背景:成人腹股沟疝是外科手术中常见且常见的疾病,容易发生在老年人或腹壁虚弱的人。尽管流行,腹股沟疝形成的分子机制尚不清楚。
目的:本研究旨在确定腹股沟疝的潜在基因标志物和可用药物。
方法:使用Pubmed2Ensembl文本挖掘来识别与“腹股沟疝”关键词相关的基因。GeneCodis系统用于指定在京都基因和基因组百科全书(KEGG)中定义的GO生物学过程术语和KEGG途径。STRING工具用于构建蛋白质-蛋白质相互作用网络,然后用Cytoscape可视化。利用CytoHubba和分子复合物检测来分析模块(MCODE)。使用DAVID平台数据库进行基因模块的GO和KEGG分析。集线器基因是那些集中在突出模块中的基因。药物基因相互作用数据库还用于根据hub基因之间的相互作用来鉴定腹股沟疝患者的潜在药物。最后,一项孟德尔随机化研究是基于全基因组关联研究进行的,目的是确定hub基因是否导致腹股沟疝.
结果:使用文本挖掘技术对与腹股沟疝相关的96个基因进行了鉴定。它是使用具有80个节点和476条边的PPI网络构建的,使用CytoHubba对基因进行测序。MCODE分析鉴定了三个基因模块。三个模块包含37个基因,这些基因聚集为与腹股沟疝患者相关的枢纽候选基因。PI3K-Akt,MAPK,年龄-愤怒,和HIF-1通路被发现在信号通路中富集。发现37个基因中有16个可被30种现有药物靶向。使用孟德尔随机化检查了枢纽基因与腹股沟疝之间的关系。研究揭示了可能与腹股沟疝有关的9个基因,比如POMC,CD40LG,TFRC,VWF,LOX,IGF2,BRCA1,TNF,和血浆中的HGF。通过方差倒数加权,ALB与腹股沟疝的风险增加相关,OR为1.203(OR[95%]=1,04[1.012至1.089],p=0.008)。
结论:我们确定了腹股沟疝的潜在枢纽基因,预测腹股沟疝的潜在药物,并通过孟德尔随机化反向验证潜在基因。这可能为无症状的预诊断方法提供进一步的见解,并有助于研究了解与腹股沟疝相关的风险基因的分子机制。
BACKGROUND: Inguinal hernia in adults is a common and frequent disease in surgery, prone to occur in the elderly or in those with a weak abdominal wall. Despite its prevalence, Molecular mechanisms underlying inguinal hernia formation are unclear.
OBJECTIVE: This study aims to identify potential gene markers for inguinal hernia and available drugs.
METHODS: Pubmed2Ensembl text mining was used to identify genes related to \"inguinal hernia\" keywords. The GeneCodis system was used to specify GO biological process terms and KEGG pathways defined in the Kyoto Encyclopedia of Genes and Genomes (KEGG). The STRING tool was used to construct protein-protein interaction networks, which were then visualized using Cytoscape.CytoHubba and Molecular Complex Detection were utilized to analyze the module (MCODE). A GO and KEGG analysis of gene modules was conducted using the DAVID platform database. Hub genes are those that are concentrated in prominent modules. The druggene interaction database was also used to identify potential drugs for inguinal hernia patients based on their interactions between the hub genes. Finally, a Mendelian randomization study was conducted based on genome-wide association studies to determine whether hub genes cause inguinal hernias.
RESULTS: The identification of 96 genes associated with inguinal hernia was carried out using text mining techniques. It was constructed using PPI networks with 80 nodes and 476 edges, and the sequence of the genes was performed using CytoHubba. MCODE analysis identified three gene modules. Three modules contain 37 genes clustered as hub candidate genes associated with inguinal hernia patients. The PI3K-Akt, MAPK, AGE-RAGE, and HIF-1 pathways were found to be enriched in signaling pathways. Sixteen of the 37 genes were found to be targetable by 30 existing drugs. The relationship between hub genes and inguinal hernia was examined using Mendelian randomization. The research revealed nine genes that may be connected with inguinal hernia, such as POMC, CD40LG, TFRC, VWF, LOX, IGF2, BRCA1, TNF, and HGF in the plasma. By inverse variance weighting, ALB was associated with an increased risk of inguinal hernia with an OR of 1.203 (OR [95%] = 1,04 [1.012 to 1.089], p = 0.008).
CONCLUSIONS: We identified potential hub genes for inguinal hernia, predicted potential drugs for inguinal hernia, and reverse-validated potential genes by Mendelian randomization. This may provide further insights into asymptomatic pre-diagnostic methods and contribute to studies to understand the molecular mechanisms of risk genes associated with inguinal hernia.