DNA methylation data from Japanese patients with Rubinstein–Taybi syndrome

Inactivating NSD1 mutations causing Sotos syndrome have been previously associated with a specific genome-wide DNA methylation (DNAm) pattern. Sotos syndrome is characterized by phenotypic overlap with other overgrowth syndromes, and a definite diagnosis might not be easily reached due to the high prevalence of variants of unknown significance (VoUS) that are identified in patients with a suggestive phenotype. we performed microarray DNAm profiling in a set of 11 individuals with a clinical suspicion of Sotos syndrome and carrying an NSD1 VoUS or previously unreported variants to solve uncertainty in defining pathogenicity of the observed variants. The impact of the training cohort size on sensitivity and prediction confidence of the classifier was assessed. The Sotos syndrome-specific DNAm signature was validated in six individuals with a clinical diagnosis of Sotos syndrome and carrying bona fide pathogenic NSD1 variants. Applying this approach to the remaining 11 individuals with NSD1 variants, we succeeded in confirming pathogenicity in eight subjects and excluding the diagnosis of Sotos syndrome in three. The sensitivity and prediction confidence of the classifier based on the different sizes of the training sets did not show substantial differences, though the overall performance was improved by using a data balancing strategy. The present approach solved uncertainty in cases with NDS1 VoUS, further demonstrating the clinical utility of DNAm profiling.

Increased age, BMI and HbA1c levels are risk factors for several non-communicable diseases. However, the impact of these factors on the genome-wide DNA methylation pattern in human adipose tissue remains unknown. We analyzed the DNA methylation of ∼480 000 sites in human adipose tissue from 96 males and 94 females and related methylation to age, BMI and HbA1c. We also compared epigenetic signatures in adipose tissue and blood. Age was significantly associated with both altered DNA methylation and expression of 1050 genes (e.g. FHL2, NOX4 and PLG). Interestingly, many reported epigenetic biomarkers of aging in blood, including ELOVL2, FHL2, KLF14 and GLRA1, also showed significant correlations between adipose tissue DNA methylation and age in our study. The most significant association between age and adipose tissue DNA methylation was found upstream of ELOVL2. We identified 2825 genes (e.g. FTO, ITIH5, CCL18, MTCH2, IRS1 and SPP1) where both DNA methylation and expression correlated with BMI. Methylation at previously reported HIF3A sites correlated significantly with BMI in females only. HbA1c (range 28-46 mmol/mol) correlated significantly with the methylation of 711 sites, annotated to, for example, RAB37, TICAM1 and HLA-DPB1. Pathway analyses demonstrated that methylation levels associated with age and BMI are overrepresented among genes involved in cancer, type 2 diabetes and cardiovascular disease. Our results highlight the impact of age, BMI and HbA1c on epigenetic variation of candidate genes for obesity, type 2 diabetes and cancer in human adipose tissue. Importantly, we demonstrate that epigenetic biomarkers in blood can mirror age-related epigenetic signatures in target tissues for metabolic diseases such as adipose tissue.

Sequencing technologies have changed not only our approaches to classical genetics, but also the field of epigenetics. Specific methods allow scientists to identify novel genome-wide epigenetic patterns of DNA methylation down to single-nucleotide resolution. DNA methylation is the most researched epigenetic mark involved in various processes in the human cell, including gene regulation and development of diseases, such as cancer. Increasing numbers of DNA methylation sequencing datasets from human genome are produced using various platforms—from methylated DNA precipitation to the whole genome bisulfite sequencing. Many of those datasets are fully accessible for repeated analyses. Sequencing experiments have become routine in laboratories around the world, while analysis of outcoming data is still a challenge among the majority of scientists, since in many cases it requires advanced computational skills. Even though various tools are being created and published, guidelines for their selection are often not clear, especially to non-bioinformaticians with limited experience in computational analyses. Separate tools are often used for individual steps in the analysis, and these can be challenging to manage and integrate. However, in some instances, tools are combined into pipelines that are capable to complete all the essential steps to achieve the result. In the case of DNA methylation sequencing analysis, the goal of such pipeline is to map sequencing reads, calculate methylation levels, and distinguish differentially methylated positions and/or regions. The objective of this review is to describe basic principles and steps in the analysis of DNA methylation sequencing data that in particular have been used for mammalian genomes, and more importantly to present and discuss the most pronounced computational pipelines that can be used to analyze such data. We aim to provide a good starting point for scientists with limited experience in computational analyses of DNA methylation and hydroxymethylation data, and recommend a few tools that are powerful, but still easy enough to use for their own data analysis.

