Lower Respiratory Tract Infections

Treatable Traits in Systemic Sclerosis

Systemic sclerosis (SSc) is a chronic systemic disease within the spectrum of connective tissue diseases, specifically characterized by vascular abnormalities and inflammatory and fibrotic involvement of the skin and internal organs resulting in high morbidity and mortality. The clinical phenotype of SSc is heterogeneous, and serum autoantibodies together with the extent of skin involvement have a predictive value in the risk stratification. Current recommendations include an organ-based management according to the predominant involvement with only limited individual factors included in the treatment algorithm. Similar to what has been proposed for other chronic diseases, we hypothesize that a "treatable trait" approach based on relevant phenotypes and endotypes could address the unmet needs in SSc stratification and treatment to maximize the outcomes. We provide herein a comprehensive review and a critical discussion of the literature regarding potential treatable traits in SSc, focusing on established and candidate biomarkers, with the purpose of setting the bases for a precision medicine-based approach. The discussion, structured based on the organ involvement, allows to conjugate the pathogenetic mechanisms of tissue injury with the proposed predictors, particularly autoantibodies and other serum biomarkers. Ultimately, we are convinced that precision medicine is the ideal guide to manage a complex condition such as SSc for which available treatments are largely unsatisfactory.

Tea consumption and risk of lower respiratory tract infections: a two-sample mendelian randomization study

BACKGROUND

Observational studies have reported the association between tea consumption and the risk of lower respiratory tract infections (LRTIs). However, a consensus has yet to be reached, and whether the observed association is driven by confounding factors or reverse causality remains unclear.

METHOD

A two-sample Mendelian randomization (MR) analysis was conducted to determine whether genetically predicted tea intake is causally associated with the risk of common LRTI subtypes. Genome-wide association study (GWAS) from UK Biobank was used to identify single-nucleotide polymorphisms (SNPs) associated with an extra cup of tea intake each day. The summary statistics for acute bronchitis, acute bronchiolitis, bronchiectasis, pneumonia, and influenza and pneumonia were derived from the FinnGen project.

RESULTS

We found that genetically predicted an extra daily cup of tea intake was causally associated with the decreased risk of bronchiectasis [odds ratio (OR) = 0.61, 95% confidence interval (CI) = 0.47-0.78, P < 0.001], pneumonia (OR = 0.90, 95% CI = 0.85-0.96, P = 0.002), influenza and pneumonia (OR = 0.91, 95% CI = 0.85-0.97, P = 0.002), but not with acute bronchitis (OR = 0.91, 95% CI = 0.82-1.01, P = 0.067) and acute bronchiolitis (OR = 0.79, 95% CI = 0.60-1.05, P = 0.100). Sensitivity analyses showed that no heterogeneity and pleiotropy could bias the results.

CONCLUSIONS

Our findings provided new evidence that genetically predicted an extra daily cup of tea intake may causally associated with a decreased risk of bronchiectasis, pneumonia, and influenza and pneumonia.

Comparison of metagenomic next-generation sequencing using cell-free DNA and whole-cell DNA for the diagnoses of pulmonary infections

Although the fast-growing metagenomic next-generation sequencing (mNGS) has been used in diagnosing infectious diseases, low detection rate of mNGS in detecting pathogens with low loads limits its extensive application. In this study, 130 patients with suspected pulmonary infections were enrolled, from whom bronchoalveolar lavage fluid (BALF) samples were collected. The conventional tests and mNGS of cell-free DNA (cfDNA) and whole-cell DNA (wcDNA) using BALF were simultaneously performed. mNGS of cfDNA showed higher detection rate (91.5%) and total coincidence rate (73.8%) than mNGS of wcDNA (83.1% and 63.9%) and conventional methods (26.9% and 30.8%). A total of 70 microbes were detected by mNGS of cfDNA, and most of them (60) were also identified by mNGS of wcDNA. The 31.8% (21/66) of fungi, 38.6% (27/70) of viruses, and 26.7% (8/30) of intracellular microbes can be only detected by mNGS of cfDNA, much higher than those [19.7% (13/66), 14.3% (10/70), and 6.7% (2/30)] only detected by mNGS of wcDNA. After in-depth analysis on these microbes with low loads set by reads per million (RPM), we found that more RPM and fungi/viruses/intracellular microbes were detected by mNGS of cfDNA than by mNGS of wcDNA. Besides, the abilities of mNGS using both cfDNA and wcDNA to detect microbes with high loads were similar. We highlighted the advantage of mNGS using cfDNA in detecting fungi, viruses, and intracellular microbes with low loads, and suggested that mNGS of cfDNA could be considered as the first choice for diagnosing pulmonary infections.

