Development of Predictive Models for Long-Term Endoscopic Response to Ustekinumab in Crohn's Disease Based on Plasma Proteomics

基于血浆蛋白质组学的克罗恩病患者长期内镜下乌司奴单抗疗效预测模型的构建

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Abstract

PURPOSE: Ustekinumab (UST) is effective for Crohn's disease (CD), yet reliable biomarkers for predicting long-term response remain scarce. This study aimed to identify novel plasma proteomic biomarkers and develop predictive models for long-term endoscopic response to UST therapy in patients. METHODS: Baseline plasma inflammatory proteins were profiled using the Olink platform in 40 CD patients treated with UST (20 responders, 20 non-responders). Differentially expressed proteins (DEPs) were identified after adjusting for age, age at diagnosis, and SES-CD scores. Stable DEPs were selected via bootstrap resampling and further validated in an independent patient group from the same center (n=20) using ELISA. Predictive models were constructed using logistic regression, random forest, and support vector machine (SVM) algorithms. RESULTS: Non-responders had elevated baseline interleukin-8 (IL8) and CD6 levels and reduced thymic stromal lymphopoietin (TSLP) compared to responders. ELISA confirmed differential expression of IL8, CD6, and TSLP, with CD6 showing the best diagnostic accuracy (AUC=0.800). The logistic regression model combining these markers achieved an AUC of 0.828 (95% CI: 0.701-0.954), outperforming random forest (AUC=0.745) and SVM (AUC=0.775). CONCLUSION: Baseline plasma IL8, CD6, and TSLP are potential predictive biomarkers of long-term endoscopic response to UST in CD, providing a basis for personalized treatment strategies.

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