探索二硫化相关基因在肺动脉高压中的诊断和免疫渗透作用。

IF 5.8 2区 医学 Q1 Medicine Respiratory Research Pub Date : 2024-10-09 DOI:10.1186/s12931-024-02978-w
Xin Tan, Ningning Zhang, Ge Zhang, Shuai Xu, Yiyao Zeng, Fenlan Bian, Bi Tang, Hongju Wang, Jili Fan, Xiaohong Bo, Yangjun Fu, Huimin Fan, Yafeng Zhou, Pinfang Kang
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引用次数: 0

摘要

背景:肺动脉高压(PH)是由各种原因导致的肺动脉压力升高,影响右心功能和存活。二硫化血症是一种新发现的细胞死亡机制,可能在 PH 中起作用,但其相关基因(DiGs)在 PH 中的作用还不十分清楚。本研究旨在确定 DiGs 在 PH 中的诊断相关性:我们利用 GSE11726 数据分析了 DiGs 及其免疫特征,以确定影响 PH 进展的核心基因。我们比较了各种机器学习模型,包括RF、SVM、GLM和XGB,以确定最有效的诊断模型。验证使用了数据集 GSE57345 和 GSE48166。此外,还建立了一个CeRNA网络,并使用缺氧诱导的PH大鼠模型进行Western印迹分析实验验证:结果:发现了 12 个与 PH 明显相关的 DiGs。XGB模型在诊断准确性(AUC = 0.958)方面表现出色,识别出了核心基因DSTN、NDUFS1、RPN1、TLN1和MYH10。验证数据集证实了该模型的有效性。构建了一个涉及这些基因、40个miRNA和115个lncRNA的CeRNA网络。在强大的分子对接结果支持下,药物预测显示了叶酸的治疗潜力。在大鼠模型中的实验验证与这些发现一致:我们发现了 PH 中 DiGs 的独特表达模式,利用 XGB 机器学习模型确定了核心基因,并建立了 CeRNA 网络。我们预测了针对核心基因的药物,并进行了分子对接。还对这些核心基因进行了实验验证。
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Exploring the diagnostic and immune infiltration roles of disulfidptosis related genes in pulmonary hypertension.

Background: Pulmonary hypertension (PH) is marked by elevated pulmonary artery pressures due to various causes, impacting right heart function and survival. Disulfidptosis, a newly recognized cell death mechanism, may play a role in PH, but its associated genes (DiGs) are not well understood in this context. This study aims to define the diagnostic relevance of DiGs in PH.

Methods: Using GSE11726 data, we analyzed DiGs and their immune characteristics to identify core genes influencing PH progression. Various machine learning models, including RF, SVM, GLM, and XGB, were compared to determine the most effective diagnostic model. Validation used datasets GSE57345 and GSE48166. Additionally, a CeRNA network was established, and a hypoxia-induced PH rat model was used for experimental validation with Western blot analysis.

Results: 12 DiGs significantly associated with PH were identified. The XGB model excelled in diagnostic accuracy (AUC = 0.958), identifying core genes DSTN, NDUFS1, RPN1, TLN1, and MYH10. Validation datasets confirmed the model's effectiveness. A CeRNA network involving these genes, 40 miRNAs, and 115 lncRNAs was constructed. Drug prediction suggested therapeutic potential for folic acid, supported by strong molecular docking results. Experimental validation in a rat model aligned with these findings.

Conclusion: We uncovered the distinct expression patterns of DiGs in PH, identified core genes utilizing an XGB machine-learning model, and established a CeRNA network. Drugs targeting the core genes were predicted and subjected to molecular docking. Experimental validation was also conducted for these core genes.

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来源期刊
Respiratory Research
Respiratory Research RESPIRATORY SYSTEM-
CiteScore
9.70
自引率
1.70%
发文量
314
审稿时长
4-8 weeks
期刊介绍: Respiratory Research publishes high-quality clinical and basic research, review and commentary articles on all aspects of respiratory medicine and related diseases. As the leading fully open access journal in the field, Respiratory Research provides an essential resource for pulmonologists, allergists, immunologists and other physicians, researchers, healthcare workers and medical students with worldwide dissemination of articles resulting in high visibility and generating international discussion. Topics of specific interest include asthma, chronic obstructive pulmonary disease, cystic fibrosis, genetics, infectious diseases, interstitial lung diseases, lung development, lung tumors, occupational and environmental factors, pulmonary circulation, pulmonary pharmacology and therapeutics, respiratory immunology, respiratory physiology, and sleep-related respiratory problems.
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