Restriction Enzyme Analysis Of Methylation Research Articles

Use of genome-wide DNA methylation analysis to identify prognostic CpG site markers associated with longer survival time in dogs with multicentric high-grade B-cell lymphoma.

DNA methylation analysis might identify prognostic CpG sites in CHOP-treated dogs with multicentric high-grade B-cell lymphoma (MHGL) with heterogenous prognosis. To identify prognostic CpG sites of MHGL through genome-wide DNA methylation analysis with pyrosequencing validation. Test group: 24 dogs. Validation group: 100 dogs. All client-owned dogs were diagnosed with MHGL and treated with CHOP chemotherapy. Cohort study. DNA was extracted from lymph node samples obtained via FNA. Genome-wide DNA methylation analysis using Digital Restriction Enzyme Analysis of Methylation (DREAM) was performed on the test group to identify differentially methylated CpG sites (DMCs). Bisulfite pyrosequencing was used to measure methylation status of candidate DMCs in the validation group. Median survival times (MST) were analyzed using Kaplan-Meier (log-rank) product limit method. DREAM analyzed 101 576 CpG sites. Hierarchical clustering of 16 262 CpG sites in test group identified group with better prognosis (MST = 55-477 days vs 10-301 days, P = .007). Volcano plot identified 1371 differentially methylated CpG sites (DMCs). DMC near the genes of FAM213A (DMC-F) and PHLPP1 (DMC-P) were selected as candidates. Bisulfite-pyrosequencing performed on validation group showed group with methylation level of DMC-F < 40% had favorable prognosis (MST = 11-1072 days vs 8-1792 days, P = .01), whereas group with the methylation level combination of DMC-F < 40% plus DMC-P < 10% had excellent prognosis (MST = 18-1072 days vs 8-1792 days, P = .009). Methylation status of prognostic CpG sites delineate canine MGHL cases with longer MST, providing owners with information on expectations of potential improved treatment outcomes.

Error-Corrected Next-Generation Sequencing Provides a Comprehensive Overview of the Subclonal Mutation Landscape and Its Prognostic Implications in Juvenile Myelomonocytic Leukemia

Introduction: Juvenile myelomonocytic leukemia (JMML) is a rare pediatric myelodysplastic/myeloproliferative neoplasm characterized by mutations in genes activating the RAS pathway ( PTPN11, NF1, NRAS, KRAS, and CBL). Approximately 20% of patients with JMML have secondary mutations in SETBP1 and/or JAK3, and recent droplet digital PCR (ddPCR) analyses revealed that mutations in these two genes, including very rare mutations (variant allele frequency [VAF] &amp;lt; 0.05) that are difficult to detect by conventional next-generation sequencing (NGS), are associated with poor prognoses. Meanwhile, the landscape of low VAF subclonal mutations of other genes in patients with JMML has not been adequately evaluated. Therefore, we utilized error-corrected NGS, which can reduce the systematic sequencing error rate of conventional NGS by incorporating molecular barcodes (MBCs). Methods: We performed error-corrected NGS in 93 patients with JMML and 11 patients with JMML-like myeloproliferative disorder with Noonan syndrome (NS/MPD) using a small panel associated with myeloid malignancies. Samples for error-corrected NGS were prepared using a SureSelect XT HS2 DNA Library Preparation Kit (Agilent Technologies), including unique dual index and duplex MBCs. A unique MBC is incorporated into each DNA fragment, and the incorporated MBC can differentiate true and false duplications, allowing for highly accurate sequencing that can detect mutations with VAF &amp;gt; 0.001. We used the HiSeq X platform (Illumina) and SureCall v.4.2 application (Agilent Technologies) for analysis. In addition, DNA methylation analysis was performed on the same cohort using the Infinium HumanMethylation 450K BeadChip and/or Digital Restriction Enzyme Analysis of Methylation as previously described (Murakami et al. 2018;131:1576-1586, Kitazawa et al. Blood Adv. 2021;5:5507-5518). This study was approved by the Ethics Committee of the Nagoya University Graduate School of Medicine. Results: In the cohort of 104 patients with JMML or NS/MPD, 160 mutations were identified, of which 30 (19%) had VAF &amp;lt; 0.05 (eight in JAK3, seven in NF1, five in ASXL1, three in NRAS, two each in PTPN11 and SOS1, and one each in SETBP1, SH2B3, and ZRSR2). Subclonal mutations in SETBP1 p.D868N and JAK3 p.R657Q identified by error-corrected NGS were confirmed using ddPCR, and consistent results were obtained for both assays (R 2 = 0.9977 and 0.9919 respectively). Of 93 patients with JMML, 30 (32%) had subclonal or clonal secondary mutations, whereas no such mutations were detected in patients with NS/MPD ( P = 0.031). Of 104 patients, 23 (22%) had secondary mutations with VAF ≥ 0.05 (Major group), 7 (7%) only had secondary mutations with VAF &amp;lt; 0.05 (Minor group), and the remaining 74 (71%) had no secondary mutations (Negative group). We assessed the associations of subclonal mutations detected by error-corrected NGS with the DNA methylation profile, the most important prognostic factor in JMML. Whereas 22 of 23 (96%) and 5 of 7 (71%) patients in the Major and Minor groups, respectively, had high methylation (HM) profiles, only 20 of 74 (27%) patients in the Negative group featured HM profiles ( P &amp;lt; 0.001). The 4-year overall survival (OS) rates were significantly lower in the Major (52.2% [95% confidence interval {CI} = 30.5%-70.0%], P = 0.01) and Minor groups (42.9% [95% CI = 9.8%-73.4%], P = 0.03) than in the Negative group (76.3% [95% CI = 64.6%-84.5%]). In a subgroup analysis of 30 patients with secondary mutations, patients with secondary mutations in RAS pathway genes (n = 18) had significantly lower 4-year OS rates than those with secondary mutations in other genes (n = 12; 32.4% [95% CI = 12.7%-54.0%] vs. 75.0% [95% CI: 40.8%-91.2%], P = 0.047). Conclusions: We successfully performed error-corrected NGS to assess comprehensive subclonal secondary mutational profiles, including very low VAF variants. The presence of subclonal mutations, particularly in RAS pathway genes, was associated with poor OS. These findings provide important information for appropriate risk stratification, which will contribute to the implementation of precision medicine for patients with JMML.

