Methylation microarray-based detection of clinical copy-number aberrations in CLL benchmarked to standard FISH analysis.

Copy-number aberrations (CNAs) are assessed using FISH analysis in diagnostics of chronic lymphocytic leukemia (CLL), but CNAs can also be extrapolated from Illumina BeadChips developed for genome-wide methylation microarray screening. Increasing numbers of microarray data-sets are available from diagnostic samples, making it useful to assess the potential in CNA diagnostics. We benchmarked the limitations of CNA testing from two Illumina BeadChips (EPIC and 450k) and using two common packages for analysis (conumee and ChAMP) to FISH-based assessment of 11q, 13q, and 17p deletions in 202 CLL samples. Overall, the two packages predicted CNAs with similar accuracy regardless of the microarray type, but lower than FISH-based assessment. We showed that the bioinformatics analysis needs to be adjusted to the specific CNA, as no general settings were identified. Altogether, we were able to predict CNAs using methylation microarray data, however, with limited accuracy, making FISH-based assessment of deletions the superior diagnostic choice.

DNA methylome in pancreatic cancer identified novel promoter hyper-methylation in NPY and FAIM2 genes associated with poor prognosis in Indian patient cohort.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is one of the leading cancers worldwide and has a poor survival, with a 5-year survival rate of only 8.5%. In this study we investigated altered DNA methylation associated with PDAC severity and prognosis. METHODS: Methylome data, generated using 450 K bead array, was compared between paired PDAC and normal samples in the TCGA cohort (n = 9) and our Indian cohort (n = 7). The total Indian Cohort (n = 75) was split into cohort 1 (n = 7), cohort 2 (n = 22), cohort 3 (n = 26) and cohort 4 (n = 20).Validation of differential methylation (6 selected CpG loci) and associated gene expression for differentially methylated genes (10 selected gDMs) were carried out in separate validation cohorts, using MSP, RT-PCR and IHC correlations between methylation and gene expression were observed in TCGA, GTEx cohorts and in validation cohorts. Kaplan-Meier survival analysis was done to study differential prognosis, during 2-5 years of follow-up. RESULTS: We identified 156 DMPs, mapped to 91 genes (gDMs), in PDAC; 68 (43.5%) DMPs were found to be differentially methylated both in TCGA cohort and our cohort, with significant concordance at hypo- and hyper-methylated loci. Enrichments of "regulation of ion transport", "Interferon alpha/beta signalling", "morphogenesis and development" and "transcriptional dysregulation" pathways were observed among 91 gDMs. Hyper-methylation of NPY and FAIM2 genes with down-regulated expression in PDAC, were significantly associated with poor prognosis in the Indian patient cohort. CONCLUSIONS: Ethnic variations among populations may determine the altered epigenetic landscape in the PDAC patients of the Indian cohort. Our study identified novel differentially methylated genes (mainly NPY and FAIM2) and also validated the previously identified differentially methylated CpG sites associated with PDAC cancer patient's survival. Comparative analysis of our data with TCGA and CPTAC cohorts showed that both NPY and FAIM2 hyper-methylation and down-regulations can be novel epigenetically regulated genes in the Indian patient population, statistically significantly associated with poor survival and advanced tumour stages.

Critical evaluation of copy number variant calling methods using DNA methylation.

Recent technological and methodological developments have enabled the use of array-based DNA methylation data to call copy number variants (CNVs). ChAMP, Conumee, and cnAnalysis450k are popular methods currently used to call CNVs using methylation data. However, so far, no studies have analyzed the reliability of these methods using real samples. Data from a cohort of individuals with genotype and DNA methylation data generated using the HumanMethylation450 and MethylationEPIC BeadChips were used to assess the consistency between the CNV calls generated by methylation and genotype data. We also took advantage of repeated measures of methylation data collected from the same individuals to compare the reliability of CNVs called by ChAMP, Conumee, and cnAnalysis450k for both the methylation arrays. ChAMP identified more CNVs than Conumee and cnAnalysis450k for both the arrays and, as a consequence, had a higher overlap (~62%) with the calls from the genotype data. However, all methods had relatively low reliability. For the MethylationEPIC array, Conumee had the highest reliability (57.6%), whereas for the HumanMethylation450 array, cnAnalysis450k had the highest reliability (43.0%). Overall, the MethylationEPIC array provided significant gains in reliability for CNV calling over the HumanMethylation450 array but not for overlap with CNVs called using genotype data.

