Effects of Anti-Fibrotic Drugs on Transcriptome of Peripheral Blood Mononuclear Cells in Idiopathic Pulmonary Fibrosis.

Two anti-fibrotic drugs, pirfenidone (PFD) and nintedanib (NTD), are currently used to treat idiopathic pulmonary fibrosis (IPF). Peripheral blood mononuclear cells (PBMCs) are immunocompetent cells that could orchestrate cell-cell interactions associated with IPF pathogenesis. We employed RNA sequencing to examine the transcriptome signature in the bulk PBMCs of patients with IPF and the effects of anti-fibrotic drugs on these signatures. Differentially expressed genes (DEGs) between "patients with IPF and healthy controls" and "before and after anti-fibrotic treatment" were analyzed. Enrichment analysis suggested that fatty acid elongation interferes with TGF-ß/Smad signaling and the production of oxidative stress since treatment with NTD upregulates the fatty acid elongation enzymes ELOVL6. Treatment with PFD downregulates COL1A1, which produces wound-healing collagens because activated monocyte-derived macrophages participate in the production of collagen, type I, and alpha 1 during tissue damage. Plasminogen activator inhibitor-1 (PAI-1) regulates wound healing by inhibiting plasmin-mediated matrix metalloproteinase activation, and the inhibition of PAI-1 activity attenuates lung fibrosis. DEG analysis suggested that both the PFD and NTD upregulate SERPINE1, which regulates PAI-1 activity. This study embraces a novel approach by using RNA sequencing to examine PBMCs in IPF, potentially revealing systemic biomarkers or pathways that could be targeted for therapy.

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

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

Transcriptomics in idiopathic pulmonary fibrosis unveiled: a new perspective from differentially expressed genes to therapeutic targets.

Background: The underlying molecular pathways of idiopathic pulmonary fibrosis (IPF), a progressive lung condition with a high death rate, are still mostly unknown. By using microarray datasets, this study aims to identify new genetic targets for IPF and provide light on the genetic factors that contribute to the development of IPF. Method: We conducted a comprehensive analysis of three independent IPF datasets from the Gene Expression Omnibus (GEO) database, employing R software for data handling and normalization. Our evaluation of the relationships between differentially expressed genes (DEGs) and IPF included differential expression analysis, expression quantitative trait loci (eQTL) analysis, and Mendelian Randomization(MR) analyses. Additionally, we used Gene Set Enrichment Analysis (GSEA) and Gene Ontology (GO)/Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis to explore the functional roles and pathways of these genes. Finally, we validated the results obtained for the target genes. Results: We identified 486 highly expressed genes and 468 lowly expressed genes that play important roles in IPF. MR analysis identified six significantly co-expressed genes associated with IPF, specifically C12orf75, SPP1, ZG16B, LIN7A, PPP1R14A, and TLR2. These genes participate in essential biological processes and pathways, including macrophage activation and neural system regulation. Additionally, CIBERSORT analysis indicated a unique immune cell distribution in IPF, emphasized the significance of immunological processes in the disease. The MR analysis was consistent with the results of the analysis of variance in the validation cohort, which strengthens the reliability of our MR findings. Conclusion: Our findings provide new insights into the molecular basis of IPF and highlight the promise of therapeutic interventions. They emphasize the potential of targeting specific molecular pathways for the treatment of IPF, laying the foundation for further research and clinical work.

Genetic association between smoking and DLCO in idiopathic pulmonary fibrosis patients.

