Lipid metabolism in idiopathic pulmonary fibrosis: From pathogenesis to therapy

Multi-omics study reveals Shuangshen Pingfei formula regulates EETs metabolic reprogramming to exert its therapeutic effect on pulmonary fibrosis

As a clinical formula derived from Renshen Pingfei San, Shuangshen Pingfei formula (SSPF) has been used to treat pulmonary fibrosis (PF). However, its in-depth mechanism of action remains unknown. In this study, the effect of SSPF was evaluated by applying a rat model of PF caused by intratracheal drip bleomycin. To characterize the molecular changes related to PF and reveal therapeutic targets for SSPF, we performed transcriptomic and metabolomic analyses on rat lung. Finally, western blotting and qPCR experiments were used to validate the multi-omics results. As a result, a significant reduction in inflammation and fibrosis caused by BLM was observed when SSPF was administered. Widespread changes in gene expression and metabolic programming were observed in the lungs of PF rats through RNA-seq and untargeted metabolomic analysis. Combined transcriptomic and metabolomic analyses revealed the involvement of arachidonic acid (AA) metabolism pathways in PF. Further validation of AA metabolite synthase genes and protein levels showed a significant decrease in the levels of epoxyeicosatrienoic acids (EETs) synthases, including Cyp2j2, Cyp2b1, in the PF lungs. SSPF treatment regulated the above changes in gene expression and metabolic programming, particularly the regulation of EETs. This study is the first to investigate the mechanism of action of SSPF in the treatment of PF from the perspective of regulating the synthesis of EETs in AA metabolism.

Fully automatic quantification of pulmonary fat attenuation volume by CT: an exploratory pilot study

BACKGROUND

Non-malignant chronic diseases remain a major public health concern. Given the alterations in lipid metabolism and deposition in the lung and its association with fibrotic interstitial lung disease (fILD) and chronic obstructive pulmonary disease (COPD), this study aimed to detect those alterations using computed tomography (CT)-based analysis of pulmonary fat attenuation volume (CTpfav).

METHODS

This observational retrospective single-center study involved 716 chest CT scans from three subcohorts: control (n = 279), COPD (n = 283), and fILD (n = 154). Fully automated quantification of CTpfav based on lung segmentation and HU-thresholding. The pulmonary fat index (PFI) was derived by normalizing CTpfav to the CT lung volume. Statistical analyses were conducted using Kruskal-Wallis with Dunn's post hoc tests.

RESULTS

Patients with fILDs demonstrated a significant increase in CTpfav (median 71.0 mL, interquartile range [IQR] 59.7 mL, p < 0.001) and PFI (median 1.9%, IQR 2.4%, p < 0.001) when compared to the control group (CTpfav median 43.6 mL, IQR 16.94 mL; PFI median 0.9%, IQR 0.5%). In contrast, individuals with COPD exhibited significantly reduced CTpfav (median 36.2 mL, IQR 11.4 mL, p < 0.001) and PFI (median 0.5%, IQR 0.2%, p < 0.001).

CONCLUSION

The study underscores the potential of CTpfav and PFI as imaging biomarkers for detecting changes in lung lipid metabolism and deposition and demonstrates a possibility of tracking these alterations in patients with COPD and ILDs. Further research is needed to validate these findings and explore the clinical relevance of CTpfav and PFI in lung disease management.

RELEVANCE STATEMENT

This study introduces a fully automated method for quantifying CTpfav, potentially establishing it as a new imaging biomarker for chronic lung diseases.

KEY POINTS

This retrospective observational study employed an open-source, automated algorithm for the quantification of CT pulmonary fat attenuation volume (CTpfav). Patients with fibrotic interstitial lung disease (fILD) showed a significantly higher CTpfav and pulmonary fat index (PFI), i.e., CTpfav/CT lung volume, compared to a control group. Patients with chronic obstructive pulmonary disease (COPD) showed significantly lower CTpfav and PFI compared to the control group. CTpfav and PFI may each serve as imaging biomarkers for various lung diseases and warrant further investigation.

