Microbiome and its role in bronchiectasis

Abstract

Bronchiectasis (BE) is a chronic respiratory disease characterized by damage to the bronchial wall structure and permanent dilation of the bronchi. The symptoms include a persistent cough, excessive production of purulent sputum, and recurrent hemoptysis. Dysbiosis of the microbiome plays a crucial role in the progression of BE. An increased abundance of pathogenic bacteria, along with viral and fungal infections, is closely associated with disease severity and clinical outcomes. Next-generation sequencing technology has significantly enhanced the sensitivity and resolution of the airway microbiome, providing powerful tools for a more detailed characterization of the microecology of BE. However, certain challenges still exist in clinical applications of this technology. In addition, extra-airway microbiomes, such as the gut and oral microbiome, may participate in airway inflammation and immune regulation through the gut-lung axis and oral-lung axis. In this review, we summarize the characteristics of microbiome dysbiosis in BE and highlight the potential value of related biomarkers in disease classification, severity assessment, and prognosis. We also provide an overview of recent treatment advancements. A deeper understanding of the microbiome’s role in BE may facilitate early diagnosis and the optimization of individualized treatment strategies.

Plain language summary

The microbiome refers to the collection of microorganisms, including bacteria, fungi, viruses, and other microbes. A healthy microbiome is essential for overall well-being, as it plays a crucial role in protecting against infections and supporting bodily functions. However, this balance can be disrupted by various diseases. Dysbiosis of the microbiome plays a significant role in the progression of BE, characterized by reduced microbial diversity and increased abundance of pathogenic bacteria. In this review, we summarize how the microbiome interacts with the immune system and influences disease severity. It also highlights emerging biomarkers and new therapies, including DPP-1 inhibitors, inhaled antibiotics, biologics that target specific immune pathways, and innovative approaches like phage therapy. However, research on extra-airway microbiomes is still limited. Furthermore, variations across different regions and populations make it challenging to apply findings universally. A better understanding of the microbiome could lead to more accurate diagnoses, personalized treatments, and ultimately better long-term outcomes for patients.

Keywords

bronchiectasis dysbiosis gut-lung axis inflammation microbiome next-generation sequencing oral-lung axis precision medicine

Search strategy

In this narrative review, we conducted a comprehensive literature search using the PubMed, Embase, and Scopus databases, focusing on English-language literature published up to January 2026. Our search strategy included the following terms: “microbiome,” “bronchiectasis,” “next-generation sequencing,” “gut-lung axis,” “dysbiosis,” “inflammation,” and “precision medicine.” To ensure the relevance and quality of the included studies, we implemented a rigorous screening process and excluded duplicate articles using Zotero software.

Introduction

In recent years, bronchiectasis (BE) has gradually emerged as a global public health issue, with significant variations in prevalence across countries and regions.¹ In developed countries such as Europe and the United States, the incidence and disease burden of BE have shown a sustained upward trend. The latest data from England indicate that the prevalence of BE rose from 0.37% to 0.46% between 2015 and 2019. During this period, hospital admissions related to BE increased from 17,584 to 24,946 cases, reflecting an average annual growth rate of 4.3%.² A cohort study based on the US Optum Clinformatics^® database identified 70,946 newly diagnosed cases of BE between 2018 and 2022, and approximately 93% of patients had at least one identifiable underlying etiology.³ In 2025, the Chinese Bronchiectasis Registry (BE-China) released baseline clinical data on Chinese patients with BE for the first time.⁴ The results showed that the major etiologies were post-infectious and tuberculosis. Notably, 54.7% of patients were classified as having severe BE. Patients in low- and middle-income regions experienced higher rates of acute exacerbations and hospitalizations, a heavier tuberculosis burden, and a poorer quality of life. BE is a highly heterogeneous disease, and its onset and progression involve multiple factors, including infection, inflammation, immune dysfunction, and genetic predisposition. Different etiologies can lead to significant differences in clinical manifestations, inflammatory phenotypes, and disease prognosis. Therefore, identifying the underlying cause is crucial for distinguishing disease subtypes and for developing individualized treatment strategies.

