A beta-mixture quantile normalization method for correcting probe design bias in Illumina Infinium 450 k DNA methylation data

An integrative pan-cancer-wide analysis of epigenetic enzymes reveals universal patterns of epigenomic deregulation in cancer

Background

One 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.

Results

Here 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.

Conclusions

This 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 material

The online version of this article (doi:10.1186/s13059-015-0699-9) contains supplementary material, which is available to authorized users.

A genome-wide identified risk variant for PTSD is a methylation quantitative trait locus and confers decreased cortical activation to fearful faces

Genetic factors appear to be highly relevant to predicting differential risk for the development of post-traumatic stress disorder (PTSD). In a discovery sample, we conducted a genome-wide association study (GWAS) for PTSD using a small military cohort (Systems Biology PTSD Biomarkers Consortium; SBPBC, N = 147) that was designed as a case-controlled sample of highly exposed, recently returning veterans with and without combat-related PTSD. A genome-wide significant single nucleotide polymorphism (SNP), rs717947, at chromosome 4p15 (N = 147, β = 31.34, P = 1.28 × 10(-8) ) was found to associate with the gold-standard diagnostic measure for PTSD (the Clinician Administered PTSD Scale). We conducted replication and follow-up studies in an external sample, a larger urban community cohort (Grady Trauma Project, GTP, N = 2006), to determine the robustness and putative functionality of this risk variant. In the GTP replication sample, SNP rs717947 associated with PTSD diagnosis in females (N = 2006, P = 0.005), but not males. SNP rs717947 was also found to be a methylation quantitative trait locus (meQTL) in the GTP replication sample (N = 157, P = 0.002). Further, the risk allele of rs717947 was associated with decreased medial and dorsolateral cortical activation to fearful faces (N = 53, P < 0.05) in the GTP replication sample. These data identify a genome-wide significant polymorphism conferring risk for PTSD, which was associated with differential epigenetic regulation and with differential cortical responses to fear in a replication sample. These results may provide new insight into understanding genetic and epigenetic regulation of PTSD and intermediate phenotypes that contribute to this disorder.

Mutational dynamics between primary and relapse neuroblastomas

Neuroblastoma is a malignancy of the developing sympathetic nervous system that is often lethal when relapse occurs. We here used whole-exome sequencing, mRNA expression profiling, array CGH and DNA methylation analysis to characterize 16 paired samples at diagnosis and relapse from individuals with neuroblastoma. The mutational burden significantly increased in relapsing tumors, accompanied by altered mutational signatures and reduced subclonal heterogeneity. Global allele frequencies at relapse indicated clonal mutation selection during disease progression. Promoter methylation patterns were consistent over disease course and were patient specific. Recurrent alterations at relapse included mutations in the putative CHD5 neuroblastoma tumor suppressor, chromosome 9p losses, DOCK8 mutations, inactivating mutations in PTPN14 and a relapse-specific activity pattern for the PTPN14 target YAP. Recurrent new mutations in HRAS, KRAS and genes mediating cell-cell interaction in 13 of 16 relapse tumors indicate disturbances in signaling pathways mediating mesenchymal transition. Our data shed light on genetic alteration frequency, identity and evolution in neuroblastoma.

A panel of induced pluripotent stem cells from chimpanzees: a resource for comparative functional genomics

Comparative genomics studies in primates are restricted due to our limited access to samples. In order to gain better insight into the genetic processes that underlie variation in complex phenotypes in primates, we must have access to faithful model systems for a wide range of cell types. To facilitate this, we generated a panel of 7 fully characterized chimpanzee induced pluripotent stem cell (iPSC) lines derived from healthy donors. To demonstrate the utility of comparative iPSC panels, we collected RNA-sequencing and DNA methylation data from the chimpanzee iPSCs and the corresponding fibroblast lines, as well as from 7 human iPSCs and their source lines, which encompass multiple populations and cell types. We observe much less within-species variation in iPSCs than in somatic cells, indicating the reprogramming process erases many inter-individual differences. The low within-species regulatory variation in iPSCs allowed us to identify many novel inter-species regulatory differences of small magnitude.

DOI:http://dx.doi.org/10.7554/eLife.07103.001

Comparing the genomes of different species can reveal how they are related to one another. Such comparative studies can also reveal how genomes are modified in species-specific ways to regulate gene activity. The genomes of humans and chimpanzees are very similar in sequence. It is therefore likely that differing patterns of gene regulation underlie many of the differences observed between the two species. However, only a few kinds of chimpanzee cell that can be grown in the laboratory are available for research; this lack of samples has limited the ability of researchers to perform such comparative studies.

One way around this problem is to use induced pluripotent stem cells (or iPSCs). IPSCs are created by exposing mature cells—for example, skin cells—to conditions and molecules that convert them into an embryonic-like state. This state—called ‘induced pluripotency’—allows the cells to be coaxed into becoming many different cell types that can be grown in the laboratory. But it is more difficult to establish high quality iPSCs from chimpanzees than it is from humans or mice.

Gallego Romero, Pavlovic et al. have now addressed this problem by creating iPSCs from skin cells taken from seven healthy chimpanzees. These cell lines were then analysed and compared to each other and to seven iPSC lines created from human cells. The chimpanzee iPSC lines were found to be much more similar to each other than the mature cells that were used to make them. Similar results were also observed for the human iSPCs, which likely reflects the conserved changes that take place when the genomes of mature cells are reprogrammed to pluripotency.

This high level of similarity between iPSCs from different individuals of the same species allowed Gallego Romero, Pavlovic et al. to discover many subtle differences in gene regulation between chimpanzees and humans. For example, over 4500 genes were found to be expressed differently in human and chimpanzee iPSCs, and over 3500 genomic regions had different patterns of certain DNA modifications that can help to regulate gene expression.

These newly created chimpanzee iPSC lines represent a valuable resource for comparative studies of gene regulation. In the future, this resource could help researchers to identify further differences in gene regulation between closely related primate species.

DOI:http://dx.doi.org/10.7554/eLife.07103.002

Novel epigenetic determinants of type 2 diabetes in Mexican-American families

Although DNA methylation is now recognized as an important mediator of complex diseases, the extent to which the genetic basis of such diseases is accounted for by DNA methylation is unknown. In the setting of large, extended families representing a minority, high-risk population of the USA, we aimed to characterize the role of epigenome-wide DNA methylation in type 2 diabetes (T2D). Using Illumina HumanMethylation450 BeadChip arrays, we tested for association of DNA methylation at 446 356 sites with age, sex and phenotypic traits related to T2D in 850 pedigreed Mexican-American individuals. Robust statistical analyses showed that (i) 15% of the methylome is significantly heritable, with a median heritability of 0.14; (ii) DNA methylation at 14% of CpG sites is associated with nearby sequence variants; (iii) 22% and 3% of the autosomal CpG sites are associated with age and sex, respectively; (iv) 53 CpG sites were significantly associated with liability to T2D, fasting blood glucose and insulin resistance; (v) DNA methylation levels at five CpG sites, mapping to three well-characterized genes (TXNIP, ABCG1 and SAMD12) independently explained 7.8% of the heritability of T2D (vi) methylation at these five sites was unlikely to be influenced by neighboring DNA sequence variation. Our study has identified novel epigenetic indicators of T2D risk in Mexican Americans who have increased risk for this disease. These results provide new insights into potential treatment targets of T2D.

Independent genomewide screens identify the tumor suppressor VTRNA2-1 as a human epiallele responsive to periconceptional environment

BACKGROUND

Interindividual epigenetic variation that occurs systemically must be established prior to gastrulation in the very early embryo and, because it is systemic, can be assessed in easily biopsiable tissues. We employ two independent genome-wide approaches to search for such variants.

RESULTS

First, we screen for metastable epialleles by performing genomewide bisulfite sequencing in peripheral blood lymphocyte (PBL) and hair follicle DNA from two Caucasian adults. Second, we conduct a genomewide screen for genomic regions at which PBL DNA methylation is affected by season of conception in rural Gambia. Remarkably, both approaches identify the genomically imprinted VTRNA2-1 as a top environmentally responsive epiallele. We demonstrate systemic and stochastic interindividual variation in DNA methylation at the VTRNA2-1 differentially methylated region in healthy Caucasian and Asian adults and show, in rural Gambians, that periconceptional environment affects offspring VTRNA2-1 epigenotype, which is stable over at least 10 years. This unbiased screen also identifies over 100 additional candidate metastable epialleles, and shows that these are associated with cis genomic features including transposable elements.