Hypomethylation in MTNR1B: a novel epigenetic marker for atherosclerosis profiling using stenosis radiophenotype and blood inflammatory cells

BackgroundChanges in gene-specific promoter methylation may result from aging and environmental influences. Atherosclerosis is associated with aging and environmental effects. Thus, promoter methylation profiling may be used as an epigenetic tool to evaluate the impact of aging and the environment on atherosclerosis development. However, gene-specific methylation changes are currently inadequate epigenetic markers for predicting atherosclerosis and cardiovascular disease pathogenesis.ResultsWe profiled and validated changes in gene-specific promoter methylation associated with atherosclerosis using stenosis radiophenotypes of cranial vessels and blood inflammatory cells rather than direct sampling of atherosclerotic plaques. First, we profiled gene-specific promoter methylation changes using digital restriction enzyme analysis of methylation (DREAM) sequencing in peripheral blood mononuclear cells from eight samples each of cranial vessels with and without severe-stenosis radiophenotypes. Using DREAM sequencing profiling, 11 tags were detected in the promoter regions of the ACVR1C, ADCK5, EFNA2, ENOSF1, GLS2, KNDC1, MTNR1B, PACSIN3, PAX8-AS1, TLDC1, and ZNF7 genes. Using methylation evaluation, we found that EFNA2, ENOSF1, GLS2, KNDC1, MTNR1B, PAX8-AS1, and TLDC1 showed > 5% promoter methylation in non-plaque intima, atherosclerotic vascular tissues, and buffy coats. Using logistic regression analysis, we identified hypomethylation of MTNR1B as an independent variable for the stenosis radiophenotype prediction model by combining it with traditional atherosclerosis risk factors including age, hypertension history, and increases in creatinine, lipoprotein (a), and homocysteine. We performed fivefold cross-validation of the prediction model using 384 patients with ischemic stroke (50 [13%] no-stenosis and 334 [87%] > 1 stenosis radiophenotype). For the cross-validation, the training dataset included 70% of the dataset. The prediction model showed an accuracy of 0.887, specificity to predict stenosis radiophenotype of 0.940, sensitivity to predict no-stenosis radiophenotype of 0.533, and area under receiver operating characteristic curve of 0.877 to predict stenosis radiophenotype from the test dataset including 30% of the dataset.ConclusionsWe identified and validated MTNR1B hypomethylation as an epigenetic marker to predict cranial vessel atherosclerosis using stenosis radiophenotypes and blood inflammatory cells rather than direct atherosclerotic plaque sampling.

Whole human genome 5’-mC methylation analysis using long read nanopore sequencing

ABSTRACT Methylation microarray and bisulphite sequencing are often used to study 5’-methylcytosine (5’-mC) modification of CpG dinucleotides in the human genome. Although both technologies produce trustworthy results, the evaluation of the methylation status of CpG sites suffers from the potential side effects of DNA modification by bisulphite and/or the ambiguity of mapping short reads in repetitive and highly homologous genomic regions, respectively. Nanopore sequencing is an attractive alternative for the study of 5’-mC since it allows sequencing of native DNA molecules, whereas the long reads produced by this technology help to increase the resolution of those genomic regions. In this work, we show that nanopore sequencing with 10X coverage depth, using DNA from a human cell line, produces 5’-mC methylation frequencies consistent with those obtained by 450k microarray, digital restriction enzyme analysis of methylation, and reduced representation bisulphite sequencing. High correlation between methylation frequencies obtained by nanopore sequencing and the other methodologies was also noticeable in either low or high GC content regions, including CpG islands and transcription start sites. We also showed that a minimum of five reads per CpG yields strong correlations (>0.89) in replicate nanopore sequencing runs and an almost uniform linearity of the methylation frequency variation between zero and one. Furthermore, nanopore sequencing was able to correctly display methylation frequency patterns based on genomic annotations of CpG regions. These results demonstrate that nanopore sequencing is a fast, robust, and reliable approach to the study of 5’-mC in the human genome with low coverage depth.

Simple and robust methylation test for risk stratification of patients with juvenile myelomonocytic leukemia

AbstractJuvenile myelomonocytic leukemia (JMML) is a rare myelodysplastic/myeloproliferative neoplasm that develops during infancy and early childhood. The array-based international consensus definition of DNA methylation has recently classified patients with JMML into the following 3 groups: high (HM), intermediate (IM), and low methylation (LM). To develop a simple and robust methylation clinical test, 137 patients with JMML were analyzed using the Digital Restriction Enzyme Analysis of Methylation (DREAM), which is a next-generation sequencing–based methylation analysis. Unsupervised consensus clustering of the discovery cohort (n = 99) using DREAM data identified HM (HM_DREAM; n = 35) and LM subgroups (LM_DREAM; n = 64). Of the 98 cases that could be compared with the international consensus classification, 90 HM (n = 30) and LM (n = 60) cases had 100% concordance with DREAM clustering results. Of the remaining 8 cases comprising the IM group, 4 were classified as belonging to the HM_DREAM group and 4 to the LM_DREAM group. A machine-learning classifier was successfully constructed using a support vector machine (SVM), which divided the validation cohort (n = 38) into HM (HM_SVM, n = 18) and LM (LM_SVM; n = 20) groups. Patients with the HM_SVM profile had a significantly poorer 5-year overall survival rate than those with the LM_SVM profile. In conclusion, we developed a robust methylation test using DREAM for patients with JMML. This simple and straightforward test can be easily incorporated into diagnosis to generate a methylation classification for patients so they can receive risk-adapted treatment in the context of future clinical trials.