The tyrosine kinase inhibitor Nintedanib induces lysosomal dysfunctionality: Role of protonation-dependent crystallization processes

Nintedanib (NIN), a multi-tyrosine kinase inhibitor clinically approved for idiopathic pulmonary fibrosis and lung cancer, is characterized by protonation-dependent lysosomotropic behavior and appearance of lysosome-specific fluorescence emission properties. Here we investigate whether spontaneous formation of a so far unknown NIN matter within the acidic cell compartment is underlying these unexpected emissive properties and investigate the consequences on lysosome functionality. Lysosomes of cells treated with NIN, but not non-protonatable NIN derivatives, exhibited lysosome-associated birefringence signals co-localizing with the NIN-derived fluorescence emission. Sensitivity of both parameters towards vATPase inhibitors confirmed pH-dependent, spontaneous adoption of novel crystalline NIN structures in lysosomes. Accordingly, NIN crystallization from buffer solutions resulted in formation of multiple crystal polymorphs with pH-dependent fluorescence properties. Cell-free crystals grown at lysosomal-like pH conditions resembled NIN-treated cell lysosomes concerning fluorescence pattern, photobleaching dynamics, and Raman spectra. However, differences in birefringence intensity and FAIM-determined anisotropy, as well as predominant association with (intra)lysosomal membrane structures, suggested formation of a semi-solid NIN crystalline matter in acidic lysosomes. Despite comparable target kinase inhibition, NIN, but not its non-protonatable derivatives, impaired lysosomal functionality, mediated massive cell vacuolization, enhanced autophagy, deregulated lipid metabolism, and induced atypical phospholipidosis. Moreover, NIN exerted distinct phototoxicity, strictly dependent on lysosomal microcrystallization events. The spontaneous formation of NIN crystalline structures was also observable in the gut mucosa of orally NIN-treated mice. Summarizing, the here-described kinase inhibition-independent impact of NIN on lysosomal functionality mediates several of its cell biological activities and might contribute to NIN adverse effects.

Comprehensive analysis of single-cell transcriptomics and genetic factors reveals the mechanisms and preventive strategies for the progression from pulmonary fibrosis to lung cancer

BACKGROUND

Pulmonary fibrosis (PF) leads to excessive deposition of fibrous connective tissue in the lungs, increasing the risk of lung cancer due to the enhanced activity of fibroblasts (FBs). Fibroblast-mediated collagen fiber deposition creates a tumor-like microenvironment, laying the foundation for tumorigenesis. Clinically, numerous cases of lung cancer induced by pulmonary fibrosis have been observed. In recent years, the study of nucleotide point mutations, which provide more detailed insights than gene expression, has made significant advancements, offering new perspectives for clinical research.

METHODS

We initially employed Mendelian randomization to ascertain that the initial stage of lung cancer induced by PF belongs to small cell lung cancer (SCLC). Subsequently, pulmonary neuroendocrine cells (PNECs) were identified by using pseudo-time series analysis as cell clusters with carcinogenic potential. We categorized FBs into four groups according to their cellular metabolism, and then analyzed the cellular communication between FBs and PNECs, as well as changes in intracellular pathways of PNECs. Additionally, we examined the characteristic genome of FBs which is significantly associated with PF and investigated the impact of FBs on immune cells in the PF microenvironment. Finally, we explored strategies for preventing the progression from PF to lung cancer.

