Matrix metalloproteinases in intestinal fibrosis

Fibrosis-related transcriptome unveils a distinctive remodeling matrix pattern in penetrating ileal Crohn's disease

BACKGROUND AND AIMS

Stricturing (B2) and penetrating (B3) ileal Crohn's disease have been reported to present similar levels of histopathological transmural fibrosis. This study aimed to compare the fibrosis-related transcriptomic profiles of penetrating and stricturing ileal Crohn's disease.

METHODS

Using Nanostring technology and comparative bioinformatics, we analyzed the expression of 787 fibrosis-related genes in 36 ileal surgical specimens, 12 B2 and 24 B3, the latter including 12 cases with associated stricture(s) (B3s) and 12 without (B3o). Quality control of extracted RNA was performed according to Nanostring parameters and principal component analysis for the distribution analysis. For the selection of the differentially expressed genes a p-adjusted <0.05 and Fold Change ≤-1.5 or ≥ 1.5 was adopted. qPCR and immunohistochemistry analyses were used to validate selected differentially expressed genes.

RESULTS

We included 34 patients with B2 and B3 phenotypes, balanced for age at diagnosis, age at surgery, gender, Crohn's disease localization, perianal disease and therapy. Inflammation and fibrosis histopathological scoring were similar in all cases. B2 and B3 groups showed a very good clustering regarding 30 significantly differentially expressed genes, all being remarkably upregulated in B3. More than half of these genes were involved in Crohn's disease fibrogenesis, while eight differentially expressed genes were so in other organs. The most significantly active biologic processes and pathways in penetrating disease were response to TGFβand matrix organization and degradation, as validated by immunohistochemistry.

CONCLUSIONS

Despite the histopathological similarities in fibrosis between stricturing and penetrating ileal Crohn's disease, their fibrosis-related transcriptomic profiles are distinct. Penetrating disease exhibits a distinctive transcriptomic landscape related to enhanced matrix remodeling.

An assessment system for clinical and biological interpretability in ulcerative colitis

Ulcerative colitis (UC) is a serious inflammatory bowel disease (IBD) with high morbidity and mortality worldwide. As the traditional diagnostic techniques have various limitations in the practice and diagnosis of early ulcerative colitis, it is necessary to develop new diagnostic models from molecular biology to supplement the existing methods. In this study, we developed a machine learning-based synthesis to construct an artificial intelligence diagnostic model for ulcerative colitis, and the correctness of the model is verified using an external independent dataset. According to the significantly expressed genes related to the occurrence of UC in the model, an unsupervised quantitative ulcerative colitis related score (UCRScore) based on principal coordinate analysis was established. The UCRScore is not only highly generalizable across UC bulk cohorts at different stages, but also highly generalizable across single-cell datasets, with the same effect in terms of cell numbers, activation pathways and mechanisms. As an important role of screening genes in disease occurrence, based on connectivity map analysis, 5 potential targeting molecular compounds were identified, which can be used as an additional supplement to the therapeutic of UC. Overall, this study provides a potential tool for differential diagnosis and assessment of bio-pathological changes in UC at the macroscopic level, providing an opportunity to optimize the diagnosis and treatment of UC.