CONCLUSIONS

The non-coding VTRNA2-1 transcript (also called nc886) is a putative tumor suppressor and modulator of innate immunity. Thus, these data indicating environmentally induced loss of imprinting at VTRNA2-1 constitute a plausible causal pathway linking early embryonic environment, epigenetic alteration, and human disease. More broadly, the list of candidate metastable epialleles provides a resource for future studies of epigenetic variation and human disease.

Compound hierarchical correlated beta mixture with an application to cluster mouse transcription factor DNA binding data

Modeling correlation structures is a challenge in bioinformatics, especially when dealing with high throughput genomic data. A compound hierarchical correlated beta mixture (CBM) with an exchangeable correlation structure is proposed to cluster genetic vectors into mixture components. The correlation coefficient, [Formula: see text], is homogenous within a mixture component and heterogeneous between mixture components. A random CBM with [Formula: see text] brings more flexibility in explaining correlation variations among genetic variables. Expectation-Maximization (EM) algorithm and Stochastic Expectation-Maximization (SEM) algorithm are used to estimate parameters of CBM. The number of mixture components can be determined using model selection criteria such as AIC, BIC and ICL-BIC. Extensive simulation studies were conducted to compare EM, SEM and model selection criteria. Simulation results suggest that CBM outperforms the traditional beta mixture model with lower estimation bias and higher classification accuracy. The proposed method is applied to cluster transcription factor-DNA binding probability in mouse genome data generated by Lahdesmaki and others (2008, Probabilistic inference of transcription factor binding from multiple data sources. PLoS One, 3: , e1820). The results reveal distinct clusters of transcription factors when binding to promoter regions of genes in JAK-STAT, MAPK and other two pathways.

Lessons learned in the analysis of high-dimensional data in vaccinomics

The field of vaccinology is increasingly moving toward the generation, analysis, and modeling of extremely large and complex high-dimensional datasets. We have used data such as these in the development and advancement of the field of vaccinomics to enable prediction of vaccine responses and to develop new vaccine candidates. However, the application of systems biology to what has been termed "big data," or "high-dimensional data," is not without significant challenges-chief among them a paucity of gold standard analysis and modeling paradigms with which to interpret the data. In this article, we relate some of the lessons we have learned over the last decade of working with high-dimensional, high-throughput data as applied to the field of vaccinomics. The value of such efforts, however, is ultimately to better understand the immune mechanisms by which protective and non-protective responses to vaccines are generated, and to use this information to support a personalized vaccinology approach in creating better, and safer, vaccines for the public health.

The cerebellum ages slowly according to the epigenetic clock

Studies that elucidate why some human tissues age faster than others may shed light on how we age, and ultimately suggest what interventions may be possible. Here we utilize a recent biomarker of aging (referred to as epigenetic clock) to assess the epigenetic ages of up to 30 anatomic sites from supercentenarians (subjects who reached an age of 110 or older) and younger subjects. Using three novel and three published human DNA methylation data sets, we demonstrate that the cerebellum ages more slowly than other parts of the human body. We used both transcriptional data and genetic data to elucidate molecular mechanisms which may explain this finding. The two largest superfamilies of helicases (SF1 and SF2) are significantly over-represented (p=9.2x10-9) among gene transcripts that are over-expressed in the cerebellum compared to other brain regions from the same subject. Furthermore, SNPs that are associated with epigenetic age acceleration in the cerebellum tend to be located near genes from helicase superfamilies SF1 and SF2 (enrichment p=5.8x10-3). Our genetic and transcriptional studies of epigenetic age acceleration support the hypothesis that the slow aging rate of the cerebellum is due to processes that involve RNA helicases.

Epigenome-wide association study (EWAS) of BMI, BMI change and waist circumference in African American adults identifies multiple replicated loci

Obesity is an important component of the pathophysiology of chronic diseases. Identifying epigenetic modifications associated with elevated adiposity, including DNA methylation variation, may point to genomic pathways that are dysregulated in numerous conditions. The Illumina 450K Bead Chip array was used to assay DNA methylation in leukocyte DNA obtained from 2097 African American adults in the Atherosclerosis Risk in Communities (ARIC) study. Mixed-effects regression models were used to test the association of methylation beta value with concurrent body mass index (BMI) and waist circumference (WC), and BMI change, adjusting for batch effects and potential confounders. Replication using whole-blood DNA from 2377 White adults in the Framingham Heart Study and CD4+ T cell DNA from 991 Whites in the Genetics of Lipid Lowering Drugs and Diet Network Study was followed by testing using adipose tissue DNA from 648 women in the Multiple Tissue Human Expression Resource cohort. Seventy-six BMI-related probes, 164 WC-related probes and 8 BMI change-related probes passed the threshold for significance in ARIC (P < 1 × 10(-7); Bonferroni), including probes in the recently reported HIF3A, CPT1A and ABCG1 regions. Replication using blood DNA was achieved for 37 BMI probes and 1 additional WC probe. Sixteen of these also replicated in adipose tissue, including 15 novel methylation findings near genes involved in lipid metabolism, immune response/cytokine signaling and other diverse pathways, including LGALS3BP, KDM2B, PBX1 and BBS2, among others. Adiposity traits are associated with DNA methylation at numerous CpG sites that replicate across studies despite variation in tissue type, ethnicity and analytic approaches.

Comparative methylome analysis in solid tumors reveals aberrant methylation at chromosome 6p in nasopharyngeal carcinoma

Altered patterns of DNA methylation are key features of cancer. Nasopharyngeal carcinoma (NPC) has the highest incidence in Southern China. Aberrant methylation at the promoter region of tumor suppressors is frequently reported in NPC; however, genome-wide methylation changes have not been comprehensively investigated. Therefore, we systematically analyzed methylome data in 25 primary NPC tumors and nontumor counterparts using a high-throughput approach with the Illumina HumanMethylation450 BeadChip. Comparatively, we examined the methylome data of 11 types of solid tumors collected by The Cancer Genome Atlas (TCGA). In NPC, the hypermethylation pattern was more dominant than hypomethylation and the majority of de novo methylated loci were within or close to CpG islands in tumors. The comparative methylome analysis reveals hypermethylation at chromosome 6p21.3 frequently occurred in NPC (false discovery rate; FDR=1.33 × 10⁻⁹), but was less obvious in other types of solid tumors except for prostate and Epstein–Barr virus (EBV)-positive gastric cancer (FDR<10⁻³). Bisulfite pyrosequencing results further confirmed the aberrant methylation at 6p in an additional patient cohort. Evident enrichment of the repressive mark H3K27me3 and active mark H3K4me3 derived from human embryonic stem cells were found at these regions, indicating both DNA methylation and histone modification function together, leading to epigenetic deregulation in NPC. Our study highlights the importance of epigenetic deregulation in NPC. Polycomb Complex 2 (PRC2), responsible for H3K27 trimethylation, is a promising therapeutic target. A key genomic region on 6p with aberrant methylation was identified. This region contains several important genes having potential use as biomarkers for NPC detection.

Pan-cancer stratification of solid human epithelial tumors and cancer cell lines reveals commonalities and tissue-specific features of the CpG island methylator phenotype

Background

The term CpG island methylator phenotype (CIMP) has been used to describe widespread DNA hypermethylation at CpG-rich genomic regions affecting clinically distinct subsets of cancer patients. Even though there have been numerous studies of CIMP in individual cancer types, a uniform analysis across tissues is still lacking.

Results

We analyze genome-wide patterns of CpG island hypermethylation in 5,253 solid epithelial tumors from 15 cancer types from TCGA and 23 cancer cell lines from ENCODE. We identify differentially methylated loci that define CIMP+ and CIMP− samples, and we use unsupervised clustering to provide a robust molecular stratification of tumor methylomes for 12 cancer types and all cancer cell lines. With a minimal set of 89 discriminative loci, we demonstrate accurate pan-cancer separation of the 12 CIMP+/− subpopulations, based on their average levels of methylation. Tumor samples in different CIMP subclasses show distinctive correlations with gene expression profiles and recurrence of somatic mutations, copy number variations, and epigenetic silencing. Enrichment analyses indicate shared canonical pathways and upstream regulators for CIMP-targeted regions across cancer types. Furthermore, genomic alterations showing consistent associations with CIMP+/− status include genes involved in DNA repair, chromatin remodeling genes, and several histone methyltransferases. Associations of CIMP status with specific clinical features, including overall survival in several cancer types, highlight the importance of the CIMP+/− designation for individual tumor evaluation and personalized medicine.