RESULTS

The genetic features of cells with carcinogenic potential in PF tissues were revealed, characterized by upregulation of Achaete-Scute Family BHLH Transcription Factor 1 (ASCL1), Homeobox B2 (HOXB2), Teashirt Zinc Finger Homeobox 2 (TSHZ2), Insulinoma-associated 1 (INSM1), and reduced activity of RE1 Silencing Transcription Factor (REST). FBs characterized by high glycolysis and low tricarboxylic acid (TCA) cycling played a key role in the progression of PF. The microenvironment of PF resembles the tumor microenvironment, providing a conducive immunosuppressive environment for the occurrence of cancer cells. In dendritic cells, rs9265808 is a susceptibility locus for progression from pulmonary fibrosis to lung cancer, mutations at this locus increase the expression of Complement Factor B (CFB), and excessive activation of the complement pathway is a crucial factor leading to lung cancer development in patients with pulmonary fibrosis. Ensuring adequate nutritional supply and physical function is one of the effective measures to prevent progression from pulmonary fibrosis to lung cancer.

CONCLUSION

CFB promotes lung cancer occurrence by inducing the accumulation and polarization of a large number of monocytes/macrophages in the lungs, driving disease progression by reducing the physical fitness of patients with pulmonary fibrosis.

Identification of PANoptosis-related genes for idiopathic pulmonary fibrosis by machine learning and molecular subtype analysis

Idiopathic pulmonary fibrosis (IPF) is a severe interstitial lung disease characterized by a grim prognosis, in which various forms of cell death are significant contributors to its development. The objective of this study is to explore diagnostic biomarkers and molecular subtypes associated with PANoptosis in IPF, and to develop reliable diagnostic models based on PANoptosis-related mechanisms. The peripheral blood transcriptomic data of IPF from the Gene Expression Omnibus (GEO) database and PANoptosis-related genes from the GeneCards database were utilized to conduct differential gene expression analysis and weighted gene co-expression network analysis (WGCNA), identifying PANoptosis-related differentially expressed genes (PDEGs). We yielded 9 PDEGs and employed machine learning algorithms to identify 3 key diagnostic biomarkers for PANoptosis in IPF: MMP9, FCMR, NIBAN3. Consensus clustering algorithm was applied to recognize two PANoptosis-related subtypes. Cluster 1 exhibited higher abundance of adaptive immune response cells and significant enrichment in DNA damage and repair-related pathways. Cluster 2 exhibited greater prevalence of innate immune response cells and predominant enhancement in pathways related to lipid cholesterol metabolism and vascular remodeling. Diagnostic models were developed with the aid of clinical decision-making and a novel approach to the diagnosis and treatment for IPF.

Identification of immune patterns in idiopathic pulmonary fibrosis patients driven by PLA2G7-positive macrophages using an integrated machine learning survival framework

Patients with advanced idiopathic pulmonary fibrosis (IPF), a complex and incurable lung disease with an elusive pathology, are nearly exclusive candidates for lung transplantation. Improved identification of patient subtypes can enhance early diagnosis and intervention, ultimately leading to better prognostic outcomes for patients. The goal of this study is to identify new immune patterns and biomarkers in patients. Immune subtypes in IPF patients were identified using single-sample gene set enrichment analysis, and immune subtype-related genes were explored using the weighted correlation network analysis algorithm. A machine learning integration framework was used to establish the optimal prognostic model, known as the immune-related risk score (IRS). Single-cell sequencing was conducted to investigate the major role of macrophage-derived PLA2G7 in the immune microenvironment. We assessed the stability of celecoxib in targeting PLA2G7 through molecular docking and surface plasmon resonance. IPF patients present two distinct immune subtypes, one characterized by immune activation and inflammation, and the other by immune suppression. IRS can predict the immune status and prognosis of IPF patients. Furthermore, multi-cohort analysis and single-cell sequencing analysis demonstrated the diagnostic and prognostic value of PLA2G7 derived from macrophages and its role in shaping the inflammatory immune microenvironment in IPF patients. Celecoxib could effectively and stably bind with PLA2G7. PLA2G7, as identified through IRS, demonstrates marked stability in diagnosing and predicting the prognosis of IPF patients as well as predicting their immune status. It can serve as a novel biomarker for IPF patients.