Airway infections, inflammation, impaired mucociliary clearance, and structural lung damage work together in a vicious cycle.⁵ In particular, neutrophil-driven inflammation plays a central role in disease progression. Activated neutrophils can release neutrophil extracellular traps (NETs) and generate substantial proteases through degranulation, including neutrophil elastase (NE), neutrophil serine proteases (NSPs), and matrix metalloproteinases. These proteases degrade elastic and collagen fibers in the airway, disrupting the bronchial wall structure.⁶ Crucially, inflammatory responses create favorable conditions for microbial colonization, proliferation, and infection by disrupting airway defense mechanisms, altering the microenvironment, impairing immune function, and promoting microbial adhesion. The respiratory microbiome in patients with BE is closely associated with systemic inflammatory levels.⁷ Among these pathogens, Pseudomonas aeruginosa (PA) is a key determinant of disease prognosis. Previous studies have shown that patients with BE exhibit airway acidification. In acidic conditions, PA activates the cGAS-STING-TBK1 pathway and induces high expression of the innate immune mediator interferon-β (IFN-β), thereby impairing host antibacterial capacity and contributing to persistent and worsening infection.⁸ Further research has found that the acidic microenvironment promotes the secretion of outer membrane vesicles by PA and induces a high expression of the gene cluster responsible for synthesizing 2-heptyl-4-quinoline (HHQ). This process significantly reduces LL-37’s binding affinity for PA, thereby enhancing PA’s resistance to LL-37.⁹

In addition, microorganisms and their metabolites can participate in the immunopathogenesis of BE through multiple mechanisms, including direct activation of immune responses, suppression of immune cell function, and disruption of mucosal barrier integrity. Maintaining microbiome diversity may help reduce the risk of acute exacerbations and is crucial for improving clinical outcomes.

Application of next-generation sequencing in BE

Traditional bacterial culture methods are limited in sensitivity and resolution when characterizing intricate microbial communities. By contrast, the emergence of next-generation sequencing, along with multi-omics integration and artificial intelligence (AI), has revolutionized the study of airway microbiota.

16S rRNA sequencing

The 16S rRNA gene sequence is highly conserved and specific, allowing for the sequencing-based identification of microbial composition in the airways and lungs, as well as the determination of dominant genera and changes in microbial diversity.¹⁰ Full-length 16S rRNA gene sequencing using amplicon-based Oxford Nanopore technology can markedly improve the accuracy of identifying microbes in BE.⁷ Furthermore, combined analysis of 16S rRNA and metabolomes has revealed the characteristics of microbial communities and metabolic profiles in BE comorbidity. BE frequently coexists with other chronic airway diseases, forming overlap syndromes. Airway microbial dysbiosis and metabolic alterations are key features of these diseases. He et al. performed 16S rRNA sequencing and targeted metabolomics in patients with chronic obstructive pulmonary disease (COPD), BE, and COPD–BE association (CBA). Their results showed that the airway microbiota and metabolic profiles of CBA patients were more similar to those of BE. In both groups, the dominant genera included Proteobacteria, Pseudomonas, and Haemophilus.¹¹ And enrichment of Pseudomonas was associated with greater disease severity and an increased risk of acute exacerbations. Another prospective cohort study showed that airway microbiota α-diversity and β-diversity in Asthma-BE overlap (ABO) patients were intermediate between those of patients with asthma alone and BE alone.¹² Pseudomonas and Rothia were identified as characteristic genera in the ABO group. Significant differences in microbial diversity and metabolic profiles were also observed between eosinophilic and non-eosinophilic inflammatory phenotypes. It suggests that airway inflammation and microbiome diversity jointly influence the risk of acute exacerbations. Furthermore, Gao et al.¹³ employed validated rapid PCR assays, 16S rRNA sequencing, and sputum inflammatory assessments to identify multiple inflammatory subtypes during acute exacerbations of BE, providing crucial biological evidence for precision therapy. However, 16S rRNA sequencing may be susceptible to contamination in low-biomass samples and has limited capacity to detect non-bacterial microorganisms, such as viruses and fungi.

