Phenotypic Clustering in Non-Cystic Fibrosis Bronchiectasis Patients: The Role of Eosinophils in Disease Severity

Wang, Xuejie; Villa, Carmen; Dobarganes, Yadira; Olveira, Casilda; Girón, Rosa; García‐Clemente, Marta; Máiz, Luís; Sibila, Oriol; Golpe, Rafael; Menéndez, Rosário; Rodríguez-López, Juan; Prados, Concepción; Martínez‐García, Miguel Ángel; Rodríguez, Juan; Rosa, David de la; Duran, Xavier; García-Ojalvo, Jordi; Barreiro, Esther

doi:10.3390/ijerph18168431

Cited by 25 publications

(23 citation statements)

References 51 publications

(64 reference statements)

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“…Such an impairment in the degree of the airway obstruction and diffusion capacity was independent of the presence of COPD, as statistically significant differences were maintained among the three study clusters after excluding the COPD patients from the analysis in all three clusters. These results confirm that the differential phenotypes are associated with bronchiectasis per se rather than with COPD or the degree of the airflow limitation as also previously demonstrated [ 14 , 19 ].…”

Section: Discussionsupporting

confidence: 91%

“…Phenotypic classification of bronchiectasis patients according to several clinical and biological markers may help predict disease severity, the risk of exacerbations, and disease prognosis. Recent investigations showed that a cut-off value greater than 5 reliably predicted hospitalizations and all-cause mortality according to the FACED (FEV 1 , age, chronic colonization, radiological extension, and dyspnea) and bronchiectasis severity index (BSI) scores [ 18 ] and that eosinophil levels defined differential clinical clusters of bronchiectasis patients [ 19 ].…”

Section: Introductionmentioning

confidence: 99%

“…The current investigation sought to tease out differential phenotypic characteristics of patients with bronchiectasis using data mining approaches on the basis of the following systemic inflammatory and nutritional parameters: blood neutrophil, eosinophil, and lymphocyte counts, C reactive protein, and hemoglobin in a large-cohort of patients from the Spanish Online Bronchiectasis Registry (RIBRON) [ 19 , 20 ]. Three clusters of patients with differential clinical phenotypes were obtained.…”

Section: Introductionmentioning

confidence: 99%

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Systemic Inflammatory Biomarkers Define Specific Clusters in Patients with Bronchiectasis: A Large-Cohort Study

Wang

Villa²,

Dobarganes³

et al. 2022

Biomedicines

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Differential phenotypic characteristics using data mining approaches were defined in a large cohort of patients from the Spanish Online Bronchiectasis Registry (RIBRON). Three differential phenotypic clusters (hierarchical clustering, scikit-learn library for Python, and agglomerative methods) according to systemic biomarkers: neutrophil, eosinophil, and lymphocyte counts, C reactive protein, and hemoglobin were obtained in a patient large-cohort (n = 1092). Clusters #1–3 were named as mild, moderate, and severe on the basis of disease severity scores. Patients in cluster #3 were significantly more severe (FEV1, age, colonization, extension, dyspnea (FACED), exacerbation (EFACED), and bronchiectasis severity index (BSI) scores) than patients in clusters #1 and #2. Exacerbation and hospitalization numbers, Charlson index, and blood inflammatory markers were significantly greater in cluster #3 than in clusters #1 and #2. Chronic colonization by Pseudomonas aeruginosa and COPD prevalence were higher in cluster # 3 than in cluster #1. Airflow limitation and diffusion capacity were reduced in cluster #3 compared to clusters #1 and #2. Multivariate ordinal logistic regression analysis further confirmed these results. Similar results were obtained after excluding COPD patients. Clustering analysis offers a powerful tool to better characterize patients with bronchiectasis. These results have clinical implications in the management of the complexity and heterogeneity of bronchiectasis patients.

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Section: Discussionsupporting

confidence: 91%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Systemic Inflammatory Biomarkers Define Specific Clusters in Patients with Bronchiectasis: A Large-Cohort Study

Wang

Villa²,

Dobarganes³

et al. 2022

Biomedicines

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“…Extrapulmonary manifestations are common among patients with chronic respiratory diseases, including those with bronchiectasis [ 5 , 6 , 7 , 8 ]. The analysis of skeletal muscle dysfunction and sarcopenia of patients with chronic obstructive pulmonary disease (COPD) have been a matter of research in multiple previous investigations [ 9 , 10 , 11 , 12 , 13 , 14 ].…”