Introduction: Wilms’ tumor (WT) is the most common childhood renal cancer. Although many children are cured with standard therapy, survivors frequently suffer chronic diseases as a result of their treatment. Historical evidence suggests that a number of children could be cured with surgery alone; however, many of these children are currently difficult to identify. Although the majority of mutations described in this disease are not prognostic, the commonest single molecular alteration in WT is epigenetic—loss of imprinting at chromosome 11p15. We therefore examined genome-wide patterns of DNA methylation in WTs to identify groups of patients with low risk of relapse. Methods: We enrolled two cohorts of patients: a discovery cohort consisting of 32 tumors and 21 matched kidneys was recruited at the time of surgery at our hospital. A validation cohort included 40 tumor-normal pairs from the Children’s Oncology Group (COG) biobank and an additional 11 pairs from our hospital. All samples had genome-wide DNA methylation and copy number variation data generated. The samples from COG additionally had whole-exome sequencing while 22 local tumors had RNA sequencing. Results: Unsupervised clustering of DNA methylation data demonstrated three DNA methylation subgroups that could be reproduced in the validation cohort using a “signature” of selected differentially methylated sites. One group (“PRO”) had genome-wide loss of methylation with specific gain of methylation at renal development genes and tumor-suppressor genes. This group also had increased expression of genes related to cell proliferation. Mutations in microRNA processing genes were found exclusively in this group and were associated with dysregulation of microRNA expression. All known cases of relapse were found in this group. A second group (“DIFF”) had a DNA methylation profile similar to normal kidney, no copy number alterations, reduced expression of genes associated with early renal development, and mutations only in WT1 or CTNNB1. No relapses were known in this group, but there was an increased incidence of bilateral disease. A third group (“INT”) had intermediate methylation values at all signature sites, a gene expression profile similar to the DIFF group, and increased microRNA dysregulation. All tumors in the INT group had either mutations in TRIM28, epithelial histology, or both. Discussion: Genome-wide DNA methylation profiling demonstrates three subgroups of WT with distinct molecular and clinical characteristics. The DIFF group has molecular features consistent with a differentiation process occurring. These patients may be candidates for therapy reduction. The INT group suggests that some patients with wild-type TRIM28 share features with tumors with mutations in the gene—known to be associated with low risk of relapse. This group may also be a candidate for therapy reduction. We are now investigating the features that drive increased proliferation in the PRO group as these may be targets of future therapy for these higher-risk patients. Citation Format: Jack Brzezinski, Sanaa Choufani, Rodrigo Romao, Cheryl Shuman, Haiying Chen, Ronald Grant, Armando Lorenzo, Rosanna Weksberg. Three distinct subgroups of Wilms’ tumors with novel molecular features and important clinical implications are defined by genome-wide DNA methylation profiles [abstract]. In: Proceedings of the AACR Special Conference on the Advances in Pediatric Cancer Research; 2019 Sep 17-20; Montreal, QC, Canada. Philadelphia (PA): AACR; Cancer Res 2020;80(14 Suppl):Abstract nr B04.

BackgroundOne of the most important recent findings in cancer genomics is the identification of novel driver mutations which often target genes that regulate genome-wide chromatin and DNA methylation marks. Little is known, however, as to whether these genes exhibit patterns of epigenomic deregulation that transcend cancer types.ResultsHere we conduct an integrative pan-cancer-wide analysis of matched RNA-Seq and DNA methylation data across ten different cancer types. We identify seven tumor suppressor and eleven oncogenic epigenetic enzymes which display patterns of deregulation and association with genome-wide cancer DNA methylation patterns, which are largely independent of cancer type. In doing so, we provide evidence that genome-wide cancer hyper- and hypo- DNA methylation patterns are independent processes, controlled by distinct sets of epigenetic enzyme genes. Using causal network modeling, we predict a number of candidate drivers of cancer DNA hypermethylation and hypomethylation. Finally, we show that the genomic loci whose DNA methylation levels associate most strongly with expression of these putative drivers are highly consistent across cancer types.ConclusionsThis study demonstrates that there exist universal patterns of epigenomic deregulation that transcend cancer types, and that intra-tumor levels of genome-wide DNA hypomethylation and hypermethylation are controlled by distinct processes.Electronic supplementary materialThe online version of this article (doi:10.1186/s13059-015-0699-9) contains supplementary material, which is available to authorized users.