Spatially resolved metabolomics visualizes heterogeneous distribution of metabolites in lung tissue and the anti-pulmonary fibrosis effect of Prismatomeris connate extract

Pulmonary fibrosis (PF) is a chronic progressive end-stage lung disease. However, the mechanisms underlying the progression of this disease remain elusive. Presently, clinically employed drugs are scarce for the treatment of PF. Hence, there is an urgent need for developing novel drugs to address such diseases. Our study found for the first time that a natural source of Prismatomeris connata Y. Z. Ruan (Huang Gen, HG) ethyl acetate extract (HG-2) had a significant anti-PF effect by inhibiting the expression of the transforming growth factor beta 1/suppressor of mothers against decapentaplegic (TGF-β1/Smad) pathway. Network pharmacological analysis suggested that HG-2 had effects on tyrosine kinase phosphorylation, cellular response to reactive oxygen species, and extracellular matrix (ECM) disassembly. Moreover, mass spectrometry imaging (MSI) was used to visualize the heterogeneous distribution of endogenous metabolites in lung tissue and reveal the anti-PF metabolic mechanism of HG-2, which was related to arginine biosynthesis and alanine, asparate and glutamate metabolism, the downregulation of arachidonic acid metabolism, and the upregulation of glycerophospholipid metabolism. In conclusion, we elaborated on the relationship between metabolite distribution and the progression of PF, constructed the regulatory metabolic network of HG-2, and discovered the multi-target therapeutic effect of HG-2, which might be conducive to the development of new drugs for PF.

Metabolic profiling of idiopathic pulmonary fibrosis in a mouse model: implications for pathogenesis and biomarker discovery

Background

Alterations in metabolites and metabolic pathways are thought to be important triggers of idiopathic pulmonary fibrosis (IPF), but our lack of a comprehensive understanding of this process has hampered the development of IPF-targeted drugs.

Methods

To fully understand the metabolic profile of IPF, C57BL/6 J male mice were injected intratracheally with bleomycin so that it could be used to construct a mouse model of IPF, and lung tissues from 28-day and control IPF mice were analyzed by pathology and immunohistochemistry. In addition, serum metabolites from IPF mice were examined using LC-ESI-MS/MS, and the differential metabolites were analyzed for KEGG metabolic pathways and screened for biomarkers using machine learning algorithms.

Results

In total, the levels of 1465 metabolites were detected, of which 104 metabolites were significantly altered after IPF formation. In IPF mouse serum, 52% of metabolite expression was downregulated, with lipids (e.g., GP, FA) and organic acids and their derivatives together accounting for more than 70% of the downregulated differentially expressed metabolites. In contrast, FA and oxidised lipids together accounted for 60% of the up-regulated differentially expressed metabolites. KEGG pathway enrichment analyses of differential metabolites were mainly enriched in the biosynthesis of unsaturated fatty acids, pentose phosphate pathway, and alanine, aspartate, and glutamate metabolism. Seven metabolites were screened by machine learning LASSO models and evaluated as ideal diagnostic tools by receiver operating characteristic curves (ROCs).

Discussion

In conclusion, the serum metabolic disorders found to be associated with pulmonary fibrosis formation will help to deepen our understanding of the pathogenesis of pulmonary fibrosis.

Exploring the causal effect between lipid-modifying drugs and idiopathic pulmonary fibrosis: a drug-target Mendelian randomization study

BACKGROUND

Idiopathic pulmonary fibrosis (IPF) is a respiratory disorder of obscure etiology and limited treatment options, possibly linked to dysregulation in lipid metabolism. While several observational studies suggest that lipid-lowering agents may decrease the risk of IPF, the evidence is inconsistent. The present Mendelian randomization (MR) study aims to determine the association between circulating lipid traits and IPF and to assess the potential influence of lipid-modifying medications for IPF.

