European Respiratory Journal

BackgroundIdiopathic 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. MethodsWe 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 DeLongs test. Validation was performed in 472 IPF individuals from the UK PROFILE cohort. ResultsIPF-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 patients personal clinical history improved the prediction of QVs carriers: AUC=0.62 for the clinical model, AUC=0.68 for WG-PRSC+T (DeLongs test, p=9.54x10-4) and AUC=0.66 for WG-PRSSBayesRC (DeLongs 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. ConclusionsIncorporating IPF-PRS into a model based on the patients 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.

RationalePrimary Ciliary Dyskinesia (PCD) is a genetic disorder characterized by impaired ciliary function, defective mucociliary clearance, and progressive lung disease. Pathogenic variants in the DNAI1 gene are a well-known cause of PCD. Currently, no approved therapies address the underlying genetic defect. RCT1100 is an inhaled mRNA therapy encoding DNAI1 currently under clinical development. This study evaluates the functional effects of RCT1100 using a fast three-dimensional explant spheroid (3DE-S) model consisting of apical-out undifferentiated nasal epithelial cells derived from patients with DNAI1 PCD. Methods3DE-S were generated from nasal brushings of five patients with confirmed biallelic DNAI1 variants. RCT1100 was administered from day 5 directly to culture wells three times weekly for two weeks. Spheroid motility was assessed throughout treatment by quantifying the proportion of moving spheroid rolling and their movement velocity. Following six doses, spheroids were harvested for high-speed video microscopy for assessment of ciliary beat frequency. ResultsEvaluable data were obtained from three of five patient samples; two samples were excluded due to contamination. After six doses of RCT1100, ciliary beat frequency increased from a baseline range of 2.8-3.5 Hz to 6.7-6.8 Hz post-harvesting. Mean spheroid movement velocity increased from 0.11 {micro}m/sec to 3.87 {micro}m/sec following dosing with 10 {micro}g/mL RCT1100, with more than 80% of spheroids exhibiting coordinated rolling motion pattern. ConclusionThe 3DE-S is a robust platform for evaluating targeted therapies. RCT1100 significantly restored ciliary function, supporting its therapeutic potential and highlighting the utility of spheroid-based systems for precision medicine approaches in DNAI1 PCD.

BackgroundThe assessment of daily-life physical activity (DLPA) using wearables in patients with pulmonary hypertension (PH) can provide information on real-world function, potentially enhancing the evaluation of disease progression. Research QuestionWhat is the existing evidence on sensor-based DLPA assessment in patients with PH and its quality? Study Design and MethodsWe searched MEDLINE and Embase from inception to January 13, 2026, extracting data on devices, DLPA outcomes, and associations with clinical outcomes. We obtained pooled estimates through random-effects models and assessed evidence quality using a customized tool. ResultsWe identified 33 studies (29 adult, 4 pediatric) including 1,257 patients mainly with pulmonary arterial hypertension (PAH), followed by chronic thromboembolic PH (CTEPH), and only rarely with PH due to lung diseases and/or hypoxia. Participants were predominantly female, WHO functional class II-III. Most studies investigated step count and time spent in different physical activity levels, but showed substantial heterogeneity in devices and their utilization. The meta-estimate was 4,811 daily steps. A moderate positive correlation was found between daily step count and six-minute walking distance (6MWD) (r=0.59, 95%CI 0.47-0.69); a weak positive correlation was found between time spent in moderate-to-vigorous physical activity and 6MWD (r=0.38; 95% CI 0.26-0.49). Inconsistent wear-time definition, non-wear reporting and temporal misalignment of DLPA may compromise validity and comparability. InterpretationWearable-based DLPA assessment in PH is feasible, though high-quality evidence remains scarce. Future research should standardize procedures, terminology, and reporting of DLPA outcomes. Concordance with established measures such as the 6MWD, and their ability to predict clinical outcomes and disease progression need to be demonstrated.

