A cross-package Bioconductor workflow for analysing methylation array data

Epigenetic clocks derived from western samples differentially reflect Taiwanese health outcomes

Introduction: Several epigenetic clocks have been developed, with five measures of epigenetic age acceleration (EAA) especially receiving extensive investigations: HannumEAA, IEAA, PhenoEAA, GrimEAA, and DunedinPACE. These epigenetic clocks were mainly developed by individuals of European or Hispanic ancestry. It remains unclear whether they can reflect disease morbidity and physiological conditions in Asian populations. Methods: I here investigated five measures of EAA of 2,474 Taiwan Biobank participants with DNA methylation data. Using logistic regressions, I sequentially regressed various health outcomes on each of the five measures of EAA while adjusting for chronological age, sex, body mass index, the number of smoking pack-years, drinking status, regular exercise, educational attainment, and six cell-type proportions. Results: Except for IEAA, all measures of EAA reflected the obesity of Taiwanese (p < 4.0E-4). Diabetes was reflected by DunedinPACE (p = 5.4E-6) and GrimEAA (p = 5.8E-5). Moreover, DunedinPACE was associated with dyslipidemia, including hypertriglyceridemia (p = 1.1E-5), low high-density lipoprotein cholesterol (HDL-C) (p = 4.0E-5), and high triglyceride to HDL-C ratio (p = 1.6E-7). Discussion: This is one of the first studies to show that epigenetic clocks (developed by individuals of European or Hispanic ancestry) can reflect Taiwanese physiological conditions. DunedinPACE was associated with more Taiwanese health outcomes than the other four measures of EAA.

Predicting the Lung Adenocarcinoma and Its Biomarkers by Integrating Gene Expression and DNA Methylation Data

The early symptoms of lung adenocarcinoma patients are inapparent, and the clinical diagnosis of lung adenocarcinoma is primarily through X-ray examination and pathological section examination, whereas the discovery of biomarkers points out another direction for the diagnosis of lung adenocarcinoma with the development of bioinformatics technology. However, it is not accurate and trustworthy to diagnose lung adenocarcinoma due to omics data with high-dimension and low-sample size (HDLSS) features or biomarkers produced by utilizing only single omics data. To address the above problems, the feature selection methods of biological analysis are used to reduce the dimension of gene expression data (GSE19188) and DNA methylation data (GSE139032, GSE49996). In addition, the Cartesian product method is used to expand the sample set and integrate gene expression data and DNA methylation data. The classification is built by using a deep neural network and is evaluated on K-fold cross validation. Moreover, gene ontology analysis and literature retrieving are used to analyze the biological relevance of selected genes, TCGA database is used for survival analysis of these potential genes through Kaplan-Meier estimates to discover the detailed molecular mechanism of lung adenocarcinoma. Survival analysis shows that COL5A2 and SERPINB5 are significant for identifying lung adenocarcinoma and are considered biomarkers of lung adenocarcinoma.

DNA Methylation Profiles of Purified Cell Types in Bronchoalveolar Lavage: Applications for Mixed Cell Paediatric Pulmonary Studies

In epigenome-wide association studies analysing DNA methylation from samples containing multiple cell types, it is essential to adjust the analysis for cell type composition. One well established strategy for achieving this is reference-based cell type deconvolution, which relies on knowledge of the DNA methylation profiles of purified constituent cell types. These are then used to estimate the cell type proportions of each sample, which can then be incorporated to adjust the association analysis. Bronchoalveolar lavage is commonly used to sample the lung in clinical practice and contains a mixture of different cell types that can vary in proportion across samples, affecting the overall methylation profile. A current barrier to the use of bronchoalveolar lavage in DNA methylation-based research is the lack of reference DNA methylation profiles for each of the constituent cell types, thus making reference-based cell composition estimation difficult. Herein, we use bronchoalveolar lavage samples collected from children with cystic fibrosis to define DNA methylation profiles for the four most common and clinically relevant cell types: alveolar macrophages, granulocytes, lymphocytes and alveolar epithelial cells. We then demonstrate the use of these methylation profiles in conjunction with an established reference-based methylation deconvolution method to estimate the cell type composition of two different tissue types; a publicly available dataset derived from artificial blood-based cell mixtures and further bronchoalveolar lavage samples. The reference DNA methylation profiles developed in this work can be used for future reference-based cell type composition estimation of bronchoalveolar lavage. This will facilitate the use of this tissue in studies examining the role of DNA methylation in lung health and disease.

