Shanxi Key Laboratory of Big Data for Clinical Decision, Shanxi Medical University, Taiyuan, China.
Ministry of Education, Key Laboratory of Cellular Physiology at Shanxi Medical University, Taiyuan, China.
J Crohns Colitis. 2023 Jun 16;17(6):909-918. doi: 10.1093/ecco-jcc/jjad011.
Ulcerative colitis [UC] is a complex heterogeneous disease. This study aims to reveal the underlying molecular features of UC using genome-scale transcriptomes of patients with UC, and to develop and validate a novel stratification scheme.
A normalised compendium was created using colon tissue samples (455 patients with UC and 147 healthy controls [HCs]), covering genes from 10 microarray datasets. Upregulated differentially expressed genes [DEGs] were subjected to functional network analysis, wherein samples were grouped using unsupervised clustering. Additionally, the robustness of subclustering was further assessed by two RNA sequencing datasets [100 patients with UC and 16 HCs]. Finally, the Xgboost classifier was applied to the independent datasets to evaluate the efficacy of different biologics in patients with UC.
Based on 267 upregulated DEGs of the transcript profiles, UC patients were classified into three subtypes [subtypes A-C] with distinct molecular and cellular signatures. Epithelial activation-related pathways were significantly enriched in subtype A [named epithelial proliferation], whereas subtype C was characterised as the immune activation subtype with prominent immune cells and proinflammatory signatures. Subtype B [named mixed] was modestly activated in all the signalling pathways. Notably, subtype A showed a stronger association with the superior response of biologics such as golimumab, infliximab, vedolizumab, and ustekinumab compared with subtype C.
We conducted a deep stratification of mucosal tissue using the most comprehensive microarray and RNA sequencing data, providing critical insights into pathophysiological features of UC, which could serve as a template for stratified treatment approaches.
溃疡性结肠炎[UC]是一种复杂的异质性疾病。本研究旨在通过 UC 患者的全基因组转录组揭示其潜在的分子特征，并开发和验证一种新的分层方案。
使用结肠组织样本（455 例 UC 患者和 147 例健康对照[HC]）创建标准化汇编，涵盖 10 个微阵列数据集的基因。对上调的差异表达基因[DEGs]进行功能网络分析，其中使用无监督聚类对样本进行分组。此外，通过两个 RNA 测序数据集[100 例 UC 患者和 16 例 HC]进一步评估子聚类的稳健性。最后，将 Xgboost 分类器应用于独立数据集，以评估不同生物制剂在 UC 患者中的疗效。
基于转录谱中 267 个上调的 DEG，UC 患者被分为具有不同分子和细胞特征的三个亚型[A-C 型]。上皮激活相关途径在亚型 A[命名为上皮增殖]中显著富集，而亚型 C 则表现为具有明显免疫细胞和促炎特征的免疫激活亚型。亚型 B[命名为混合]在所有信号通路中均有适度激活。值得注意的是，与亚型 C 相比，亚型 A 与生物制剂如戈利木单抗、英夫利昔单抗、vedolizumab 和 ustekinumab 的优越反应具有更强的相关性。
我们使用最全面的微阵列和 RNA 测序数据对黏膜组织进行了深入分层，为 UC 的病理生理特征提供了重要见解，这可以作为分层治疗方法的模板。
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