Z Gastroenterol 2005; 43 - 29
DOI: 10.1055/s-2005-869676

Comparation of whole genomic expression pattern of ulcerative colitis and Crohn-colitis biopsy samples

O Galamb 1, F Sipos 1, B Győrffy 1, S Spisák 1, B Molnár 1, Z Tulassay 1
  • 1Semmelweis Egyetem II.sz. Belgyógyászati Klinika

Background: The biological interpretation of hundreds of down- and upregulated genes from the gene expression analyses' results was not worked out until present days.

Aims: our purpose was to find altered biological pathways in severely active ulcerative colitis and Crohn's disease samples compared to normal using Pathway Assist software.

Materials and Methods: Total RNA was extracted from frozen colonic biopsy specimens of 9 patients with ulcerative colitis (UC), 5 with Crohn's colitis (CD) and 8 healthy normal controls. The mRNA fraction from the extracted total RNA was amplified by T7 RNA amplification. Biotin-labelled cRNA probes were synthesized (Affymetrix Inc.) and fragmented. The genome-wide mRNA expression profile was evaluated by GeneChip U133 Plus 2.0 microarrays (Affymetrix Inc., US, over 47 000 transcripts and variants) and GeneChip Scanner 3000 (Affymetrix Inc., US). T-test, self-organizing map clustering were done by the Data Mining Tool software (Affymetrix Inc., US). Pathway analysis was done by the Pathway Assist 2.53 software.

Results: In severe ulcerative colitis 2 clusters of genes (765 and 695 genes) were found to be down-, and 2 clusters of genes (525 and 478 genes) were found to be upregulated compared to normal. In severe Crohn's colitis one upregulated gene cluster (261 genes) and one down-regulated gene cluster (193 genes) was found. Genes encoding proteins without unknown functions were removed from the pathway analysis. Upregulated UC genes were classified into 21 and 23, downregulated into 19 and 21, upregulated CD genes into 15, and downregulated into 12 different biological pathways. Selected pathways were graphically visualized.

Conclusions: Pathway analysis of whole genomic expression profiles is a useful method for biological interpretation of a large amount of data.