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通过综合生物信息学分析鉴定 CPAP 治疗阻塞性睡眠呼吸暂停中关键基因和免疫浸润的作用。

Identification of key genes and immune infiltration modulated by CPAP in obstructive sleep apnea by integrated bioinformatics analysis.

机构信息

Department of Geriatrics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.

出版信息

PLoS One. 2021 Sep 16;16(9):e0255708. doi: 10.1371/journal.pone.0255708. eCollection 2021.

Abstract

Patients with obstructive sleep apnea (OSA) experience partial or complete upper airway collapses during sleep resulting in nocturnal hypoxia-normoxia cycling, and continuous positive airway pressure (CPAP) is the golden treatment for OSA. Nevertheless, the exact mechanisms of action, especially the transcriptome effect of CPAP on OSA patients, remain elusive. The goal of this study was to evaluate the longitudinal alterations in peripheral blood mononuclear cells transcriptome profiles of OSA patients in order to identify the hub gene and immune response. GSE133601 was downloaded from Gene Expression Omnibus (GEO). We identified black module via weighted gene co-expression network analysis (WGCNA), the genes in which were correlated significantly with the clinical trait of CPAP treatment. Finally, eleven hub genes (TRAV10, SNORA36A, RPL10, OBP2B, IGLV1-40, H2BC8, ESAM, DNASE1L3, CD22, ANK3, ACP3) were traced and used to construct a random forest model to predict therapeutic efficacy of CPAP in OSA with a good performance with AUC of 0.92. We further studied the immune cells infiltration in OSA patients with CIBERSORT, and monocytes were found to be related with the remission of OSA and partially correlated with the hub genes identified. In conclusion, these key genes and immune infiltration may be of great importance in the remission of OSA and related research of these genes may provide a new therapeutic target for OSA in the future.

摘要

患有阻塞性睡眠呼吸暂停(OSA)的患者在睡眠期间会经历部分或完全的上呼吸道塌陷,导致夜间低氧-正常氧循环,持续气道正压通气(CPAP)是 OSA 的黄金治疗方法。然而,CPAP 对 OSA 患者的确切作用机制,特别是转录组效应,仍然难以捉摸。本研究旨在评估 OSA 患者外周血单核细胞转录组谱的纵向变化,以确定关键基因和免疫反应。从基因表达综合数据库(GEO)中下载 GSE133601。我们通过加权基因共表达网络分析(WGCNA)识别黑色模块,其中的基因与 CPAP 治疗的临床特征显著相关。最后,追踪到 11 个关键基因(TRAV10、SNORA36A、RPL10、OBP2B、IGLV1-40、H2BC8、ESAM、DNASE1L3、CD22、ANK3、ACP3),并构建随机森林模型,以 0.92 的 AUC 预测 CPAP 治疗 OSA 的疗效。我们进一步通过 CIBERSORT 研究了 OSA 患者的免疫细胞浸润,发现单核细胞与 OSA 的缓解有关,与鉴定的关键基因部分相关。总之,这些关键基因和免疫浸润可能对 OSA 的缓解非常重要,对这些基因的研究可能为 OSA 的未来治疗提供新的靶点。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c073/8445487/3d35f6485608/pone.0255708.g001.jpg

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