BACKGROUND: Observational studies have shown that smoking is related to the diffusing capacity of the lungs for carbon monoxide (DLCO) in individuals with idiopathic pulmonary fibrosis (IPF). Nevertheless, further investigation is needed to determine the causal effect between these two variables. Therefore, we conducted a study to investigate the causal relationship between smoking and DLCO in IPF patients using two-sample Mendelian randomization (MR) analysis. METHODS: Large-scale genome-wide association study (GWAS) datasets from individuals of European descent were analysed. These datasets included published lifetime smoking index (LSI) data for 462,690 participants and DLCO data for 975 IPF patients. The inverse-variance weighting (IVW) method was the main method used in our analysis. Sensitivity analyses were performed by MR‒Egger regression, Cochran's Q test, the leave-one-out test and the MR-PRESSO global test. RESULTS: A genetically predicted increase in LSI was associated with a decrease in DLCO in IPF patients [ORIVW = 0.54; 95% CI 0.32-0.93; P = 0.02]. CONCLUSIONS: Our study suggested that smoking is associated with a decrease in DLCO. Patients diagnosed with IPF should adopt an active and healthy lifestyle, especially by quitting smoking, which may be effective at slowing the progression of IPF.

HE4-based nomogram for predicting overall survival in patients with idiopathic pulmonary fibrosis: construction and validation.

Idiopathic pulmonary fibrosis (IPF) is a life-threatening interstitial lung disease. Identifying biomarkers for early diagnosis is of great clinical importance. The epididymis protein 4 (HE4) is important in the process of inflammation and fibrosis in the epididymis. Its prognostic value in IPF, however, has not been studied. The mRNA and protein levels of HE4 were used to determine the prognostic value in different patient cohorts. In this study, prognostic nomograms were generated based on the results of the cox regression analysis. We identified the HE4 protein level increased in IPF patients, but not the HE4 gene expression. The increased expression of HE4 correlated positively with a poor prognosis for patients with IPF. The HR and 95% CI were 2.62 (1.61-4.24) (p < 0.001) in the training set. We constructed a model based on the risk-score = 0.16222182 * HE4 + 0/0.37580659/1.05003609 (for GAP index 0-3/4-5/6-8) + (- 1.1183375). In both training and validation sets, high-risk patients had poor prognoses (HR: 3.49, 95%CI 2.10-5.80, p = 0.001) and higher likelihood of dying (HR: 6.00, 95%CI 2.04-17.67, p = 0.001). Analyses of calibration curves and decision curves suggest that the method is effective in predicting outcomes. Furthermore, a similar formulation was used in a protein-based model based on HE4 that also showed prognostic value when applied to IPF patients. Accordingly, HE4 is an independent poor prognosis factor, and it has the potential to predict IPF patient survival.

The causal relationship between genetically predicted blood metabolites and idiopathic pulmonary fibrosis: A bidirectional two-sample Mendelian randomization study.

BACKGROUND: Numerous metabolomic studies have confirmed the pivotal role of metabolic abnormalities in the development of idiopathic pulmonary fibrosis (IPF). Nevertheless, there is a lack of evidence on the causal relationship between circulating metabolites and the risk of IPF. METHODS: The potential causality between 486 blood metabolites and IPF was determined through a bidirectional two-sample Mendelian randomization (TSMR) analysis. A genome-wide association study (GWAS) involving 7,824 participants was performed to analyze metabolite data, and a GWAS meta-analysis involving 6,257 IPF cases and 947,616 control European subjects was conducted to analyze IPF data. The TSMR analysis was performed primarily with the inverse variance weighted model, supplemented by weighted mode, MR-Egger regression, and weighted median estimators. A battery of sensitivity analyses was performed, including horizontal pleiotropy assessment, heterogeneity test, Steiger test, and leave-one-out analysis. Furthermore, replication analysis and meta-analysis were conducted with another GWAS dataset of IPF containing 4,125 IPF cases and 20,464 control subjects. Mediation analyses were used to identify the mediating role of confounders in the effect of metabolites on IPF. RESULTS: There were four metabolites associated with the elevated risk of IPF, namely glucose (odds ratio [OR] = 2.49, 95% confidence interval [95%CI] = 1.13-5.49, P = 0.024), urea (OR = 6.24, 95% CI = 1.77-22.02, P = 0.004), guanosine (OR = 1.57, 95%CI = 1.07-2.30, P = 0.021), and ADpSGEGDFXAEGGGVR (OR = 1.70, 95%CI = 1.00-2.88, P = 0.0496). Of note, the effect of guanosine on IPF was found to be mediated by gastroesophageal reflux disease. Reverse Mendelian randomization analysis displayed that IPF might slightly elevate guanosine levels in the blood. CONCLUSION: Conclusively, hyperglycemia may confer a promoting effect on IPF, highlighting that attention should be paid to the relationship between diabetes and IPF, not solely to the diagnosis of diabetes. Additionally, urea, guanosine, and ADpSGEGDFXAEGGGVR also facilitate the development of IPF. This study may provide a reference for analyzing the potential mechanism of IPF and carry implications for the prevention and treatment of IPF.