Conclusions

We present a comprehensive computational study of CIMP that reveals pan-cancer commonalities and tissue-specific differences underlying concurrent hypermethylation of CpG islands across tumors. Our stratification of solid tumors and cancer cell lines based on CIMP status is data-driven and agnostic to tumor type by design, which protects against known biases that have hindered classic methods previously used to define CIMP. The results that we provide can be used to refine existing molecular subtypes of cancer into more homogeneously behaving subgroups, potentially leading to more uniform responses in clinical trials.

Electronic supplementary material

The online version of this article (doi:10.1186/s13072-015-0007-7) contains supplementary material, which is available to authorized users.

Genome wide DNA methylation profiles provide clues to the origin and pathogenesis of germ cell tumors

The cell of origin of the five subtypes (I-V) of germ cell tumors (GCTs) are assumed to be germ cells from different maturation stages. This is (potentially) reflected in their methylation status as fetal maturing primordial germ cells are globally demethylated during migration from the yolk sac to the gonad. Imprinted regions are erased in the gonad and later become uniparentally imprinted according to fetal sex. Here, 91 GCTs (type I-IV) and four cell lines were profiled (Illumina’s HumanMethylation450BeadChip). Data was pre-processed controlling for cross hybridization, SNPs, detection rate, probe-type bias and batch effects. The annotation was extended, covering snRNAs/microRNAs, repeat elements and imprinted regions. A Hidden Markov Model-based genome segmentation was devised to identify differentially methylated genomic regions. Methylation profiles allowed for separation of clusters of non-seminomas (type II), seminomas/dysgerminomas (type II), spermatocytic seminomas (type III) and teratomas/dermoid cysts (type I/IV). The seminomas, dysgerminomas and spermatocytic seminomas were globally hypomethylated, in line with previous reports and their demethylated precursor. Differential methylation and imprinting status between subtypes reflected their presumed cell of origin. Ovarian type I teratomas and dermoid cysts showed (partial) sex specific uniparental maternal imprinting. The spermatocytic seminomas showed uniparental paternal imprinting while testicular teratomas exhibited partial imprinting erasure. Somatic imprinting in type II GCTs might indicate a cell of origin after global demethylation but before imprinting erasure. This is earlier than previously described, but agrees with the totipotent/embryonic stem cell like potential of type II GCTs and their rare extra-gonadal localization. The results support the common origin of the type I teratomas and show strong similarity between ovarian type I teratomas and dermoid cysts. In conclusion, we identified specific and global methylation differences between GCT subtypes, providing insight into their developmental timing and underlying developmental biology. Data and extended annotation are deposited at GEO (GSE58538 and GPL18809).

Impact of age, BMI and HbA1c levels on the genome-wide DNA methylation and mRNA expression patterns in human adipose tissue and identification of epigenetic biomarkers in blood

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.

Genome-wide blood DNA methylation alterations at regulatory elements and heterochromatic regions in monozygotic twins discordant for obesity and liver fat

Background

The current epidemic of obesity and associated diseases calls for swift actions to better understand the mechanisms by which genetics and environmental factors affect metabolic health in humans. Monozygotic (MZ) twin pairs showing discordance for obesity suggest that epigenetic influences represent one such mechanism. We studied genome-wide leukocyte DNA methylation variation in 30 clinically healthy young adult MZ twin pairs discordant for body mass index (BMI; average within-pair BMI difference: 5.4 ± 2.0 kg/m²).

Results

There were no differentially methylated cytosine-guanine (CpG) sites between the co-twins discordant for BMI. However, stratification of the twin pairs based on the level of liver fat accumulation revealed two epigenetically highly different groups. Significant DNA methylation differences (n = 1,236 CpG sites (CpGs)) between the co-twins were only observed if the heavier co-twins had excessive liver fat (n = 13 twin pairs). This unhealthy pattern of obesity was coupled with insulin resistance and low-grade inflammation. The differentially methylated CpGs included 23 genes known to be associated with obesity, liver fat, type 2 diabetes mellitus (T2DM) and metabolic syndrome, and potential novel metabolic genes. Differentially methylated CpG sites were overrepresented at promoters, insulators, and heterochromatic and repressed regions. Based on predictions by overlapping histone marks, repressed and weakly transcribed sites were significantly more often hypomethylated, whereas sites with strong enhancers and active promoters were hypermethylated. Further, significant clustering of differentially methylated genes in vitamin, amino acid, fatty acid, sulfur, and renin-angiotensin metabolism pathways was observed.

Conclusions

The methylome in leukocytes is altered in obesity associated with metabolic disturbances, and our findings indicate several novel candidate genes and pathways in obesity and obesity-related complications.

Electronic supplementary material

The online version of this article (doi:10.1186/s13148-015-0073-5) contains supplementary material, which is available to authorized users.

Correlation between Reversal of DNA Methylation and Clinical Symptoms in Psoriatic Epidermis Following Narrow-Band UVB Phototherapy

Epigenetic modifications by DNA methylation are associated with a wide range of diseases. Previous studies in psoriasis have concentrated on epigenetic changes in immune cells or in total skin biopsies that include stromal-associated changes. In order to improve our understanding of the role of DNA methylation in psoriasis, we sought to obtain a comprehensive DNA methylation signature specific for the epidermal component of psoriasis and to analyze methylation changes during therapy. Genome-wide DNA methylation profiling of epidermal cells from 12 patients undergoing narrow-band UVB phototherapy and 12 corresponding healthy controls revealed a distinct DNA methylation pattern in psoriasis compared with controls. A total of 3,665 methylation variable positions (MVPs) were identified with an overall hypomethylation in psoriasis patient samples. DNA methylation pattern was reversed at the end of phototherapy in patients showing excellent clinical improvement. Only 7% of phototherapy-affected MVPs (150 out of 2,108) correlate with nearby gene expression. Enrichment of MVPs in enhancers indicates tissue-specific modulation of the transcriptional regulatory machinery in psoriasis. Our study identified key epigenetic events associated with psoriasis pathogenesis and helps understand the dynamic DNA methylation landscape in the human genome.

Variational Bayesian Matrix Factorization for Bounded Support Data

A novel Bayesian matrix factorization method for bounded support data is presented. Each entry in the observation matrix is assumed to be beta distributed. As the beta distribution has two parameters, two parameter matrices can be obtained, which matrices contain only nonnegative values. In order to provide low-rank matrix factorization, the nonnegative matrix factorization (NMF) technique is applied. Furthermore, each entry in the factorized matrices, i.e., the basis and excitation matrices, is assigned with gamma prior. Therefore, we name this method as beta-gamma NMF (BG-NMF). Due to the integral expression of the gamma function, estimation of the posterior distribution in the BG-NMF model can not be presented by an analytically tractable solution. With the variational inference framework and the relative convexity property of the log-inverse-beta function, we propose a new lower-bound to approximate the objective function. With this new lower-bound, we derive an analytically tractable solution to approximately calculate the posterior distributions. Each of the approximated posterior distributions is also gamma distributed, which retains the conjugacy of the Bayesian estimation. In addition, a sparse BG-NMF can be obtained by including a sparseness constraint to the gamma prior. Evaluations with synthetic data and real life data demonstrate the good performance of the proposed method.

DNA methylation markers for early detection of women's cancer: promise and challenges

Breast, ovarian and endometrial cancers cause significant morbidity and mortality. Despite the presence of existing screening, diagnostic and treatment modalities, they continue to pose considerable unsolved challenges. Overdiagnosis is a growing problem in breast cancer screening and neither screening nor early diagnosis of ovarian or endometrial cancer is currently possible. Moreover, treatment of the diversity of these cancers presenting in the clinic is not sufficiently personalized at present. Recent technological advances, including reduced representation bisulfite sequencing, methylation arrays, digital PCR, next-generation sequencing and advanced statistical data analysis, enable the analysis of methylation patterns in cell-free tumor DNA in serum/plasma. Ongoing work is bringing these methods together for the analysis of samples from large clinical trials, which have been collected well in advance of cancer diagnosis. These efforts pave the way for the development of a noninvasive method that would enable us to overcome existing challenges to personalized medicine.

