Su Qin , Jing Zhang , Meifang Cao , Tao Jiang , Baohong Jiang
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Five hub genes (HSPA5, RAB10, RAB1A, RAF1, SMAD4) identified by machine learning may serve as diagnostic candidates for AAA patients through nomogram and ROC evaluation. Gene set enrichment analysis (GSEA) and immune infiltration analysis were performed further to understand the function of these candidate genes and explore the effect of immunity in AAA, respectively. By establishing an AAA animal model, it was found that the iliac lymph nodes around the abdominal aorta were significantly enlarged, and the number and lumen size of lymphatic vessels in the vessel wall were both significantly increased during the progression of AAA. Additionally, AAA was significantly promoted by ligating lymphatic vessels, which caused lymphatic drainage obstruction around the abdominal aorta. Our findings have the potential to enhance knowledge about the development and diagnosis of AAA.</div></div>","PeriodicalId":49799,"journal":{"name":"Molecular and Cellular Probes","volume":"85 ","pages":"Article 102054"},"PeriodicalIF":3.0000,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Identification of lymphangiogenesis-related diagnostic model for predicting abdominal aortic aneurysm onset and progression and validation of lymphopoiesis in abdominal aortic aneurysm\",\"authors\":\"Su Qin , Jing Zhang , Meifang Cao , Tao Jiang , Baohong Jiang\",\"doi\":\"10.1016/j.mcp.2025.102054\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>This study aims to explore the lymphangiogenesis (LG)-related diagnostic markers of abdominal aortic aneurysm (AAA) through bioinformatics, as well as the alteration of the regional lymphatic system during the progression of AAA and the influence of lymphatic drainage obstruction on AAA progression. 2957 differentially expressed genes (DEGs) were identified between the AAA patient group and the healthy donor group in Gene Expression Omnibus microarray datasets. Subsequently, the DEGs and the LG gene were intersected, and 93 genes were obtained. Weighted gene co-expression network analysis (WGCNA) was performed to obtain module genes. Module genes intersected with the above 93 genes, and 26 genes were obtained. Five hub genes (HSPA5, RAB10, RAB1A, RAF1, SMAD4) identified by machine learning may serve as diagnostic candidates for AAA patients through nomogram and ROC evaluation. Gene set enrichment analysis (GSEA) and immune infiltration analysis were performed further to understand the function of these candidate genes and explore the effect of immunity in AAA, respectively. By establishing an AAA animal model, it was found that the iliac lymph nodes around the abdominal aorta were significantly enlarged, and the number and lumen size of lymphatic vessels in the vessel wall were both significantly increased during the progression of AAA. 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引用次数: 0
摘要
本研究旨在通过生物信息学的方法探讨腹主动脉瘤(AAA)的淋巴管生成(LG)相关诊断指标,以及AAA进展过程中局部淋巴系统的改变及淋巴引流阻塞对AAA进展的影响。在基因表达集成芯片(Gene Expression Omnibus microarray)数据集中,鉴定出AAA患者组与健康供者组之间存在2957个差异表达基因。随后,将DEGs与LG基因进行交叉,得到93个基因。采用加权基因共表达网络分析(WGCNA)获得模块基因。模块基因与上述93个基因相交,得到26个基因。通过机器学习识别的5个中心基因(HSPA5、RAB10、RAB1A、RAF1、SMAD4)可通过nomogram和ROC评价作为AAA患者的候选诊断基因。进一步进行基因集富集分析(GSEA)和免疫浸润分析,分别了解这些候选基因的功能,探讨免疫在AAA中的作用。通过建立AAA动物模型发现,在AAA的进展过程中,腹主动脉周围的髂淋巴结明显增大,血管壁淋巴管数量和管腔大小均明显增加,结扎淋巴管可明显促进AAA,造成腹主动脉周围淋巴管引流阻塞。我们的发现有可能提高对AAA的发展和诊断的认识。
Identification of lymphangiogenesis-related diagnostic model for predicting abdominal aortic aneurysm onset and progression and validation of lymphopoiesis in abdominal aortic aneurysm
This study aims to explore the lymphangiogenesis (LG)-related diagnostic markers of abdominal aortic aneurysm (AAA) through bioinformatics, as well as the alteration of the regional lymphatic system during the progression of AAA and the influence of lymphatic drainage obstruction on AAA progression. 2957 differentially expressed genes (DEGs) were identified between the AAA patient group and the healthy donor group in Gene Expression Omnibus microarray datasets. Subsequently, the DEGs and the LG gene were intersected, and 93 genes were obtained. Weighted gene co-expression network analysis (WGCNA) was performed to obtain module genes. Module genes intersected with the above 93 genes, and 26 genes were obtained. Five hub genes (HSPA5, RAB10, RAB1A, RAF1, SMAD4) identified by machine learning may serve as diagnostic candidates for AAA patients through nomogram and ROC evaluation. Gene set enrichment analysis (GSEA) and immune infiltration analysis were performed further to understand the function of these candidate genes and explore the effect of immunity in AAA, respectively. By establishing an AAA animal model, it was found that the iliac lymph nodes around the abdominal aorta were significantly enlarged, and the number and lumen size of lymphatic vessels in the vessel wall were both significantly increased during the progression of AAA. Additionally, AAA was significantly promoted by ligating lymphatic vessels, which caused lymphatic drainage obstruction around the abdominal aorta. Our findings have the potential to enhance knowledge about the development and diagnosis of AAA.
期刊介绍:
MCP - Advancing biology through–omics and bioinformatic technologies wants to capture outcomes from the current revolution in molecular technologies and sciences. The journal has broadened its scope and embraces any high quality research papers, reviews and opinions in areas including, but not limited to, molecular biology, cell biology, biochemistry, immunology, physiology, epidemiology, ecology, virology, microbiology, parasitology, genetics, evolutionary biology, genomics (including metagenomics), bioinformatics, proteomics, metabolomics, glycomics, and lipidomics. Submissions with a technology-driven focus on understanding normal biological or disease processes as well as conceptual advances and paradigm shifts are particularly encouraged. The Editors welcome fundamental or applied research areas; pre-submission enquiries about advanced draft manuscripts are welcomed. Top quality research and manuscripts will be fast-tracked.