Search Results (103)

Background: Chronic obstructive pulmonary disease (COPD) is a heterogeneous condition marked by airway inflammation, airflow limitation, and structural remodeling. Exosomal microRNAs (exo-miRNAs) are stable, cell-free biomarkers reflecting airway molecular changes. While serum and BALF exosomal miRNAs have been examined, sputum-derived profiles remain underexplored. Methods: Induced sputum was collected from 20 clinically stable COPD patients and 10 age-matched healthy controls. Exosomes were isolated by polymer-based precipitation and verified by transmission electron microscopy and Western blotting for CD9 and CD81. Nine candidate miRNAs (miR-21, miR-155, miR-34a, miR-126, miR-210, miR-146a, miR-199a-5p, miR-223, miR-1246) were quantified by RT-qPCR. Group comparisons used the Mann–Whitney U test, correlations Pearson’s r, and diagnostic accuracy ROC analysis. Results: Sputum-derived exosomes displayed characteristic morphology and canonical protein markers. COPD patients showed significant dysregulation of exosomal miRNAs, including upregulation of miR-21 (fold change = 3.4; 95% CI: 0.12–0.64 vs. 0.18–0.22; p < 0.001) and miR-223 (fold change = 2.1; 95% CI: 0.00–3.79 vs. 0.86–1.22; p = 0.004), and downregulation of miR-155 (fold change = 0.35; 95% CI: 0.43–0.67 vs. 0.86–1.22; p = 0.002), miR-126 (fold change = 0.42; 95% CI: 0.30–0.39 vs. 0.80–1.42; p = 0.009), and miR-146a (fold change = 0.28; 95% CI: 0.49–1.12 vs. 0.87–1.35; p = 0.006). miR-21 correlated with symptom burden (CAT; r = 0.445; p = 0.049). Among individual biomarkers, miR-155 exhibited the best diagnostic performance for COPD detection (AUC = 0.730; 95% CI: 0.53–0.93), which further improved when combined with miR-126 and miR-146a (AUC = 0.841; 95% CI: 0.69–0.98). For disease stratification, miR-126 most effectively discriminated mild from moderate-to-severe COPD (AUC = 0.728; 95% CI: 0.50–0.96). These results indicate that sputum-derived exosomal miRNAs—particularly miR-155, miR-126, and miR-146a—may serve as promising non-invasive biomarkers for COPD diagnosis and clinical phenotyping. Conclusions: Sputum exosomal miRNAs reveal a distinct COPD-specific signature reflecting inflammation, impaired repair, and immune dysregulation. Composite panels incorporating miR-155, miR-126, and miR-146a enhance diagnostic accuracy and could be integrated into non-invasive workflows for COPD detection and staging. Full article

Background: The Global Initiative for Chronic Obstructive Lung Disease (GOLD) recognizes asthma as a potential causal pathway for chronic obstructive pulmonary disease, referred to as the COPD-A etiotype. However, the clinical and inflammatory characteristics of this phenotype remain poorly defined. Objectives: This study aimed to characterize clinical traits and cytokine profiles in stable asthmatics exhibiting persistent airflow limitation compatible with COPD-A. Methods: In this cross-sectional study, 94 stable asthmatic patients (71.3% female; age = 54.0 ± 15.6 years) without relevant smoking or environmental exposures were evaluated. COPD-A was defined by a post-bronchodilator FEV₁/FVC ratio < 0.70. Asthma control (ACQ, ACT), quality of life (AQLQ), and lung function were assessed. Levels of IL-5, IL-8, IL-13, IL-17A, IL-17F, IL-25, IL-33, and TNF were quantified in nasal lavage, induced sputum, and blood samples. Results: Among the participants, 42 (44.7%) fulfilled COPD-A criteria. Compared with non-COPD-A subjects, those with COPD-A were older (60.5 vs. 48.7 years; p < 0.001) and had longer disease duration (39.8 vs. 30.1 years; p < 0.001), lower post-bronchodilator FEV₁% predicted (68.1 vs. 87.1%; p < 0.001), and poorer asthma control (ACQ = 1.00 vs. 0.64; p = 0.003). Cytokine levels were comparable between groups except for higher IL-8 concentrations in induced sputum of COPD-A subjects (7.66 vs. 2.51 pg/mL; p = 0.024). Sputum IL-8 ≥ 3.096 pg/mL independently predicted COPD-A (aOR = 12.82; p = 0.023). Conclusions: Over 40% of non-smoking asthmatics exhibited persistent airflow limitation consistent with COPD-A. Elevated sputum IL-8 levels may be a potential biomarker of this etiotype. Full article

