Ying-Lei Miao1, Yu-Liang Xiao, Yan Du, Li-Ping Duan. 1. Department of Gastroenterology, The First Affiliated Hospital of Kunming Medical University, Kunming 650032, Yunan Province, China. myldu@sina.com
Abstract
AIM: To identify peripheral blood mononuclear cell (PBMC) gene expression profiles of ulcerative colitis (UC) patients, using oligonucleotide microarrays, to gain insights into UC molecular mechanisms. METHODS: The Human OneArray microarrays were used for a complete genome-wide transcript profiling of PBMCs from 12 UC patients and 6 controls. Differential analysis per gene was performed with a random variance model; t test and P values were adjusted to control the false discovery rate (5%). Gene ontology (GO) was deployed to analyze differentially expressed genes at significant levels between patients and controls to identify the biological processes involved in UC. RESULTS: Comparative analysis revealed that 4438 probes (4188 genes) were differentially expressed between the two groups, of which 3689 probes (3590 genes) were down-regulated whereas 749 probes (598 genes) were up-regulated. Many disregulated genes in our data have been reported by previous microarray studies carried out on intestinal mucosa samples, such as S100A8, CEACAM1 and S100A9. GO enrichment analysis revealed 67 high enrichment up-regulated categories and one significant down-regulated category. The up-regulated genes were mainly involved in immune and inflammatory response, cell cycle and proliferation, DNA metabolism and repair. CONCLUSION: Gene expression profiling of PBMCs from patients with UC has highlighted several novel gene categories that could contribute to the pathogenesis of UC.
AIM: To identify peripheral blood mononuclear cell (PBMC) gene expression profiles of ulcerative colitis (UC) patients, using oligonucleotide microarrays, to gain insights into UC molecular mechanisms. METHODS: The Human OneArray microarrays were used for a complete genome-wide transcript profiling of PBMCs from 12 UC patients and 6 controls. Differential analysis per gene was performed with a random variance model; t test and P values were adjusted to control the false discovery rate (5%). Gene ontology (GO) was deployed to analyze differentially expressed genes at significant levels between patients and controls to identify the biological processes involved in UC. RESULTS: Comparative analysis revealed that 4438 probes (4188 genes) were differentially expressed between the two groups, of which 3689 probes (3590 genes) were down-regulated whereas 749 probes (598 genes) were up-regulated. Many disregulated genes in our data have been reported by previous microarray studies carried out on intestinal mucosa samples, such as S100A8, CEACAM1 and S100A9. GO enrichment analysis revealed 67 high enrichment up-regulated categories and one significant down-regulated category. The up-regulated genes were mainly involved in immune and inflammatory response, cell cycle and proliferation, DNA metabolism and repair. CONCLUSION: Gene expression profiling of PBMCs from patients with UC has highlighted several novel gene categories that could contribute to the pathogenesis of UC.
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