Generation of a Broadly Useful Model for COVID-19 Pathogenesis, Vaccination, and Treatment.

COVID-19, caused by SARS-CoV-2, is a virulent pneumonia, with >4,000,000 confirmed cases worldwide and >290,000 deaths as of May 15, 2020. It is critical that vaccines and therapeutics be developed very rapidly. Mice, the ideal animal for assessing such interventions, are resistant to SARS-CoV-2. Here, we overcome this difficulty by exogenous delivery of human ACE2 with a replication-deficient adenovirus (Ad5-hACE2). Ad5-hACE2-sensitized mice developed pneumonia characterized by weight loss, severe pulmonary pathology, and high-titer virus replication in lungs. Type I interferon, T cells, and, most importantly, signal transducer and activator of transcription 1 (STAT1) are critical for virus clearance and disease resolution in these mice. Ad5-hACE2-transduced mice enabled rapid assessments of a vaccine candidate, of human convalescent plasma, and of two antiviral therapies (poly I:C and remdesivir). In summary, we describe a murine model of broad and immediate utility to investigate COVID-19 pathogenesis and to evaluate new therapies and vaccines.

ErbB3 Governs Endothelial Dysfunction in Hypoxia-Induced Pulmonary Hypertension.

BACKGROUND: Pulmonary hypertension, characterized by vascular remodeling, currently lacks curative therapeutic options. The dysfunction of pulmonary artery endothelial cells plays a pivotal role in the initiation and progression of pulmonary hypertension (PH). ErbB3 (human epidermal growth factor receptor 3), also recognized as HER3, is a member of the ErbB family of receptor tyrosine kinases. METHODS: Microarray, immunofluorescence, and Western blotting analyses were conducted to investigate the pathological role of ErbB3. Blood samples were collected for biomarker examination from healthy donors or patients with hypoxic PH. The pathological functions of ErbB3 were further validated in rodents subjected to chronic hypoxia- and Sugen-induced PH, with or without adeno-associated virus-mediated ErbB3 overexpression, systemic deletion, or endothelial cell-specific ErbB3 knockdown. Primary human pulmonary artery endothelial cells and pulmonary artery smooth muscle cells were used to elucidate the underlying mechanisms. RESULTS: ErbB3 exhibited significant upregulation in the serum, lungs, distal pulmonary arteries, and pulmonary artery endothelial cells isolated from patients with PH compared with those from healthy donors. ErbB3 overexpression stimulated hypoxia-induced endothelial cell proliferation, exacerbated pulmonary artery remodeling, elevated systolic pressure in the right ventricle, and promoted right ventricular hypertrophy in murine models of PH. Conversely, systemic deletion or endothelial cell-specific knockout of ErbB3 yielded opposite effects. Coimmunoprecipitation and proteomic analysis identified YB-1 (Y-box binding protein 1) as a downstream target of ErbB3. ErbB3 induced nuclear translocation of YB-1 and subsequently promoted hypoxia-inducible factor 1/2α transcription. A positive loop involving ErbB3-periostin-hypoxia-inducible factor 1/2α was identified to mediate the progressive development of this disease. MM-121, a human anti-ErbB3 monoclonal antibody, exhibited both preventive and therapeutic effects against hypoxia-induced PH. CONCLUSIONS: Our study reveals, for the first time, that ErbB3 serves as a novel biomarker and a promising target for the treatment of PH.

Artificial intelligence in COPD CT images: identification, staging, and quantitation.

Chronic obstructive pulmonary disease (COPD) stands as a significant global health challenge, with its intricate pathophysiological manifestations often demanding advanced diagnostic strategies. The recent applications of artificial intelligence (AI) within the realm of medical imaging, especially in computed tomography, present a promising avenue for transformative changes in COPD diagnosis and management. This review delves deep into the capabilities and advancements of AI, particularly focusing on machine learning and deep learning, and their applications in COPD identification, staging, and imaging phenotypes. Emphasis is laid on the AI-powered insights into emphysema, airway dynamics, and vascular structures. The challenges linked with data intricacies and the integration of AI in the clinical landscape are discussed. Lastly, the review casts a forward-looking perspective, highlighting emerging innovations in AI for COPD imaging and the potential of interdisciplinary collaborations, hinting at a future where AI doesn't just support but pioneers breakthroughs in COPD care. Through this review, we aim to provide a comprehensive understanding of the current state and future potential of AI in shaping the landscape of COPD diagnosis and management.

