Polygenic risk scores identify heterogeneity in asthma and chronic obstructive pulmonary disease.

BACKGROUND: Asthma and chronic obstructive pulmonary disease (COPD) have distinct and overlapping genetic and clinical features. OBJECTIVE: We sought to test the hypothesis that polygenic risk scores (PRSs) for asthma (PRSAsthma) and spirometry (FEV1 and FEV1/forced vital capacity; PRSspiro) would demonstrate differential associations with asthma, COPD, and asthma-COPD overlap (ACO). METHODS: We developed and tested 2 asthma PRSs and applied the higher performing PRSAsthma and a previously published PRSspiro to research (Genetic Epidemiology of COPD study and Childhood Asthma Management Program, with spirometry) and electronic health record-based (Mass General Brigham Biobank and Genetic Epidemiology Research on Adult Health and Aging [GERA]) studies. We assessed the association of PRSs with COPD and asthma using modified random-effects and binary-effects meta-analyses, and ACO and asthma exacerbations in specific cohorts. Models were adjusted for confounders and genetic ancestry. RESULTS: In meta-analyses of 102,477 participants, the PRSAsthma (odds ratio [OR] per SD, 1.16 [95% CI, 1.14-1.19]) and PRSspiro (OR per SD, 1.19 [95% CI, 1.17-1.22]) both predicted asthma, whereas the PRSspiro predicted COPD (OR per SD, 1.25 [95% CI, 1.21-1.30]). However, results differed by cohort. The PRSspiro was not associated with COPD in GERA and Mass General Brigham Biobank. In the Genetic Epidemiology of COPD study, the PRSAsthma (OR per SD: Whites, 1.3; African Americans, 1.2) and PRSspiro (OR per SD: Whites, 2.2; African Americans, 1.6) were both associated with ACO. In GERA, the PRSAsthma was associated with asthma exacerbations (OR, 1.18) in Whites; the PRSspiro was associated with asthma exacerbations in White, LatinX, and East Asian participants. CONCLUSIONS: PRSs for asthma and spirometry are both associated with ACO and asthma exacerbations. Genetic prediction performance differs in research versus electronic health record-based cohorts.

Stratification of asthma by lipidomic profiling of induced sputum supernatant.

BACKGROUND: Asthma is a chronic respiratory disease with significant heterogeneity in its clinical presentation and pathobiology. There is need for improved understanding of respiratory lipid metabolism in asthma patients and its relation to observable clinical features. OBJECTIVE: We performed a comprehensive, prospective, cross-sectional analysis of the lipid composition of induced sputum supernatant obtained from asthma patients with a range of disease severities, as well as from healthy controls. METHODS: Induced sputum supernatant was collected from 211 adults with asthma and 41 healthy individuals enrolled onto the U-BIOPRED (Unbiased Biomarkers for the Prediction of Respiratory Disease Outcomes) study. Sputum lipidomes were characterized by semiquantitative shotgun mass spectrometry and clustered using topologic data analysis to identify lipid phenotypes. RESULTS: Shotgun lipidomics of induced sputum supernatant revealed a spectrum of 9 molecular phenotypes, highlighting not just significant differences between the sputum lipidomes of asthma patients and healthy controls, but also within the asthma patient population. Matching clinical, pathobiologic, proteomic, and transcriptomic data helped inform the underlying disease processes. Sputum lipid phenotypes with higher levels of nonendogenous, cell-derived lipids were associated with significantly worse asthma severity, worse lung function, and elevated granulocyte counts. CONCLUSION: We propose a novel mechanism of increased lipid loading in the epithelial lining fluid of asthma patients resulting from the secretion of extracellular vesicles by granulocytic inflammatory cells, which could reduce the ability of pulmonary surfactant to lower surface tension in asthmatic small airways, as well as compromise its role as an immune regulator.

The role of inflammation in anxiety and depression in the European U-BIOPRED asthma cohorts.