Metagenomic next-generation sequencing

Compared with traditional culture and molecular diagnostic methods, Metagenomic next-generation sequencing (mNGS) offers a shorter turnaround time and higher sensitivity, particularly for detecting mixed infections and rare pathogens.¹⁴ A study involving sputum samples from 59 patients showed that the overall bacterial detection rate was significantly higher with mNGS than with traditional culture (100% vs 85.7%), highlighting the potential of mNGS in pathogen detection for BE.¹⁵ Patients with BE have a unique antibiotic resistance gene profile. Mac Aogáin et al.¹⁶ identified two “resistotypes,” RT1 and RT2, in BE utilizing whole-genome shotgun metagenomics, where RT2 was strongly associated with poor clinical outcomes and the enrichment of multidrug resistance genes. The RT2 microbiome was predominantly characterized by PA and Klebsiella pneumoniae. Notably, targeted eradication of PA could shift RT2 toward RT1. The EMBARC-BRIDGE cohort study further validated this classification and revealed significant geographic differences in the prevalence of the two resistome types and in airway microbiome composition, providing important guidance for antimicrobial use across Europe.¹⁷ Although RT1 and RT2 offer a novel framework for precision stratification in BE, it is essential to highlight that these resistome types are primarily research tools at present. Currently, there are no large-scale prospective clinical trials that have confirmed whether resistotype-guided therapeutic strategies lead to improved patient outcomes. Therefore, further high-quality studies are needed to establish their clinical efficacy and safety before they can be integrated into routine practice. mNGS has significant application value, yet the vast amount of data it generates places considerable demands on bioinformatics and computational resources. Moreover, accurately distinguishing pathogenic, colonizing, and contaminating bacteria remains a major challenge.

Multi-omics and artificial intelligence

In recent years, multi-omics analyses, including microbiomics, genomics, transcriptomics, and metabolomics, have emerged as an important research direction, providing insights into the pathogenesis and progression of BE. Previous studies have integrated bacterial, viral, and fungal data from the airways of patients with BE using weighted similarity network analysis.¹⁸ They found that patients at high risk for acute exacerbation exhibited simpler microbial co-occurrence networks and stronger antagonistic interactions. Furthermore, the emergence of AI and machine learning (ML) models has further accelerated research.¹⁹ In particular, SHAP-based analyses identified that microbial diversity is a crucial predictor of acute exacerbation.²⁰ In addition, another study combining mNGS with ML has shown that age, disease subtype, and infection type significantly influence the microbial composition of the lower respiratory tract. Predictive models based on specific microbial communities can effectively estimate hospitalization duration and clinical outcomes.²¹

Microbial dysbiosis in bronchiectasis

The respiratory immune microenvironment is composed of diverse immune cells, humoral factors, physicochemical barriers, and the microbiota. It plays a pivotal role in maintaining airway homeostasis, defending against pathogen invasion, and promoting tissue repair. Among these components, reduced microbiome diversity and increased abundance of pathogenic bacteria are closely associated with disease severity (Figure 1).

Figure 1.

Microbial dysbiosis and interactions in bronchiectasis.

Bacterial dysbiosis in bronchiectasis

Dysbiosis of the airway microbiota plays a significant role in the progression of BE, typically characterized by reduced microbial diversity and increased abundance of pathogenic bacteria.^22,23 Among these, PA is the most frequently isolated pathogen, and a higher abundance of PA is strongly correlated with acute exacerbations. By contrast, a reduction in commensal bacteria such as Rothia, Haemophilus, and Streptococcus may further strengthen this association.²⁴ Cabrera et al.²⁵ reported that PA exhibits significantly increased expression of virulence factors during acute exacerbations, which is closely correlated with serum IL-6 levels and dynamic changes in specific immunoglobulin subclasses, suggesting potential biomarkers for predicting exacerbations. Activation of the NLRP3 inflammasome leads to the production of IL-1β, which has been shown to suppress IFN-β generation and modulate host antimicrobial responses, highlighting the complex interplay between innate immune responses and infection.²⁶ However, other studies have demonstrated that elevated IL-1β levels are positively correlated with disease severity and are often accompanied by enrichment of pathogens such as Proteobacteria.²⁷ Persistently high levels of IL-1β can disrupt epithelial barrier integrity, promote mucus hypersecretion, impair ciliary function, and further activate the NLRP3 inflammasome, thereby establishing a positive feedback loop that amplifies inflammation. Consequently, modulation of the IL-1β signaling pathway may represent a promising therapeutic strategy for restoring immune homeostasis in BE.

Non-tuberculous mycobacteria (NTM) are also common pathogens associated with BE. A systematic review encompassing 21 international studies reported that the isolation rate of NTM and the prevalence of NTM pulmonary disease among adult patients with BE were 7.7% and 4.1%, respectively.²⁸ Another study conducted in Vietnam discovered NTM in 52.5% of bronchoalveolar lavage fluid (BALF) samples from patients with stable BE.²⁹ Importantly, NTM could be identified in the early stages of disease, suggesting its potential role as a marker of disease progression. Furthermore, Chinese studies have reported that the detection rate of NTM reached 38.2% in patients with BE during acute exacerbations, and NTM colonization was associated with a significantly increased risk of exacerbation. Low BMI, reduced lipid levels, and the presence of Rothia mucilaginosa or Streptococcus parasanguinis in BALF were identified as susceptibility factors for NTM colonization.³⁰