METHODS

Summary statistics of 5 lipid traits (high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, triglyceride, apolipoprotein A, and apolipoprotein B) and IPF were sourced from the UK Biobank and FinnGen Project Round 10. The study's focus on lipid-regulatory genes encompassed PCSK9, NPC1L1, ABCG5, ABCG8, HMGCR, APOB, LDLR, CETP, ANGPTL3, APOC3, LPL, and PPARA. The primary effect estimates were determined using the inverse-variance-weighted method, with additional analyses employing the contamination mixture method, robust adjusted profile score, the weighted median, weighted mode methods, and MR-Egger. Summary-data-based Mendelian randomization (SMR) was used to confirm significant lipid-modifying drug targets, leveraging data on expressed quantitative trait loci in relevant tissues. Sensitivity analyses included assessments of heterogeneity, horizontal pleiotropy, and leave-one-out methods.

RESULTS

There was no significant effect of blood lipid traits on IPF risk (all P＞0.05). Drug-target MR analysis indicated that genetic mimicry for inhibitor of NPC1L1, PCSK9, ABCG5, ABCG8, and APOC3 were associated with increased IPF risks, with odds ratios (ORs) and 95% confidence intervals (CIs) as follows: 2.74 (1.05-7.12, P = 0.039), 1.36 (1.02-1.82, P = 0.037), 1.66 (1.12-2.45, P = 0.011), 1.68 (1.14-2.48, P = 0.009), and 1.42 (1.20-1.67, P = 3.17×10-5), respectively. The SMR method identified a significant association between PCSK9 gene expression in whole blood and reduced IPF risk (OR = 0.71, 95% CI: 0.50-0.99, P = 0.043). Sensitivity analyses showed no evidence of bias.

CONCLUSIONS

Serum lipid traits did not significantly affect the risk of idiopathic pulmonary fibrosis. Drug targets MR studies examining 12 lipid-modifying drugs indicated that PCSK9 inhibitors could dramatically increase IPF risk, a mechanism that may differ from their lipid-lowering actions and thus warrants further investigation.

Exploring ABHD5 as a Lipid-Related Biomarker in Idiopathic Pulmonary Fibrosis: Integrating Machine Learning, Bioinformatics, and In Vitro Experiments

Recent studies increasingly suggest a connection between lipids and idiopathic pulmonary fibrosis (IPF). This study was aimed at exploring potential lipid-related biomarkers for IPF and uncovering the mechanisms underlying pulmonary fibrosis. IPF-related datasets were retrieved from the GEO database, and the ComBat algorithm was used to merge multiple datasets and eliminate batch effects. Weighted gene co-expression network analysis (WGCNA) was utilized to identify modules and genes associated with IPF. Potential hub genes were determined by intersecting these genes with lipid-related genes from the GeneCards database. A machine learning-based integrative approach was developed to construct diagnostic and prognostic signatures, which were validated across several datasets. Additionally, single-cell sequencing data was used to validate the expression differences of core IPF-related genes across various cell types. The effect of ABHD5 on fibroblasts was assessed using the cell counting kit-8, 5-ethynyl-2'-deoxyuridine, and cell scratch assays. The expression levels of fibrotic factors were measured using real-time quantitative polymerase chain reaction and western blot analysis. WGCNA identified a red module potentially related to IPF, and the intersection with lipid-related genes yielded 51 hub genes. These genes were used to build diagnostic and prognostic models that demonstrated robust validation capabilities across multiple datasets. Single-cell sequencing analysis revealed low expression of ABHD5 in the lung tissues of IPF patients, with a higher proportion of fibroblasts exhibiting low ABHD5 expression. Cell experiments showed that under the influence of TGF-β1, knockdown of ABHD5 slightly promoted fibroblast proliferation. Additionally, fibroblasts with low ABHD5 expression exhibited enhanced migratory capabilities and secreted more fibrotic factors. Lipid-related diagnostic and prognostic models for IPF were developed, and ABHD5 may serve as a potential biomarker. Low ABHD5 expression could potentially accelerate the progression of pulmonary fibrosis.