BACKGROUND: Growing evidence indicates high comorbid anxiety and depression in patients with asthma. However, the mechanisms underlying this comorbid condition remain unclear. The aim of this study was to investigate the role of inflammation in comorbid anxiety and depression in three asthma patient cohorts of the Unbiased Biomarkers for the Prediction of Respiratory Disease Outcomes (U-BIOPRED) project. METHODS: U-BIOPRED was conducted by a European Union consortium of 16 academic institutions in 11 European countries. A subset dataset from subjects with valid anxiety and depression measures and a large blood biomarker dataset were analysed, including 198 non-smoking patients with severe asthma (SAn), 65 smoking patients with severe asthma (SAs), 61 non-smoking patients with mild-to-moderate asthma (MMA), and 20 healthy non-smokers (HC). The Hospital Anxiety and Depression Scale was used to measure anxiety and depression and a series of inflammatory markers were analysed by the SomaScan v3 platform (SomaLogic, Boulder, Colo). ANOVA and the Kruskal-Wallis test were used for multiple-group comparisons as appropriate. RESULTS: There were significant group effects on anxiety and depression among the four cohort groups (p < 0.05). Anxiety and depression of SAn and SAs groups were significantly higher than that of MMA and HC groups (p < 0.05. There were significant differences in serum IL6, MCP1, CCL18, CCL17, IL8, and Eotaxin among the four groups (p < 0.05). Depression was significantly associated with IL6, MCP1, CCL18 level, and CCL17; whereas anxiety was associated with CCL17 only (p < 0.05). CONCLUSIONS: The current study suggests that severe asthma patients are associated with higher levels of anxiety and depression, and inflammatory responses may underlie this comorbid condition.

Mapping atopic dermatitis and anti-IL-22 response signatures to type 2-low severe neutrophilic asthma.

BACKGROUND: Transcriptomic changes in patients who respond clinically to biological therapies may identify responses in other tissues or diseases. OBJECTIVE: We sought to determine whether a disease signature identified in atopic dermatitis (AD) is seen in adults with severe asthma and whether a transcriptomic signature for patients with AD who respond clinically to anti-IL-22 (fezakinumab [FZ]) is enriched in severe asthma. METHODS: An AD disease signature was obtained from analysis of differentially expressed genes between AD lesional and nonlesional skin biopsies. Differentially expressed genes from lesional skin from therapeutic superresponders before and after 12 weeks of FZ treatment defined the FZ-response signature. Gene set variation analysis was used to produce enrichment scores of AD and FZ-response signatures in the Unbiased Biomarkers for the Prediction of Respiratory Disease Outcomes asthma cohort. RESULTS: The AD disease signature (112 upregulated genes) encompassing inflammatory, T-cell, TH2, and TH17/TH22 pathways was enriched in the blood and sputum of patients with asthma with increasing severity. Patients with asthma with sputum neutrophilia and mixed granulocyte phenotypes were the most enriched (P < .05). The FZ-response signature (296 downregulated genes) was enriched in asthmatic blood (P < .05) and particularly in neutrophilic and mixed granulocytic sputum (P < .05). These data were confirmed in sputum of the Airway Disease Endotyping for Personalized Therapeutics cohort. IL-22 mRNA across tissues did not correlate with FZ-response enrichment scores, but this response signature correlated with TH22/IL-22 pathways. CONCLUSIONS: The FZ-response signature in AD identifies severe neutrophilic asthmatic patients as potential responders to FZ therapy. This approach will help identify patients for future asthma clinical trials of drugs used successfully in other chronic diseases.

Plasma proteins elevated in severe asthma despite oral steroid use and unrelated to Type-2 inflammation.

RATIONALE: Asthma phenotyping requires novel biomarker discovery. OBJECTIVES: To identify plasma biomarkers associated with asthma phenotypes by application of a new proteomic panel to samples from two well-characterised cohorts of severe (SA) and mild-to-moderate (MMA) asthmatics, COPD subjects and healthy controls (HCs). METHODS: An antibody-based array targeting 177 proteins predominantly involved in pathways relevant to inflammation, lipid metabolism, signal transduction and extracellular matrix was applied to plasma from 525 asthmatics and HCs in the U-BIOPRED cohort, and 142 subjects with asthma and COPD from the validation cohort BIOAIR. Effects of oral corticosteroids (OCS) were determined by a 2-week, placebo-controlled OCS trial in BIOAIR, and confirmed by relation to objective OCS measures in U-BIOPRED. RESULTS: In U-BIOPRED, 110 proteins were significantly different, mostly elevated, in SA compared to MMA and HCs. 10 proteins were elevated in SA versus MMA in both U-BIOPRED and BIOAIR (alpha-1-antichymotrypsin, apolipoprotein-E, complement component 9, complement factor I, macrophage inflammatory protein-3, interleukin-6, sphingomyelin phosphodiesterase 3, TNF receptor superfamily member 11a, transforming growth factor-ß and glutathione S-transferase). OCS treatment decreased most proteins, yet differences between SA and MMA remained following correction for OCS use. Consensus clustering of U-BIOPRED protein data yielded six clusters associated with asthma control, quality of life, blood neutrophils, high-sensitivity C-reactive protein and body mass index, but not Type-2 inflammatory biomarkers. The mast cell specific enzyme carboxypeptidase A3 was one major contributor to cluster differentiation. CONCLUSIONS: The plasma proteomic panel revealed previously unexplored yet potentially useful Type-2-independent biomarkers and validated several proteins with established involvement in the pathophysiology of SA.

