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BACKGROUND: Eosinophilic esophagitis (EoE) is an emerging, chronic, rare allergic disease associated with marked eosinophil accumulation in the esophagus. Prior genome-wide association studies (GWAS) have provided strong evidence for three genome-wide susceptibility loci. OBJECTIVE: We aimed to replicate known and suggestive EoE genetic risk loci and conduct a meta-analysis of previously reported datasets. METHODS: An EoE-Custom SNP Chip (EoE-CSC) containing 956 candidate EoE risk single-nucleotide polymorphisms (SNPs) was employed to genotype 627 cases and 365 controls. Statistical power was enhanced by adding 1990 external controls and performing meta-analyses with two independent EoE GWAS. RESULTS: Meta-analysis identified replicated association and genome-wide significance at six loci: 2p23 (two independent genetic effects), 5q22, 10p14, 11q13, and 16p13. Seven additional loci were identified at suggestive significance (p < 10(−6)): 1q31, 5q23, 6q15, 6q21, 8p21, 17q12, and 22q13. From these risk loci, 13 protein-coding EoE candidate risk genes were expressed in a genotype-dependent manner. EoE risk genes were expressed in disease-relevant cell types, including esophageal epithelia, fibroblasts, and immune cells, with some expressed as a function of disease activity. The genetic risk burden of EoE-associated genetic variants was markedly larger in cases relative to controls (P

Eosinophilic esophagitis (EoE) is a chronic, food-driven allergic disease resulting in eosinophilic esophageal inflammation. We recently found that EoE susceptibility is associated with genetic variants in the promoter ofCAPN14, a gene with reported esophagus-specific expression.CAPN14is dynamically up-regulated as a function of EoE disease activity and after exposure of epithelial cells to interleukin-13 (IL-13). Herein, we aimed to explore molecular modulation ofCAPN14expression. We identified three putative binding sites for the IL-13-activated transcription factor STAT6 in the promoter and first intron ofCAPN14. Luciferase reporter assays revealed that the two most distal STAT6 elements were required for the ~10-fold increase in promoter activity subsequent to stimulation with IL-13 or IL-4, and also for the genotype-dependent reduction in IL-13-induced promoter activity. One of the STAT6 elements in the promoter was necessary for IL-13-mediated induction ofCAPN14promoter activity while the other STAT6 promoter element was necessary for full induction. Chromatin immunoprecipitation in IL-13 stimulated esophageal epithelial cells was used to further support STAT6 binding to the promoter ofCAPN14at these STAT6 binding sites. The highestCAPN14and calpain-14 expression occurred with IL-13 or IL-4 stimulation of esophageal epithelial cells under culture conditions that allow the cells to differentiate into a stratified epithelium. This work corroborates a candidate molecular mechanism for EoE disease etiology in which the risk variant at 2p23 dampens mediatedCAPN14expression in differentiated esophageal epithelial cells following IL-13/STAT6 induction ofCAPN14promoter activity.

Background DNA methylation is a stable epigenetic mark that is frequently altered in tumors. DNA methylation features are attractive biomarkers for disease states given the stability of DNA methylation in living cells and in biologic specimens typically available for analysis. Widespread accumulation of methylation in regulatory elements in some cancers (specifically the CpG island methylator phenotype, CIMP) can play an important role in tumorigenesis. High resolution assessment of CIMP for the entire genome, however, remains cost prohibitive and requires quantities of DNA not available for many tissue samples of interest. Genome-wide scans of methylation have been undertaken for large numbers of tumors, and higher resolution analyses for a limited number of cancer specimens. Methods for analyzing such large datasets and integrating findings from different studies continue to evolve. An approach for comparison of findings from a genome-wide assessment of the methylated component of tumor DNA and more widely applied methylation scans was developed. Methods Methylomes for 76 primary endometrial cancer and 12 normal endometrial samples were generated using methylated fragment capture and second generation sequencing, MethylCap-seq. Publically available Infinium HumanMethylation 450 data from The Cancer Genome Atlas (TCGA) were compared to MethylCap-seq data. Results Analysis of methylation in promoter CpG islands (CGIs) identified a subset of tumors with a methylator phenotype. We used a two-stage approach to develop a 13-region methylation signature associated with a “hypermethylator state.” High level methylation for the 13-region methylation signatures was associated with mismatch repair deficiency, high mutation rate, and low somatic copy number alteration in the TCGA test set. In addition, the signature devised showed good agreement with previously described methylation clusters devised by TCGA. Conclusion We identified a methylation signature for a “hypermethylator phenotype” in endometrial cancer and developed methods that may prove useful for identifying extreme methylation phenotypes in other cancers.