Acceleration of age-associated methylation patterns in HIV-1-infected adults

Patients with treated HIV-1-infection experience earlier occurrence of aging-associated diseases, raising speculation that HIV-1-infection, or antiretroviral treatment, may accelerate aging. We recently described an age-related co-methylation module comprised of hundreds of CpGs; however, it is unknown whether aging and HIV-1-infection exert negative health effects through similar, or disparate, mechanisms. We investigated whether HIV-1-infection would induce age-associated methylation changes. We evaluated DNA methylation levels at >450,000 CpG sites in peripheral blood mononuclear cells (PBMC) of young (20-35) and older (36-56) adults in two separate groups of participants. Each age group for each data set consisted of 12 HIV-1-infected and 12 age-matched HIV-1-uninfected samples for a total of 96 samples. The effects of age and HIV-1 infection on methylation at each CpG revealed a strong correlation of 0.49, p<1 x 10(-200) and 0.47, p<1 x 10(-200). Weighted gene correlation network analysis (WGCNA) identified 17 co-methylation modules; module 3 (ME3) was significantly correlated with age (cor=0.70) and HIV-1 status (cor=0.31). Older HIV-1+ individuals had a greater number of hypermethylated CpGs across ME3 (p=0.015). In a multivariate model, ME3 was significantly associated with age and HIV status (Data set 1: βage=0.007088, p=2.08 x 10(-9); βHIV=0.099574, p=0.0011; Data set 2: βage=0.008762, p=1.27 x 10(-5); βHIV=0.128649, p=0.0001). Using this model, we estimate that HIV-1 infection accelerates age-related methylation by approximately 13.7 years in data set 1 and 14.7 years in data set 2. The genes related to CpGs in ME3 are enriched for polycomb group target genes known to be involved in cell renewal and aging. The overlap between ME3 and an aging methylation module found in solid tissues is also highly significant (Fisher-exact p=5.6 x 10(-6), odds ratio=1.91). These data demonstrate that HIV-1 infection is associated with methylation patterns that are similar to age-associated patterns and suggest that general aging and HIV-1 related aging work through some common cellular and molecular mechanisms. These results are an important first step for finding potential therapeutic targets and novel clinical approaches to mitigate the detrimental effects of both HIV-1-infection and aging.

Ageing-associated changes in the human DNA methylome: genomic locations and effects on gene expression

Background

Changes in DNA methylation are among the mechanisms contributing to the ageing process. We sought to identify ageing-associated DNA methylation changes at single-CpG-site resolution in blood leukocytes and to ensure that the observed changes were not due to differences in the proportions of leukocytes. The association between DNA methylation changes and gene expression levels was also investigated in the same individuals.

Results

We identified 8540 high-confidence ageing-associated CpG sites, 46% of which were hypermethylated in nonagenarians. The hypermethylation-associated genes belonged to a common category: they were predicted to be regulated by a common group of transcription factors and were enriched in a related set of GO terms and canonical pathways. Conversely, for the hypomethylation-associated genes only a limited set of GO terms and canonical pathways were identified. Among the 8540 CpG sites associated with ageing, methylation level of 377 sites was also associated with gene expression levels. These genes were enriched in GO terms and canonical pathways associated with immune system functions, particularly phagocytosis.

Conclusions

We find that certain ageing-associated immune-system impairments may be mediated via changes in DNA methylation. The results also imply that ageing-associated hypo- and hypermethylation are distinct processes: hypermethylation could be caused by programmed changes, whereas hypomethylation could be the result of environmental and stochastic processes.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1381-z) contains supplementary material, which is available to authorized users.

Between-array normalization for 450K data

The Illumina Infinium HumanMethylation450 BeadChip is frequently used in epigenetic research. Besides quantile normalization there is currently no standard method to normalize the data between arrays. We describe some properties of the data generated by this platform and present a normalization method based on local regression. We compare the performance of this method with other commonly used approaches in three benchmarks (correlation between 21 pairs of technical replicates, detection of differential methylation and correlation of methylation levels for smoking-associated CpG sites with smoking behavior of 655 participants of an epidemiological study). Results indicate that the proposed method improves reproducibility, whereas some commonly used methods can have adverse effects.

Genome-wide DNA methylation profiles indicate CD8+ T cell hypermethylation in multiple sclerosis

OBJECTIVE

Determine whether MS-specific DNA methylation profiles can be identified in whole blood or purified immune cells from untreated MS patients.

METHODS

Whole blood, CD4+ and CD8+ T cell DNA from 16 female, treatment naïve MS patients and 14 matched controls was profiled using the HumanMethylation450K BeadChip. Genotype data were used to assess genetic homogeneity of our sample and to exclude potential SNP-induced DNA methylation measurement errors.

RESULTS

As expected, significant differences between CD4+ T cells, CD8+ T cells and whole blood DNA methylation profiles were observed, regardless of disease status. Strong evidence for hypermethylation of CD8+ T cell, but not CD4+ T cell or whole blood DNA in MS patients compared to controls was observed. Genome-wide significant individual CpG-site DNA methylation differences were not identified. Furthermore, significant differences in gene DNA methylation of 148 established MS-associated risk genes were not observed.

CONCLUSION

While genome-wide significant DNA methylation differences were not detected for individual CpG-sites, strong evidence for DNA hypermethylation of CD8+ T cells for MS patients was observed, indicating a role for DNA methylation in MS. Further, our results suggest that large DNA methylation differences for CpG-sites tested here do not contribute to MS susceptibility. In particular, large DNA methylation differences for CpG-sites within 148 established MS candidate genes tested in our study cannot explain missing heritability. Larger studies of homogenous MS patients and matched controls are warranted to further elucidate the impact of CD8+ T cell and more subtle DNA methylation changes in MS development and pathogenesis.

ZNF695 methylation predicts a response of esophageal squamous cell carcinoma to definitive chemoradiotherapy

PURPOSE

Definitive chemoradiotherapy (dCRT) is one of the standard treatments for esophageal squamous cell carcinoma. Patients with a response to dCRT have a better prognosis than those resistant to dCRT while survival benefits for patients with residual tumors are limited. Nevertheless, few molecular markers to predict the response to dCRT are currently available. Here, we aimed to establish a DNA methylation marker to predict the response to dCRT.

METHODS

A total of 104 patients were divided into screening (n = 43) and validation (n = 61) sets. A genome-wide DNA methylation analysis was performed using an Infinium HumanMethylation450 BeadChip array. Methylation levels were measured by quantitative methylation-specific PCR and normalized by the fraction of cancer cells in a sample.

RESULTS

The genome-wide methylation analysis of seven responders and eight non-responders identified 18 genomic regions specifically (un)methylated in the responders. Among these, methylation of the promoter CpG island of ZNF695 was significantly associated with the response to dCRT in the screening set (P = 0.004), and a cutoff value was determined. In the validation set, the association was successfully validated (P = 0.021), and a high specificity (90 %) for the prediction of responders was obtained using the prefixed cutoff value. In addition, a multivariate analysis showed that ZNF695 methylation was an independent predictive factor for the response to dCRT (OR 7.55, 95 % CI 2.12-26.9, P = 0.002).

CONCLUSION

ZNF695 methylation was significantly associated with the response to dCRT and is a promising predictive marker for the response to dCRT.

Aberrant DNA methylation of imprinted loci in hepatocellular carcinoma and after in vitro exposure to common risk factors

BACKGROUND

Hepatocellular carcinoma (HCC) is among the most frequent human malignancies and a major cause of cancer-related death worldwide. It is characterized by late detection and fast progression, and it is believed that epigenetic disruption may be one of the molecular mechanisms leading to hepatocarcinogenesis. Previous studies from our group revealed that HCC tumors exhibit specific DNA methylation signatures associated with major risk factors and tumor progression. Imprinted genes are mono-allelically expressed in a parent-of-origin-dependent manner and have been suggested to be more susceptible to deregulation in cancer. To test this notion, we performed a targeted analysis of DNA methylation in known imprinted genes, using HCC samples and in vitro models of carcinogenic exposure.

