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Aim: To assess whether DNA methylation levels account for the noninherited phenotypic variations observed among cystic fibrosis (CF) patients. Patients & methods: Using the 450 K BeadChip, we profiled DNA methylation in nasal epithelial cells collected from 32 CF patients and 16 controls. Results: We detected substantial DNA methylation differences up to 55% (median β change 0.13; IQR: 0.15–0.11) between CF patients and controls. DNA methylation levels differed between mild and severe CF patients and correlated with lung function at 50 CpG sites. Conclusion: In CF samples, dynamic changes of DNA methylation occurred in genes responsible for the integrity of the epithelium and the inflammatory and immune responses, were prominent in transcriptionally active genomic regions and were over-represented in enhancers active in lung tissues. ( Clinicaltrials.gov NCT02884622).

The quickly evolving field of genome engineering has now also embraced epigenomics and promises to revolutionize the possibilities to functionally investigate and validate the importance of epigenetic modifications at any locus in the genome. These approaches will allow for the first time to determine if epigenetic changes are causal to observed phenotypic changes and will substantially further our understanding of the multifaceted roles of epigenetic modifications and their combinations in chromatin, which is key to the answer of many biomedical questions. Epigenome editing will help identify and evaluate the role of intergenic gene regulatory elements such as enhancers in the regulation of endogenous gene expression in a cell-type-specific context through targeted alteration of the local chromatin structure. Furthermore, and perhaps most exiting, editing of the epigenome has also the potential to provide in the near future new tools to correct disease-specific epigenetic modifications in a personalized manner by re-establishing normal gene expression programs in the targeted cells. Three major technological approaches have been pursued in the past to localize effector domains of epigenetic modifiers to a specific genomic context. They all can permanently alter the epigenetic code of the target region by depositing or removing specific epigenetic marks close to their binding site and thereby provide evidence for the role of an epigenetic mark at a locus of interest. These include transcription activator-like effectors (TALEs), zinc finger-based artificial transcription factors (ATFs) and the CRISPR/Cas9 system [1–4]. They all can be combined with a large number of effector domains, catalytically active protein fragments of epigenetic enzymes such as DNA methyltransferases, TETs and histone (de)methylases, acetyltransferases and deacetylases as well as transcriptional repressors and activators that are able to recruit chromatin modifying and remodeling complexes [4]. Initial studies using epigenome engineering tools have focused on the selective modulation of DNA methylation at specific loci using rationally designed zinc finger arrays. The clinically used DNA demethylating drugs are considered relatively safe because nonmalignant cells recover their ‘normal’ DNA methylation profile relatively rapidly. Nonetheless, they demethylate the entire genome of all cells regardless of the disease status of the cell. Therefore, strategies have been developed to target, for example, DNA demethylases such as the TET enzymes to hypermethylated promoters that are solely present in cancer cells and reactivate the corresponding gene that could have tumor suppressive properties using either zinc fingers [5] or TALEs [6]. On the other hand, genes specifically overexpressed in malignant cells can – to variable degrees – be silenced by targeting zinc finger-conjugated subunits of DNA Engineering of the epigenome: synthetic biology to define functional causality and develop innovative therapies

Aim: Most studies have considered gastroenteropancreatic neuroendocrine tumors (GEP-NETs) as a homogenous group of samples or distinguish only gastrointestinal from pancreatic endocrine tumors. This article investigates if DNA methylation patterns could distinguish subtypes of GEP-NETs. Materials & methods: The DNA methylation level of 807 cancer-related genes was investigated in insulinomas, gastrinomas, non-functioning pancreatic endocrine tumors and small intestine endocrine tumors. Results: DNA methylation patterns were found to be tumor type specific for each of the pancreatic tumor subtypes and identified two distinct methylation-based groups in small intestine endocrine tumors. Differences of DNA methylation levels were validated by pyrosequencing for 20 candidate genes and correlated with differences at the transcriptional level for four candidate genes. Conclusion: The heterogeneity of DNA methylation patterns in the different subtypes of gastroenteropancreatic neuroendocrine tumors suggests different underlying pathways and, therefore, these tumors should be considered as distinct entities in molecular and clinical studies.

The detection of specific DNA methylation patterns bears great promise as biomarker for personalized management of cancer patients. Co-amplification at lower denaturation temperature-PCR (COLD-PCR) assays are sensitive methods, but have previously only been able to analyze loss of DNA methylation.Enhanced (E)-ice-COLD-PCR reactions starting from 2 ng of bisulfite-converted DNA were developed to analyze methylation patterns in two promoters with locked nucleic acid (LNA) probes blocking amplification of unmethylated CpGs. The enrichment of methylated molecules was compared to quantitative (q)PCR and quantified using serial dilutions.E-ice-COLD-PCR allowed the multiplexed enrichment and quantification of methylated DNA. Assays were validated in primary breast cancer specimens and circulating cell-free DNA from cancer patients.E-ice-COLD-PCR could prove a useful tool in the context of DNA methylation analysis for personalized medicine.

Allergic diseases are on the rise in the Western world and well-known allergy-protecting and -driving factors such as microbial and dietary exposure, pollution and smoking mediate their influence through alterations of the epigenetic landscape. Here, we review key facts on the involvement of epigenetic modifications in allergic diseases and summarize and critically evaluate the lessons learned from epigenome-wide association studies. We show the potential of epigenetic changes for various clinical applications: as diagnostic tools, to assess tolerance following immunotherapy or possibly predict the success of therapy at an early time point. Furthermore, new technological advances such as epigenome editing and DNAzymes will allow targeted alterations of the epigenome in the future and provide novel therapeutic tools.

Background: Huge progress has been made in the development of array- or sequencing-based technologies for DNA methylation analysis. The Illumina Infinium® Human Methylation 450K BeadChip (Illumina Inc., CA, USA) allows the simultaneous quantitative monitoring of more than 480,000 CpG positions, enabling large-scale epigenotyping studies. However, the assay combines two different assay chemistries, which may cause a bias in the analysis if all signals are merged as a unique source of methylation measurement. Materials & methods: We confirm in three 450K data sets that Infinium I signals are more stable and cover a wider dynamic range of methylation values than Infinium II signals. We evaluated the methylation profile of Infinium I and II probes obtained with different normalization protocols and compared these results with the methylation values of a subset of CpGs analyzed by pyrosequencing. Results: We developed a subset quantile normalization approach for the processing of 450K BeadChips. The Infinium I signals were used as ‘anchors’ to normalize Infinium II signals at the level of probe coverage categories. Our normalization approach outperformed alternative normalization or correction approaches in terms of bias correction and methylation signal estimation. We further implemented a complete preprocessing protocol that solves most of the issues currently raised by 450K array users. Conclusion: We developed a complete preprocessing pipeline for 450K BeadChip data using an original subset quantile normalization approach that performs both sample normalization and efficient Infinium I/II shift correction. The scripts, being freely available from the authors, will allow researchers to concentrate on the biological analysis of data, such as the identification of DNA methylation signatures.