To better understand the molecular mechanisms of atherosclerosis, we conducted acomparative analysis of DNA methylation patterns in right coronary arteries in the area of advanced atherosclerotic plaques (CAP), great saphenous vein (GSV), and internal mammary artery (IMA) of patients affected by coronary heart disease. DNA methylation data (accession number E‑GEOD-62867) were divided into three paired groups: CAP vs. IMA, CAP vs. GSV, and IMA vs. GSV. Differentially methylated genes (DMGs) were extracted to analyze the changes in the DMGs in the three different tissues. The gplots package was used for the clustering and heatmap analysis of DMGs. Subsequently, DMG-related pathways were identified using DAVID (Database for Annotation, Visualization and Integrated Discovery) and transcription factors (TFs) were predicted. Based on the filtering criterion of p< 0.05, and a mean beta value difference of ≥0.2, there were 252, 373, and 259 DMGs, respectively, in the CAP vs. IMA, CAP vs. GSV, and IMA vs. GSV groups. Interestingly, the S100A10 gene was hypomethylated in CAP compared with IMA and GSV. Clustering and heatmap analyses suggested that DMGs were segregated into two distinct clusters. Hypermethylated genes in CAP as compared with GSV were only involved in the pathway of fat digestion and absorption, while hypomethylated genes in CAP compared with GSV mainly participated in immune response-associated pathways (cytokine-cytokine receptor interaction, MAPK signaling pathway). The DNA methylation differences in vascular tissues of patients with coronary artery disease may provide new insights into the mechanisms underlying the development of atherosclerosis. The functions identified here-cytokine-cytokine receptor interaction, MAPK signaling pathway, DMG (S100A10), and TF (NF-kB)-may serve as potential targets in the treatment of atherosclerosis.

BackgroundEpigenetic factors regulate tissue-specific expression and X-chromosome inactivation. Previous studies have identified epigenetic differences between sexes in some human tissues. However, it is unclear whether epigenetic modifications contribute to sex-specific differences in insulin secretion and metabolism. Here, we investigate the impact of sex on the genome-wide DNA methylation pattern in human pancreatic islets from 53 males and 34 females, and relate the methylome to changes in expression and insulin secretion.ResultsGlucose-stimulated insulin secretion is higher in female versus male islets. Genome-wide DNA methylation data in human islets clusters based on sex. While the chromosome-wide DNA methylation level on the X-chromosome is higher in female versus male islets, the autosomes do not display a global methylation difference between sexes. Methylation of 8,140 individual X-chromosome sites and 470 autosomal sites shows sex-specific differences in human islets. These include sites in/near AR, DUSP9, HNF4A, BCL11A and CDKN2B. 61 X-chromosome genes and 18 autosomal genes display sex-specific differences in both DNA methylation and expression. These include NKAP, SPESP1 and APLN, which exhibited lower expression in females. Functional analyses demonstrate that methylation of NKAP and SPESP1 promoters in vitro suppresses their transcriptional activity. Silencing of Nkap or Apln in clonal beta-cells results in increased insulin secretion. Differential methylation between sexes is associated with altered levels of microRNAs miR-660 and miR-532 and related target genes.ConclusionsChromosome-wide and gene-specific sex differences in DNA methylation associate with altered expression and insulin secretion in human islets. Our data demonstrate that epigenetics contribute to sex-specific metabolic phenotypes.Electronic supplementary materialThe online version of this article (doi:10.1186/s13059-014-0522-z) contains supplementary material, which is available to authorized users.

