Accelerated Lung Function Decline and Mucus-Microbe Evolution in Chronic Obstructive Pulmonary Disease

Abstract

Rationale: Progressive lung function loss is recognized in chronic obstructive pulmonary disease (COPD); however, no study concurrently evaluates how accelerated lung function decline relates to mucus properties and the microbiome in COPD. Objectives: Longitudinal assessment of mucus and microbiome changes accompanying accelerated lung function decline in patients COPD. Methods: This was a prospective, longitudinal assessment of the London COPD cohort exhibiting the greatest FEV₁ decline (n = 30; accelerated decline; 156 ml/yr FEV₁ loss) and with no FEV₁ decline (n = 28; nondecline; 49 ml/yr FEV₁ gain) over time. Lung microbiomes from paired sputum (total 116 specimens) were assessed by shotgun metagenomics and corresponding mucus profiles evaluated for biochemical and biophysical properties. Measurements and Main Results: Biochemical and biophysical mucus properties are significantly altered in the accelerated decline group. Unsupervised principal component analysis showed clear separation, with mucus biochemistry associated with accelerated decline, whereas biophysical mucus characteristics contributed to interindividual variability. When mucus and microbes are considered together, an accelerated decline mucus-microbiome association emerges, characterized by increased mucin (MUC5AC [mucin 5AC] and MUC5B [mucin 5B]) concentration and the presence of Achromobacter and Klebsiella. As COPD progresses, mucus-microbiome shifts occur, initially characterized by low mucin concentration and transition from viscous to elastic dominance accompanied by the commensals Veillonella, Gemella, Rothia, and Prevotella (Global Initiative for Chronic Obstructive Lung Disease [GOLD] A and B) before transition to increased mucus viscosity, mucins, and DNA concentration together with the emergence of pathogenic microorganisms including Haemophilus, Moraxella, and Pseudomonas (GOLD E). Conclusions: Mucus-microbiome associations evolve over time with accelerated lung function decline, symptom progression, and exacerbations affording fresh therapeutic opportunities for early intervention.

Keywords: COPD; lung function decline; metagenomics; mucus; rheology.

Figure 1.

Mucus biochemical profiles in chronic obstructive pulmonary disease with accelerated decline in lung function demonstrate significantly elevated (A) mucus solids, (B) total mucins, (C) MUC5AC, (D) MUC5B, (E) MUC5AC/MUC5B ratio, and (F) DNA concentration compared with individuals exhibiting no lung function decline between the initial and follow-up time points. P values calculated using Wilcoxon signed-rank test. *P < 0.05, **P < 0.01, ***P < 0.001, and ****P < 0.0001. DNA = sputum DNA concentration; MUC5AC = mucin 5AC; MUC5B = mucin 5B; ns = nonsignificant.

Figure 2.

Mucus biophysical profiles in chronic obstructive pulmonary disease with accelerated decline in lung function demonstrate significantly elevated (A) complex viscosity, constituent (B) elastic and (C) viscous components, and (D) ratio of viscous to elastic components (tanδ) compared with individuals exhibiting no lung function decline between the initial and follow-up time points. P values calculated using Wilcoxon signed-rank test. *P < 0.05, **P < 0.01, ***P < 0.001, and ****P < 0.0001. Rheological measurements performed at 10 rad/s. δ = ratio of the viscous to elastic effects; ns = nonsignificant; Pa = pascals; Pa.s = pascal-seconds; tanδ = the tangent of the phase angle.

Figure 3.

(A) Unsupervised principal component analysis (PCA) plot demonstrating significant differences in mucus profile between accelerated decline (black circles) and nondecline (red squares) groups, with each point representing the delta-change between the two time points (initial and follow-up) after correction for each individual’s duration of study participation. Each study participant is represented by a symbol and colored according to group status, with ellipses representing 95% confidence intervals. Permutational multivariate ANOVA (PERMANOVA): P < 0.0001. (B) Individual loadings plot outlining the direction and degree of contributed variance of the biochemical (orange circles and direction arrows) and biophysical (teal squares and direction arrows) mucus components driving the observed variability seen in the presented PCA (A). P values calculated using PERMANOVA using Euclidean distance. Data centered and scaled before PCA analysis. 5AC/5B ratio = ratio of MUC5AC to MUC5B; DNA = sputum DNA concentration; G′= elastic component; G″ = viscous component; MUC5AC = mucin 5AC; MUC5B = mucin 5B; η* = complex viscosity; tanδ = the tangent of the phase angle.

Figure 4.

(A) Supervised partial least square discriminant analysis (PLS-DA) classifying patients by decliner status and airway microbiomes. Accelerated decline (black circles) and nondecline (red squares) groups represent the pairwise difference of the centered log ratio (CLR)-transformed microbiome composition between the two time points (initial and follow-up) after correction for each individual’s duration of study participation. Each participant is represented by a symbol and colored according to group status, with ellipses representing 95% confidence intervals. Permutational multivariate ANOVA (PERMANOVA): P < 0.0001. (B) Individual loadings plot outlining genus-level airway microbiome change (purple direction arrows) driving the variability observed in the presented PLS-DA (A). (C) PLS-DA classifying patients by decliner status and incorporating biochemical and biophysical mucus assessment with airway microbiomes (i.e., the top 10 distinguishing microbial taxa identified in B). Accelerated decline (black circles) and nondecline (red squares) groups represent the pairwise difference in delta-change mucus and the CLR-transformed microbiome composition between the two time points (initial and follow-up) after correction for each individual’s duration of study participation. Each participant is represented by a symbol and colored according to group status, with ellipses representing 95% confidence intervals. PERMANOVA: P < 0.0001. (D) Individual loadings plot outlining biochemical (orange direction arrows) and biophysical (teal direction arrows) mucus assessments with airway microbiomes (purple direction arrows) (i.e., top 10 genus-level distinguishing microbial taxa) driving the observed variability seen in the presented PLS-DA (C). P values calculated using PERMANOVA using Euclidean distance. Data centered and scaled before principal component analysis analysis. MUC5AC = mucin 5AC; MUC5B = mucin 5B; 5AC/5B ratio = ratio of MUC5AC to MUC5B; DNA = sputum DNA concentration; Tan(δ) = the tangent of the phase angle.

Figure 5.

Summary of the (A) GOLD (2023) ABE assessment tool and related (B) mucus biochemical profile, (C) mucus biophysical profile, and (D) airway microbiome profile (18). (E) A combined assessment summarizing mucus properties and airway microbiome relationships within the respective categories as follows: A: low risk, fewer symptoms; B: low risk, more symptoms; E: high risk, frequent exacerbations irrespective of symptoms. P value calculated using Mann-Whitney U test with Benjamin-Hochberg correction for multiple comparisons. 5AC/5B ratio = ratio of MUC5AC to MUC5B; ABE = A (low symptoms, low risk), B (high symptoms, low risk) and E (high symptoms, high risk); DNA = sputum DNA concentration; CAT = Chronic Obstructive Pulmonary Disease Assessment Test; GOLD = Global Initiative for Chronic Obstructive Lung Disease; G* = Complex modulus; G′ = elastic component; G″ = viscous component; mMRC = modified Medical Research Council test; MUC5AC = mucin 5AC; MUC5B = mucin 5B.