Digestive Endoscopy Department, Jiangsu Province Hospital, The First Affiliated Hospital with Nanjing Medical University, Nanjing, China.
Front Immunol. 2023 Jul 19;14:1162458. doi: 10.3389/fimmu.2023.1162458. eCollection 2023.
As yet, the genetic abnormalities involved in the exacerbation of Ulcerative colitis (UC) have not been adequately explored based on bioinformatic methods.
The gene microarray data and clinical information were downloaded from Gene Expression Omnibus (GEO) repository. The scale-free gene co-expression networks were constructed by R package "WGCNA". Gene enrichment analysis was performed Metascape database. Differential expression analysis was performed using "Limma" R package. The "randomForest" packages in R was used to construct the random forest model. Unsupervised clustering analysis performed by "ConsensusClusterPlus"R package was utilized to identify different subtypes of UC patients. Heat map was established using the R package "pheatmap". Diagnostic parameter capability was evaluated by ROC curve. The"XSum"packages in R was used to screen out small-molecule drugs for the exacerbation of UC based on cMap database. Molecular docking was performed with Schrodinger molecular docking software.
Via WGCNA, a total 77 high Mayo score-associated genes specific in UC were identified. Subsequently, the 9 gene signatures of the exacerbation of UC was screened out by random forest algorithm and Limma analysis, including BGN,CHST15,CYYR1,GPR137B,GPR4,ITGA5,LILRB1,SLFN11 and ST3GAL2. The ROC curve suggested good predictive performance of the signatures for exacerbation of UC in both the training set and the validation set. We generated a novel genotyping scheme based on the 9 signatures. The percentage of patients achieved remission after 4 weeks intravenous corticosteroids (CS-IV) treatment was higher in cluster C1 than that in cluster C2 (54% . 27%, Chi-square test, =0.02). Energy metabolism-associated signaling pathways were significantly up-regulated in cluster C1, including the oxidative phosphorylation, pentose and glucuronate interconversions and citrate cycle TCA cycle pathways. The cluster C2 had a significant higher level of CD4+ T cells. The"XSum"algorithm revealed that Exisulind has a therapeutic potential for UC. Exisulind showed a good binding affinity for GPR4, ST3GAL2 and LILRB1 protein with the docking glide scores of -7.400 kcal/mol, -7.191 kcal/mol and -6.721 kcal/mol, respectively.We also provided a comprehensive review of the environmental toxins and drug exposures that potentially impact the progression of UC.
Using WGCNA and random forest algorithm, we identified 9 gene signatures of the exacerbation of UC. A novel genotyping scheme was constructed to predict the severity of UC and screen UC patients suitable for CS-IV treatment. Subsequently, we identified a small molecule drug (Exisulind) with potential therapeutic effects for UC. Thus, our study provided new ideas and materials for the personalized clinical treatment plans for patients with UC.
基于生物信息学方法，尚未充分探讨溃疡性结肠炎（UC）恶化所涉及的遗传异常。
从基因表达综合数据库（GEO）下载基因微阵列数据和临床信息。使用 R 包“WGCNA”构建无标度基因共表达网络。使用 Metascape 数据库进行基因富集分析。使用“Limma”R 包进行差异表达分析。使用 R 中的“randomForest”包构建随机森林模型。使用“ConsensusClusterPlus”R 包进行无监督聚类分析，以识别不同类型的 UC 患者。使用 R 包“pheatmap”构建热图。使用 R 中的“XSum”包根据 cMap 数据库筛选出用于治疗 UC 恶化的小分子药物。使用 Schrödinger 分子对接软件进行分子对接。
通过 WGCNA，确定了 77 个与 UC 高 Mayo 评分相关的特定基因。随后，通过随机森林算法和 Limma 分析筛选出 9 个 UC 恶化的基因特征，包括 BGN、CHST15、CYYR1、GPR137B、GPR4、ITGA5、LILRB1、SLFN11 和 ST3GAL2。ROC 曲线表明，该特征对训练集和验证集 UC 恶化的预测性能良好。我们基于 9 个特征生成了一种新的基因分型方案。与聚类 C2 相比（54%[27%]，卡方检验，=0.02），在聚类 C1 中，接受 4 周静脉皮质类固醇（CS-IV）治疗后达到缓解的患者比例更高。能量代谢相关信号通路在聚类 C1 中显著上调，包括氧化磷酸化、戊糖和葡萄糖醛酸相互转化以及柠檬酸循环 TCA 循环途径。聚类 C2 中 CD4+T 细胞水平显著升高。“XSum”算法表明，Exisulind 对 UC 具有治疗潜力。Exisulind 与 GPR4、ST3GAL2 和 LILRB1 蛋白具有良好的结合亲和力，对接 Glide 评分分别为-7.400 kcal/mol、-7.191 kcal/mol 和-6.721 kcal/mol。我们还全面回顾了可能影响 UC 进展的环境毒素和药物暴露。
使用 WGCNA 和随机森林算法，我们确定了 9 个 UC 恶化的基因特征。构建了一种新的基因分型方案，以预测 UC 的严重程度并筛选适合 CS-IV 治疗的 UC 患者。随后，我们发现了一种具有治疗 UC 潜力的小分子药物（Exisulind）。因此，我们的研究为 UC 患者的个性化临床治疗方案提供了新的思路和材料。
