Heterogeneous gene expression signatures correspond to distinct lung pathologies and biomarkers of disease severity in idiopathic pulmonary fibrosis

Noninvasive assessment of the lung inflammation-fibrosis axis by targeted imaging of CMKLR1

Precision management of fibrotic lung diseases is challenging due to their diverse clinical trajectories and lack of reliable biomarkers for risk stratification and therapeutic monitoring. Here, we validated the accuracy of CMKLR1 as an imaging biomarker of the lung inflammation-fibrosis axis. By analyzing single-cell RNA sequencing datasets, we demonstrated CMKLR1 expression as a transient signature of monocyte-derived macrophages (MDMφ) enriched in patients with idiopathic pulmonary fibrosis (IPF). Consistently, we identified MDMφ as the major driver of the uptake of CMKLR1-targeting peptides in a murine model of bleomycin-induced lung fibrosis. Furthermore, CMKLR1-targeted positron emission tomography in the murine model enabled quantification and spatial mapping of inflamed lung regions infiltrated by CMKLR1-expressing macrophages and emerged as a robust predictor of subsequent lung fibrosis. Last, high CMKLR1 expression by bronchoalveolar lavage cells identified an inflammatory endotype of IPF with poor survival. Our investigation supports the potential of CMKLR1 as an imaging biomarker for endotyping and risk stratification of fibrotic lung diseases.

Unveiling the role of copper metabolism and STEAP2 in idiopathic pulmonary fibrosis molecular landscape

Idiopathic pulmonary fibrosis (IPF) is a debilitating interstitial lung disease characterized by progressive fibrosis and poor prognosis. Despite advancements in treatment, the pathophysiological mechanisms of IPF remain elusive. Herein, we conducted an integrated bioinformatics analysis combining clinical data and carried out experimental validations to unveil the intricate molecular mechanism of IPF. Leveraging three IPF datasets, we identified 817 upregulated and 560 downregulated differentially expressed genes (DEGs). Of these, 14 DEGs associated with copper metabolism were identified, shedding light on the potential involvement of disrupted copper metabolism in IPF progression. Immune infiltration analysis revealed dysregulated immune cell infiltration in IPF, with a notable correlation between copper metabolism-related genes and immune cells. Weighted gene co-expression network analysis (WGCNA) identified a central module correlated with IPF-associated genes, among which STEAP2 emerged as a key hub gene. Subsequent in vivo and in vitro studies confirmed the upregulation of STEAP2 in IPF model. Knockdown of STEAP2 using siRNA alleviated fibrosis in vitro, suggesting potential pathway related to copper metabolism in the pathophysiological progression of IPF. Our study established a novel link between immune cell infiltration and dysregulated copper metabolism. The revelation of intracellular copper overload and upregulated STEAP2 unravelled a potential therapeutic option. These findings offer valuable insights for future research and therapeutic interventions targeting STEAP2 and associated pathways in IPF.

Plausible role of INPP4A dysregulation in idiopathic pulmonary fibrosis

INPP4A has been shown to be involved in the regulation of cell proliferation and apoptosis of multiple cell types including fibroblasts. Previous reports from our group have demonstrated the role of inositol polyphosphate 4-phosphatase Type I A (INPP4A) in these functions. Though existing evidences suggest a critical role for INPP4A in the maintenance of lung homeostasis, its role in chronic lung diseases is relatively under explored. In the current study, we made an attempt to understand the regulation of INPP4A in idiopathic pulmonary fibrosis (IPF). Through integration of relevant INPP4A gene expression data from public repositories with our results from in vitro experiments and mouse models, we show that INPP4A is altered in IPF. Interestingly, the direction of the change is dependent both on the disease stage and the region of the lung used. INPP4A was found to be upregulated when analyzed in lung sample representative of the whole lung, but was downregulated in the fibrotic regions of the lung. Similarly, INPP4A was found to be high, compared to controls, only in the early stage of the disease. Though the observed increase in INPP4A was found to be negatively correlated to physiological indices, FVC, and DLCO, of lung function, treatment with anti-INPP4A antibody worsened the condition in bleomycin treated mice. These contrasting results taken together are suggestive of a nuanced regulation of INPP4A in IPF which is dependent on the disease stage, cellular state and extent of fibrosis in the lung region being analyzed.

Idiopathic pulmonary fibrosis (IPF): Diagnostic routes using novel biomarkers

Idiopathic pulmonary fibrosis (IPF) diagnosis is still the diagnosis of exclusion. Differentiating from other forms of interstitial lung diseases (ILDs) is essential, given the various therapeutic approaches. The IPF course is now unpredictable for individual patients, although some genetic factors and several biomarkers have already been associated with various IPF prognoses. Since its early stages, IPF may be asymptomatic, leading to a delayed diagnosis. The present review critically examines the recent literature on molecular biomarkers potentially useful in IPF diagnostics. The examined biomarkers are grouped into breath and sputum biomarkers, serologically assessed extracellular matrix neoepitope markers, and oxidative stress biomarkers in lung tissue. Fibroblasts and complete blood count have also gained recent interest in that respect. Although several biomarker candidates have been profiled, there has yet to be a single biomarker that proved specific to the IPF disease. Nevertheless, various IPF biomarkers have been used in preclinical and clinical trials to verify their predictive and monitoring potential.

Discovery of common molecular signatures and drug repurposing for COVID-19/Asthma comorbidity: ACE2 and multi-partite networks

Angiotensin-converting enzyme 2 (ACE2) is identified as the functional receptor for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of the ongoing global coronavirus disease-2019 (COVID-19) pandemic. This study aimed to elucidate potential therapeutic avenues by scrutinizing approved drugs through the identification of the genetic signature associated with SARS-CoV-2 infection in individuals with asthma. This exploration was conducted through an integrated analysis, encompassing interaction networks between the ACE2 receptor and common host (co-host) factors implicated in COVID-19/asthma comorbidity. The comprehensive analysis involved the identification of common differentially expressed genes (cDEGs) and hub-cDEGs, functional annotations, interaction networks, gene set variation analysis (GSVA), gene set enrichment analysis (GSEA), and module construction. Interaction networks were used to identify overlapping disease modules and potential drug targets. Computational biology and molecular docking analyzes were utilized to discern functional drug modules. Subsequently, the impact of the identified drugs on the expression of hub-cDEGs was experimentally validated using a mouse model. A total of 153 cDEGs or co-host factors associated with ACE2 were identified in the COVID-19 and asthma comorbidity. Among these, seven significant cDEGs and proteins - namely, HRAS, IFNG, JUN, CDH1, TLR4, ICAM1, and SCD-were recognized as pivotal host factors linked to ACE2. Regulatory network analysis of hub-cDEGs revealed eight top-ranked transcription factors (TFs) proteins and nine microRNAs as key regulatory factors operating at the transcriptional and post-transcriptional levels, respectively. Molecular docking simulations led to the proposal of 10 top-ranked repurposable drug molecules (Rapamycin, Ivermectin, Everolimus, Quercetin, Estradiol, Entrectinib, Nilotinib, Conivaptan, Radotinib, and Venetoclax) as potential treatment options for COVID-19 in individuals with comorbid asthma. Validation analysis demonstrated that Rapamycin effectively inhibited ICAM1 expression in the HDM-stimulated mice group (p < 0.01). This study unveils the common pathogenesis and genetic signature underlying asthma and SARS-CoV-2 infection, delineated by the interaction networks of ACE2-related host factors. These findings provide valuable insights for the design and discovery of drugs aimed at more effective therapeutics within the context of lung disease comorbidities.

Circulating biomarker analyses in a longitudinal cohort of patients with IPF

Idiopathic pulmonary fibrosis (IPF) is an incurable interstitial lung disease characterized by fibrosis. Two FDA-approved drugs, pirfenidone and nintedanib, only modestly prolong survival. In this study, we asked whether levels of select circulating biomarkers in patients with IPF demonstrated changes in response to treatment over time and whether treatment with pirfenidone and nintedanib led to differential biomarker expression. Serial plasma samples from 48 patients with IPF on usual treatment and six healthy volunteers were analyzed to identify differentially expressed blood protein. Hypothesis-driven potential biomarker selection was based on recent literature, internal preclinical data, and the PROLIFIC Consortium (Schafer P. 6th Annual IPF Summit. Boston, MA, 2022) proposed biomarkers of pulmonary fibrosis. We compared our findings to public databases to provide insights into relevant signaling pathways in IPF. Of the 26 proteins measured, we found that 11 (SP-D, TIMP1, MMP7, CYFRA21-1, YKL40, CA125, sICAM, IP-10, MDC, CXCL13) were significantly elevated in patients with IPF compared with healthy volunteers but their levels did not significantly change over time. In the IPF samples, seven proteins were elevated in the treatment group compared with the no-treatment group. However, protein profiles were not distinguishable between patients on pirfenidone versus nintedanib. We demonstrated that most proteins differentially detected in our samples were predicted to be secreted from the lung epithelial or interstitial compartments. However, a significant minority of the proteins are not known to be transcriptionally expressed by lung cells, suggesting an ongoing systemic response. Understanding the contributions of the systemic response in IPF may be important as new therapeutics are developed.NEW & NOTEWORTHY In this study, we confirmed protein expression differences in only a subset of predicted biomarkers from IPF and control subjects. Most differentially expressed proteins were predicted to be secreted from lung cells. However, a significant minority of the proteins are not known to be transcriptionally expressed by lung cells, suggesting an ongoing systemic response. The contributions of the systemic response in IPF may be important as new therapeutics are developed.