Background: Nontuberculous mycobacterial pulmonary disease (NTM-PD) is a chronic respiratory infection primarily caused by Mycobacterium avium complex (MAC) and Mycobacterium abscessus. These species differ markedly in antibiotic susceptibility and treatment response, yet the contribution of the respiratory microbiome to this clinical variability remains unclear. To date, however, comparative analyses of microbiome differences between MAC-PD and M. abscessus-PD and their associations with disease severity are limited. Methods: We conducted microbiome analysis of sputum from 37 patients with NTM-PD. Patients were antibiotic-naïve and classified into MAC-PD (n = 29) and M. abscessus-PD (n = 8) groups. Disease severity was determined using radiologic extent on chest computed tomography. Bacterial communities were profiled by 16S rRNA gene sequencing, and differential taxa and predicted functional pathways were analyzed using LEfSe and KEGG orthology databases. Results: Distinct microbiome profiles were observed between MAC-PD and M. abscessus-PD. Three anaerobic species—Porphyromonas pasteri, Fusobacterium periodonticum, and Prevotella nanceiensis—were significantly enriched in M. abscessus-PD (LDA effect size > 3, p < 0.05). Functional biomarker analysis revealed significant enrichment of the cobalamin (vitamin B12) biosynthesis pathway in patients with severe disease, while the C19/C18 steroid hormone biosynthesis pathway was enriched in those with mild disease (p < 0.05). Conclusions: In conclusion, our study demonstrates distinct differences in the respiratory microbiome between MAC-PD and M. abscessus-PD and identifies specific functional pathways associated with disease severity in NTM-PD. These findings highlight the potential value of microbial metabolic signatures as biomarkers for disease assessment. Full article

Non-small cell lung cancer (NSCLC) remains a leading cause of cancer-related mortality globally, driven by marked molecular and cellular heterogeneity that complicates diagnosis and treatment. Despite advances in targeted therapies and immunotherapies, treatment resistance frequently emerges, and clinical benefits remain limited to specific molecular subtypes. To improve early detection and dynamic monitoring, novel diagnostic strategies—including liquid biopsy, low-dose computed tomography scans (CT) with radiomic analysis, and AI-integrated multi-modal platforms—are under active investigation. Non-invasive sampling of exhaled breath, saliva, and sputum, and high-throughput profiling of peripheral T-cell receptors and immune signatures offer promising, patient-friendly biomarker sources. In parallel, multi-omic technologies such as single-cell sequencing, spatial transcriptomics, and proteomics are providing granular insights into tumor evolution and immune interactions. The integration of these data with real-world clinical evidence and machine learning is refining predictive models and enabling more adaptive treatment strategies. Emerging therapeutic modalities—including antibody–drug conjugates, bispecific antibodies, and cancer vaccines—further expand the therapeutic landscape. This review synthesizes recent advances in NSCLC diagnostics and treatment, outlines key challenges, and highlights future directions to improve long-term outcomes. These advancements collectively improve personalized and effective management of NSCLC, offering hope for better-quality survival. Continued research and integration of cutting-edge technologies will be crucial to overcoming current challenges and achieving long-term clinical success. Full article