RESULTS

Analysis of HCC DNA methylation in two independent datasets showed that differentially methylated loci are significantly enriched in imprinted genes. Most of the promoters of imprinted genes were found hypomethylated in HCC tumors compared to surrounding tissues, contrasting with the frequent promoter hypermethylation observed in tumors. We next investigated the status of methylation of the imprinting control region (ICR) of different imprinted clusters and found that the 15q11-13 ICR was significantly hypomethylated in tumors relative to their surrounding tissues. In addition, expression of imprinted genes within this cluster was frequently deregulated in a gene-specific manner, suggesting distinct mechanisms of regulation in this region. Finally, primary human hepatocytes and hepatocyte-like HepaRG cells displayed higher methylation variability in certain imprinted loci after natural hepatitis B virus (HBV) infection and after lipid accumulation, respectively.

CONCLUSION

The methylation status of a large panel of imprinted genes was found deregulated in HCC, suggesting a major role of this mechanism during hepatocarcinogenesis. In vitro models support the hypothesis of imprinted gene methylation as a potential marker of environmental exposures.

Long-range epigenetic regulation is conferred by genetic variation located at thousands of independent loci

The interplay between genetic and epigenetic variation is only partially understood. One form of epigenetic variation is methylation at CpG sites, which can be measured as methylation quantitative trait loci (meQTL). Here we report that in a panel of lymphocytes from 1,748 individuals, methylation levels at 1,919 CpG sites are correlated with at least one distal (trans) single-nucleotide polymorphism (SNP) (P<3.2 × 10(-13); FDR<5%). These trans-meQTLs include 1,657 SNP-CpG pairs from different chromosomes and 262 pairs from the same chromosome that are >1 Mb apart. Over 90% of these pairs are replicated (FDR<5%) in at least one of two independent data sets. Genomic loci harbouring trans-meQTLs are significantly enriched (P<0.001) for long non-coding transcripts (2.2-fold), known epigenetic regulators (2.3-fold), piwi-interacting RNA clusters (3.6-fold) and curated transcription factors (4.1-fold), including zinc-finger proteins (8.75-fold). Long-range epigenetic networks uncovered by this approach may be relevant to normal and disease states.

An integrative multi-scale analysis of the dynamic DNA methylation landscape in aging

Recent studies have demonstrated that the DNA methylome changes with age. This epigenetic drift may have deep implications for cellular differentiation and disease development. However, it remains unclear how much of this drift is functional or caused by underlying changes in cell subtype composition. Moreover, no study has yet comprehensively explored epigenetic drift at different genomic length scales and in relation to regulatory elements.

Here we conduct an in-depth analysis of epigenetic drift in blood tissue. We demonstrate that most of the age-associated drift is independent of the increase in the granulocyte to lymphocyte ratio that accompanies aging and that enrichment of age-hypermethylated CpG islands increases upon adjustment for cellular composition. We further find that drift has only a minimal impact on in-cis gene expression, acting primarily to stabilize pre-existing baseline expression levels. By studying epigenetic drift at different genomic length scales, we demonstrate the existence of mega-base scale age-associated hypomethylated blocks, covering approximately 14% of the human genome, and which exhibit preferential hypomethylation in age-matched cancer tissue. Importantly, we demonstrate the feasibility of integrating Illumina 450k DNA methylation with ENCODE data to identify transcription factors with key roles in cellular development and aging. Specifically, we identify REST and regulatory factors of the histone methyltransferase MLL complex, whose function may be disrupted in aging.

In summary, most of the epigenetic drift seen in blood is independent of changes in blood cell type composition, and exhibits patterns at different genomic length scales reminiscent of those seen in cancer. Integration of Illumina 450k with appropriate ENCODE data may represent a fruitful approach to identify transcription factors with key roles in aging and disease.

Two well-known features of aging are the gradual decline of the body’s ability to regenerate tissues, as well as an increased incidence of diseases like cancer and Alzheimers. One of the most recent exciting findings which may underlie the aging process is a gradual modification of DNA, called epigenetic drift, which is effected by the covalent addition and removal of methyl groups, which in turn can deregulate the activity of nearby genes. However, this study presents the most convincing evidence to date that epigenetic drift acts to stabilize the activity levels of nearby genes. This study shows that instead, epigenetic drift may act primarly to disrupt DNA binding patterns of proteins which regulate the activity of many genes, and moreover identifies specific regulatory proteins with key roles in cancer and Alzheimers. The study also performs the most comprehensive analysis of epigenetic drift at different spatial scales, demonstrating that epigenetic drift on the largest length scales is highly reminiscent of those seen in cancer. In summary, this work substantially supports the view that epigenetic drift may contribute to the age-associated increased risk of diseases like cancer and Alzheimers, by disrupting master regulators of genomewide gene activity.

A coherent approach for analysis of the Illumina HumanMethylation450 BeadChip improves data quality and performance in epigenome-wide association studies

DNA methylation plays a fundamental role in the regulation of the genome, but the optimal strategy for analysis of genome-wide DNA methylation data remains to be determined. We developed a comprehensive analysis pipeline for epigenome-wide association studies (EWAS) using the Illumina Infinium HumanMethylation450 BeadChip, based on 2,687 individuals, with 36 samples measured in duplicate. We propose new approaches to quality control, data normalisation and batch correction through control-probe adjustment and establish a null hypothesis for EWAS using permutation testing. Our analysis pipeline outperforms existing approaches, enabling accurate identification of methylation quantitative trait loci for hypothesis driven follow-up experiments.

Methylation of bone SOST, its mRNA, and serum sclerostin levels correlate strongly with fracture risk in postmenopausal women

Inhibition of sclerostin, a glycoprotein secreted by osteocytes, offers a new therapeutic paradigm for treatment of osteoporosis (OP) through its critical role as Wnt/catenin signaling regulator. This study describes the epigenetic regulation of SOST expression in bone biopsies of postmenopausal women. We correlated serum sclerostin to bone mineral density (BMD), fractures, and bone remodeling parameters, and related these findings to epigenetic and genetic disease mechanisms. Serum sclerostin and bone remodeling biomarkers were measured in two postmenopausal groups: healthy (BMD T-score > -1) and established OP (BMD T-score < -2.5, with at least one low-energy fracture). Bone specimens were used to analyze SOST mRNAs, single nucleotide polymorphisms (SNPs), and DNA methylation changes. The SOST gene promoter region showed increased CpG methylation in OP patients (n = 4) compared to age and body mass index (BMI) balanced controls (n = 4) (80.5% versus 63.2%, p = 0.0001) with replication in independent cohorts (n = 27 and n = 36, respectively). Serum sclerostin and bone SOST mRNA expression correlated positively with age-adjusted and BMI-adjusted total hip BMD (r = 0.47 and r = 0.43, respectively; both p < 0.0005), and inversely to serum bone turnover markers. Five SNPs, one of which replicates in an independent population-based genomewide association study (GWAS), showed association with serum sclerostin or SOST mRNA levels under an additive model (p = 0.0016 to 0.0079). Genetic and epigenetic changes in SOST influence its bone mRNA expression and serum sclerostin levels in postmenopausal women. The observations suggest that increased SOST promoter methylation seen in OP is a compensatory counteracting mechanism, which lowers serum sclerostin concentrations and reduces inhibition of Wnt signaling in an attempt to promote bone formation.

Quality control and statistical modeling for environmental epigenetics: a study on in utero lead exposure and DNA methylation at birth

DNA methylation data assayed using pyrosequencing techniques are increasingly being used in human cohort studies to investigate associations between epigenetic modifications at candidate genes and exposures to environmental toxicants and to examine environmentally-induced epigenetic alterations as a mechanism underlying observed toxicant-health outcome associations. For instance, in utero lead (Pb) exposure is a neurodevelopmental toxicant of global concern that has also been linked to altered growth in human epidemiological cohorts; a potential mechanism of this association is through alteration of DNA methylation (e.g., at growth-related genes). However, because the associations between toxicants and DNA methylation might be weak, using appropriate quality control and statistical methods is important to increase reliability and power of such studies. Using a simulation study, we compared potential approaches to estimate toxicant-DNA methylation associations that varied by how methylation data were analyzed (repeated measures vs. averaging all CpG sites) and by method to adjust for batch effects (batch controls vs. random effects). We demonstrate that correcting for batch effects using plate controls yields unbiased associations, and that explicitly modeling the CpG site-specific variances and correlations among CpG sites increases statistical power. Using the recommended approaches, we examined the association between DNA methylation (in LINE-1 and growth related genes IGF2, H19 and HSD11B2) and 3 biomarkers of Pb exposure (Pb concentrations in umbilical cord blood, maternal tibia, and maternal patella), among mother-infant pairs of the Early Life Exposures in Mexico to Environmental Toxicants (ELEMENT) cohort (n = 247). Those with 10 μg/g higher patella Pb had, on average, 0.61% higher IGF2 methylation (P = 0.05). Sex-specific trends between Pb and DNA methylation (P < 0.1) were observed among girls including a 0.23% increase in HSD11B2 methylation with 10 μg/g higher patella Pb.

