Inflammation-associated DNA methylation patterns in epithelium of ulcerative colitis

<p>Aberrant DNA methylation patterns have been reported in inflamed tissues and may play a role in disease. We studied DNA methylation and gene expression profiles of purified intestinal epithelial cells from ulcerative colitis patients, comparing inflamed and non-inflamed areas of the colon. We identified 577 differentially methylated sites (false discovery rate <0.2) mapping to 210 genes. From gene expression data from the same epithelial cells, we identified 62 differentially expressed genes with increased expression in the presence of inflammation at prostate cancer susceptibility genes <i>PRAC1</i> and <i>PRAC2</i>. Four genes showed inverse correlation between methylation and gene expression; <i>ROR1, GXYLT2, FOXA2,</i> and, notably, <i>RARB</i>, a gene previously identified as a tumor suppressor in colorectal adenocarcinoma as well as breast, lung and prostate cancer. We highlight targeted and specific patterns of DNA methylation and gene expression in epithelial cells from inflamed colon, while challenging the importance of epithelial cells in the pathogenesis of chronic inflammation.</p

Analysis of CRY1 CpG island promoter methylation status measured with the Bisulphite MassArray assay.

<p><b>A</b> Results of CRY1 CpG island methylation analysis performed on CLL samples and normal donors (ND) grouped by CD38 expression (CD38− samples, n = 28; CD38+ samples, n = 30; ND, n = 5). Each value represents the average amount of methylated CpGs of all analyzable CpGs within the CpG island promoter from one patient. The values represent the mean of duplicate experiments. The IgVH mutational status of each patient (if available) is highlighted in red; circles and squares indicate unmutated IgVH/V3-21 and mutated IgVH status, respectively. The median is marked as a line, error bars indicate SEM. Unpaired two-tailed t-test was used to compute p-values. <b>B</b> Samples from CLL patients and ND were subjected to both CRY1 mRNA expression and DNA methylation analysis with the bisulphite MassArray assay. mRNA expression values and percentage of methylated CpG were found to be highly correlated (r = −0.63, p<0.0001, Spearman correlation). The regression line in the plot was produced by linear regression analysis using promoter methylation as dependent and CRY1 mRNA expression as independent variable. <b>C</b> Correlation between the methylation data resulting from bisulphite genomic sequencing and the MassArray method showed high consistency (r = 0.86, p<0.0001, Spearman correlation).</p

Expression of CRY1 in CLL subgroups and normal donors.

<p><i>CRY1</i> mRNA expression in normal donors (ND, n = 35) in comparison to CLL samples from prognostic subgroups defined by CD38 expression (A, CD38+ samples, n = 36 vs. CD38− samples, n = 39) and IgVH mutational status (B, IgVH unmutated/V3-21, UM/V3-21, n = 23 vs. IgVH mutated, M, n = 18). mRNA levels are relative to GAPDH. Data are presented in a box-and-whisker format: the difference of the 25th and 75th percentile form the box (interquartile range, IQR), with the median marked as a line; the whiskers go down to the smallest value and up to the largest values. The Mann-Whitney U-test was used to compute p-values for pairwise comparisons.</p

Comparative analysis of CRY1 expression in a panel of different lymphoid malignancies.

<p>qRT-PCR analyses of PBMC samples obtained from patients with T-prolymphocytic leukemia (T-PLL), mantle cell lymphoma (MCL), plasma cell leukemia (PCL), hairy cell leukemia (HCL), B and T cell acute lymphoblastic leukemia (B-ALL, T-ALL), CLL and normal donors (ND), A. Red characters indicate samples that were further subjected to DNA methylation analysis of the CRY1 promoter, A. Analysis of CRY1 CpG island promoter methylation status, B. For experimental details and description of the graph in panel B refer to the legend of <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0034347#pone-0034347-g002" target="_blank">Figure 2</a>.</p

Development of a Targeted Multi-Disorder High-Throughput Sequencing Assay for the Effective Identification of Disease-Causing Variants

<div><p>Background</p><p>While next generation sequencing (NGS) is a useful tool for the identification of genetic variants to aid diagnosis and support therapy decision, high sequencing costs have limited its application within routine clinical care, especially in economically depressed areas. To investigate the utility of a multi-disease NGS based genetic test, we designed a custom sequencing assay targeting over thirty disease-associated areas including cardiac disorders, intellectual disabilities, hearing loss, collagenopathies, muscular dystrophy, Ashkenazi Jewish genetic disorders, and complex Mendelian disorders. We focused on these specific areas based on the interest of our collaborative clinical team, suggesting these diseases being the ones in need for the development of a sequencing-screening assay.</p><p>Results</p><p>We targeted all coding, untranslated regions (UTR) and flanking intronic regions of 650 known disease-associated genes using the Roche-NimbleGen EZ SeqCapV3 capture system and sequenced on the Illumina HiSeq 2500 Rapid Run platform. Eight controls with known variants and one HapMap sample were first sequenced to assess the performance of the panel. Subsequently, as a proof of principle and to explore the possible utility of our test, we analyzed test disease subjects (n = 16). Eight had known Mendelian disorders and eight had complex pediatric diseases. In addition to assess whether copy number variation may be of utility as a companion assay relative to these specific disease areas, we used the Affymetrix Genome-Wide SNP Array 6.0 to analyze the same samples.</p><p>Conclusion</p><p>We identified potentially disease-associated variants: 22 missense, 4 nonsense, 1 frameshift, and 1 splice variants (16 previously identified, 12 novel among dbSNP and 15 novel among NHLBI Exome Variant Server). We found multi-disease targeted high-throughput sequencing to be a cost efficient approach in detecting disease-associated variants to aid diagnosis.</p></div

Treatment-free survival according to the methylation status of the CRY1 promoter region.

<p>Treatment-free survival of 53 CLL patients with lowly methylated (n = 26) and highly methylated (n = 27) CRY1 promoter.</p

Patient characteristics.

*<p>n.a., not available.</p

Custom panel design.

<p>The pie chart illustrates the percent of genes included in the custom design categorized based on specific diseases/abnormalities. Of note the Ashkenazi Jews variant disorders have been kept separate because they represent an ethnic division commonly associated with specific disease and genetic variants.</p

Cost comparison of target sequencing panel Einstein_v1 versus Whole Exome Sequencing.

<p>* The number of SNVs/InDels identified was based on samples used in the current analysis (n = 2 for WES and matching target sequencing).</p><p>** Based on estimated $1,400/lane 150 bp pair end sequencing on Illumina 2500.</p><p>Cost comparison of target sequencing panel Einstein_v1 versus Whole Exome Sequencing.</p

Summary of sequencing coverage and detected variants for test cohort.

<p>* indicates samples that were multiplexed together.</p><p>TG471.002 was added to another lane for logistic reasons.</p><p>Summary of sequencing coverage and detected variants for test cohort.</p