Epithelial IL5RA promotes epithelial-mesenchymal transition in pulmonary fibrosis via Jak2/STAT3 cascade

Pulmonary fibrosis is a progressive and debilitating lung disease characterized by the excessive accumulation of extracellular matrix (ECM) components within the lung parenchyma. However, the underlying mechanism remains largely elusive, and the treatment options available for pulmonary fibrosis are limited. Interleukin 5 receptor, alpha (IL5RA) is a well-established regulator of eosinophil activation, involved in eosinophil-mediated anti-parasitic activities and allergic reactions. Recent studies have indicated additional roles of IL5RA in lung epithelium and fibroblasts. Nevertheless, its involvement in pulmonary fibrosis remains unclear. In present study, we employed single-cell analyses alongside molecular and cellular assays to unveil the expression of IL5RA in lung epithelial cells. Moreover, using both in vitro and in vivo models, we demonstrated a notable upregulation of epithelial IL5RA during the progression of pulmonary fibrosis. This upregulated IL5RA expression subsequently promotes epithelial-mesenchymal transition (EMT), leading to the generation of mesenchymal phenotype with augmented capability for ECM production. Importantly, our findings uncovered that the pro-fibrotic function of IL5RA is mediated by Jak2/STAT3 signaling cascades. Inhibiting IL5RA has the potential to deactivate Jak2/STAT3 and suppress the downstream EMT process and ECM production, thereby offering a promising therapeutic strategy for pulmonary fibrosis.

The mechanism of gut-lung axis in pulmonary fibrosis

Pulmonary fibrosis (PF) is a terminal change of a lung disease that is marked by damage to alveolar epithelial cells, abnormal proliferative transformation of fibroblasts, excessive deposition of extracellular matrix (ECM), and concomitant inflammatory damage. Its characteristics include short median survival, high mortality rate, and limited treatment effectiveness. More in-depth studies on the mechanisms of PF are needed to provide better treatment options. The idea of the gut-lung axis has emerged as a result of comprehensive investigations into the microbiome, metabolome, and immune system. This theory is based on the material basis of microorganisms and their metabolites, while the gut-lung circulatory system and the shared mucosal immune system act as the connectors that facilitate the interplay between the gastrointestinal and respiratory systems. The emergence of a new view of the gut-lung axis is complementary and cross-cutting to the study of the mechanisms involved in PF and provides new ideas for its treatment. This article reviews the mechanisms involved in PF, the gut-lung axis theory, and the correlation between the two. Exploring the gut-lung axis mechanism and treatments related to PF from the perspectives of microorganisms, microbial metabolites, and the immune system. The study of the gut-lung axis and PF is still in its early stages. This review systematically summarizes the mechanisms of PF related to the gut-lung axis, providing ideas for subsequent research and treatment of related mechanisms.

Genome-wide SNP-sex interaction analysis of susceptibility to idiopathic pulmonary fibrosis

Background

Idiopathic pulmonary fibrosis (IPF) is a chronic lung condition that is more prevalent in males than females. The reasons for this are not fully understood, with differing environmental exposures due to historically sex-biased occupations, or diagnostic bias, being possible explanations. To date, over 20 independent genetic variants have been identified to be associated with IPF susceptibility, but these have been discovered when combining males and females. Our aim was to test for the presence of sex-specific associations with IPF susceptibility and assess whether there is a need to consider sex-specific effects when evaluating genetic risk in clinical prediction models for IPF.

Methods

We performed genome-wide single nucleotide polymorphism (SNP)-by-sex interaction studies of IPF risk in six independent IPF case-control studies and combined them using inverse-variance weighted fixed effect meta-analysis. In total, 4,561 cases (1,280 females and 2,281 males) and 23,500 controls (8,360 females and 14,528 males) of European genetic ancestry were analysed. We used polygenic risk scores (PRS) to assess differences in genetic risk prediction between males and females.

Findings

Three independent genetic association signals were identified. All showed a consistent direction of effect across all individual IPF studies and an opposite direction of effect in IPF susceptibility between females and males. None had been previously identified in IPF susceptibility genome-wide association studies (GWAS). The predictive accuracy of the PRSs were similar between males and females, regardless of whether using combined or sex-specific GWAS results.

Interpretation

We prioritised three genetic variants whose effect on IPF risk may be modified by sex, however these require further study. We found no evidence that the predictive accuracy of common SNP-based PRSs varies significantly between males and females.

Hydrogen sulfide inhibits alveolar type II cell senescence and limits pulmonary fibrosis via promoting MDM2-mediated p53 degradation

AIM

Senescence of alveolar type II (AT2) cells is an important driver of pulmonary fibrosis. This study aimed to investigate whether and how dysregulation of hydrogen sulfide (H2 S) production affected AT2 cell senescence, and then explored the effect of H2 S on the communication between AT2 and fibroblasts.

METHODS

ICR mice were intratracheally administered with bleomycin (3 mg/kg). Sodium hydrosulfide (NaHS, 28 μmol/kg/d) was intraperitoneally injected for 2 weeks. The H2 S-generating enzyme cystathionine-β-synthase (CBS) knockout heterozygous (CBS+/- ) mice were used as a low H2 S production model.

RESULTS

Analysis of microarray datasets revealed downregulation of H2 S-generating enzymes in lung tissues of patients with pulmonary fibrosis. Decreased H2 S production was correlated with higher levels of cell senescence markers p53 and p21 in bleomycin-induced lung fibrosis. CBS+/- mice exhibited increased levels of p53 and p21. The numbers of AT2 cells positive for p53 and p21 were increased in CBS+/- mice as compared to control mice. H2 S donor NaHS attenuated bleomycin-induced AT2 cell senescence both in vivo and in vitro. H2 S donor suppressed bleomycin-induced senescence-associated secretory phenotype (SASP) of AT2 cells via inhibiting p53/p21 pathway, consequently suppressing proliferation and myofibroblast transdifferentiation of fibroblasts. Mechanically, H2 S suppressed p53 expression by enhancing the mouse double-minute 2 homologue (MDM2)-mediated ubiquitination and degradation of p53.

CONCLUSION

H2 S inactivated p53-p21 pathway, consequently suppressing AT2 cell senescence as well as cell communication between senescent AT2 cells and fibroblasts. Aberrant H2 S synthesis may contribute to the development of pulmonary fibrosis through promoting the activation loop involving senescent AT2 cells and activated fibroblasts.

Unagi: Deep Generative Model for Deciphering Cellular Dynamics and In-Silico Drug Discovery in Complex Diseases

Human diseases are characterized by intricate cellular dynamics. Single-cell sequencing provides critical insights, yet a persistent gap remains in computational tools for detailed disease progression analysis and targeted in-silico drug interventions. Here, we introduce UNAGI, a deep generative neural network tailored to analyze time-series single-cell transcriptomic data. This tool captures the complex cellular dynamics underlying disease progression, enhancing drug perturbation modeling and discovery. When applied to a dataset from patients with Idiopathic Pulmonary Fibrosis (IPF), UNAGI learns disease-informed cell embeddings that sharpen our understanding of disease progression, leading to the identification of potential therapeutic drug candidates. Validation via proteomics reveals the accuracy of UNAGI's cellular dynamics analyses, and the use of the Fibrotic Cocktail treated human Precision-cut Lung Slices confirms UNAGI's predictions that Nifedipine, an antihypertensive drug, may have antifibrotic effects on human tissues. UNAGI's versatility extends to other diseases, including a COVID dataset, demonstrating adaptability and confirming its broader applicability in decoding complex cellular dynamics beyond IPF, amplifying its utility in the quest for therapeutic solutions across diverse pathological landscapes.

PTK2-associated gene signature could predict the prognosis of IPF

Idiopathic pulmonary fibrosis (IPF) is a progressive and fatal lung disease with a poor prognosis. Current/available clinical prediction tools have limited sensitivity and accuracy when evaluating clinical outcomes of IPF. Research has shown that focal adhesion kinase (FAK), produced by the protein tyrosine kinase 2 (PTK2) gene, is crucial in IPF development. FAK activation is a characteristic of lesional fibroblasts; Thus, FAK may be a valuable therapeutic target or prognostic biomarker for IPF. This study aimed to create a gene signature based on PTK2-associated genes and microarray data from blood cells to predict disease prognosis in patients with IPF. PTK2 levels were found to be higher in lung tissues of IPF patients compared to healthy controls, and PTK2 inhibitor Defactinib was found to reduce TGFβ-induced FAK activation and increase α-smooth muscle actin. Although the blood PTK2 levels were higher in IPF patients, blood PTK level alone could not predict IPF prognosis. From 196 PTK2-associated genes, 11 genes were prioritized to create a gene signature (PTK2 molecular signature) and a risk score system using univariate and multivariate Cox regression analysis. Patients were divided into high-risk and low-risk groups using PTK2 molecular signature. Patients in the high-risk group experienced decreased survival rates compared to patients in the low-risk group across all discovery and validation cohorts. Further functional enrichment and immune cell proportion analyses revealed that the PTK2 molecular signature strongly reflected the activation levels of immune pathways and immune cells. These findings suggested that PTK2 is a molecular target of IPF and the PTK2 molecular signature is an effective IPF prognostic biomarker.

