European Respiratory Journal最新文献

Background: Sensitisation to Aspergillus fumigatus is linked to worse outcomes in patients with COPD; however, its prevalence and clinical implications in domestic (residential) settings remains unknown.

Methods: Individuals with COPD (n=43) recruited in Singapore had their residences prospectively sampled and assessed by shotgun metagenomic sequencing including indoor air, outdoor air and touch surfaces (a total of 126 specimens). The abundance of environmental A. fumigatus and the occurrence of A. fumigatus (Asp f) allergens in the environment were determined and immunological responses to A. fumigatus allergens determined in association with clinical outcomes including exacerbation frequency. Findings were validated in 12 individuals (31 specimens) with COPD in Vancouver, Canada, a climatically different region.

Results: 157 metagenomes from 43 homes were assessed. 11 and nine separate Aspergillus spp. were identified in Singapore and Vancouver, respectively. Despite climatic, temperature and humidity variation, A. fumigatus was detectable in the environment from both locations. The relative abundance of environmental A. fumigatus was significantly associated with exacerbation frequency in both Singapore (r=0.27, p=0.003) and Vancouver (r=0.49, p=0.01) and individuals with higher Asp f 3 sensitisation responses lived in homes with a greater abundance of environmental Asp f 3 allergens (p=0.037). Patients exposed and sensitised to Asp f 3 allergens demonstrated a higher rate of COPD exacerbations at 1-year follow-up (p=0.021).

Conclusion: Environmental A. fumigatus exposure in the home environment including air and surfaces with resulting sensitisation carries pathogenic potential in individuals with COPD. Targeting domestic A. fumigatus abundance may reduce COPD exacerbations.

Fungal lung disease encompasses a wide spectrum of organisms and associated clinical conditions, presenting a significant global health challenge. The type and severity of disease are determined by underlying host immunity and infecting fungal strain. The most common group of diseases are associated with the filamentous fungus Aspergillus species and include allergic bronchopulmonary aspergillosis, sensitisation, aspergilloma and chronic and invasive pulmonary aspergillosis. Fungal lung disease remains epidemiologically heterogenous and is influenced by geography, environment and host comorbidities. Diagnostic modalities continue to evolve and now include novel molecular assays and biomarkers; however, persisting challenges include achieving rapid and accurate diagnosis, particularly in resource-limited settings, and in differentiating fungal infection from other pulmonary conditions. Treatment strategies for fungal lung diseases rely mainly on antifungal agents but the emergence of drug-resistant strains poses a substantial global threat and adds complexity to existing therapeutic challenges. Emerging antifungal agents and increasing insight into the lung mycobiome may offer fresh and personalised approaches to diagnosis and treatment. Innovative methodologies are required to mitigate drug resistance and the adverse effects of treatment. This state-of-the-art review describes the current landscape of fungal lung disease, highlighting key clinical insights, current challenges and emerging approaches for its diagnosis and treatment.

Aim: To elucidate the important cellular and molecular drivers of pulmonary long COVID, we generated a single-cell transcriptomic map of the airway mucosa using bronchial brushings from patients with long COVID who reported persistent pulmonary symptoms.

Method: Adults with and without long COVID were recruited from the general community in Greater Vancouver, Canada. The cohort was divided into those with pulmonary long COVID, which was defined as persons with new or worsening respiratory symptoms following ≥12 weeks from their initial acute severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection (n=9); and control subjects defined as SARS-CoV-2 infected persons whose acute respiratory symptoms had fully resolved or individuals who had no history of acute coronavirus disease 2019 (COVID-19) (n=9). These participants underwent bronchoscopy from which a single cell suspension was created from bronchial brush samples and then sequenced.

Results: A total of 56 906 cells were recovered for the downstream analysis, with 34 840 cells belonging to the pulmonary long COVID group, which strikingly showed a unique cluster of neutrophils in the pulmonary long COVID group (p<0.05). Ingenuity Pathway Analysis revealed that the neutrophil degranulation pathway was enriched across epithelial cell clusters. Differential gene expression analysis between the pulmonary long COVID and control groups demonstrated upregulation of inflammatory chemokines and epithelial barrier dysfunction across epithelial cell clusters, as well as over-expression of mucin genes across secretory cell clusters.

