Identification and Validation of Aging-Related Genes in Idiopathic Pulmonary Fibrosis - He, Jie; Li, Xiaoyan (Frontiers in Genetics, 2022)
Objective: Aging plays a significant role in the occurrence and development of idiopathic pulmonary fibrosis (IPF). This research is aimed at identifying and verifying the potential genes related to aging in IPF by performing bioinformatics analysis and experiments. Methods: The mRNA expression profile data set GSE150910 provided by the GEO database and the R software were used for screening the differentially expressed aging-related genes of IPF. Subsequently, the analysis of protein-protein interaction (PPI), correlation analysis, gene ontology (GO) enrichment analysis, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed on differentially expressed aging-related genes. Afterward, aging-related genes were further screened by two techniques; the LASSO regression and support vector machine, and the ROC curves were drawn. Lastly, qRT-PCR was performed for the verification of RNA expression of the 6 differentially expressed aging-related genes that were finally screened in the blood samples of patients with IPF and healthy individuals in the control group. Results: 16 differentially expressed aging-related genes were detected among which 12 were up-regulated and 4 were down-regulated. The interaction of these aging-related genes was observed after analyzing the PPI results. The GO and KEGG enrichment analysis of the differentially expressed aging-related genes indicated the presence of several enriched terms related to senescence and apoptotic mitochondrial changes. Further screening by LASSO regression and support vector machine provided 6 genes (IGF-1, RET, IGFBP2, CDKN2A, JUN, TFAP2A) that can serve as potential biomarkers for the diagnosis of IPF. The results of qRT-PCR indicated that out of the above-mentioned 6 aging-related genes, only the expression levels of IGF-1, RET, and IGFBP2 in patients suffering from IPF and healthy individuals in the control group were similar to the results of bioinformatics analysis. Conclusion: Bioinformatics analysis helped in finding 16 potential aging-related genes associated to IPF. Clinical sample validation suggested that IGF-1, RET, and IGFBP2 may have a role in the incidence and prognosis of IPF by the regulation of aging. These results may help us understand IPF better and can provide a beneficial approach towards the treatment of IPF.