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

Radiation dose dependent positive correlations between plasma and liver metabolites for whole liver irradiation for the combined radiation levels of 0, 10 or 50 Gy.

<p>The Spearman’s correlation coefficient, is defined in Methods.</p><p>Radiation dose dependent positive correlations between plasma and liver metabolites for whole liver irradiation for the combined radiation levels of 0, 10 or 50 Gy.</p

Integrative Metabolic Signatures for Hepatic Radiation Injury

<div><p>Background</p><p>Radiation-induced liver disease (RILD) is a dose-limiting factor in curative radiation therapy (RT) for liver cancers, making early detection of radiation-associated liver injury absolutely essential for medical intervention. A metabolomic approach was used to determine metabolic signatures that could serve as biomarkers for early detection of RILD in mice.</p><p>Methods</p><p>Anesthetized C57BL/6 mice received 0, 10 or 50 Gy Whole Liver Irradiation (WLI) and were contrasted to mice, which received 10 Gy whole body irradiation (WBI). Liver and plasma samples were collected at 24 hours after irradiation. The samples were processed using Gas Chromatography/Mass Spectrometry and Liquid Chromatography/Mass Spectrometry.</p><p>Results</p><p>Twenty four hours after WLI, 407 metabolites were detected in liver samples while 347 metabolites were detected in plasma. Plasma metabolites associated with 50 Gy WLI included several amino acids, purine and pyrimidine metabolites, microbial metabolites, and most prominently bradykinin and 3-indoxyl-sulfate. Liver metabolites associated with 50 Gy WLI included pentose phosphate, purine, and pyrimidine metabolites in liver. Plasma biomarkers in common between WLI and WBI were enriched in microbial metabolites such as 3 indoxyl sulfate, indole-3-lactic acid, phenyllactic acid, pipecolic acid, hippuric acid, and markers of DNA damage such as 2-deoxyuridine. Metabolites associated with tryptophan and indoles may reflect radiation-induced gut microbiome effects. Predominant liver biomarkers in common between WBI and WLI were amino acids, sugars, TCA metabolites (fumarate), fatty acids (lineolate, n-hexadecanoic acid) and DNA damage markers (uridine).</p><p>Conclusions </p><p>We identified a set of metabolomic markers that may prove useful as plasma biomarkers of RILD and WBI. Pathway analysis also suggested that the unique metabolic changes observed after liver irradiation was an integrative response of the intestine, liver and kidney.</p></div

Liver metabolites key to group separation predicted by PLS-DA assessed using variable influence on projections (VIPs).

<p>Liver PLS-DA VIPs identified potential biomarkers and exhibited strong overlap with metabolites important for classification using the Random Forest approach. VIP values greater than 1 delineated metabolites most important for cluster classification. An asterisk indicates metabolites in the purine synthesis pathway while a 'P' indicates the pentose phosphate pathway. Both purines and pentose phosphate metabolites were highly important for liver group classification, reinforcing Random Forest findings, and might be determinants of the liver radiation response.</p

Plasma metabolites key to group separation predicted by Random Forest classification.

<p>The top 30 plasma metabolites important for increasing class separation as determined by the Random Forest approach. Bradykinin was seen as most important for class separation, however, smaller peptides also showed class discrimination, such as L-aspartyl-L-phenylalanine, and alanyl-alanine. Energy metabolism, as reflected by the presence of riboflavin as a biomarker, was indicated. Metabolites suggesting multiple organ interactions, i.e. kidney/liver/GI tract/microbiome were indicated (see text).</p

Example of consistent metabolite signatures in liver and plasma.

<p>Malic acid and riboflavine are shown as two examples of metabolites, which showed distinctive, consistent signatures in both liver and plasma samples. Supporting information tables show further hits that were consistently altered post-radiation in either liver, or plasma, or both.</p

CoolMap and identification of unknown metabolites.

<p>CoolMap hierarchical clustering analysis was used for detection of relationships between metabolites, and biological processes in liver or plasma. The top and bottom panels, for plasma and liver, respectively, illustrate on how the “known unknown” metabolites within both plasma and liver samples were correlated with known metabolites that were grouped into ontologies to potentially aid in identification/inference of function. This enabled the relevance of the “known unknowns” seen to be important for class separation by Random Forest and PLS-DA. Top panel: “known unknown” metabolites in plasma are related to urea cycle, branched chain amino acids, tryptophan and microbial metabolites. Bottom panel: “known unknown” metabolites in liver are related to Purine metabolism (see text).</p

Levels of metabolites changing between 0 Gy and 10 Gy in liver and plasma.

<p>Liver and plasma metabolites are positively correlated, except for N-acetylalanine, EPA, 1-monolinolein and Docosahexaenoic Acid which are negatively correlated.</p><p>Levels of metabolites changing between 0 Gy and 10 Gy in liver and plasma.</p

Pentose Phosphate Pathway changes in response to liver irradiation.

<p>The pentose phosphate pathway generates NADPH, ribose 5-phosphate, and intermediates of the glycolytic pathway. The NADPH is utilized for reductive pathways, such as fatty acid biosynthesis and the glutathione defense system against injury by reactive oxygen species. Ribose 5-phosphate provides the sugar for nucleotide synthesis. Increased levels of pentose phosphate intermediates may indicate altered glucose and/or nucleotide metabolism.</p

Plasma metabolites key to group separation predicted by PLS-DA assessed using variable influence on projections (VIPs).

<p>The most significant known hits for plasma VIPs included: bradykinin, niacinamide, riobflavine, 3-indoxyl-sulfate, and 3-hydroxycinnamic acid. Levels of plasma bradykinin increased more than 25-fold following high dose irradiation. Based on its vasodilator effects, bradykinin may help increase permeability in vasculature damaged by radiation. As in the previous figures, VIP values greater than 1 delineated metabolites most important for cluster classification.</p