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

Abstract

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.

Keywords: C reactive protein; blood neutrophil; clinical outcomes; disease severity scores; eosinophil; hemoglobin; hierarchical clustering; lymphocyte counts; multivariate analyses; non-cystic fibrosis bronchiectasis; phenotypic clusters.

Figure 1

Flow-chart of the study.

Figure 2

Uniform Manifold Approximation and Projection (UMAP) representation of the three clusters of patients. Three clusters of patients: blue, light brown, and green represent mild, moderate, and severe bronchiectasis patients, respectively.

Figure 3

Diagonal plots represent the distribution of the target variable across the three patient clusters. The distribution of the individual values in pairs of variables for the three clusters are represented in scattered plots. Three clusters of patients: blue, light brown, and green represent mild, moderate, and severe bronchiectasis patients, respectively.

Figure 4

Histograms of the proportions of patients who were classified as mild, moderate, or severe according to BSI (A), EFACED (B) and FACED (C) among the three clusters. Score subdivisions were as follows: (1) BSI: mild: 0–4, moderate: 5–8, severe: ≥9, (2) EFACED: mild: 0–3, moderate: 4–6, severe: 7–9; and (3) FACED: mild: 0–2, moderate: 3–4, severe: 5–7. Statistical significance: *, p ≤ 0.05; **, p ≤ 0.01; ***, p ≤ 0.001: Comparisons were assessed between either group # 3 or group # 2 and group # 1 (less severe); §§, p ≤ 0.01; §§§, p ≤ 0.001: Comparisons between groups # 3 and # 2. n.s.: no significance.

Figure 5

(A) Mean values and standard deviation of total number of neutrophils (10³/microL) among cluster 1, cluster 2, and cluster 3 in all the study patients. (B) Mean values and standard deviation of total number of lymphocytes (10³/microL) among cluster 1, cluster 2, and cluster 3 in all the study patients. Statistical significance: ***, p ≤ 0.001: Comparisons were assessed between either group # 3 or group # 2 and group # 1 (less severe §§§, p ≤ 0.001: Comparisons between groups # 3 and # 2.

Figure 6

(A) Mean values and standard deviation of total number of neutrophils (10³/microL) in the three clusters of patients excluding those with COPD. (B) Mean values and standard deviation of total number of lymphocytes (10³/microL) in the three clusters of patients excluding those with COPD. Statistical significance: ***, p ≤ 0.001: Comparisons were assessed between either group # 3 or group # 2 and group # 1 (less severe §§§, p ≤ 0.001: Comparisons between groups # 3 and # 2.

Figure 7

Correlation matrix of the disease severity and analytical variables, in which the positive correlations are represented in blue, while the negative correlations are represented in red: (A) all the study patients, (B) patients in cluster # 1, (C) patients in cluster # 2, and (D) patients in cluster # 3. The intersection within the circle represents a p-value > 0.05. The color intensity and the size of the circle are proportional to the correlation coefficients, as indicated in the Y-axis on the right-hand side of the graph.

Figure 7

Correlation matrix of the disease severity and analytical variables, in which the positive correlations are represented in blue, while the negative correlations are represented in red: (A) all the study patients, (B) patients in cluster # 1, (C) patients in cluster # 2, and (D) patients in cluster # 3. The intersection within the circle represents a p-value > 0.05. The color intensity and the size of the circle are proportional to the correlation coefficients, as indicated in the Y-axis on the right-hand side of the graph.

Figure 7

Correlation matrix of the disease severity and analytical variables, in which the positive correlations are represented in blue, while the negative correlations are represented in red: (A) all the study patients, (B) patients in cluster # 1, (C) patients in cluster # 2, and (D) patients in cluster # 3. The intersection within the circle represents a p-value > 0.05. The color intensity and the size of the circle are proportional to the correlation coefficients, as indicated in the Y-axis on the right-hand side of the graph.

Figure 8

Multivariate ordinal logistic regression, in which the outcome variable was clusters (ordered from 1, the lowest level, to 3, the highest level) was used to assess the potential associations of EFACED score with each of the clusters. The following clinically meaningful confounders were considered: Charlson index, COPD, platelets, ESR, fibrinogen, creatinine, total protein concentration, and albumin levels. The multivariate regression odds ratio (OR) is represented as a black dot in each of the confounders along with the corresponding confidence intervals, which were depicted in a forest plot. In the Y-axis, all the confounder variables are plotted, while in the X-axis, the width of the confidence intervals is represented. The one value is represented as a dotted vertical line.