Single-cell analysis reveals alterations in cellular composition and cell-cell communication associated with airway inflammation and remodeling in asthma.

BACKGROUND: Asthma is a heterogeneous disease characterized by airway inflammation and remodeling, whose pathogenetic complexity was associated with abnormal responses of various cell types in the lung. The specific interactions between immune and stromal cells, crucial for asthma pathogenesis, remain unclear. This study aims to determine the key cell types and their pathological mechanisms in asthma through single-cell RNA sequencing (scRNA-seq). METHODS: A 16-week mouse model of house dust mite (HDM) induced asthma (n = 3) and controls (n = 3) were profiled with scRNA-seq. The cellular composition and gene expression profiles were assessed by bioinformatic analyses, including cell enrichment analysis, trajectory analysis, and Gene Set Enrichment Analysis. Cell-cell communication analysis was employed to investigate the ligand-receptor interactions. RESULTS: The asthma model results in airway inflammation coupled with airway remodeling and hyperresponsiveness. Single-cell analysis revealed notable changes in cell compositions and heterogeneities associated with airway inflammation and remodeling. GdT17 cells were identified to be a primary cellular source of IL-17, related to inflammatory exacerbation, while a subpopulation of alveolar macrophages exhibited numerous significantly up-regulated genes involved in multiple pathways related to neutrophil activities in asthma. A distinct fibroblast subpopulation, marked by elevated expression levels of numerous contractile genes and their regulators, was observed in increased airway smooth muscle layer by immunofluorescence analysis. Asthmatic stromal-immune cell communication significantly strengthened, particularly involving GdT17 cells, and macrophages interacting with fibroblasts. CXCL12/CXCR4 signaling was remarkedly up-regulated in asthma, predominantly bridging the interaction between fibroblasts and immune cell populations. Fibroblasts and macrophages could jointly interact with various immune cell subpopulations via the CCL8/CCR2 signaling. In particular, fibroblast-macrophage cell circuits played a crucial role in the development of airway inflammation and remodeling through IL1B paracrine signaling. CONCLUSIONS: Our study established a mouse model of asthma that recapitulated key pathological features of asthma. ScRNA-seq analysis revealed the cellular landscape, highlighting key pathological cell populations associated with asthma pathogenesis. Cell-cell communication analysis identified the crucial ligand-receptor interactions contributing to airway inflammation and remodeling. Our findings emphasized the significance of cell-cell communication in bridging the possible causality between airway inflammation and remodeling, providing valuable hints for therapeutic strategies for asthma.

Human genetic associations of the airway microbiome in chronic obstructive pulmonary disease.

Little is known about the relationships between human genetics and the airway microbiome. Deeply sequenced airway metagenomics, by simultaneously characterizing the microbiome and host genetics, provide a unique opportunity to assess the microbiome-host genetic associations. Here we performed a co-profiling of microbiome and host genetics with the identification of over 5 million single nucleotide polymorphisms (SNPs) through deep metagenomic sequencing in sputum of 99 chronic obstructive pulmonary disease (COPD) and 36 healthy individuals. Host genetic variation was the most significant factor associated with the microbiome except for geography and disease status, with its top 5 principal components accounting for 12.11% of the microbiome variability. Within COPD individuals, 113 SNPs mapped to candidate genes reported as genetically associated with COPD exhibited associations with 29 microbial species and 48 functional modules (P < 1 × 10-5), where Streptococcus salivarius exhibits the strongest association to SNP rs6917641 in TBC1D32 (P = 9.54 × 10-8). Integration of concurrent host transcriptomic data identified correlations between the expression of host genes and their genetically-linked microbiome features, including NUDT1, MAD1L1 and Veillonella parvula, TTLL9 and Stenotrophomonas maltophilia, and LTA4H and Haemophilus influenzae. Mendelian randomization analyses revealed a potential causal link between PARK7 expression and microbial type III secretion system, and a genetically-mediated association between COPD and increased relative abundance of airway Streptococcus intermedius. These results suggest a previously underappreciated role of host genetics in shaping the airway microbiome and provide fresh hypotheses for genetic-based host-microbiome interactions in COPD.

The association between preserved ratio impaired spirometry and adverse outcomes of depression and anxiety: evidence from the UK Biobank.

