Identification of Autophagy-Related Genes in Idiopathic Pulmonary Fibrosis Using Bioinformatics Methods
Idiopathic pulmonary fibrosis (IPF) is a chronic, progressive, and fibrotic lung disease characterized by symptoms such as dyspnea, decreased lung function, and cough. The median survival time for patients with IPF is approximately three years, and the five-year survival rate is less than 30%. Despite advancements in anti-fibrotic therapies, IPF remains incurable, necessitating further exploration of its pathological processes from a cellular biology perspective. Autophagy, a cellular process that involves the degradation of organelles, proteins, or intracellular pathogens in lysosomes, has been implicated in various diseases. However, its role in IPF remains poorly understood. This study aimed to identify autophagy-related genes in IPF using bioinformatics methods to provide insights into the disease’s development and potential therapeutic targets.
The study utilized data from the Gene Expression Omnibus (GEO) database, specifically dataset GSE24206, which includes gene expression profiles from 17 IPF patients and six healthy controls. The Human Autophagy Database (HADb) was used to obtain 222 autophagy-related genes. Principal component analysis (PCA) was performed to distinguish between IPF and normal samples, revealing significant differences between the two groups. The R package “limma” was employed to identify differentially expressed autophagy-related genes, with thresholds set at an adjusted P value of less than 0.05 and an absolute fold change greater than 1.5.
The analysis identified 20 differentially expressed autophagy-related genes in IPF, including 11 up-regulated genes (TP63, ITGB4, CTSD, TNFSF10, DIRAS3, TP53, GAA, EIF2AK2, ERBB2, TSC2, and CDKN2A) and nine down-regulated genes (ERN1, FOXO1, IL24, DDIT3, BNIP3, DLC1, CXCR4, MYC, and NAMPT). Visual representations of these findings were generated using R packages “ggplot2,” “pheatmap,” and “ggpubr,” including volcano plots, heatmaps, and box plots. The Spearman correlation analysis was used to examine the relationships between these genes, revealing significant positive and negative correlations.
Protein-protein interaction (PPI) analysis was conducted using the STRING database and visualized with Cytoscape. The PPI network demonstrated interactions among the encoded proteins of the 20 autophagy-related genes, with a minimum required interaction score of 0.4. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using the Metascape database to explore the functional roles and pathways associated with these genes. The GO analysis revealed enrichment in processes such as positive regulation of the apoptotic process, autophagy, and regulation of cellular response to stress. The KEGG analysis highlighted pathways including apoptosis, autophagy, and the FOXO signaling pathway.
The study’s findings suggest that autophagy-related genes play a significant role in the development of IPF. For instance, FOXO1 has been shown to regulate autophagy and influence hepatocellular carcinoma development through the adenosine monophosphate-activated protein kinase-FOXO1-unc-51 like autophagy activating kinase 1 signaling axis. Similarly, CXCR4-targeted PET imaging has been used to predict outcomes in IPF patients treated with pirfenidone. These results underscore the importance of autophagy in IPF and other respiratory diseases.
However, the study has limitations. The expression of the identified autophagy-related genes was not experimentally validated in IPF patients and healthy controls. Additionally, the lack of patient survival information in the GSE24206 dataset precluded analysis of the genes’ impact on IPF prognosis. Future research should focus on validating these findings and elucidating the detailed mechanisms of autophagy in IPF.
In conclusion, this study identified 20 autophagy-related genes differentially expressed in IPF, providing potential therapeutic targets and insights into the disease’s pathogenesis. The findings highlight the importance of autophagy in IPF and suggest that further investigation into these genes could enhance our understanding of the disease and inform the development of novel treatments.
doi.org/10.1097/CM9.0000000000001633
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