Tissue-specific patterns of gene expression in the epithelium and stroma of normal colon in healthy individuals in an aspirin intervention trial

AbstractRegular aspirin use reduces colon adenoma and carcinoma incidence. UDP-glucuronosyltransferases (UGT) are involved in aspirin metabolism and clearance, and variant alleles in UGT1A6 have been shown to alter salicylic acid metabolism and risk of colon neoplasia. In a randomized, cross-over, placebo-controlled trial of 44 healthy men and women, homozygous for UGT1A6*1 or UGT1A6*2, we explored differences between global epithelial and stromal expression, using Affymetrix U133+2.0 microarrays and tested effects of 60-day aspirin supplementation (325mg/d) on epithelial and stromal gene expression and colon prostaglandin E2 (PGE2) levels. We conducted a comprehensive study of differential gene expression between normal human colonic epithelium and stroma from healthy individuals. Although no statistically significant differences in gene expression were observed in response to aspirin or UGT1A6 genotype, we have identified the genes uniquely and reproducibly expressed in each tissue type and have analyzed the biologic processes they represent. Here we describe in detail how the data, deposited in the Gene Expression Omnibus (GEO) – accession number GSE71571 – was generated including the basic analysis as contained in the manuscript published in BMC Medical Genetics with the PMID 25927723 (Thomas et al., 2015 [9])

Methylenetetrahydrofolate Reductase and Thymidylate Synthase Genotypes and Risk of Acute Graft-versus-Host Disease Following Hematopoietic Cell Transplantation for Chronic Myelogenous Leukemia

AbstractMethylenetetrahydrofolate reductase (MTHFR) and thymidylate synthase (TS) play key roles in intracellular folate metabolism. Polymorphisms in these enzymes have been shown to modify toxicity of methotrexate (MTX) after hematopoietic cell transplantation. In this study, we evaluated the risk of acute graft-versus-host disease (GVHD) associated with genetic variation in recipient and donor MTHFR and TS genotypes to assess whether genotype alters the efficacy of MTX in acute GVHD prophylaxis. Data on the transplantation course were abstracted from medical records for 304 adults who received allogeneic hematopoietic cell transplants. MTHFR (C677T and A1298C) and TS (enhancer-region 28-base pair repeat, TSER, and 1494del6) genotypes were determined using polymerase chain reaction/restriction fragment length polymorphism and TaqMan assays. Multivariable logistic regression was used to assess the associations between genotypes and risk of acute GVHD. Compared with recipients with the wild-type MTHFR 677CC genotype, those with the variant 677T allele showed a decreased risk of detectable acute GVHD (677CT: odds ratio, 0.8; 95% confidence interval, 0.4-1.6; 677TT: odds ratio, 0.4; 95% confidence interval, 0.2-0.8; P for trend = .01). The variant MTHFR 1298C allele in recipients was associated with an increased risk of acute GVHD compared with the wild-type MTHFR 1298AA genotype (1298AC: odds ratio, 2.0; 95% confidence interval, 1.1-3.9; 1298CC: odds ratio, 3.6; 95% confidence interval, 1.0-12.7; P for trend < .01). No association with risk of acute GVHD was observed for donor MTHFR genotypes or for recipient or donor TS genotypes, with the exception of an increase in acute GVHD among recipients whose donors had the TSER 3R/2R genotype (odds ratio, 3.0; 95% confidence interval, 1.3-7.2). These findings indicate that host, but not donor, MTHFR genotypes modify the risk of acute GVHD in recipients receiving MTX, in a manner consistent with our previously reported associations between MTHFR genotypes and MTX toxicity. A direct trade-off between drug toxicity and drug efficacy may play a role. Alternatively, the systemic folate environment, regulated by host tissues, might influence donor T-cell growth and activity

Effect of Implementing Fold-Change and p-value Cut-offs on a Comparison Between Two Experiments.

<p>Panels A-D show a hexbin plot comparison of the average log10(ratio) values between the Gudjonsson Low and the NCT00867100 data sets with (A) no cut-offs, (B) a p-value≤0.05 cut-off in the source set only, (C) p-value≤0.05 and log10(ratio)≥0.1 cut-offs only in the source set, and (D) p-value≤0.05 and log10(ratio)≥0.1 cut-offs in the source set and a p-value≤0.05 cut-off in the target set. The numbers in the panel corners indicate the number of data points in those quadrants. Panel E shows average log10(ratio) distributions in the Gudjonsson Low data set (target set) for sequences with log10(ratio) values of 0.100±0.005 (blue), 0.200±0.005 (pink), and 0.300±0.005 (green) in the source set (NCT00867100).</p

Effect of log10(ratio) on Proportion of “Disagreeing” Probe Sets at a p-value of 0.05 in the Source Set.

<p>The data sets are the same as for the data shown in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0052242#pone-0052242-g001" target="_blank">Figure 1</a>. Either NCT00867100 (A, C) or Gudjonsson Low (B, D) were chosen as the source set. The proportion of probe sets disagreeing (out of all the probe sets) is shown for different log10(ratio) cutoffs. A and B: p-value of 0.05 in the source set and no cut-offs in the target sets; C and D: p-value cut-off of 0.05 in source and target set.</p

Comparison of Fold-changes in Psoriasis PP/PN Pairs by Microarray and qRT-PCR.

<p>Fold-changes for a selection of mostly immune system transcripts were assessed by qRT-PCR and microarray in a subset of eight psoriasis PP/PN skin biopsies from the Asterand set. Transcripts were selected based on relevance to psoriasis, range of expression level and range of fold-changes; patient biopsies were selected based on microarray data so that the range of differential expression was large. The black line indicates complete concordance.</p

Comparison of Differential Expression Across Data Sets.

<p>For each data set a list of probe sets with differential expression at p≤0.05 was generated and compared to all the other data sets. The probe sets were then categorized into four different groups according to the extent of agreement between the source data set and the other data sets: i) “consistent” meant that there was at least one other data set in which the probe set showed differential expression in the same direction with p≤0.05 and no data sets with differential expression in the opposite direction with p≤0.05; ii) “inconsistent between platforms” indicated that there was at least one data set from the other platform with differential expression at p≤0.05 in the opposite direction; iii) the “inconsistent within platform” group contained probe sets with differential expression at p≤0.05 in different directions within the same platform; and iv) the “p>0.05 in all other” group contained probe sets where the source set was the only one with significant differential expression. The number of probe sets with differential expression in the Zaba (GSE11903) and the Reischl sets were smaller because samples were run on U133A arrays, which contain only 22,215 probe sets.</p