Severe asthma is a heterogeneous condition often resistant to conventional corticosteroid therapy, necessitating the identification of novel biomarkers and therapeutic targets. This study investigates immunological, transcriptional, and proteomic biomarkers in severe asthma patients from the Brazilian ProAR cohort. Cytokines were measured using a multiplex technology and the differential sputum cell count was performed by cytospin preparations. Sputum transcriptomics was performed by RNA-seq using Ion S5 next-generation sequencing platform. The proteomic study of sputum was performed by liquid chromatography–tandem mass spectrometry (LC-MS/MS) using Q Exactive Orbitrap technology. Compared to mild-to-moderate asthma (MMA) and treatment-controlled severe asthma (SAC), the treatment-resistant severe asthma (SAR) group exhibited increased sputum neutrophilia, eosinophilia, and elevated IL-6 and TNF levels, correlating with impaired lung function. Transcriptomic and proteomic analyses revealed a Th2-independent molecular signature characterized by downregulation of the Hippo signaling pathway and upregulation of JAK–STAT inflammatory cascades. Distinctive microRNA profiles suggest regulatory involvement in inflammatory and proliferative processes. These findings align with prior studies, reinforcing the presence of an IL-6- and TNF-high severe asthma phenotype across diverse populations. Our results highlight key inflammatory pathways that may underlie corticosteroid resistance, offering potential targets for personalized therapeutic interventions in severe asthma. Full article

Microfluidic paper-based analytical devices (µPADs) are ideal for point-of-care diagnostics due to their low cost, compact size, and ease of use. However, current designs have limited multiplexing capabilities, making it difficult to simultaneously detect pathogens and biomarkers in the same sample. In this work, we introduce NanoArrayPAD−X, a novel µPAD design that combines wax-printed microfluidic networks with an array of nanoprobes for the simultaneous detection of multiple targets. This is achieved by distributing the sample through the microfluidic network containing X detection areas. There, targets are captured through physical interactions and recognized by specific antibody-coated nanoprobes released from the nanoprobe array. This generates X dots whose color depends on the concentration of the targets in the sample. A NanoArrayPAD−5 platform capable of detecting five targets was developed to aid in the diagnosis of ventilator-associated pneumonia (VAP). The sensor array could detect Pseudomonas aeruginosa, Klebsiella pneumoniae, Staphylococcus aureus, Escherichia coli, and the inflammatory biomarker myeloperoxidase (MPO) with a total turnaround time of 25 min, which is faster than waiting for an overnight culture and the results of an ELISA. Notably, our prototype successfully detected the targets in 87 bronchial aspirate (BAS) specimens, thus demonstrating the suitability of the platform for analyzing complex samples with sputum-like qualities. These findings establish NanoArrayPAD−X as a promising tool for the rapid, multiplexed screening of respiratory pathogens and biomarkers, with potential for guiding personalized antimicrobial therapy in suspected cases of nosocomial pneumonia. Full article

Background: Most of the currently approved TB diagnostics are sputum-based. However, due to unusual clinical presentations of TB among HIV patients, they may not have TB symptoms and be able to produce sputum. Hence, these diagnostics may not be able to detect as many TB cases as possible among these patients. Therefore, this study assessed the performance of C-reactive protein (CRP) and interferon-gamma-inducible protein 10 (IP-10) as a screening tool for TB. Methods: This prospective study was conducted by consecutively recruiting patients with TB symptoms, collecting their sputum and blood samples, using sputum culture as the reference standard, and determining the best cut-off point of serum levels of CRP and IP-10 (separately and in combination) for TB diagnosis. Findings: CRP and IP-10 were measured in 408 patients with TB symptoms, of which 21% had culture-confirmed TB. CRP’s sensitivity and specificity were (91.4% and 33.2%), (95.3% and 42.6%) and (84.8% and 22.1%) for the whole study population, HIV-negative and HIV-positive patients, respectively. The sensitivity and specificity of IP-10 were (87.3% and 40.9%), (87.5% and 50.3%) and (79.4% and 47.2%) for the patients’ categories, respectively. Combination of CRP and IP-10 slightly improved the performance of the biomarkers among HIV-negative patients, with sensitivity of 97.5% and specificity of 43.3%. Interpretation: Though CRP and IP-10 performed better in HIV-negative patients than among people living with HIV (PLHIV), the performance of the biomarkers is lower than what is recommended by the WHO (sensitivity ≥ 90% and specificity ≥ 70%) for a TB screening tool. Hence, there is a need for better non-sputum-based TB diagnostics. Full article

