RELIC: a novel dye-bias correction method for Illumina Methylation BeadChip

Supplementary_Material. This docx file contains all supplementary tables and supplementary figures. (DOCX 424 kb

DMRforPairs: Identifying Differentially Methylated Regions between unique samples using array based methylation profiles

Background: Array based methylation profiling is a cost-effective solution to study the association between genome methylation and human disease & development. Available tools to analyze the Illumina Infinium HumanMethylation450 BeadChip focus on comparing methylation levels per locus. Other tools combine multiple probes into a range, identifying differential methylated regions (DMRs). These tools all require groups of samples to compare. However, comparison of unique, individual samples is essential in situations where larger sample sizes are not possible.Results: DMRforPairs was designed to compare regional methylation status between unique samples. It identifies probe dense genomic regions and quantifies/tests their (difference in) methylation level between the samples. As a proof of concept, DMRforPairs is applied to public data from four human cell lines: two lymphoblastoid cell lines from healthy individuals and the cancer cell lines A431 and MCF7 (including 2 technical replicates each). DMRforPairs identified an increasing number of DMRs related to the sample phenotype when biological similarity of the samples decreased. DMRs identified by DMRforPairs were related to the biological origin of the cell lines.Conclusion: To our knowledge, DMRforPairs is the first tool to identify and visualize relevant and significant differentially methylated regions between unique samples

Maternal BMI as a predictor of methylation of obesity-related genes in saliva samples from preschool-age Hispanic children at-risk for obesity.

BackgroundThe study of epigenetic processes and mechanisms present a dynamic approach to assess complex individual variation in obesity susceptibility. However, few studies have examined epigenetic patterns in preschool-age children at-risk for obesity despite the relevance of this developmental stage to trajectories of weight gain. We hypothesized that salivary DNA methylation patterns of key obesogenic genes in Hispanic children would 1) correlate with maternal BMI and 2) allow for identification of pathways associated with children at-risk for obesity.ResultsGenome-wide DNA methylation was conducted on 92 saliva samples collected from Hispanic preschool children using the Infinium Illumina HumanMethylation 450 K BeadChip (Illumina, San Diego, CA, USA), which interrogates >484,000 CpG sites associated with ~24,000 genes. The analysis was limited to 936 genes that have been associated with obesity in a prior GWAS Study. Child DNA methylation at 17 CpG sites was found to be significantly associated with maternal BMI, with increased methylation at 12 CpG sites and decreased methylation at 5 CpG sites. Pathway analysis revealed methylation at these sites related to homocysteine and methionine degradation as well as cysteine biosynthesis and circadian rhythm. Furthermore, eight of the 17 CpG sites reside in genes (FSTL1, SORCS2, NRF1, DLC1, PPARGC1B, CHN2, NXPH1) that have prior known associations with obesity, diabetes, and the insulin pathway.ConclusionsOur study confirms that saliva is a practical human tissue to obtain in community settings and in pediatric populations. These salivary findings indicate potential epigenetic differences in Hispanic preschool children at risk for pediatric obesity. Identifying early biomarkers and understanding pathways that are epigenetically regulated during this critical stage of child development may present an opportunity for prevention or early intervention for addressing childhood obesity.Trial registrationThe clinical trial protocol is available at ClinicalTrials.gov ( NCT01316653 ). Registered 3 March 2011

Clopidogrel Pharmacogenetics, resistance to antiplatelet therapy in ischemic stroke by Epigenome Wide Association Study (EWAS).

Curs 2012-2013Clopidogrel is a widely used antiplatelet drug used in preventing vascular events after suffering a first stoke. Genome-wide association studies (GWAS) has not been able to establish a clear association between polymorphisms and recurrence. Therefore in the present final master project an epigenetic approach is proposed. Using an array based technology, 450.000 CpG sites across all genome were assessed in 48 individuals (21 cases and 21 controls). Looking at differentially methylated levels between cases and controls, 58 CpG sites (DMGs) were found. Although, no clear locus was observed. Looking individually to each 49 genes, two appeared to be important to our study. TRAF3 and ADAMTS2 are gens highly related to platelet aggregation. In orther to confirm these result, a new DNA methylation study will be done in a larger cohort, using Sequenom technology.Director/a: Israel Fernandez Cadenas i Tutor/a: Jordi Plana

DNA methylation assessment as a prognostic factor in invasive breast cancer using methylation-specific multiplex ligation dependent probe amplification