BACKGROUND: Preserved ratio impaired spirometry (PRISm) is a new lung function impairment phenotype and has been recognized as a risk factor for various adverse outcomes. We aimed to examine the associations of this new lung function impairment phenotype with depression and anxiety in longitudinal studies. METHODS: We included 369 597 participants from the UK Biobank cohort, and divided them into population 1 without depression or anxiety and population 2 with depression or anxiety at baseline. Cox proportional hazard models were performed to evaluate the associations of lung function impairment phenotype with adverse outcomes of depression and anxiety, as well as their subtypes. RESULTS: At baseline, 38 879 (10.5%) participants were diagnosed with PRISm. In population 1, the adjusted hazard ratios (HRs) for PRISm (v. normal spirometry) were 1.12 (95% CI 1.07-1.18) for incident depression, and 1.11 (95% CI 1.06-1.15) for incident anxiety, respectively. In population 2, PRISm was a risk factor for mortality in participants with depression (HR: 1.46; 95% CI 1.31-1.62) and anxiety (HR: 1.70; 95% CI 1.44-2.02), compared with normal spirometry. The magnitudes of these associations were similar in the phenotypes of lung function impairment and the subtypes of mental disorders. Trajectory analysis showed that the transition from normal spirometry to PRISm was associated with a higher risk of mortality in participants with depression and anxiety. CONCLUSIONS: PRISm and airflow obstruction have similar risks of depression and anxiety. PRISm recognition may contribute to the prevention of depression and anxiety.

Predicting Acute Exacerbation Phenotype in Chronic Obstructive Pulmonary Disease Patients Using VGG-16 Deep Learning.

INTRODUCTION: Exacerbations of chronic obstructive pulmonary disease (COPD) have a significant impact on hospitalizations, morbidity, and mortality of patients. This study aimed to develop a model for predicting acute exacerbation in COPD patients (AECOPD) based on deep-learning (DL) features. METHODS: We performed a retrospective study on 219 patients with COPD who underwent inspiratory and expiratory HRCT scans. By recording the acute respiratory events of the previous year, these patients were further divided into non-AECOPD group and AECOPD group according to the presence of acute exacerbation events. Sixty-nine quantitative CT (QCT) parameters of emphysema and airway were calculated by NeuLungCARE software, and 2,000 DL features were extracted by VGG-16 method. The logistic regression method was employed to identify AECOPD patients, and 29 patients of external validation cohort were used to access the robustness of the results. RESULTS: The model 3-B achieved an area under the receiver operating characteristic curve (AUC) of 0.933 and 0.865 in the testing cohort and external validation cohort, respectively. Model 3-I obtained AUC of 0.895 in the testing cohort and AUC of 0.774 in the external validation cohort. Model 7-B combined clinical characteristics, QCT parameters, and DL features achieved the best performance with an AUC of 0.979 in the testing cohort and demonstrating robust predictability with an AUC of 0.932 in the external validation cohort. Likewise, model 7-I achieved an AUC of 0.938 and 0.872 in the testing cohort and external validation cohort, respectively. CONCLUSIONS: DL features extracted from HRCT scans can effectively predict acute exacerbation phenotype in COPD patients.

Use of CAPTURE to Identify Individuals Who May or May Not Require Treatment for Chronic Obstructive Pulmonary Disease.

