Background The treatment concept for inflammatory bowel disease (IBD) has been transformed with biologics now recommended as the first-line therapy for moderate-to-severe patients. However, the significant heterogeneity among IBD patients has limited the efficacy of selected biologics based on traditional clinical factors. Therefore, it is imperative to molecularly stratify patients to match them with the most appropriate biologics. In this study, we systematically reviewed baseline omics biomarkers that have the potential to predict response to biological therapies, aiming to facilitate precision medicine in IBD. Methods We conducted a comprehensive literature search using PubMed by which we included studies that explore the role of omics biomarkers in predicting the efficacy of various biologics including anti-TNFα, anti-integrin, anti-IL-12/23P40 and anti-IL-23 P19 in patients with IBD. Results Our review included 110 studies. Of these, 86 studies focused on anti-TNFα, 17 focused on anti-integrin and 7 focused on anti-IL-12/23P40 and/or anti-IL-23P19. These studies investigated multi-levels baseline biomarkers, including genomics, transcriptomics (bulk RNA and sc-RNA sequence), proteomics, microbiome, and metabolomics (derived from serum, urine, or stool). Furthermore, recent studies already focused on integrating multiple omics analysis and showed that the predictive model based on multi-omics data could significantly enhance their performance. Among the available biomarkers, mucosal transcription of OSM (AUROC = 0.83), IL-13RA2 (AUROC = 0.90), and TREM-1 transcription in mucosal biopsy (AUROC = 0.77) as well as in PBMC ( AUROC varies between 0.78 and 0.94) could accurately predict the response to anti-TNFα. The mucosal IL-23A transcription could discriminate responders from non-responders to anti-IL-12/23P40 with an AUROC of 0.90. OSM, biomarkers of intestinal collagen turnover like C4M, IL-17, IL-22, and TNFα in serum also showed significant potential in predicting the response to anti-TNFα, anti-integrin and anti-IL-12/23P40. In addition, single-cell molecular signatures with sc-RNA sequencing provided more profound insights into predicting the response to biologics. The lack of reproducibility in results across different groups may be due to the disparity in patient selection, methodology, and study designs among different investigations. Conclusion Numerous omics markers have shown great potential in predicting the efficacy of biologics. However, it is crucial to explore and validate these novel biomarkers in larger cohorts using harmonized protocols to facilitate their evaluation into actual clinical practice, especially for newer biologics like anti-IL-12/23P40 and anti-IL-23P19.

中文翻译：

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P915 用于预测炎症性肠病患者对生物制剂反应的多组学生物标志物

背景 炎症性肠病 (IBD) 的治疗理念已经改变，生物制剂现已被推荐为中重度患者的一线治疗。然而，IBD 患者之间的显着异质性限制了基于传统临床因素选择的生物制剂的疗效。因此，必须对患者进行分子分层，以便为他们匹配最合适的生物制剂。在这项研究中，我们系统地回顾了有潜力预测生物疗法反应的基线组学生物标志物，旨在促进 IBD 的精准医疗。方法 我们使用 PubMed 进行了全面的文献检索，其中纳入了探索组学生物标志物在预测各种生物制剂（包括抗 TNFα、抗整合素、抗 IL-12/23P40 和抗 IL-23）功效中的作用的研究。 IBD 患者的 P19。结果 我们的审查包括 110 项研究。其中，86 项研究重点关注抗 TNFα，17 项研究重点关注抗整合素，7 项研究重点关注抗 IL-12/23P40 和/或抗 IL-23P19。这些研究调查了多水平基线生物标志物，包括基因组学、转录组学（大量 RNA 和 sc-RNA 序列）、蛋白质组学、微生物组和代谢组学（源自血清、尿液或粪便）。此外，最近的研究已经集中在整合多组学分析上，并表明基于多组学数据的预测模型可以显着提高其性能。在可用的生物标志物中，粘膜活检中的 OSM (AUROC = 0.83)、IL-13RA2 (AUROC = 0.90) 和 TREM-1 转录 (AUROC = 0.77) 以及 PBMC 中的粘膜转录（AUROC 在 0.78 和 0.94 之间变化）可以准确预测抗 TNFα 的反应。粘膜 IL-23A 转录可以区分抗 IL-12/23P40 的应答者和非应答者，AUROC 为 0.90。OSM、血清中的肠道胶原蛋白更新的生物标志物（如 C4M、IL-17、IL-22 和 TNFα）在预测抗 TNFα、抗整合素和抗 IL-12/23P40 的反应方面也显示出显着的潜力。此外，单细胞分子特征与 sc-RNA 测序为预测生物制剂的反应提供了更深刻的见解。不同群体的结果缺乏可重复性可能是由于不同研究之间的患者选择、方法和研究设计的差异造成的。结论 许多组学标记物在预测生物制剂疗效方面显示出巨大潜力。然而，至关重要的是使用统一的方案在更大的队列中探索和验证这些新型生物标志物，以促进它们在实际临床实践中的评估，特别是对于抗 IL-12/23P40 和抗 IL-23P19 等新型生物制剂。