Association of DNA methylation with age, gender, and smoking in an Arab population

BACKGROUND

Modification of DNA by methylation of cytosines at CpG dinucleotides is a widespread phenomenon that leads to changes in gene expression, thereby influencing and regulating many biological processes. Recent technical advances in the genome-wide determination of single-base DNA-methylation enabled epigenome-wide association studies (EWASs). Early EWASs established robust associations between age and gender with the degree of CpG methylation at specific sites. Other studies uncovered associations with cigarette smoking. However, so far these studies were mainly conducted in Caucasians, raising the question of whether these findings can also be extrapolated to other populations.

RESULTS

Here, we present an EWAS with age, gender, and smoking status in a family study of 123 individuals of Arab descent. We determined DNA methylation at over 450,000 CpG sites using the Illumina Infinium HumanMethylation450 BeadChip, applied state-of-the-art data processing protocols, including correction for blood cell type heterogeneity and hidden confounders, and eliminated probes containing SNPs at the targeted CpG site using 40× whole-genome sequencing data. Using this approach, we could replicate the leading published EWAS associations with age, gender and smoking, and recovered hallmarks of gender-specific epigenetic changes. Interestingly, we could even replicate the recently reported precise prediction of chronological age based on the methylation of only a few selected CpG sites.

CONCLUSION

Our study supports the view that when applied with state-of-the art protocols to account for all potential confounders, DNA methylation arrays represent powerful tools for EWAS with more complex phenotypes that can also be successfully applied to non-Caucasian populations.

Analysis pipelines and packages for Infinium HumanMethylation450 BeadChip (450k) data

The Illumina HumanMethylation450 BeadChip has become a popular platform for interrogating DNA methylation in epigenome-wide association studies (EWAS) and related projects as well as resource efforts such as the International Cancer Genome Consortium (ICGC) and the International Human Epigenome Consortium (IHEC). This has resulted in an exponential increase of 450k data in recent years and triggered the development of numerous integrated analysis pipelines and stand-alone packages. This review will introduce and discuss the currently most popular pipelines and packages and is particularly aimed at new 450k users.

Relationship between expression and methylation of obesity-related genes in children

Epigenetic control of gene expression in children remains poorly understood, but new technologies can help elucidate the relationship between expression and DNA methylation. Here, we utilized the nCounter Analysis System to characterise the expression of 60 genes in 69 9-year-old children from a cohort with a high prevalence of obesity. nCounter expression levels ranged broadly (from 3 to over 10000 messenger RNA counts) and were divided into four categories: high (>2000 counts), moderate (200-1000 counts), low (100-200 counts) and marginal (<100 counts). For a subset of five genes (ADIPOR1, PPARG1, GSTM1, PON1 and ACACA) from different expression level categories, we validated nCounter data using reverse transcription-polymerase chain reaction (RT-PCR), and expanded RT-PCR analysis of ADIPOR1 to include 180 children. Expression data from the two methodologies were correlated for all five genes included in the validation experiment, with estimates ranging from r s = 0.26 (P = 0.02) to r s = 0.88 (P < 5×10(-6)). ADIPOR1 and PPARG1 nCounter expression levels were negatively correlated (r = -0.60, P < 5×10(-5)), and this relationship was stronger in overweight children (r = -0.73, P < 5×10(-5)) than in normal weight children (r = -0.42, P = 0.016). Using methylation data from the Infinium HumanMethylation450 BeadChip (n = 180), we found eight CpG sites in ADIPOR1 and PPARG where methylation level was associated with expression by RT-PCR (P < 0.05). Hypomethylation of PPARG gene body site cg10499651 was associated with increased expression as measured by both RT-PCR and nCounter (P < 0.05). We found no statistically significant relationships between either expression or methylation of ADIPOR1 and PPARG and body mass index or waist circumference. In addition to demonstrating the validity of expression data derived from nCounter, our results illustrate the use of new technologies in assessing epigenetic effects on expression in children.

DNA methylation of lipid-related genes affects blood lipid levels

BACKGROUND

Epigenetic mechanisms might be involved in the regulation of interindividual lipid level variability and thus may contribute to the cardiovascular risk profile. The aim of this study was to investigate the association between genome-wide DNA methylation and blood lipid levels high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, triglycerides, and total cholesterol. Observed DNA methylation changes were also further analyzed to examine their relationship with previous hospitalized myocardial infarction.

METHODS AND RESULTS

Genome-wide DNA methylation patterns were determined in whole blood samples of 1776 subjects of the Cooperative Health Research in the Region of Augsburg F4 cohort using the Infinium HumanMethylation450 BeadChip (Illumina). Ten novel lipid-related CpG sites annotated to various genes including ABCG1, MIR33B/SREBF1, and TNIP1 were identified. CpG cg06500161, located in ABCG1, was associated in opposite directions with both high-density lipoprotein cholesterol (β coefficient=-0.049; P=8.26E-17) and triglyceride levels (β=0.070; P=1.21E-27). Eight associations were confirmed by replication in the Cooperative Health Research in the Region of Augsburg F3 study (n=499) and in the Invecchiare in Chianti, Aging in the Chianti Area study (n=472). Associations between triglyceride levels and SREBF1 and ABCG1 were also found in adipose tissue of the Multiple Tissue Human Expression Resource cohort (n=634). Expression analysis revealed an association between ABCG1 methylation and lipid levels that might be partly mediated by ABCG1 expression. DNA methylation of ABCG1 might also play a role in previous hospitalized myocardial infarction (odds ratio, 1.15; 95% confidence interval=1.06-1.25).

CONCLUSIONS

Epigenetic modifications of the newly identified loci might regulate disturbed blood lipid levels and thus contribute to the development of complex lipid-related diseases.

Genome-wide methylation analysis in Silver-Russell syndrome patients

Silver-Russell syndrome (SRS) is a clinically heterogeneous disorder characterised by severe in utero growth restriction and poor postnatal growth, body asymmetry, irregular craniofacial features and several additional minor malformations. The aetiology of SRS is complex and current evidence strongly implicates imprinted genes. Approximately, half of all patients exhibit DNA hypomethylation at the H19/IGF2 imprinted domain, and around 10% have maternal uniparental disomy of chromosome 7. We measured DNA methylation in 18 SRS patients at >485,000 CpG sites using DNA methylation microarrays. Using a novel bioinformatics methodology specifically designed to identify subsets of patients with a shared epimutation, we analysed methylation changes genome-wide as well as at known imprinted regions to identify SRS-associated epimutations. Our analysis identifies epimutations at the previously characterised domains of H19/IGF2 and at imprinted regions on chromosome 7, providing proof of principle that our methodology can detect DNA methylation changes at imprinted loci. In addition, we discovered two novel epimutations associated with SRS and located at imprinted loci previously linked to relevant mouse and human phenotypes. We identify RB1 as an additional imprinted locus associated with SRS, with a region near the RB1 differentially methylated region hypermethylated in 13/18 (~70%) patients. We also report 6/18 (~33%) patients were hypermethylated at a CpG island near the ANKRD11 gene. We do not observe consistent co-occurrence of epimutations at multiple imprinted loci in single SRS individuals. SRS is clinically heterogeneous and the absence of multiple imprinted loci epimutations reflects the heterogeneity at the molecular level. Further stratification of SRS patients by molecular phenotypes might aid the identification of disease causes.

CpG island hypermethylation as a biomarker for the early detection of lung cancer

Lung cancer is the most frequent cause of cancer-related deaths and causes over one million deaths worldwide each year. Despite significant strides in the diagnosis and treatment of lung cancer, the prognosis is extremely poor, with the overall 5-year survival rates still remaining around 15 %. This is largely due to occult metastatic dissemination, which appears in approximately two-thirds of patients at the time of detection. Thus, the development of efficient diagnostic methods to enable the early detection of cancer for these patients is clearly imperative.One promising approach is the identification of lung cancer-specific biomarkers at an early stage. The de novo methylation of CpG islands within the promoters of tumor suppressor genes is one of the most frequently acquired epigenetic changes during the pathogenesis of lung cancer and usually associated with transcriptional downregulation of a gene. The analysis of DNA methylation patterns in sputum, bronchial fluid, plasma, or serum could become a powerful tool for the accurate and early diagnosis of lung cancer with unparalleled specificity and sensitivity.

