Hong Yiguang, Zeng Suyi, Wang Xueqian, Kang Wei, Chen Bihua, Lan De, Wei Xuemei
Department of Otolaryngology-Head and Neck Surgery, Clinical Medical College & Affiliated Hospital of Chengdu University, Chengdu University, Chengdu, China.
Front Neurol. 2025 Aug 29;16:1499573. doi: 10.3389/fneur.2025.1499573. eCollection 2025.
Palmitoylation influences patients with obstructive sleep apnea (OSA) by modulating amyloid-β production. However, the involvement of palmitoylation-related genes (PRGs) in OSA remains unclear. This study aims to investigate this mechanism using bioinformatics approaches.
Datasets GSE38792 and GSE135917 were retrieved from the Gene Expression Omnibus (GEO) database. Differentially expressed PRGs (DE-PRGs) were identified through differential expression analysis and weighted gene co-expression network analysis (WGCNA). Candidate genes were pinpointed using the max cluster centrality method in cytoHubba. Biomarkers were selected through machine learning algorithms, expression profiling, and ROC analysis, with diagnostic potential evaluated using a nomogram. Further insights into the role of biomarkers in OSA were provided through enrichment analysis, molecular regulatory network construction, and drug prediction.
HIF1A and PDIA3 emerged as potential biomarkers, with the nomogram showing high predictive accuracy for OSA. Enrichment analysis revealed that HIF1A and PDIA3 were co-enriched in pathways such as "focal adhesion," "olfactory transduction," "RNA degradation," "spliceosome," and "ubiquitin-mediated proteolysis." A lncRNA-miRNA-mRNA regulatory network was constructed, featuring multiple regulatory pairs, including CYTOR-hsa-miR-1-3p-HIF1A and CYTOR-hsa-miR-1-3p-PDIA3. Drug prediction analysis identified potential compounds targeting HIF1A, such as klugine, puupehenone, and isocephaeline.
HIF1A and PDIA3 were highlighted as significant potential biomarkers, providing valuable insights into the molecular mechanisms of palmitoylation in OSA and potential therapeutic targets.
棕榈酰化通过调节β淀粉样蛋白的产生影响阻塞性睡眠呼吸暂停（OSA）患者。然而，棕榈酰化相关基因（PRGs）在OSA中的作用仍不清楚。本研究旨在使用生物信息学方法探究这一机制。
从基因表达综合数据库（GEO）中检索数据集GSE38792和GSE135917。通过差异表达分析和加权基因共表达网络分析（WGCNA）鉴定差异表达的PRGs（DE-PRGs）。使用cytoHubba中的最大聚类中心性方法确定候选基因。通过机器学习算法、表达谱分析和ROC分析选择生物标志物，并使用列线图评估诊断潜力。通过富集分析、分子调控网络构建和药物预测进一步深入了解生物标志物在OSA中的作用。
HIF1A和PDIA3成为潜在的生物标志物，列线图显示对OSA具有较高的预测准确性。富集分析表明，HIF1A和PDIA3共同富集于“粘着斑”、“嗅觉转导”、“RNA降解”、“剪接体”和“泛素介导的蛋白水解”等通路。构建了lncRNA-miRNA-mRNA调控网络，其具有多个调控对，包括CYTOR-hsa-miR-1-3p-HIF1A和CYTOR-hsa-miR-1-3p-PDIA3。药物预测分析确定了靶向HIF1A的潜在化合物，如klugine、puupehenone和异千金藤碱。
HIF1A和PDIA3被确定为重要的潜在生物标志物，为OSA中棕榈酰化的分子机制和潜在治疗靶点提供了有价值的见解。