Exploring the causal relationship between immune cells and idiopathic pulmonary fibrosis: a bi-directional Mendelian randomization study.

BACKGROUND: The potential pathogenic mechanism of idiopathic pulmonary fibrosis is widely recognized to involve immune dysregulation. However, the current pool of studies has yet to establish a unanimous agreement regarding the correlation between various types of immune cells and IPF. METHODS: By conducting a two-sample Mendelian randomization analysis using publicly available genetic data, the study examined the causal relationship between IPF and 731 immune cells. To ensure the reliability of the results, combined sensitivity analyses and inverse Mendelian analyses were conducted. Moreover, within subgroups, multivariate Mendelian randomization analyses were utilized to investigate the autonomous causal connection between immune cell characteristics and IPF. RESULTS: After adjusting for false discovery rate, it was discovered that 20 immunophenotypes exhibited a significant association with IPF. After subgrouping for multivariate Mendelian randomization analysis, there were six immunophenotypes that remained significantly associated with IPF. These included CD33 + HLA DR + CD14dim (OR = 0.96, 95% CI 0.93-0.99, P = 0.033), HLA DR + NK (OR = 0.92, 95% CI 0.85-0.98, P = 0.017), CD39 + CD8 + T cell %T cell (OR = 0.93, 95% CI 0.88-0.99, P = 0.024), CD3 on activated & secreting Treg (OR = 0.91, 95% CI 0.84-0.98, P = 0.026), PDL-1 on CD14- CD16 + monocyte (OR = 0.89, 95% CI 0.84-0.95, P = 8 × 10-4), and CD45 on CD33 + HLA DR + CD14- (OR = 1.08, 95% CI 1.01-1.15, P = 0.011). CONCLUSION: Our study reveals a noteworthy association between IPF and various immune cells, providing valuable insights for clinical research and aiding the advancement of immunologically-based therapeutic strategies.

Age at menarche and idiopathic pulmonary fibrosis: a two-sample mendelian randomization study.

BACKGROUND: Sex difference in the incidence rate of idiopathic pulmonary fibrosis (IPF) indicates that estrogen has a certain protective effect on the disease. Nevertheless, there is a dearth of study investigating the association between factors pertaining to endogenous estrogen exposure level, such as age at menarche (AAM) in women, and IPF. Our study intended to employ Mendelian randomization (MR) method to elucidate the causal association between AAM and IPF. METHODS: Our study utilized AAM as a measure of endogenous estrogen exposure and investigated its causal effect on the risk of IPF through MR. We employed the inverse variance weighted (IVW) method to assess the causal relationship between AAM and IPF risk, with supplementary analyses conducted using the weighted median estimator (WME) and MR-Egger method. Several sensitivity analyses were performed to assess the dependability of MR estimates. RESULTS: A total of 9 selected single nucleotide polymorphisms (SNPs) significantly associated with AAM were selected as instrumental variables. The IVW method showed that genetically later AAM was associated with an increased risk of IPF (odds ratio [OR] = 1.0014, 95%confidence interval [CI] = 1.0005-1.0023, p = 0.001). The median weighting method and the MR-Egger method obtained similar estimates, and no heterogeneity or pleiotropy was found, indicating that the results were robust. CONCLUSIONS: Our MR study suggested a causal relationship between a later onset of menarche and a heightened susceptibility to IPF.

