CATA: a comprehensive chromatin accessibility database for cancer

Chromatin accessibility is a crucial epigenetic concept that plays a biological role in oncology. As humans become more involved in cancer research, a comprehensive database is required to identify and annotate tumor chromatin accessible regions (CARs). Here, CATA was developed to provide cancer-related CAR annotation. Currently, CATA possesses 2,991,163 CARs, relevant clinical data, and transcription factor binding predictions for cancer CARs from 410 tumor samples of 24 cancer types. Furthermore, CARs were annotated by SNPs, risk SNPs, eQTLs, linkage disequilibrium SNPs, transcription factors, CNV, SNV, enhancer, and 450K methylation sites in our database. By combining all these resources, we believe that CATA will provide better service for researchers on oncology. Our database is accessible at http://bio.licpathway.net/cata/

Derivation of Poly-Methylomic Profile Scores for Schizophrenia

Schizophrenia (SZ) and bipolar disorder (BD) share numerous clinical and biological features as well as environmental risk factors that may be associated with altered DNA methylation. In this study we sought to construct a Poly-Methylomic Profile Score (PMPS) for SZ, representing the degree of epigenome-wide methylation according to previously published findings; we then examined its association with SZ and BD in an independent sample. DNA methylation for 57 SZ, 59 BD cases and 55 healthy controls (HCs) was quantified using the Illumina 450K methylation beadchip. We constructed five PMPSs for different p-value thresholds using summary statistics reported in a large epigenome-wide schizophrenia case-control association study, weighted by individual CpG effect sizes. All SZ PMPSs were significantly elevated in SZ cases relative to HCs, with the score calculated at the most stringent threshold accounting for the greatest amount of variance in SZ (compared to other PMPSs derived at more inclusivep-value thresholds). However, none of the PMPSs were associated with BD, or a combined cohort of BD and SZ cases relative to HCs. Results demonstrating elevated PMPSs in SZ relative to BD did not survive correction for multiple testing. PMPSs were also not associated with positive or negative symptom severity. That this SZ-derived PMPSs was elevated among SZ, but not BD participants, suggests that epigenome-wide methylation patterns associated with schizophrenia may represent distinct pathophysiology that is yet to be elucidated. Whether this PMPS may be associated with neuroanatomical or other biological endophenotypes relevant to SZ and/or BD remains to be determined.

Discovery and Validation of Methylation Biomarkers for Ulcerative Colitis Associated Neoplasia

Background and aims Ulcerative colitis (UC) is associated with a higher background risk of dysplasia and/or neoplasia due to chronic inflammation. There exist few biomarkers for identification of patients with dysplasia, and targeted biopsies in this group of patients are inaccurate in reliably identifying dysplasia. We aimed to examine the epigenome of UC dysplasia and to identify and validate potential biomarkers Methods Colonic samples from patients with UC-associated dysplasia or neoplasia underwent epigenome-wide analysis on the Illumina 450K methylation array. Markers were validated by bisulphite pyrosequencing on a secondary validation cohort and accuracy calculated using logistic regression and receiver-operator curves. Results Twelve samples from 4 patients underwent methylation array analysis and 6 markers (GNG7, VAV3, KIF5C, PIK3R5, TUBB6, and ZNF583) were taken forward for secondary validation on a cohort of 71 colonic biopsy samples consisting of normal uninflamed mucosa from control patients, acute and chronic colitis, “field” mucosa in patients with dysplasia/neoplasia, dysplasia, and neoplasia. Methylation in the beta-tubulin TUBB6 correlated with the presence of dysplasia (P < 0.0001) and accurately discriminated between dysplasia and nondysplastic tissue, even in the apparently normal field mucosa downstream from dysplastic lesions (AUC 0.84, 95% CI 0.81–0.87). Conclusions Methylation in TUBB6 is a potential biomarker for UC- associated dysplasia. Further validation is needed and is ongoing as part of the ENDCAP-C study.

pyMAP: a Python package for small and large scale analysis of Illumina 450k methylation platform

PyMAP is a native python module for analysis of 450k methylation platform and is freely available for public use. The package can be easily deployed to cloud platforms that support python scripting language for large-scale methylation studies. By implementing fast parsing functionality, this module can be used to analyze large scale methylation datasets. Additionally, command-line executables shipped with the module can be used to perform common analysis tasks on personal computers.Availability and implementation: PyMAP is implemented in Python and the source code is available under GPL v2 license from http://aminmahpour.github.io/PyMAP/.

Genome-wide methylation data mirror ancestry information

Genetic data are known to harbor information about human demographics, and genotyping data are commonly used for capturing ancestry information by leveraging genome-wide differences between populations. In contrast, it is not clear to what extent population structure is captured by whole-genome DNA methylation data. We demonstrate, using three large cohort 450K methylation array data sets, that ancestry information signal is mirrored in genome-wide DNA methylation data, and that it can be further isolated more effectively by leveraging the correlation structure of CpGs with cis-located SNPs. Based on these insights, we propose a method, EPISTRUCTURE, for the inference of ancestry from methylation data, without the need for genotype data. EPISTRUCTURE can be used to infer ancestry information of individuals based on their methylation data in the absence of corresponding genetic data. Although genetic data are often collected in epigenetic studies of large cohorts, these are typically not made publicly available, making the application of EPISTRUCTURE especially useful for anyone working on public data. Implementation of EPISTRUCTURE is available in GLINT, our recently released toolset for DNA methylation analysis at: http://glint-epigenetics.readthedocs.io.