Associations between air pollutants and risk of respiratory infection: patient-based bacterial culture in sputum

Air pollution is a crucial risk factor for respiratory infection. However, the relationships between air pollution and respiratory infection based on pathogen detection are scarcely explored in the available literature. We detected respiratory infections through patient-based bacterial culture in sputum, obtained hourly data of all six pollutants (PM_2.5, PM₁₀, SO₂, NO, CO, and O₃) from four air quality monitoring stations, and assessed the relationships of air pollutants and respiratory bacterial infection and multi-drug-resistant bacteria. Air pollution remains a challenge for Mianyang, China, especially PM_2.5 and PM₁₀, and there are seasonal differences; pollution is the heaviest in winter and the lowest in summer. A total of 4237 pathogenic bacteria were detected, and the positive rate of multi-drug-resistant bacteria was 0.38%. Similar seasonal differences were found with respect to respiratory infection. In a single-pollutant model, all pollutants were significantly associated with respiratory bacterial infection, but only O₃ was significantly associated with multi-drug-resistant bacteria. In multi-pollutant models (adjusted for one pollutant), the relationships of air pollutants with respiratory bacterial infection remained significant, while PM_2.5, PM₁₀, and O₃ were significantly associated with the risk of infection with multi-drug-resistant bacteria. When adjusted for other five pollutants, only O₃ was significantly associated with respiratory bacterial infection and the risk of infection with multi-drug-resistant bacteria, showing that O₃ is an independent risk factor for respiratory bacterial infection and infection with multi-drug-resistant bacteria. In summary, this study highlights the adverse effects of air pollution on respiratory infection and the risk of infection with multi-drug-resistant bacteria, which may provide a basis for the formulation of environmental policy to prevent respiratory infections.

Characteristics of the lung microbiota in lower respiratory tract infections with and without history of pneumonia

Lung microbiota plays an important role in many diseases including lower respiratory tract infections (LRTI) and pneumonia. This study aimed to explore the effects of community-acquired pneumonia (CAP) on microbial diversity and identify potential biomarkers of respiratory tract in CAP LRTI patients. In the current study, a comprehensive bioinformatics analysis was performed based on metagenomic next generation sequencing technology, followed by alpha and beta diversity, LEfSe, and co-occurrence network analysis, and random forest model construction. Our results showed that CAP dramatically influenced taxon abundance, and the significant differences in microbiota including Proteobacteria, Bacteroidetes, Euryarchaeota, Firmicutes and Spirochaetes were observed at the phylum level. Co-occurrence network selected out novel modules involved in microbial proliferation-associated pathways. A random forest model screened Klebsiella pneumoniae and Bacillus cereus as potential diagnostic biomarkers with high AUC values. The microbial composition was different between CAP LRTI patients and non-CAP LRTI patients. Klebsiella pneumoniae and Bacillus cereus were strongly associated with increased severity of LRTI with a pneumonia history. Our findings provided an insight for a better understanding of community and structure of lung microbiota for future diagnosis and treatment in LRTI patients with a history of pneumonia. Moreover, these microbes were considered as potential biomarkers for predicting the risks for the treatment strategies of LRTI.

Evaluation of a Commercial Multiplexed Molecular Lower Respiratory Panel at a Tertiary Care Cancer Center

Diagnosis and management of bacterial pneumonia still relies on bacterial culture and antimicrobial susceptibility testing. The Unyvero Lower Respiratory Tract panel (LRT) is a multiplex molecular assay that provides results within approximately 4.5 hours. This study evaluated the analytical performance of the LRT on bronchoalveolar lavage (BAL) fluids and bronchial washings (BW) in a cancer patient population and retrospectively determined clinical impact on therapy. Sensitivity and specificity of LRT on BAL and BW compared with bacterial culture and susceptibilities were calculated. Chart reviews were performed to determine whether antibiotic management would have changed based on the LRT results. A total of 113 BAL and 123 BW respiratory samples from 191 patients were included. The overall sensitivity and specificity were 91.7% (95% CI, 77.5%-98.3%) and 92.0% (95% CI, 87.3%-95.4%), respectively. Staphylococcus aureus was the most common target detected (n = 21) with 89.5% (95% CI, 66.8%-98.7%) sensitivity and 98.2% (95% CI, 95.4%-99.5%) specificity. Based on availability of LRT results, 4.8% of patients could have been de-escalated faster. The LRT demonstrated an overall high accuracy for the detection of common bacteria associated with pneumonia. In this cancer inpatient cohort, treatment adjustment based on LRT results would have occurred in a small number of cases. Larger studies are necessary to understand the real-world impact within specific high-risk populations.

A Critical Review on Emerging Trends in Dry Powder Inhaler Formulation for the Treatment of Pulmonary Aspergillosis

Pulmonary aspergillosis (PA), a pulmonary fungal infection caused by Aspergillus spp., is a concern for immunocompromised populations. Despite substantial research efforts, conventional treatments of PA using antifungal agents are associated with limitations such as excessive systemic exposure, serious side effects and limited availability of the therapeutics in the lungs for an adequate duration. To overcome the limitations associated with the conventional regimens, pulmonary delivery of antifungal agents has become a focal point of research because of the superiority of local and targeted drug delivery. Dry powder inhalers and nebulized formulations of antifungal agents have been developed and evaluated for their capability to effectively deliver antifungal agents to the lungs. Moreover, progress in nanotechnology and the utilization of nanocarriers in the development of pulmonary delivery formulations has allowed further augmentation of treatment capability and efficiency. Thus, the following review provides an insight into the advantages and therapeutic potential of the utilization of nanocarriers in pulmonary delivery of antifungal agents for the treatment of PA. In addition, discussions on formulation aspects and safety concerns together with the clinical and regulatory aspects of the formulations are presented, which suggest the possibility and desirability of utilization of nanocarriers in the treatment of PA.