Comparative analyses of cystic fibrosis bronchiectasis (CFB) and non-CF bronchiectasis (NCFB) revealed both shared features and distinct differences. Both exhibited reduced microbial diversity, lower Bacteroidetes abundance, and elevated levels of Pseudomonas. However, NCFB was characterized by an increased abundance of Haemophilus influenzae and Prevotella. By contrast, CFB showed enrichment of Burkholderiaceae and a higher Firmicutes-to-Bacteroidetes ratio.³¹

The virome and mycobiome

In addition to bacterial infections, viruses and fungi also play an essential role in the progression of BE (Table 1).³²

Table 1.

Dominant pathogens/phenotypes in bronchiectasis.

Microbiome category	Pathogen/phenotype	Clinical associations
Bacteria	Pseudomonas aeruginosa	Higher risk of acute exacerbations; Greater disease severity; Worse lung function; Poorer quality of life
	Haemophilus influenzae
	Mixed/other (e.g., Staphylococcus aureus, Moraxella catarrhalis)
	Eggerthella lenta	The gut-lung axis
	Oral commensal (e.g., Fusobacterium, Neisseria)	The oral-lung axis
Non-tuberculous mycobacteria		NTM-PD can lead to BE, and BE is a common factor for NTM-PD.
Virome	Rhinovirus	Acute exacerbation of BE; Secondary bacterial infections
	Influenza virus
	Epstein-Barr virus
	SARS-CoV-2
Mycobiome	Aspergillus spp.	ABPA; eosinophilic inflammation
	Candida spp.	Opportunistic pathogen

ABPA, allergic bronchopulmonary aspergillosis; NTM, non-tuberculous mycobacteria.

Viruses are major triggers of acute exacerbations in chronic respiratory diseases. A meta-analysis indicated that rhinovirus is the most frequently detected respiratory virus in patients with BE.³³ Studies have shown that even mild to moderate COVID-19 infection is closely associated with an increased frequency of acute exacerbations in patients with BE.³⁴ In pediatric patients with BE, the load of torque teno virus correlates with the severity of bronchial dilation and peripheral airflow limitation.³⁵ Viral infections can not only directly trigger and amplify airway inflammatory responses, but also further compromise airway immune defenses through mechanisms such as disruption of the airway epithelial barrier and suppression of mucociliary clearance. This creates conditions conducive to bacterial colonization and overgrowth.³⁶ Concurrently, dysbiosis of the airway microbiota may inhibit the interferon response, increasing host susceptibility to viral infection. This interaction between viral triggers and secondary bacterial exacerbations can amplify the inflammatory cascade, forming a vicious cycle that aggravates structural damage to the airways and accelerates disease progression. Consequently, in the clinical management of BE, emphasis should be placed not only on antimicrobial therapy but also on strengthening the prevention and control of viral infections, to reduce the risk of acute exacerbations and improve outcomes.

In addition, fungi represent important contributing factors to acute exacerbations of BE. A retrospective study reported that the positive rate of fungal culture in BALF from patients with BE could be as high as 80.8%.³⁷ Aspergillus spp. and Candida spp. were the most frequently isolated fungi.³³ Aspergillus antigens can drive a strong Th2 immune response, promoting eosinophilic inflammation and IgE production. In Aspergillus‑associated pulmonary diseases, elevated specific IgG has been identified as an independent risk factor for disease deterioration.³⁸ Allergic bronchopulmonary aspergillosis (ABPA) represents an important subtype of BE. Studies have shown that patients with moderate or extensive BE have a significantly higher risk of acute exacerbations compared with those with mild disease, and greater radiological extent of bronchial dilation is associated with worse lung function.³⁹ Further in-depth investigation of the virome and mycobiome may offer novel therapeutic targets for microbiome‑based interventions in BE.