Genome-wide DNA methylation analysis of dogs with high lead exposure living near a lead mining area in Kabwe, Zambia

Lead (Pb) is a heavy metal that has been proven to be toxic to both animals and humans. Genom-wide DNA methylation in domestic dogs exposed to high levels of Pb in Kabwe, Zambia was analyzed in this study. Using next-generation sequencing on samples from 20 domestic dogs (mean blood Pb concentration: 43.6 μg/dL and 7.2 μg/dL in the high and low exposure groups), a digital restriction enzyme analysis of methylation was performed to identify the genomic locations of differentially methylated CpG sites. A validation study on an additional 20 dogs followed (blood Pb concentration: 4.9–29.7 μg/dL). The cluster analysis resolved two broad clusters indicating high and low Pb exposure. The study identified 827 (1.2%) CpG sites with differences in methylation (101 CpG sites were hypermethylated in the low exposure group and 726 were hypermethylated in the high exposure group). The sites corresponded to 26 genes with differentially methylated CpG sites at their promoter regions, including the NGF gene. The methylation of four CpG sites was validated using bisulfite pyrosequencing. The results indicate that aberrant hypermethylation is prevalent in dogs exposed to Pb. The altered DNA methylation of the genes identified in this study contributes to a greater understanding of the epigenetic changes caused by Pb exposure and highlights novel biomarker discoveries across species.

High folic acid intake increases methylation-dependent expression of Lsr and dysregulates hepatic cholesterol homeostasis

Food fortification with folic acid and increased use of vitamin supplements have raised concerns about high folic acid intake. We previously showed that high folic acid intake was associated with hepatic degeneration, decreased levels of methylenetetrahydrofolate reductase (MTHFR), lower methylation potential, and perturbations of lipid metabolism. MTHFR synthesizes the folate derivative for methylation reactions. In this study, we assessed the possibility that high folic acid diets, fed to wild-type and Mthfr+/− mice, could alter DNA methylation and/or deregulate hepatic cholesterol homeostasis. Digital restriction enzyme analysis of methylation in liver revealed DNA hypomethylation of a CpG in the lipolysis-stimulated lipoprotein receptor (Lsr) gene, which is involved in hepatic uptake of cholesterol. Pyrosequencing confirmed this methylation change and identified hypomethylation of several neighboring CpG dinucleotides. Lsr expression was increased and correlated negatively with DNA methylation and plasma cholesterol. A putative binding site for E2F1 was identified. ChIP-qPCR confirmed reduced E2F1 binding when methylation at this site was altered, suggesting that it could be involved in increasing Lsr expression. Expression of genes in cholesterol synthesis, transport or turnover (Abcg5, Abcg8, Abcc2, Cyp46a1, and Hmgcs1) was perturbed by high folic acid intake. We also observed increased hepatic cholesterol and increased expression of genes such as Sirt1, which might be involved in a rescue response to restore cholesterol homeostasis. Our work suggests that high folic acid consumption disturbs cholesterol homeostasis in liver. This finding may have particular relevance for MTHFR-deficient individuals, who represent ~10% of many populations.

Genome-Wide Methylation Analysis Using the Digital Restriction Enzyme Analysis of Methylation for Stratification of Patients with Juvenile Myelomonocytic Leukemia

Background Juvenile myelomonocytic leukemia (JMML) is a rare myelodysplastic/ myeloproliferative neoplasm that occurs during infancy and early childhood. The clinical course of the disease varies widely. The majority of children require allogenic hematopoietic stem cell transplantation (HSCT) for long term survival, but the disease will eventually resolve spontaneously in ~15% of patients. Previous studies have identified clinical and molecular risk factors in JMML. More recently, three groups independently discovered that genome-wide methylation profiling using 450K Illumina array revealed that the high methylation (HM) subgroup was significantly associated with poor survival compared to the low methylation (LM) subgroup (Murakami 2018 Blood, Stieglitz 2017 Nat. Commun., Lipka 2017 Nat. Commun.). 450K could be a standard assay for stratification of JMML. However, it is now unavailable because the manufacture replaced it with EPIC array. Here, we developed a next-generation sequencing-based clinical test recapitulate 450K clustering results using the digital restriction enzyme analysis of methylation (DREAM) method (Jelinek 2012 Epigenetics). Patients and Methods We studied 99 children (67 boys and 32 girls) with JMML. All the patients were included in our previous publications. First, we assessed JMML samples with DREAM. Briefly, genomic DNA was sequentially cut with two enzymes SmaI and XmaI recognizing the same sequence, CCCGGG sites in DNA. Enzyme-treated DNA was then used to generate sequencing libraries according to the Illumina protocols, and run on an Illumina Hiseq 2500. We assessed 10 JMML samples with reduced representation bisulfite sequencing (RRBS) (Meissner 2005 Nucleic Acids Res.). In brief, purified genomic DNA was digested by the methylation-insensitive restriction enzyme MspI to generate short fragments that contain CpG dinucleotides at the ends. The CpG-rich DNA fragments (40-220 bp) were size selected, subjected to bisulfite conversion, PCR amplified and end sequenced on an Illumina Genome analyzer. Results We analyzed 99 samples using the DREAM with 8.87 (4.09-16.35) million reads (median, [range]), and determined methylation level in 62,525 (52,356-75,185) CpG sites (median [range]). We observed a strong correlation between DREAM methylation ratio and 450K beta-value of overlapping CpG sites (Pearson r2 = 0.95 [0.913-0.962], median [range]). We performed unsupervised consensus clustering with DREAM methylation data of 7,704 CpG sites within ±1 kb from TSS on autosomal chromosomes detected in ≥95% of the samples with imputation of the missing data using the median of each CpG site methylation level. Clustering identified two distinct subgroups, the HM subgroup (n = 35) and the LM subgroup (n = 64), matching 95% (94 of 99) with the 450K clustering results. The HM subgroup patients showed significantly poorer 5-year OS than the LM subgroup patients (41.9% [95% confidence interval {CI}], 25.3%-57.6%) vs. 71.4% [95% CI, 56.2%-82.1%]; P = 0.00345). Discrepancies in the clustering results between DREAM and 450K were observed in only 5 patients (2 survived and 3 died); all 5 patients were reclassified as those with LM with DREAM from being HM with 450K. We also performed RRBS methylation analysis on 10 patients. Unsupervised consensus clustering using promoter-associated 4,971 CpG sites measured with RRBS identified HM (n = 5) and LM (n = 5) subgroups and completely matched with the classification made using DREAM and 450K. Then, we developed a prediction model of the methylation subgroups using a machine-learning program. We selected 85 CpG sites from 7,704 CpG sites used for unsupervised clustering of the DREAM assay that showed a distinct difference in the average methylation level (&gt;0.3) between the HM and LM subgroups of the learning cohort (n = 70) and developed a support vector machine (SVM) model. As a validation cohort, we analyzed the remaining 29 JMML samples with a SVM model and confirmed a high matching rate with 450K clustering results (100%, 29 of 29). Conclusions We could develop a methylation test for JMML using the DREAM assay. Both the unsupervised clustering analysis and SVM model could repeat the result of 450K-based methylation classification, i.e., the HM and LM subgroups. The relatively lower cost of the DREAM assay (US$200/sample) enabled us to incorporate methylation classification in JMML in most settings. Disclosures No relevant conflicts of interest to declare.