Introduction: Retinoblastoma (Rb) is the most common childhood intraocular cancer. Tissue biopsy of Rb can cause tumor spread, so it is contraindicated. We demonstrated that aqueous humor (AH), an ocular fluid, is a high yield liquid biopsy enabling in vivo detection of tumor-derived cell free DNA (cfDNA) thus overcoming the contraindication to biopsy. Prognostic genomic cfDNA biomarkers in Rb AH enables objective real time disease monitoring. In ~13% of Rb, tumor progression is driven by epigenetic deregulation of tumor-promoting pathways without detectable genomic alterations. However, epigenetic studies have been done only on tumor from surgically removed eyes. The frequency and effect of epigenomic regulation in eyes that have been saved with therapy is not clear due to no access to in vivo tumor. Therefore, epigenetic analysis of AH cfDNA is highly desired to understand the broader spectrum of Rb tumorigenesis and prognosis. Materials and Methods: 16 AH samples and 4 Rb tumors from 12 patients with 14 Rb eyes were included in the study. We conducted global DNA methylation profiling of tumor tissues from surgically removed Rb eyes, AH samples collected from different clinical stages with different treatment outcomes using the Illumina Infinium EPIC DNA methylation BeadArray platform. Publicly available DNA methylation data of normal retina, Rb eyes, and Rb patients were obtained from Gene Expression Omnibus (GEO, GSE57362) for cell type DNA methylation comparisons. Results: Our preliminary studies revealed a high degree of concordance in genome-wide differential DNA methylation patterns between paired AH and tumor samples. Integrating our data with large public datasets, we identified reliable RB DNA methylation signatures in cfDNA that have potential diagnostic and prognostic values. We also identified hypermethylation at RB1 promoter, which suggested RB1 is druggable to DNA methylation inhibitors. By integrating DNA methylation data with gene expression data, we identified over 300 differentially expressed genes potentially regulated by DNA methylation change. Pathway analysis indicated several tumor suppressor pathways (e.g., RB1 and P53 pathways) were suppressed and some oncogenic pathways were activated (e.g., E2F pathways). Conclusions: Our study sets the stage for exploiting epigenetic markers in AH and identifying potential therapeutic targets to improve the clinical management of patients with RB. Citation Format: Liya Xu, Hongtao Li, Dan Weisenberger, Gangning Liang, Jesse Berry. Identifying DNA methylation signatures of retinoblastoma via aqueous humor, a novel ocular liquid biopsy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2499.

BackgroundCirculating free fatty acids are often elevated in patients with type 2 diabetes (T2D) and obese individuals. Chronic exposure to high levels of saturated fatty acids has detrimental effects on islet function and insulin secretion. Altered gene expression and epigenetics may contribute to T2D and obesity. However, there is limited information on whether fatty acids alter the genome-wide transcriptome profile in conjunction with DNA methylation patterns in human pancreatic islets. To dissect the molecular mechanisms linking lipotoxicity to impaired insulin secretion, we investigated the effects of a 48 h palmitate treatment in vitro on genome-wide mRNA expression and DNA methylation patterns in human pancreatic islets.MethodsGenome-wide mRNA expression was analyzed using Affymetrix GeneChip® Human Gene 1.0 ST whole transcript-based array (n = 13) and genome-wide DNA methylation was analyzed using Infinium HumanMethylation450K BeadChip (n = 13) in human pancreatic islets exposed to palmitate or control media for 48 h. A non-parametric paired Wilcoxon statistical test was used to analyze mRNA expression. Apoptosis was measured using Apo-ONE® Homogeneous Caspase-3/7 Assay (n = 4).ResultsWhile glucose-stimulated insulin secretion was decreased, there was no significant effect on apoptosis in human islets exposed to palmitate. We identified 1,860 differentially expressed genes in palmitate-treated human islets. These include candidate genes for T2D, such as TCF7L2, GLIS3, HNF1B and SLC30A8. Additionally, genes in glycolysis/gluconeogenesis, pyruvate metabolism, fatty acid metabolism, glutathione metabolism and one carbon pool by folate were differentially expressed in palmitate-treated human islets. Palmitate treatment altered the global DNA methylation level and DNA methylation levels of CpG island shelves and shores, 5′UTR, 3′UTR and gene body regions in human islets. Moreover, 290 genes with differential expression had a corresponding change in DNA methylation, for example, TCF7L2 and GLIS3. Importantly, out of the genes differentially expressed due to palmitate treatment in human islets, 67 were also associated with BMI and 37 were differentially expressed in islets from T2D patients.ConclusionOur study demonstrates that palmitate treatment of human pancreatic islets gives rise to epigenetic modifications that together with altered gene expression may contribute to impaired insulin secretion and T2D.