Epigenetic mechanisms, including DNA methylation, are responsible for determining and maintaining cell fate, stably differentiating the various tissues in our bodies. Increasing evidence shows that DNA methylation plays a significant role in cancer, from the silencing of tumor suppressors to the activation of oncogenes and the promotion of metastasis. Recent studies also suggest a role for DNA methylation in drug resistance. This perspective article discusses how DNA methylation may contribute to the development of acquired endocrine resistance, with a focus on breast cancer. In addition, we discuss DNA methylome profiling and how recent developments in this field are shedding new light on the role of epigenetics in endocrine resistance. Hormone ablation is the therapy of choice for hormone-sensitive breast tumors, yet as many as 40% of patients inevitably relapse, and these hormone refractory tumors often have a poor prognosis. Epigenetic studies could provide DNA methylation biomarkers to predict and diagnose acquired resistance in response to treatment. Elucidation of epigenetic mechanisms may also lead to the development of new treatments that specifically target epigenetic abnormalities or vulnerabilities in cancer cells. Expectations must be tempered by the fact that epigenetic mechanisms of endocrine resistance remain poorly understood, and further study is required to better understand how altering epigenetic pathways with therapeutics can promote or inhibit endocrine resistance in different contexts. Going forward, DNA methylome profiling will become increasingly central to epigenetic research, heralding a network-based approach to epigenetics that promises to advance our understanding of the etiology of cancer in ways not previously possible.