GENOME-WIDE METHYLOME ANALYSIS USING METHYLCAP-SEQ UNCOVERS NOVEL METHYLATED MARKERS FOR CANINE LYMPHOMA CELL LINE CLBL-1

The most common type of tumor occurring in canine is the lymphomas. Epigenetic factors like DNA methylation is one of the important factors for causing cancer in canine. Cytology-based screening methods, such as fine needle aspiration (FNA) or immunocytochemistry (ICC), for canine lymphomas lack sensitivity. Despite an improvement in the detection of canine lymphomas by the DNA methylation analysis of lymph scrapings, only few methylation markers have been described. Even though technique like Digital Restriction Enzyme Analysis of Methylation (DREAM) can analyze the methylation profile of canine lymphoma cell line CLBL-1 at very low experimental cost without specific antibodies, the sensitivity and accuracy remain low in comparison to MethylCap-seq. In this study, a methylated DNA fragment of CLBL-1 was successfully captured by a specific protein for MethylCap-seq, and the methylation map of CLBL-1 was reconstructed by high throughput sequencing. For the first time, the genomic methylation region of canine CLBL-1 was analyzed. Using CLBL-1, we aimed to identify novel methylated markers for monitoring canine lymphomas. With the aid of methylation maps, several researchers have attempted to explore the relationship between DNA methylation and specific cancers. Additionally, the discovery of important biomarkers can predict or observe the course of canine cancer. Finally, the proposed advanced methylation information is likely to be suitable as a useful reference for clinical application of canine lymphoma research.

Abstract LB-141: CIMP is associated with altered microbiota composition in colorectal cancer patients

Abstract DNA methylation changes are important in cancer development and the etiology of the CpG Island Methylator Phenotype (CIMP), the most extreme form of aberrant promoter DNA methylation in cancer, can only partially be explained by genetic changes. An association between CIMP and the gut microbiota has been implicated in colorectal cancer (CRC) pathogenesis but the exact mechanisms underlying the observations are poorly understood. In order to clarify the link between CIMP and the microbiome in CRC, we studied human primary tumor and adjacent mucosal tissues (normal) from CRC patients (n=46). The patient samples were categorized by tumor sites (23 proximal and 23 distal), sex (28 males and 18 females), and age (69 yrs ±11). Bisulfite pyrosequencing and Digital Restriction Enzyme Analysis of Methylation (DREAM) were performed to determine the methylation of CpG sites in the CRC tumors. The tumor samples were selected based on their CIMP status (10 high, 10 low, and 26 negative) and the tumor sites. 16S rRNA gene sequencing using Illumina-Hi-Seq was performed on those samples. Principle Coordinate analysis of the 16S rRNA sequences showed that the microbiota of CIMP-positive (CIMP-high and -low combined) tumors was significantly different from the microbiota of the CIMP-negative tumors (PERMANOVA, P = 0.013). Linear discriminant analysis effect size (LEfSe) showed an enrichment of specific bacterial taxa in the CIMP-positive microbiota. Fusobacterium (LDA score = 4.71, p=0.033) and Erysipelotrichaceae (LDA score = 3.77, p=0.004) were most enriched in the CIMP-positive tumors along with Bacteroides. The microbiota of different tumor sites also showed significant difference with Fusobacterium (LDA score = 4.32, p=0.047) and Erysipelotrichaceae (LDA score = 3.45, p=0.039) being enriched in the proximal tumors compared to the distal tumors. All these bacterial taxa have previous been found to be associated with CRC and/or metabolic disorders. We validated the 16S rRNA data by qPCR analysis using genus-specific probes. In the same samples, Pan-Fusobacterium and Bacteroides fragilis were enriched in the CIMP-positive tumors. The median number of Pan-Fusobacterium per 100 human cells was 12-fold higher in the CIMP-positive tumors (p=0.0015) and 6-fold higher in the case of B. fragilis (p=0.0228). Thus, our data show broad difference in the microbiota of CIMP-positive CRCs compared to CIMP-negative CRCs. The significantly enriched bacterial taxa in CIMP-positive CRC suggest that these specific taxa could play an important role in aberrant DNA methylation modulation in colorectal cancer, and further studies should elucidate the mechanism underlying the CIMP/microbiota link in the context of CRC. Citation Format: Pyoung Hwa Park, Raad Z. Gharaibeh, Lauren Cole, Ang Sun, Woonbok Chung, Jaroslav Jelinek, Jillian L. Pope, Christian Jobin, Jean-Pierre J. Issa. CIMP is associated with altered microbiota composition in colorectal cancer patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr LB-141.