Section: Introductionmentioning

confidence: 99%

Respiratory and Peripheral Muscle Weakness and Body Composition Abnormalities in Non-Cystic Fibrosis Bronchiectasis Patients: Gender Differences

et al. 2022

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As demonstrated in COPD, bronchiectasis patients may experience respiratory and peripheral muscle dysfunction. We hypothesized that respiratory and peripheral (upper and lower limbs) muscle function and nutritional status may be more significantly altered in female than in males for identical age and disease severity. In mild-to-moderate bronchiectasis patients (n = 150, 114 females) and 37 controls (n = 37, 21 females), radiological extension, maximal inspiratory and expiratory pressures (MIP and MEP), sniff nasal inspiratory pressure (SNIP), hand grip and quadriceps muscle strengths, body composition, and blood analytical biomarkers were explored. Compared to the controls, in all bronchiectasis patients (males and females), BMI, fat-free mass index (FFMI), fat tissue, upper and lower limb muscle strength, and respiratory muscle strength significantly declined, and FFMI, fat tissue, and quadriceps muscle function were significantly lower in female than male patients. In patients with mild-to-moderate bronchiectasis, respiratory and peripheral muscle function is significantly impaired and only partly related to lung disease status. Quadriceps muscle strength was particularly weakened in the female patients and was negatively associated with their exercise tolerance. Muscle weakness should be therapeutically targeted in bronchiectasis patients. Body composition and peripheral muscle function determination should be part of the comprehensive clinical assessment of these patients.

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“…This inflammation, along with various products of microorganisms (mainly bacterial proteolytic substances), is what ultimately causes the irreversible damage to the bronchial wall and airway dilation that characterize bronchiectasis and explain its symptoms [ 7 ]. Furthermore, a variable percentage of patients, especially those with greater severity, present a certain degree of systemic inflammation of a very heterogeneous nature [ 3 , 13 , 14 , 15 , 16 , 17 ], although some authors have found homogeneous groups based on parameters of cell or molecular counts in peripheral blood [ 18 , 19 , 20 ].…”

Section: Introductionmentioning

confidence: 99%

Peripheral Neutrophil-to-Lymphocyte Ratio in Bronchiectasis: A Marker of Disease Severity

et al. 2022

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Most patients with bronchiectasis have a predominantly neutrophilic inflammatory profile, although other cells such as lymphocytes (as controllers of bronchial inflammation) and eosinophils also play a significant pathophysiological role. Easy-to-interpret blood biomarkers with a discriminative capacity for severity or prognosis are needed. The objective of this study was to assess whether the peripheral neutrophil-to-lymphocyte ratio (NLR) is associated with different outcomes of severity in bronchiectasis. A total of 1369 patients with bronchiectasis from the Spanish Registry of Bronchiectasis were included. To compare groups, the sample was divided into increasing quartiles of NLR ratio. Correlations between quantitative variables were established using Pearson’s P test. A simple linear regression (with the value of exacerbations as a quantitative variable) was used to determine the independent relationship between the number and severity of exacerbations and the NLR ratio. The area under the curve (AUC)-ROC was used to determine the predictive capacity of the NLR for severe bronchiectasis, according to the different multidimensional scores. Mean age: 69 (15) years (66.3% of women). The mean NLR was 2.92 (2.03). A higher NLR was associated with more severe bronchiectasis (with an especially significant discriminative power for severe forms) according to the commonly used scores (FACED, E-FACED and BSI), as well as with poorer quality of life (SGRQ), more comorbidities (Charlson index), infection by pathogenic microorganisms, and greater application of treatment. Furthermore, the NLR correlated better with severity scores than other parameters of systemic inflammation. Finally, it was an independent predictor of the incident number and severity of exacerbations. In conclusion, the NLR is an inexpensive and easy-to-measure marker of systemic inflammation for determining severity and predicting exacerbations (especially the most severe) in patients with bronchiectasis.

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Phenotypic Clustering in Non-Cystic Fibrosis Bronchiectasis Patients: The Role of Eosinophils in Disease Severity

Cited by 25 publications

References 51 publications

Systemic Inflammatory Biomarkers Define Specific Clusters in Patients with Bronchiectasis: A Large-Cohort Study

Systemic Inflammatory Biomarkers Define Specific Clusters in Patients with Bronchiectasis: A Large-Cohort Study

Respiratory and Peripheral Muscle Weakness and Body Composition Abnormalities in Non-Cystic Fibrosis Bronchiectasis Patients: Gender Differences

Peripheral Neutrophil-to-Lymphocyte Ratio in Bronchiectasis: A Marker of Disease Severity

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