Brain areas involved with obsessive-compulsive disorder present different DNA methylation modulation

Background

Obsessive-compulsive disorder (OCD) is characterized by intrusive thoughts and repetitive actions, that presents the involvement of the cortico-striatal areas. The contribution of environmental risk factors to OCD development suggests that epigenetic mechanisms may contribute to its pathophysiology. DNA methylation changes and gene expression were evaluated in post-mortem brain tissues of the cortical (anterior cingulate gyrus and orbitofrontal cortex) and ventral striatum (nucleus accumbens, caudate nucleus and putamen) areas from eight OCD patients and eight matched controls.

Results

There were no differentially methylated CpG (cytosine-phosphate-guanine) sites (DMSs) in any brain area, nevertheless gene modules generated from CpG sites and protein-protein-interaction (PPI) showed enriched gene modules for all brain areas between OCD cases and controls. All brain areas but nucleus accumbens presented a predominantly hypomethylation pattern for the differentially methylated regions (DMRs). Although there were common transcriptional factors that targeted these DMRs, their targeted differentially expressed genes were different among all brain areas. The protein-protein interaction network based on methylation and gene expression data reported that all brain areas were enriched for G-protein signaling pathway, immune response, apoptosis and synapse biological processes but each brain area also presented enrichment of specific signaling pathways. Finally, OCD patients and controls did not present significant DNA methylation age differences.

Conclusions

DNA methylation changes in brain areas involved with OCD, especially those involved with genes related to synaptic plasticity and the immune system could mediate the action of genetic and environmental factors associated with OCD.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12863-021-00993-0.

Redox Imbalance and Methylation Disturbances in Early Childhood Obesity

Obesity is increasing worldwide in prepubertal children, reducing the age of onset of associated comorbidities, including type 2 diabetes. Sulfur-containing amino acids, methionine, cysteine, and their derivatives play important roles in the transmethylation and transsulfuration pathways. Dysregulation of these pathways leads to alterations in the cellular methylation patterns and an imbalanced redox state. Therefore, we tested the hypothesis that one-carbon metabolism is already dysregulated in prepubertal children with obesity. Peripheral blood was collected from 64 children, and the plasma metabolites from transmethylation and transsulfuration pathways were quantified by HPLC. The cohort was stratified by BMI z-scores and HOMA-IR indices into healthy lean (HL), healthy obese (HO), and unhealthy obese (UHO). Fasting insulin levels were higher in the HO group compared to the HL, while the UHO had the highest. All groups presented normal fasting glycemia. Furthermore, high-density lipoprotein (HDL) was lower while triglycerides and lactate levels were higher in the UHO compared to HO subjects. S-adenosylhomocysteine (SAH) and total homocysteine levels were increased in the HO group compared to HL. Additionally, glutathione metabolism was also altered. Free cystine and oxidized glutathione (GSSG) were increased in the HO as compared to HL subjects. Importantly, the adipocyte secretory function was already compromised at this young age. Elevated circulating leptin and decreased adiponectin levels were observed in the UHO as compared to the HO subjects. Some of these alterations were concomitant with alterations in the DNA methylation patterns in the obese group, independent of the impaired insulin levels. In conclusion, our study informs on novel and important metabolic alterations in the transmethylation and the transsulfuration pathways in the early stages of obesity. Moreover, the altered secretory function of the adipocyte very early in life may be relevant in identifying early metabolic markers of disease that may inform on the increased risk for specific future comorbidities in this population.