Urinary metabotype of severe asthma evidences decreased carnitine metabolism independent of oral corticosteroid treatment in the U-BIOPRED study.

INTRODUCTION: Asthma is a heterogeneous disease with poorly defined phenotypes. Patients with severe asthma often receive multiple treatments including oral corticosteroids (OCS). Treatment may modify the observed metabotype, rendering it challenging to investigate underlying disease mechanisms. Here, we aimed to identify dysregulated metabolic processes in relation to asthma severity and medication. METHODS: Baseline urine was collected prospectively from healthy participants (n=100), patients with mild-to-moderate asthma (n=87) and patients with severe asthma (n=418) in the cross-sectional U-BIOPRED cohort; 12-18-month longitudinal samples were collected from patients with severe asthma (n=305). Metabolomics data were acquired using high-resolution mass spectrometry and analysed using univariate and multivariate methods. RESULTS: A total of 90 metabolites were identified, with 40 significantly altered (p<0.05, false discovery rate <0.05) in severe asthma and 23 by OCS use. Multivariate modelling showed that observed metabotypes in healthy participants and patients with mild-to-moderate asthma differed significantly from those in patients with severe asthma (p=2.6×10-20), OCS-treated asthmatic patients differed significantly from non-treated patients (p=9.5×10-4), and longitudinal metabotypes demonstrated temporal stability. Carnitine levels evidenced the strongest OCS-independent decrease in severe asthma. Reduced carnitine levels were associated with mitochondrial dysfunction via decreases in pathway enrichment scores of fatty acid metabolism and reduced expression of the carnitine transporter SLC22A5 in sputum and bronchial brushings. CONCLUSIONS: This is the first large-scale study to delineate disease- and OCS-associated metabolic differences in asthma. The widespread associations with different therapies upon the observed metabotypes demonstrate the need to evaluate potential modulating effects on a treatment- and metabolite-specific basis. Altered carnitine metabolism is a potentially actionable therapeutic target that is independent of OCS treatment, highlighting the role of mitochondrial dysfunction in severe asthma.

Urinary Leukotriene E4 and Prostaglandin D2 Metabolites Increase in Adult and Childhood Severe Asthma Characterized by Type 2 Inflammation. A Clinical Observational Study.

Rationale: New approaches are needed to guide personalized treatment of asthma.Objectives: To test if urinary eicosanoid metabolites can direct asthma phenotyping.Methods: Urinary metabolites of prostaglandins (PGs), cysteinyl leukotrienes (CysLTs), and isoprostanes were quantified in the U-BIOPRED (Unbiased Biomarkers for the Prediction of Respiratory Diseases Outcomes) study including 86 adults with mild-to-moderate asthma (MMA), 411 with severe asthma (SA), and 100 healthy control participants. Validation was performed internally in 302 participants with SA followed up after 12-18 months and externally in 95 adolescents with asthma.Measurement and Main Results: Metabolite concentrations in healthy control participants were unrelated to age, body mass index, and sex, except for the PGE2 pathway. Eicosanoid concentrations were generally greater in participants with MMA relative to healthy control participants, with further elevations in participants with SA. However, PGE2 metabolite concentrations were either the same or lower in male nonsmokers with asthma than in healthy control participants. Metabolite concentrations were unchanged in those with asthma who adhered to oral corticosteroid treatment as documented by urinary prednisolone detection, whereas those with SA treated with omalizumab had lower concentrations of LTE4 and the PGD2 metabolite 2,3-dinor-11ß-PGF2α. High concentrations of LTE4 and PGD2 metabolites were associated with lower lung function and increased amounts of exhaled nitric oxide and eosinophil markers in blood, sputum, and urine in U-BIOPRED participants and in adolescents with asthma. These type 2 (T2) asthma associations were reproduced in the follow-up visit of the U-BIOPRED study and were found to be as sensitive to detect T2 inflammation as the established biomarkers.Conclusions: Monitoring of urinary eicosanoids can identify T2 asthma and introduces a new noninvasive approach for molecular phenotyping of adult and adolescent asthma.Clinical trial registered with www.clinicaltrials.gov (NCT01976767).