Integrated differential DNA methylation and gene expression of formalin-fixed paraffin-embedded uveal melanoma specimens identifies genes associated with early metastasis and poor prognosis.

PURPOSE: Uveal melanoma (UM) is an aggressive malignancy, in which nearly 50% of the patients die from metastatic disease. Aberrant DNA methylation is recognized as an important epigenomic event in carcinogenesis. Formalin-fixed paraffin-embedded (FFPE) samples represent a valuable source of tumor tissue, and recent technology has enabled the use of these samples in genome-wide DNA methylation analyses. Our aim was to investigate differential DNA methylation in relation to histopathological classification and survival data. In addition we sought to identify aberrant DNA methylation of genes that could be associated with metastatic disease and poor survival. METHODS: FFPE samples from UM patients (n = 23) who underwent enucleation of the eye in the period 1976-1989 were included. DNA methylation was assessed using the Illumina Infinium HumanMethylation450 array and coupled to histopathological data, Cancer Registry of Norway- (registered UM metastasis) and Norwegian Cause of Death Registry- (time and cause of death) data. Differential DNA methylation patterns contrasting histological classification, survival data and clustering properties were investigated. Survival groups were defined as "Early metastasis" (metastases and death within 2-5 years after enucleation, n = 8), "Late metastasis" (metastases and death within 9-21 years after enucleation, n = 7) and "No metastasis" (no detected metastases ≥18 years after enucleation, n = 8). A subset of samples were selected based on preliminary multi-dimensional scaling (MDS) plots, histopathological classification, chromosome 3 status, survival status and clustering properties; "Subset Early metastasis" (n = 4) vs "Subset No metastasis" (n = 4). Bioinformatics analyses were conducted in the R statistical software. Differentially methylated positions (DMPs) and differentially methylated regions (DMRs) in various comparisons were assessed. Gene expression of relevant subgroups was determined by microarray analysis and quantitative reverse-transcription polymerase chain reaction (qRT-PCR). RESULTS: DNA methylation analyses identified 2 clusters that separated the samples according to chromosome 3 status. Cluster 1 consisted of samples (n = 5) with chromosome 3 disomy (D3), while Cluster 2 was comprised of samples (n = 15) with chromosome 3 monosomy (M3). 1212 DMRs and 9386 DMPs were identified in M3 vs D3. No clear clusters were formed based on our predefined survival groups ("Early", "Late", "No") nor histopathological classification (Epithelioid, Mixed, Spindle). We identified significant changes in DNA methylation (beta FC ≥ 0.2, adjusted p < 0.05) between two sample subsets (n = 8). "Subset Early metastasis" (n = 4) vs "Subset No metastasis" (n = 4) identified 348 DMPs and 36 DMRs, and their differential gene expression by microarray showed that 14 DMPs and 2 DMRs corresponded to changes in gene expression (FC ≥ 1.5, p < 0.05). RNF13, ZNF217 and HYAL1 were hypermethylated and downregulated in "Subset Early metastasis" vs "Subset No metastasis" and could be potential tumor suppressors. TMEM200C, RGS10, ADAM12 and PAM were hypomethylated and upregulated in "Subset Early metastasis vs "Subset No metastasis" and could be potential oncogenes and thus markers of early metastasis and poor prognosis in UM. CONCLUSIONS: DNA methylation profiling showed differential clustering of samples according to chromosome 3 status: Cluster 1 (D3) and Cluster 2 (M3). Integrated differential DNA methylation and gene expression of two subsets of samples identified genes associated with early metastasis and poor prognosis. RNF13, ZNF217 and HYAL1 are hypermethylated and candidate tumor suppressors, while TMEM200C, RGS10, ADAM12 and PAM are hypomethylated and candidate oncogenes linked to early metastasis. UM FFPE samples represent a valuable source for methylome studies and enable long-time follow-up.

Differential methylation of genes in the human placenta associated with bisphenol A exposure.