Autism spectrum disorders (ASDs) are a heterogeneous and common group of developmental disorders. Affected infants and children demonstrate severe and persistent impairments in expressive and receptive language and social interaction skills that are evident before age 3, as well as a variety of stereotypic and repetitive behaviors. There is overwhelming scientific evidence demonstrating high heritability (≥90%) and a strong genetic component to the etiologies of autism (reviewed in [Abrahams & Geschwind, 2008]). However, identifiable causes, such as Fragile X syndrome and chromosome abnormalities, account for ≤10% of cases. It is estimated that 10 to >100 genes, in addition to environmental effects, may contribute to disease susceptibility. Recently, small de novo genomic rearrangements or copy number variations (CNVs), that are likely pathogenic, have been identified in an additional ~10% of ASD cases [Marshall et al., 2008; Sebat et al., 2007; Shen et al., 2010; Szatmari et al., 2007]. Selected inherited CNVs likely represent additional susceptibility loci [Marshall et al., 2008; Shen et al., 2010; Szatmari et al., 2007]. A unifying theme among many of the CNVs identified, as well as susceptibility loci ascertained by linkage and association studies and direct gene sequencing, is localization of the involved protein at neural synapses. Contactin 4 (CNTN4), also called BIG-2, is a member of the immunoglobulin (Ig) superfamily of axon-associated adhesion molecules. The structure for the six human contactins consists of an N-terminal signal peptide followed by 6 Ig-like and 4 fibronectin type III-like domains, and a C-terminal glycosylphosphatidylinositol (GPI) binding site that anchors the protein to the external surface of the plasma membrane [Shimoda & Watanabe, 2009]. Cell surface contactins complex with one or more of 5 human contactin-associated proteins (CNTNAPs) that are members of the neurexin gene family (reviewed in [Burbach & van der Zwaag, 2009; Katidou, Vidaki, Strigini, & Karagogeos, 2008]). These complexes are believed to participate in neuronal migration, axon guidance, and neuronal and glial cell interactions, with exact functions dependent on the developmental stage and exact localization of the interacting proteins. Recent research implicates contactins and contactin-associated proteins (CNTNAPs) in neurodevelopmental disorders, including autism. Linkage and association analyses [Alarcon et al., 2008; Arking et al., 2008], as well as deep resequencing [Bakkaloglu et al., 2008], identified CNTNAP2 as a susceptibility locus for autism. Homozygosity mapping identified a homozygous deletion in the 5′ UTR of CNTN3 (BIG-1) in an autistic individual from a consanguineous mating, further implicating this gene family [Morrow et al., 2008]. CNTN4 maps to 3p26.3 and is deleted in individuals with 3p− syndrome, a rare microdeletion syndrome associated with developmental delay/mental retardation, microcephaly, and characteristic facies [Fernandez et al., 2008; Malmgren, Sahlen, Wide, Lundvall, & Blennow, 2007]. The CNTN4 gene has been considered a strong candidate for the developmental delay and microcephaly associated with 3p− syndrome, based on its postulated role in neurodevelopment and its disruption in patients with features of 3p− syndrome and a balanced 3;10 or unbalanced 3;13 chromosome translocation, respectively [Fernandez et al., 2004; Fernandez et al., 2008]. Several studies performing molecular characterization of patients with 3p− syndrome have concluded that CNTN4 lies within the minimal critical region [Dijkhuizen et al., 2006; Malmgren et al., 2007]. However, in a more recent investigation, CNTN4 appears to be excluded from the critical region based on a single patient with an interstitial 3p26 deletion [Shuib et al., 2009]. In addition, rare phenotypically normal individuals have been reported with visible deletions involving 3p26 that include CNTN4 ([Pohjola, de Leeuw, Penttinen, & Kaariainen, 2010; Shuib et al., 2009] and references therein). More recently, an intragenic deletion within CNTN4 [Roohi et al., 2009] was reported in two siblings with an ASD and their clinically unaffected father. A third affected child did not carry the deletion. Similarly, inherited and de novo intragenic duplications disrupting CNTN4 in individuals with an ASD have also recently been reported [Glessner et al., 2009; Roohi et al., 2009]. We recently identified a maternally inherited deletion of 3p26.3 that includes the 5′ UTR of CNTN4 in a child with severe autism. Based on the increasing evidence implicating contactins in ASDs, as well as localization of CNTN4 within the 3p− syndrome critical region, we undertook sequencing of the coding regions of the gene in a local cohort of ASD patients.

Background DNA methylation is an important epigenetic mark and dysregulation of DNA methylation is associated with many diseases including cancer. Advances in next-generation sequencing now allow unbiased methylome profiling of entire patient cohorts, greatly facilitating biomarker discovery and presenting new opportunities to understand the biological mechanisms by which changes in methylation contribute to disease. Enrichment-based sequencing assays such as MethylCap-seq are a cost effective solution for genome-wide determination of methylation status, but the technical reliability of methylation reconstruction from raw sequencing data has not been well characterized. Methods We analyze three MethylCap-seq data sets and perform two different analyses to assess data quality. First, we investigate how data quality is affected by excluding samples that do not meet quality control cutoff requirements. Second, we consider the effect of additional reads on enrichment score, saturation, and coverage. Lastly, we verify a method for the determination of the global amount of methylation from MethylCap-seq data by comparing to a spiked-in control DNA of known methylation status. Results We show that rejection of samples based on our quality control parameters leads to a significant improvement of methylation calling. Additional reads beyond ~13 million unique aligned reads improved coverage, modestly improved saturation, and did not impact enrichment score. Lastly, we find that a global methylation indicator calculated from MethylCap-seq data correlates well with the global methylation level of a sample as obtained from a spike-in DNA of known methylation level. Conclusions We show that with appropriate quality control MethylCap-seq is a reliable tool, suitable for cohorts of hundreds of patients, that provides reproducible methylation information on a feature by feature basis as well as information about the global level of methylation.