Coagulation markers as predictors for clinical events in COPD.

BACKGROUND AND OBJECTIVE: Activation of the blood coagulation system is a common observation in inflammatory diseases. The role of coagulation in COPD is underexplored. METHODS: The study included 413 COPD patients and 49 controls from the 3-year Bergen COPD Cohort Study (BCCS). One hundred and forty-eight COPD patients were also examined during AECOPD. The plasma markers of coagulation activation, TAT complex, APC-PCI complex and D-dimer, were measured at baseline and during exacerbations by enzyme immunoassays. Differences in levels of the markers between stable COPD patients and controls, and between stable COPD and AECOPD were examined. The associations between coagulation markers and later AECOPD and mortality were examined by negative binomial and Cox regression analyses. RESULTS: TAT was significantly lower in stable COPD (1.03 ng/mL (0.76-1.44)) than in controls (1.28 (1.04-1.49), P = 0.002). During AECOPD, all markers were higher than in the stable state: TAT 2.56 versus 1.43 ng/mL, APC-PCI 489.3 versus 416.4 ng/mL and D-dimer 763.5 versus 479.7 ng/mL (P < 0.001 for all). Higher D-dimer in stable COPD predicted a higher mortality (HR: 1.60 (1.24-2.05), P < 0.001). Higher TAT was associated with both an increased risk of later exacerbations, with a yearly incidence rate ratio of 1.19 (1.04-1.37), and a faster time to the first exacerbation (HR: 1.25 (1.10-1.42), P = 0.001, all after adjustment). CONCLUSION: Activation of the coagulation system is increased during COPD exacerbations. Coagulation markers are potential predictors of later COPD exacerbations and mortality.

Repeated bronchoscopy in health and obstructive lung disease: is the airway microbiome stable?

OBJECTIVE: Little is known concerning the stability of the lower airway microbiome. We have compared the microbiota identified by repeated bronchoscopy in healthy subjects and patients with ostructive lung diseaseases (OLD). METHODS: 21 healthy controls and 41 patients with OLD completed two bronchoscopies. In addition to negative controls (NCS) and oral wash (OW) samples, we gathered protected bronchoalveolar lavage in two fractions (PBAL1 and PBAL2) and protected specimen brushes (PSB). After DNA extraction, we amplified the V3V4 region of the 16S rRNA gene, and performed paired-end sequencing (Illumina MiSeq). Initial bioinformatic processing was carried out in the QIIME-2 pipeline, identifying amplicon sequence variants (ASVs) with the DADA2 algorithm. Potentially contaminating ASVs were identified and removed using the decontam package in R and the sequenced NCS. RESULTS: A final table of 551 ASVs consisted of 19 × 106 sequences. Alpha diversity was lower in the second exam for OW samples, and borderline lower for PBAL1, with larger differences in subjects not having received intercurrent antibiotics. Permutational tests of beta diversity indicated that within-individual changes were significantly lower than between-individual changes. A non-parametric trend test showed that differences in composition between the two exams (beta diversity) were largest in the PSBs, and that these differences followed a pattern of PSB > PBAL2 > PBAL1 > OW. Time between procedures was not associated with increased diversity. CONCLUSION: The airways microbiota varied between examinations. However, there is compositional microbiota stability within a person, beyond that of chance, supporting the notion of a transient airways microbiota with a possibly more stable individual core microbiome.

IL-17-high asthma with features of a psoriasis immunophenotype.

