70 DM genes. The lists of DM genes were further investigated based on a functional relationship database analysis, which pointed to an IL6/JAK1/STAT3 node, related to TNF-signalling and engagement in Th17 cell differentiation amongst many pathways. Five DM genes for cell surface markers (CD4, IL6R, IL2RA/CD25, CD62L, CXCR4) were investigated towards identifying subpopulations of CD4+ T-cells undergoing these modifications and pointed to a subset of naïve T-cells, with high levels of CD4, IL2R, and CXCR4, but reduction and loss of IL6R and CD62L, respectively. CONCLUSION: Our data provided novel conceptual advances in the understanding of early RA pathogenesis, with implications for early treatment and prevention.

Array-based DNA methylation profiling reveals peripheral blood differential methylation in male infertility.

OBJECTIVE: To study peripheral blood DNA differential methylation in oligozoospermic infertile men in comparison with normozoospermic fertile controls. DESIGN: Case-control study. SETTING: Reproductive biology laboratory. PATIENTS(S): Azoospermic and oligozoospermic infertile patients (n = 6) and normozoospermic fertile controls (n = 6) in the discovery phase, and oligo/asthenozoospermic infertile men (n = 11) and normozoospermic fertile controls (n = 10) in the validation phase. INTERVENTION(S): Blood samples drawn from all participants, DNA isolation and methylation analysis. MAIN OUTCOME MEASURE(S): DNA methylation values analyzed using genomewide methylation 450K BeadChip array, followed by deep sequencing of selected regions for methylation analysis in the neighborhood regions of differentially methylated CpGs. RESULT(S): We found 329 differentially methylated CpG spots, out of which 245 referred to the genes, representing 170 genes. Deep-sequencing analysis confirmed the methylation pattern suggested by 450K array. A thorough literature search suggested that 38 genes play roles in spermatogenesis (PDHA2, PARP12, FHIT, RPTOR, GSTM1, GSTM5, MAGI2, BCAN, DDB2, KDM4C, AGPAT3, CAMTA1, CCR6, CUX1, DNAH17, ELMO1, FNDC3B, GNRHR, HDAC4, IRS2, LIF, SMAD3, SOD3, TALDO1, TRIM27, GAA, PAX8, RNF39, HLA-C, HLA-DRB6), are testis enriched (NFATC1, NMNAT3, PIAS2, SRPK2, WDR36, WWP2), or show methylation differences between infertile cases and controls (PTPRN2, RPH3AL). CONCLUSION(S): We found a statistically significant correlation between peripheral blood DNA methylation and male infertility, raising the hope that epigenome-based blood markers can be used for screening male infertility risk. The study also identified new candidates for spermatogenesis and fertility.

Computational and Statistical Analysis of Array-Based DNA Methylation Data.

The characterization of aberrant DNA methylation is emerging as a key part of the study of cancer development and phenotype. The technical advancements and decreasing costs of methods for high-throughput profiling of DNA methylation have brought about a high interest in the use of such methods in disease association studies. Here we discuss the principles for DNA methylation analysis using data from the Infinium DNA methylation BeadChip assays and describe the computational steps and statistical considerations going from processing of the raw array data to analysis of differential methylation. Moreover, we provide detailed guidelines on how to perform tumor subtype classification based on DNA methylation signatures.

Integration of DNA methylation patterns and genetic variation in human pediatric tissues help inform EWAS design and interpretation.