The outcome of older (≥ 60 years) acute myeloid leukemia (AML) patients is poor, and novel treatments are needed. In a phase 2 trial for older AML patients, low-dose (20 mg/m2 per day for 10 days) decitabine, a DNA hypomethylating azanucleoside, produced 47% complete response rate with an excellent toxicity profile. To assess the genome-wide activity of decitabine, we profiled pretreatment and post treatment (day 25/course 1) methylomes of marrow samples from patients (n = 16) participating in the trial using deep-sequencing analysis of methylated DNA captured by methyl-binding protein (MBD2). Decitabine significantly reduced global methylation compared with pretreatment baseline (P = .001). Percent marrow blasts did not correlate with global methylation levels, suggesting that hypomethylation was related to the activity of decitabine rather than to a mere decrease in leukemia burden. Hypomethylation occurred predominantly in CpG islands and CpG island-associated regions (P ranged from .03 to .04) A significant concentration (P < .001) of the hypomehtylated CpG islands was found in chromosome subtelomeric regions, suggesting a differential activity of decitabine in distinct chromosome regions. Hypermethylation occurred much less frequently than hypomethylation and was associated with low CpG content regions. Decitabine-related methylation changes were concordant with those previously reported in distinct genes. In summary, our study supports the feasibility of methylome analyses as a pharmacodynamic endpoint for hypomethylating therapies.

Advances in whole genome profiling have revolutionized the cancer research field, but at the same time have raised new bioinformatics challenges. For next generation sequencing (NGS), these include data storage, computational costs, sequence processing and alignment, delineating appropriate statistical measures, and data visualization. The NGS application MethylCap-seq involves the in vitro capture of methylated DNA and subsequent analysis of enriched fragments by massively parallel sequencing. Here, we present a scalable, flexible workflow for MethylCap-seq Quality Control, secondary data analysis, tertiary analysis of multiple experimental groups, and data visualization. This workflow and its suite of features will assist biologists in conducting methylation profiling projects and facilitate meaningful biological interpretation.

Background Advances in whole genome profiling have revolutionized the cancer research field, but at the same time have raised new bioinformatics challenges. For next generation sequencing (NGS), these include data storage, computational costs, sequence processing and alignment, delineating appropriate statistical measures, and data visualization. Currently there is a lack of workflows for efficient analysis of large, MethylCap-seq datasets containing multiple sample groups. Methods The NGS application MethylCap-seq involves the in vitro capture of methylated DNA and subsequent analysis of enriched fragments by massively parallel sequencing. The workflow we describe performs MethylCap-seq experimental Quality Control (QC), sequence file processing and alignment, differential methylation analysis of multiple biological groups, hierarchical clustering, assessment of genome-wide methylation patterns, and preparation of files for data visualization. Results Here, we present a scalable, flexible workflow for MethylCap-seq QC, secondary data analysis, tertiary analysis of multiple experimental groups, and data visualization. We demonstrate the experimental QC procedure with results from a large ovarian cancer study dataset and propose parameters which can identify problematic experiments. Promoter methylation profiling and hierarchical clustering analyses are demonstrated for four groups of acute myeloid leukemia (AML) patients. We propose a Global Methylation Indicator (GMI) function to assess genome-wide changes in methylation patterns between experimental groups. We also show how the workflow facilitates data visualization in a web browser with the application Anno-J. Conclusions This workflow and its suite of features will assist biologists in conducting methylation profiling projects and facilitate meaningful biological interpretation.