Prenatal exposure to bisphenol A (BPA) is associated with numerous adverse health outcomes among offspring. Although DNA methylation is considered one of the underlying causes of these associations, few studies have focused on the association between prenatal BPA exposure and DNA methylation in the human placenta. In this study, we examined the association between prenatal BPA exposure and DNA methylation in the placenta of 146 mother-infant pairs from the Shanghai-Minhang Birth Cohort Study. BPA concentrations in maternal urine samples were measured using high-performance liquid chromatography. Six placenta samples were selected for whole-genome methylation analysis using Infinium Human Methylation 450K Beadchip, followed by pyrosequencing-based methylation analysis of three selected genes in 146 placentas. Among 282 differentially methylated CpGs, representing 208 genes, 127 were hypermethylated, and 155 were hypomethylated in the BPA exposure group. Prenatal BPA exposure was associated with a higher methylation level of HLA-DRB6 in individuals as determined using pyrosequencing, which was consistent with the whole-genome methylation analysis results. Compared with that subjects with low BPA exposure, the methylation level (ln-transformed) of HLA-DRB6 in placentas from those with high BPA exposure increased by 0.29% (95% confidence interval[CI]: 0.02%, 0.56%) at the CpG2 site, and the average methylation level (ln-transformed) of the three CpG sites increased by 0.30% (95%CI: -0.03%, 0.63%). Our findings provide evidence that prenatal BPA exposure might alter DNA methylation levels in the placenta.

Genome-Wide DNA Methylation Analysis of a Cohort of 41 Patients Affected by Oculo-Auriculo-Vertebral Spectrum (OAVS).

Oculo-auriculo-vertebral-spectrum (OAVS; OMIM 164210) is a rare disorder originating from abnormal development of the first and second branchial arch. The clinical phenotype is extremely heterogeneous with ear anomalies, hemifacial microsomia, ocular defects, and vertebral malformations being the main features. MYT1, AMIGO2, and ZYG11B gene variants were reported in a few OAVS patients, but the etiology remains largely unknown. A multifactorial origin has been proposed, including the involvement of environmental and epigenetic mechanisms. To identify the epigenetic mechanisms contributing to OAVS, we evaluated the DNA-methylation profiles of 41 OAVS unrelated affected individuals by using a genome-wide microarray-based methylation approach. The analysis was first carried out comparing OAVS patients with controls at the group level. It revealed a moderate epigenetic variation in a large number of genes implicated in basic chromatin dynamics such as DNA packaging and protein-DNA organization. The alternative analysis in individual profiles based on the searching for Stochastic Epigenetic Variants (SEV) identified an increased number of SEVs in OAVS patients compared to controls. Although no recurrent deregulated enriched regions were found, isolated patients harboring suggestive epigenetic deregulations were identified. The recognition of a different DNA methylation pattern in the OAVS cohort and the identification of isolated patients with suggestive epigenetic variations provide consistent evidence for the contribution of epigenetic mechanisms to the etiology of this complex and heterogeneous disorder.

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.

Identification of methylation states of DNA regions for Illumina methylation BeadChip.

BACKGROUND: Methylation of cytosine bases in DNA is a critical epigenetic mark in many eukaryotes and has also been implicated in the development and progression of normal and diseased cells. Therefore, profiling DNA methylation across the genome is vital to understanding the effects of epigenetic. In recent years the Illumina HumanMethylation450 (HM450K) and MethylationEPIC (EPIC) BeadChip have been widely used to profile DNA methylation in human samples. The methods to predict the methylation states of DNA regions based on microarray methylation datasets are critical to enable genome-wide analyses. RESULT: We report a computational approach based on the two layers two-state hidden Markov model (HMM) to identify methylation states of single CpG site and DNA regions in HM450K and EPIC BeadChip. Using this mothed, all CpGs detected by HM450K and EPIC in H1-hESC and GM12878 cell lines are identified as un-methylated, middle-methylated and full-methylated states. A large number of DNA regions are segmented into three methylation states as well. Comparing the identified regions with the result from the whole genome bisulfite sequencing (WGBS) datasets segmented by MethySeekR, our method is verified. Genome-wide maps of chromatin states show that methylation state is inversely correlated with active histone marks. Genes regulated by un-methylated regions are expressed and regulated by full-methylated regions are repressed. Our method is illustrated to be useful and robust. CONCLUSION: Our method is valuable for DNA methylation genome-wide analyses. It is focusing on identification of DNA methylation states on microarray methylation datasets. For the features of array datasets, using two layers two-state HMM to identify to methylation states on CpG sites and regions creatively, our method which takes into account the distribution of genome-wide methylation levels is more reasonable than segmentation with a fixed threshold.