Emerging role of immune cells as drivers of pulmonary fibrosis

The pathogenesis of pulmonary fibrosis, including idiopathic pulmonary fibrosis (IPF) and other forms of interstitial lung disease, involves a complex interplay of various factors including host genetics, environmental pollutants, infection, aberrant repair and dysregulated immune responses. Highly variable clinical outcomes of some ILDs, in particular IPF, have made it difficult to identify the precise mechanisms involved in disease pathogenesis and thus the development of a specific cure or treatment to halt and reverse the decline in patient health. With the advent of in-depth molecular diagnostics, it is becoming evident that the pathogenesis of IPF is unlikely to be the same for all patients and therefore will likely require different treatment approaches. Chronic inflammation is a cardinal feature of IPF and is driven by both innate and adaptive immune responses. Inflammatory cells and activated fibroblasts secrete various pro-inflammatory cytokines and chemokines that perpetuate the inflammatory response and contribute to the recruitment and activation of more immune cells and fibroblasts. The balance between pro-inflammatory and regulatory immune cell subsets, as well as the interactions between immune cell types and resident cells within the lung microenvironment, ultimately determines the extent of fibrosis and the potential for resolution. This review examines the role of the innate and adaptive immune responses in pulmonary fibrosis, with an emphasis on IPF. The role of different immune cell types is discussed as well as novel anti-inflammatory and immunotherapy approaches currently in clinical trial or in preclinical development.

Homeostatic chemokines as putative therapeutic targets in idiopathic pulmonary fibrosis

Idiopathic pulmonary fibrosis (IPF) is a fatal chronic interstitial lung disease (ILD) that affects lung mechanical functions and gas exchange. IPF is caused by increased fibroblast activity and collagen deposition that compromise the alveolar-capillary barrier. Identifying an effective therapy for IPF remains a clinical challenge. Chemokines are key proteins in cell communication that have functions in immunity as well as in tissue homeostasis, damage, and repair. Chemokine receptor signaling induces the activation and proliferation of lung-resident cells, including alveolar macrophages (AMs) and fibroblasts. AMs are an important source of chemokines and cytokines during IPF. We highlight the complexity of this system and, based on insights from genetic and transcriptomic studies, propose a new role for homeostatic chemokine imbalance in IPF, with implications for putative therapeutic targets.

Combining single-cell RNA sequencing data and transcriptomic data to unravel potential mechanisms and signature genes of the progression of idiopathic pulmonary fibrosis to lung adenocarcinoma and predict therapeutic agents

Patients with idiopathic pulmonary fibrosis (IPF) have a significantly higher prevalence of lung adenocarcinoma (LUAD) than normal subjects, although the underlying association is unclear. The raw data involved were obtained from the Gene Expression Omnibus (GEO) database. Differential expression analysis and weighted gene co-expression network analysis were used to screen for differentially expressed genes (DEGs) and modular signature genes (MSGs). Genes intersecting DEGs and MSGs were considered hub genes for IPF and LUAD. Machine learning algorithms were applied to capture epithelial cell-derived signature genes (EDSGs) shared. External cohort data were exploited to validate the robustness of EDSGs. Immunohistochemical staining and K-M plots were used to denote the prognostic value of EDSGs in LUAD. Based on EDSGs, we constructed a TF-gene-miRNA regulatory network. Molecular docking can validate the strength of action between candidate drugs and EDSGs. Epithelial cells, 650 DEGs, and 1773 MSGs were shared by IPF and LUAD. As for 379 hub genes, we performed pathway and functional enrichment analysis. By analyzing sc-RNA seq data, we identified 1234 marker genes of IPF epithelial cell-derived and 1481 of LUAD. And these genes shared 8 items with 379 hub genes. Through the machine learning algorithms, we further fished TRIM2, S100A14, CYP4B1, LMO7, and SFN. The ROC curves emphasized the significance of EDSGs in predicting the onset of LUAD and IPF. The TF-gene-miRNA network revealed regulatory relationships behind EDSGs. Finally, we predicted appropriate therapeutic agents. Our study preliminarily identified potential mechanisms between IPF and LUAD, which will inform subsequent studies.

Machine learning identified MDK score has prognostic value for idiopathic pulmonary fibrosis based on integrated bulk and single cell expression data

Idiopathic pulmonary fibrosis (IPF) is a progressive and fatal lung disease that poses a significant challenge to medical professionals due to its increasing incidence and prevalence coupled with the limited understanding of its underlying molecular mechanisms. In this study, we employed a novel approach by integrating five expression datasets from bulk tissue with single-cell datasets; they underwent pseudotime trajectory analysis, switch gene selection, and cell communication analysis. Utilizing the prognostic information derived from the GSE47460 dataset, we identified 22 differentially expressed switch genes that were correlated with clinical indicators as important genes. Among these genes, we found that the midkine (MDK) gene has the potential to serve as a marker of Idiopathic pulmonary fibrosis because its cellular communicating genes are differentially expressed in the epithelial cells. We then utilized midkine and its cellular communication-related genes to calculate the midkine score. Machine learning models were further constructed through midkine and related genes to predict Idiopathic pulmonary fibrosis disease through the bulk gene expression datasets. The midkine score demonstrated a correlation with clinical indexes, and the machine learning model achieved an AUC of 0.94 and 0.86 in the Idiopathic pulmonary fibrosis classification task based on lung tissue samples and peripheral blood mononuclear cell samples, respectively. Our findings offer valuable insights into the pathogenesis of Idiopathic pulmonary fibrosis, providing new therapeutic directions and target genes for further investigation.

Identification of the shared gene signatures between pulmonary fibrosis and pulmonary hypertension using bioinformatics analysis

Pulmonary fibrosis (PF) and pulmonary hypertension (PH) have common pathophysiological features, such as the significant remodeling of pulmonary parenchyma and vascular wall. There is no effective specific drug in clinical treatment for these two diseases, resulting in a worse prognosis and higher mortality. This study aimed to screen the common key genes and immune characteristics of PF and PH by means of bioinformatics to find new common therapeutic targets. Expression profiles are downloaded from the Gene Expression Database. Weighted gene co-expression network analysis is used to identify the co-expression modules related to PF and PH. We used the ClueGO software to enrich and analyze the common genes in PF and PH and obtained the protein-protein interaction (PPI) network. Then, the differential genes were screened out in another cohort of PF and PH, and the shared genes were crossed. Finally, RT-PCR verification and immune infiltration analysis were performed on the intersection genes. In the result, the positive correlation module with the highest correlation between PF and PH was determined, and it was found that lymphocyte activation is a common feature of the pathophysiology of PF and PH. Eight common characteristic genes (ACTR2, COL5A2, COL6A3, CYSLTR1, IGF1, RSPO3, SCARNA17 and SEL1L) were gained. Immune infiltration showed that compared with the control group, resting CD4 memory T cells were upregulated in PF and PH. Combining the results of crossing characteristic genes in ImmPort database and RT-PCR, the important gene IGF1 was obtained. Knocking down IGF1 could significantly reduce the proliferation and apoptosis resistance in pulmonary microvascular endothelial cells, pulmonary smooth muscle cells, and fibroblasts induced by hypoxia, platelet-derived growth factor-BB (PDGF-BB), and transforming growth factor-β1 (TGF-β1), respectively. Our work identified the common biomarkers of PF and PH and provided a new candidate gene for the potential therapeutic targets of PF and PH in the future.

Anti-UBE2T antibody: A novel biomarker of progressive-fibrosing interstitial lung disease

BACKGROUND

Anti-fibrotic therapy has demonstrated efficacy against progressive-fibrosing interstitial lung disease (PF-ILD); therefore, identifying disease behavior before progression has become a priority. As autoimmunity is implicated in the pathogenesis of various ILDs, this study explored circulating biomarkers that could predict the chronic progressive behavior of ILDs.

METHODS

A single-center retrospective cohort study was conducted. Circulating autoantibodies in patients with ILD were screened using microarray analysis to identify candidate biomarkers. An enzyme-linked immunosorbent assay was performed with a larger sample set for the quantification of antibodies. After 2 years of follow-up, ILDs were reclassified as PF or non-PF. The relationship between the participants' autoantibody levels measured at enrolment and final diagnosis of PF-ILD was determined.

RESULTS

In total, 61 healthy participants and 66 patients with ILDs were enrolled. Anti-ubiquitin-conjugating enzyme E2T (UBE2T) antibody was detected as a candidate biomarker. Anti-UBE2T antibody levels were elevated in patients with idiopathic pulmonary fibrosis (IPF). After following up on the study participants for 2 years, anti-UBE2T levels measured at enrolment significantly correlated with the new PF-ILD diagnosis. Immunohistochemical staining of normal lung tissues revealed sparsely located UBE2T in the bronchiole epithelium and macrophages, whereas IPF lung tissues showed robust expression in the epithelial lining of honeycomb structures.

CONCLUSION

To our knowledge, this is the first report to describe an anti-UBE2T antibody, a new biomarker that is significantly elevated in patients with ILD who present future disease progression.

Identifying oxidative stress-related biomarkers in idiopathic pulmonary fibrosis in the context of predictive, preventive, and personalized medicine using integrative omics approaches and machine-learning strategies

Background

Idiopathic pulmonary fibrosis (IPF) is a rare interstitial lung disease with a poor prognosis that currently lacks effective treatment methods. Preventing the acute exacerbation of IPF, identifying the molecular subtypes of patients, providing personalized treatment, and developing individualized drugs are guidelines for predictive, preventive, and personalized medicine (PPPM / 3PM) to promote the development of IPF. Oxidative stress (OS) is an important pathological process of IPF. However, the relationship between the expression levels of oxidative stress-related genes (OSRGs) and clinical indices in patients with IPF is unclear; therefore, it is still a challenge to identify potential beneficiaries of antioxidant therapy. Because PPPM aims to recognize and manage diseases by integrating multiple methods, patient stratification and analysis based on OSRGs and identifying biomarkers can help achieve the above goals.