BACKGROUND: The role of IL-17 immunity is well established in patients with inflammatory diseases, such as psoriasis and inflammatory bowel disease, but not in asthmatic patients, in whom further study is required. OBJECTIVE: We sought to undertake a deep phenotyping study of asthmatic patients with upregulated IL-17 immunity. METHODS: Whole-genome transcriptomic analysis was performed by using epithelial brushings, bronchial biopsy specimens (91 asthmatic patients and 46 healthy control subjects), and whole blood samples (n = 498) from the Unbiased Biomarkers for the Prediction of Respiratory Disease Outcomes (U-BIOPRED) cohort. Gene signatures induced in vitro by IL-17 and IL-13 in bronchial epithelial cells were used to identify patients with IL-17-high and IL-13-high asthma phenotypes. RESULTS: Twenty-two of 91 patients were identified with IL-17, and 9 patients were identified with IL-13 gene signatures. The patients with IL-17-high asthma were characterized by risk of frequent exacerbations, airway (sputum and mucosal) neutrophilia, decreased lung microbiota diversity, and urinary biomarker evidence of activation of the thromboxane B2 pathway. In pathway analysis the differentially expressed genes in patients with IL-17-high asthma were shared with those reported as altered in psoriasis lesions and included genes regulating epithelial barrier function and defense mechanisms, such as IL1B, IL6, IL8, and ß-defensin. CONCLUSION: The IL-17-high asthma phenotype, characterized by bronchial epithelial dysfunction and upregulated antimicrobial and inflammatory response, resembles the immunophenotype of psoriasis, including activation of the thromboxane B2 pathway, which should be considered a biomarker for this phenotype in further studies, including clinical trials targeting IL-17.

Identification and prospective stability of electronic nose (eNose)-derived inflammatory phenotypes in patients with severe asthma.

BACKGROUND: Severe asthma is a heterogeneous condition, as shown by independent cluster analyses based on demographic, clinical, and inflammatory characteristics. A next step is to identify molecularly driven phenotypes using "omics" technologies. Molecular fingerprints of exhaled breath are associated with inflammation and can qualify as noninvasive assessment of severe asthma phenotypes. OBJECTIVES: We aimed (1) to identify severe asthma phenotypes using exhaled metabolomic fingerprints obtained from a composite of electronic noses (eNoses) and (2) to assess the stability of eNose-derived phenotypes in relation to within-patient clinical and inflammatory changes. METHODS: In this longitudinal multicenter study exhaled breath samples were taken from an unselected subset of adults with severe asthma from the U-BIOPRED cohort. Exhaled metabolites were analyzed centrally by using an assembly of eNoses. Unsupervised Ward clustering enhanced by similarity profile analysis together with K-means clustering was performed. For internal validation, partitioning around medoids and topological data analysis were applied. Samples at 12 to 18 months of prospective follow-up were used to assess longitudinal within-patient stability. RESULTS: Data were available for 78 subjects (age, 55 years [interquartile range, 45-64 years]; 41% male). Three eNose-driven clusters (n = 26/33/19) were revealed, showing differences in circulating eosinophil (P = .045) and neutrophil (P = .017) percentages and ratios of patients using oral corticosteroids (P = .035). Longitudinal within-patient cluster stability was associated with changes in sputum eosinophil percentages (P = .045). CONCLUSIONS: We have identified and followed up exhaled molecular phenotypes of severe asthma, which were associated with changing inflammatory profile and oral steroid use. This suggests that breath analysis can contribute to the management of severe asthma.

Stratification of asthma phenotypes by airway proteomic signatures.

BACKGROUND: Stratification by eosinophil and neutrophil counts increases our understanding of asthma and helps target therapy, but there is room for improvement in our accuracy in prediction of treatment responses and a need for better understanding of the underlying mechanisms. OBJECTIVE: We sought to identify molecular subphenotypes of asthma defined by proteomic signatures for improved stratification. METHODS: Unbiased label-free quantitative mass spectrometry and topological data analysis were used to analyze the proteomes of sputum supernatants from 246 participants (206 asthmatic patients) as a novel means of asthma stratification. Microarray analysis of sputum cells provided transcriptomics data additionally to inform on underlying mechanisms. RESULTS: Analysis of the sputum proteome resulted in 10 clusters (ie, proteotypes) based on similarity in proteomic features, representing discrete molecular subphenotypes of asthma. Overlaying granulocyte counts onto the 10 clusters as metadata further defined 3 of these as highly eosinophilic, 3 as highly neutrophilic, and 2 as highly atopic with relatively low granulocytic inflammation. For each of these 3 phenotypes, logistic regression analysis identified candidate protein biomarkers, and matched transcriptomic data pointed to differentially activated underlying mechanisms. CONCLUSION: This study provides further stratification of asthma currently classified based on quantification of granulocytic inflammation and provided additional insight into their underlying mechanisms, which could become targets for novel therapies.

