Prediction and Bioinformatics Analysis of Key Genes in Placental Implantation Immunity

目的:通过生物信息学方法预测胎盘植入疾病的关键免疫基因。方法:本研究在GEO数据库中选出数据集GSE189267,采用R语言软件(“limma”R包)对各组表达基因进行差异分析,筛选出有差异意义的差异表达基因(DEGs),随后通过基因本体论(GO)、京都基因与基因组百科全书(KEGG)分析、加权基因表达网络分析(WGCNA)、蛋白质相互作用网络分析及基因集富集分析(GSEA)等生物信息学分析方法确定与胎盘植入性疾病显著相关的免疫基因。结果:共筛选出93个与胎盘植入性疾病高度相关的差异表达基因,通过WGCNA进一步鉴定出与穿透性胎盘植入显著相关的17个免疫相关基因。其中,瘦素(LEP)、绒毛膜生长激素1 (CSH1)、绒毛膜生长激素2 (CSH2)为前三个枢纽基因。对其分别进行单基因GSEA分析显示,LEP可能参与膜裂解、多泡体组织和核膜的重组,而CSH1和CSH2则参与了相似的生物过程,包括调节RAC蛋白信号转导和SRP依赖的共转译蛋白质膜定位。结论:本研究通过生物信息学方法提示LEP、CSH1和CSH2是穿透性胎盘植入的关键免疫基因,可能通过膜裂解、多泡体组织和核膜的重组、调节RAC蛋白信号转导和SRP依赖的共转译蛋白质膜定位等机制参与穿透性胎盘植入的发生,有助于更深入地理解穿透性胎盘植入,并为该疾病的潜在诊断和治疗靶点提供了进一步的见解。Objective: To predict key immune-related genes in placental implantation disorders using bioinformatics methods. Methods: In this study, the dataset GSE189267 was selected from the GEO database. Differential expression analysis of genes in each group was performed using R software (“limma” R package) to identify differentially expressed genes (DEGs) with statistical significance. Subsequently, bioinformatics analysis methods, including Gene Ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, weighted gene co-expression network analysis (WGCNA), protein-protein interaction network analysis, and gene set enrichment analysis (GSEA), were employed to determine immune-related genes significantly associated with placental implantation disorders. Results: A total of 93 DEGs highly associated with placental implantation disorders were identified. Further analysis using WGCNA revealed 17 immune-related genes significantly associated with placenta percreta. Among them, leptin (LEP), chorionic somatomammotropin 1 (CSH1), and chorionic somatomammotropin 2 (CSH2) were identified as the top three hub genes. Single-gene GSEA analysis showed that LEP may be involved in membrane fission, multivesicular body organization, and nuclear membrane reorganization, while CSH1 and CSH2 were involved in similar biological processes, including regulation of RAC protein signal transduction and SRP-dependent cotranslational protein membrane targeting. Conclusion: This study suggests that LEP, CSH1, and CSH2 are key immune-related genes in placenta percreta. They may participate in the development of placenta percreta through mechanisms such as membrane fission, multivesicular body organization, nuclear membrane reorganization, regulation of RAC protein signal transduction, and SRP-dependent cotranslational protein membrane targeting. These findings help to deepen the understanding of placenta percreta and provide further insights into potential diagnostic and therapeutic targets for this disorder.

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Publication Details

Journal
Journal of Clinical Personalized Medicine
Published
2025-01-01
DOI
https://doi.org/10.12677/jcpm.2025.42258
Primary Topic
Reproductive System and Pregnancy
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article
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article

Prediction and Bioinformatics Analysis of Key Genes in Placental Implantation Immunity

铧丹 张
Journal of Clinical Personalized Medicine
Reproductive System and Pregnancy
article

Prediction and Bioinformatics Analysis of Key Genes in Placental Implantation Immunity

铧丹 张
article en

Abstract

目的:通过生物信息学方法预测胎盘植入疾病的关键免疫基因。方法:本研究在GEO数据库中选出数据集GSE189267,采用R语言软件(“limma”R包)对各组表达基因进行差异分析,筛选出有差异意义的差异表达基因(DEGs),随后通过基因本体论(GO)、京都基因与基因组百科全书(KEGG)分析、加权基因表达网络分析(WGCNA)、蛋白质相互作用网络分析及基因集富集分析(GSEA)等生物信息学分析方法确定与胎盘植入性疾病显著相关的免疫基因。结果:共筛选出93个与胎盘植入性疾病高度相关的差异表达基因,通过WGCNA进一步鉴定出与穿透性胎盘植入显著相关的17个免疫相关基因。其中,瘦素(LEP)、绒毛膜生长激素1 (CSH1)、绒毛膜生长激素2 (CSH2)为前三个枢纽基因。对其分别进行单基因GSEA分析显示,LEP可能参与膜裂解、多泡体组织和核膜的重组,而CSH1和CSH2则参与了相似的生物过程,包括调节RAC蛋白信号转导和SRP依赖的共转译蛋白质膜定位。结论:本研究通过生物信息学方法提示LEP、CSH1和CSH2是穿透性胎盘植入的关键免疫基因,可能通过膜裂解、多泡体组织和核膜的重组、调节RAC蛋白信号转导和SRP依赖的共转译蛋白质膜定位等机制参与穿透性胎盘植入的发生,有助于更深入地理解穿透性胎盘植入,并为该疾病的潜在诊断和治疗靶点提供了进一步的见解。Objective: To predict key immune-related genes in placental implantation disorders using bioinformatics methods. Methods: In this study, the dataset GSE189267 was selected from the GEO database. Differential expression analysis of genes in each group was performed using R software (“limma” R package) to identify differentially expressed genes (DEGs) with statistical significance. Subsequently, bioinformatics analysis methods, including Gene Ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, weighted gene co-expression network analysis (WGCNA), protein-protein interaction network analysis, and gene set enrichment analysis (GSEA), were employed to determine immune-related genes significantly associated with placental implantation disorders. Results: A total of 93 DEGs highly associated with placental implantation disorders were identified. Further analysis using WGCNA revealed 17 immune-related genes significantly associated with placenta percreta. Among them, leptin (LEP), chorionic somatomammotropin 1 (CSH1), and chorionic somatomammotropin 2 (CSH2) were identified as the top three hub genes. Single-gene GSEA analysis showed that LEP may be involved in membrane fission, multivesicular body organization, and nuclear membrane reorganization, while CSH1 and CSH2 were involved in similar biological processes, including regulation of RAC protein signal transduction and SRP-dependent cotranslational protein membrane targeting. Conclusion: This study suggests that LEP, CSH1, and CSH2 are key immune-related genes in placenta percreta. They may participate in the development of placenta percreta through mechanisms such as membrane fission, multivesicular body organization, nuclear membrane reorganization, regulation of RAC protein signal transduction, and SRP-dependent cotranslational protein membrane targeting. These findings help to deepen the understanding of placenta percreta and provide further insights into potential diagnostic and therapeutic targets for this disorder.

Journal of Clinical Personalized MedicineVol. 04(02)
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Reproductive System and Pregnancy
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