Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Expression data from intestinal mucosa of patients with CD under anti-TNF-alpha therapy.

ABSTRACT: Crohn's Disease (CD) is a chronic inflammatory disease of the intestinal tract. We performed a whole-genome transcriptional analysis using colonic biopsies from CD patients before and after anti-TNF-α therapy. Involved colonic samples from Crohn's disease patients and healthy colonic samples from non-inflammatory controls were collected for RNA extraction and hybridization on Affymetrix microarrays. Inclusion criteria for CD patients were: age between 18 and 70, diagnosis of CD established at least 4 months before inclusion and exclusion of concomitant infection. Active disease was defined by endoscopic and clinical score: endoscopic active disease was defined as a CD endoscopic index of severity (CDEIS) of 5 or more and the presence of large ulcers (> 0.5 cm diameter) in at least one of the explored segments. Clinical activity was defined as a CD activity index (CDAI) above 150. Finally, a total of 39 biopsies were analyzed: 17 healthy controls, 10 active CD without anti-TNF therapy, 5 active CD with anti-TNF therapy (non-responders) and 7 inactive CD with anti-TNF therapy (responders).

ORGANISM(S): Homo sapiens

SUBMITTER: Azucena Salas

PROVIDER: E-GEOD-52746 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

Identification of inflammatory mediators in patients with Crohn's disease unresponsive to anti-TNFα therapy.

Leal Raquel Franco RF Planell Núria N Kajekar Radhika R Lozano Juan J JJ Ordás Ingrid I Dotti Isabella I Esteller Miriam M Masamunt M Carme MC Parmar Harsukh H Ricart Elena E Panés Julián J Salas Azucena A

Gut 20140403 2

<h4>Background</h4>Anti-tumour necrosis factor α (TNFα) therapy effectively induces and maintains remission in Crohn's disease (CD). Up to 40% of patients, however, fail to respond to anti-TNFα.<h4>Objective</h4>To identify the mechanisms underlying the persistence of mucosal lesions in patients who fail to respond to anti-TNFα therapy.<h4>Design</h4>An observational study based on whole-genome transcriptional analysis was carried out using intestinal biopsy specimens from patients with CD recei ...[more]

PMID: 24700437

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Project description:The objective of this study was to identify pre-treatment colonic gene expression patterns in patients with inflammatory bowel disease (Ulcerative Colitis and colonic Crohn’s disease) that are predictive of a good versus poor response to treatment with the bioloic anti-TNFa. By identifying key pathways that are altered in responders versus non-responders we also aimed to propose novel targets for therapy. Pre-treatment colonic endoscopic biopsies were collected in RNAlater from 22 patients (14 CD and 8 UC) who were starting anti-TNFa therapy. 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 responders, partial responders or non-responders according to their endoscopic presentation 12 weeks after therapy. For UC patients the Mayo score was used: Responders Mayo= 0, Partial responders 1<= Mayo <3 and Non Responders Mayo >=3. For CD patients % reduction in the SES-CD score was used: Responders >=50% of SES-CD, Partial responders 50%<SES-CD<75%, Non responders SES-CD > 75%. 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 to calculate their variable Importance in Projection (VIP) score. To understand the biological significance and pathways represented in the DEGS, we also performed enrichment analysis using the DAVID Gene Functional Classification Tool (REF I,II). Finally, strongest indicators of response were predicted by Random Forest Area Under the Curve (AUC) analysis.

Dataset Information

Expression data from intestinal mucosa of patients with CD under anti-TNF-alpha therapy.

Publications

Identification of inflammatory mediators in patients with Crohn's disease unresponsive to anti-TNFα therapy.

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