Epigenome-wide DNA methylation and risk of breast cancer: a systematic review.

BACKGROUND: DNA methylation is a potential biomarker for early detection of breast cancer. However, robust evidence of a prospective relationship between DNA methylation patterns and breast cancer risk is still lacking. The objective of this study is to provide a systematic analysis of the findings of epigenome-wide DNA methylation studies on breast cancer risk, in light of their methodological strengths and weaknesses. METHODS: We searched major databases (MEDLINE, EMBASE, Web of Science, CENTRAL) from inception up to 30th June 2019, for observational or intervention studies investigating the association between epigenome-wide DNA methylation (using the HM450k or EPIC BeadChip), measured in any type of human sample, and breast cancer risk. A pre-established protocol was drawn up following the Cochrane Reviews rigorous methodology. Study selection, data abstraction, and risk of bias assessment were performed by at least two investigators. A qualitative synthesis and systematic comparison of the strengths and weaknesses of studies was performed. RESULTS: Overall, 20 studies using the HM450k BeadChip were included, 17 of which had measured blood-derived DNA methylation. There was a consistent trend toward an association of global blood-derived DNA hypomethylation and higher epigenetic age with higher risk of breast cancer. The strength of associations was modest for global hypomethylation and relatively weak for most of epigenetic age algorithms. Differences in length of follow-up periods may have influenced the ability to detect associations, as studies reporting follow-up periods shorter than 10 years were more likely to observe an association with global DNA methylation. Probe-wise differential methylation analyses identified between one and 806 differentially methylated CpGs positions in 10 studies. None of the identified differentially methylated sites overlapped between studies. Three studies used breast tissue DNA and suffered major methodological issues that precludes any conclusion. Overall risk of bias was critical mainly because of incomplete control of confounding. Important issues relative to data preprocessing could have limited the consistency of results. CONCLUSIONS: Global DNA methylation may be a short-term predictor of breast cancer risk. Further studies with rigorous methodology are needed to determine spatial distribution of DNA hypomethylation and identify differentially methylated sites associated with risk of breast cancer. PROSPERO REGISTRATION NUMBER: CRD42020147244.

Epigenome Wide Association and Stochastic Epigenetic Mutation Analysis on Cord Blood of Preterm Birth.

Preterm birth (PTB) can be defined as the endpoint of a complex process that could be influenced by maternal and environmental factors. Epigenetics recently emerged as an interesting field of investigation since it represents an important mechanism of regulation. This study evaluates epigenetic impact of preterm birth on DNA methylation. Genome-wide DNAm was measured using the Illumina 450K array in cord blood samples obtained from 72 full term and 18 preterm newborns. Lymphocyte composition was calculated based on specific epigenetic markers that are present on the 450k array. Differential methylation analysis was performed both at site and region level; moreover, stochastic epigenetic mutations (SEMs) were also evaluated. The study showed significant differences in blood cell composition between the two groups. Moreover, after multiple testing correction, statistically significant differences in DNA methylation levels emerged between the two groups both at site and region levels. Results obtained were compared to those reported by previous EWAS, leading to a list of more consistent genes associated with PTB. Finally, the SEMs analysis revealed that the burden of SEMs resulted significantly higher in the preterm group. In conclusion, PTB resulted associated to specific epigenetic signatures that involve immune system. Moreover, SEMs analysis revealed an increased epigenetic drift at birth in the preterm group.

A framework for analyzing DNA methylation data from Illumina Infinium HumanMethylation450 BeadChip.

BACKGROUND: DNA methylation has been identified to be widely associated to complex diseases. Among biological platforms to profile DNA methylation in human, the Illumina Infinium HumanMethylation450 BeadChip (450K) has been accepted as one of the most efficient technologies. However, challenges exist in analysis of DNA methylation data generated by this technology due to widespread biases. RESULTS: Here we proposed a generalized framework for evaluating data analysis methods for Illumina 450K array. This framework considers the following steps towards a successful analysis: importing data, quality control, within-array normalization, correcting type bias, detecting differentially methylated probes or regions and biological interpretation. CONCLUSIONS: We evaluated five methods using three real datasets, and proposed outperform methods for the Illumina 450K array data analysis. Minfi and methylumi are optimal choice when analyzing small dataset. BMIQ and RCP are proper to correcting type bias and the normalized result of them can be used to discover DMPs. R package missMethyl is suitable for GO term enrichment analysis and biological interpretation.