Age estimation in a long-lived seabird (Ardenna tenuirostris) using DNA methylation-based biomarkers.

Age structure is a fundamental aspect of animal population biology. Age is strongly related to individual physiological condition, reproductive potential and mortality rate. Currently, there are no robust molecular methods for age estimation in birds. Instead, individuals must be ringed as chicks to establish known-age populations, which is a labour-intensive and expensive process. The estimation of chronological age using DNA methylation (DNAm) is emerging as a robust approach in mammals including humans, mice and some non-model species. Here, we quantified DNAm in whole blood samples from a total of 71 known-age Short-tailed shearwaters (Ardenna tenuirostris) using digital restriction enzyme analysis of methylation (DREAM). The DREAM method measures DNAm levels at thousands of CpG dinucleotides throughout the genome. We identified seven CpG sites with DNAm levels that correlated with age. A model based on these relationships estimated age with a mean difference of 2.8years to known age, based on validation estimates from models created by repeated sampling of training and validation data subsets. Longitudinal observation of individuals re-sampled over 1 or 2years generally showed an increase in estimated age (6/7 cases). For the first time, we have shown that epigenetic changes with age can be detected in a wild bird. This approach should be of broad interest to researchers studying age biomarkers in non-model species and will allow identification of markers that can be assessed using targeted techniques for accurate age estimation in large population studies.

Nerve Injury-Induced Chronic Pain Is Associated with Persistent DNA Methylation Reprogramming in Dorsal Root Ganglion.

Nerve injury-induced hyperactivity of primary sensory neurons in the dorsal root ganglion (DRG) contributes to chronic pain development, but the underlying epigenetic mechanisms remain poorly understood. Here we determined genome-wide changes in DNA methylation in the nervous system in neuropathic pain. Spinal nerve ligation (SNL), but not paclitaxel treatment, in male Sprague Dawley rats induced a consistent low-level hypomethylation in the CpG sites in the DRG during the acute and chronic phases of neuropathic pain. DNA methylation remodeling in the DRG occurred early after SNL and persisted for at least 3 weeks. SNL caused DNA methylation changes at 8% of CpG sites with prevailing hypomethylation outside of CpG islands, in introns, intergenic regions, and repetitive sequences. In contrast, SNL caused more gains of methylation in the spinal cord and prefrontal cortex. The DNA methylation changes in the injured DRGs recapitulated developmental reprogramming at the neonatal stage. Methylation reprogramming was correlated with increased gene expression variability. A diet deficient in methyl donors induced hypomethylation and pain hypersensitivity. Intrathecal administration of the DNA methyltransferase inhibitor RG108 caused long-lasting pain hypersensitivity. DNA methylation reprogramming in the DRG thus contributes to nerve injury-induced chronic pain. Restoring DNA methylation may represent a new therapeutic approach to treat neuropathic pain.SIGNIFICANCE STATEMENT Epigenetic mechanisms are critically involved in the transition from acute to chronic pain after nerve injury. However, genome-wide changes in DNA methylation in the nervous system and their roles in neuropathic pain development remain unclear. Here we used digital restriction enzyme analysis of methylation to quantitatively determine genome-wide DNA methylation changes caused by nerve injury. We showed that nerve injury caused DNA methylation changes at 8% of CpG sites with prevailing hypomethylation outside of CpG islands in the dorsal root ganglion. Reducing DNA methylation induced pain hypersensitivity, whereas increasing DNA methylation attenuated neuropathic pain. These findings extend our understanding of the epigenetic mechanism of chronic neuropathic pain and suggest new strategies to treat nerve injury-induced chronic pain.

Abstract WMP73: Adck5, Mtnr1b And Kndc1 : Atherosclerosis-related Epigenetic Biomarkers Identified From Peripheral Leukocytes of Atherosclerotic Patients

Background and objectives: The present study initially profiled and identified gene-specific promoter methylation changes in peripheral leukocytes (WBC) of patients having severe atherosclerosis. Then, the gene-specific promoter methylation changes of WBC were validated in atherosclerotic plaques by comparison with normal intima. Methods: We first profiled and identified specific genes showing promoter methylation differences between WBC of 8 patients having severe atherosclerosis and of other 8 patients having no-atherosclerosis in extra- and intra-cranial vessels using Digital Restriction Enzyme Analysis of Methylation (DREAM) sequencing. To select candidate CpG sites from DREAM sequencing data, we used criteria; located in -1,000 bp from transcription start sites, &lt; or &gt;5% of methylation differences between two groups, and &lt;0.05 false positive rate. Significance of the gene-specific promoter methylation changes identified from WBC were validated from normal intima and atherosclerotic plaques obtained from common carotid artery of 20 human cadaveric donors (male, 13, age, 62.2±14.2 years). Results: On DREAM sequencing, CpG sites located in promoter regions of ADCK5 (no-atherosclerosis, 67.57% vs. atherosclerosis patients, 55.18%), KNDC1 (67.08% vs. 56.81%), MTNR1B (11.5% vs. 3.8%) had over 5% of the methylation differences with &lt;0.05 false positive rate. On validation experiments using human vascular tissues, all ADCK5 (normal intima, 4.02±1.02; plaque, 4.79±1.14, p&lt; 0.05), KNDC1 (9.76±2.25 vs. 12.11±2.91, p&lt; 0.05), MTNR1B (14.08±2.93 vs. 17.53±5.07, p&lt; 0.05) showed significant higher promoter methylation in atherosclerotic plaques than normal intima. Conclusion: The present study identified promoter methylation changes in ADCK5 , KNDC1 , and MTNR1B from WBC of atherosclerotic patients, and validated their significance in human atherosclerotic tissues. The three genes showed possibilities as epigenetic biomarkers for atherosclerosis, even though future validations are needed for their significance in atherosclerosis development.