Airway microbiome characteristics across different phenotypes

BE is a highly heterogeneous disease characterized by multiple inflammatory endotypes. Choi et al.⁴⁰ were among the first to integrate inflammatory markers with microbiome characteristics and to identify four molecular inflammatory endotypes of BE. The microbiome composition differed significantly across these endotypes and was closely associated with the risk of acute exacerbations. Further studies revealed that most patients exhibit a neutrophilic inflammatory endotype, while approximately 30% present with an eosinophilic inflammatory endotype.⁴¹ Persistent bacterial infection has been shown to shift adaptive immunity from a Th1-dominant response toward a Th2-driven inflammatory response, accompanied by impaired Treg function. Cant et al.⁴² also revealed significant differences in sputum microbiomes across inflammatory endotypes, which clustered into two major groups characterized by neutrophilic and Th2-type inflammation. The neutrophilic cluster was more prevalent and was characterized by reduced α-diversity and increased Proteobacteria abundance. Integrating clinical phenotypes with microbiome characteristics facilitates a more comprehensive understanding of disease heterogeneity and supports the development of individualized therapeutic strategies.

Upper airway microbiome dysbiosis and its impact on the lower airways

In recent years, microbiome research has gradually expanded to the upper airway. Choi et al.⁴³ found that microbial α-diversity in the upper airway was significantly reduced in patients with severe BE, with Pseudomonas species predominating the microbiota. By contrast, patients with mild disease were enriched in commensals such as Corynebacterium and Dolosigranulum. Notably, the abundance of Pseudomonas in the nasopharynx positively showed a strong positive correlation with PA growth in sputum cultures. Further analyses defined dysbiosis as a relative abundance of pathogenic bacteria greater than 10%. The researchers confirmed that upper airway dysbiosis was significantly associated with an increased risk of severe acute exacerbations, worsening respiratory symptoms, and greater damage to the nasal epithelial structure. These findings suggest that upper airway microbiome characteristics may serve as important biomarkers for predicting acute exacerbations and assessing disease severity.

Chronic rhinosinusitis (CRS) is one of the potential risk factors for NCFB.⁴⁴ A study reported that among patients with CRS who underwent chest CT examination, the detection rate of BE was approximately 24.3%.⁴⁵ Motile ciliary disorder (MCD) represents a common pathological basis for both rhinosinusitis and BE. Zhang et al.⁴⁶ found that nearly 89.8% of patients with BE exhibited MCD in the upper airway, and aberrant expression of key ciliary markers in nasal epithelial cells was closely associated with disease severity. Furthermore, acute upper airway infection is an important trigger for acute exacerbations of BE.⁴⁷ Patients with BE complicated by upper respiratory infection often present with a more complex lower airway pathogen spectrum, greater symptom burden, prolonged recovery time, and a significantly increased risk of future infection-related exacerbations. Therefore, prevention and timely management of upper respiratory infections are crucial for improving long-term outcomes in patients with BE.

Extra-pulmonary microbiomes

The gut and oral microbiome, as important components of the extra-airway microbiome, may affect the pathogenesis, progression, and severity of BE through multiple mechanisms.

The gut-lung axis

Dysbiosis of the gut microbiome can influence airway immune responses via the gut-lung axis.⁴⁸ Studies have shown that the modulation of the gut microbiome can improve the pulmonary immune environment indirectly.⁴⁹ Wang et al.⁵⁰ analyzed fecal samples from patients with NCFB and reported significant changes in both the gut microbiome and metabolome in these patients, including reduced microbial diversity, decreased abundance of Bifidobacterium and Lactobacillus, and abnormal levels of metabolites. Furthermore, tauroursodeoxycholic acid (TUDCA), a metabolite produced by Eggerthella lenta (E. lenta), was significantly enriched in the gut and serum of patients with BE.⁵¹ TUDCA can inhibit AMPK phosphorylation in neutrophils, thereby impairing their phagocytic and bactericidal functions, which may exacerbate pulmonary infection and tissue injury.

Dysregulation of the gut-lung axis has been linked to unfavorable outcomes in BE. Narayana et al.⁵² reported that a high gut-lung interaction cluster, characterized by an enrichment of PA in the lungs and Lactobacillus in the gut, was associated with greater disease severity. By contrast, the low gut-lung interaction cluster, dominated by pulmonary commensals and intestinal Candida, was associated with milder disease. Animal experiments further demonstrated that treatment with imipenem could disrupt this interaction, suggesting that targeted modulation of the gut microbiota may be a potential strategy for improving the pulmonary immune microenvironment.