Astragaloside IV inhibits idiopathic pulmonary fibrosis through activation of autophagy by miR-21-mediated PTEN/PI3K/AKT/mTOR pathway.

As the main active ingredient of Astragalus, Astragaloside IV (AS-IV) can ameliorate pulmonary fibrosis. In this experiment, we studied how AS-IV reduces idiopathic pulmonary fibrosis (IPF). Bleomycin (BLM) or TGF-ß1 was treated in mice or alveolar epithelial cells to mimic IPF in vivo as well as in vitro. ASV-IV alleviated levels of inflammatory cytokines and fibrosis markers in IPF model. Through detection of autophagy-related genes, ASV-IV was observed to induce autophagy in IPF. Besides, ASV-IV inhibited miR-21 expression in IPF models, and overexpression of miR-21 could reverse the protective potential of ASV-IV on IPF. PTEN was targeted by miR-21 and was up-regulated by ASV-IV in IPF models. In addition, levels of inflammatory cytokines and fibrosis markers, autophagy, as well as the PI3K/AKT/mTOR pathway regulated by ASV-IV could be neutralized after treatment with autophagy inhibitors, miR-21 mimics, or si-PTEN. Our study demonstrates that ASV-IV inhibits IPF through activation of autophagy by miR-21-mediated PTEN/PI3K/AKT/mTOR pathway, suggesting that ASV-IV could be acted to be a promising therapeutic method for IPF.

Identifying a survival-associated cell type based on multi-level transcriptome analysis in idiopathic pulmonary fibrosis.

BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is a progressive disease with a five-year survival rate of less than 40%. There is significant variability in survival time among IPF patients, but the underlying mechanisms for this are not clear yet. METHODS AND RESULTS: We collected single-cell RNA sequence data of 13,223 epithelial cells taken from 32 IPF patients and bulk RNA sequence data from 456 IPF patients in GEO. Based on unsupervised clustering analysis at the single-cell level and deconvolution algorithm at bulk RNA sequence data, we discovered a special alveolar type 2 cell subtype characterized by high expression of CCL20 (referred to as ATII-CCL20), and found that IPF patients with a higher proportion of ATII-CCL20 had worse prognoses. Furthermore, we uncovered the upregulation of immune cell infiltration and metabolic functions in IPF patients with a higher proportion of ATII-CCL20. Finally, the comprehensive decision tree and nomogram were constructed to optimize the risk stratification of IPF patients and provide a reference for accurate prognosis evaluation. CONCLUSIONS: Our study by integrating single-cell and bulk RNA sequence data from IPF patients identified a special subtype of ATII cells, ATII-CCL20, which was found to be a risk cell subtype associated with poor prognosis in IPF patients. More importantly, the ATII-CCL20 cell subtype was linked with metabolic functions and immune infiltration.

Exosomal circRNAs in the plasma serve as novel biomarkers for IPF diagnosis and progression prediction.