BackgroundBoth rare and common variants in the SRY-Box Transcription Factor 17 (SOX17) locus are associated with pulmonary arterial hypertension (PAH). SOX17 dysregulation leads to pulmonary artery endothelial cell (PAEC) dysfunction and the obstructive remodelling that characterises PAH. HypothesisImpaired SOX17 expression contributes to the pathogenesis of PAH. Restoring the function of SOX17 or its downstream targets using compounds that mimic its transcriptomic signature will rescue PAEC dysfunction and prevent PAH development. Methods and ResultsWe defined thousands of genes with direct SOX17 genomic binding sites and identified important potential binding partners, including ETS-transcription factors such as ERG by ChIP-seq in PAECs. Through the integration of three PAEC RNA-seq datasets involving overexpression and silencing of SOX17, we defined a robust SOX17 transcriptomic signature. In PAH patients, circulating plasma protein levels of 10 SOX17 signature genes were associated with the SOX17 common risk variants. This included EFNB2 and UNC5B; knockdown of these genes altered the viability and apoptosis of PAECs in response to TNF treatment. The drug-transcriptome database Connectivity Map (CMap) was used to predict novel potential therapeutic compounds to correct the SOX17 transcriptomic signature. Five compounds were selected for in vitro testing and were able to partially reinstate SOX17 target gene expression in PAECs. One compound, BX-912, was selected for in vivo testing as it corrected the levels of multiple target genes, including suppressing Runt-related transcription factor-1 (RUNX1). BX-912 blocked the development of pulmonary hypertension in mice lacking the SOX17 enhancer associated with human disease. ConclusionWe have demonstrated the therapeutic potential of targeting SOX17 in PAH through correction of its gene targets, identifying BX-912 as a lead compound with in vivo efficacy.

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 ([≤]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.

Background The European Association for the Study of the Liver (ESAL) - Steatotic Liver Disease (SLD) screening algorithm involves two steps; initial screening with FIB-4 followed by referral for vibration-controlled transient elastography (VCTE) in patients likely to have significant fibrosis (SF). However, VCTE is not widely available in resource-limited settings. Aim To optimise the EASL SLD screening algorithm for resource-poor settings using machine learning (ML). Methods We analysed data from 964 adults aged [≥]35 years who underwent VCTE at a tertiary referral centre in Sri Lanka between November 2024 and 2025. Multiple ML models using different methods and variable combinations were trained on 80% of the dataset and tested on the remaining 20%. Best models were selected based on performance and externally validated using data from 430 patients who underwent VCTE before November 2024. Model performance was compared with the FIB-4 using confusion matrices. Results A Random Forest model incorporating age, AST, ALT, and platelet count separately, rather than using FIB-4, outperformed. The all-variable ML model showed the best predictive performance for SF, with accuracy of 77.2%, recall of 0.762, precision of 0.778, and AUC-ROC of 0.818. The variables used in the model, in descending order of feature importance, were AST, platelet count, BMI, ALT, age, diabetes mellitus, hypertension, dyslipidaemia, sex, family history, hypothyroidism, diabetes complication and smoking. External validation demonstrated 75.1% accuracy and an AUC of 0.779. When used as the first step of the SLD screening algorithm, the all-variable ML model identified 37 (17.1%) additional true positives and reduced false-negative diagnoses by 50% compared with FIB-4. Conclusions ML-based models were more effective than the FIB-4 score as the first-line screening tool for VCTE referral, substantially improving the identification of patients with significant fibrosis in this South Asian cohort.

Background. The intrapulmonary pharmacokinetics of antimicrobial agents used to treat nontuberculous mycobacterial (NTM) pulmonary disease remain poorly characterized, limiting the optimization of dosing regimens. This study characterized the plasma and intrapulmonary pharmacokinetics of azithromycin, ethambutol, rifampicin, clofazimine, and amikacin, as well as their penetration into pulmonary lesion sites. Methods. We prospectively enrolled patients undergoing guideline-based treatment for NTM pulmonary disease who were indicated for surgical resection at a single center in Japan. Drug concentrations were measured in the plasma and lung samples, and analyzed using a population pharmacokinetic model. The lung lesion site, cavity, or nodule/bronchiectatic were evaluated as covariates of the plasma-to-lung partition ratios. Results. Twenty-four patients were enrolled in the study. Antimicrobial agents other than rifampicin and amikacin accumulate in the lungs at concentrations > 40-fold higher than those in the plasma. Notably, the intrapulmonary half-life of ethambutol, which has not been well-characterized to date, is estimated to be approximately 2 months, indicating prolonged retention within the lungs. Evaluation of drug penetration into cavities and nodular/bronchiectatic lesions showed no clearly reduced concentration compared to that of normal lung tissue. However, in the single case where the caseum was obtained, azithromycin, ethambutol, and rifampicin levels exhibited clearly lower concentrations. Conclusions. Ethambutol shows a prolonged intrapulmonary half-life, suggesting sustained lung exposure even with intermittent dosing. The absence of clearly reduced drug penetration into lesion sites suggests that lesion phenotype alone may have limited value in guiding drug selection.

