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使用加权基因共表达网络分析(WGCNA)和两样本孟德尔随机化研究对克罗恩病生物标志物和免疫疗法进行验证

Validation of Biomarkers and Immunotherapy With Crohn's Disease Using WGCNA and Two-Sample Mendelian Randomization Study.

作者信息

Hu Cong, Nong Shuxiong, Liu Chenang, Chen Yongfeng, Liao Chilin, Wu Meng

机构信息

Department of Ultrasound, Zhongnan Hospital of Wuhan University, Wuhan, Hubei, China.

Department of Cardiology, Baise People's Hospital, Affiliated Southwest Hospital of Youjiang Medical University for Nationalities, Baise, Guangxi, China.

出版信息

Gastroenterol Res Pract. 2025 Jul 1;2025:8194480. doi: 10.1155/grp/8194480. eCollection 2025.


DOI:10.1155/grp/8194480
PMID:40630894
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12237559/
Abstract

Crohn's disease (CD) is a chronic systemic inflammatory disease that mainly affects the intestine, accompanied by extraintestinal symptoms and immune problems. The progression of the disease may cause permanent damage to the structure and function of the intestine. Due to unclear early symptoms and lack of precise detection methods, early diagnosis of CD is difficult. Many patients were diagnosis at late stage, which may lead to delayed treatment and increased risk of complications. Identifying hub genes related to CD and using them to predict CD is of great significance. DEG and WGCNA were employed to identify key genes associated with CD and to detect modules significantly linked to the disease. GO and KEGG analyses were conducted to explore the functions of these identified genes. Additionally, MR method was utilized to assess the causal relationships between the most significant gene and CD. WCGNA identified 3240 differentially expressed genes, with the magenta module being the most significant among the nine clustered modules. The enrichment of GO and KEGG pathways indicates that the hub genes in the magenta module are related to the positive regulation of heme binding, tetrapyrrole binding, carboxylic acid binding, organic acid binding, IL-17 signaling pathway, and amoebiasis pathway. The Top 5 hub genes are CXCL1, LCN2, NOS2, S100A8, and DUOX2. Mendelian randomization analysis found a significant correlation between CXCL1 and CD. The study screened five potential biomarker genes in CD patients using a bioinformatics approach and Mendelian randomization study. Our results provided insights into CXCL1, LCN2, NOS2, S100A8, and DUOX2 in CD and suggested that CXCL1 may potentially be the optimal biomarker that could be a relatively easy path to clinical translation.

摘要

克罗恩病(CD)是一种慢性全身性炎症性疾病,主要影响肠道,并伴有肠外症状和免疫问题。疾病进展可能导致肠道结构和功能的永久性损害。由于早期症状不明确且缺乏精确的检测方法,CD的早期诊断较为困难。许多患者在疾病晚期才被诊断出来,这可能导致治疗延迟和并发症风险增加。识别与CD相关的枢纽基因并将其用于预测CD具有重要意义。本研究采用差异表达基因(DEG)和加权基因共表达网络分析(WGCNA)来识别与CD相关的关键基因,并检测与该疾病显著相关的模块。通过基因本体论(GO)和京都基因与基因组百科全书(KEGG)分析来探索这些已识别基因的功能。此外,采用孟德尔随机化(MR)方法评估最显著基因与CD之间的因果关系。WCGNA识别出3240个差异表达基因,在九个聚类模块中,品红色模块最为显著。GO和KEGG通路的富集表明,品红色模块中的枢纽基因与血红素结合、四吡咯结合、羧酸结合、有机酸结合、白细胞介素-17信号通路和阿米巴病通路的正调控有关。排名前5的枢纽基因是CXCL1、LCN2、NOS2、S100A8和DUOX2。孟德尔随机化分析发现CXCL1与CD之间存在显著相关性。本研究使用生物信息学方法和孟德尔随机化研究筛选出了CD患者的五个潜在生物标志物基因。我们的研究结果为CXCL1、LCN2、NOS2、S100A8和DUOX2在CD中的作用提供了见解,并表明CXCL1可能是最佳的生物标志物,有望为临床转化提供一条相对便捷的途径。

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本文引用的文献

[1]
Altered inflammatory mucosal signatures within their spatial and cellular context during active ileal Crohn's disease.

JCI Insight. 2025-3-10

[2]
Single-cell integration reveals metaplasia in inflammatory gut diseases.

Nature. 2024-11

[3]
Identification of key genes associated with acute myocardial infarction using WGCNA and two-sample mendelian randomization study.

PLoS One. 2024

[4]
Mitochondrial perturbation in the intestine causes microbiota-dependent injury and gene signatures discriminative of inflammatory disease.

Cell Host Microbe. 2024-8-14

[5]
Author Correction: Macrophage and neutrophil heterogeneity at single-cell spatial resolution in human inflammatory bowel disease.

Nat Commun. 2024-1-29

[6]
Transcriptome analysis identifies genetic risk markers and explores the pathogenesis for inflammatory bowel disease.

Biochim Biophys Acta Mol Basis Dis. 2024-3

[7]
Multi-omic insight into the molecular networks of mitochondrial dysfunction in the pathogenesis of inflammatory bowel disease.

EBioMedicine. 2024-1

[8]
Identifying immune cell infiltration and effective diagnostic biomarkers in Crohn's disease by bioinformatics analysis.

Front Immunol. 2023

[9]
Predicting diagnostic biomarkers associated with immune infiltration in Crohn's disease based on machine learning and bioinformatics.

Eur J Med Res. 2023-7-26

[10]
Exploration of the shared gene signatures and molecular mechanisms between periodontitis and inflammatory bowel disease: evidence from transcriptome data.

Gastroenterol Rep (Oxf). 2023-7-14

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