Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Expression data from intestinal mucosa of patients with UC

ABSTRACT: Ulcerative colitis (UC) is a chronic inflammatory disease of the colon with preiods of active disease followed by remission. We performed a whole-genome transcriptional analysis of colonic biopsies from patients with histologically active and inactive UC, as well as non-inflammatory controls. Ulcerative colitis patients and non-inflammatory controls were collected for RNA extraction and hybridization on Affymetrix microarrays. Inclusion criteria for UC patients were: age between 18 and 65, diagnosis of UC established at least 6 months before inclusion and exclusion of concomitant infection. Active disease was defined by endoscopic and histologic score: Mayo sub score >=2 and MATTS >=3 respectively . Inactive disease was also defined by endoscopic and histologic score: Mayo sub score =0 and MATTS <=2 respectively, and a remission state for a minimum of 5 month prior to biopsy collection, and remained inactive for at least 6 months after. Uninvolved mucosa from patients with active UC was defined as a colonic segment with completely normal endoscopic appearance, normal histology, and absence of any previous evidence of active disease. Finally, a total of 43 biopsies were analyzed: 13 healthy controls, 8 inactive UC, 7 non-involved active UC and 15 involved active UC.

ORGANISM(S): Homo sapiens

SUBMITTER: Azucena Salas

PROVIDER: E-GEOD-38713 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

ACCESS DATA

Publications

Transcriptional analysis of the intestinal mucosa of patients with ulcerative colitis in remission reveals lasting epithelial cell alterations.

Planell Núria N Lozano Juan J JJ Mora-Buch Rut R Masamunt M Carme MC Jimeno Mireya M Ordás Ingrid I Esteller Miriam M Ricart Elena E Piqué Josep M JM Panés Julián J Salas Azucena A

Gut 20121107 7

<h4>Objective</h4>Ulcerative colitis (UC) is a chronic condition characterised by the relapsing inflammation despite previous endoscopic and histological healing. Our objective was to identify the molecular signature associated with UC remission.<h4>Design</h4>We performed whole-genome transcriptional analysis of colonic biopsies from patients with histologically active and inactive UC, and non-inflammatory bowel disease (non-IBD) controls. Real-time reverse transcriptase-PCR and immunostaining ...[more]

PMID: 23135761

Shared Molecules

Only show the datasets with similarity scores above: 0.5

Threshold

0.5

Similar Datasets

Project description:The objective of the study was to understand gene expression patterns and pathways that relate to Endoscopic Remission and Histologic remission in IBD as defined by different endoscopic and histological disease activity scores. Colonic Endoscopic biopsies were collected in RNAlater from 21 UC patients undergoingcolonoscopies withthe endocytoscope CF- Y-0058-1 prototype Olympus, Japan). RNA was extracted using RNeasy columns (Qiagen) and quantified by Qubit (Life Technologies). 0.5ng RNA was used to prepare uniquely indexed cDNA QIAseq UPX 3’ Transcriptome libraries according to manufacturer’s instructions (Qiagen). Libraries were quantified and quality-controlled using the QIAseq Library Quant Assay Kit and tapestation analysis and sequenced on the Miseq and Nextseq Illumina platforms using the illumina sequencing primer and PhiX 15% to a depth of 1-3milion reads/sample. Read numbers were set as 101 bp (R1) x 51 bp (R2). Fastq files were obtained through BaseSpace and reads de-multiplexed, aligned to human genome GRCh38, quantified and normalised by the TPM method using the CLC Genomics Workbench (Qiagen). The following differential expression procedure was performed for participants classified as healed versus non-healed according different histologic and endoscpic scores which included the histological scores: Nancy and Robarts Histological Index (RHI) as well as the mayo endoscopic score (MES) and the endocytoscopy score system (ECSS). Normalised values were log-transformed with a pseudocount of 1 added. Transcripts with < 1 transformed count in any sample were excluded from further analysis, as were transcripts with low variance (defined as less than 10% unique counts across both conditions and greater than a 19:1 ratio of the most frequent count to the second most frequent across both conditions). Differential expression analysis between conditions was conducted with the limma package. Library size was estimated using reduced maximum likelihood estimator with 500 iterations. Initial fitting was performed using a robust M-estimation, and moderated test statistics computed by empirical Bayes. A FDR corrected p value <0.05 was considered and filtered for further downstream data analysis. Partial least squares discriminant analysis (PLS-DA) modelling was performed on these genes and a variable Importance in Projection (VIP) score of >1 was used to further filter the genes. To understand the biological significance and pathways, we also performed enrichment analysis using EnrichR involving three databases: Gene ontology, Wiki pathways and Kyoto Encyclopaedia of Genes and Genomes (KEGG).