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.

ObjectiveTo test whether machine learning (ML) models trained on tidal breathing flow time series can discriminate between individuals with and without respiratory disease and predict lung function indices obtained from conventional pulmonary function testing. BackgroundAccurate assessment of respiratory function in infants and young children is challenging because conventional pulmonary function testing requires sophisticated equipment and/or active patient cooperation. Tidal breathing measurements, in contrast, can be obtained non-invasively with little or no patient cooperation and at low cost, yet their clinical utility has been limited. We hypothesized that sufficiently long tidal breathing flow time series contain clinically relevant information that can be extracted using a recurrent neural network known as a long short-term memory (LSTM) network. ApproachWe evaluated LSTM models in two scenarios within the Basel-Bern Infant Lung Development cohort. First, we assessed the ability of a model trained on flow and derived volume time series to detect bronchopulmonary dysplasia (BPD) in 329 infants. Second, we examined whether a model trained on tidal breathing flow alone could predict forced expiratory volume in one second (FEV1) in 135 school-age children. Signals were filtered and normalized prior to model training, and performance was evaluated on held-out test datasets. Main resultsFor BPD detection, the model achieved 97.0% accuracy, 100% specificity, 91.7% sensitivity, 100% precision, and an F1-score of 95.7%. For FEV1 prediction, Bland-Altman analysis showed a mean bias of -0.009 L (95% CI -0.091 to 0.074), with limits of agreement of -0.416 L and 0.399 L. The mean relative prediction error was 13.7%. SignificanceThese findings demonstrate that temporal patterns in tidal breathing flow signals contain diagnostically and functionally relevant information. ML applied to tidal breathing measurements may provide a low-burden, minimal-cooperation approach for early respiratory disease detection and functional assessment across early life stages.

RationaleFibrotic lung diseases, such as idiopathic pulmonary fibrosis (IPF) and fibroproliferative remodeling in acute respiratory distress syndrome (ARDS), are characterized by increased extracellular matrix (ECM) deposition. However, measuring collagen accumulation alone does not capture differences in ECM organization or biochemical maturation that may distinguish persistent fibrosis from potentially reversible remodeling. ObjectivesTo examine collagen organization characteristics and mature (pyridinoline) collagen crosslinking amount in established end stage fibrotic lung disease (IPF) and fibroproliferation following an acutely damaged lung (non-resolving (NR) ARDS) and to investigate any relationships in these parameters and temporal tissue remodeling. MethodsHuman lung tissue samples from control subjects, patients with IPF, and NR-ARDS were analyzed. Collagen amount and fiber organization were digitally quantified using picrosirius red staining. Mature collagen crosslinking was assessed by quantification of pyridinoline crosslinks. Measurements and Main ResultsLung tissue from both IPF and NR-ARDS lungs had higher collagen content compared with controls. Collagen fiber organization differed between groups. IPF lungs exhibited collagen architectures consistent with established fibrosis, whereas NR-ARDS lungs showed altered but less stabilized collagen organization despite similarly elevated collagen levels. Mature collagen crosslinks were significantly higher in IPF lungs but not in NR-ARDS lungs compared to controls. Integrated analyses identified distinct disease-associated ECM phenotypes, indicating that higher collagen abundance in NR-ARDS, unlike IPF, is not accompanied by more mature and persistent collagen crosslinking. ConclusionsDespite shared increases in collagen content, IPF and NR-ARDS lungs differ fundamentally in collagen organization and crosslinking maturity, suggesting differences in the reversibility of these conditions.

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.

BackgroundRecent 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. MethodsWe 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. ResultsIn 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. ConclusionFeNO 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.

