European Respiratory Journal

RationaleIdiopathic pulmonary fibrosis (IPF) is a rare, chronic, progressive lung disease with high mortality and few treatment options. Using an additive genetic model, genome-wide association studies (GWAS) have identified multiple risk loci highlighting new genes and pathways of interest. Since IPF risk could also be influenced by non-additive effects, we hypothesised that association analyses using alternative genetic models may provide additional mechanistic insight. ObjectivesTo perform GWAS of IPF susceptibility to detect associations where the underlying effects are consistent with recessive or dominant genetic models. MethodsWe performed GWAS of IPF susceptibility, with logistic regression assuming dominant or recessive genetic models, including 5,159 IPF cases, from clinically-curated sources, and 27,459 controls. We functionally annotated independent signals and performed variant-to-gene mapping, applying fine-mapping to define potentially causal variants and genes. We assessed differential expression levels of genes of interest in publicly available single cell RNAseq data and in primary cells derived from IPF donors and controls. Main ResultsWe identified five genome-wide significant signals, under a recessive model, that had not been reported previously. These included exonic variants in the cell-cycle gene Polyamine-Modulated Factor 1 (PMF1) and in Epsin 3 (EPN3) genes. We also observed evidence of increased PMF1 expression in airway basal cells of IPF patients compared to controls. ConclusionsUsing alternative genetic models in IPF susceptibility GWAS identified new signals and genes, providing new insights into IPF pathogenesis and potential future therapies.

BackgroundThe extracellular matrix (ECM) is a dynamic network that provides structural support and maintains tissue homeostasis. Collagens are the main structural components of the ECM, occupying distinct tissue compartments and serving specialized roles. Dysregulated ECM remodeling involves an imbalance between collagen production and degradation, generating neoepitope-specific fragments that can be released into circulation. Serological measurements of these fragments can be used as biomarkers of disease and have been associated with progression and mortality in different fibrotic diseases, including pulmonary fibrosis (PF). This study aimed to investigate whether these systemic biomarkers originate from human lung tissue in patients with PF and non-fibrotic controls. MethodsLung tissue was collected from patients with PF (n = 21) and non-fibrotic controls (n = 21) and processed in parallel as formalin-fixed paraffin-embedded or snap-frozen samples. Serum samples were collected from patients with PF and healthy controls (n = 21). Neoepitope-specific biomarkers reflecting type III, IV, and VI collagen production (PRO-C3, PRO-C4, and PRO-C6) and degradation (C3M, C4M, C4Ma3, and C6M) were quantified in serum and proteolytically degraded lung tissue, and their spatial distribution was assessed by immunohistochemistry in lung tissue sections. ResultsAll collagen remodeling biomarkers were significantly increased in serum of patients with PF compared with healthy controls (PRO-C3: p = 0.0006, all others: p < 0.0001). Collagen degradation fragments (C3M, C4M, and C6M) could be generated and released from both non-fibrotic and fibrotic human lung tissue following proteolytic cleavage with pepsin, collagenase, and/or MMP-9. All biomarkers were detected in lung tissue by immunohistochemical staining, with widespread distribution of type III and IV collagen fragments, whereas type VI collagen (PRO-C6) production showed a more compartment-specific pattern. ConclusionsThese findings demonstrated that neoepitope-specific collagen remodeling biomarkers, usually detected in circulation, are present and can be released from human lung tissue. Their spatial distribution suggests that ECM remodeling is heterogeneous and differs according to collagen type and distinct tissue compartments. Collectively, our findings support the use of collagen remodeling biomarkers as tools to assess ECM remodeling in pulmonary disease.