Prenatal arsenic exposure and the epigenome: identifying sites of 5-methylcytosine alterations that predict functional changes in gene expression in newborn cord blood and subsequent birth outcomes

Prenatal exposure to inorganic arsenic (iAs) is detrimental to the health of newborns and increases the risk of disease development later in life. Here we examined a subset of newborn cord blood leukocyte samples collected from subjects enrolled in the Biomarkers of Exposure to ARsenic (BEAR) pregnancy cohort in Gómez Palacio, Mexico, who were exposed to a range of drinking water arsenic concentrations (0.456-236 µg/l). Changes in iAs-associated DNA 5-methylcytosine methylation were assessed across 424,935 CpG sites representing 18,761 genes and compared with corresponding mRNA expression levels and birth outcomes. In the context of arsenic exposure, a total of 2919 genes were identified with iAs-associated differences in DNA methylation. Site-specific analyses identified DNA methylation changes that were most predictive of gene expression levels where CpG methylation within CpG islands positioned within the first exon, the 5' untranslated region and 200 bp upstream of the transcription start site yielded the most significant association with gene expression levels. A set of 16 genes was identified with correlated iAs-associated changes in DNA methylation and mRNA expression and all were highly enriched for binding sites of the early growth response (EGR) and CCCTC-binding factor (CTCF) transcription factors. Furthermore, DNA methylation levels of 7 of these genes were associated with differences in birth outcomes including gestational age and head circumference.These data highlight the complex interplay between DNA methylation, functional changes in gene expression and health outcomes and underscore the need for functional analyses coupled to epigenetic assessments.

DNA extracted from saliva for methylation studies of psychiatric traits: evidence tissue specificity and relatedness to brain

DNA methylation has become increasingly recognized in the etiology of psychiatric disorders. Because brain tissue is not accessible in living humans, epigenetic studies are most often conducted in blood. Saliva is often collected for genotyping studies but is rarely used to examine DNA methylation because the proportion of epithelial cells and leukocytes varies extensively between individuals. The goal of this study was to evaluate whether saliva DNA is informative for studies of psychiatric disorders. DNA methylation (HumanMethylation450 BeadChip) was assessed in saliva and blood samples from 64 adult African Americans. Analyses were conducted using linear regression adjusted for appropriate covariates, including estimated cellular proportions. DNA methylation from brain tissues (cerebellum, frontal cortex, entorhinal cortex, and superior temporal gyrus) was obtained from a publically available dataset. Saliva and blood methylation was clearly distinguishable though there was positive correlation overall. There was little correlation in CpG sites within relevant candidate genes. Correlated CpG sites were more likely to occur in areas of low CpG density (i.e., CpG shores and open seas). There was more variability in CpG sites from saliva than blood, which may reflect its heterogeneity. Finally, DNA methylation in saliva appeared more similar to patterns from each of the brain regions examined overall than methylation in blood. Thus, this study provides a framework for using DNA methylation from saliva and suggests that DNA methylation of saliva may offer distinct opportunities for epidemiological and longitudinal studies of psychiatric traits.

PON1 as a model for integration of genetic, epigenetic, and expression data on candidate susceptibility genes

Recent genome- and epigenome-wide studies demonstrate that the DNA methylation is controlled in part by genetics, highlighting the importance of integrating genetic and epigenetic data. To better understand molecular mechanisms affecting gene expression, we used the candidate susceptibility gene paraoxonase 1 (PON1) as a model to assess associations of PON1 genetic polymorphisms with DNA methylation and arylesterase activity, a marker of PON1 expression. PON1 has been associated with susceptibility to obesity, cardiovascular disease, and pesticide exposure. In this study, we assessed DNA methylation in 18 CpG sites located along PON1 shores, shelves, and its CpG island in blood specimens collected from newborns and 9-year-old children participating (n = 449) in the CHAMACOS birth cohort study. The promoter polymorphism, PON1_-108 , was strongly associated with methylation, particularly for CpG sites located near the CpG island (P << 0.0005). Among newborns, these relationships were even more pronounced after adjusting for blood cell composition. We also observed significant decreases in arylesterase activity with increased methylation at the same nine CpG sites at both ages. Using causal mediation analysis, we found statistically significant indirect effects of methylation (β(95% confidence interval): 6.9(1.5, 12.4)) providing evidence that DNA methylation mediates the relationship between PON1_-108 genotype and PON1 expression. Our findings show that integration of genetic, epigenetic, and expression data can shed light on the functional mechanisms involving genetic and epigenetic regulation of candidate susceptibility genes like PON1.

Determination of DNA methylation levels using Illumina HumanMethylation450 BeadChips

DNA methylation is a modifiable epigenetic phenomenon that has a strong influence over transcriptional regulation and as such has been consistently implicated in development and disease. Several platforms are targeted toward the identification of DNA methylation changes that might be pertinent to the disease process and include regional analysis (e.g., pyrosequencing) as well as genome-wide analysis (e.g., next-generation sequencing and microarray). The Illumina HumanMethylation450 BeadChip is one of the most comprehensive microarray platforms available, and due to the high costs associated with next-generation sequencing, it is becoming a widely used tool for the analysis of genome-wide DNA methylation levels. Providing quantitative DNA methylation levels at 482,421 CpG sites within CpG islands, shores, and shelves, as well as intergenic regions, the HumanMethylation450 BeadChip can allow accurate assessment of differential methylation across large studies. This chapter outlines the laboratory methodologies associated with performing the Illumina Infinium Methylation Assay, including bisulfite conversion, whole-genome amplification, BeadChip hybridization, XStain procedures, and imaging systems. Furthermore, this chapter provides an outline of data analysis tools, including the GenomeStudio pipeline, quality control measures, and additional statistical considerations. This comprehensive overview can aid not only in performing the Illumina Infinium Methylation Assay but also in the interpretation of data derived from this platform.

Integrated analysis of cancer-related pathways affected by genetic and epigenetic alterations in gastric cancer

BACKGROUND

The profiles of genetic and epigenetic alterations in cancer-related pathways are considered to be useful for selection of patients likely to respond to specific drugs, including molecular-targeted and epigenetic drugs. In this study, we aimed to characterize such profiles in gastric cancers (GCs).

METHODS

Genetic alterations of 55 cancer-related genes were analyzed by a benchtop next-generation sequencer. DNA methylation statuses were analyzed by a bead array with 485,512 probes.

RESULTS

The WNT pathway was activated by mutations of CTNNB1 in 2 GCs and potentially by aberrant methylation of its negative regulators, such as DKK3, NKD1, and SFRP1, in 49 GCs. The AKT/mTOR pathway was activated by mutations of PIK3CA and PTPN11 in 4 GCs. The MAPK pathway was activated by mutations and gene amplifications of ERBB2, FLT3, and KRAS in 11 GCs. Cell-cycle regulation was affected by aberrant methylation of CDKN2A and CHFR in 13 GCs. Mismatch repair was affected by a mutation of MLH1 in 1 GC and by aberrant methylation of MLH1 in 2 GCs. The p53 pathway was inactivated by mutations of TP53 in 19 GCs and potentially by aberrant methylation of its downstream genes in 38 GCs. Cell adhesion was affected by mutations of CDH1 in 2 GCs.

CONCLUSIONS

Genes involved in cancer-related pathways were more frequently affected by epigenetic alterations than by genetic alterations. The profiles of genetic and epigenetic alterations are expected to be useful for selection of the patients who are likely to benefit from specific drugs.

