Study on Potential Differentially Expressed Genes in Idiopathic Pulmonary Fibrosis by Bioinformatics and Next-Generation Sequencing Data Analysis

Identification and Analysis of Key Immune- and Inflammation-Related Genes in Idiopathic Pulmonary Fibrosis

Background

Studies suggest that immune and inflammation processes may be involved in the development of idiopathic pulmonary fibrosis (IPF); however, their roles remain unclear. This study aims to identify key genes associated with immune response and inflammation in IPF using bioinformatics.

Methods

We identified differentially expressed genes (DEGs) in the GSE93606 dataset and GSE28042 dataset, then obtained differentially expressed immune- and inflammation-related genes (DE-IFRGs) by overlapping DEGs. Two machine learning algorithms were used to further screen key genes. Genes with an area under curve (AUC) of > 0.7 in receiver operating characteristic (ROC) curves, significant expression and consistent trends across datasets were considered key genes. Based on these key genes, we carried out nomogram construction, enrichment and immune analyses, regulatory network mapping, drug prediction, and expression verification.

Results

27 DE-IFRGs were identified by intersecting 256 DEGs, 1793 immune-related genes, and 1019 inflammation-related genes. Three genes (RNASE3, S100A12, S100A8) were obtained by crossing two machine algorithms (Boruta and LASSO),which had good diagnostic performance with AUC values. These key genes were all enriched in the same pathways, such as GOCC_azurophil_granule, IL-12 signalling and production in macrophages is the pathway with the strongest role for key genes. Six distinct immune cells, including naive CD4 T cells, T cells CD4 memory resting, T cells regulatory (Tregs), Monocytes, Macrophages M2, Neutrophils were identified. Real-time quantitative polymerase chain reaction (RT-qPCR) results were consistent with the training and validation sets, and the expression of these key genes was significantly upregulated in the IPF samples.

Conclusion

This study identified three key genes (RNASE3, S100A12 and S100A8) associated with immune response and inflammation in IPF, providing valuable insights into the diagnosis and treatment of IPF.

Proteome-wide mendelian randomization identifies causal plasma proteins in interstitial lung disease

Interstitial lung disease (ILD) has shown limited treatment advancements, with minimal exploration of circulating protein biomarkers causally linked to ILD and its subtypes beyond idiopathic pulmonary fibrosis (IPF). In this study, we aimed to identify potential drug targets and circulating protein biomarkers for ILD and its subtypes. We utilized the most recent large-scale plasma protein quantitative trait loci (pQTL) data detected from the antibody-based method and ILD and its subtypes' GWAS data from the updated FinnGen database for Mendelian randomization analysis. To enhance the reliability of causal associations, we conducted external validation and sensitivity analyses, including Bayesian colocalization and bidirectional Mendelian randomization analysis. Our study identified eight plasma proteins genetically associated with ILD or its subtypes. Among these, three proteins-CDH15 (Cadherin-15), LTBR (Lymphotoxin-beta receptor), and ADAM15 (A disintegrin and metalloproteinase 15)-emerged as priority biomarkers and potential therapeutic targets, demonstrating more reliable associations by passing a series of sensitivity analyses compared to the others. Based on these findings, we propose for the first time that CDH15, ADAM15, and LTBR hold promise as novel potential circulating protein biomarkers and therapeutic targets for the diagnosis and treatment of ILD, IPF, and sarcoidosis, respectively, especially ADAM15, and these findings have the potential to provide new perspectives for advancing the research on the heterogeneity of ILD.

An FGF2-Derived Short Peptide Attenuates Bleomycin-Induced Pulmonary Fibrosis by Inhibiting Collagen Deposition and Epithelial-Mesenchymal Transition via the FGFR/MAPK Signaling Pathway

Following the COVID-19 pandemic, the prevalence of pulmonary fibrosis has increased significantly, placing patients at higher risk and presenting new therapeutic challenges. Current anti-fibrotic drugs, such as Nintedanib, can slow the decline in lung function, but their severe side effects highlight the urgent need for safer and more targeted alternatives. This study explores the anti-fibrotic potential and underlying mechanisms of an endogenous peptide (P5) derived from fibroblast growth factor 2 (FGF2), developed by our research team. Using a bleomycin-induced pulmonary fibrosis mouse model, we observed that P5 alleviated fibrosis by inhibiting collagen deposition, as confirmed by CT scans and histological staining. In TGF-β-induced cell models, P5 effectively suppressed collagen deposition and epithelial-mesenchymal transition (EMT). Transcriptome analysis highlighted pathways related to receptor binding, extracellular matrix organization, and cell adhesion, with KEGG analysis confirming FGFR/MAPK signaling inhibition as the primary mechanism underlying its anti-fibrotic effects. In summary, our study demonstrates that P5 significantly attenuates pulmonary fibrosis through the inhibition of EMT, collagen deposition, and FGFR/MAPK signaling, providing a promising therapeutic approach for fibrosis.