Methods

Transcriptome data from 250 IPF patients were divided into training and validation sets. Core OSRGs were identified in the training set and subsequently clustered to identify oxidative stress-related subtypes. The oxidative stress scores, clinical characteristics, and expression levels of senescence-associated secretory phenotypes (SASPs) of different subtypes were compared to identify patients who were sensitive to antioxidant therapy to conduct differential gene functional enrichment analysis and predict potential therapeutic drugs. Diagnostic markers between subtypes were obtained by integrating multiple machine learning methods, their expression levels were tested in rat models with different degrees of pulmonary fibrosis and validation sets, and nomogram models were constructed. CIBERSORT, single-cell RNA sequencing, and immunofluorescence staining were used to explore the effects of OSRGs on the immune microenvironment.

Results

Core OSRGs classified IPF into two subtypes. Patients classified into subtypes with low oxidative stress levels had better clinical scores, less severe fibrosis, and lower expression of SASP-related molecules. A reliable nomogram model based on five diagnostic markers was constructed, and these markers' expression stability was verified in animal experiments. The number of neutrophils in the immune microenvironment was significantly different between the two subtypes and was closely related to the degree of fibrosis.

Conclusion

Within the framework of PPPM, this work comprehensively explored the role of OSRGs and their mediated cellular senescence and immune processes in the progress of IPF and assessed their capabilities aspredictors of high oxidative stress and disease progression,targets of the vicious loop between regulated pulmonary fibrosis and OS for targeted secondary and tertiary prevention, andreferences for personalized antioxidant and antifibrotic therapies.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-023-00334-4.

Time-course transcriptome analysis of a double challenge bleomycin-induced lung fibrosis rat model uncovers ECM homoeostasis-related translationally relevant genes

BACKGROUND

Idiopathic pulmonary fibrosis (IPF) is an irreversible disorder with a poor prognosis. The incomplete understanding of IPF pathogenesis and the lack of accurate animal models is limiting the development of effective treatments. Thus, the selection of clinically relevant animal models endowed with similarities with the human disease in terms of lung anatomy, cell biology, pathways involved and genetics is essential. The bleomycin (BLM) intratracheal murine model is the most commonly used preclinical assay to evaluate new potential therapies for IPF. Here, we present the findings derived from an integrated histomorphometric and transcriptomic analysis to investigate the development of lung fibrosis in a time-course study in a BLM rat model and to evaluate its translational value in relation to IPF.

METHODS

Rats were intratracheally injected with a double dose of BLM (days 0-4) and sacrificed at days 7, 14, 21, 28 and 56. Histomorphometric analysis of lung fibrosis was performed on left lung sections. Transcriptome profiling by RNAseq was performed on the right lung lobes and results were compared with nine independent human gene-expression IPF studies.

RESULTS

The histomorphometric and transcriptomic analyses provided a detailed overview in terms of temporal gene-expression regulation during the establishment and repair of the fibrotic lesions. Moreover, the transcriptomic analysis identified three clusters of differentially coregulated genes whose expression was modulated in a time-dependent manner in response to BLM. One of these clusters, centred on extracellular matrix (ECM)-related process, was significantly correlated with histological parameters and gene sets derived from human IPF studies.

CONCLUSIONS

The model of lung fibrosis presented in this study lends itself as a valuable tool for preclinical efficacy evaluation of new potential drug candidates. The main finding was the identification of a group of persistently dysregulated genes, mostly related to ECM homoeostasis, which are shared with human IPF.

Precision medicine advances in idiopathic pulmonary fibrosis

Idiopathic pulmonary fibrosis (IPF) is a highly heterogeneous, unpredictable and ultimately lethal chronic lung disease. Over the last decade, two anti-fibrotic agents have been shown to slow disease progression, however, both drugs are administered uniformly with minimal consideration of disease severity and inter-individual molecular, genetic, and genomic differences. Advances in biological understanding of disease endotyping and the emergence of precision medicine have shown that "a one-size-fits-all approach" to the management of chronic lung diseases is no longer appropriate. While precision medicine approaches have revolutionized the management of other diseases such as lung cancer and asthma, the implementation of precision medicine in IPF clinical practice remains an unmet need despite several reports demonstrating a large number of diagnostic, prognostic and theragnostic biomarker candidates in IPF. This review article aims to summarize our current knowledge of precision medicine in IPF and highlight barriers to translate these research findings into clinical practice.

Underlying Molecular Mechanism and Construction of a miRNA-Gene Network in Idiopathic Pulmonary Fibrosis by Bioinformatics

Idiopathic pulmonary fibrosis (IPF) is a chronic, progressive lung disease, but its pathogenesis is still unclear. Bioinformatics methods were used to explore the differentially expressed genes (DEGs) and to elucidate the pathogenesis of IPF at the genetic level. The microarray datasets GSE110147 and GSE53845 were downloaded from the Gene Expression Omnibus (GEO) database and analyzed using GEO2R to obtain the DEGs. The DEGs were further analyzed for Gene Ontology (GO) and Kyoto Encyclopedia of Genomes (KEGG) pathway enrichment using the DAVID database. Then, using the STRING database and Cytoscape, a protein-protein interaction (PPI) network was created and the hub genes were selected. In addition, lung tissue from a mouse model was validated. Lastly, the network between the target microRNAs (miRNAs) and the hub genes was constructed with NetworkAnalyst. A summary of 240 genes were identified as DEGs, and functional analysis highlighted their role in cell adhesion molecules and ECM-receptor interactions in IPF. In addition, eight hub genes were selected. Four of these hub genes (VCAM1, CDH2, SPP1, and POSTN) were screened for animal validation. The IHC and RT-qPCR of lung tissue from a mouse model confirmed the results above. Then, miR-181b-5p, miR-4262, and miR-155-5p were predicted as possible key miRNAs. Eight hub genes may play a key role in the development of IPF. Four of the hub genes were validated in animal experiments. MiR-181b-5p, miR-4262, and miR-155-5p may be involved in the pathophysiological processes of IPF by interacting with hub genes.

Fibroblast Upregulation of Vitamin D Receptor Represents a Self-Protective Response to Limit Fibroblast Proliferation and Activation during Pulmonary Fibrosis

Dysregulation of vitamin D receptor (VDR) is implicated in chronic obstructive pulmonary disease. However, whether VDR dysregulation contributes to the development of pulmonary fibrosis remains largely unknown. Analysis of bulk and single-cell RNA profiling datasets revealed VDR upregulation in lung fibroblasts from patients with pulmonary fibrosis or fibrotic mice, which was validated in lung fibroblasts from bleomycin-exposed mice and bleomycin-treated fibroblasts. Stable VDR knockdown promoted, whereas the VDR agonist paricalcitol suppressed lung fibroblast proliferation and activation. Gene set enrichment analysis (GSEA) showed that the JAK/STAT pathway and unfolded protein response (UPR), a process related to endoplasmic reticulum (ER) stress, were enriched in lung fibroblasts of fibrotic lungs. Stable VDR knockdown stimulated, but paricalcitol suppressed ER stress and JAK1/STAT3 activation in lung fibroblasts. The STAT3 inhibitor blocked bleomycin- or stable VDR knockdown-induced ER stress. Paricalcitol inhibited the bleomycin-induced enrichment of STAT3 to the ATF6 promoter, thereby suppressing ATF6 expression in fibroblasts. Paricalcitol or intrapulmonary VDR overexpression inactivated JAK1/STAT3 and suppressed ER stress in bleomycin-treated mice, thus resulting in the inhibition of fibroblast proliferation and activation. Collectively, this study suggests that fibroblast VDR upregulation may be a self-protective response to limit fibroblast proliferation and activation during pulmonary fibrosis by suppressing the JAK1/STAT3/ER stress pathway.

Idiopathic Pulmonary Fibrosis Molecular Substrates Revealed by Competing Endogenous RNA Regulatory Networks

Idiopathic pulmonary fibrosis (IPF) is a chronic progressive fibrotic disease of the lung with poor prognosis. Fibrosis results from remodeling of the interstitial tissue. A wide range of gene expression changes are observed, but the role of micro RNAs (miRNAs) and circular RNAs (circRNA) is still unclear. Therefore, this study aimed to establish an messenger RNA (mRNA)-miRNA-circRNA competing endogenous RNA (ceRNA) regulatory network to uncover novel molecular signatures using systems biology tools. Six datasets were used to determine differentially expressed genes (DEGs) and miRNAs (DEmiRNA). Accordingly, protein-protein, mRNA-miRNA, and miRNA-circRNA interactions were constructed. Modules were determined and further analyzed in the Drug Gene Budger platform to identify potential therapeutic compounds. We uncovered common 724 DEGs and 278 DEmiRNAs. In the protein-protein interaction network, TMPRSS4, ESR2, TP73, CLEC4E, and TP63 were identified as hub protein coding genes. The mRNA-miRNA interaction network revealed two modules composed of ADRA1A, ADRA1B, hsa-miR-484 and CDH2, TMPRSS4, and hsa-miR-543. The DEmiRNAs in the modules further analyzed to propose potential circRNA regulators in the ceRNA network. These results help deepen the understanding of the mechanisms of IPF. In addition, the molecular leads reported herein might inform future innovations in diagnostics and therapeutics research and development for IPF.