Detecting Differentially Methylated Promoters in Genes Related to Disease Phenotypes Using R

DNA methylation in gene promoters plays a major role in gene expression regulation, and alterations in methylation patterns have been associated with several diseases. In this context, different software suites and statistical methods have been proposed to analyze differentially methylated positions and regions. Among them, the novel statistical method implemented in the mCSEA R package proposed a new framework to detect subtle, but consistent, methylation differences. Here, we provide an easy-to-use pipeline covering all the necessary steps to detect differentially methylated promoters with mCSEA from Illumina 450K and EPIC methylation BeadChips data. This protocol covers the download of data from public repositories, quality control, data filtering and normalization, estimation of cell type proportions, and statistical analysis. In addition, we show the procedure to compare disease vs. normal phenotypes, obtaining differentially methylated regions including promoters or CpG Islands. The entire protocol is based on R programming language, which can be used in any operating system and does not require advanced programming skills.

Estimands in epigenome-wide association studies

Background

In DNA methylation analyses like epigenome-wide association studies, effects in differentially methylated CpG sites are assessed. Two kinds of outcomes can be used for statistical analysis: Beta-values and M-values. M-values follow a normal distribution and help to detect differentially methylated CpG sites. As biological effect measures, differences of M-values are more or less meaningless. Beta-values are of more interest since they can be interpreted directly as differences in percentage of DNA methylation at a given CpG site, but they have poor statistical properties. Different frameworks are proposed for reporting estimands in DNA methylation analysis, relying on Beta-values, M-values, or both.

Results

We present and discuss four possible approaches of achieving estimands in DNA methylation analysis. In addition, we present the usage of M-values or Beta-values in the context of bioinformatical pipelines, which often demand a predefined outcome. We show the dependencies between the differences in M-values to differences in Beta-values in two data simulations: a analysis with and without confounder effect. Without present confounder effects, M-values can be used for the statistical analysis and Beta-values statistics for the reporting. If confounder effects exist, we demonstrate the deviations and correct the effects by the intercept method. Finally, we demonstrate the theoretical problem on two large human genome-wide DNA methylation datasets to verify the results.

Conclusions

The usage of M-values in the analysis of DNA methylation data will produce effect estimates, which cannot be biologically interpreted. The parallel usage of Beta-value statistics ignores possible confounder effects and can therefore not be recommended. Hence, if the differences in Beta-values are the focus of the study, the intercept method is recommendable. Hyper- or hypomethylated CpG sites must then be carefully evaluated. If an exploratory analysis of possible CpG sites is the aim of the study, M-values can be used for inference.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13148-021-01083-9.

The Comparative Methylome and Transcriptome After Change of Direction Compared to Straight Line Running Exercise in Human Skeletal Muscle

The methylome and transcriptome signatures following exercise that are physiologically and metabolically relevant to sporting contexts such as team sports or health prescription scenarios (e.g., high intensity interval training/HIIT) has not been investigated. To explore this, we performed two different sport/exercise relevant high-intensity running protocols in five male sport team members using a repeated measures design of: (1) change of direction (COD) versus; (2) straight line (ST) running exercise with a wash-out period of at least 2 weeks between trials. Skeletal muscle biopsies collected from the vastus lateralis 30 min and 24 h post exercise, were assayed using 850K methylation arrays and a comparative analysis with recent (subject-unmatched) sprint and acute aerobic exercise meta-analysis transcriptomes was performed. Despite COD and ST exercise being matched for classically defined intensity measures (speed × distance and number of accelerations/decelerations), COD exercise elicited greater movement (GPS-Playerload), physiological (HR), metabolic (lactate) as well as central and peripheral (differential RPE) exertion measures compared with ST exercise, suggesting COD exercise evoked a higher exercise intensity. The exercise response alone across both conditions evoked extensive alterations in the methylome 30 min and 24 h post exercise, particularly in MAPK, AMPK and axon guidance pathways. COD evoked a considerably greater hypomethylated signature across the genome compared with ST exercise, particularly at 30 min post exercise, enriched in: Protein binding, MAPK, AMPK, insulin, and axon guidance pathways. Comparative methylome analysis with sprint running transcriptomes identified considerable overlap, with 49% of genes that were altered at the expression level also differentially methylated after COD exercise. After differential methylated region analysis, we observed that VEGFA and its downstream nuclear transcription factor, NR4A1 had enriched hypomethylation within their promoter regions. VEGFA and NR4A1 were also significantly upregulated in the sprint transcriptome and meta-analysis of exercise transcriptomes. We also confirmed increased gene expression of VEGFA, and considerably larger increases in the expression of canonical metabolic genes PPARGC1A (that encodes PGC1-α) and NR4A3 in COD vs. ST exercise. Overall, we demonstrate that increased physiological/metabolic load via COD exercise in human skeletal muscle evokes considerable epigenetic modifications that are associated with changes in expression of genes responsible for adaptation to exercise.