DNA methylation of promoter regions is a common molecular mechanism for inactivation of tumor suppressor genes that participates in carcinogenesis. Determining the methylation status of genes in cancer and their association with clinical features play an essential role in early diagnosis, prognosis and determine appropriate treatment for patients. The purpose of the present study was to evaluate the methylation of tumor suppressor genes in patients with invasive ductal carcinoma (IDC). Furthermore, we evaluated the association between clinical parameters and DNA methylation as a biomarker in diagnostic IDC patients. The methylation-specific multiplex ligation dependent probe amplification (MS-MLPA) assay was used to analyze the methylation profile of 24 genes in formalin-fixed paraffin embedded (FFPE) tissue samples from 75 patients with IDC. Each of the patients showed a distinctive methylation profile. We observed higher methylation in the RASSF1 (48 %), CDH13 (44 %) and GSTP1 (36 %) genes. Some of the methylated genes were associated with clinical features. Methylation of GSTP1 (P=0.028) and RASSF1 (P=0.012) were related with lymph node metastasis. Methylation of GSTP1 (P=0.005) was associated with high histological grade. Moreover, concurrent methylation of GSTP1 and CDH13 was observed in IDC patients (p<0.001). Hierarchical cluster analysis based on the methylation profile revealed two main clusters of patients, the highly methylated cluster being significantly associated with high histological grade and lymph node metastasis. The results of this study indicate that the methylation status of RASSF1 and CDH13 and GSTP1 can be a prognostic marker to better management of IDC patients

An evaluation of processing methods for HumanMethylation450 BeadChip data

BackgroundIllumina's HumanMethylation450 arrays provide the most cost-effective means of high-throughput DNA methylation analysis. As with other types of microarray platforms, technical artifacts are a concern, including background fluorescence, dye-bias from the use of two color channels, bias caused by type I/II probe design, and batch effects. Several approaches and pipelines have been developed, either targeting a single issue or designed to address multiple biases through a combination of methods. We evaluate the effect of combining separate approaches to improve signal processing.ResultsIn this study nine processing methods, including both within- and between- array methods, are applied and compared in four datasets. For technical replicates, we found both within- and between-array methods did a comparable job in reducing variance across replicates. For evaluating biological differences, within-array processing always improved differential DNA methylation signal detection over no processing, and always benefitted from performing background correction first. Combinations of within-array procedures were always among the best performing methods, with a slight advantage appearing for the between-array method Funnorm when batch effects explained more variation in the data than the methylation alterations between cases and controls. However, when this occurred, RUVm, a new batch correction method noticeably improved reproducibility of differential methylation results over any of the signal-processing methods alone.ConclusionsThe comparisons in our study provide valuable insights in preprocessing HumanMethylation450 BeadChip data. We found the within-array combination of Noob + BMIQ always improved signal sensitivity, and when combined with the RUVm batch-correction method, outperformed all other approaches in performing differential DNA methylation analysis. The effect of the data processing method, in any given data set, was a function of both the signal and noise

Genome-Wide DNA Methylation Profiling in Human Breast Tissue by Illumina TruSeq Methyl Capture EPIC Sequencing and Infinium MethylationEPIC Beadchip Microarray

A newly-developed platform, the Illumina TruSeq Methyl Capture EPIC library prep (TruSeq EPIC), builds on the content of the Infinium MethylationEPIC Beadchip Microarray (EPIC-array) and leverages the power of next-generation sequencing for targeted bisulphite sequencing. We empirically examined the performance of TruSeq EPIC and EPIC-array in assessing genome-wide DNA methylation in breast tissue samples. TruSeq EPIC provided data with a much higher density in the regions when compared to EPIC-array (~2.74 million CpGs with at least 10X coverage vs ~752 K CpGs, respectively). Approximately 398 K CpGs were common and measured across the two platforms in every sample. Overall, there was high concordance in methylation levels between the two platforms (Pearson correlation r = 0.98, P \u3c 0.0001). However, we observed that TruSeq EPIC measurements provided a wider dynamic range and likely a higher quantitative sensitivity for CpGs that were either hypo- or hyper-methylated (β close to 0 or 1, respectively). In addition, when comparing different breast tissue types TruSeq EPIC identified more differentially methylated CpGs than EPIC-array, not only out of additional sites interrogated by TruSeq EPIC alone, but also out of common sites interrogated by both platforms. Our results suggest that both platforms show high reproducibility and reliability in genome-wide DNA methylation profiling, while TruSeq EPIC had a significant improvement over EPIC-array regarding genomic resolution and coverage. The wider dynamic range and likely higher precision of the estimates by the TruSeq EPIC may lead to the identification of novel differentially methylated markers that are associated with disease risk