Digital Restriction Enzyme Analysis of Methylation (DREAM).

Digital Restriction Enzyme Analysis of Methylation (DREAM) is a method for quantitative mapping of DNA methylation across genomes using next-generation sequencing (NGS) technology. The method is based on sequential cuts of genomic DNA with a pair of restriction enzymes (SmaI and XmaI) at CCCGGG target sites. Unmethylated sites are first digested with SmaI. This enzyme cuts the sites in the middle at CCC^GGG, leaving behind blunt ended fragments. CpG methylation completely blocks SmaI; therefore, only unmethylated sites are cleaved. The remaining methylated sites are digested with XmaI in the next step. This enzyme is not blocked by CpG methylation. It cuts the recognition site sideways at C^CCGGG forming 5'-CCGG overhangs. The sequential cuts thus create distinct methylation-specific signatures at the ends of restriction fragments: 5'-GGG for unmethylated CpG sites and 5'-CCGGG for methylated sites. The DNA fragments resulting from the digestions are ligated to NGS adapters. Sequencing libraries are prepared using hexanucleotide barcodes for sample identification. Individual libraries with distinct barcodes are pooled and sequenced using a paired ends protocol. The sequencing reads are aligned to the genome and mapped to unique CCCGGG target sites. Methylation at individual CpG sites is calculated as the ratio of sequencing reads with the methylated signature to the total number of reads mapping to the site. Sequencing of 25million reads per sample typically yields 50,000 unique CpG sites covered with hundreds of reads enabling accurate determination of DNA methylation levels. DREAM does not require bisulfite conversion, has a very low background, and has high sensitivity to low levels of methylation. The method is simple, cost-effective, quantitative, highly reproducible, and can be applied to any species.

Single Cell Restriction Enzyme-Based Analysis of Methylation at Genomic Imprinted Regions in Preimplantation Mouse Embryos.

The methylation of cytosines in DNA is a fundamental epigenetic regulatory mechanism. During preimplantation development, mammalian embryos undergo extensive epigenetic reprogramming, including the global erasure of germ cell-specific DNA methylation marks, to allow for the establishment of the pluripotent state of the epiblast. However, DNA methylation marks at specific regions, such as imprinted gene regions, escape this reprogramming process, as their inheritance from germline to soma is paramount for proper development. To study the dynamics of DNA methylation marks in single blastomeres of mouse preimplantation embryos, we devised a new approach-single cell restriction enzyme analysis of methylation (SCRAM). SCRAM allows for reliable, fast, and high-throughput analysis of DNA methylation states of multiple regions of interest from single cells. In the method described below, SCRAM is specifically used to address loss of DNA methylation at genomic imprints or other highly methylated regions of interest.

Abstract 4441: Non-pathogenic bacteria change host DNA methylation in vivo

Abstract Introduction: More than a thousand species of bacteria live in a normal person's gastrointestinal tract. Epigenetic effects on the colon directly caused by the commensal bacteria remain elusive. In the current study, we explore the bacterial effects on DNA methylation of the host colon. Methods: Eight non-pathogenic bacterial species were introduced to the gut of germ-free (GF) mice to make specific-pathogen free (SPF) mice. Our study consisted of the following groups (n = 6 for each): wildtype (WT) GF, WT SPF, IL-10 knockout (KO) GF, IL-10 KO SPF, and IL-10 KO GF or SPF treated with azoxymethane (AOM). We analyzed DNA methylation in genomic DNA extracted from the proximal colon using Digital Restriction Enzyme Analysis of Methylation (DREAM) and compared methylation levels at CpG sites among different groups. Results: 1) Principal component analysis (PCA) performed on methylomes of all the samples separated the mouse samples based on presence or absence of bacteria, IL-10 KO status or AOM treatment into 6 distinct groups. 2) We analyzed CpG sites differentially methylated between GF and SPF mice at p&amp;lt;0.05 significance level. In WT mice, there were 1871 CpG sites (11% out of 17475 analyzed sites), in IL10 KO mice, there were 5986 CpG sites (33% out of 18254 analyzed sites) and in IL10 KO AOM-treated mice there were 6755 CpG sites (31% out of 21697 analyzed sites) differentially methylated. 3) There were 756 common CpG sites differentially methylated in all SPF vs GF comparisons. Interestingly, these sites were enriched 2.6-fold for aging-related CpG sites. 4) WT SPF mice showed increased methylation at CpG sites hypomethylated in WT GF mice and, conversely, decreased methylation at CpG sites hypermethylated in WT GF mice. This pattern of DNA methylation change was also observed by comparing GF with SPF in IL-10 KO mice with or without AOM treatment. 5) Both in GF and SPF mice the DNA methylation changes were more pronounced in IL10 KO while AOM had little additional effect. 6) IL10 KO resulted in genome-wide increase of methylation. However, the introduction of bacteria in SPF mice resulted in the methylation change mainly at CpG islands. Conclusions: Non-pathogenic bacteria introduced in the colon cause methylation gains at CpG sites with low DNA methylation and methylation losses at sites with high DNA methylation in a pattern similar to the changes observed in aging and cancer. Citation Format: Ang Sun, Jaroslav Jelinek, Shinji Maegawa, Christian Jobin, Jean-Pierre Issa. Non-pathogenic bacteria change host DNA methylation in vivo. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 4441.