BACKGROUND: Idiopathic Pulmonary Fibrosis (IPF) is a type of chronic interstitial pneumonia, often fatal, with elusive causes and a bleak prognosis. Its treatment options are limited and largely ineffective. Early detection and precise diagnosis are pivotal in managing the disease effectively and enhancing patient survival rates. Recently, the quest for trustworthy biomarkers for IPF has gained momentum. Notably, emerging studies indicate that circular RNAs (circRNAs) found in exosomes may hold significant potential as valuable diagnostic markers. METHODS: In this study, we initially explored the expression profile of circRNAs in exosomes sourced from the blood of IPF patients and healthy volunteers, employing a human circRNA microarray. We then utilized RT-qPCR to corroborate the dysregulated circRNAs identified by the microarray during the training phase. Next, the circRNAs that displayed a significant increase during the training phase were selected for further validation in a larger cohort encompassing 113 IPF patients and 76 healthy volunteers. Ultimately, the expression level and function of hsa_circ_0044226 were substantiated through a series of in vivo and in vitro experiments. RESULTS: Utilizing a human circRNA microarray, we identified 11 dysregulated circRNAs in the exosomes derived from the blood of IPF patients and control volunteers. Subsequent RT-qPCR analysis revealed significant increases in three circRNAs (hsa_circ_0044226, hsa_circ_0004099, hsa_circ_0008898) within the IPF patients. Notably, hsa_circ_0044226 was markedly elevated in patients experiencing acute exacerbation of IPF (AE-IPF) compared to those with stable IPF (S-IPF). Additionally, an upregulation of hsa_circ_0044226 was observed in the blood exosomes derived from a bleomycin-induced IPF mouse model. CONCLUSION: The expression levels of hsa_circ_0044226, hsa_circ_0004099, and hsa_circ_0008898 in plasma exosomes introduce a new paradigm of biomarkers for the diagnosis and progression of IPF.

Diabetes mellitus and idiopathic pulmonary fibrosis: a Mendelian randomization study.

BACKGROUND: The question as to whether or not diabetes mellitus increases the risk of idiopathic pulmonary fibrosis (IPF) remains controversial. This study aimed to investigate the causal association between type 1 diabetes (T1D), type 2 diabetes (T2D), and IPF using Mendelian randomization (MR) analysis. METHODS: We used two-sample univariate and multivariate MR (MVMR) analyses to investigate the causal relationship between T1D or T2D and IPF. We obtained genome-wide association study (GWAS) data for T1D and T2D from the European Bioinformatics Institute, comprising 29,652 T1D samples and 101,101 T1D single nucleotide polymorphisms (SNPs) and 655,666 T2D samples and 5,030,727 T2D SNPs. We also used IPF GWAS data from the FinnGen Biobank comprising 198,014 IPF samples and 16,380,413 IPF SNPs. All cases and controls in these datasets were derived exclusively from European populations. In the univariate MR analysis, we employed inverse variance-weighted (IVW), weighted median (WM), and MR-Egger regression methods. For the MVMR analysis, we used the multivariate IVW method primarily, and supplemented it with multivariate MR-Egger and multivariate MR- least absolute shrinkage and selection operator methods. Heterogeneity tests were conducted using the MR-IVW and MR-Egger regression methods, whereas pleiotropic effects were assessed using the MR-Egger intercept. The results of MR and sensitivity analyses were visualized using forest, scatter, leave-one-out, and funnel plots. RESULTS: Univariate MR revealed a significant causal relationship between T1D and IPF (OR = 1.118, 95% CI = 1.021-1.225, P = 0.016); however, no significant causal relationship was found between T2D and IPF (OR = 0.911, 95% CI = 0.796-1.043, P = 0.178). MVMR analysis further confirmed a causal association between T1D and IPF (OR = 1.133, 95% CI = 1.011-1.270, P = 0.032), but no causal relationship between T2D and IPF (OR = 1.009, 95% CI = 0.790-1.288, P = 0.950). Sensitivity analysis results validated the stability and reliability of our findings. CONCLUSION: Univariate and multivariate analyses demonstrated a causal relationship between T1D and IPF, whereas no evidence was found to support a causal relationship between T2D and IPF. Therefore, in clinical practice, patients with T1D should undergo lung imaging for early detection of IPF.

O-GlcNAc regulates anti-fibrotic genes in lung fibroblasts through EZH2.