Aggresomes predict poor outcomes and implicate proteostasis in the pathogenesis of pediatric choroid plexus tumors

Purpose

Protein misfolding and aggregation result in proteotoxic stress and underlie the pathogenesis of many diseases. To overcome proteotoxicity, cells compartmentalize misfolded and aggregated proteins in different inclusion bodies. The aggresome is a paranuclear inclusion body that functions as a storage compartment for misfolded proteins. Choroid plexus tumors (CPTs) are rare neoplasms comprised of three pathological subgroups. The underlying mechanisms of their pathogenesis remain unclear. This study aims to elucidate the prognostic role and the biological effects of aggresomes in pediatric CPTs.

Methods

We examined the presence of aggresomes in 42 patient-derived tumor tissues by immunohistochemistry and we identified their impact on patients’ outcomes. We then investigated the proteogenomics signature associated with aggresomes using whole-genome DNA methylation and proteomic analysis to define their role in the pathogenesis of pediatric CPTs.

Results

Aggresomes were detected in 64.2% of samples and were distributed among different pathological and molecular subgroups. The presence of aggresomes with different percentages was correlated with patients’ outcomes. The ≥ 25% cutoff had the most significant impact on overall and event-free survival (p-value < 0.001) compared to the pathological and the molecular stratifications.

Conclusions

These results support the role of aggresome as a novel prognostic molecular marker for pediatric CPTs that was comparable to the molecular classification in segregating samples into two distinct subgroups, and to the pathological stratification in the prediction of patients’ outcomes. Moreover, the proteogenomic signature of CPTs displayed altered protein homeostasis, manifested by enrichment in processes related to protein quality control.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11060-020-03694-3.

DNA methylation across the genome in aged human skeletal muscle tissue and muscle-derived cells: the role of HOX genes and physical activity