Bronchiectasis is a heterogeneous chronic airway disease traditionally viewed as neutrophil-driven. Emerging evidence demonstrates distinct complex inflammatory phenotypes influencing clinical outcomes, prognosis and therapeutic options. A narrative review was conducted, informed by a structured literature search on PubMed and Google Scholar databases, focusing on inflammatory phenotypes in bronchiectasis. Based on the prevalent cellular population, four distinct phenotypes can be described. The most common is the neutrophilic phenotype, which is associated with frequent Pseudomonas infection, severe disease, exacerbations and poor prognosis. Targeted novel-agents for this group such as brensocatib (neutrophil protease inhibition) emerge. The eosinophilic phenotype is defined by elevated blood or sputum eosinophils and is associated with FeNO, IL-5/IL-13 signaling, a possible response to inhaled corticosteroids and biologic agents. The mixed phenotype demonstrates dual neutrophilic and Th2 inflammation. Paucigranulocytic phenotypes remain poorly characterized but with distinct characteristics. Finally, dysregulation of macrophages and lymphocytes as inflammation mediators needs to be studied further. Recent advances have introduced a variety of therapeutic strategies targeting specific inflammatory pathways. Bronchiectasis has a spectrum of inflammatory phenotypes with distinct biological and clinical implications. Recognition and better understanding of inflammatory phenotypes in bronchiectasis may enable opportunities for personalized precision medicine through the transition from empirical management to biomarker-guided, personalized care. Full article

Background: Patients with pulmonary tuberculosis (TB) typically produce sputa, which are used to identify the pathogen. Sputum also contains host proteins that may aid in diagnosis. We hypothesized that sputa from TB patients will have unique proteomes when compared to other lung diseases. Methods: Sputa were collected from 219 patients with suspected TB. Neutrophil-derived protein calprotectin (CP), which was used as a marker for lung damage, was quantified and compared between TB and non-TB groups. Three sputa with high or low CP from each group were selected and analyzed using label-free proteomics. Results: There was no difference in CP amounts between TB and non-TB groups. However, TB samples had other differentially abundant neutrophil-associated proteins. Compared to low CP, samples with high CP had much smaller number of proteins that could differentiate between TB and non-TB groups. Only two proteins, MUC5AC and MMP8, were more abundant in TB samples, regardless of CP levels. Conclusions: Our findings suggest that TB sputa may have unique proteomes that depend on CP levels, which should be further validated due to the small sample size. Therefore, controlled and more advanced TB may need a different set of biomarkers to reliably distinguish TB from other lung diseases. Full article

Chronic airway inflammation with variable airflow obstruction is clinical asthma, and it arises from distinct molecular and pathological mechanisms called endotypes. Biomarkers allow for precise endotype characterization and have been used in clinical trials to design, monitor, and evaluate outcomes for asthma biologic therapies. This review will highlight the central and evolving role of biomarkers for past, present, and future asthma, with a focus on regulatory-approved biologic therapies and emerging biomarkers. Established biomarkers, including serum immunoglobulin E (IgE), blood eosinophils, the fraction of exhaled nitric oxide (FeNO), and serum periostin, helped elucidate the complex pathophysiology of the eosinophilic type 2 (T2) asthma endotype. Emerging biomarkers, or older biomarkers with emerging utility, include sputum inflammatory cells (eosinophils, neutrophils, interleukins), thymus and activation-regulated chemokine (TARC), plasma eotaxin-3, eosinophil peroxidase (EPX), Clara/club cell secretory protein (CC16), and quantitative computerized tomography (QCT) imaging biomarkers (evaluating mucus plugging, air trapping, airway wall thickness, small airway remolding) and are increasingly used in clinical trials as secondary endpoints in evaluating efficacy, as well as in the clinical setting at specialized centers. The rapid advances in asthma research, due in part to biomarkers and biologic therapies, may soon standardize an end goal: symptom-free asthma remission without exacerbations. Full article