BackgroundPsychiatric symptomatology during late childhood and early adolescence tends to persist later in life. In the present longitudinal study, we aimed to identify changes in genome-wide DNA methylation patterns that were associated with the emergence of psychopathology in youths from the Brazilian High-Risk Cohort (HRC) for psychiatric disorders. Moreover, for the differentially methylated genes, we verified whether differences in DNA methylation corresponded to differences in mRNA transcript levels by analyzing the gene expression levels in the blood and by correlating the variation of DNA methylation values with the variation of mRNA levels of the same individuals. Finally, we examined whether the variations in DNA methylation and mRNA levels were correlated with psychopathology measurements over time.MethodsWe selected 24 youths from the HRC who presented with an increase in dimensional psychopathology at a 3-year follow-up as measured by the Child Behavior Checklist (CBCL). The DNA methylation and gene expression data were compared in peripheral blood samples (n = 48) obtained from the 24 youths before and after developing psychopathology. We implemented a methodological framework to reduce the effect of chronological age on DNA methylation using an independent population of 140 youths and the effect of puberty using data from the literature.ResultsWe identified 663 differentially methylated positions (DMPs) and 90 differentially methylated regions (DMRs) associated with the emergence of psychopathology. We observed that 15 DMPs were mapped to genes that were differentially expressed in the blood; among these, we found a correlation between the DNA methylation and mRNA levels of RB1CC1 and a correlation between the CBCL and mRNA levels of KMT2E. Of the DMRs, three genes were differentially expressed: ASCL2, which is involved in neurogenesis; HLA-E, which is mapped to the MHC loci; and RPS6KB1, the gene expression of which was correlated with an increase in the CBCL between the time points.ConclusionsWe observed that changes in DNA methylation and, consequently, in gene expression in the peripheral blood occurred concurrently with the emergence of dimensional psychopathology in youths. Therefore, epigenomic modulations might be involved in the regulation of an individual’s development of psychopathology.

Combined hepatocellular-cholangiocarcinoma (HCC-CCA) is a rare liver tumor comprising histologic features of both HCC and CCA. Due to its heterogeneous nature, treatment of combined HCC-CCA is a significant clinical challenge and prognosis remains poor. Therefore, further understanding of the tumor biology underlying the individual subtypes of this mixed tumor is required to improve treatment stratification and optimize treatment strategies. This study sought to identify epigenetic regulation underlying gene expression patterns in the individual components of combined HCC-CCA. Formalin fixed paraffin embedded tumor specimens from 10 patients diagnosed with combined HCC-CCA were utilized in this study. Hematoxylin and eosin staining was performed for each sample, and regions representative of the individual HCC and CCA components were delineated by a pathologist. Unstained slides were cut and dissected to separate HCC and CCA components. DNA and RNA extraction was performed for each sample for DNA methylation (n = 8 HCC and 7 CCA) and gene expression (n = 8 HCC and 8 CCA) profiling via reduced representation bisulfite sequencing and RNA-seq, respectively. As expected, DNA methylation levels at transcription start sites (TSS) were negatively correlated with gene expression in all samples (Spearman’s rho = -0.133 to -0.546; p &amp;lt; 2.2 x 10-16). Samples did not cluster by tumor subtype when comparing genome-wide DNA methylation and gene expression patterns. Interestingly, of the 5 patients with DNA methylation data available for both subtypes, 4 clustered by patient as opposed to cancer subtype, suggesting similar epigenetic regulatory patterns arising from development in the same microenvironment and genetic background. Differential gene expression analysis resulted in the identification of 58 differentially expressed genes (DEGs) between the HCC and CCA subtypes (q-value &amp;lt; 0.05). In addition, a total of 474 differentially methylated regions (DMRs) were identified between the HCC and CCA subtypes (minimum difference &amp;gt; 25%; q-value &amp;lt; 0.05). Of these, 422 DMRs overlapped with 324 known genes, 1 of which (STK38L) displayed increased expression (log2 fold change = 4.39; q-value = 0.01) associated with hypomethylation of 2 regions (-34.86% and -27.47%; q-value &amp;lt; 1 x 10-38) in the CCA compared to HCC group. STK38L encodes a serine/threonine kinase involved in Hippo signaling, a highly conserved signaling pathway that functions as a key coordinator of tissue growth and homeostasis. In all, these results provide insights into the epigenetic regulatory patterns associated with the two components of combined HCC-CCA. Future studies may aim to understand the effects of epigenetic regulation on treatment response for this deadly disease. Citation Format: Kyle M. Schachtschneider, Ryan Peter Lokken, Yu-Hui Huang, Grace Guzman, Lawrence B. Schook, Ron C. Gaba. Epigenetic regulation of combined hepatocellular-cholangiocarcinoma subtypes [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 4336.