BACKGROUND: The widespread use of accessible peripheral tissues for epigenetic analyses has prompted increasing interest in the study of tissue-specific DNA methylation (DNAm) variation in human populations. To date, characterizations of inter-individual DNAm variability and DNAm concordance across tissues have been largely performed in adult tissues and therefore are limited in their relevance to DNAm profiles from pediatric samples. Given that DNAm patterns in early life undergo rapid changes and have been linked to a wide range of health outcomes and environmental exposures, direct investigations of tissue-specific DNAm variation in pediatric samples may help inform the design and interpretation of DNAm analyses from early life cohorts. In this study, we present a systematic comparison of genome-wide DNAm patterns between matched pediatric buccal epithelial cells (BECs) and peripheral blood mononuclear cells (PBMCs), two of the most widely used peripheral tissues in human epigenetic studies. Specifically, we assessed DNAm variability, cross-tissue DNAm concordance and genetic determinants of DNAm across two independent early life cohorts encompassing different ages. RESULTS: BECs had greater inter-individual DNAm variability compared to PBMCs and highly the variable CpGs are more likely to be positively correlated between the matched tissues compared to less variable CpGs. These sites were enriched for CpGs under genetic influence, suggesting that a substantial proportion of DNAm covariation between tissues can be attributed to genetic variation. Finally, we demonstrated the relevance of our findings to human epigenetic studies by categorizing CpGs from published DNAm association studies of pediatric BECs and peripheral blood. CONCLUSIONS: Taken together, our results highlight a number of important considerations and practical implications in the design and interpretation of EWAS analyses performed in pediatric peripheral tissues.

DNA methylation profiling allows for characterization of atrial and ventricular cardiac tissues and hiPSC-CMs.

BACKGROUND: Cardiac disease modelling using human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CM) requires thorough insight into cardiac cell type differentiation processes. However, current methods to discriminate different cardiac cell types are mostly time-consuming, are costly and often provide imprecise phenotypic evaluation. DNA methylation plays a critical role during early heart development and cardiac cellular specification. We therefore investigated the DNA methylation pattern in different cardiac tissues to identify CpG loci for further cardiac cell type characterization. RESULTS: An array-based genome-wide DNA methylation analysis using Illumina Infinium HumanMethylation450 BeadChips led to the identification of 168 differentially methylated CpG loci in atrial and ventricular human heart tissue samples (n = 49) from different patients with congenital heart defects (CHD). Systematic evaluation of atrial-ventricular DNA methylation pattern in cardiac tissues in an independent sample cohort of non-failing donor hearts and cardiac patients using bisulfite pyrosequencing helped us to define a subset of 16 differentially methylated CpG loci enabling precise characterization of human atrial and ventricular cardiac tissue samples. This defined set of reproducible cardiac tissue-specific DNA methylation sites allowed us to consistently detect the cellular identity of hiPSC-CM subtypes. CONCLUSION: Testing DNA methylation of only a small set of defined CpG sites thus makes it possible to distinguish atrial and ventricular cardiac tissues and cardiac atrial and ventricular subtypes of hiPSC-CMs. This method represents a rapid and reliable system for phenotypic characterization of in vitro-generated cardiomyocytes and opens new opportunities for cardiovascular research and patient-specific therapy.

Replicated methylation changes associated with eczema herpeticum and allergic response.

BACKGROUND: Although epigenetic mechanisms are important risk factors for allergic disease, few studies have evaluated DNA methylation differences associated with atopic dermatitis (AD), and none has focused on AD with eczema herpeticum (ADEH+). We will determine how methylation varies in AD individuals with/without EH and associated traits. We modeled differences in genome-wide DNA methylation in whole blood cells from 90 ADEH+, 83 ADEH-, and 84 non-atopic, healthy control subjects, replicating in 36 ADEH+, 53 ADEH-, and 55 non-atopic healthy control subjects. We adjusted for cell-type composition in our models and used genome-wide and candidate-gene approaches. RESULTS: We replicated one CpG which was significantly differentially methylated by severity, with suggestive replication at four others showing differential methylation by phenotype or severity. Not adjusting for eosinophil content, we identified 490 significantly differentially methylated CpGs (ADEH+ vs healthy controls, genome-wide). Many of these associated with severity measures, especially eosinophil count (431/490 sites). CONCLUSIONS: We identified a CpG in IL4 associated with serum tIgE levels, supporting a role for Th2 immune mediating mechanisms in AD. Changes in eosinophil level, a measure of disease severity, are associated with methylation changes, providing a potential mechanism for phenotypic changes in immune response-related traits.