Leveraging neighborhood representations of single-cell data to achieve sensitive DE testing with miloDE

Single-cell RNA-sequencing enables testing for differential expression (DE) between conditions at a cell type level. While powerful, one of the limitations of such approaches is that the sensitivity of DE testing is dictated by the sensitivity of clustering, which is often suboptimal. To overcome this, we present miloDE-a cluster-free framework for DE testing (available as an open-source R package). We illustrate the performance of miloDE on both simulated and real data. Using miloDE, we identify a transient hemogenic endothelia-like state in mouse embryos lacking Tal1 and detect distinct programs during macrophage activation in idiopathic pulmonary fibrosis.

Evaluating the impact of type 2 diabetes mellitus on pulmonary vascular function and the development of pulmonary fibrosis

The increasing prevalence of type 2 diabetes mellitus (T2DM) is a significant worldwide health concern caused by sedentary lifestyles and unhealthy diets. Beyond glycemic control, T2DM impacts multiple organ systems, leading to various complications. While traditionally associated with cardiovascular and microvascular complications, emerging evidence indicates significant effects on pulmonary health. Pulmonary vascular dysfunction and fibrosis, characterized by alterations in vascular tone and excessive extracellular matrix deposition, are increasingly recognized in individuals with T2DM. The onset of T2DM is often preceded by prediabetes, an intermediate hyperglycemic state that is associated with increased diabetes and cardiovascular disease risk. This review explores the relationship between T2DM, pulmonary vascular dysfunction and pulmonary fibrosis, with a focus on potential links with prediabetes. Pulmonary vascular function, including the roles of nitric oxide (NO), prostacyclin (PGI2), endothelin-1 (ET-1), thromboxane A2 (TxA2) and thrombospondin-1 (THBS1), is discussed in the context of T2DM and prediabetes. Mechanisms linking T2DM to pulmonary fibrosis, such as oxidative stress, dysregulated fibrotic signaling, and chronic inflammation, are explained. The impact of prediabetes on pulmonary health, including endothelial dysfunction, oxidative stress, and dysregulated vasoactive mediators, is highlighted. Early detection and intervention during the prediabetic stage may reduce respiratory complications associated with T2DM, emphasizing the importance of management strategies targeting blood glucose regulation and vascular health. More research that looks into the mechanisms underlying pulmonary complications in T2DM and prediabetes is needed.

Immune cells crosstalk Pathways, and metabolic alterations in Idiopathic pulmonary fibrosis

Idiopathic pulmonary fibrosis (IPF) presents a challenging progression characterized by lung tissue scarring and abnormal extracellular matrix deposition. This review examines the influence of immune responses, emphasizing their complex role in initiating and perpetuating fibrosis. It highlights how metabolic pathways modulate immune cell function during IPF. Immune cell modulation holds promise in managing pulmonary fibrosis (PF). Inhibiting neutrophil recruitment and monitoring mast cell levels offer insights into PF progression. Low-dose IL-2 therapy and regulation of fibroblast recruitment present potential therapeutic avenues, while the role of innate lymphoid cells (ILC2s) in allergic lung inflammation sheds light on disease mechanisms. The review focuses on metabolic reprogramming's role in shaping immune cell function during IPF progression. While some immune cells use glycolysis for pro-inflammatory responses, others favor fatty acid oxidation for regulatory functions. Targeting specialized pro-resolving lipid mediators (SPMs) presents significant potential for managing fibrotic disorders. Additionally, it highlights the pivotal role of amino acid metabolism in synthesizing serine and glycine as crucial regulators of collagen production and exploring the interconnectedness of lipid metabolism, mitochondrial dysfunction, and adipokines in driving fibrotic processes. Moreover, the review discusses the impact of metabolic disorders such as obesity and diabetes on lung fibrosis. Advocating for a holistic approach, it emphasizes the importance of considering this interplay between immune cell function and metabolic pathways in developing effective and personalized treatments for IPF.