Background: DNA methylation is a dynamic epigenetic mark that is essential for mammalian organismal development. For human prostate cancer (PCa), abundant evidence has accumulated to suggest that somatic epigenetic alterations may appear early during cancer development, as well as more commonly and consistently, than genetic changes. Several cancer-associated genes have been reported to show significant differences in DNA methylation pattern in prostate tissues from African-American (AA) and European-American men, but the genome-wide pattern and extent of these differences are largely unknown. The current study investigated genome-wide DNA methylation differences in AA and EA prostate tissue samples with the aim of assessing the variation of genome-wide patterns of DNA methylation. Methods: To comprehensively examine the DNA methylation pattern in AA and EA samples, we used illumina 450 K methylation platform (Infunium Chip) to conduct genome-wide large scale analysis of DNA methylation changes in 7 normal and 3 PCa tissue samples from AA versus 8 normal and 3 PCa tissue samples from EA. This chip interrogates &amp;gt;485,000 CpG methylation sites per sample at single-nucleotide resolution and assigns each site an average beta value for quantitative methylation level. Results: Pathway analysis of the genes with altered methylation patterns identified top canonical pathways for the involvement of cancer related network for genes involved in axonal guidance, antigen presentation, androgen signaling and protein ubiquitination pathways in prostate cancer tissues compared with normal prostate tissues obtained from AA men. On the other hand, the top canonical pathways identified in prostate cancer tissues compared with normal prostate tissues obtained from EA men are genes involved in epithelial-mesenchymal transition, p53 signaling, nucleotide sugars metabolism and germ cell-sertoli cell junction signaling pathways. Conclusion: Using this quantitative sequencing-based approach, our work uncovers significant global DNA methylation alterations in AA versus EA prostate tissues and provides a mechanistic explanation for the disease disparity. Citation Format: Bernard Kwabi-Addo, Songping Wang, Joseph Devaney. Epigenome-wide profiling identified significant differences in DNA methylation between African-American and European-American men with prostate cancer. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 388. doi:10.1158/1538-7445.AM2014-388

Potential epigenetic mechanisms underlying fetal alcohol syndrome (FAS) include alcohol-induced alterations of methyl metabolism, resulting in aberrant patterns of DNA methylation and gene expression during development. Having previously demonstrated an essential role for epigenetics in neural stem cell (NSC) development and that inhibiting DNA methylation prevents NSC differentiation, here we investigated the effect of alcohol exposure on genome-wide DNA methylation patterns and NSC differentiation. Neural stem cells in culture were treated with or without a 6-hour 88 mM ("binge-like") alcohol exposure and examined at 48 hours, for migration, growth, and genome-wide DNA methylation. The DNA methylation was examined using DNA-methylation immunoprecipitation followed by microarray analysis. Further validation was performed using Independent Sequenom analysis. Neural stem cell differentiated in 24 to 48 hours with migration, neuronal expression, and morphological transformation. Alcohol exposure retarded the migration, neuronal formation, and growth processes of NSC, similar to treatment with the methylation inhibitor 5-aza-cytidine. When NSC departed from the quiescent state, a genome-wide diversification of DNA methylation was observed-that is, many moderately methylated genes altered methylation levels and became hyper- and hypomethylated. Alcohol prevented many genes from such diversification, including genes related to neural development, neuronal receptors, and olfaction, while retarding differentiation. Validation of specific genes by Sequenom analysis demonstrated that alcohol exposure prevented methylation of specific genes associated with neural development [cut-like 2 (cutl2), insulin-like growth factor 1 (Igf1), epidermal growth factor-containing fibulin-like extracellular matrix protein 1 (Efemp1), and SRY-box-containing gene 7 (Sox 7)]; eye development, lens intrinsic membrane protein 2 (Lim 2); the epigenetic mark Smarca2 (SWI/SNF related, matrix associated, actin dependent regulator of chromatin, subfamily a, member 2); and developmental disorder [DiGeorge syndrome critical region gene 2 (Dgcr2)]. Specific sites altered by DNA methylation also correlated with transcription factor binding sites known to be critical for regulating neural development. The data indicate that alcohol prevents normal DNA methylation programming of key neural stem cell genes and retards NSC differentiation. Thus, the role of DNA methylation in FAS warrants further investigation.