Abstract 2779: A CpG island methylator phenotype in acute myeloid leukemia independent of IDH mutations and associated with a favorable outcome

Abstract Background: Acute myeloid leukemia (AML) causes the most leukemia-related deaths in the United States, and has frequent epigenetic aberrations, including a CpG island methylator phenotype (CIMP). CIMP defines unique molecular subtypes of other cancers and has been linked to mutations in IDH1/2, however the clinical consequences of CIMP and the role of IDH1/2 mutations in AML remain unclear. Methods: To measure genome-wide CpG methylation we used Digital Restriction Enzyme Analysis of Methylation (DREAM) on AML bone marrow samples and normal peripheral blood controls. For validation we used methylation data from patient samples from The Cancer Genome Atlas (TCGA) on the Illumina Infinium HumanMethylation450 platform. We also used RNA-seq data from TCGA, and microarray data from GEO (GSE6891). Statistical analysis was done using R. Results: Genome-wide analysis of variably methylated CpG sites in 96 AML bone marrow samples using DREAM revealed two distinct CpG island methylator phenotypes by hierarchical clustering: IDH-CIMP (I-CIMP) in which 7/10 cases had oncogenic IDH1/2 mutations, and AML-CIMP (A-CIMP), which lacked any mutations in IDH1/2. At median follow-up of 6.16 years, A-CIMP cases, but not I-CIMP cases were associated with longer overall survival (median OS, years: A-CIMP = Not reached, P = 0.08; I-CIMP = 3.35, P = 0.50; CIMP-negative = 1.17). We validated and extended these findings using TCGA data. In this cohort A-CIMP cases also had significantly longer OS compared to CIMP-negative (median OS, years: A-CIMP = 2.34, P = 0.01; I-CIMP = 1.25, P = 0.89; CIMP-negative = 1.00). Aberrant hypermethylation in A-CIMP occurred preferentially at CpG islands by a factor greater than 3, while I-CIMP cases demonstrated a slight preference for hypermethylation at sites outside CpG islands. Interestingly, A-CIMP was enriched in CEBPA (19%) and WT1 mutations (14%), but inversely correlated with IDH, TET2, and NPM1 mutations. Functional pathway analysis revealed that genes hypermethylated in A-CIMP are associated with pluripotency maintenance - including PAX6, GBX2, and HOXA9 - and RNA-seq data largely, but not entirely, recapitulated methylation-based patterns. There was a strong correlation between promoter CpG island methylation and gene expression for many A-CIMP genes. Finally, the transcriptional program associated with A-CIMP was found to correlate with outcome and genetic backgrounds in both TCGA and additional independent datasets. Conclusions: Taken together, our data suggest that CIMP in AML is complex, multifactorial and cannot be explained solely by coding gene mutations (e.g. IDH1/2, TET2). There is an association between A-CIMP and curability in multiple AML datasets that cannot be recapitulated by mutational data alone and that may be worth validating in prospective studies. Citation Format: Andrew D. Kelly, Heike Kroeger, Jumpei Yamazaki, Rodolphe Taby, Frank Neumann, Sijia Yu, Justin T. Lee, Rong He, Shoudan Liang, Yue Lu, Matteo Cesaroni, Sherry A. Pierce, Steven M. Kornblau, Carlos E. Bueso-Ramos, Farhad Ravandi, Hagop M. Kantarjain, Jaroslav Jelinek, Jean-Pierre J. Issa. A CpG island methylator phenotype in acute myeloid leukemia independent of IDH mutations and associated with a favorable outcome. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 2779.

DREAM: A Simple Method for DNA Methylation Profiling by High-throughput Sequencing.

The digital restriction enzyme analysis of methylation (DREAM) is a simple method for DNA methylation analysis at tens of thousands of CpG sites across the genome. The method creates specific signatures at unmethylated and methylated CpG sites by sequential digests of genomic DNA with restriction endonucleases SmaI and XmaI, respectively. Both enzymes have the same CCCGGG recognition site; however, they differ in their sensitivity to CpG methylation and their cutting pattern. SmaI cuts only unmethylated sites leaving blunt 5'-GGG ends. XmaI cuts remaining methylated CC(me)CGG sites leaving 5'-CCGGG ends. Restriction fragments with distinct signatures at their ends are ligated to Illumina sequencing adaptors with sample-specific barcodes. High-throughput sequencing of pooled libraries follows. Sequencing reads are mapped to the restriction sites in the reference genome, and signatures corresponding to methylation status of individual DNA molecules are resolved. Methylation levels at target CpG sites are calculated as the proportion of sequencing reads with the methylated signature to the total number of reads mapping to the particular restriction site. Aligning the reads to the reference genome of any species is straightforward, since the method does not rely on bisulfite conversion of DNA. Sequencing of 25 million reads per human DNA library yields over 50,000 unique CpG sites with high coverage enabling accurate determination of DNA methylation levels. DREAM has a background less than 1 % making it suitable for accurate detection of low methylation levels. In summary, the method is simple, robust, highly reproducible, and cost-effective.