Equine asthma (EA) is a highly prevalent, chronic, inflammatory disease of the lower airways ranging from mild-to-moderate to severe clinical presentations. Diagnosis currently relies on bronchoalveolar lavage fluid (BALF) cytology, an invasive method associated with interobserver variability, which highlights the need for more reproducible approaches. MicroRNAs (miRNAs) are small noncoding RNAs involved in post-transcriptional gene regulation. They are stable and readily detectable in body fluids and have shown promising results as biomarkers in human asthma. The aim of this study was to characterize miRNA abundance profiles in BALF and serum from horses with distinct EA endotypes to evaluate their biomarker potential and explore their involvement in disease pathogenesis. A total of 43 horses were included and classified as either EA (n=32) or controls (n=11), based on clinical examination and BALF cytology. The EA horses were further divided into three endotypes based on BALF inflammatory cell composition: neutrophilic asthma (n=10), mastocytic asthma (n=15), and mixed asthma (n=7). RNA was isolated from both serum and BALF samples and analyzed by quantitative real-time PCR (qPCR) targeting 103 miRNAs linked to asthma and pulmonary inflammation in humans. Differential miRNA abundance was analyzed across EA endotypes. The most significantly differentially abundant miRNAs were used for in silico target prediction and pathway enrichment analyses. Horses with mixed EA had significantly lower levels of eca-miR-125a-3p and eca-miR-125b-5p in BALF compared to controls. Additionally, eca-miR-146a-5p abundance was significantly increased in BALF from horses with neutrophilic EA compared to mastocytic EA. Target and pathway enrichment analyses for eca-miR-146a-5p identified immune-relevant pathways, such as MAPK and T-cell receptor signaling, supporting its involvement in inflammatory processes associated with asthma. This study identified three promising candidates, eca-miR-125a-3p, eca-miR-125b-5p, and eca-miR-146a-5p, as potential biomarkers associated with different EA endotypes. These miRNAs are interesting candidates for further investigation in an independent cohort.

Background/Objectives: Influenza infection is a major trigger of pneumonia and acute exacerbations among patients with chronic obstructive pulmonary disease (COPD). However, national laboratory-confirmed evidence on influenza vaccine effectiveness (VE) in this high-risk population remains limited. This study aimed to estimate the effectiveness of seasonal influenza vaccination against influenza-associated pneumonia and COPD exacerbations among patients with COPD in Thailand.Methods: We conducted a nationwide retrospective test-negative design study using administrative healthcare data from the National Health Security Office linked with laboratory-confirmed influenza surveillance data between June 1, 2013, and May 31, 2025, covering twelve influenza seasons (2013-2024). COPD-related clinical episodes among patients aged [≥]40 years who presented with pneumonia or acute exacerbation of COPD and underwent RT-PCR testing for influenza were included. Multilevel Poisson regression models were used to estimate adjusted risk ratios (RRs), and VE was calculated as (1 - adjusted RR) x 100.Results: A total of 606,072 COPD-related clinical episodes were included, of which 192,224 (31.7%) were influenza-positive. The overall adjusted VE against influenza-associated pneumonia was 63.2% (95% CI: 62.5-64.0), while VE against influenza-associated COPD exacerbations was 67.0% (95% CI: 48.8-78.8). VE estimates were broadly similar across age groups and remained substantial across COPD severity strata. Although point estimates were numerically higher in severe and very severe COPD, subgroup differences should be interpreted cautiously.Conclusions: Seasonal influenza vaccination was associated with substantial protection against influenza-associated pneumonia and COPD exacerbations among patients with COPD in Thailand.

BackgroundPleuroparenchymal fibroelastosis (PPFE) is a rare, fibrotic lung disease with poor prognosis, usually affecting adults which most commonly occurs idiopathically. Biallelic pathogenic variants in DGUOK cause mitochondrial DNA (mtDNA) depletion syndrome, predominantly affecting infants with severe hepatic and neurological symptoms. Detailed description of pulmonary manifestations with late-onset presentation have not been reported. MethodsWe describe nine patients with PPFE and DGUOK-associated mitochondriopathy. Clinical, radiological, histopathological, and genetic data were systematically collected from all patients. Functional studies, single nucleus RNA sequencing (snRNAseq), immunofluorescence staining, transmission electron microscopy and respiratory chain enzyme activity assays were conducted on patient-derived fibroblasts, muscle or lung tissues. mtDNA content quantification was performed on whole genome sequencing (WGS) data. ResultsAll patients (ages 5-36) presented with progressive dyspnea, weight loss and some with spontaneous pneumothoraces. Chest computed tomography and lung biopsies showed features of PPFE. Biallelic pathogenic DGUOK variants were identified in all patients, seven of them carry an unreported intronic variant leading to mtDNA depletion. snRNAseq of lung tissue from four pediatric patients identified Aberrant Basaloid cells and intermediate cells as their precursor localized at the fibrotic edge. Mitochondrial alterations were identified by electron microscopy. ConclusionPPFE in children and young adults is associated with DGUOK-related mitochondriopathy. For the first time, we demonstrate Aberrant Basaloid cells in pediatric fibrotic lung tissue. Since pulmonary involvement may be underrecognized or misinterpreted and the clinical presentation may not always be typical of a mitochondriopathy, we recommend genetic testing in all patients with PPFE of unknown origin.

