A prognostic model of idiopathic pulmonary fibrosis was constructed based on macrophage-related genes and mitochondria-related genes

Author:

Bao Yu1,Yang Shiyuan1,Zhao Hailan1,Zhu Xue2,Wang Yezhen2,Li Ke2,Liu Xue2,Zhang Wei2

Affiliation:

1. Shandong University of Chinese Medicine

2. Affiliated Hospital of Shandong University of Chinese Medicine

Abstract

Abstract Background Studies have shown that mitochondrial function and macrophages may play a role in the development of idiopathic pulmonary fibrosis (IPF). However, the mechanism of macrophages and mitochondria in IPF is not fully understood. Methods To construct a prognostic model for IPF based on Macrophage-associated genes (MaRGs) and Mitochondria-associated genes (MitoRGs), differential analysis was performed to achieve differentially expressed genes (DEGs) between IPF and Control groups in the GSE28042 dataset. Then, MitoRGs, MaRGs and DEGs were overlapped to screen out the crossover genes. The univariate Cox analysis and the least absolute shrinkage and selection operator (LASSO) algorithm were implemented to achieve biomarkers. Furthermore, the independent prognostic analysis was employed. The ingenuity pathway analysis (IPA) was employed to further understand the molecular mechanisms of biomarkers. Next, the immune infiltration analysis was implemented to identify differential immune cells between two risk subgroups. Results There were 4791 DEGs between IPF and Control groups. Furthermore, 26 crossover genes were achieved by the intersection processing. Three biomarkers including ALDH2, MCL1, and BCL2A1 were achieved, and the risk model based on the biomarkers was created. In addition, a nomogram for survival forecasting of IPF patients was created based on riskScore, Age, and Gender, and we found that biomarkers were associated with classical pathways including ‘Apoptosis Signaling’, ‘PI3K/AKT Signaling’, and so on. Next, two differential immune cells including Monocytes and CD8 T cells were identified between two risk subgroups. Moreover, we found that MIR29B2CHG and hsa-mir-1-3p could regulate the expression of ALDH2. Conclusion We achieved 3 biomarkers including ALDH2, MCL1, and BCL2A1 associated with IPF, providing a new theoretical basis for clinical treatment of IPF.

Publisher

Research Square Platform LLC

Reference52 articles.

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