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Identification of a Crohn's disease specific transcript with potential as a diagnostic marker.

ABSTRACT: BACKGROUND: A long time goal of the medical research community has been the identification of a reliable and valid marker for Crohn's disease. AIM: To identify differences in the genetic expression patterns of healthy and diseased tissues. METHOD: The RNA arbitrarily primed polymerase chain reaction (RAP-PCR) procedure was modified to improve its potential to identify clinical markers in heterogeneous RNA populations. RESULTS: With this procedure, a 1065 bp PCR product associated with the inflammation that occurs in Crohn's disease was identified, cloned and sequenced. Northern blot hybridisations showed that this novel sequence originates from a unique RNA species of 3.1 kb. Dot blot hybridisations clearly showed that this RNA species was specific to Crohn's disease. Moreover, its abundance seemed to correlate with the severity of inflammation. Finally, this RNA species was also detected in macroscopically normal areas from Crohn's disease specimens, suggesting that it appears either early during the disease or at least before severe manifestations. CONCLUSION: This finding of a 3.1 kb RNA species permits the discrimination of Crohn's disease manifestations. Although further clinical work is required, this transcript appears to have definite potential as a diagnostic marker.

SUBMITTER: Lafontaine DA

PROVIDER: S-EPMC1727157 | biostudies-other | 1998 Jun

REPOSITORIES: biostudies-other

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Project description:Crohn's disease (CD) has an increasing incidence and prevalence worldwide. The etiology of CD remains unclear and there is no gold standard for diagnosis. The dysregulated immune response and different infiltration status of immune cells are critical for CD pathogenesis; therefore, it is important to provide an overview of immune-cell alterations in CD and explore a novel method for auxiliary diagnosis. Here we analyzed microarray datasets from Gene Expression Omnibus (GEO), and an extended version of Cell-type Identification By Estimating Relative Subsets Of RNA Transcripts (CIBERSORTx) was utilized to estimate the fraction of 22 types of immune cells. Differentially expressed genes (DEGs) and a protein-protein interaction (PPI) network were identified, and we performed gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA) to identify differentially regulated pathways in CD. Least absolute shrinkage and selection operator (LASSO) regression was conducted to filter features, and a diagnostic nomogram based on logistic regression was built and validated in an independent validation cohort. In the derivation cohort, we found a proportion of 17 immune-cell types to be significantly altered between CD and healthy controls and a total of 150 DEGs were identified, which were mostly related to the immune response. Among the 15 hub genes based on the PPI network, C-X-C chemokine ligand 8 (CXCL8) and interleukin-1B (IL-1B) showed the highest degree of interaction. Additionally, GSEA and GSVA identified five significantly enriched pathways, among which the nucleotide-binding oligomerization domain (NOD)-like receptor signaling pathway was critical in the CD development. Furthermore, six variables comprising of CXCL8, IL-1B, M1 macrophages, regulatory T cells, CD8+ T cells, and plasma cells were identified by LASSO regression and incorporated into a logistic regression model. The nomogram displayed a good prediction, with a 0.915 area under the receiver operating curve (AUC) and a C-index of 0.915 [95% confidence interval (CI): 0.875-0.955]. Similar results were found in the validation cohort, with an AUC of 0.884 and a 0.884 C-index (95% CI: 0.843-0.924). These results provide novel in silico insight into cellular and molecular characteristics of CD and potential biomarkers for diagnosis and targeted therapy.

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Identification of a Crohn's disease specific transcript with potential as a diagnostic marker.

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