Network Pharmacology and Machine Learning Reveal Salidroside's Mechanisms in Idiopathic Pulmonary Fibrosis Treatment

Purpose

Idiopathic pulmonary fibrosis (IPF) is an irreversible respiratory disease. In this study, we evaluated the efficacy of salidroside (SAL), the main component of Rhodiola rosea, in treating IPF.

Methods

The pharmacological effects of SAL against epithelial-mesenchymal transition (EMT) and IPF were assessed through in vivo and in vitro experiments. Targets for SAL in treating IPF were identified from various databases and a PPI network was constructed. Functional analyses of target genes were performed using GO, KEGG, DO, and GSEA. Core target genes were identified using LASSO logistic regression and support vector machine (SVM) analysis, followed by molecular docking simulations. Predicted targets and pathways were validated through Western blotting, qRT-PCR, and IHC.

Results

Our results demonstrated that SAL ameliorated alveolar epithelial cells (AECs) EMT and mitigated bleomycin -induced pulmonary fibrosis. Through network pharmacology, we identified 74 targets for SAL in the treatment of IPF (PFDR<0.05) and analyzed their biological functions. Based on these findings, we further applied machine learning techniques to narrow down 9 core targets (PFDR<0.05). Integrating the results from molecular docking, KEGG, and GSEA analyses, we selected three key targets-IGF1, hypoxia-inducible factor 1-alpha (HIF-1α), and MAPK (PFDR<0.05)-for further investigation. Our study revealed that SAL inhibits the IGF1 signaling pathway, thereby improving AECs senescence and cell cycle arrest. By inhibiting the HIF-1α pathway, SAL alleviates endoplasmic reticulum stress and reduces intracellular ROS accumulation. Moreover, SAL suppresses the activation of the MAPK signaling pathway, leading to a decrease in inflammation markers in AECs and lung tissue.

Conclusion

Experimental results suggest that SAL effectively ameliorates BLM-induced EMT and IPF, likely through the inhibition of IGF1, HIF-1α, and MAPK signaling pathways. This study holds potential translational prospects and may provide new perspectives and insights for the use of traditional Chinese medicine in the treatment of IPF.

Assessment of pulmonary fibrosis using weighted gene co-expression network analysis

For many industrial chemicals toxicological data is sparse regarding several regulatory endpoints, so there is a high and often unmet demand for NAMs that allow for screening and prioritization of these chemicals. In this proof of concept case study we propose multi-gene biomarkers of compounds' ability to induce lung fibrosis and demonstrate their application in vitro. For deriving these biomarkers we used weighted gene co-expression network analysis to reanalyze a study where the time-dependent pulmonary gene-expression in mice treated with bleomycin had been documented. We identified eight modules of 58 to 273 genes each which were particularly activated during the different phases (inflammatory; acute and late fibrotic) of the developing fibrosis. The modules' relation to lung fibrosis was substantiated by comparison to known markers of lung fibrosis from DisGenet. Finally, we show the modules' application as biomarkers of chemical inducers of lung fibrosis based on an in vitro study of four diketones. Clear differences could be found between the lung fibrosis inducing diketones and other compounds with regard to their tendency to induce dose-dependent increases of module activation as determined using a previously proposed differential activation score and the fraction of differentially expressed genes in the modules. Accordingly, this study highlights the potential use of composite biomarkers mechanistic screening for compound-induced lung fibrosis.

Role of BAL and Serum Krebs von den Lungen-6 (KL-6) in Patients with Pulmonary Fibrosis

Background: Interstitial lung diseases (ILDs) encompass a diverse group of disorders affecting the lung interstitium, leading to inflammation, fibrosis, and impaired respiratory function. Currently, the identification of new diagnostic and prognostic biomarkers for ILDs turns out to be necessary. Several studies show the role of KL-6 in various types of interstitial lung disease and suggest that serum KL-6 levels can be used as a prognostic marker of disease. The aim of this study was to analyze KL-6 expression either in serum or bronchoalveolar lavage samples in order to: (i) make a serum vs. BAL comparison; (ii) better understand the local behavior of fibrosis vs. the systemic one; and (iii) evaluate any differences in patients with progressive fibrosis (PPF) versus patients with non-progressive fibrosis (nPPF). Methods: We used qRT-PCR to detect KL-6 expression both in serum and BAL samples. Mann-Whitney's U test was used to compare the differential expression between groups. Results: In serum, KL-6 is more highly expressed in PPF than in non-progressive fibrosis (p = 0.0295). This difference is even more significant in BAL (p < 0.001). Therefore, it is clear that KL-6 values are related to disease progression. Significant differences were found by making a comparison between BAL and serum. KL-6 was markedly higher in serum than BAL (p = 0.0146). Conclusions: This study identifies KL-6 as a promising biomarker for the severity of the fibrosing process and disease progression in ILDs, with significantly higher levels observed in PPF compared to nPPF. Moreover, the marked difference in KL-6 levels between serum and BAL emphasizes its potential diagnostic and prognostic relevance, providing enlightening insights into both the local and systemic aspects of ILDs.