Rationale: The CAPTURE tool (Chronic Obstructive Pulmonary Disease [COPD] Assessment in Primary Care to Identify Undiagnosed Respiratory Disease and Exacerbation Risk) was developed to identify patients with undiagnosed COPD with an FEV1 <60% predicted or risk of exacerbation as treatment criteria. Objectives: To test the ability of CAPTURE to identify patients requiring treatment because of symptoms or risk of exacerbation or hospitalization. Methods: Data were from COMPASS (Clinical, Radiological and Biological Factors Associated with Disease Progression, Phenotypes and Endotypes of COPD in China), a prospective study of COPD, chronic bronchitis without airflow limitation (postbronchodilator FEV1/FVC ratio ≥0.70), and healthy never-smokers. CAPTURE was tested as questions alone and with peak expiratory flow measurement. Sensitivity, specificity, and positive and negative predicted values (PPV and NPV) were calculated for COPD Assessment Test (CAT) scores ⩾10 versus <10, modified Medical Research Council (mMRC) scores ⩾2 versus <2, and at least one moderate exacerbation or hospitalization in the previous year versus none. Measurements and Main Results: Patients with COPD (n = 1,696) had a mean age of 65 ± 7.5 years, and 90% were male, with a postbronchodilator FEV1 of 66.5 ± 20.1% predicted. Control participants (n = 307) had a mean age of 60.2 ± 7.0 years, and 65% were male, with an FEV1/FVC ratio of 0.78 ± 0.04. CAPTURE using peak expiratory flow showed the best combination of sensitivity and specificity. Sensitivity and specificity were 68.5% and 64.0%, respectively, to detect a CAT score ⩾10; 85.6% and 61.0% to detect an mMRC score ⩾2; 63.5% and 55.6% to detect at least one moderate exacerbation; and 70.2% and 59.4% to detect at least one hospitalization. PPVs ranged from 15.6% (moderate exacerbations) to 47.8% (CAT score). NPVs ranged from 80.8% (CAT score) to 95.6% (mMRC score). Conclusions: CAPTURE has good sensitivity to identify patients with COPD who may require treatment because of increased symptoms or risk of exacerbations or hospitalization, including those with an FEV1 >60% predicted. High NPV values show that CAPTURE can also exclude those who may not require treatment. Clinical trial registered with www.clinicaltrials.gov (NCT04853225).

Learning and depicting lobe-based radiomics feature for COPD Severity staging in low-dose CT images.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is a prevalent and debilitating respiratory condition that imposes a significant healthcare burden worldwide. Accurate staging of COPD severity is crucial for patient management and treatment planning. METHODS: The retrospective study included 530 hospital patients. A lobe-based radiomics method was proposed to classify COPD severity using computed tomography (CT) images. First, we segmented the lung lobes with a convolutional neural network model. Secondly, the radiomic features of each lung lobe are extracted from CT images, the features of the five lung lobes are merged, and the selection of features is accomplished through the utilization of a variance threshold, t-Test, least absolute shrinkage and selection operator (LASSO). Finally, the COPD severity was classified by a support vector machine (SVM) classifier. RESULTS: 104 features were selected for staging COPD according to the Global initiative for chronic Obstructive Lung Disease (GOLD). The SVM classifier showed remarkable performance with an accuracy of 0.63. Moreover, an additional set of 132 features were selected to distinguish between milder (GOLD I + GOLD II) and more severe instances (GOLD III + GOLD IV) of COPD. The accuracy for SVM stood at 0.87. CONCLUSIONS: The proposed method proved that the novel lobe-based radiomics method can significantly contribute to the refinement of COPD severity staging. By combining radiomic features from each lung lobe, it can obtain a more comprehensive and rich set of features and better capture the CT radiomic features of the lung than simply observing the lung as a whole.

Association between cooking fuel exposure and respiratory health: Longitudinal evidence from the China Health and Retirement Longitudinal Study (CHARLS).

The epidemiological evidences for the association between cooking fuel exposure and respiratory health were inconsistent, and repeated-measures prospective evaluation of cooking fuel exposure was still lacking. We assessed the longitudinal association of chronic lung disease (CLD) and lung function with cooking fuel types among Chinese adults aged ≥ 40 years. In this prospective, nationwide representative cohort of the China Health and Retirement Longitudinal Study from 2011 to 2018, 9004 participants from 28 provinces in China were included. CLD was identified based on self-reported physician diagnosis in 2018. Lung function was assessed by peak expiratory flow (PEF) in 2011, 2013 and 2015. Multivariable logistic and linear mixed-effects repeated-measures models were conducted to measure the associations of CLD and PEF with cooking fuel types. Three-level mixed-effects model was performed as sensitivity analysis. Among the participants, 3508 and 3548 participants used persistent solid and clean cooking fuels throughout the survey, and 1948 participants who used solid cooking fuels at baseline switched to clean cooking fuels. Use of persistent clean cooking fuels (adjusted odds ratio [aOR] = 0.73, 95 % confidence interval [CI]: 0.61, 0.88) and switch of solid fuels to clean fuels (aOR = 0.81, 95 % CI: 0.67, 0.98) were associated with lower risk of CLD. The use of clean cooking fuels throughout the survey and switch of solid fuels to clean fuels in 2013 were also significantly associated with higher PEF level. Similar results were observed in stratified analyses and different statistical models. The evidence from CHARLS cohort suggested that reducing solid cooking fuel exposure was associated with lower risk of CLD and better lung function. Given the recent evidence, improving household air quality will reduce the burden of chronic lung diseases.