The oral-lung axis

The oral microbiome can enter the lower airway through microaspiration and hematogenous dissemination, thereby influencing pulmonary microbial composition and respiratory health.^53,54 In patients with NCFB, structural and functional abnormalities of the airways impair mucociliary clearance, creating favorable conditions for colonization of the oral microbiome in the lower airway. Previous studies have shown that oral microbiota such as Prevotella, Streptococcus, Fusobacterium, and Pauljensenia are closely associated with respiratory infections, with Fusobacterium in particular significantly increasing the risk of BE.⁵⁵ Neisseria, an oral commensal, acts as an opportunistic pathogen in lower airway infections. It can utilize nitrate generated in inflammatory environments for anaerobic respiration, thereby adapting to the chronically inflamed and relatively hypoxic conditions of the airways.⁵⁶ Periodontal pathogens can promote the adhesion and invasion of respiratory pathogens, induce apoptosis of airway epithelial cells and excessive expression of mucin, ultimately disrupting epithelial immune homeostasis and contributing to persistent pulmonary inflammation and infection.^57,58 In addition, certain oral microbes can establish persistent colonization by adhering to the airway epithelium or forming biofilms.

The differences in the composition of oral microbiota and pulmonary defense functions among different individuals may affect the stability of oral bacteria in the lower airway. Elderly individuals, intubated patients, and immunocompromised hosts are particularly susceptible to persistent pulmonary colonization by oral microbes due to increased risk of microaspiration and impaired host defenses. However, compared to the gut microbiome, research on the role of the oral microbiome in BE remains limited. Further studies are needed to clarify its contribution to disease progression and its potential as a therapeutic target.

Precision diagnosis and treatment in bronchiectasis

The microbiome plays a crucial role in the early diagnosis, disease assessment, and prognosis prediction of BE. Deeply integrating microbiomics into clinical practice is key to achieving precision diagnosis and treatment for disease.

Biomarkers

Biomarkers play a crucial role in the early identification, disease classification, and prognostic assessment of BE. A comprehensive strategy that integrates multiple biomarkers, microbiome, and clinical evaluation facilitates precise management throughout the patient’s care. In recent years, a range of biomarkers related to infection, inflammation, immune responses, and structural airway damage have been proposed and validated, providing new directions for disease management (Figure 2).

Figure 2.

Biomarkers associated with bronchiectasis.

Sputum analysis directly reflects airway inflammation, pathogen burden, and immune responses. Studies have shown that increased sputum purulence and volume are closely associated with adverse outcomes, including poorer quality of life, lower forced expiratory volume in one second (FEV₁), and a higher risk of bacterial infection.⁵⁹ Moreover, sputum color also indirectly reflects its properties. Purulent sputum has a higher solid concentration and greater elastic stiffness. This viscoelastic abnormality can reduce mucus hydration and inhibit ciliary beating, thereby reducing airway clearance efficiency.⁶⁰ Zhou et al.⁶¹ reported that patients with BE colonized by PA had significantly elevated total nitrate/nitrite concentrations in sputum, which were closely correlated with acute exacerbation frequency and disease severity. Li et al.⁶² were the first to identify Neisseria spp. as opportunistic pathogens in BE through multi-omics analysis. Neisseria subflava, isolated from patients, directly impaired respiratory epithelial barrier function and aggravated pulmonary inflammation, challenging the traditional view that Neisseria species are harmless commensals in the airway and have no impact on pulmonary diseases. Previous studies have indicated that sputum color is an objective indicator of disease severity and prognosis. In addition, sputum myeloperoxidase levels (MPO) reflect the intensity of neutrophilic airway inflammation and may serve as a potential biomarker for evaluating acute exacerbations of BE.⁶³ Recent evidence further indicates that the Quality of Life-Bronchiectasis-Respiratory Symptom Scale (QoL-B-RSS) score has predictive value comparable to prior exacerbation history and represents an independent risk factor for future acute exacerbations. This finding provides a strong theoretical basis for optimizing treatment strategies and disease management for patients in China.⁶⁴

The ratio of neutrophils to lymphocytes in peripheral blood is an important indicator reflecting the systemic inflammatory burden and can serve as a potential biomarker for assessing inflammation levels and disease progression.⁶⁵ The majority of patients with BE exhibit neutrophilic inflammation. Shoemark et al.⁶⁶ enrolled 951 patients with BE from five countries and found that approximately 20% of patients exhibited the eosinophilic inflammatory subtype. Blood eosinophil counts (BECs) can serve as a crucial indicator of eosinophilic inflammation in patients with BE.⁶⁷ Patients with BECs ⩾ 300 cells/μL commonly had Streptococcus or PA identified in their sputum microbiome. After adjusting for infections, elevated BECs were associated with a shorter time to acute exacerbation of BE (HR 3.99, 95% CI 2.20–7.85), suggesting that BECs may represent a treatable aspect of the disease. In addition, a multicenter, prospective observational study has revealed a U-shaped relationship between BECs and key clinical indicators, including disease severity, exacerbation frequency, lung function, and pathogen characteristics.⁶⁸ This association was particularly notable in patients with BECs < 50 cells/μL. However, inhaled corticosteroid treatment was effective only in patients with BECs ⩾ 300 cells/μL, significantly reducing the frequency and severity of acute exacerbations. Moreover, the level of fractional exhaled nitric oxide (FeNO) is closely related to eosinophilic inflammation. Elevated FeNO in patients with BE indicates the presence of Th2 inflammation and may serve as a marker for non-invasive assessment of airway inflammation.⁶⁹