Background[RP1.1] In low-burden countries such as France, whole-genome sequencing (WGS) is increasingly integrated into routine tuberculosis (TB) surveillance to improve case management and transmission monitoring. However, applying WGS to all TB cases generates large volumes of data, requiring automated tools for timely interpretation and outbreak response. Methods Since November 2016, all clinical M. tuberculosis isolates diagnosed in eight hospitals from three cities of Auvergne-Rhone-Alpes in France have undergone WGS. In July 2023, an automated pipeline for anti-TB drug resistance prediction and unbiased detection of transmission clusters based on SNP distances was implemented. Epidemiological, microbiological and clinical data were collected, with contact duration classified as household, frequent, or occasional. Index cases were stratified by their level of extra-household transmission (EHT), and statistical analyses were performed to identify associated factors. Findings Among 1,152 TB patients diagnosed between 2016 and 2025, 75 clusters involving 247 patients (21.4%) were identified. WGS reliably detected resistance to first-line anti-TB drugs, leveraging the WHO mutation catalogue. Routine WGS enabled real-time alerts for TB control centres, leading to expanded field investigations, including community spillover, nosocomial transmissions, and school outbreak. Classical indicators of contagiousness (smear results, cavitary disease) were not associated with EHT level. Instead, lower TB severity indices and longer duration of symptoms were linked to higher EHT level. Interpretation Systematic WGS supports timely identification of drug resistance and transmission events and provides new insights into contagiousness factors. The automated pipeline enables direct interpretation by clinical microbiologists, facilitating real-time public health action. In this study, we demonstrate how, with the appropriate pipeline, WGS offered a time- and cost-effective solution for routine TB management. Funding This work was supported by SHAPE-Med@Lyon, a French government grant managed by the French National Research Agency under the France 2030 program (reference ANR-22-EXES-0012).

Background Genetic studies to date are yet to define the major portion of the genetic risk for adult-onset pulmonary fibrosis (PF). Further the dearth of knowledge of clinically actionable variants for PF is hampering efforts to implement genetic testing to aid early diagnosis and improve disease management. Here we evaluated the contribution of rare and common variants to PF in cohorts with and without a family history of PF. Method Whole genome sequencing (WGS) was performed in a familial cohort comprising PF cases and their family members (85 individuals representing 55 families); and 122 cases from the Australian IPF Registry (AIPFR) with and without a self-reported family history of PF. WGS data were interrogated for rare potentially PF-causing variants in 33 genes previously associated with PF. Variants that were rare and predicted to be likely causative were formally curated using the American College of Medical Genetics and Association for Molecular Pathology (ACMG-AMP) guidelines. Additionally, to examine the common risk variant contribution, a weighted polygenic risk score (PRS) was generated using 16 previously IPF-associated common SNPs. PRS were generated from WGS for the 85 clinically confirmed familial cases and 122 AIPFR cases. In the remaining 202 AIPFR cases, PRS were generated from TaqMan genotyping data. Results Interrogation of WGS generated from 207 individuals with PF revealed multiple rare putative pathogenic variants in both familial and AIPFR cohorts. Formal curation revealed pathogenic (P) or likely pathogenic (LP) variants confirmed in TERT or RTEL1 in four families (7.3%) with the majority of remaining variants classified as variants of uncertain significance (VUS; 12.7%) in seven additional families. Amongst AIPFR participants, four variants met the threshold for classification as P/LP variants (3.3%), with a further six individuals found to harbour VUS following curation (4.9%). Overall weighted PRS did not differ significantly between individuals with familial PF or with no reported family history. However, PRS in all patient groups were significantly elevated compared with population controls. Conclusion VUS remain the major portion of rare variants identified in known PF -related genes. For ~80% individuals with a confirmed family history no potentially causative variants were identified in known PF related genes nor was there evidence that a high burden of common variants contributed to risk in these families. Similarly, we found no evidence that a high burden of common variants contributes to a significant proportion of risk PF in those individuals with no reported family history.