Skeletal muscle tissue demonstrates global hypermethylation with age. However, methylome changes across the time-course of differentiation in aged human muscle derived cells, and larger coverage arrays in aged muscle tissue have not been undertaken. Using 850K DNA methylation arrays we compared the methylomes of young (27 ± 4.4 years) and aged (83 ± 4 years) human skeletal muscle and that of young/aged heterogenous muscle-derived human primary cells (HDMCs) over several time points of differentiation (0, 72 h, 7, 10 days). Aged muscle tissue was hypermethylated compared with young tissue, enriched for; pathways-in-cancer (including; focal adhesion, MAPK signaling, PI3K-Akt-mTOR signaling, p53 signaling, Jak-STAT signaling, TGF-beta and notch signaling), rap1-signaling, axon-guidance and hippo-signalling. Aged cells also demonstrated a hypermethylated profile in pathways; axon-guidance, adherens-junction and calcium-signaling, particularly at later timepoints of myotube formation, corresponding with reduced morphological differentiation and reductions in MyoD/Myogenin gene expression compared with young cells. While young cells showed little alterations in DNA methylation during differentiation, aged cells demonstrated extensive and significantly altered DNA methylation, particularly at 7 days of differentiation and most notably in focal adhesion and PI3K-AKT signalling pathways. While the methylomes were vastly different between muscle tissue and HDMCs, we identified a small number of CpG sites showing a hypermethylated state with age, in both muscle tissue and cells on genes KIF15, DYRK2, FHL2, MRPS33, ABCA17P. Most notably, differential methylation analysis of chromosomal regions identified three locations containing enrichment of 6–8 CpGs in the HOX family of genes altered with age. With HOXD10, HOXD9, HOXD8, HOXA3, HOXC9, HOXB1, HOXB3, HOXC-AS2 and HOXC10 all hypermethylated in aged tissue. In aged cells the same HOX genes (and additionally HOXC-AS3) displayed the most variable methylation at 7 days of differentiation versus young cells, with HOXD8, HOXC9, HOXB1 and HOXC-AS3 hypermethylated and HOXC10 and HOXC-AS2 hypomethylated. We also determined that there was an inverse relationship between DNA methylation and gene expression for HOXB1, HOXA3 and HOXC-AS3. Finally, increased physical activity in young adults was associated with oppositely regulating HOXB1 and HOXA3 methylation compared with age. Overall, we demonstrate that a considerable number of HOX genes are differentially epigenetically regulated in aged human skeletal muscle and HDMCs and increased physical activity may help prevent age-related epigenetic changes in these HOX genes.

Genomic DNA methylation profiling indicates immune response following thermal ablation treatment for HBV-associated hepatocellular carcinoma

Hepatitis B virus (HBV)-associated hepatocellular carcinoma (HCC) is the most common type of liver cancer in China. Thermal ablation is one of the main strategies for HCC treatment. However, few studies have investigated the properties of the immune response following thermal ablation thus far. In the present study, five subjects with HBV-associated HCC were recruited from The Beijing Youan Hospital. Peripheral blood mononuclear cells (PBMCs) were collected at three time points: Prior to thermal ablation (PR), 1-3 days post-ablation (P1) and 5-7 days post-ablation (P7). An Illumina 850K methylation microarray was employed to determine the DNA methylation profile of each sample. Data were analyzed using different methylation probes with the Bioconductor package in R. Following annotation of different methylation CG sites (CGs), the associated genes were subjected to an Ingenuity Pathway Analysis. A total of 3,000 significantly different CGs (adjusted P<0.05; |log(fold-change)|>0.5) were identified within the PR, P1 and P7 time points. Of these, 744 (24.8%) sites increased between the PR and P1 time points but gradually decreased at the P7 time point. The remaining 2,256 (75.2%) sites decreased between the PR and P1 time points gradually increased at the P7 time point. Following gene annotation of different CGs on the promoter, signaling pathways analysis demonstrated that 'p70S6K signaling', 'CXCR4 signaling', 'dendritic cell maturation', 'production of nitric oxide and reactive oxygen species in macrophages' pathways were activated at the P7 time point. The present study suggested that PBMC DNA methylation had changed soon after thermal ablation for subjects with HBV-associated HCC, and systemic immune responses were activated, particularly at the P7 time point.

Assessment of DNA Methylation Patterns in the Bone and Cartilage of a Nonhuman Primate Model of Osteoarthritis

OBJECTIVE

Osteoarthritis (OA) affects humans and several other animals. Thus, the mechanisms underlying this disorder, such as specific skeletal tissue DNA methylation patterns, may be evolutionary conserved. However, associations between methylation and OA have not been readily studied in nonhuman animals. Baboons serve as important models of disease and develop OA at rates similar to those in humans. Therefore, this study investigated the associations between methylation and OA in baboons to advance the evolutionary understanding of OA.

DESIGN

Trabecular bone and cartilage was collected from the medial condyles of adult female baboon femora, 5 with and 5 without knee OA. The Infinium HumanMethylation450 BeadChip (450K array) was used to identify DNA methylation patterns in these tissues.