BackgroundIdiopathic pulmonary fibrosis (IPF) is a progressive fibrotic lung disease characterized by epithelial cell senescence. Pirfenidone and nintedanib are approved drugs for the treatment of IPF. They significantly slow disease progression, but their mechanisms of action, especially on alveolar type 2 (AT2) cells, are poorly understood. We addressed this question by evaluating colony formation and growth of human AT2 cells co-cultured with fibroblasts in organoid culture in the presence of pirfenidone and nintedanib. We further evaluated molecular changes induced by these drugs via single cell RNA-seq of treated organoids. MethodsAT2 cells isolated from normal donor lungs or IPF patients were mixed with human fibroblasts in 3D culture and grown in the absence or presence of pirfenidone or nintedanib. After 14 days in culture, the organoids were quantified and cells extracted from Matrigel for single cell RNA-seq. ResultsAT2 cell organoids cultured in the presence of pirfenidone or nintedanib resulted in increased colony formation and, in the case of nintedanib, in larger colonies. We observed that untreated or pirfenidone treated AT2 cells lost surfactant protein C (SFTPC) expression and acquired an expression profile consistent with keratin (KRT)17high/KRT5- basaloid cells, whereas a larger proportion of nintedanib treated cells retained SFTPC expression. In contrast, AT2 cells treated with TGF{beta} inhibitor exhibited intermediate (SFTPC-/KRT17low) gene expression profile. ConclusionThese results suggest that nintedanib maintains an AT2-like expression state in culture and acts proximal to TGF{beta}. Conflict of Interest StatementPJW was supported by grants from Boehringer Ingelheim, Roche, Sanofi, Pliant and Arda Therapeutics and received personal fees from Boehringer Ingelheim and Sanofi. None of these companies had a role in the design or analysis of the study or in the writing of the manuscript. ASM, GP, JRR and DG are employees of Genetech. The other authors have no conflicts of interest to declare.

BackgroundReliable detection of latent Mycobacterium tuberculosis (Mtb) infection (LTBI) remains challenging, particularly in TB contacts and immunocompromised individuals, where interferon-{gamma} release assays (IGRAs) demonstrate variable sensitivity. IP-10, a chemokine produced at substantially higher concentrations than IFN-{gamma}, represents a promising immune marker. This study aimed to evaluate the diagnostic performance of two IP-10 based assays RIDA(R)QUICK TB (lateral flow) and RIDASCREEN(R) TB (ELISA), by comparison with QuantiFERON-TB Gold Plus (QFT-Plus) assay or a composite reference standard. MethodsA cross-sectional diagnostic accuracy study enrolled 99 adults: 49 with culture-confirmed active pulmonary TB, 30 close TB contacts and 20 individuals with autoimmune disease, in Bucharest, Romania. All participants underwent RIDA Quick, RIDA Screen and QFT-Plus testing. Indeterminate results for all assays were reclassified using a composite reference standard. ResultsAgainst culture in active TB cases, RIDA(R)QUICK TB demonstrated a sensitivity of 85.7% (95% CI: 72.8-94.1) and PPV of 97.7%, while RIDA(R)SCREEN TB achieved 91.8% sensitivity (95% CI: 80.4-97.7) and 97.8% PPV. Specificity and NPV could not be reliably estimated due to the near-absence of true-negative individuals. Agreement with QFT-Plus was moderate to good ({kappa}=0.47-0.93).ROC analysis performed against QFT-Plus as a comparator demonstrated good immunological discrimination for RIDA(R)QUICK TB (AUC = 0.828) and RIDA(R)SCREEN TB (AUC = 0.767), reflecting concordance with QFT-Plus rather than diagnostic accuracy against confirmed infection. ConclusionIP-10 based assays demonstrated higher sensitivity than QFT-Plus and excellent PPV across bacteriological standard, supporting their use as complementary tools for LTBI detection. Larger, more heterogeneous cohorts are needed to accurately define specificity and operational integration.

Background and AimsThe prognosis of interstitial lung diseases (ILDs) other than idiopathic pulmonary fibrosis (IPF) has not been studied as extensively as IPF. This study aimed to evaluate baseline factors associated with mortality in non-IPF ILD, including demographic characteristics, respiratory function test (RFT), comorbidities, and ILD subtypes. MethodsThis retrospective cohort study analysed prospectively collected data of patients with non-IPF ILD at a single tertiary centre in Malaysia (2010-2023). Patients without baseline RFT or HRCT were excluded. Survival was assessed using Kaplan-Meier analysis, and mortality predictors were identified using Cox regression. ResultsThe mean age was 60 {+/-} 15 years, with a male-to-female ratio of 1:3. Indian ethnicity constituted the largest group (n = 109, 47.6%). The mean baseline forced vital capacity (FVC) was 53.3 {+/-} 21% predicted. An FVC <50% predicted, age [&ge;]50 years at diagnosis, specific ILD subtypes, and ethnicity were independently associated with mortality. Compared with Malays, both Chinese (hazard ratio [HR] 9.86, 95% confidence interval [CI] 1.27-76.89, p = 0.037) and Indians (HR 8.59, 95% CI 1.14-64.69, p = 0.001) were associated with a higher risk of death. Kaplan-Meier analysis demonstrated significant differences in survival across non-IPF ILD subtypes (log-rank p = 0.048), with hypersensitivity pneumonitis showing the poorest prognosis (mean survival 6.1 years). ConclusionEthnicity emerged as an independent prognostic factor for mortality in non-IPF ILD. The underlying mechanisms remain unclear and may reflect differences in genetic variation, cultural factors, or environmental exposures. Larger prospective studies are required to validate these findings.

