Abstract Background Crohn’s disease (CD) is frequently complicated by intestinal strictures, necessitating early recognition and management. This study aims to identify biomarkers associated with CD-related strictures using serum and intestinal proteomics and to develop diagnostic and predictive models for potential clinical application. Methods Serum samples from treatment-naïve CD patients and paired intestinal samples from stricturing intestine were subjected to proteomic analysis. Machine learning approaches were employed to select stricture-related biomarkers and develop models. Screened proteins were validated using external cohorts and molecular experiments. Results The Discovery Cohort included 62 patients for analysis. A diagnostic model for intestinal stricture was developed based on the serum levels of three proteins (GPC6, PRKCSH, and AOC1), achieving an area under the curve (AUC) of 0.836. A predictive model was developed using the levels of six proteins (GPC6, ATP6V1D, IGHV3-43, IMUP, SAR1B, and SF3A2), with an AUC of 0.886. Serum ELISA results from the FAH-SYSU and SRRSH cohorts (n = 62) demonstrated elevated GPC6 levels in the stricturing (B2) group, with a similar trend observed in intestinal expression in the progression group of the RISK cohort (n = 237). Single-cell transcriptomic analysis and immunofluorescence staining confirmed higher GPC6 gene expression and protein level in fibrostenotic mucosa/submucosa, particularly in fibroblasts. Conclusion This study has developed diagnostic and predictive models for intestinal strictures, which may aid clinical decision-making. GPC6 showed potential as a biomarker and could potentially contribute to the development of anti-fibrotic therapies. References: 1. Haberman Y, Minar P, Karns R, et al. Mucosal Inflammatory and Wound Healing Gene Programs Reveal Targets for Stricturing Behavior in Pediatric Crohn’s Disease. Journal of Crohn’s 15(2):273-286. doi:10.1093/ecco-jcc/jjaa166 2. Ungaro RC, Hu L, Ji J, et al. Machine learning identifies novel blood protein predictors of penetrating and stricturing complications in newly diagnosed paediatric Crohn’s disease. Aliment Pharm Ther. 2021;53(2):281-290. doi:10.1111/apt.16136 3. Shi W, Kaneiwa T, Cydzik M, Gariepy J, Filmus J. Glypican-6 stimulates intestinal elongation by simultaneously regulating Hedgehog and non-canonical Wnt signaling. Matrix Biology: Journal of the International Society for Matrix Biology. 2020;88:19-32. doi:10.1016/j.matbio.2019.11.002 4. Capurro M, Wanless IR, Sherman M, et al. Glypican-3: a novel serum and histochemical marker for hepatocellular carcinoma. Gastroenterology. 2003;125(1):89-97. doi:10.1016/s0016-5085(03)00689-9 Conflict of interest: Liu, Zishan: No conflict of interest Wu, Xiaomin: No conflict of interest Huang, Weidong: No conflict of interest Zhang, Yao: No conflict of interest Cao, Qian: No conflict of interest Haberman, Yael: No conflict of interest Chen, Minhu: No conflict of interest Feng, Rui: No conflict of interest Wang, Guibin: No conflict of interest Hu, Shixian: No conflict of interest Mao, Ren: None
Liu et al. (Thu,) studied this question.