Loss of cytochrome P450 (CYP)1B1 mitigates hyperoxia response in adult mouse lung by reprogramming metabolism and translation

Oxygen supplementation is life saving for premature infants and for COVID-19 patients but can induce long-term pulmonary injury by triggering inflammation, with xenobiotic-metabolizing CYP enzymes playing a critical role. Murine studies showed that CYP1B1 enhances, while CYP1A1 and CYP1A2 protect from, hyperoxic lung injury. In this study we tested the hypothesis that Cyp1b1-null mice would revert hyperoxia-induced transcriptomic changes observed in WT mice at the transcript and pathway level. Wild type (WT) C57BL/6J and Cyp1b1-null mice aged 8-10 weeks were maintained in room air (21% O2) or exposed to hyperoxia (>95% O2) for 48h. Transcriptomic profiling was conducted using the Illumina microarray platform. Hyperoxia exposure led to robust changes in gene expression and in the same direction in WT, Cyp1a1-, Cyp1a2-, and Cyp1b1-null mice, but to different extents for each mouse genotype. At the transcriptome level, all Cyp1-null murine models reversed hyperoxia effects. Gene Set Enrichment Analysis identified 118 hyperoxia-affected pathways mitigated only in Cyp1b1-null mice, including lipid, glutamate, and amino acid metabolism. Cell cycle genes Cdkn1a and Ccnd1 were induced by hyperoxia in both WT and Cyp1b1-null mice but mitigated in Cyp1b1-null O2 compared to WT O2 mice. Hyperoxia gene signatures associated positively with bronchopulmonary dysplasia (BPD), which occurs in premature infants (with supplemental oxygen being one of the risk factors), but only in the Cyp1b1-null mice did the gene profile after hyperoxia exposure show a partial rescue of BPD-associated transcriptome. Our study suggests that CYP1B1 plays a pro-oxidant role in hyperoxia-induced lung injury.

Single-cell transcriptome sequencing-based analysis: probing the mechanisms of glycoprotein NMB regulation of epithelial cells involved in silicosis

Chronic exposure to silica can lead to silicosis, one of the most serious occupational lung diseases worldwide, for which there is a lack of effective therapeutic drugs and tools. Epithelial mesenchymal transition plays an important role in several diseases; however, data on the specific mechanisms in silicosis models are scarce. We elucidated the pathogenesis of pulmonary fibrosis via single-cell transcriptome sequencing and constructed an experimental silicosis mouse model to explore the specific molecular mechanisms affecting epithelial mesenchymal transition at the single-cell level. Notably, as silicosis progressed, glycoprotein non-metastatic melanoma protein B (GPNMB) exerted a sustained amplification effect on alveolar type II epithelial cells, inducing epithelial-to-mesenchymal transition by accelerating cell proliferation and migration and increasing mesenchymal markers, ultimately leading to persistent pulmonary pathological changes. GPNMB participates in the epithelial-mesenchymal transition in distant lung epithelial cells by releasing extracellular vesicles to accelerate silicosis. These vesicles are involved in abnormal changes in the composition of the extracellular matrix and collagen structure. Our results suggest that GPNMB is a potential target for fibrosis prevention.

Identification of potential biomarkers for idiopathic pulmonary fibrosis and validation of TDO2 as a potential therapeutic target

BACKGROUND

Idiopathic pulmonary fibrosis (IPF) is a progressive interstitial lung disease with a high mortality rate. On this basis, exploring potential therapeutic targets to meet the unmet needs of IPF patients is important.

AIM

To explore novel hub genes for IPF therapy.

METHODS

Here, we used public datasets to identify differentially expressed genes between IPF patients and healthy donors. Potential targets were considered based on multiple bioinformatics analyses, especially the correlation between hub genes and carbon monoxide diffusing capacity of carbon monoxide, forced vital capacity, and patient survival rate. The mRNA levels of the hub genes were determined through quantitative real-time polymerase chain reaction.

RESULTS

We found that TDO2 was upregulated in IPF patients and predicted poor prognosis. Surprisingly, single-cell RNA sequencing data analysis revealed significant enrichment of TDO2 in alveolar fibroblasts, indicating that TDO2 may participate in the regulation of proliferation and survival. Therefore, we verified the upregulated expression of TDO2 in an experimental mouse model of transforming growth factor-β (TGF-β)-induced pulmonary fibrosis. Furthermore, the results showed that a TDO2 inhibitor effectively suppressed TGF-β-induced fibroblast activation. These findings suggest that TDO2 may be a potential target for IPF treatment. Based on transcription factors-microRNA prediction and scRNA-seq analysis, elevated TDO2 promoted the IPF proliferation of fibroblasts and may be involved in the P53 pathway and aggravate ageing and persistent pulmonary fibrosis.

CONCLUSION

We provided new target genes prediction and proposed blocking TGF-β production as a potential treatment for IPF.

Potential biomarkers for diagnosis and disease evaluation of idiopathic pulmonary fibrosis

ABSTRACT

Idiopathic pulmonary fibrosis (IPF) is a chronic progressive lung disease characterized by progressive lung fibrogenesis and histological features of usual interstitial pneumonia. IPF has a poor prognosis and presents a spectrum of disease courses ranging from slow evolving disease to rapid deterioration; thus, a differential diagnosis remains challenging. Several biomarkers have been identified to achieve a differential diagnosis; however, comprehensive reviews are lacking. This review summarizes over 100 biomarkers which can be divided into six categories according to their functions: differentially expressed biomarkers in the IPF compared to healthy controls; biomarkers distinguishing IPF from other types of interstitial lung disease; biomarkers differentiating acute exacerbation of IPF from stable disease; biomarkers predicting disease progression; biomarkers related to disease severity; and biomarkers related to treatment. Specimen used for the diagnosis of IPF included serum, bronchoalveolar lavage fluid, lung tissue, and sputum. IPF-specific biomarkers are of great clinical value for the differential diagnosis of IPF. Currently, the physiological measurements used to evaluate the occurrence of acute exacerbation, disease progression, and disease severity have limitations. Combining physiological measurements with biomarkers may increase the accuracy and sensitivity of diagnosis and disease evaluation of IPF. Most biomarkers described in this review are not routinely used in clinical practice. Future large-scale multicenter studies are required to design and validate suitable biomarker panels that have diagnostic utility for IPF.

PCSK6 and Survival in Idiopathic Pulmonary Fibrosis

Rationale: Idiopathic pulmonary fibrosis (IPF) is a devastating disease characterized by limited treatment options and high mortality. A better understanding of the molecular drivers of IPF progression is needed. Objectives: To identify and validate molecular determinants of IPF survival. Methods: A staged genome-wide association study was performed using paired genomic and survival data. Stage I cases were drawn from centers across the United States and Europe and stage II cases from Vanderbilt University. Cox proportional hazards regression was used to identify gene variants associated with differential transplantation-free survival (TFS). Stage I variants with nominal significance (P < 5 × 10-5) were advanced for stage II testing and meta-analyzed to identify those reaching genome-wide significance (P < 5 × 10-8). Downstream analyses were performed for genes and proteins associated with variants reaching genome-wide significance. Measurements and Main Results: After quality controls, 1,481 stage I cases and 397 stage II cases were included in the analysis. After filtering, 9,075,629 variants were tested in stage I, with 158 meeting advancement criteria. Four variants associated with TFS with consistent effect direction were identified in stage II, including one in an intron of PCSK6 (proprotein convertase subtilisin/kexin type 6) reaching genome-wide significance (hazard ratio, 4.11 [95% confidence interval, 2.54-6.67]; P = 9.45 × 10-9). PCSK6 protein was highly expressed in IPF lung parenchyma. PCSK6 lung staining intensity, peripheral blood gene expression, and plasma concentration were associated with reduced TFS. Conclusions: We identified four novel variants associated with IPF survival, including one in PCSK6 that reached genome-wide significance. Downstream analyses suggested that PCSK6 protein plays a potentially important role in IPF progression.

An Integrative Multiomics Framework for Identification of Therapeutic Targets in Pulmonary Fibrosis

Pulmonary fibrosis (PF) is a heterogeneous disease with a poor prognosis. Therefore, identifying additional therapeutic modalities is required to improve outcome. However, the lack of biomarkers of disease progression hampers the preclinical to clinical translational process. Here, this work assesses and identifies progressive alterations in pulmonary function, transcriptomics, and metabolomics in the mouse lung at 7, 14, 21, and 28 days after a single dose of oropharyngeal bleomycin. By integrating multi-omics data, this work identifies two central gene subnetworks associated with multiple critical pathological changes in transcriptomics and metabolomics as well as pulmonary function. This work presents a multi-omics-based framework to establish a translational link between the bleomycin-induced PF model in mice and human idiopathic pulmonary fibrosis to identify druggable targets and test therapeutic candidates. This work also indicates peripheral cannabinoid receptor 1 (CB1 R) antagonism as a rational therapeutic target for clinical translation in PF. Mouse Lung Fibrosis Atlas can be accessed freely at https://niaaa.nih.gov/mouselungfibrosisatlas.