BackgroundProgressive pulmonary fibrosis carries poor prognosis despite availability of antifibrotics. Current progression criteria rely on functional decline (FVC [&ge;]10% decline over 6-12 months), which detects disease worsening after significant structural damage. Previous quantitative CT (qCT) methods using fixed Hounsfield unit (HU) thresholds or volume-only measurements have shown inconsistent sensitivity for early progression. We hypothesized that a hybrid approach combining HU thresholding with Z-score normalization would detect qualitative progression (tissue densification) before quantitative territorial expansion. MethodsWe developed a novel hybrid CT analysis method integrating: (1) HU threshold-based fibrosis detection (>-600 HU), (2) Z-score normalization for severity stratification (mild Z=1-2, moderate Z=2-3, severe Z[&ge;]3), and (3) five clinical progression criteria including qualitative worsening ({Delta}Z-score [&ge;]0.5). The method was validated in two ILD patients with serial CT at short intervals (3.5 and 10 months). Automated lung segmentation, fibrosis quantification, and clinical decision support were implemented in Python (scikit-image, SimpleITK, NumPy). ResultsIn the index case (progressive COPD-fibrosis overlap, 3.5-month interval), traditional volume-based analysis showed minimal change (+1 mL, +2%), below significance threshold. However, the hybrid method detected significant qualitative progression: Z-score increased from 2.35 to 2.87 (+0.52 SD, p<0.05 criterion threshold), with emergence of 24 mL new severe fibrosis (Z[&ge;]3). This represented redistribution from mild/moderate to severe categories despite stable total volume. The qualitative progression criterion triggered clinical recommendation for antifibrotic consideration, which volume-only analysis would have missed. In a comparative case (10-month interval), massive quantitative progression (+136 mL, +191.5%) with moderate qualitative component ({Delta}Z +0.24) was detected, demonstrating method sensitivity across extreme progression patterns (pure densification vs dominant territorial expansion). ConclusionsThe hybrid HU-Z-score method overcomes critical limitations of previous qCT approaches by detecting qualitative fibrosis progression (tissue densification) independent of territorial expansion. This enables identification of "Phase 1 progression" (densification) at 3-6 month intervals, earlier than functional criteria (6-12 months) or traditional volumetric CT analysis. The method provides objective, standardized clinical decision support for antifibrotic therapy initiation, addressing a critical gap in progressive fibrosing ILD management. Prospective validation in larger cohorts is warranted to establish optimal {Delta}Z-score thresholds and evaluate impact on clinical outcomes.

BackgroundTBX4 variants are a recognised cause of paediatric pulmonary hypertension (PH), often associated with interstitial lung disease (ILD). Evidence for ILD-directed therapy in this group is lacking. MethodsWe conducted a retrospective study of children ([&le;]18 years) with TBX4-associated PH at a national centre (2001-2025). ILD was defined using ChILD-EU criteria. Patients treated with pulsed intravenous methylprednisolone were assessed for response using ChILD-EU categories. Secondary outcomes included respiratory severity score (RSS), functional class (FC), echocardiographic measures, and NT-proBNP. ResultsOf 21 children, 11 (52%) had ILD; 9 received corticosteroids. Median age at treatment was 0.8 years. A clear or best response occurred in 7/9 (78%). RSS improved in 6/9 (p=0.02), with all children on respiratory support showing partial or complete weaning. Functional class improved in all with FC III/IV at baseline (p=0.02). Right ventricular function improved (TAPSE z-score +1.65, p=0.04), and elevated NT-proBNP normalised. Key clinical milestones included ECMO weaning, transplant delisting, and discontinuation of prostacyclin therapy. No significant adverse effects were observed. Untreated children showed no early improvement. ConclusionsCorticosteroids were associated with meaningful improvements in respiratory and PH outcomes in TBX4-associated PH with ILD. Prospective evaluation is warranted.