Biomarkers in idiopathic pulmonary fibrosis: Current insight and future direction

Idiopathic pulmonary fibrosis (IPF) is a chronic and progressive interstitial lung disease with a dismal prognosis. Early diagnosis, accurate prognosis, and personalized therapeutic interventions are essential for improving patient outcomes. Biomarkers, as measurable indicators of biological processes or disease states, hold significant promise in IPF management. In recent years, there has been a growing interest in identifying and validating biomarkers for IPF, encompassing various molecular, imaging, and clinical approaches. This review provides an in-depth examination of the current landscape of IPF biomarker research, highlighting their potential applications in disease diagnosis, prognosis, and treatment response. Additionally, the challenges and future perspectives of biomarker integration into clinical practice for precision medicine in IPF are discussed.

Beyond the Acute Phase: Long-Term Impact of COVID-19 on Functional Capacity and Prothrombotic Risk-A Pilot Study

Background and Objectives: Assessment of the prothrombotic, proinflammatory, and functional status of a cohort of COVID-19 patients at least two years after the acute infection to identify parameters with potential therapeutic and prognostic value. Materials and Methods: We conducted a retrospective, descriptive study that included 117 consecutive patients admitted to Iasi Pulmonary Rehabilitation Clinic for reassessment and a rehabilitation program at least two years after a COVID-19 infection. The cohort was divided into two groups based on the presence (n = 49) or absence (n = 68) of pulmonary fibrosis, documented through high-resolution computer tomography. Results: The cohort comprises 117 patients, 69.23% females, with a mean age of 65.74 ± 10.19 years and abnormal body mass index (31.42 ± 5.71 kg/m2). Patients with pulmonary fibrosis have significantly higher levels of C-reactive protein (CRP) (p < 0.05), WBC (7.45 ± 7.86/mm3 vs. 9.18 ± 17.24/mm3, p = 0.053), neutrophils (4.68 ± 7.88/mm3 vs. 9.07 ± 17.44/mm3, p < 0.05), mean platelet volume (MPV) (7.22 ± 0.93 vs. 10.25 ± 0.86 fL, p < 0.05), lactate dehydrogenase (p < 0.05), and D-dimers (p < 0.05), but not ferritin (p = 0.470), reflecting the chronic proinflammatory and prothrombotic status. Additionally, patients with associated pulmonary fibrosis had a higher mean heart rate (p < 0.05) and corrected QT interval (p < 0.05). D-dimers were strongly and negatively correlated with diffusion capacity corrected for hemoglobin (DLCO corr), and ROC analysis showed that the persistence of high D-dimers values is a predictor for low DLCO values (ROC analysis: area under the curve of 0.772, p < 0.001). The results of pulmonary function tests (spirometry, body plethysmography) and the 6-minute walk test demonstrated no significant difference between groups, without notable impairment within either group. Conclusions: Patients with COVID-19-related pulmonary fibrosis have a persistent long-term proinflammatory, prothrombotic status, despite the functional recovery. The persistence of elevated D-dimer levels could emerge as a predictive factor associated with impaired DLCO.

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

Idiopathic pulmonary fibrosis (IPF) is a chronic progressive lung disease with reduced quality of life and earlier mortality, but its pathogenesis and key genes are still unclear. In this investigation, bioinformatics was used to deeply analyze the pathogenesis of IPF and related key genes, so as to investigate the potential molecular pathogenesis of IPF and provide guidance for clinical treatment. Next-generation sequencing dataset GSE213001 was obtained from Gene Expression Omnibus (GEO), and the differentially expressed genes (DEGs) were identified between IPF and normal control group. The DEGs between IPF and normal control group were screened with the DESeq2 package of R language. The Gene Ontology (GO) and REACTOME pathway enrichment analyses of the DEGs were performed. Using the g:Profiler, the function and pathway enrichment analyses of DEGs were performed. Then, a protein-protein interaction (PPI) network was constructed via the Integrated Interactions Database (IID) database. Cytoscape with Network Analyzer was used to identify the hub genes. miRNet and NetworkAnalyst databaseswereused to construct the targeted microRNAs (miRNAs), transcription factors (TFs), and small drug molecules. Finally, receiver operating characteristic (ROC) curve analysis was used to validate the hub genes. A total of 958 DEGs were screened out in this study, including 479 up regulated genes and 479 down regulated genes. Most of the DEGs were significantly enriched in response to stimulus, GPCR ligand binding, microtubule-based process, and defective GALNT3 causes HFTC. In combination with the results of the PPI network, miRNA-hub gene regulatory network and TF-hub gene regulatory network, hub genes including LRRK2, BMI1, EBP, MNDA, KBTBD7, KRT15, OTX1, TEKT4, SPAG8, and EFHC2 were selected. Cyclothiazide and rotigotinethe are predicted small drug molecules for IPF treatment. Our findings will contribute to identification of potential biomarkers and novel strategies for the treatment of IPF, and provide a novel strategy for clinical therapy.