Epigenetic modifications are involved in fibrotic diseases, such as idiopathic pulmonary fibrosis (IPF), and contribute to the silencing of anti-fibrotic genes. H3K27me3, a key repressive histone mark, is catalysed by the methyltransferase enhancer of Zeste homologue 2 (EZH2), which is regulated by the post-translational modification, O-linked N-Acetylglucosamine (O-GlcNAc). In this study, we explored the effects of O-GlcNAc and EZH2 on the expression of antifibrotic genes, cyclooxygenase-2 (Cox2) and Heme Oxygenase (Homx1). The expression of Cox2 and Hmox1 was examined in primary IPF or non-IPF lung fibroblasts with or without EZH2 inhibitor EZP6438, O-GlcNAc transferase (OGT) inhibitor (OSMI-1) or O-GlcNAcase (OGA) inhibitor (thiamet G). Non-IPF cells were also subjected to TGF-ß1 with or without OGT inhibition. The reduced expression of Cox2 and Hmox1 in IPF lung fibroblasts is restored by OGT inhibition. In non-IPF fibroblasts, TGF-ß1 treatment reduces Cox2 and Hmox1 expression, which was restored by OGT inhibition. ChIP assays demonstrated that the association of H3K27me3 is reduced at the Cox2 and Hmox1 promoter regions following OGT or EZH2 inhibition. EZH2 levels and stability were decreased by reducing O-GlcNAc. Our study provided a novel mechanism of O-GlcNAc modification in regulating anti-fibrotic genes in lung fibroblasts and in the pathogenesis of IPF.

Drug-Gene Risk Stratification in Patients with Suspected Drug-Induced Interstitial Lung Disease.

BACKGROUND: Pulmonary toxicity has been associated with drug use. This is often not recognized in clinical practice, and underestimated. OBJECTIVE: We aimed to establish whether polymorphisms in certain genes corresponding with a metabolic pathway of drug(s) used are associated with pulmonary toxicity in patients with suspected drug-induced interstitial lung disease (DI-ILD). METHODS: This retrospective observational study explored genetic variations in three clinically relevant cytochrome P450 (CYP) iso-enzymes (i.e., CYP2D6, CYP2C9, and CYP2C19) in a group of patients with a fibroticinterstitial lung disease, either non-specific interstitial pneumonia (n = 211) or idiopathic pulmonary fibrosis (n = 256), with a suspected drug-induced origin. RESULTS: Of the 467 patients, 79.0% showed one or more polymorphisms in the tested genes accompanied by the use of drug(s) metabolized by a corresponding affected metabolic pathway (60.0% poor metabolizers and/or using two or more drugs [likely DI-ILD], 37.5% using three or more [highly likely DI-ILD]). Most commonly used drugs were statins (63.1%) with a predominance among men (69.4 vs 47.1%, p < 0.0001). Nitrofurantoin, not metabolized by the tested pathways, was prescribed more frequently among women (51.9 vs 4.5%, p < 0.00001). CONCLUSIONS: In our cohort with suspected DI-ILD, 79% carried one or more genetic variants accompanied by the use of drugs metabolized by a corresponding affected pathway. In 60%, the diagnosis of DI-ILD was likely, whereas in 37.5%, it was highly likely, based on CYP analyses. This study underlines the importance of considering both drug use and genetic make-up as a possible cause, or at least a contributing factor, in the development and/or progression of fibrotic lung diseases. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov identifier NCT00267800, registered in 2005.

Localized Administration of Bcar3 siRNA via Nano-Self-Assembly to Treat Idiopathic Pulmonary Fibrosis by Disrupting Macrophage-Fibroblast Crosstalk.