The ERS/ATS22 interpretative flowchart classifies diffusing capacity (DLco) into 5 scenarios with associated pathophysiology, and has not been tested on large patient groups. We aimed to obtain a more layered DLco interpretation, by interrogating DLco components Kco and VA, and by estimating lung inflation during the DLco test to identify the presence of restriction, which crucially impacts Kco interpretation. By assessing a "low VA" against lung inflation, a novel 9-scenario DLco classification with associated pathophysiology can be obtained. Lung patients from a tertiary center were classified according to the ERS/ATS22 chart and the novel 9-scenario one. Besides a control group of healthy subjects (n=303), disease groups under study were the following : asthma (n=1615), COPD (n=1338), CF (n=108), extrapulmonary restriction (n=122), ILD (n=98), post-COVID (n=193). Except for COPD, the prevalence of "normal DLco" (ERS/ATS22) was generally greater than that of "normal VA and normal Kco" (9-scenario); this discrepancy was most marked in CF (81% vs 56%) and in extrapulmonary restriction (57% vs 37%). With the novel 9-scenario chart, patients from very different diagnostic groups with a "low DLco" due to emphysema, bronchial disease, interstitial damage or incomplete expansion got classified across distinct scenarios, whereas ERS/ATS22 just grouped them together. In conclusion, when "low VA" is evaluated against lung inflation, a differentiation of DLco interpretation can be obtained in various patient groups involving obstruction and/or restriction. This approach can be readily implemented in clinical practice.

Background: Idiopathic pulmonary fibrosis (IPF) is a rare disease with a poor prognosis. Disease risk involves rare and common genetic variants. However, an inverse association have been described between them. Accordingly, IPF patients with a higher polygenic risk score (PRS) for IPF are less likely to carry rare deleterious variants and vice versa. Here, we evaluate weather PRS of IPF could serve as an additional criterion to patient prioritisation for rare variant discovery. Methods: We identified carriers based on the presence of rare qualifying variants (QVs) in genes linked to monogenic forms of pulmonary fibrosis in 888 IPF patients from the Pulmonary Fibrosis Foundation Patient Registry (PFF-PR). Genome-wide association study (GWAS) summary statistics from independent cohorts were used to construct a whole-genome PRS (WG-PRS) using a clumping and thresholding method (C+T) and a Bayesian method (SBayesRC). PRS were also derived from 19 known common sentinel IPF variants (Sentinel-PRS). Logistic regression models were used to evaluate associations between PRS and carrier status. Discriminatory performance was evaluated using area under the curve (AUC) analysis, and comparisons were made with DeLong test. Validation was performed in 472 IPF individuals from the UK PROFILE cohort. Results: IPF-PRS were strongly associated with the QVs carrier status: Odds Ratio [OR] 0.65 (95% Confidence Interval [CI] 0.53-0.79) for WG-PRSC+T, OR 0.71 (95% CI 0.59-0.86) for WG-PRSSBayesRC, and OR 0.77 (95% CI 0.63-0.94) for Sentinel-PRS. Adding WG-PRS to the patient personal clinical history improved the prediction of QVs carriers: AUC=0.62 for the clinical model, AUC=0.68 for WG-PRSC+T (DeLong test, p=9.54x10-4) and AUC=0.66 for WG-PRSSBayesRC (DeLong test, p=0.02). Adding of IPF-PRS to clinical variables correctly reclassified 22.8% of carriers when using WG-PRSC+T, 20.8% when using Sentinel-PRS, and 16.7% for WG-PRSSBayesRC. WG-PRSSBayesRC and the Sentinel-PRS also demonstrated improved prediction of QVs carriers in telomere-related genes in PROFILE. Conclusions: Incorporating IPF-PRS into a model based on the patient clinical history improves the identification of QVs carriers. Although the overall discriminatory power was moderate, these findings raise de the possibility of using WG-PRS as useful criterion for rare variant discovery in patients with IPF and enhance decision-making.

