AUTHOR=Ye Chenglin , Zhu Sizhe , Gao Yuan , Huang Yabing 

TITLE=Landscape of sialylation patterns identify biomarkers for diagnosis and prediction of response to anti-TNF therapy in crohn’s disease

JOURNAL=Frontiers in Genetics

VOLUME=Volume 13 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2022.1065297

DOI=10.3389/fgene.2022.1065297

ISSN=1664-8021

ABSTRACT=Crohn’s disease (CD), a subtype of inflammatory bowel disease (IBD), causes chronic inflammation of the gastrointestinal tract. 30% of patients have no response to anti-tumor necrosis factor (TNF) therapy. Sialylation is involved in the pathogenesis of IBD. We aimed to explore potential biomarkers for diagnosis and predicting the outcome of anti-TNF medication in CD. Three potential biomarkers (SERPINB2, TFPI2, and SLC9B2) were screened by bioinformatics analysis and machine learning based on sialylation-related genes. Moreover, the combined model integrated SERPINB2, TFPI2, and SLC9B2 had excellent diagnostic values both in the training and validation cohorts. Importantly, a Sial-score was constructed based on the expression of SERPINB2, TFPI2, and SLC9B2. The Sial-low group had a lower level of immune infiltration than the Sial-high group. Whereas 94.4% of patients in the Sial-low group responded to anti-TNF therapy while only 15.8 % of patients in the Sial-high group had response. The Sial-score had an outstanding ability to predict and distinguish responders and non-responders. Our comprehensive analysis indicated that SERPINB2, TFPI2, and SLC9B2 play important roles in both pathogenesis and anti-TNF therapy resistance in CD. Furthermore, it might provide novel concepts for treating CD patients individually.