Lung fibroblasts are key regulators of tissue homeostasis and extracellular matrix (ECM) remodeling, and their aberrant activation drives the progressive parenchymal scarring characteristic of idiopathic pulmonary fibrosis (IPF), a fatal disease with limited therapeutic options. Despite their central pathogenic role, lung fibroblasts are difficult to isolate due to their embedded position within the ECM, and standard in vitro culture conditions may lead to the loss of their native functional and transcriptional characteristics, hampering the study of fibroblast behavior in disease. The transcriptional heterogeneity of lung fibroblast subtypes and the extent to which culture-induced alterations diverge from native tissue signatures remain poorly understood. Here, we integrated single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics of lung tissue from IPF patients and age-matched healthy donors with transcriptomic profiling of cultured fibroblasts collected at passages 1 and 6 after isolation using three optimized protocols: whole lung cell suspension (WLCS), negative fraction enrichment, and outgrowth. Tissue-based analysis identified six transcriptionally distinct mesenchymal subtypes: alveolar, adventitial, inflammatory, peribronchial, CTHRC1+ and smooth muscle cell (SMC). The fibroblast subtype CTHRC1+ represented the most transcriptionally activated pro-fibrotic subtype, showing the greatest upregulation of ECM biosynthesis genes, a prominent role in intercellular communication, and preferential enrichment within fibroblastic foci in IPF lung tissue. Pseudotime trajectory analysis supported a directional transcriptional continuum from alveolar and inflammatory fibroblasts toward the CTHRC1+ state, driven by coordinated activation of pro-fibrotic transcription factors, including RUNX2, CREB3L1, and SCX. In vitro culture progressively reshaped fibroblast transcriptional identity relative to native tissue, with increased collagen and matrix metalloproteinase (MMP) expression during passaging, loss of distinct CTHRC1+ fibroblasts, and gain of alveolar fibroblasts displaying pro-fibrotic activation across all isolation protocols. These findings provide a high-resolution transcriptional map of lung fibroblast heterogeneity in IPF and highlight critical limitations of standard in vitro culture systems for recapitulating native fibroblast diversity, with important implications for the development and evaluation of fibroblast-targeted therapeutic strategies in IPF.

ABSTRACT Background: Corticosteroids reduce mortality in severe COVID-19 requiring oxygen or invasive mechanical ventilation, yet emerging data suggest that SARS-CoV-2-associated acute lung injury is biologically heterogeneous and that treatment response may vary across molecularly defined disease states. Lung-derived molecular endotypes of severe COVID-19-associated acute lung injury have been described, but direct molecular profiling is not routinely available at the bedside. We evaluated whether a clinical predictor of previously defined lung molecular endotype identifies heterogeneity in corticosteroid treatment effect among mechanically ventilated patients with COVID-19. Methods: We utilized a single-center cohort of 5,000 patients with COVID-19 treated at the University of North Carolina Hospital between January 1, 2020, and December 31, 2022, to emulate a target trial assessing the effect of corticosteroid receipt on mortality, length of stay, and incident organ support. Confounding was addressed through inverse probability of treatment weighting (IPTW). Outcomes for severely ill patients requiring mechanical ventilation were compared to the RECOVERY trial results, with subsequent moderation analysis and stratified analysis by clinically predicted lung molecular endotype and vaccination status. The primary outcome was 28-day mortality. Secondary Outcomes were time to discharge alive and progression to additional organ support. Results: This emulated target trial showed a directionally favorable but non-statistically significant association between corticosteroid treatment and reduced 28-day mortality in patients requiring mechanical ventilation for SARS-CoV-2 infection. A clinical predictor of lung molecular endotype moderated the effect of corticosteroids on 28-day mortality (p-value for interaction 0.038) and identified distinct predicted endotype-specific treatment effect. Corticosteroid treatment was associated with lower 28-day mortality in the predicted Hyper-Inflammatory endotype (OR 0.62, 95% CI 0.39, 0.99) but not in the predicted Metabolic Dysregulation endotype (OR 1.15, 95% CI 0.82, 1.61). We did not detect significant effect modification by vaccination status (p-value for interaction 0.65), although inference was limited by the small, vaccinated subgroup (28-mortality OR 0.78, 95% CI 0.37, 1.65 in vaccinated vs 0.94, 95% CI 0.70, 1.26 in unvaccinated). Conclusions: In this target trial emulation of mechanically ventilated patients with severe COVID-19, corticosteroid treatment showed a directionally favorable but non-statistically significant association with reduced 28-day mortality in the overall cohort. However, a clinical predictor of lung molecular endotype identified significant heterogeneity in treatment effect, with benefit concentrated in the predicted Hyper-Inflammatory endotype and no apparent benefit in the predicted Metabolic Dysregulation endotype. These findings support prospective validation of clinically deployable endotype-guided corticosteroid treatment strategies in acute lung injury and ARDS.