BackgroundIdiopathic pulmonary fibrosis (IPF) remains a fatal interstitial lung disease with limited diagnostic specificity and therapeutic options. This study integrates bulk and single-cell RNA sequencing (RNA-seq) to identify novel biomarkers and elucidate molecular mechanisms underlying IPF pathogenesis. MethodsWe prospectively enrolled 14 treatment-naive IPF patients and 6 controls. Bulk RNA-seq was performed on bronchoalveolar lavage fluid (BALF), while single-cell RNA-seq analyzed lung tissues from 4 IPF patients and 3 controls. Differentially expressed genes (DEGs) were identified (|log2FC| >1, FDR <0.05), followed by functional enrichment, protein-protein interaction (PPI) network analysis, and cell-type-specific expression profiling. Results1. DEG Identification: Bulk RNA-seq revealed 108 DEGs (24 upregulated, 84 downregulated). KEGG enrichment analysis of DEGs revealed that upregulated genes were mainly enriched in inflammation and immune pathways (such as NF-{kappa}B signaling pathway, Fc epsilon RI signaling pathway, B cell receptor signaling pathway, phagosome, Fc gamma R-mediated phagocytosis), pyrimidine metabolism, cell cycle, and PI3K-Akt signaling pathway. 2. PPI Network: Module analysis identified a proliferative gene module 1 (NUF2, CEP55, ANLN, TTK, TK1, MYBL2, CCNA2, RRM2, CDT1) linked to cell division and cycle regulation. 3. Single-Cell Insights: scRNA-seq of 30,477 cells delineated 11 populations. Module 1 genes exhibited predominant expression in proliferating cells, Module 1 signature score of proliferating cells was significantly higher in IPF than in control group. 4. Pathogenic Links: Key genes (e.g., CEP55, TTK) were associated with PI3K/AKT signaling, epithelial-mesenchymal transition (EMT), and anti-apoptotic pathways, mirroring oncogenic mechanisms. ConclusionThis multi-omics approach uncovers a proliferation-centric gene module in IPF, revealing shared molecular pathways with tumorigenesis. Our findings highlight novel diagnostic biomarkers and suggest repurposing cell cycle inhibitors as potential therapies. Future studies should validate these targets in preclinical models to advance precision medicine for IPF.

BackgroundInterstitial lung abnormalities (ILA) are radiologic findings of increased lung density or fibrosis in individuals without clinical interstitial lung disease (ILD) and are associated with increased mortality and progression to ILD. Understanding physiologic trajectories of lung function preceding ILA diagnosis may illuminate early mechanisms of lung injury. MethodsWe recruited participants from the Coronary Artery Risk Development in Young Adults (CARDIA) Lung Study, a prospective cohort of adults enrolled at ages 18-30 years and followed longitudinally for 25 years. Percent predicted forced vital capacity (ppFVC) was measured at five study visits over 20 years. Individual ppFVC trajectories were estimated using random coefficient models. Person-specific slopes were incorporated into logistic regression models to examine associations with visually detected ILA on chest CT at exam year 25. Models were adjusted for age, sex, race, body mass index, pack-years of smoking, and study center. ResultsAmong 3,136 participants with complete data, 57 (1.8%) had ILA at mean age 51 years. In univariable and multivariable models, individuals with ILA had greater cumulative decline in ppFVC over the 20 years preceding diagnosis. Each 10% absolute decline in ppFVC was associated with more than twice the odds of ILA (adjusted OR 2.21, 95% confidence interval 1.47-3.31, p = 0.0001). ConclusionsGreater longitudinal decline in FVC from early adulthood was strongly associated with the presence of ILA at midlife. These findings suggest that physiologic impairments precede radiologic evidence of subclinical parenchymal lung abnormalities, underscoring the potential of life course lung function trajectories to identify individuals at risk for developing ILD.

Background Scalable, non invasive tools are critically needed to improve early lung cancer detection and optimize primary care referral pathways. We evaluated Inflammacheck, a point-of-care device utilizing exhaled breath condensate (EBC) H2O2 and physiological parameters with machine learning, for non-invasive lung cancer detection in a real-world screening population. Methods ExPeL study participants, from the UK Targeted Lung Health Check (TLHC) programme, included individuals with suspected lung cancer and low-risk ever-smoker controls. EBC was collected via Inflammacheck, measuring H2O2;, end-tidal CO2;, humidity, temperature, and exhalation flow rate. Multivariate analyses (PCA, LDA, Mahalanobis distance) assessed intrinsic group separation. SMOTE-balanced data trained supervised machine learning models (stacked and voting ensembles), which were then evaluated on held-out test sets. In parallel, untargeted LCMS metabolomics was performed to identify discriminatory molecular features. Results Analysing 34 participants with valid EBC data, 83% of cancer cases were early-stage (I or II), reflecting a screening population. Multivariate analysis clearly separated lung cancer and controls across PCA, LDA, and Mahalanobis mapping. The voting ensemble model achieved: Accuracy 85.7%, Sensitivity 80%, Specificity 100%, Precision (PPV) 100%, ROC AUC 0.90, MCC 0.73. Crucially, no false positives were identified. EBC variables revealed greater dispersion in cancer patients, reflecting physiological heterogeneity missed by univariate analysis. Untargeted metabolomics identified 2,132 features, with four key metabolites yielding an AUC of 0.969 for cancer discrimination. Discussion Inflammacheck effectively distinguishes early-stage lung cancer via a rapid, non-invasive breath test, findings which are highly relevant for primary care and screening triage, where non-specific symptoms and low prevalence pose challenges.