Antigenic responses are hallmarks of fibrotic interstitial lung diseases independent of underlying etiologies

Interstitial lung diseases (ILD) are heterogeneous conditions that may lead to progressive fibrosis and death of affected individuals. Despite diversity in clinical manifestations, enlargement of lung-associated lymph nodes (LLN) in fibrotic ILD patients predicts worse survival. Herein, we revealed a common adaptive immune landscape in LLNs of all ILD patients, characterized by highly activated germinal centers and antigen-activated T cells including regulatory T cells (Tregs). In support of these findings, we identified serum reactivity to 17 candidate auto-antigens in ILD patients through a proteome-wide screening using phage immunoprecipitation sequencing. Autoantibody responses to actin binding LIM protein 1 (ABLIM1), a protein highly expressed in aberrant basaloid cells of fibrotic lungs, were correlated with LLN frequencies of T follicular helper cells and Tregs in ILD patients. Together, we demonstrate that end-stage ILD patients have converging immune mechanisms, in part driven by antigen-specific immune responses, which may contribute to disease progression.

PhIP-Seq uncovers novel autoantibodies and unique endotypes in interstitial lung disease

Interstitial lung diseases (ILDs) are a heterogeneous group of disorders that can develop in patients with connective tissue diseases (CTD). Establishing autoimmunity in ILD impacts prognosis and treatment. ILD patients are screened for autoimmunity by assaying for anti-nuclear autoantibodies, rheumatoid factors and other non-specific tests. However, this approach has not been rigorously validated and may miss autoimmunity that manifests as autoantibodies to tissue antigens not previously defined in ILD. Here, we use Phage Immunoprecipitation-Sequencing (PhIP-Seq) to conduct a large, multi-center unbiased autoantibody discovery screen of ILD patients and controls. PhIP-Seq identified 17 novel autoreactive targets, and machine learning classifiers derived from these targets discriminated ILD serum from controls. Among these 17 candidates, we validated Cadherin Related Family Member 5 (CDHR5) as an autoantigen and found CDHR5 autoantibodies in patients with rheumatologic disorders and importantly, subjects not previously diagnosed with autoimmunity. Lung tissue of CDHR5 autoreactive patients showed transcriptional profiles consistent with activation of NFκB signaling and upregulation of chitotriosidase (CHIT1), a molecular pathway linked to fibrosis. Our study shows PhIP-Seq uncovers novel autoantibodies in ILD patients not revealed by standard clinical tests. Furthermore, CDHR5 autoantibodies may define a novel molecular endotype of ILD characterized by inflammation and fibrosis.

Machine learning-based prediction of candidate gene biomarkers correlated with immune infiltration in patients with idiopathic pulmonary fibrosis

Objective

This study aimed to identify candidate gene biomarkers associated with immune infiltration in idiopathic pulmonary fibrosis (IPF) based on machine learning algorithms.

Methods

Microarray datasets of IPF were extracted from the Gene Expression Omnibus (GEO) database to screen for differentially expressed genes (DEGs). The DEGs were subjected to enrichment analysis, and two machine learning algorithms were used to identify candidate genes associated with IPF. These genes were verified in a validation cohort from the GEO database. Receiver operating characteristic (ROC) curves were plotted to assess the predictive value of the IPF-associated genes. The cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT) algorithm was used to evaluate the proportion of immune cells in IPF and normal tissues. Additionally, the correlation between the expression of IPF-associated genes and the infiltration levels of immune cells was examined.

Results

A total of 302 upregulated and 192 downregulated genes were identified. Functional annotation, pathway enrichment, Disease Ontology and gene set enrichment analyses revealed that the DEGs were related to the extracellular matrix and immune responses. COL3A1, CDH3, CEBPD, and GPIHBP1 were identified as candidate biomarkers using machine learning algorithms, and their predictive value was verified in a validation cohort. Additionally, ROC analysis revealed that the four genes had high predictive accuracy. The infiltration levels of plasma cells, M0 macrophages and resting dendritic cells were higher and those of resting natural killer (NK) cells, M1 macrophages and eosinophils were lower in the lung tissues of patients with IPF than in those of healthy individuals. The expression of the abovementioned genes was correlated with the infiltration levels of plasma cells, M0 macrophages and eosinophils.

Conclusion

COL3A1, CDH3, CEBPD, and GPIHBP1 are candidate biomarkers of IPF. Plasma cells, M0 macrophages and eosinophils may be involved in the development of IPF and may serve as immunotherapeutic targets in IPF.

Wilms Tumor 1-Driven Fibroblast Activation and Subpleural Thickening in Idiopathic Pulmonary Fibrosis

Idiopathic pulmonary fibrosis (IPF) is a progressive fibrotic lung disease that is often fatal due to the formation of irreversible scar tissue in the distal areas of the lung. Although the pathological and radiological features of IPF lungs are well defined, the lack of insight into the fibrogenic role of fibroblasts that accumulate in distinct anatomical regions of the lungs is a critical knowledge gap. Fibrotic lesions have been shown to originate in the subpleural areas and extend into the lung parenchyma through processes of dysregulated fibroproliferation, migration, fibroblast-to-myofibroblast transformation, and extracellular matrix production. Identifying the molecular targets underlying subpleural thickening at the early and late stages of fibrosis could facilitate the development of new therapies to attenuate fibroblast activation and improve the survival of patients with IPF. Here, we discuss the key cellular and molecular events that contribute to (myo)fibroblast activation and subpleural thickening in IPF. In particular, we highlight the transcriptional programs involved in mesothelial to mesenchymal transformation and fibroblast dysfunction that can be targeted to alter the course of the progressive expansion of fibrotic lesions in the distal areas of IPF lungs.

Combination of esomeprazole and pirfenidone enhances antifibrotic efficacy in vitro and in a mouse model of TGFβ-induced lung fibrosis

Idiopathic pulmonary fibrosis (IPF) is a progressive and fatal lung disease of unknown etiology. Currently, pirfenidone and nintedanib are the only FDA-approved drugs for the treatment of IPF and are now the standard of care. This is a significant step in slowing down the progression of the disease. However, the drugs are unable to stop or reverse established fibrosis. Several retrospective clinical studies indicate that proton pump inhibitors (PPIs; FDA-approved to treat gastroesophageal reflux) are associated with favorable outcomes in patients with IPF, and emerging preclinical studies report that PPIs possess antifibrotic activity. In this study, we evaluated the antifibrotic efficacy of the PPI esomeprazole when combined with pirfenidone in vitro and in vivo. In cell culture studies of IPF lung fibroblasts, we assessed the effect of the combination on several fibrosis-related biological processes including TGFβ-induced cell proliferation, cell migration, cell contraction, and collagen production. In an in vivo study, we used mouse model of TGFβ-induced lung fibrosis to evaluate the antifibrotic efficacy of esomeprazole/pirfenidone combination. We also performed computational studies to understand the molecular mechanisms by which esomeprazole and/or pirfenidone regulate lung fibrosis. We found that esomeprazole significantly enhanced the anti-proliferative effect of pirfenidone and favorably modulated TGFβ-induced cell migration and contraction of collagen gels. We also found that the combination significantly suppressed collagen production in response to TGFβ in comparison to pirfenidone monotherapy. In addition, our animal study demonstrated that the combination therapy effectively inhibited the differentiation of lung fibroblasts into alpha smooth muscle actin (αSMA)-expressing myofibroblasts to attenuate the progression of lung fibrosis. Finally, our bioinformatics study of cells treated with esomeprazole or pirfenidone revealed that the drugs target several extracellular matrix (ECM) related pathways with esomeprazole preferentially targeting collagen family members while pirfenidone targets the keratins. In conclusion, our cell biological, computational, and in vivo studies show that the PPI esomeprazole enhances the antifibrotic efficacy of pirfenidone through complementary molecular mechanisms. This data supports the initiation of prospective clinical studies aimed at repurposing PPIs for the treatment of IPF and other fibrotic lung diseases where pirfenidone is prescribed.

CXCL12 and CXCL13 Cytokine Serum Levels Are Associated with the Magnitude and the Quality of SARS-CoV-2 Humoral Responses

A better understanding of the immunological markers associated with long-lasting immune responses to SARS-CoV-2 infection is of paramount importance. In the present study, we characterized SARS-CoV-2-specific humoral responses in hospitalized (ICU and non-ICU) and non-hospitalized individuals at six months post-onset of symptoms (POS) (N = 95). We showed that the proportion of individuals with detectable anti-SARS-CoV-2 IgG or neutralizing (NAb) responses and the titers of antibodies were significantly reduced in non-hospitalized individuals, compared to ICU- or non-ICU-hospitalized individuals at 6 months POS. Interestingly, SARS-CoV-2-specific memory B cells persist at 6 months POS in both ICU and non-ICU patients and were enriched in cells harboring an activated and/or exhausted phenotype. The frequency/phenotype of SARS-CoV-2-specific memory B cells and the magnitude of IgG or NAb responses at 6 months POS correlated with the serum immune signature detected at patient admission. In particular, the serum levels of CXCL13, IL-1RA, and G-CSF directly correlated with the frequency of Spike-specific B cells and the magnitude of Spike-specific IgG or NAb, while the serum levels of CXCL12 showed an antagonizing effect. Our results indicate that the balance between CXCL12 and CXCL13 is an early marker associated with the magnitude and the quality of the SARS-CoV-2 humoral memory.

Identification and immune characteristics of molecular subtypes related to fatty acid metabolism in idiopathic pulmonary fibrosis

Background

Although fatty acid metabolism has been confirmed to be involved in the pathological process of idiopathic pulmonary fibrosis (IPF), systematic analyses on the immune process mediated by fatty acid metabolism-related genes (FAMRGs) in IPF remain lacking.