Combined hepatocellular carcinoma-cholangiocarcinoma (HCC-CCA) is a rare liver tumor comprising histologic features of both HCC and CCA. Due to its heterogeneous nature, treatment of combined HCC-CCA is a significant clinical challenge and prognosis remains poor. Therefore, further understanding of the tumor biology underlying the individual subtypes of this mixed tumor is required to improve treatment stratification and optimize treatment strategies. This study sought to identify altered epigenetic regulation and gene expression patterns in the individual components of combined HCC-CCA. Formalin fixed paraffin embedded (FFPE) tumor specimens from 9 patients diagnosed with combined HCC-CCA were utilized in this study. Hematoxylin and eosin (H&E) staining was performed for each sample, and regions representative of the individual HCC and CCA components were delineated. Adjacent unstained slides were cut and dissected to separate HCC and CCA components. DNA and RNA extraction was performed for each sample for DNA methylation (n = 7 HCC and 7 CCA) and gene expression (n = 7 HCC and 8 CCA) profiling via reduced representation bisulfite sequencing (RRBS) and RNA-seq, respectively. Samples did not cluster by tumor type when comparing genome-wide DNA methylation or gene expression patterns. Of the 5 patients with DNA methylation data available for both subtypes, 4 clustered by patient as opposed to cancer subtype, suggesting similar epigenetic regulatory patterns arising from development in the same microenvironment and genetic background. Differential analysis resulted in the identification of 57 differentially expressed genes (DEGs) and 808 differentially methylated regions (DMRs) between the HCC and CCA subtypes. Genes associated with DMRs were associated with Wnt signaling, voltage-gated channels, metal binding, and cellular regulation. Finally, increased expression of several genes previously implicated in tumor aggressiveness, prognosis, and treatment responses were identified. These results highlight the potential importance of accounting for underlying HCC and CCA tumor biology when determining the optimal course of treatment for this deadly disease.

Epigenetic mechanisms are implicated in gene regulation and the development of different diseases. The epigenome differs between cell types and has until now only been characterized for a few human tissues. Environmental factors potentially alter the epigenome. Here we describe the genome-wide pattern of DNA methylation in human adipose tissue from 23 healthy men, with a previous low level of physical activity, before and after a six months exercise intervention. We also investigate the differences in adipose tissue DNA methylation between 31 individuals with or without a family history of type 2 diabetes. DNA methylation was analyzed using Infinium HumanMethylation450 BeadChip, an array containing 485,577 probes covering 99% RefSeq genes. Global DNA methylation changed and 17,975 individual CpG sites in 7,663 unique genes showed altered levels of DNA methylation after the exercise intervention (q<0.05). Differential mRNA expression was present in 1/3 of gene regions with altered DNA methylation, including RALBP1, HDAC4 and NCOR2 (q<0.05). Using a luciferase assay, we could show that increased DNA methylation in vitro of the RALBP1 promoter suppressed the transcriptional activity (p = 0.03). Moreover, 18 obesity and 21 type 2 diabetes candidate genes had CpG sites with differences in adipose tissue DNA methylation in response to exercise (q<0.05), including TCF7L2 (6 CpG sites) and KCNQ1 (10 CpG sites). A simultaneous change in mRNA expression was seen for 6 of those genes. To understand if genes that exhibit differential DNA methylation and mRNA expression in human adipose tissue in vivo affect adipocyte metabolism, we silenced Hdac4 and Ncor2 respectively in 3T3-L1 adipocytes, which resulted in increased lipogenesis both in the basal and insulin stimulated state. In conclusion, exercise induces genome-wide changes in DNA methylation in human adipose tissue, potentially affecting adipocyte metabolism.