Phase IIa pulmonary tuberculosis (TB) trials typically assess the early bactericidal activity (EBA) of monotherapy for over 14 days. However, few studies have evaluated drug combinations, even though optimal monotherapy doses may not directly translate to combinations. Translational pharmacokinetic-pharmacodynamic (PK-PD) modeling has shown promise in predicting human treatment responses based on preclinical monotherapy data; however, its application in drug combinations remains limited. This study aimed to extend and validate our previously developed translational monotherapy PK-PD modeling platform to predict the EBA of two-drug combinations. Interactions between bedaquiline, pretomanid, linezolid, and pyrazinamide were characterized using two modeling approaches: the empirical SUPER method and the mechanistic General Pharmacodynamic Interaction model. Both approaches were independently linked to our translational platform and validated using mouse data and Phase IIa clinical results from the NC-001 study. Both modeling methods identified consistent interaction patterns, including antagonistic interactions when bedaquiline was combined with either pretomanid or linezolid. Pyrazinamide has emerged as the most effective companion for both bedaquiline and pretomanid. Our platform reasonably predicted 14-day clinical sputum colony-forming unit counts for multiple two-drug combinations, with most observations falling within the 95% prediction intervals, supporting its use in accelerating regimen development. Our study demonstrated that the translational PK-PD platform reliably predicts both short- and long-term outcomes for combinations, regardless of the interaction model. This supports its application across drug development stages to inform dose selection and effective companion drugs for anti-TB therapies.

Genome-wide association studies of idiopathic pulmonary fibrosis (IPF) have identified 35 common genetic risk loci associated with IPF susceptibility. In this study, we evaluated the effects of the reported variants in clinically curated non-European individuals. Despite limited sample sizes, we observed partial replication, limited transferability of some variants and evidence of ancestry-specific effects. The MUC5B promoter variant rs35705950 emerged as the dominant and most consistent signal across ancestries. Our findings highlight the need for larger, well-characterised studies in understudied populations to support robust discovery and translation.

Background Acute respiratory distress syndrome (ARDS) is characterised by substantial physiological heterogeneity, which contribute to a very variable clinical outcomes and therefore inconsistent responses to ventilatory strategies. We aimed to externally validate physiological ARDS subphenotypes previously identified using routine ventilatory and gas-exchange variables, assess their prognostic relevance across independent cohorts, and examine heterogeneity of treatment effect according to PEEP strategy. Methods Unsupervised Gaussian Mixture Modelling was used to identify physiological subphenotypes based on ventilatory mechanics and gas-exchange parameters. Labels were subsequently used to train and validate supervised classifiers using XGBoost. Prognostic relevance was assessed across three independent cohorts, including two randomised controlled trials (ALVEOLI and LOVS). Predictive enrichment for PEEP strategy was evaluated using individual patient data from ALVEOLI and LOVS (n = 1,532) using intention-to-treat analyses, applying both one-stage and two-stage fixed-effects IPD meta-analytic approaches to test for interaction between physiological subphenotype and PEEP strategy. Results Two distinct physiological subphenotypes, termed Efficient and Restrictive, were replicated across independent cohorts. Across each cohort, patients classified as Restrictive consistently exhibited higher all-cause 28-day mortality compared to Efficient patients. When pooled across studies, the Restrictive subphenotype was associated with a significantly increased risk of death (pooled odds ratio 1.75, 95% CI 1.36-2.24), with no evidence of between-study heterogeneity. Predictive analyses showed a statistically significant interaction between physiological subphenotype and PEEP strategy in the one-stage IPD model (p for interaction = 0.037), with concordant findings in the two-stage fixed-effects IPD meta-analysis (interaction OR 1.91, 95% CI 1.00-3.66; I2 = 0%). Higher PEEP was associated with increased mortality in Efficient patients and reduced mortality in Restrictive patients, indicating effect modification by physiological subphenotype. Interpretation Physiological ARDS subphenotypes derived from routinely collected bedside data provide robust and externally validated prognostic stratification across observational and randomised trial cohorts. The observed interaction with PEEP strategy suggests that underlying physiological profiles may influence treatment response, supporting the concept that physiology-based be a starting point for personalized medicine and therefore better ventilatory strategies in future clinical trials.