Large-Scale Label-Free Quantitative Mapping of the Sputum Proteome.

Analysis of induced sputum supernatant is a minimally invasive approach to study the epithelial lining fluid and, thereby, provide insight into normal lung biology and the pathobiology of lung diseases. We present here a novel proteomics approach to sputum analysis developed within the U-BIOPRED (unbiased biomarkers predictive of respiratory disease outcomes) international project. We present practical and analytical techniques to optimize the detection of robust biomarkers in proteomic studies. The normal sputum proteome was derived using data-independent HDMSE applied to 40 healthy nonsmoking participants, which provides an essential baseline from which to compare modulation of protein expression in respiratory diseases. The "core" sputum proteome (proteins detected in ≥40% of participants) was composed of 284 proteins, and the extended proteome (proteins detected in ≥3 participants) contained 1666 proteins. Quality control procedures were developed to optimize the accuracy and consistency of measurement of sputum proteins and analyze the distribution of sputum proteins in the healthy population. The analysis showed that quantitation of proteins by HDMSE is influenced by several factors, with some proteins being measured in all participants' samples and with low measurement variance between samples from the same patient. The measurement of some proteins is highly variable between repeat analyses, susceptible to sample processing effects, or difficult to accurately quantify by mass spectrometry. Other proteins show high interindividual variance. We also highlight that the sputum proteome of healthy individuals is related to sputum neutrophil levels, but not gender or allergic sensitization. We illustrate the importance of design and interpretation of disease biomarker studies considering such protein population and technical measurement variance.

Lipid phenotyping of lung epithelial lining fluid in healthy human volunteers.

BACKGROUND: Lung epithelial lining fluid (ELF)-sampled through sputum induction-is a medium rich in cells, proteins and lipids. However, despite its key role in maintaining lung function, homeostasis and defences, the composition and biology of ELF, especially in respect of lipids, remain incompletely understood. OBJECTIVES: To characterise the induced sputum lipidome of healthy adult individuals, and to examine associations between different ELF lipid phenotypes and the demographic characteristics within the study cohort. METHODS: Induced sputum samples were obtained from 41 healthy non-smoking adults, and their lipid compositions analysed using a combination of untargeted shotgun and liquid chromatography mass spectrometry methods. Topological data analysis (TDA) was used to group subjects with comparable sputum lipidomes in order to identify distinct ELF phenotypes. RESULTS: The induced sputum lipidome was diverse, comprising a range of different molecular classes, including at least 75 glycerophospholipids, 13 sphingolipids, 5 sterol lipids and 12 neutral glycerolipids. TDA identified two distinct phenotypes differentiated by a higher total lipid content and specific enrichments of diacyl-glycerophosphocholines, -inositols and -glycerols in one group, with enrichments of sterols, glycolipids and sphingolipids in the other. Subjects presenting the lipid-rich ELF phenotype also had significantly higher BMI, but did not differ in respect of other demographic characteristics such as age or gender. CONCLUSIONS: We provide the first evidence that the ELF lipidome varies significantly between healthy individuals and propose that such differences are related to weight status, highlighting the potential impact of (over)nutrition on lung lipid metabolism.

Lung hyperinflation and functional exercise capacity in patients with COPD - a three-year longitudinal study.