RESULTS

Approximately 44% of the 450K array probes reliably align to the baboon genome, contain a CpG site of interest, and maintain a wide distribution throughout the genome. Of the 2 filtering methods tested, both identified significantly differentially methylated positions (DMPs) between healthy and OA individuals in cartilage tissues, and some of these patterns overlap with those previously identified in humans. Conversely, no DMPs were found between tissue types or between disease states in bone tissues.

CONCLUSIONS

Overall, the 450K array can be used to measure genome-wide DNA methylation in baboon tissues and identify significant associations with complex traits. The results of this study indicate that some DNA methylation patterns associated with OA are evolutionarily conserved, while others are not. This warrants further investigation in a larger and more phylogenetically diverse sample set.

DNA methylation profiling reliably distinguishes pulmonary enteric adenocarcinoma from metastatic colorectal cancer

Pulmonary enteric adenocarcinoma is a rare non-small cell lung cancer subtype. It is poorly characterized and cannot be distinguished from metastatic colorectal or upper gastrointestinal adenocarcinomas by means of routine pathological methods. As DNA methylation patterns are known to be highly tissue specific, we aimed to develop a methylation-based algorithm to differentiate these entities. To this end, genome-wide methylation profiles of 600 primary pulmonary, colorectal, and upper gastrointestinal adenocarcinomas obtained from The Cancer Genome Atlas and the Gene Expression Omnibus database were used as a reference cohort to train a machine learning algorithm. The resulting classifier correctly classified all samples from a validation cohort consisting of 680 primary pulmonary, colorectal and upper gastrointestinal adenocarcinomas, demonstrating the ability of the algorithm to reliably distinguish these three entities. We then analyzed methylation data of 15 pulmonary enteric adenocarcinomas as well as four pulmonary metastases and four primary colorectal adenocarcinomas with the algorithm. All 15 pulmonary enteric adenocarcinomas were reliably classified as primary pulmonary tumors and all four metastases as well as all four primary colorectal cancer samples were identified as colorectal adenocarcinomas. In a t-distributed stochastic neighbor embedding analysis, the pulmonary enteric adenocarcinoma samples did not form a separate methylation subclass but rather diffusely intermixed with other pulmonary cancers. Additional characterization of the pulmonary enteric adenocarcinoma series using fluorescence in situ hybridization, next-generation sequencing and copy number analysis revealed KRAS mutations in nine of 15 samples (60%) and a high number of structural chromosomal changes. Except for an unusually high rate of chromosome 20 gain (67%), the molecular data was mostly reminiscent of standard pulmonary adenocarcinomas. In conclusion, we provide sound evidence of the pulmonary origin of pulmonary enteric adenocarcinomas and in addition provide a publicly available machine learning-based algorithm to reliably distinguish these tumors from metastatic colorectal cancer.

Laundry detergents and detergent residue after rinsing directly disrupt tight junction barrier integrity in human bronchial epithelial cells

BACKGROUND

Defects in the epithelial barrier have recently been associated with asthma and other allergies. The influence of laundry detergents on human bronchial epithelial cells (HBECs) and their barrier function remain unknown.

OBJECTIVE

We investigated the effects of laundry detergents on cytotoxicity, barrier function, the transcriptome, and the epigenome in HBECs.

METHODS

Air-liquid interface cultures of primary HBECs from healthy control subjects, patients with asthma, and patients with chronic obstructive pulmonary disease were exposed to laundry detergents and detergent residue after rinsing. Cytotoxicity and epithelial barrier function were evaluated. RNA sequencing, Assay for Transposase Accessible Chromatin with high-throughput sequencing, and DNA methylation arrays were used for checking the transcriptome and epigenome.