Longitudinal changes of telomere length and epigenetic age related to traumatic stress and post-traumatic stress disorder

Several studies have reported an association between traumatic stress and telomere length suggesting that traumatic stress has an impact on ageing at the cellular level. A newly derived tool provides an additional means to investigate cellular ageing by estimating epigenetic age based on DNA methylation profiles. We therefore hypothesise that in a longitudinal study of traumatic stress both indicators of cellular ageing will show increased ageing. We expect that particularly in individuals that developed symptoms of post-traumatic stress disorder (PTSD) increases in these ageing parameters would stand out. From an existing longitudinal cohort study, ninety-six male soldiers were selected based on trauma exposure and the presence of symptoms of PTSD. All military personnel were deployed in a combat zone in Afghanistan and assessed before and 6 months after deployment. The Self-Rating Inventory for PTSD was used to measure the presence of PTSD symptoms, while exposure to combat trauma during deployment was measured with a 19-item deployment experiences checklist. These groups did not differ for age, gender, alcohol consumption, cigarette smoking, military rank, length, weight, or medication use. In DNA from whole blood telomere length was measured and DNA methylation levels were assessed using the Illumina 450K DNA methylation arrays. Epigenetic ageing was estimated using the DNAm age estimator procedure. The association of trauma with telomere length was in the expected direction but not significant (B=-10.2, p=0.52). However, contrary to our expectations, development of PTSD symptoms was associated with the reverse process, telomere lengthening (B=1.91, p=0.018). In concordance, trauma significantly accelerated epigenetic ageing (B=1.97, p=0.032) and similar to the findings in telomeres, development of PTSD symptoms was inversely associated with epigenetic ageing (B=-0.10, p=0.044). Blood cell count, medication and premorbid early life trauma exposure did not confound the results. Overall, in this longitudinal study of military personnel deployed to Afghanistan we show an acceleration of ageing by trauma. However, development of PTSD symptoms was associated with telomere lengthening and reversed epigenetic ageing. These findings warrant further study of a perhaps dysfunctional compensatory cellular ageing reversal in PTSD.

Identification of functionally methylated regions based on discriminant analysis through integrating methylation and gene expression data

DNA methylation is essential not only in cellular differentiation but also in diseases.

Epigenome-wide association studies (EWAS): past, present, and future

Just as genome-wide association studies (GWAS) grew from the field of genetic epidemiology, so too do epigenome-wide association studies (EWAS) derive from the burgeoning field of epigenetic epidemiology, with both aiming to understand the molecular basis for disease risk. While genetic risk of disease is currently unmodifiable, there is hope that epigenetic risk may be reversible and or modifiable. This review will take a look back at the origins of this field and revisit the past early efforts to conduct EWAS using the 27k Illumina methylation beadarrays, to the present where most investigators are using the 450k Illumina beadarrays and finally to the future where next generation sequencing based methods beckon. There have been numerous diseases, exposures and lifestyle factors investigated with EWAS, with several significant associations now identified. However, much like the GWAS studies, EWAS are likely to require large international consortium-based approaches to reach the numbers of subjects, and statistical and scientific rigor, required for robust findings.

Adiposity is associated with DNA methylation profile in adipose tissue

BACKGROUND

Adiposity is a risk factor for type 2 diabetes and cardiovascular disease, suggesting an important role for adipose tissue in the development of these conditions. The epigenetic underpinnings of adiposity are not well understood, and studies of DNA methylation in relation to adiposity have rarely focused on target adipose tissue. Objectives were to evaluate whether genome-wide DNA methylation profiles in subcutaneous adipose tissue and peripheral blood leukocytes are associated with measures of adiposity, including central fat mass, body fat distribution and body mass index.

METHODS

Participants were 106 men and women (mean age 47 years) from the New England Family Study. DNA methylation was evaluated using the Infinium HumanMethylation450K BeadChip. Adiposity phenotypes included dual-energy X-ray absorptiometry-assessed android fat mass, android:gynoid fat ratio and trunk:limb fat ratio, as well as body mass index.

RESULTS

Adipose tissue genome-wide DNA methylation profiles were associated with all four adiposity phenotypes, after adjusting for race, sex and current smoking (omnibus p-values <0.001). After further adjustment for adipose cell-mixture effects, associations with android fat mass, android:gynoid fat ratio, and trunk:limb fat ratio remained. In gene-specific analyses, adiposity phenotypes were associated with adipose tissue DNA methylation in several genes that are biologically relevant to the development of adiposity, such as AOC3, LIPE, SOD3, AQP7 and CETP. Blood DNA methylation profiles were not associated with adiposity, before or after adjustment for blood leukocyte cell mixture effects.

CONCLUSION

Findings show that DNA methylation patterns in adipose tissue are associated with adiposity.

Global analysis of methylation profiles from high resolution CpG data

New high throughput technologies are now enabling simultaneous epigenetic profiling of DNA methylation at hundreds of thousands of CpGs across the genome. A problem of considerable practical interest is identification of large scale, global changes in methylation that are associated with environmental variables, clinical outcomes, or other experimental conditions. However, there has been little statistical research on methods for global methylation analysis using technologies with individual CpG resolution. To address this critical gap in the literature, we develop a new strategy for global analysis of methylation profiles using a functional regression approach wherein we approximate either the density or the cumulative distribution function (CDF) of the methylation values for each individual using B-spline basis functions. The spline coefficients for each individual are allowed to summarize the individual's overall methylation profile. We then test for association between the overall distribution and a continuous or dichotomous outcome variable using a variance component score test that naturally accommodates the correlation between spline coefficients. Simulations indicate that our proposed approach has desirable power while protecting type I error. The method was applied to detect methylation differences, both genome wide and at LINE1 elements, between the blood samples from rheumatoid arthritis patients and healthy controls and to detect the epigenetic changes of human hepatocarcinogenesis in the context of alcohol abuse and hepatitis C virus infection. A free implementation of our methods in the R language is available in the Global Analysis of Methylation Profiles (GAMP) package at http://research.fhcrc.org/wu/en.html.

Assessment of patient-derived tumour xenografts (PDXs) as a discovery tool for cancer epigenomics

BACKGROUND

The use of tumour xenografts is a well-established research tool in cancer genomics but has not yet been comprehensively evaluated for cancer epigenomics.

METHODS

In this study, we assessed the suitability of patient-derived tumour xenografts (PDXs) for methylome analysis using Infinium 450 K Beadchips and MeDIP-seq.

RESULTS

Controlled for confounding host (mouse) sequences, comparison of primary PDXs and matching patient tumours in a rare (osteosarcoma) and common (colon) cancer revealed that an average 2.7% of the assayed CpG sites undergo major (Δβ ≥ 0.51) methylation changes in a cancer-specific manner as a result of the xenografting procedure. No significant subsequent methylation changes were observed after a second round of xenografting between primary and secondary PDXs. Based on computational simulation using publically available methylation data, we additionally show that future studies comparing two groups of PDXs should use 15 or more samples in each group to minimise the impact of xenografting-associated changes in methylation on comparison results.

CONCLUSIONS

Our results from rare and common cancers indicate that PDXs are a suitable discovery tool for cancer epigenomics and we provide guidance on how to overcome the observed limitations.

Quantitative methodology is critical for assessing DNA methylation and impacts on correlation with patient outcome

BACKGROUND

DNA hypermethylation is reported as a frequent event and prognostic marker in head and neck squamous cell carcinomas (HNSCC). Methylation has been commonly assessed with non-quantitative methodologies, such as methylation-specific PCR (MSP). We investigated previously reported hypermethylated genes with quantitative methodology in oral tongue squamous cell carcinomas (OTSCC).

RESULTS

The methylation status of 12 genes in 115 OTSCC samples was assessed by one or more of three quantitative analyses: methylation sensitive high resolution melting (MS-HRM), sensitive-melting analysis after real time-methylation specific PCR (SMART-MSP), and bisulfite pyrosequencing. In contrast to much of the literature, either no or infrequent locus-specific methylation was identified by MS-HRM for DAPK1, RASSF1A, MGMT, MLH1, APC, CDH1, CDH13, BRCA1, ERCC1, and ATM. The most frequently methylated loci were RUNX3 (18/108 methylated) and ABO (22/107 methylated). Interrogation of the Cancer Genome Atlas (TCGA) HNSCC cohort confirmed the frequency of significant methylation for the loci investigated. Heterogeneous methylation of RUNX3 (18/108) and ABO (22/107) detected by MS-HRM, conferred significantly worse survival (P = 0.01, and P = 0.03). However, following quantification of methylation levels using pyrosequencing, only four tumors had significant quantities (>15%) of RUNX3 methylation which correlated with a worse patient outcome (P <0.001), while the prognostic significance of ABO hypermethylation was lost. RUNX3 methylation was not prognostic for the TCGA cohort (P = 0.76).

CONCLUSIONS

We demonstrated the critical need for quantification of methylation levels and its impact on correlative analyses. In OTSCC, we found little evidence of significant or frequent hypermethylation of many loci reported to be commonly methylated. It is likely that previous reports have overestimated the frequency of significant methylation events as a consequence of the use of non-quantitative methodology.