收稿日期: 2023-08-07
录用日期: 2023-11-30
网络出版日期: 2024-02-28
基金资助
国家自然科学基金(81802226);上海市浦江人才计划(2019PJD038);上海市“医苑新星”青年医学人才培养资助计划;上海交通大学医学院“双百人”项目(20220017);上海市第六人民医院优秀人才培育项目(ynyq202101)
Exploration of the relationship between nicotinamide metabolism-related genes and osteoarthritis
Received date: 2023-08-07
Accepted date: 2023-11-30
Online published: 2024-02-28
Supported by
National Natural Science Foundation of China(81802226);Shanghai Pujiang Program(2019PJD038);Shanghai “Rising Stars of Medical Talent” Youth Development Program (Youth Medical Talents-Specialist Program);“Two-hundred Talents” Program of Shanghai Jiao Tong University School of Medicine(20220017);Shanghai Sixth People's Hospital Excellent Young Scientist Development Program(ynyq202101)
目的·利用生物信息学方法探索骨关节炎与烟酰胺代谢相关基因之间的关系，找到具有诊断价值和治疗潜力的关键基因。方法·以“Osteoarthritis”为检索词，在GEO数据库中获取GSE12021、GSE55235和GSE55457数据集，将GSE55457作为验证集。去除GSE12021和GSE55235数据集的批次效应后，得到标准化的合并数据集，将其作为训练集，并在训练集中筛选出差异表达基因（differentially expressed genes，DEGs）。在GeneCards数据库和MSigDB数据库中获取所有烟酰胺代谢相关基因（nicotinamide metabolism-related genes，NMRGs）。将DEGs与NMRGs取交集，得到烟酰胺代谢相关差异表达基因（nicotinamide metabolism-related differentially expressed genes，NMRDEGs）。对训练集进行基因集富集分析（gene set enrichment analysis，GSEA），对NMRDEGs进行基因本体（Gene Ontology，GO）、京都基因与基因组百科全书（Kyoto Encyclopedia of Genes and Genomes，KEGG）分析。通过LASSO（least absolute shrinkage and selection operator）和支持向量机（support vector machine，SVM）分析筛选出NMRDEGs关键基因，构建骨关节炎诊断模型，并用验证集GSE55457进行验证。通过单样本基因集富集分析（single sample gene set enrichment analysis，ssGSEA）分析免疫细胞的浸润类型。通过DGIdb数据库、ENCORI数据库和CHIPBase数据库对关键基因的mRNA进行相互作用网络和药物小分子预测。通过干扰小RNA（small interfering RNA，siRNA）敲降软骨细胞内NMRDEGs关键基因，用实时荧光定量聚合酶链反应（real-time fluorogenic quantitative polymerase chain reaction，RT-qPCR）检测关键基因敲降对软骨形成相关基因表达的影响。结果·发现了NAMPT、TIPARP等7个NMRDEGs。GO和KEGG分析富集到核因子κB信号通路和正向调节白细胞介素-1介导的信号通路等。GSEA富集到缺氧诱导因子-1转录因子通路（Hif1 Tfpathway）和多配体蛋白聚糖1（syndecan 1）通路等信号通路。LASSO分析和SVM分析共同筛选得到NPAS2、TIPARP和NAMPT关键基因并构建了骨关节炎诊断模型，验证集检验提示诊断模型诊断效果具有高准确度。ssGSEA免疫浸润分析的结果显示，巨噬细胞等15种免疫细胞存在显著差异（均P<0.05）。找到了7个针对关键基因的潜在药物小分子，19种与关键基因相互作用且上游基因与下游基因数量之和大于10的miRNA，19种与关键基因结合且上游基因与下游基因数量之和大于7的转录因子，27个聚类数>19的RNA结合蛋白。RT-qPCR结果显示，关键基因敲降会降低软骨形成相关基因的表达。结论·NPAS2、TIPARP和NAMPT为烟酰胺代谢相关的关键基因，可据此构建骨关节炎诊断模型。
邓青松 , 张长青 , 陶诗聪 . 烟酰胺代谢相关基因与骨关节炎的关系探索[J]. 上海交通大学学报（医学版）, 2024 , 44(2) : 145 -160 . DOI: 10.3969/j.issn.1674-8115.2024.02.001
Objective ·To explore the relationship between osteoarthritis and nicotinamide metabolism-related genes using bioinformatics analysis, and identify key genes with diagnostic value and therapeutic potential. Methods ·By using "Osteoarthritis" as a search term, GSE12021, GSE55235, and GSE55457 were obtained from the GEO database, with GSE55457 being used as the validation set. After removing batch effects from the GSE12021 and GSE55235 datasets, the standardized combined dataset was obtained and used as the training dataset. Differentially expressed genes (DEGs) were identified from the training dataset. All nicotinamide metabolism-related genes (NMRGs) were obtained from the GeneCards and MSigDB databases. The intersection of DEGs and NMRGs was taken to obtain nicotinamide metabolism-related differentially expressed genes (NMRDEGs). Gene set enrichment analysis (GSEA) was performed on the training dataset, while gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) analysis were performed on NMRDEGs. Key genes were selected by using least absolute shrinkage and selection operator (LASSO) and support vector machine (SVM) analysis in NMRDEGs to build an osteoarthritis diagnosis model which was validated by using the GSE55457 dataset. Single sample gene set enrichment analysis (ssGSEA) was used to analyze the immune cell infiltration type. Interactions networks and drug molecule predictions were obtained for these key genes' mRNA with the DGIdb, ENCORI, and CHIPBase databases. siRNA was used to knock down the key genes in chondrocytes, and then real-time fluorescence quantitative polymerase chain reaction (RT-qPCR) was used to detect the expression of chondrogenesis-related genes. Results ·Seven NMRDEGs, including NAMPT, TIPARP, were discovered. GO and KEGG analysis enriched some signaling pathways, such as nuclear factor-κB signaling pathway and positive regulation of interleukin-1-mediated signaling pathway. GSEA enriched pathways such as Hif1 Tfpathway and syndecan 1 pathway. Key genes NPAS2, TIPARP, and NAMPT were identified through LASSO and SVM analysis, and used to construct an osteoarthritis diagnostic model. The validated results showed that the diagnostic model had high accuracy. Immune infiltration analysis results obtained by ssGSEA showed significant differences (all P<0.05) in 15 types of immune cells, including macrophages. Seven potential small molecules targeting key genes were identified, along with 19 miRNAs with the sum of upstream and downstream >10, 19 transcription factors with upstream and downstream >7, and 27 RNA binding proteins with clusterNum >19. The results of RT-qPCR showed that knocking down key genes reduced the expression of chondrogenesis-related genes. Conclusion ·Through bioinformatics analysis, key genes related to nicotinamide metabolism, NPAS2, TIPARP, and NAMPT, are discovered, and an osteoarthritis diagnostic model is constructed.
Key words： osteoarthritis; nicotinamide metabolism; bioinformatics; diagnostic model; nomogram
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