Identification of cough-variant asthma phenotypes based on clinical and pathophysiologic data.

BACKGROUND: Cough-variant asthma (CVA) may respond differently to antiasthmatic treatment. There are limited data on the heterogeneity of CVA. OBJECTIVE: We aimed to classify patients with CVA using cluster analysis based on clinicophysiologic parameters and to unveil the underlying molecular pathways of these phenotypes with transcriptomic data of sputum cells. METHODS: We applied k-mean clustering to 342 newly physician-diagnosed patients with CVA from a prospective multicenter observational cohort using 10 prespecified baseline clinical and pathophysiologic variables. The clusters were compared according to clinical features, treatment response, and sputum transcriptomic data. RESULTS: Three stable CVA clusters were identified. Cluster 1 (n = 176) was characterized by female predominance, late onset, normal lung function, and a low proportion of complete resolution of cough (60.8%) after antiasthmatic treatment. Patients in cluster 2 (n = 105) presented with young, nocturnal cough, atopy, high type 2 inflammation, and a high proportion of complete resolution of cough (73.3%) with a highly upregulated coexpression gene network that related to type 2 immunity. Patients in cluster 3 (n = 61) had high body mass index, long disease duration, family history of asthma, low lung function, and low proportion of complete resolution of cough (54.1%). TH17 immunity and type 2 immunity coexpression gene networks were both upregulated in clusters 1 and 3. CONCLUSION: Three clusters of CVA were identified with different clinical, pathophysiologic, and transcriptomic features and responses to antiasthmatics treatment, which may improve our understanding of pathogenesis and help clinicians develop individualized cough treatment in asthma.

Longitudinal reciprocal association between rheumatoid arthritis and chronic obstructive pulmonary disease and mediation of inflammation.

OBJECTIVES: To elucidate the longitudinal reciprocal association between rheumatoid arthritis (RA) and chronic obstructive pulmonary disease (COPD), and the mediating role of systemic inflammation in the association. METHODS: 403045 participants from UK Biobank were enrolled in this study. A cross-lagged panel model was used to investigate the longitudinal reciprocal association between RA and COPD. Cox-proportional hazard regression and logistic regression models were also conducted to examine the association between baseline RA and COPD during follow-up, and vice versa. Causal mediation analysis was then performed to explore the mediating roles of 160 systemic inflammatory biomarkers in the bidirectional association. RESULTS: At baseline, 4755 (1.2%) and 6989 (1.7%) individuals were diagnosed with RA and COPD, respectively. After adjusting for the covariates, the result of cross-lagged panel model revealed a bidirectional association between RA and COPD (ß = 0.018, P < 0.001 for RA→COPD path; ß = 0.010, P < 0.001 for COPD→RA path). In the non-COPD population, the risk of future COPD was increased in RA patients (Cox: HR = 1.65, 95% CI, 1.50-1.83; logistic: OR = 1.85, 95% CI, 1.66-2.07). In the non-RA population, baseline COPD was associated with a higher risk of RA during follow-up (Cox: HR = 1.67, 95% CI, 1.44-1.92; logistic: OR = 1.70, 95% CI, 1.47-1.97). Five inflammatory factors mediated the RA→COPD path, and C-reactive protein mediated the COPD→RA path (FDR < 0.05). CONCLUSIONS: A significant bidirectional association exists between RA and COPD, and it is partially mediated by systemic inflammation.

A rare case of severe leptospirosis infection presenting as septic shock in a non-endemic area: a case report and literature review.

BACKGROUND: Leptospirosis is a zoonosis caused by spirochete "genus" leptospira. The clinical presentations of leptospirosis range from an influenza-like presentation of fever and myalgia, to severe forms. Leptospirosis can potentially lead to a misdiagnosis or delay in diagnosis when clinical similarities exist. CASE PRESENTATION: A 63-year-old man presented with fever, shock and thrombocytopenia followed by diffuse pulmonary hemorrhage. Peripheral blood Metagenomic Next-generation Sequencing (mNGS) reported Leptospira interrogans. The patient was treated with piperacillin-tazobactam (TZP) plus doxycycline and improved dramatically after 7 days. CONCLUSION: We conclude that leptospirosis can potentially lead to a misdiagnosis or delay in diagnosis. Correctly evaluation of thrombocytopenia in acute febrile illnesses facilitates the differential diagnosis of leptospirosis. mNGS can accurately detect Leptospira DNA during the early stage of the infection.