Background Recent guidelines differ in how fractional exhaled nitric oxide (FeNO) is used to diagnose school-age asthma, either as one of several tests with a cut-off at 25 ppb or as a single rule-in test at 35 ppb. Evidence on its diagnostic performance and clinical utility in subgroups remain limited. Methods We analysed data from 1,979 school-age children in the Swiss Paediatric Airway Cohort referred for suspected asthma. We investigated FeNO performance with diagnosis by paediatric pulmonologists as reference standard using receiver operating characteristics curves, selected cut-offs and simulated predictive values across different prevalence. Subgroup analyses considered allergic sensitisation with allergic rhinitis and current inhaled corticosteroid (ICS) use. Results In the overall cohort (asthma diagnosis 70%), FeNO showed poor discrimination for asthma (AUC 0.66; 95% CI 0.64-0.68) with an optimal cut-off at 22 ppb. At 25 and 35 ppb, sensitivity was low (43%, 95% CI 40-46; 31%, 95% CI 29-34) and specificity moderate to high (84%, 95% CI 77-84; 90%, 95% CI 87-92). Positive predictive value at 35 ppb was 88% and was 57% when simulated at a prevalence of 30%. FeNO had no diagnostic value in non-sensitised children and lower performance in sensitised children with allergic rhinitis than in those without (AUC 0.59 vs 0.68). Current ICS use did not influence performance. Conclusion FeNO has limited diagnostic performance as a stand-alone test for school-age asthma, and underlying asthma prevalence and allergic characteristics should be considered in the interpretation.

Functional capacity, muscle strength, and patient-reported outcome measures are important indicators of health. In chronic obstructive pulmonary disease (COPD), these traits are often impaired beyond normal age-related decline. Substantial variability exists in both COPD and healthy populations, the biological basis of which remains poorly understood. Given the known contribution of genetics to complex traits, genetic factors may partly explain this variability. This study aimed to identify genetic variants associated with measures used to characterise extrapulmonary traits in COPD. Genome-wide association studies were conducted on the Lab3R-ESSUA cohort for the 6-minute walk test (6MWT), the 1-minute sit-to-stand test (1-min STS), the quadriceps maximal voluntary contraction (QMVC), the handgrip muscle strength, and the chronic airways assessment test (CAAT), adjusting for age, sex, body mass index, pack-years and ancestry. Variants with P<1E-05 were selected for replication in the EARLYCOPD cohort, and effects compared between COPD and healthy populations (two-way ANOVA). A total of 639 participants (364 people with COPD, 275 healthy; 75% male, median age 67 years; BMI of 27 Kg/m2; 10 pack-years) were included. Significant variants were identified for the 6MWT (rs1108983:G, {beta}=-186.5m, P=4.8E-08), the 1-min STS (rs5889103:GTT, {beta}=4.2reps, P=4.8E-08), the Handgrip (rs67352743:A, {beta}=-4.4Kg, P=2.8E-08), and for the CAAT (rs11747040:C, {beta}=4.4points, P=4.0E-09; rs11041680:A, {beta}=-2.6points, P=2.5E-08). Effects were independent of COPD diagnosis. Replication in EARLYCOPD (n=282) confirmed one SNP for 6MWT and three for CAAT. These findings highlight genetic contributions to functional capacity, muscle strength, and disease burden. COPD-related impairments appear to build on pre-existing genetic predisposition, contributing to disease heterogeneity.

Pulmonary fibrosis (PF) can arise from mutations in alveolar epithelial type 2 (AT2) cell-specific genes, but manifests in fibrotic activation of mesenchymal cells, thus involving fibrogenic epithelial-mesenchymal crosstalk. The ligand-receptor interactions underlying the onset and early progression of PF remain poorly understood. Induced pluripotent stem cell (iPSC)-derived models are powerful tools to study respiratory diseases, yet are currently limited to reductionist single lineage epithelial models or multi-lineage systems that lack purity and lung-specificity of the mesenchyme. Here we generate a human iPSC line carrying both a lung mesenchyme-specific reporter (TBX4-LERtdTomato) and a reporter for mesenchymal activation/differentiation (ACTA2GFP). Applying this line, we develop a directed differentiation protocol capable of generating cells that express key molecular and functional features of primary human developing lung mesenchyme across multiple iPSC genetic backgrounds. We then establish co-cultures of these iPSC-derived lung mesenchymal cells (iLM) with patient-specific iPSC-derived alveolar epithelial type 2 cells (iAT2s) carrying an SFTPCI73T mutation as a model for PF. We find increased expression of fibrotic markers in co-cultures with mutant iAT2s as compared to co-cultures with gene-corrected iAT2s. Moreover, mutant iAT2s express markers of alveolar-basal intermediate (ABI) cells only in the presence of iLM, suggesting that bidirectional crosstalk promotes this aberrant cell state. We identify ligand-receptor pairs enriched in co-cultures with mutant iAT2s, including TGF{beta}, multiple integrins, and additional genes that have not been previously linked to PF. Finally, we show that small molecule-mediated inhibition of TGF{beta} or integrins V{beta}1/V{beta}6 attenuates both fibrotic mesenchymal activation and the presence of ABI cells in iLM/iAT2 co-cultures. Thus, we have established a human iPSC-derived co-culture system that recapitulates key molecular hallmarks of bidirectional fibrogenic epithelial-mesenchymal crosstalk in pulmonary fibrosis, and enables the identification and study of potentially druggable pathways involved in disease initiation and progression.

