ATG9A as a potential diagnostic marker of intervertebral disc degeneration: Inferences from experiments and bioinformatics analysis incorporating sc-RNA-seq data

GENE(2024)

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Abstract
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 coexpression 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. Conclusion: ATG9A was identified as a diagnostic gene for IDD, indicating its viability as a effective target for therapy disease.
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Key words
Intervertebral disc degeneration (IDD),Immune infiltration,Bioinformatic analysis,Autophagy,ATG9A
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