Methods

The gene expression data of 315 patients with IPF were obtained from Gene Expression Omnibus database and were divided into the training and verification sets. The core FAMRGs of the training set were identified through weighted gene co-expression network analysis. Then, the fatty acid metabolism-related subtypes in IPF were identified on the basis of k-means unsupervised clustering. The scores of fatty acid metabolism and the expression of the fibrosis biomarkers in different subtypes were compared, and functional enrichment analysis was carried out on the differentially expressed genes between subtypes. A random forest model was used to select important FAMRGs as diagnostic markers for distinguishing between subtypes, and a line chart model was constructed and verified by using other datasets and rat models with different degrees of pulmonary fibrosis. The difference in immune cell infiltration among subtypes was evaluated with CIBERSORT, and the correlation between core diagnostic markers and immune cells were analyzed.

Results

Twenty-four core FAMRGs were differentially expressed between the training set and normal samples, and IPF was divided into two subtypes. Significant differences were observed between the two subtypes in biological processes, such as linoleic acid metabolism, cilium movement, and natural killer (NK) cell activation. The subtype with high fatty acid metabolism had more severe pulmonary fibrosis than the other subtype. A reliable construction line chart model based on six diagnostic markers was constructed, and ABCA3 and CYP24A1 were identified as core diagnostic markers. Significant differences in immune cell infiltration were found between the two subtypes, and ABCA3 and CYP24A1 were closely related to NK cells.

Conclusion

Fatty acid metabolism and the immune process that it mediates play an important role in the occurrence and development of IPF. The analysis of the role of FAMRGs in IPF may provide a new potential therapeutic target for IPF.

Spatially resolved deconvolution of the fibrotic niche in lung fibrosis

A defining pathological feature of human lung fibrosis is localized tissue heterogeneity, which challenges the interpretation of transcriptomic studies that typically lose spatial information. Here we investigate spatial gene expression in diagnostic tissue using digital profiling technology. We identify distinct, region-specific gene expression signatures as well as shared gene signatures. By integration with single-cell data, we spatially map the cellular composition within and distant from the fibrotic niche, demonstrating discrete changes in homeostatic and pathologic cell populations even in morphologically preserved lung, while through ligand-receptor analysis, we investigate cellular cross-talk within the fibrotic niche. We confirm findings through bioinformatic, tissue, and in vitro analyses, identifying that loss of NFKB inhibitor zeta in alveolar epithelial cells dysregulates the TGFβ/IL-6 signaling axis, which may impair homeostatic responses to environmental stress. Thus, spatially resolved deconvolution advances understanding of cell composition and microenvironment in human lung fibrogenesis.

Regeneration or Repair? The Role of Alveolar Epithelial Cells in the Pathogenesis of Idiopathic Pulmonary Fibrosis (IPF)

Idiopathic pulmonary fibrosis (IPF) is a chronic, progressive interstitial lung disease (ILD) with unknown etiology in which gradual fibrotic scarring of the lungs leads to usual interstitial pneumonia (UIP) and, ultimately, to death. IPF affects three million people worldwide, and the only currently available treatments include the antifibrotic drugs nintedanib and pirfenidone, which effectively reduce fibrosis progression are, unfortunately, not effective in curing the disease. In recent years, the paradigm of IPF pathogenesis has shifted from a fibroblast-driven disease to an epithelium-driven disease, wherein, upon recurrent microinjuries, dysfunctional alveolar type II epithelial cells (ATII) are not only unable to sustain physiological lung regeneration but also promote aberrant epithelial–mesenchymal crosstalk. This creates a drift towards fibrosis rather than regeneration. In the context of this review article, we discuss the most relevant mechanisms involved in IPF pathogenesis with a specific focus on the role of dysfunctional ATII cells in promoting disease progression. In particular, we summarize the main causes of ATII cell dysfunction, such as aging, environmental factors, and genetic determinants. Next, we describe the known mechanisms of physiological lung regeneration by drawing a parallel between embryonic lung development and the known pathways involved in ATII-driven alveolar re-epithelization after injury. Finally, we review the most relevant interventional clinical trials performed in the last 20 years with the aim of underlining the urgency of developing new therapies against IPF that are not only aimed at reducing disease progression by hampering ECM deposition but also boost the physiological processes of ATII-driven alveolar regeneration.

Blood gene expression risk profiles and interstitial lung abnormalities: COPDGene and ECLIPSE cohort studies

BACKGROUND

Interstitial lung abnormalities (ILA) are radiologic findings that may progress to idiopathic pulmonary fibrosis (IPF). Blood gene expression profiles can predict IPF mortality, but whether these same genes associate with ILA and ILA outcomes is unknown. This study evaluated if a previously described blood gene expression profile associated with IPF mortality is associated with ILA and all-cause mortality.

METHODS

In COPDGene and ECLIPSE study participants with visual scoring of ILA and gene expression data, we evaluated the association of a previously described IPF mortality score with ILA and mortality. We also trained a new ILA score, derived using genes from the IPF score, in a subset of COPDGene. We tested the association with ILA and mortality on the remainder of COPDGene and ECLIPSE.

RESULTS

In 1469 COPDGene (training n = 734; testing n = 735) and 571 ECLIPSE participants, the IPF score was not associated with ILA or mortality. However, an ILA score derived from IPF score genes was associated with ILA (meta-analysis of test datasets OR 1.4 [95% CI: 1.2-1.6]) and mortality (HR 1.25 [95% CI: 1.12-1.41]). Six of the 11 genes in the ILA score had discordant directions of effects compared to the IPF score. The ILA score partially mediated the effects of age on mortality (11.8% proportion mediated).

CONCLUSIONS

An ILA gene expression score, derived from IPF mortality-associated genes, identified genes with concordant and discordant effects on IPF mortality and ILA. These results suggest shared, and unique biologic processes, amongst those with ILA, IPF, aging, and death.

Differences and Similarities between the Lung Transcriptomic Profiles of COVID-19, COPD, and IPF Patients: A Meta-Analysis Study of Pathophysiological Signaling Pathways

Coronavirus disease 2019 (COVID-19) is a pandemic respiratory disease associated with high morbidity and mortality. Although many patients recover, long-term sequelae after infection have become increasingly recognized and concerning. Among other sequelae, the available data indicate that many patients who recover from COVID-19 could develop fibrotic abnormalities over time. To understand the basic pathophysiology underlying the development of long-term pulmonary fibrosis in COVID-19, as well as the higher mortality rates in patients with pre-existing lung diseases, we compared the transcriptomic fingerprints among patients with COVID-19, idiopathic pulmonary fibrosis (IPF), and chronic obstructive pulmonary disease (COPD) using interactomic analysis. Patients who died of COVID-19 shared some of the molecular biological processes triggered in patients with IPF, such as those related to immune response, airway remodeling, and wound healing, which could explain the radiological images seen in some patients after discharge. However, other aspects of this transcriptomic profile did not resemble the profile associated with irreversible fibrotic processes in IPF. Our mathematical approach instead showed that the molecular processes that were altered in COVID-19 patients more closely resembled those observed in COPD. These data indicate that patients with COPD, who have overcome COVID-19, might experience a faster decline in lung function that will undoubtedly affect global health.

BAL Transcriptomes Characterize Idiopathic Pulmonary Fibrosis Endotypes With Prognostic Impact

BACKGROUND

Given the plethora of pathophysiologic mechanisms described in idiopathic pulmonary fibrosis (IPF), we hypothesize that the mechanisms driving fibrosis in IPF may be different from one patient to another.

RESEARCH QUESTION

Do IPF endotypes exist and are they associated with outcome?

STUDY DESIGN AND METHODS

Using a publicly available gene expression dataset retrieved from BAL samples of patients with IPF and control participants (GSE70867), we clustered IPF samples based on a dimension reduction algorithm specifically designed for -omics data, called DDR Tree. After clustering, gene set enrichment analysis was performed for functional annotation, associations with clinical variables and prognosis were investigated, and differences in transcriptional regulation were determined using motif enrichment analysis. The findings were validated in three independent publicly available gene expression datasets retrieved from IPF blood samples.

RESULTS

One hundred seventy-six IPF samples from three centers were clustered in six IPF clusters, with distinct functional enrichment. Although clinical characteristics did not differ between the clusters, one cluster conferred worse sex-age-physiology score-corrected survival, whereas another showed a numeric trend toward worse survival (P = .08). The first was enriched for increased epithelial and innate and adaptive immunity signatures, whereas the other showed important telomere and mitochondrial dysfunction, loss of proteostasis, and increased myofibroblast signatures. The existence of these two endotypes, including the impact on survival of the immune endotype, was validated in three independent validation cohorts. Finally, we identified transcription factors regulating the expression of endotype-specific survival-associated genes.

INTERPRETATION

Gene expression-based endotyping in IPF is feasible and can inform clinical evolution. As endotype-specific pathways and survival-associated transcription factors are identified, endotyping may open up the possibility of endotype-tailored therapy.