Introduction: Cystic fibrosis (CF) is a genetic condition affecting several organs and systems, including the pancreas, colon, respiratory system, and reproductive system. The detection of a growing number of CFTR variants and genotypes has contributed to an increase in the CF population which, in turn, has had an impact on the overall statistics regarding the prognosis and outcome of the condition. Given the increase in life expectancy, it is critical to better predict outcomes and prognosticate in CF. Thus, each person’s choice to aggressively treat specific disease components can be more appropriate and tailored, further increasing survival. The objective of our narrative review is to summarize the most recent information concerning the value and significance of clinical parameters in predicting outcomes, such as gender, diabetes, liver and pancreatic status, lung function, radiography, bacteriology, and blood and sputum biomarkers of inflammation and disease, and how variations in these parameters affect prognosis from the prenatal stage to maturity. Materials and methods: A methodological search of the available data was performed with regard to prognostic factors in the evolution of CF in children and young adults. We evaluated articles from the PubMed academic search engine using the following search terms: prognostic factors AND children AND cystic fibrosis OR mucoviscidosis. Results: We found that it is crucial to customize CF patients’ care based on their unique clinical and biological parameters, genetics, and related comorbidities. Conclusions: The predictive significance of more dynamic clinical condition markers provides more realistic future objectives to center treatment and targets for each patient. Over the past ten years, improvements in care, diagnostics, and treatment have impacted the prognosis for CF. Although genotyping offers a way to categorize CF to direct research and treatment, it is crucial to understand that a variety of other factors, such as epigenetics, genetic modifiers, environmental factors, and socioeconomic status, can affect CF outcomes. The long-term management of this complicated multisystem condition has been made easier for patients, their families, and physicians by earlier and more accurate identification techniques, evidence-based research, and centralized expert multidisciplinary care. Full article

Asthma represents a heterogeneous disorder characterized by a dynamic balance between pro-inflammatory and anti-inflammatory forces, with allergic sensitization contributing substantially to airway hyperresponsiveness and remodeling. Central to its pathogenesis are cytokines such as IL-4, IL-5, IL-13, IL-17, and IL-33, which drive recruitment of eosinophils, neutrophils, and other effector cells, thereby precipitating episodic exacerbations in response to viral and environmental triggers. Conventional biomarkers, including blood and sputum eosinophil counts, IgE levels, and fractional exhaled nitric oxide, facilitate phenotypic classification and guide the emerging biologic era. Monoclonal antibodies targeting IgE (omalizumab) and IL-5 (mepolizumab, benralizumab, reslizumab, depemokimab) have demonstrated the ability to reduce exacerbation frequency and improve lung function, with newer agents such as depemokimab offering extended dosing intervals. Itepekimab, an anti-IL-33 antibody, effectively engages its target and mitigates tissue eosinophilia, while CM310-stapokibart, tralokinumab, and lebrikizumab inhibit IL-4/IL-13 signaling with variable efficacy depending on patient biomarkers. Comparative analyses of these biologics, encompassing affinity, dosing regimens, and trial outcomes, underscore the imperative of personalized therapy to optimize disease control in severe asthma. Full article