Effect of continuing the use of renin-angiotensin system inhibitors on mortality in patients hospitalized for coronavirus disease 2019: a systematic review, meta-analysis, and meta-regression analysis.

BACKGROUND: The effect of angiotensin-converting enzyme inhibitors (ACEIs)/angiotensin receptor blockers (ARBs) on mortality was preliminarily explored through the comparison of ACEIs/ARBs with non-ACEIs/ARBs in patients with coronavirus disease 2019 (COVID-19). Reaching a conclusion on whether previous ACEI/ARB treatment should be continued in view of the different ACE2 levels in the comparison groups was not unimpeachable. Therefore, this study aimed to further elucidate the effect of ACEI/ARB continuation on hospital mortality, intensive care unit (ICU) admission, and invasive mechanical ventilation (IMV) in the same patient population. METHODS: We searched PubMed, the Cochrane Library, Ovid, and Embase for relevant articles published between December 1, 2019 and April 30, 2022. Continuation of ACEI/ARB use after hospitalization due to COVID-19 was considered as an exposure and discontinuation of ACEI/ARB considered as a control. The primary outcome was hospital mortality, and the secondary outcomes included 30-day mortality, rate of ICU admission, IMV, and other clinical outcomes. RESULTS: Seven observational studies and four randomized controlled trials involving 2823 patients were included. The pooled hospital mortality in the continuation group (13.04%, 158/1212) was significantly lower than that (22.15%, 278/1255) in the discontinuation group (risk ratio [RR] = 0.45; 95% confidence interval [CI], 0.28-0.72; P = 0.001). Continuation of ACEI/ARB use was associated with lower rates of ICU admission (10.5% versus 16.2%, RR = 0.63; 95% CI 0.5-0.79; P < 0.0001) and IMV (8.2% versus 12.5%, RR = 0.62; 95% CI 0.46-0.83, P = 0.001). Nevertheless, the effect was mainly demonstrated in the observational study subgroup (P < 0.05). Continuing ACEI/ARB had no significant effect on 30-day mortality (P = 0.34), acute myocardial infarction (P = 0.08), heart failure (P = 0.82), and acute kidney injury after hospitalization (P = 0.98). CONCLUSION: Previous ACEI/ARB treatment could be continued since it was associated with lower hospital deaths, ICU admission, and IMV in patients with COVID-19, although the benefits of continuing use were mainly shown in observational studies. More evidence from multicenter RCTs are still needed to increase the robustness of the data. Trial registration PROSPERO (CRD42022341169). Registered 27 June 2022.

Impacts of short-term low-level exposure to air pollutants on hospital admissions for pulmonary sepsis in elderly patients.

BACKGROUND: Acute exposures to high levels of air pollutants are thought to be associated with hospitalization of patients with lung infection, while relatively little is known about the association between air pollutants and HOSPITAL ADMISSIONS FOR pulmonary sepsis. OBJECTIVES: To assess the correlation between low-level exposure to air pollutants and the hospitalizations for pulmonary sepsis in elderly patients. METHODS: A total of 249 elderly patients with pulmonary sepsis from January 2018 to December 2020 in Shenzhen people's hospital were included. The data regarding hospitalizations for pulmonary sepsis, meteorological factors, and daily average levels of air pollutants on single-day lags (Lag0 to Lag7) in Shenzhen were collected. Low-level exposure was defined as the annual means of air pollutants below the levels of the Ambient Air Quality Standard (AAQS) in China (NO. GB3095-2012) and/or Global Air Quality Guidelines (AQG). A time-stratified case-crossover study design approach was used to evaluate the associations between exposure to air pollutants and incidence of the disease, univariate and multivariate logistic regression analysis to analyze the association between levels of air pollutants and hospitalizations for pulmonary sepsis in elderly patients. RESULTS: Exposure to PM1(P = 0.007, Lag 2 day; P = 0.038, Lag6 day), PM2.5(P = 0.046, Lag2 day), PM10(P = 0.048, Lag4 day), and O3(P = 0.044, Lag6 day) was positively correlated with elevated risk of hospitalizations for pulmonary sepsis. In addition, logistic regression analysis revealed that exposure to PM1 (OR = 1.833, 95%CI:1.032 ~ 3.256, Lag6 day) and O3 (OR = 2.091, 95%CI:1.019 ~ 4.289, Lag6 day) were the independent risk factors of pulmonary sepsis in elderly patients. CONCLUSION: Our results demonstrate that short-term low-level exposure to PM1 and O3 could elevate the risk of hospitalizations for pulmonary sepsis in elderly patients in Shenzhen, providing evidence for developing early warning and screening systems for pulmonary sepsis.