Background: Idiopathic pulmonary fibrosis (IPF) is a severe interstitial lung disease characterized by chronic lung injury leading to macrophage infiltration and fibroblast activation. However, there is no effective therapeutic strategy targeting the crucial crosstalk between macrophages and fibroblasts to halt IPF progression. Methods: Studies were conducted in IPF patients and fibrotic mice models to elucidate the role of Bcar3 in the pathogenesis of pulmonary fibrosis. The effect of Bcar3 on macrophage polarization, fibroblast activation, and related signaling pathways were next investigated to unravel the underlying mechanisms. Results: Our study elucidates a marked increase in Bcar3 expression in lung tissues from IPF patients and fibrotic mice, recording 1.7 and 7.8-fold increases compared to control subjects, respectively. Additionally, Bcar3 was found to significantly enhance macrophage activation and fibroblast differentiation, observable in both in vivo and in vitro settings. Mechanistically, the upregulation of Bcar3 in macrophages was reliant on Stat6, while in fibroblasts, it depended on TGFßR1/Smad3. Furthermore, Bcar3 augmented IL-4/Stat6 pathway in macrophages and TGF-ß/Smad3 pathway in fibroblasts, supporting a synergistic activation loop that expedited lung fibrogenesis. Notably, intratracheal injection of liposomes containing Bcar3 siRNA precisely delivered gene therapeutics to lung macrophages and fibroblasts, effectively reducing Bcar3 expression to 59% of baseline levels. Importantly, this intervention protected mice from lung fibrosis induced by either FITC or bleomycin, as well as human precision-cut lung slices against TGF-ß1 stimulation. Conclusion: Our study underscores the pivotal role of Bcar3 in orchestrating the macrophage-fibroblast crosstalk during pulmonary fibrosis progression. Targeting Bcar3 emerges as a novel therapeutic avenue to halt IPF progression and enhance patient prognosis.

Standigm ASK™: knowledge graph and artificial intelligence platform applied to target discovery in idiopathic pulmonary fibrosis.

Standigm ASK™ revolutionizes healthcare by addressing the critical challenge of identifying pivotal target genes in disease mechanisms-a fundamental aspect of drug development success. Standigm ASK™ integrates a unique combination of a heterogeneous knowledge graph (KG) database and an attention-based neural network model, providing interpretable subgraph evidence. Empowering users through an interactive interface, Standigm ASK™ facilitates the exploration of predicted results. Applying Standigm ASK™ to idiopathic pulmonary fibrosis (IPF), a complex lung disease, we focused on genes (AMFR, MDFIC and NR5A2) identified through KG evidence. In vitro experiments demonstrated their relevance, as TGFß treatment induced gene expression changes associated with epithelial-mesenchymal transition characteristics. Gene knockdown reversed these changes, identifying AMFR, MDFIC and NR5A2 as potential therapeutic targets for IPF. In summary, Standigm ASK™ emerges as an innovative KG and artificial intelligence platform driving insights in drug target discovery, exemplified by the identification and validation of therapeutic targets for IPF.

Transcriptomic and network analysis identifies shared and unique pathways and immune changes across fibrotic interstitial lung diseases.

BACKGROUND: Interstitial lung disease (ILD) encompasses a diverse group of disorders characterized by chronic inflammation and fibrosis of the pulmonary interstitium. Three ILDs, namely idiopathic pulmonary fibrosis (IPF), fibrotic hypersensitivity pneumonitis (fHP), and connective tissue disease-associated ILD (CTD-ILD), exhibit similar progressive fibrosis phenotypes, yet possess distinct etiologies, encouraging us to explore their different underlying mechanisms. METHODS: Transcriptome data of fibrotic lung tissues from patients with IPF, fHP, and CTD-ILD were subjected to functional annotation, network, and pathway analyses. Additionally, we employed the xCell deconvolution algorithm to predict immune cell infiltration in patients with fibrotic ILDs and healthy controls. RESULTS: We identified a shared progressive fibrosis-related module in these diseases which was related to extracellular matrix (ECM) degradation and production and potentially regulated by the p53 family transcription factors. In IPF, neuron-related processes emerged as a critical specific mechanism in functional enrichment. In fHP, we observed that B cell signaling and immunoglobulin A (IgA) production may act as predominant processes, which was further verified by B cell infiltration and the central role of CD19 gene. In CTD-ILD, active chemokine processes were enriched, and active dendritic cells (aDCs) were predicted to infiltrate the lung tissues. CONCLUSIONS: This study revealed shared and specific molecular and cellular pathways among IPF, fHP, and CTD-ILD, providing a basis for understanding their pathogenesis and identifying potential therapeutic targets.