Zebrafish embryos as a screen for DNA methylation modifications after compound exposure

Modified epigenetic programming early in life is proposed to underlie the development of an adverse adult phenotype, known as the Developmental Origins of Health and Disease (DOHaD) concept. Several environmental contaminants have been implicated as modifying factors of the developing epigenome. This underlines the need to investigate this newly recognized toxicological risk and systematically screen for the epigenome modifying potential of compounds. In this study, we examined the applicability of the zebrafish embryo as a screening model for DNA methylation modifications. Embryos were exposed from 0 to 72h post fertilization (hpf) to bisphenol-A (BPA), diethylstilbestrol, 17α-ethynylestradiol, nickel, cadmium, tributyltin, arsenite, perfluoroctanoic acid, valproic acid, flusilazole, 5-azacytidine (5AC) in subtoxic concentrations. Both global and site-specific methylation was examined. Global methylation was only affected by 5AC. Genome wide locus-specific analysis was performed for BPA exposed embryos using Digital Restriction Enzyme Analysis of Methylation (DREAM), which showed minimal wide scale effects on the genome, whereas potential informative markers were not confirmed by pyrosequencing. Site-specific methylation was examined in the promoter regions of three selected genes vasa, vtg1 and cyp19a2, of which vasa (ddx4) was the most responsive. This analysis distinguished estrogenic compounds from metals by direction and sensitivity of the effect compared to embryotoxicity. In conclusion, the zebrafish embryo is a potential screening tool to examine DNA methylation modifications after xenobiotic exposure. The next step is to examine the adult phenotype of exposed embryos and to analyze molecular mechanisms that potentially link epigenetic effects and altered phenotypes, to support the DOHaD hypothesis.

Abstract B22: Genome-wide methylation analysis reveals an independently validated CpG island methylator phenotype associated with favorable prognosis in acute myeloid leukemia.

Abstract Background: Acute myeloid leukemia (AML) accounts for the most leukemia-related deaths in the United States and its incidence has been rising as the population ages. Although certain molecular aberrations are prognostic and have come into mainstream clinical practice, the genetic and epigenetic determinants of curability in AML remain incompletely understood. Our study examines the role of DNA methylation patterns in AML prognosis and expands on our preliminary work showing DNA hypermethylation may associate with improved overall survival. Methods: To quantitatively interrogate genome-wide CpG methylation we used Digital Restriction Enzyme Analysis of Methylation (DREAM) on a cohort of 102 AML patient samples and 25 normal control samples. We validated our findings using DNA methylation data from 194 patient samples from The Cancer Genome Atlas (TCGA) on the Illumina Infinium HumanMethylation450 platform. Statistical analysis was done using R. Results: Preliminary analysis by our group of DNA methylation levels at promoter CpG islands (CGI) of OSCP1, NPM2, OLIG2, SCGB3A1, and SLC26A4 showed significant hypermethylation in a small group of long-surviving AML patients compared to a short-surviving cohort (median OS = 2,694 days vs. 207 days). We expanded on this observation using DREAM to measure genome-wide DNA methylation in clinical AML samples and found that hierarchical clustering based on 2,537 CpG sites with a standard deviation above 20% stratified patients into three groups with significant differences in overall survival. The hypermethylated cluster had the best prognosis and seemed to be defined by hypermethylation at promoter CGIs, suggesting that a CGI methylator phenotype (CIMP) in AML may be a favorable prognostic factor (median OS: CIMP = 5,110 days, Cluster 2 = 380 days, Cluster 3 = 555 days; log-rank p=0.0162). We then validated these findings using TCGA data from AML patient samples. Hierarchical clustering on the basis of CGI promoter sites revealed three distinct groups with the CIMP cluster having significantly improved overall survival compared to the other clusters (median OS: CIMP = 761 days, Cluster 2 = 306 days, Cluster 3 = 365 days; log-rank p=0.0013). There was also a trend in overall survival when non-CGI non-promoter sites were used to cluster samples (median OS: CIMP = 593 days, Cluster 2 = 245 days, Cluster 3 = 456 days; log-rank p=0.1530). Consistent with our DREAM data, combining CGI promoter sites with non-CGI, non-promoter sites revealed a hierarchical clustering pattern of three major clusters with significant differences in overall survival (median OS: CIMP = 822 days, Cluster 2 = 365 days, Cluster 3 = 365 days; log-rank p=0.0295). Despite technical differences between platforms, there was significant overlap in the genes most proximal to differentially methylated sites between the DREAM and TCGA analyses. These common genes were significantly enriched in transcription factors, pyrimidine metabolism genes, and development genes. Interestingly, the presence of IDH1 R140 mutations was significantly greater in the CIMP clusters in both the DREAM and TCGA analyses (p&amp;lt;0.0001, p=0.0004 for DREAM and TCGA respectively). Taken together the results from our DREAM data and the TCGA validation support the hypothesis that CIMP is a favorable prognostic feature in AML. Conclusions: We propose that the CIMP methylation pattern is associated with favorable prognosis in AML. We have identified a subset of methylation sites that, when interrogated, predict overall survival independent of other clinical factors. Citation Format: Andrew D. Kelly, Heike Kroeger, Jumpei Yamazaki, Rodolphe Taby, Frank Neumann, Justin T. Lee, Rong He, Shoudan Liang, Yue Lu, Matteo Cesaroni, Sherry A. Pierce, Steven M. Kornblau, Carlos E. Bueso-Ramos, Farhad Ravandi, Hagop M. Kantarjian, Jean-Pierre J. Issa, Jaroslav Jelinek. Genome-wide methylation analysis reveals an independently validated CpG island methylator phenotype associated with favorable prognosis in acute myeloid leukemia. [abstract]. In: Proceedings of the AACR Special Conference on Hematologic Malignancies: Translating Discoveries to Novel Therapies; Sep 20-23, 2014; Philadelphia, PA. Philadelphia (PA): AACR; Clin Cancer Res 2015;21(17 Suppl):Abstract nr B22.