背景:功能失调的自噬在椎间盘退变(IDD)的进展中起着关键作用。然而,自噬相关基因9A(ATG9A)与IDD的关系尚未见报道.
方法:首先,来自GeneCards的GEO和自噬相关基因(ARGs)的转录组数据集使用R进行。通过最小绝对收缩和选择算子(LASSO)等方法鉴定IDD特异性特征基因,随机森林(RF),和支持向量机(SVM)分析。这些发现的验证通过体外实验进行,独立数据集的评估,接收器工作特性(ROC)曲线分析。随后的步骤纳入共表达分析,基因本体论(GO)分析,京都基因和基因组百科全书(KEGG)途径分析,基因集富集分析(GSEA),并构建竞争内源性RNA(ceRNA)网络。最后部分建立了免疫细胞浸润之间的相关性,ATG9A,和IDD利用CIBERSORT算法和单细胞RNA(scRNA)测序数据。
结果:研究确定了87个差异表达基因,只有ATG9A标记为IDD签名基因。体外实验和独立数据集的分析揭示了变性组中ATG9A表达的减少。在ROC分析后,ATG9A的曲线下面积(AUC)超过0.8。此外,免疫细胞浸润和scRNA测序数据分析阐明了免疫细胞在IDD进展中的重要作用.构建了一个ceRNA网络,以ATG9A为中心,包括4种miRNAs和22种lncRNAs。
结论:ATG9A被鉴定为IDD的诊断基因,表明其作为治疗疾病的有效靶标的可行性。
BACKGROUND: Disfunctional autophagy plays a pivotal role in Intervertebral Disc Degeneration (IDD) progression. however, the connection between Autophagy-related gene 9A (ATG9A) and IDD has not been reported.
METHODS: Firstly, transcriptome datasets from the GEO and Autophagy-related genes (ARGs) from GeneCards were carried out using R. Following this, IDD-specific signature genes were identified through methods such as least absolute shrinkage and selection operator (LASSO), random forest (RF), and support vector machine (SVM) analyses. Validation of these findings proceeded through in vitro experiments, evaluation of independent datasets, and analysis of receiver operating characteristic (ROC) curves. Subsequent steps incorporated co-expression analysis, Gene Ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, Gene Set Enrichment Analysis (GSEA), and construction of competing endogenous RNA (ceRNA) network. The final section established the correlation between immune cell infiltration, ATG9A, and IDD utilizing the CIBERSORT algorithm and single-cell RNA (scRNA) sequencing data.
RESULTS: Research identified 87 differentially expressed genes, with only ATG9A noted as an IDD signature gene. Analysis of in vitro experiments and independent datasets uncovered a decrease in ATG9A expression within the degeneration group. The area under the curve (AUC) of ATG9A exceeded 0.8 following ROC analysis. Furthermore, immune cell infiltration and scRNA sequencing data analysis elucidated the substantial role of immune cells in IDD progression. A ceRNA network was constructed, centered around ATG9A, included 4 miRNAs and 22 lncRNAs.
CONCLUSIONS: ATG9A was identified as a diagnostic gene for IDD, indicating its viability as a effective target for therapy disease.