Integrative Analysis of Transcriptomic and Proteomic Profiling in Inflammatory Bowel Disease Colon Biopsies.

Integrative Analysis of Transcriptomic and Proteomic Profiling in Inflammatory Bowel Disease Colon Biopsies.

Inflamm Bowel Dis. 2019 Jun 07;:

Authors: Jin L, Li L, Hu C, Paez-Cortez J, Bi Y, Macoritto M, Cao S, Tian Y

Abstract
BACKGROUND: Crohn’s disease (CD) and ulcerative colitis (UC) are intestinal chronic inflammatory conditions characterized by altered epithelial barrier function and tissue damage. Despite significant efforts to understanding the biological mechanisms responsible for gut inflammation, the pathophysiology of CD and UC remains poorly understood.
METHODS: To help elucidate the potential mechanisms responsible for gut inflammation in CD and UC, transcriptomic and proteomic profiling of human colon biopsy specimens was performed. Dysregulated genes and proteins in disease tissues compared with normal tissues were characterized from the expression profiles and further subjected to pathway analysis to identify altered biological processes and signaling pathways.
RESULTS: Sample analysis showed 4250 genes with matched protein expression and a wide range of correlation of RNA-protein abundance across samples. Pathway analysis of dysregulated genes and proteins in CD and UC showed alterations in immune and inflammatory responses, complement cascade, and the suppression of metabolic processes and PPAR signaling. In CD, increased T-helper cell differentiation and elevated toll-like receptor and JAK/STAT signaling were observed. Interestingly, increased MAPK signaling was only observed in UC. Weighted gene co-expression network analysis suggested a possible role of epigenetic regulation in UC. Of note, a large discrepancy between regulation of RNA and protein levels in inflamed colon samples was detected for previously identified biomarkers including MMP14 and LAMP1.
CONCLUSIONS: With the analysis of dysregulated genes and pathways, the present study unravels key mechanisms contributing to CD and UC pathogenesis and emphasizes that integrative analysis of multi-omics data sets can provide more insight into understanding complex disease mechanisms.

PMID: 31173627 [PubMed – as supplied by publisher]

PubMed Link: https://www.ncbi.nlm.nih.gov/pubmed/31173627?dopt=Abstract