Consensus Gene Co-Expression Network Analysis Identifies Novel Genes Associated with Severity of Fibrotic Lung Disease

Idiopathic pulmonary fibrosis (IPF) is a severe fibrotic lung disease characterized by irreversible scarring of the lung parenchyma leading to dyspnea, progressive decline in lung function, and respiratory failure. We analyzed lung transcriptomic data from independent IPF cohorts using weighted gene co-expression network analysis (WGCNA) to identify gene modules based on their preservation status in these cohorts. The consensus gene modules were characterized by leveraging existing clinical and molecular data such as lung function, biological processes, pathways, and lung cell types. From a total of 32 consensus gene modules identified, two modules were found to be significantly correlated with the disease, lung function, and preserved in other IPF datasets. The upregulated gene module was enriched for extracellular matrix, collagen metabolic process, and BMP signaling while the downregulated module consisted of genes associated with tube morphogenesis, blood vessel development, and cell migration. Using a combination of connectivity-based and trait-based significance measures, we identified and prioritized 103 "hub" genes (including 25 secretory candidate biomarkers) by their similarity to known IPF genetic markers. Our validation studies demonstrate the dysregulated expression of CRABP2, a retinol-binding protein, in multiple lung cells of IPF, and its correlation with the decline in lung function.

Asthma and Post-Asthmatic Fibrosis: A Search for New Promising Molecular Markers of Transition from Acute Inflammation to Pulmonary Fibrosis

Asthma is a heterogeneous pulmonary disorder, the progression and chronization of which leads to airway remodeling and fibrogenesis. To understand the molecular mechanisms of pulmonary fibrosis development, key genes forming the asthma-specific regulome and involved in lung fibrosis formation were revealed using a comprehensive bioinformatics analysis. The bioinformatics data were validated using a murine model of ovalbumin (OVA)-induced asthma and post-asthmatic fibrosis. The performed analysis revealed a range of well-known pro-fibrotic markers (Cat, Ccl2, Ccl4, Ccr2, Col1a1, Cxcl12, Igf1, Muc5ac/Muc5b, Spp1, Timp1) and a set of novel genes (C3, C3ar1, Col4a1, Col4a2, Cyp2e1, Fn1, Thbs1, Tyrobp) mediating fibrotic changes in lungs already at the stage of acute/subacute asthma-driven inflammation. The validation of genes related to non-allergic bleomycin-induced pulmonary fibrosis on asthmatic/fibrotic lungs allowed us to identify new universal genes (Col4a1 and Col4a2) associated with the development of lung fibrosis regardless of its etiology. The similarities revealed in the expression profiles of nodal fibrotic genes between asthma-driven fibrosis in mice and nascent idiopathic pulmonary fibrosis in humans suggest a tight association of identified genes with the early stages of airway remodeling and can be considered as promising predictors and early markers of pulmonary fibrosis.

The MIR100HG/miR-29a-3p/Tab1 axis modulates TGF-β1-induced fibrotic changes in type II alveolar epithelial cells BLM-caused lung fibrogenesis in mice

Transforming growth factor (TGF)-β1-induced fibrotic changes in alveolar epithelium is a critical event in pulmonary fibrosis. Herein, we recognized that lncRNA mir-100-let-7a-2-mir-125b-1 cluster host gene (MIR100HG) was abnormally upregulated within human idiopathic pulmonary fibrosis (IPF) lung tissue, bleomycin (BLM)-caused pulmonary fibrotic model mice and TGF-β1-stimulated mice type II alveolar epithelial cells. In vivo, MIR100HG knockdown attenuated BLM-caused lung fibrogenesis in mice; in vitro, MIR100HG knockdown attenuated TGF-β1-induced fibrotic changes in mice type II alveolar epithelial cells. Through direct binding, MIR100HG knockdown upregulated microRNA-29a-3p (miR-29a-3p) expression; through serving as competing endogenous RNA for miR-29a-3p, MIR100HG knockdown downregulated TGF-beta activated kinase 1/MAP3K7 binding protein 1 (Tab1) expression. Finally, under TGF-β1 stimulation, Tab1 knockdown attenuated TGF-β1-induced fibrotic changes and partially attenuated the effects of miR-29a-3p inhibition. In conclusion, we demonstrated the aberrant upregulation of lncRNA MIR100HG in BLM-caused lung fibrogenesis and TGF-β1-stimulated MLE 12 cells. The MIR100HG/miR-29a-3p/Tab1 axis could modulate TGF-β1-induced fibrotic changes in type II alveolar epithelial cells and, thus, might be promising targets for pulmonary fibrosis therapy.

ACPA Alleviates Bleomycin-Induced Pulmonary Fibrosis by Inhibiting TGF-β-Smad2/3 Signaling-Mediated Lung Fibroblast Activation

Pulmonary fibrosis is a group of life-threatening diseases with limited therapeutic options. The involvement of cannabinoid type 1 receptors (CB₁R) has been indicated in fibrotic diseases, but whether or not the activation of CB₁R can be a benefit for fibrosis treatment is controversial. In this study, we investigated the effects of arachidonoylcyclopropylamide (ACPA), as a selective CB₁R agonist, on bleomycin (BLM)-induced pulmonary fibrosis. We showed that ACPA treatment significantly improved the survival rate of BLM-treated mice, alleviated BLM-induced pulmonary fibrosis, and inhibited the expressions of extracellular matrix (ECM) markers, such as collagen, fibronectin, and α-SMA. The enhanced expressions of ECM markers in transforming growth factor-beta (TGF-β)-challenged primary lung fibroblasts isolated from mouse lung tissues were inhibited by ACPA treatment in a dose-dependent manner, and the fibroblast migration triggered by TGF-β was dose-dependently diminished after ACPA administration. Moreover, the increased mRNA levels of CB₁R were observed in both lung fibroblasts of BLM-induced fibrotic mice in vivo and TGF-β-challenged primary lung fibroblasts in vitro. CB₁R-specific agonist ACPA significantly diminished the activation of TGF-β–Smad2/3 signaling, i.e., the levels of p-Smad2 and p-Smad3, and decreased the expressions of downstream effector proteins including slug and snail, which regulate ECM production, in TGF-β-challenged primary lung fibroblasts. Collectively, these findings demonstrated that CB₁R-specific agonist ACPA exhibited antifibrotic efficacy in both in vitro and in vivo models of pulmonary fibrosis, revealing a novel anti-fibrosis approach to fibroblast-selective inhibition of TGF-β-Smad2/3 signaling by targeting CB₁R.

S100A12 as Biomarker of Disease Severity and Prognosis in Patients With Idiopathic Pulmonary Fibrosis

Background

Idiopathic pulmonary fibrosis (IPF) is one of interstitial lung diseases (ILDs) with poor prognosis. S100 calcium binding protein A12 (S100A12) has been reported as a prognostic serum biomarker in the IPF, but its correlation with IPF remains unclear in the lung tissue and bronchoalveolar lavage fluids (BALF).

Methods

Datasets were collected from the Gene Expression Omnibus (GEO) database. Person correlation coefficient, Kaplan–Meier analysis, Cox regression analysis, functional enrichment analysis and so on were used. And single cell RNA-sequencing (scRNA-seq) analysis was also used to explore the role of S100A12 and related genes in the IPF.

Results

S100A12 was mainly and highly expressed in the monocytes, and its expression was downregulated in the lung of patients with IPF according to scRNA-seq and the transcriptome analysis. However, S100A12 expression was upregulated both in blood and BALF of patients with IPF. In addition, 10 genes were found to interact with S100A12 according to protein–protein interaction (PPI) network, and the first four transcription factors (TF) targeted these genes were found according to hTFtarget database. Two most significant co-expression genes of S100A12 were S100A8 and S100A9. The 3 genes were significantly negatively associated with lung function and positively associated with the St. George’s Respiratory Questionnaire (SGRQ) scores in the lung of patients with IPF. And, high expression of the 3 genes was associated with higher mortality in the BALF, and shorter transplant-free survival (TFS) and progression-free survival (PFS) time in the blood. Prognostic predictive value of S100A12 was more superior to S100A8 and S100A9 in patients with IPF, and the composited variable [S100A12 + GAP index (gender, age, and physiological index)] may be a more effective predictive index.

Conclusion

These results imply that S100A12 might be an efficient disease severity and prognostic biomarker in patients with IPF.

Identification of hub genes associated with COVID-19 and idiopathic pulmonary fibrosis by integrated bioinformatics analysis

INTRODUCTION

The coronavirus disease 2019 (COVID-19), emerged in late 2019, was caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The risk factors for idiopathic pulmonary fibrosis (IPF) and COVID-19 are reported to be common. This study aimed to determine the potential role of differentially expressed genes (DEGs) common in IPF and COVID-19.

MATERIALS AND METHODS

Based on GEO database, we obtained DEGs from one SARS-CoV-2 dataset and five IPF datasets. A series of enrichment analysis were performed to identify the function of upregulated and downregulated DEGs, respectively. Two plugins in Cytoscape, Cytohubba and MCODE, were utilized to identify hub genes after a protein-protein interaction (PPI) network. Finally, candidate drugs were predicted to target the upregulated DEGs.

RESULTS

A total of 188 DEGs were found between COVID-19 and IPF, out of which 117 were upregulated and 71 were downregulated. The upregulated DEGs were involved in cytokine function, while downregulated DEGs were associated with extracellular matrix disassembly. Twenty-two hub genes were upregulated in COVID-19 and IPF, for which 155 candidate drugs were predicted (adj.P.value < 0.01).

CONCLUSION

Identifying the hub genes aberrantly regulated in both COVID-19 and IPF may enable development of molecules, encoded by those genes, as therapeutic targets for preventing IPF progression and SARS-CoV-2 infections.