Conclusion: A single-cell transcriptomic landscape of the small airways suggest that neutrophils may play a significant role in mediating the chronic small airway inflammation driving pulmonary symptoms of long COVID.

Background: Risk prediction tools are routinely utilised in cardiothoracic surgery but have not been developed for pulmonary endarterectomy (PEA). There is no data on whether patients undergoing PEA may benefit from a tailored risk modelling approach. We develop and validate a clinically-usable tool to predict PEA 90-day mortality (90 DM) with the secondary aim of informing factors that may influence five-year mortality (5 YM) and improvement in patient-reported outcomes (PROchange) using common clinical assessment parameters. Derived model predictions were compared to those of the currently most widely implemented cardiothoracic surgery risk tool, EuroSCORE II.

Methods: Consecutive patients undergoing PEA for chronic thromboembolic pulmonary hypertension (CTEPH) between 2007 and 2018 (n=1334) were included in a discovery dataset. Outcome predictors included an intentionally broad array of variables, incorporating demographic, functional and physiological measures. Three statistical models (linear regression, penalised linear regression and random forest) were considered per outcome, each calibrated, fitted and assessed using cross-validation, ensuring internal consistency. The best predictive models were incorporated into an open-source PEA risk tool and validated using a separate prospective PEA cohort from 2019 to 2021 (n=443) at the same institution.

Results: Random forest models had the greatest predictive accuracy for all three outcomes. Novel risk models had acceptable discriminatory ability for outcome 90 DM (AUROC 0.82) outperforming that of EuroSCORE II (AUROC 0.65). CTEPH related factors were important for outcome 90 DM but 5 YM was driven by non-CTEPH factors, dominated by generic cardiovascular risk. We were unable to accurately predict a positive improvement in PRO status (AUROC 0.47).

Conclusions: Operative mortality from PEA can be predicted pre-operatively to a potentially clinically useful degree. Our validated models enable individualised risk stratification at clinician point-of-care to better inform shared decision making.

Objective: Gene expression (transcriptomics) studies have revealed potential mechanisms of interstitial lung disease (ILD), yet sample sizes of studies are often limited and between-subtype comparisons are scarce. The aim of this study was to identify and validate consensus transcriptomic signatures of ILD subtypes.

Methods: We performed a systematic review and meta-analysis of fibrotic ILD transcriptomics studies using an individual participant data approach, and included studies examining bulk transcriptomics of human adult ILD samples and excluding those focusing on individual cell populations. Patient-level data and expression matrices were extracted from 43 studies and integrated using a multivariable integrative algorithm to develop ILD classification models.

Results: Using 1459 samples from 24 studies, we identified transcriptomic signatures for idiopathic pulmonary fibrosis (IPF), hypersensitivity pneumonitis (HP), idiopathic nonspecific interstitial pneumonia (NSIP), and systemic sclerosis-associated ILD (SSc-ILD) against control samples, which were validated on 308 samples from 8 studies (area under receiver operating curve [AUC]=0.99 [95% CI: 0.99-1.00], HP AUC=0.91 [0.84-0.99], NSIP AUC=0.94 [0.88-0.99], SSc-ILD AUC=0.98 [0.93-1.00]). Significantly, meta-analysis allowed, for the first time, identification of robust lung transcriptomics signatures to discriminate IPF (AUC=0.71 [0.63-0.79]) and HP (AUC=0.76 [0.63-0.89]) from other fibrotic ILDs, and unsupervised learning algorithms identified putative molecular endotypes of ILD associated with decreased forced vital capacity (FVC) and diffusing capacity of the lungs for carbon monoxide (D_LCO) % predicted. Transcriptomics signatures were reflective of both cell-specific and disease-specific changes in gene expression.

Conclusion: We present the first systematic review and largest meta-analysis of fibrotic ILD transcriptomics to date, identifying reproducible transcriptomic signatures with clinical relevance.