Many analyses of critically ill patients focus on admission features and discharge outcomes, overlooking daily events and intercurrent complications. Pneumonia is a syndromic entity that is difficult to adjudicate outcomes without clinical expertise. Here, we examine clinical features on a day-by-day basis, mirroring the practice of daily multidisciplinary rounds, with annotated pneumonia episodes and outcomes. The Successful Clinical Response in Pneumonia Therapy (SCRIPT) CarpeDiem Dataset includes 21,931 patient-hospital-days from 704 patients enrolled in the SCRIPT study between June 2018 and May 2023. These patients were all receiving mechanical ventilation and underwent bronchoalveolar lavage to diagnose and establish the etiology of their pneumonia or an alternative diagnosis. The dataset captures patient demographics, daily clinical parameters, including vital signs, laboratory results, and mechanical support data, detailed pneumonia episode results adjudicated by critical care physicians, and outcomes. All data are de-identified per HIPAA Safe Harbor guidelines. This dataset offers a unique resource for analyzing the clinical trajectories of patients with severe pneumonia.

BackgroundPatients with acute respiratory failure requiring non-invasive respiratory support are at high risk of deterioration. Different advanced monitoring instruments are available that can provide objective measurements. However, there is currently no evidence synthesis on these instruments. The aim of this project is to systematically synthetise data identifying the advanced monitoring instruments used and their effectiveness. MethodsWe conducted a systematic search of MEDLINE (via Pubmed), EMBASE, Web of Science, Cochrane Library and CINAHL (PROSPERO registration: CRD42024597047). We included studies with acute respiratory failure patients requiring non-invasive respiratory support where the investigators used advanced monitoring instrument during hospital stay. We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. ResultsSeventy-eight studies including 3709 patients fulfilled the selection criteria. The monitoring instruments used were respiratory muscle ultrasound in 32% (n= 25/78), oesophageal manometry in 32% (n= 25/78), electrical impedance tomography in 24% (n= 19/78), electrical activity of the diaphragm (Eadi) catheter in 18% (n= 14/78) and surface EMG of parasternal muscle in 6% (n= 5/78). Thirteen studies (17%) used a multi-modal monitoring approach. Patients failing non-invasive respiratory support showed higher oesophageal pressure ({Delta}Pes) [MD 12.60 (95% CI 4.03;21.16), p=0.004], lung ultrasound score (LUS) [MD 3.93 (95% CI 1.29,6.570), p=0.003] and parasternal intercostal thickening fraction (PIC-TF%) [MD 12.58 (95% CI 8.02,17.13), p<0.001] but lower diaphragmatic thickening fraction (DTF%) [MD - 17.20 (95% CI -20.97,-13.42); p<0.001] and lower diaphragmatic excursion (DE) [MD - 0.95 (95% CI -1.08,-0.82); p<0.001. ConclusionAdvanced monitoring instruments may detect patient failing non-invasive respiratory support. Take home messageAdvanced bedside monitoring during non-invasive respiratory support can provide unique physiological insights into respiratory muscle workload and treatment response in acute respiratory failure. Our meta-analysis shows that five measurements: i) oesophageal pressure changes ({Delta}Pes), ii) lung ultrasound score (LUS), iii) parasternal intercostal thickening fraction (PIC-TF%), iv) diaphragmatic thickening fraction (DTF%) and v) diaphragmatic excursion (DE) may discriminate patients who are responders from non-responders to non-invasive respiratory support.