Genome-wide DNA methylation assessment of 'BRCA1-like' early-onset breast cancer: Data from the Australian Breast Cancer Family Registry.

Breast cancers arising in women carrying a germline mutation in BRCA1 are typically high-grade, early-onset and have distinct morphological features (BRCA1-like). However, the majority of early-onset breast cancers of this morphological type are not associated with germline BRCA1 mutations or constitutional BRCA1 promoter methylation. We aimed to assess DNA methylation across the genome for associations with the "BRCA1-like" morphology. Genome-wide methylation in blood-derived DNA was measured using the Infinium HumanMethylation450K BeadChip assay for women under the age of 40 years participating in the Australian Breast Cancer Family Study (ABCFS) diagnosed with: i) BRCA1-like breast cancer (n = 30); and ii) breast cancer without BRCA1-like morphological features (non BRCA1-like; n = 30), and age-matched unaffected women (controls; n = 30). Corresponding tumour-derived DNA from 43 of the affected women was also assessed. Methylation of blood-derived DNA was found to be elevated across 17 consecutive marks in the BRCA1 promoter region and decreased at several other genomic regions (including TWIST2 and CTBP1) for 7 women (23%) diagnosed with BRCA1-like breast cancer compared with women in the other groups. Corresponding tumour-derived DNA available from 5 of these 7 women had elevated methylation within the BRCA1 and SPHK2 promoter region and decreased methylation within the ADAP1, IGF2BP3 and SPATA13 promoter region when compared with the other breast tumours. These methylation marks could be biomarkers of risk for BRCA1-like breast cancer, and could be responsible in part for their distinctive morphological features and biology. As such, they may assist with prevention and targeted therapies for this cancer subtype.

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.

Investigation of correlations between DNA methylation, suicidal behavior and aging.

OBJECTIVES: Suicidal behavior (SB) is a major cause of mortality for patients diagnosed with bipolar disorder (BD). In this study, we investigated epigenetic differences in BD participants with and without a history of SB. METHODS: We used suicidality scores constructed from Schedule for Clinical Assessments in Neuropsychiatry (SCAN) interview questions about suicidal thought and behavior to identify individuals from a BD cohort of n=452; participants with the most extreme high (H-SB, n=18) and most extreme low (L-SB, n=22) scores were used as cases and controls, respectively. Epigenome-wide DNA methylation patterns were compared between the two groups using the Illumina Infinium Human Methylation 450 BeadChip microarray. DNA methylation age was compared to chronological tissue age. RESULTS: We observed highly significant differences in methylation between cases and controls in three genomic regions enriched for epigenetic modifications corresponding to gene regulatory regions. BD participants with a history of SB showed less overall methylation in the 5' untranslated region of Membrane palmitoylated protein 4 (MPP4) (P=7.42×10-7 ) and in intron 3 of TRE2/BUB2/CDC16 domain family member 16 (TBC1D16) (P=6.47×10-7 ), while exon 1 of Nucleoporin 133 (NUP133) was less methylated in controls (P=1.17x10-6 ). Moreover, we observed a greater correlation between DNA methylation age and tissue age in controls (r=.91, P<.0001) than in the H-SB group (r=.83, P<.0001). CONCLUSIONS: We report significant findings at three loci based on a methylome scan of participants with BD for an SB phenotype, and potentially altered molecular aging in suicide attempters. Despite the small sample size, our proof-of-concept study highlights the potential for epigenetic factors to be useful in understanding the molecular underpinnings of suicide with the ultimate aim of its prevention.

Concordance of DNA methylation profiles between breast core biopsy and surgical excision specimens containing ductal carcinoma in situ (DCIS).