Low human beta-defensin-2 levels in the sputum of COPD patients are associated with the risk of exacerbations.

RATIONALE: Chronic obstructive pulmonary disease (COPD) is a complicated chronic inflammatory disease. It is important to investigate the characteristics of acute exacerbation of COPD to develop new therapeutic strategies. OBJECTIVE: This study aimed to determine the relationship between the human beta-defensin-2 (hBD-2) levels and aggravation of COPD. METHODS: We detected the sputum hBD-2 level of 254 patients from Guangzhou, China, for 2 years. The study participants were categorized into the COPD group (n = 203, GOLD 0-4) and the control group (n = 51, 40-79 years old). At baseline, 12th month, and 24th month, we detected the sputum hBD-2 level and levels of cytokines, such as CXCL10, CXCL11, and IFN. RESULTS: At baseline, there were no significant differences in the sputum and serum hBD-2 levels between the patients and the controls. However, the sputum hBD-2 levels of patients who had at least one symptom aggravation over the next 2 years were significantly lower than those of patients without any exacerbations (1130.9 ± 858.4 pg/mL vs. 2103.7 ± 1294.2 pg/mL, respectively; p = 0.001). Nevertheless, there were no statistically significant differences in the sputum hBD-2 levels between patients (no aggravation history) and controls (2084.9 ± 1317.6 pg/mL vs. 2152.5 ± 1251.6 pg/mL, respectively; p = 0.626). We used a logistic regression model to assess the relationship between aggravation and sputum hBD-2 levels. Interestingly, we found that low hBD-2 level (< 1000 pg/mL) was significantly associated with exacerbations. Specifically, patients with low hBD-2 levels were more likely to experience exacerbations in the next 12 months (0.333 vs. 0.117; p = 0.001). Moreover, we compared the hBD-2 levels between controls and patients with GOLD 3-4 and found that participants with bacteria (+) and/or viruses (+) had an association between hBD-2 level and disease severity (p = 0.02). CONCLUSION: Patients at risk of exacerbations are more likely to have lower sputum hBD-2 levels. These results have important implications for future therapies for COPD.

The Establishment of China Bronchiectasis Registry and Research Collaboration (BE-China): Protocol of a prospective multicenter observational study.

BACKGROUND: Bronchiectasis is a highly heterogeneous chronic airway disease with marked geographic and ethnic variations. Most influential cohort studies to date have been performed in Europe and USA, which serve as the examples for developing a cohort study in China where there is a high burden of bronchiectasis. The Establishment of China Bronchiectasis Registry and Research Collaboration (BE-China) is designed to: (1) describe the clinical characteristics and natural history of bronchiectasis in China and identify the differences of bronchiectasis between the western countries and China; (2) identify the risk factors associated with disease progression in Chinese population; (3) elucidate the phenotype and endotype of bronchiectasis by integrating the genome, microbiome, proteome, and transcriptome with detailed clinical data; (4) facilitate large randomized controlled trials in China. METHODS: The BE-China is an ongoing prospective, longitudinal, multi-center, observational cohort study aiming to recruit a minimum of 10,000 patients, which was initiated in January 2020 in China. Comprehensive data, including medical history, aetiological testing, lung function, microbiological profiles, radiological scores, comorbidities, mental status, and quality of life (QoL), will be collected at baseline. Patients will be followed up annually for up to 10 years to record longitudinal data on outcomes, treatment patterns and QoL. Biospecimens, if possible, will be collected and stored at - 80 °C for further research. Up to October 2021, the BE-China has enrolled 3758 patients, and collected 666 blood samples and 196 sputum samples from 91 medical centers. The study protocol has been approved by the Shanghai Pulmonary Hospital ethics committee, and all collaborating centers have received approvals from their local ethics committee. All patients will be required to provide written informed consent to their participation. CONCLUSIONS: Findings of the BE-China will be crucial to reveal the clinical characteristics and natural history of bronchiectasis and facilitate evidence-based clinical practice in China. Trial registration Registration Number in ClinicalTrials.gov: NCT03643653.