Emerging opportunities to treat idiopathic pulmonary fibrosis: Design, discovery, and optimizations of small-molecule drugs targeting fibrogenic pathways

Idiopathic pulmonary fibrosis (IPF) is the most common fibrotic form of idiopathic diffuse lung disease. Due to limited treatment options, IPF patients suffer from poor survival. About ten years ago, Pirfenidone (Shionogi, 2008; InterMune, 2011) and Nintedanib (Boehringer Ingelheim, 2014) were approved, greatly changing the direction of IPF drug design. However, limited efficacy and side effects indicate that neither can reverse the process of IPF. With insights into the occurrence of IPF, novel targets and agents have been proposed, which have fundamentally changed the treatment of IPF. With the next-generation agents, targeting pro-fibrotic pathways in the epithelial-injury model offers a promising approach. Besides, several next-generation IPF drugs have entered phase II/III clinical trials with encouraging results. Due to the rising IPF treatment requirements, there is an urgent need to completely summarize the mechanisms, targets, problems, and drug design strategies over the past ten years. In this review, we summarize known mechanisms, target types, drug design, and novel technologies of IPF drug discovery, aiming to provide insights into the future development and clinical application of next-generation IPF drugs.

Longitudinal assessment of bleomycin-induced pulmonary fibrosis by evaluating TGF-β1/Smad2, Nrf2 signaling and metabolomic analysis in mice

INTRODUCTION

Pulmonary fibrosis (PF) is characterized by an increase in collagen synthesis and deposition of extracellular matrix. Several factors, including transforming growth factor-β1 (TGF-β1), mothers against decapentaplegic homolog family proteins (Smad), and alpha-smooth muscle actin (α-SMA) trigger extracellular matrix (ECM) accumulation, fibroblast to myofibroblasts conversion, and epithelial-to-mesenchymal-transition (EMT) leading to PF. However, the role of cellular defense mechanisms such as the role of nuclear factor erythroid 2-related factor 2 (Nrf2) signaling during the onset and progression of PF is not understood completely.

AIM

The present study aims to analyze the involvement of TGF-β1/Smad signaling, and Nrf2 in the EMT and metabolic alterations that promote fibrosis in a time-dependent manner using bleomycin (BLM)-induced PF model in C57BL/6 mice.

KEY FINDINGS

Histopathological studies revealed loss of lung architecture and increased collagen deposition in BLM-exposed mice. BLM upregulated TGF-β1/Smad signaling and α-SMA at all time-points. The gradual increase in the accumulation of α-SMA and collagen implied the progression of PF. BLM exposure raises Nrf2 throughout each specified time-point, which suggests that Nrf2 activation might be responsible for TGF-β1-induced EMT and the development of PF. Further, metabolomic studies linked the development of PF to alterations in metabolic pathways. The pentose phosphate pathway (PPP) was consistently enriched across all the time-points. Additionally, alterations in 22 commonly enriched pathways, associated with fatty acid (FA) and amino acid metabolism were observed in 30- and 60-days.

SIGNIFICANCE

This study elucidates the association of TGF-β1/Smad and Nrf2 signaling in the EMT and metabolic alterations associated with the etiology and progression of PF.