The utility and reliability of assessing molecular biomarkers for translational applications on pre-operative core biopsy specimens assume consistency of molecular profiles with larger surgical specimens. Whether DNA methylation in ductal carcinoma in situ (DCIS), measured in core biopsy and surgical specimens are similar, remains unclear. Here, we compared genome-scale DNA methylation measured in matched core biopsy and surgical specimens from DCIS, including specific DNA methylation biomarkers of subsequent invasive cancer. DNA was extracted from guided 2mm cores of formalin fixed paraffin embedded (FFPE) specimens, bisulfite-modified, and measured on the Illumina HumanMethylation450 BeadChip. DNA methylation profiles of core biopsies exhibited high concordance with matched surgical specimens. Within-subject variability in DNA methylation was significantly lower than between-subject variability (all P<2.20E-16). In 641 CpGs whose methylation was related with increased hazard of invasive breast cancer, lower within-subject than between-subject variability was observed in 92.3% of the study participants (P<0.05). Between patient-matched core biopsy and surgical specimens, <0.6% of CpGs measured had changes in median DNA methylation >15%, and a pathway analysis of these CpGs indicated enrichment for genes related with wound healing. Our results indicate that DNA methylation measured in core biopsies are representative of the matched surgical specimens and suggest that DCIS biomarkers measured in core biopsies can inform clinical decision-making.

Methylome analysis reveals alterations in DNA methylation in the regulatory regions of left ventricle development genes in human dilated cardiomyopathy.

Dilated cardiomyopathy (DCM) is one of the main causes of heart failure (called cardiomyopathies) in adults. Alterations in epigenetic regulation (i.e., DNA methylation) have been implicated in the development of DCM. Here, we identified a total of 1828 differentially methylated probes (DMPs) using the Infinium 450K HumanMethylation Bead chip by comparing the methylomes between 18 left ventricles and 9 right ventricles. Alterations in DNA methylation levels were observed mainly in lowly methylated regions corresponding to promoter-proximal regions, which become hypermethylated in severely affected left ventricles. Subsequent mRNA microarray analysis showed that the effect of DNA methylation on gene expression regulation is not unidirectional but is controlled by the functional sub-network context. DMPs were significantly enriched in the transcription factor binding sites (TFBSs) we tested. Alterations in DNA methylation were specifically enriched in the cis-regulatory regions of cardiac development genes, the majority of which are involved in ventricular development (e.g., TBX5 and HAND1).

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.

Genome-wide DNA methylation patterns in CD4+ T cells from Chinese Han patients with rheumatoid arthritis.

INTRODUCTION: Rheumatoid arthritis (RA) is an autoimmune disease that causes chronic inflammation of the joints. Recent evidence indicated the epigenetic changes may contribute to the pathogenesis of RA. METHOD: To understand the extent and nature of dysregulated DNA methylation in RA CD4T cells, we performed a genome-wide DNA methylation study in CD4 + T cells in 12 RA patients compared to 12 matched normal healthy controls. Cytosine methylation status was quantified with Illumina methylation 450K microarray. RESULT: The DNA methylation profiling showed 383 hyper- and 785 hypo-methylated genes in the CD4 + T cells of the RA patients (p < 3.4 × 10-7). Gene ontology analysis indicated transcript alternative splicing and protein modification mediated by DNA methylation might play an important role in the pathogenesis of RA. In addition, the result showed that human leukocyte antigen (HLA) region including HLA-DRB6, HLA-DQA1 and HLA-E was frequently hypomethylated, but HLA-DQB1 hypermethylated in CpG island region and hypomethylated in CpG shelf region in RA patients. Outside the MHC region, HDAC4, NXN, TBCD and TMEM61 were the most hypermethylated genes, while ITIH3, TCN2, PRDM16, SLC1A5 and GALNT9 are the most hypomethylated genes. CONCLUSION: Genome-wide DNA methylation profile revealed significant DNA methylation change in CD4 + T cells from patients with RA.

MethPed: an R package for the identification of pediatric brain tumor subtypes.

BACKGROUND: DNA methylation profiling of pediatric brain tumors offers a new way of diagnosing and subgrouping these tumors which improves current clinical diagnostics based on histopathology. We have therefore developed the MethPed classifier, which is a multiclass random forest algorithm, based on DNA methylation profiles from many subgroups of pediatric brain tumors. RESULTS: We developed an R package that implements the MethPed classifier, making it easily available and accessible. The package can be used for estimating the probability that an unknown sample belongs to each of nine pediatric brain tumor diagnoses/subgroups. CONCLUSIONS: The MethPed R package efficiently classifies pediatric brain tumors using the developed MethPed classifier. MethPed is available via Bioconductor: http://bioconductor.org/packages/MethPed/.