Matrix metalloproteinase-8 (MMP-8) and matrix metalloproteinase-9 (MMP-9) are significantly elevated in the sputum of patients with BE and are closely associated with neutrophilic inflammatory activity, decline in lung function, and disease severity.⁷⁰ During acute exacerbations, MMP levels further increased, subsequently declining during recovery, suggesting MMP-8 and MMP-9 may serve as biomarkers for assessing disease activity and prognosis. In patients with NCFB, serum IL-6 and tissue inhibitor of metalloproteinases-1 (TIMP-1) levels are significantly elevated and are strongly associated with airway colonization by PA.⁷¹ In patients with ABPA, peripheral helper T cells (Tph) are highly expressed in peripheral blood and BALF.⁷² It promotes B-cell differentiation and induces IgE production through the secretion of cytokines such as IL-5, IL-13, and IL-21, thereby driving disease progression. Tph cells may serve as a potential immunological biomarker for monitoring disease activity in ABPA, and therapeutic strategies targeting Tph cells may offer new directions for precision treatment in the future. Nevertheless, the precision diagnosis and treatment of BE remain challenging. Future trials should incorporate biomarkers to improve the accuracy of predicting treatment efficacy.

Anti-infective and anti-inflammatory therapies for BE

Controlling chronic infection and airway inflammation are two essential aspects in the treatment of BE. With a deeper understanding of pathogens and pathogenesis, new targeted therapies targeting key pathological pathways, such as neutrophilic and eosinophilic inflammation, have demonstrated promising clinical prospects (Table 2).

Table 2.

Summary of therapeutic strategies targeting key pathogenic mechanisms in BE.

Drug	Mechanism	Phase	Reference
Tobramycin inhalation solution	Inhaled aminoglycoside antibiotic	Approved	/
Brensocatib	DPP-1 inhibitor	Approved	/
HSK31858	DPP-1 inhibitor	Phase III	CTR20253262, CTR20243623
BI 1291583	DPP-1 inhibitor	Phase III	CTR20252522
RSS0343	DPP-1 inhibitor	Phase II	CTR20250101
XH S004	DPP-1 inhibitor	Phase II	CTR20251293
Itepekimab	Subcutaneous injection of IL-33 monoclonal antibody	Phase II	NCT06280391
Benralizumab	Anti-IL-5Rα monoclonal antibody	Phase III	NCT05006573
GSK3862995B	Anti-IL-33 monoclonal antibody	Phase II	NCT07201051

Timely and standardized antimicrobial therapy is essential for controlling infection, alleviating symptoms, and slowing disease progression. PA infection is an independent risk factor for acute exacerbations, and eradication therapy targeting PA has been shown to improve patient outcomes.⁷³ Tobramycin inhalation solution (TIS) is the first inhaled antibiotic specifically approved for BE in China. Phase III clinical trials have demonstrated that nebulized TIS can significantly reduce bacterial load in sputum, decrease 24-h sputum volume, and decrease sputum purulent scores.⁷⁴ However, bacterial load often rebounds after treatment discontinuation, and chronic infection remains difficult to eradicate completely. Consequently, the ERASE study, led by Chinese researchers, aimed to explore eradication strategies for new PA infections in patients with BE, aiming to provide more durable infection control approaches.⁷⁵ In addition, the PROMIS-I and PROMIS-II randomized controlled trials assessed inhaled colistin dry powder therapy in patients with bronchiectasis at high risk of exacerbation and chronic PA infection. The results showed that inhaled colistimethate sodium significantly reduced the annual exacerbation rate (RR = 0.61, 95% CI: 0.46–0.82), with greater benefits observed in patients with good treatment adherence.⁷⁶ Moreover, this therapy significantly prolonged the time to first exacerbation, indicating potential microbiological and clinical benefits in patients with chronic PA infection.