Pathogenic variants identified using whole-exome sequencing in Chinese patients with primary ciliary dyskinesia.

The genetic factors contributing to primary ciliary dyskinesia (PCD), a rare autosomal recessive disorder, remain elusive for ~20%-35% of patients with complex and abnormal clinical phenotypes. Our study aimed to identify causative variants of PCD-associated pathogenic candidate genes using whole-exome sequencing (WES). All patients were diagnosed with PCD based on clinical phenotype or transmission electron microscopy images of cilia. WES and bioinformatic analysis were then conducted on patients with PCD. Identified candidate variants were validated by Sanger sequencing. Pathogenicity of candidate variants was then evaluated using in silico software and the American College of Medical Genetics and Genomics (ACMG) database. In total, 13 rare variants were identified in patients with PCD, among which were three homozygous causative variants (including one splicing variant) in the PCD-associated genes CCDC40 and DNAI1. Moreover, two stop-gain heterozygous variants of DNAAF3 and DNAH1 were classified as pathogenic variants based on the ACMG criteria. This study identified novel potential pathogenic genetic factors associated with PCD. Noteworthy, the patients with PCD carried multiple rare causative gene variants, thereby suggesting that known causative genes along with other functional genes should be considered for such heterogeneous genetic disorders.

The microRNA-1278/SHP-1/STAT3 pathway is involved in airway smooth muscle cell proliferation in a model of severe asthma both intracellularly and extracellularly.

This study investigated the regulatory effects of microRNA-1278 (miR-1278) on airway inflammation, airway reconstruction, and the proliferation and apoptosis of airway smooth muscle cells (ASMCs) induced by transforming growth factor ß1 (TGF-ß1). The results showed that miR-1278 was upregulated in the blood and lung tissues (LTs) of patients with asthma compared with that in healthy volunteers; miR-1278 expression was also upregulated in asthmatic mice, and miR-1278 inhibition improved the LTs of asthmatic mice. Moreover, miR-1278 inhibited inflammation in asthmatic mice and counteracted the effect of TGF-ß1 of induced proliferation and reduced apoptosis in ASMCs. DLRA indicated that miR-1278 targeted the 3'-UTR of Src-homology 2-containing phosphatase 1 (SHP-1). Furthermore, miR-1278 promoted ASMC proliferation, in which TGF-ß1 played an important role by regulating the SHP-1/STAT3 signaling pathway. In conclusion, this study showed that miR-1278 played a critical role in the processes of airway remodeling and reduction of apoptosis by targeting SHP-1.

Outcomes after lung transplantation among Chinese patients with connective tissue disease-associated interstitial lung disease and pulmonary hypertension: a retrospective cohort study.

OBJECTIVES: The present study aimed to compare the post-lung transplant survival and complications of connective tissue disease (CTD)-related interstitial lung disease (ILD) and/or pulmonary arterial hypertension with idiopathic pulmonary fibrosis (IPF). METHODS: The clinical data of patients with CTD-ILD or IPF who received lung transplantation between 2015 and 2020 were retrospectively reviewed. Cumulative survival rates after transplantation were estimated using the Kaplan-Meier method. RESULTS: The study included 31 patients with confirmed CTD-ILD and 98 with IPF. Patients with CTD-ILD were significantly younger (53.2 ± 13.7 vs. 62.3 ± 7.2 years, p=0.001) and more likely female (61.3% vs. 7.1%, p<0.001) than patients with IPF. No significant difference was noticed in the 1-year and 5-year survival rates between CTD-ILD and IPF patients (1-year, 73.2% vs 71.4%, p=0.76; 5-year, 69.1% vs. 39.5%, p=0.21). The incidence of primary graft dysfunction was significantly higher in CTD-ILD patients (90.3% vs. 70.4%, p=0.03), while there was no significant difference in primary graft dysfunction-related mortality (6.5% vs. 6.1%, p=0.95) between the two groups. CONCLUSIONS: There was no significant difference in post-lung transplant survival and complications between CTD-ILD and IPF.