The gene expression of CALD1, CDH2, and POSTN in fibroblast are related to idiopathic pulmonary fibrosis.

Introduction: Idiopathic pulmonary fibrosis (IPF) is characterized by progressive lung dysfunction due to excessive collagen production and tissue scarring. Despite recent advancements, the molecular mechanisms remain unclear. Methods: RNA sequencing identified 475 differentially expressed genes (DEGs) in the TGF-ß1-induced primary lung fibrosis model. Gene expression chips GSE101286 and GSE110147 from NCBI gene expression omnibus (GEO) database were analyzed using GEO2R, revealing 94 DEGs in IPF lung tissue samples. The gene ontology (GO) and pathway enrichment, Protein-protein interaction (PPI) network construction, and Maximal Clique Centrality (MCC) scoring were performed. Experimental validation included RT-qPCR, Immunohistochemistry (IHC), and Western Blot, with siRNA used for gene knockdown. A co-expression network was constructed by GeneMANIA. Results: GO enrichment highlighted significant enrichment of DEGs in TGF-ß cellular response, connective tissue development, extracellular matrix components, and signaling pathways such as the AGE-RAGE signaling pathway and ECM-receptor interaction. PPI network analysis identified hub genes, including FN1, COL1A1, POSTN, KIF11, and ECT2. CALD1 (Caldesmon 1), CDH2 (Cadherin 2), and POSTN (Periostin) were identified as dysregulated hub genes in both the RNA sequencing and GEO datasets. Validation experiments confirmed the upregulation of CALD1, CDH2, and POSTN in TGF-ß1-treated fibroblasts and IPF lung tissue samples. IHC experiments probed tissue-level expression patterns of these three molecules. Knockdown of CALD1, CDH2, and POSTN attenuated the expression of fibrotic markers (collagen I and α-SMA) in response to TGF-ß1 stimulation in primary fibroblasts. Co-expression analysis revealed interactions between hub genes and predicted genes involved in actin cytoskeleton regulation and cell-cell junction organization. Conclusions: CALD1, CDH2, and POSTN, identified as potential contributors to pulmonary fibrosis, present promising therapeutic targets for IPF patients.

Psoriasis may increase the risk of idiopathic pulmonary fibrosis: a two-sample Mendelian randomization study.

BACKGROUND: Although some studies have indicated that Psoriasis could contribute to the risk of idiopathic pulmonary fibrosis (IPF), no study has reported a clear causal association between them. Our aim was to explore the potential relationship between Psoriasis and IPF using Mendelian randomization (MR) design. METHODS: To explore a causal association between Psoriasis and IPF, we used genetic instruments from the largest available genome-wide association study (GWAS) of European ancestry, including psoriasis (5314 cases, 457,619 controls) and IPF (1028 cases, 196,986 controls). Our main analyses were conducted by inverse-variance weighted (IVW) method with random-effects model, with the other complementary four analyses: weighted median method, weighted mode, multivariable MR and MR-Egger approach. RESULTS: The results of IVW methods demonstrated that genetically predicted psoriasis was significantly associated with higher odds of IPF, with an odds ratio (OR) of 1.09 (95%CI, 1.01-1.18; P = 0.02). Weighted median method, weighted mode and multivariable MR also demonstrated directionally similar results (P < 0.05), while the MR-Egger regression did not reveal the impact of psoriasis on IPF (OR = 1.09, 95%CI, 0.98-1.21; P = 0.11). In addition, both funnel plots and MR-Egger intercepts indicated no directional pleiotropic effects between psoriasis and IPF. CONCLUSIONS: Our study provided potential evidence between genetically predicted psoriasis and IPF, which suggests that understanding the mutual risk factors between psoriasis and IPF can facilitate the clinical management of both diseases.