Identification of heterogeneity of immune cells in healthy colonic biopsies
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ABSTRACT:
PROVIDER: PRJNA638908 | ENA |
REPOSITORIES: ENA
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Project description:Background & Aims: Genome-wide gene expression (GWGE) profiles of mucosal colonic biopsies have suggested the existence of a continuous inflammatory state in quiescent ulcerative colitis (UC). The aim of this study was to use DNA microarray-based GWGE profiling of mucosal colonic biopsies and isolated colonocytes from UC patients and controls in order to identify the cell types responsible for the continuous inflammatory state. Methods: Adjacent mucosal colonic biopsies were obtained endoscopically from the descending colon in patients with active UC (n=8), quiescent UC (n=9), and with irritable bowel syndrome (controls, n=10). After isolation of colonocytes and subsequent extraction of total RNA, GWGE data were acquired using Human Genome U133 Plus 2.0 GeneChip Array (Affymetrix, Santa Clara, CA). Data analysis was carried out by principal component analysis and projection to latent structure-discriminant analysis using the SIMCA-P11 software (Umetrics, Umeå, Sweden). Results: A clear separation between active UC, quiescent UC and control biopsies were found, whereas the model for the colonocytes was unable to distinguish between quiescent UC and controls. The differentiation between quiescent UC and control biopsies was governed by unique profiles containing gene expressions with significant fold changes. These primarily belonged to the family of homeostatic chemokines revealing a plausible explanation to the abnormal regulated innate immune response seen in patients with UC. Conclusion: This study has demonstrated the presence of a continuous inflammatory state in quiescent UC, which seems to reflect an altered gene expression profile of lamina propria cells. Keywords: Colonocytes, continuous inflammation, mucosal colonic biopsies, gene expression profiles
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Project description:Background & Aims: Genome-wide gene expression (GWGE) profiles of mucosal colonic biopsies have suggested the existence of a continuous inflammatory state in quiescent ulcerative colitis (UC). The aim of this study was to use DNA microarray-based GWGE profiling of mucosal colonic biopsies and isolated colonocytes from UC patients and controls in order to identify the cell types responsible for the continuous inflammatory state. Methods: Adjacent mucosal colonic biopsies were obtained endoscopically from the descending colon in patients with active UC (n=8), quiescent UC (n=9), and with irritable bowel syndrome (controls, n=10). After isolation of colonocytes and subsequent extraction of total RNA, GWGE data were acquired using Human Genome U133 Plus 2.0 GeneChip Array (Affymetrix, Santa Clara, CA). Data analysis was carried out by principal component analysis and projection to latent structure-discriminant analysis using the SIMCA-P11 software (Umetrics, Umeå, Sweden). Results: A clear separation between active UC, quiescent UC and control biopsies were found, whereas the model for the colonocytes was unable to distinguish between quiescent UC and controls. The differentiation between quiescent UC and control biopsies was governed by unique profiles containing gene expressions with significant fold changes. These primarily belonged to the family of homeostatic chemokines revealing a plausible explanation to the abnormal regulated innate immune response seen in patients with UC. Conclusion: This study has demonstrated the presence of a continuous inflammatory state in quiescent UC, which seems to reflect an altered gene expression profile of lamina propria cells. Keywords: Colonocytes, continuous inflammation, mucosal colonic biopsies, gene expression profiles Adjacent mucosal colonic biopsies were attained endoscopically from the descending colon in patients with active UC (n=8), quiescent UC (n=9), and in controls (n=10). After extraction of total RNA, genome-wide gene expression data were acquired using Human Genome U133 Plus 2.0 GeneChip Array (Affymetrix, Santa Clara, CA). Amplification was required to obtain sufficient amounts of labelled complementary RNA (cRNA) target for analysis with arrays. Data analysis was carried out by principal component analysis and projection to latent structure-discriminant analysis using the SIMCA-P11 software (Umetrics, Umeå, Sweden).
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