RESULTS

Laundry detergents and rinse residue showed dose-dependent toxic effects on HBECs, with irregular cell shape and leakage of lactate dehydrogenase after 24 hours of exposure. A disrupted epithelial barrier function was found with decreased transepithelial electrical resistance, increased paracellular flux, and stratified tight junction (TJ) immunostaining in HBECs exposed to laundry detergent at 1:25,000 dilutions or rinse residue at further 1:10 dilutions. RNA sequencing analysis showed that lipid metabolism, apoptosis progress, and epithelially derived alarmin-related gene expression were upregulated, whereas cell adhesion-related gene expression was downregulated by laundry detergent at 1:50,000 dilutions after 24 hours of exposure without substantially affecting chromatin accessibility and DNA methylation.

CONCLUSION

Our data demonstrate that laundry detergents, even at a very high dilution, and rinse residue show significant cell-toxic and directly disruptive effects on the TJ barrier integrity of HBECs without affecting the epigenome and TJ gene expression.

Multi-generational impacts of arsenic exposure on genome-wide DNA methylation and the implications for arsenic-induced skin lesions

As a nonmutagenic human carcinogen, arsenic (As)'s carcinogenic activity is likely the result of epigenetic changes, particularly alterations in DNA methylation. While increasing studies indicate a potentially important role for timing of As exposure on DNA methylation patterns and the subsequent differential risks for As toxicity and carcinogenesis, there is a lack of research that tackles these critical questions, particularly in human based populations. Here we reported a family-based study including three generations, in which each generation living in the same household had a distinctive timing of As exposure: in adulthood, in utero and during early childhood, and in germlines exposure for grandparents, parents, and grandchildren, respectively. We generated genome-wide DNA methylation data for 18 As-exposed families, nine control families, as well as 18 arsenical skin lesion patients. Our analysis showed that As exposure may leave detectable DNA methylation changes even though exposure occurred decades ago, and the most significant changes of global DNA methylation were observed among patients afflicted with arsenical skin lesions. As exposure across generations shared common differentially methylated DNA loci and regions (744 DML and 15 DMRs) despite the distinctive exposure timing in each generation. Importantly, based on these DML, clustering analysis grouped skin lesion patients together with grandparents in exposed families in the same cluster, separated from grandparents in control families. Further analysis identified a number of DML and several molecular pathways that were significantly distinguished between controls, exposed populations, as well as skin lesion patients. Finally, our exploratory analysis suggested that some of these DML altered by As exposure, may have the potential to be inherited affecting not only those directly exposed but also later generations. Together, our results suggest that common DML and/or DMRs associated with an increased risk for disease development could be identified regardless of when exposure to As occurred during their life span, and thus may be able to serve as biomarkers for identifying individuals at risk for As-induced skin lesions and possible cancers.

The Genomic Impact of DNA CpG Methylation on Gene Expression; Relationships in Prostate Cancer

The process of DNA CpG methylation has been extensively investigated for over 50 years and revealed associations between changing methylation status of CpG islands and gene expression. As a result, DNA CpG methylation is implicated in the control of gene expression in developmental and homeostasis processes, as well as being a cancer-driver mechanism. The development of genome-wide technologies and sophisticated statistical analytical approaches has ushered in an era of widespread analyses, for example in the cancer arena, of the relationships between altered DNA CpG methylation, gene expression, and tumor status. The remarkable increase in the volume of such genomic data, for example, through investigators from the Cancer Genome Atlas (TCGA), has allowed dissection of the relationships between DNA CpG methylation density and distribution, gene expression, and tumor outcome. In this manner, it is now possible to test that the genome-wide correlations are measurable between changes in DNA CpG methylation and gene expression. Perhaps surprisingly is that these associations can only be detected for hundreds, but not thousands, of genes, and the direction of the correlations are both positive and negative. This, perhaps, suggests that CpG methylation events in cancer systems can act as disease drivers but the effects are possibly more restricted than suspected. Additionally, the positive and negative correlations suggest direct and indirect events and an incomplete understanding. Within the prostate cancer TCGA cohort, we examined the relationships between expression of genes that control DNA methylation, known targets of DNA methylation and tumor status. This revealed that genes that control the synthesis of S-adenosyl-l-methionine (SAM) associate with altered expression of DNA methylation targets in a subset of aggressive tumors.