Tuberculosis (TB) is an infectious disease caused by Mycobacterium tuberculosis. Despite the improvements in diagnostic techniques, the accuracy of TB diagnosis is still low. In recent years, the development of artificial intelligence (AI) has opened up new possibilities in diagnosing and treating TB with high accuracy compared to traditional methods. Traditional diagnostic techniques, such as sputum smear microscopy, culture tests, and chest X-rays, are time-consuming, with less sensitivity for the detection of TB in patients. Due to the new developments in AI, advanced diagnostic and treatment techniques have been developed with high accessibility, speed, and accuracy. AI, including various specific methodologies, is becoming vital in managing TB. Machine learning (ML) methodologies, such as support vector machines (SVMs) and random forests (RF), alongside deep learning (DL) technologies, particularly convolutional neural networks (CNNs) for image analysis, are employed to analyze diverse patient data, including medical images and biomarkers, to enhance the accuracy and speed of tuberculosis diagnosis. This study summarized the benefits and drawbacks of both traditional and AI-driven TB diagnosis, highlighting how AI can support traditional techniques to increase early detection, lower misdiagnosis, and strengthen international TB control initiatives. Full article

Patients with chronic obstructive pulmonary disease (COPD) often experience acute exacerbations characterized by elevated neutrophilic inflammation in the lungs. Currently, this condition is diagnosed through visual inspection of sputum color and volume, a method prone to personal bias and unsuitable for patients who are unable to expectorate spontaneously. In this manuscript, we present a novel approach for measuring and monitoring exhaled myeloperoxidase (MPO), a biomarker of neutrophilic airway inflammation, without the need for sputum analysis. The method involves analyzing an unmodified surgical facemask worn by the patient for 30 min using biosensing decals that transfer antibody-coated nanoparticles. These colloids specifically interact with MPO trapped by the facemask in a dose-dependent manner, enabling the quantification of MPO levels, with a dynamic range up to 3 · 10¹ µg·mL⁻¹. The proposed diagnostic approach successfully differentiated patients with acute exacerbations from stable patients with 100% sensitivity and specificity. Healthy individuals also showed significantly lower MPO levels compared to COPD patients. Our results suggest that facemask analysis could be a non-invasive diagnostic tool for airway diseases, particularly in patients unable to expectorate. Full article

Since the World Health Organization (WHO) issued guidelines for developing a non-sputum test for active tuberculosis (TB) diagnosis that exhibits similar performance characteristics to sputum-based diagnosis, salivary diagnostic techniques have gained prominence as potential screening tools or adjuncts to existing diagnostics. We searched online databases for studies that looked at salivary diagnostic techniques. Afterwards, duplicates were removed, titles and abstracts were screened, and full-text studies were assessed for eligibility based on inclusion and exclusion criteria. The studies chosen for final analysis underwent a rigorous quality assessment following a QUADAS-2 template, and data were extracted. The primary outcome assessed the difference in mean levels of interleukins between TB+ patients and TB-controls (Hedges’ g). We then conducted two subgroup analyses: the first segregated the control group into healthy patients, and those with other respiratory diseases (ORD), and the second addressed three different interleukins separately (IL-6, IL-5, IL-17). The secondary outcome involved comparing salivary molecular diagnostic assays to WHO guidelines. This study is registered with PROSPERO, CRD42024536884. A total of 17 studies, out of an initial 1010, were chosen for the final analysis, but one was then excluded for being of poor quality. Our meta-analyses for the primary outcome revealed minimal diagnostic potential for interleukins. Our first subgroup analysis showed that interleukins were incapable of differentiating active TB patients from both healthy controls and ORD patients. Our second subgroup analysis showed that IL-17 was reduced in active TB patients. Assessment of the secondary outcome revealed that most studies relied on a GeneXpert MTB/RIF assay on saliva, but none fulfilled WHO guidelines for a non-sputum test. Individual biomarkers currently lack sufficient discriminatory power to definitively distinguish active tuberculosis from healthy individuals or those with other respiratory diseases (ORD), reinforcing the need for multi-biomarker panels. Interleukins may be alternatively used as markers for prognosis, severity, or treatment response. Our findings also suggest that assays are unable to meet WHO guidelines. Full article