The excessive release of NSPs plays a vital role in driving chronic inflammation and airway damage in BE. Dipeptidyl peptidase-1 (DPP-1) inhibitors can reduce neutrophil-mediated inflammation and tissue injury by blocking activation of NSPs. The phase II WILLOW trial demonstrated that 10 mg and 25 mg of brensocatib could reduce the risk of acute exacerbations and prolong the time to first exacerbation in patients with BE.⁷⁷ At the 2025 World Bronchiectasis Conference, Professor James D. Chalmers presented results from the phase III ASPEN trial, which further confirmed that brensocatib at 10 mg and 25 mg significantly reduced the annual rate of acute exacerbations over 52 weeks and prolonged the time to first exacerbation. Compared to placebo, the 25 mg dose significantly slowed the decline in FEV₁ and improved quality of life.⁷⁸ Besides, HSK31858, the first domestically developed DPP-1 inhibitor in China, also demonstrated favorable efficacy in a phase II trial. Doses of 20 mg and 40 mg reduced the risk of acute exacerbations by 48% and 60%, respectively, and significantly decreased 24-h sputum volume and sputum purulence scores, with an overall favorable safety profile.⁷⁹

Biologics and phage therapy

The application of biologics in the treatment of BE is still in the exploratory phase. Current evidence suggests that several biologics, such as omalizumab, dupilumab, and mepolizumab, show promising potential for patients with type 2 inflammatory phenotypes. Benralizumab, for instance, works by selectively eliminating eosinophils through antibody-dependent cellular cytotoxicity, effectively reducing Th2-driven airway inflammation. Based on this mechanism, the ongoing MAHALE trial aims to evaluate the efficacy of benralizumab in patients with NCFB. In addition, monoclonal antibodies targeting the alarmin pathway, such as itepekimab, astegolimab, and tezepelumab, can suppress both Th1 and Th2 inflammation.⁸⁰ Furthermore, PDE3 and PDE4 inhibitors can exert anti-inflammatory effects, dilate bronchi, and enhance mucus clearance by elevating cAMP levels in cells. However, large-scale clinical validation is still lacking.⁸¹

Phage therapy is particularly suitable for the treatment of multidrug-resistant organisms and chronic infections due to its host specificity and ability to penetrate bacterial biofilms.⁸² Recently, researchers have made the novel discovery that inhaled phage preparations targeting PA can significantly reduce bacterial load in sputum, improve lung function, and minimize risks associated with systemic drug exposure.⁸³ Despite its substantial therapeutic potential, several challenges limit its clinical application in BE. Effective treatment requires adequate delivery of phages to the lower airway; however, the complex physiological environment may affect phage stability and bioavailability. In cases of intracellular bacterial infection, phages must overcome cellular membrane barriers, and current delivery strategies still require optimization. Furthermore, the host immune system may recognize and eliminate phages, particularly with repeated administration, which can reduce their therapeutic efficacy. Moreover, bacteria may also develop resistance to phages, further complicating the clinical translation. In addition, as phage therapy is an emerging therapeutic approach, a unified global regulatory framework has not yet been established. Therefore, multidisciplinary collaboration will be essential in the future to promote technological innovation, strengthen clinical evidence, and establish corresponding regulatory policies to drive phage therapy toward safer, more effective, and more accessible clinical applications.

Conclusion

The BE-China study has provided valuable insights into the baseline clinical characteristics of patients with BE in China. It offers a comprehensive overview of the distribution of etiological factors, the disease burden, microbiome profiles, and treatment patterns. However, there are differences in the microbiome across different regions, influenced by factors such as genetic background, environmental exposure, diet, the use of antibiotics, and local disease etiology. Therefore, findings from studies based on specific populations may not be universally applicable to other regions. To address this, future research should involve cross-regional and multi-center studies to validate the clinical significance of different microbiome characteristics in different populations and regions.

The microbiome can serve as a treatable trait for BE, providing a basis for formulating individualized therapeutic strategies. Moreover, innovative technologies such as nanodelivery systems and autologous transplantation of P63+ lung progenitor cells provide novel therapeutic approaches for patients. Predictive models based on AI and ML can further improve the efficiency of disease diagnosis and treatment. In summary, future research on BE should focus on the multi-omics, multidisciplinary, and precision medicine to improve the long-term prognosis of patients.

Footnotes

Acknowledgements

All figures included in this manuscript were created by the authors using BioRender.

Declarations

ORCID iDs

Yiting Pan

Jin-Fu Xu

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