BACKGROUND: Lung hyperinflation contributes to dyspnea, morbidity and mortality in chronic obstructive pulmonary disease (COPD). The inspiratory-to-total lung capacity (IC/TLC) ratio is a measure of lung hyperinflation and is associated with exercise intolerance. However, knowledge of its effect on longitudinal change in the 6-min walk distance (6MWD) in patients with COPD is scarce. We aimed to study whether the IC/TLC ratio predicts longitudinal change in 6MWD in patients with COPD. METHODS: This prospective cohort study included 389 patients aged 40-75 years with clinically stable COPD in Global Initiative for Chronic Obstructive Lung Disease stages II-IV. The 6MWD was measured at baseline, and after one and 3 years. We performed generalized estimating equation regression analyses to examine predictors for longitudinal change in 6MWD. Predictors at baseline were: IC/TLC ratio, age, gender, pack years, fat mass index (FMI), fat-free mass index (FFMI), number of exacerbations within 12 months prior to inclusion, Charlson index for comorbidities, forced vital capacity (FVC), forced expiratory volume in 1 s (FEV1), and light and hard self-reported physical activity. RESULTS: Reduced IC/TLC ratio (p < 0.001) was a statistically significant predictor for decline in 6MWD. With a 0.1-unit decrease in baseline IC/TLC ratio, the annual decline in 6MWD was 12.7 m (p < 0.001). Study participants with an IC/TLC ratio in the upper quartiles maintained their 6MWD from baseline to year 3, while it was significantly reduced for the patients with an IC/TLC ratio in the lower quartiles. Absence of light and hard physical activity, increased age and FMI, decreased FEV1 and FVC, more frequent exacerbations and higher Charlson comorbidity index were also predictors for lower 6MWD at any given time, but did not predict higher rate of decline over the timespan of the study. CONCLUSION: Our findings demonstrated that patients with less lung hyperinflation at baseline maintained their functional exercise capacity during the follow-up period, and that it was significantly reduced for patients with increased lung hyperinflation.

U-BIOPRED clinical adult asthma clusters linked to a subset of sputum omics.

BACKGROUND: Asthma is a heterogeneous disease in which there is a differential response to asthma treatments. This heterogeneity needs to be evaluated so that a personalized management approach can be provided. OBJECTIVES: We stratified patients with moderate-to-severe asthma based on clinicophysiologic parameters and performed an omics analysis of sputum. METHODS: Partition-around-medoids clustering was applied to a training set of 266 asthmatic participants from the European Unbiased Biomarkers for the Prediction of Respiratory Diseases Outcomes (U-BIOPRED) adult cohort using 8 prespecified clinic-physiologic variables. This was repeated in a separate validation set of 152 asthmatic patients. The clusters were compared based on sputum proteomics and transcriptomics data. RESULTS: Four reproducible and stable clusters of asthmatic patients were identified. The training set cluster T1 consists of patients with well-controlled moderate-to-severe asthma, whereas cluster T2 is a group of patients with late-onset severe asthma with a history of smoking and chronic airflow obstruction. Cluster T3 is similar to cluster T2 in terms of chronic airflow obstruction but is composed of nonsmokers. Cluster T4 is predominantly composed of obese female patients with uncontrolled severe asthma with increased exacerbations but with normal lung function. The validation set exhibited similar clusters, demonstrating reproducibility of the classification. There were significant differences in sputum proteomics and transcriptomics between the clusters. The severe asthma clusters (T2, T3, and T4) had higher sputum eosinophilia than cluster T1, with no differences in sputum neutrophil counts and exhaled nitric oxide and serum IgE levels. CONCLUSION: Clustering based on clinicophysiologic parameters yielded 4 stable and reproducible clusters that associate with different pathobiological pathways.

Growth differentiation factor-15 is a predictor of important disease outcomes in patients with COPD.

Increased levels of growth differentiation factor-15 (GDF15) are associated with cachexia, cardiovascular disease and all-cause mortality. The role of GDF15 in chronic obstructive pulmonary disease (COPD) is unknown.The study included 413 patients with COPD from the Bergen COPD Cohort Study. All patients had a forced expiratory volume in 1 s (FEV1) <80% predicted, a FEV1 to forced vital capacity (FVC) ratio <0.7 and a history of smoking. Spirometry, fat free mass index, blood gases and plasma GDF15 were measured at baseline. Patients were followed for 3 years regarding exacerbations and changes in lung function, and 9 years for mortality. Yearly exacerbation rate, survival and yearly change in FEV1/FVC were evaluated with regression models.Median plasma GDF15 was 0.86 ng·mL-1 (interquartile range 0.64-1.12 ng·mL-1). The distribution was not normal and GDF15 was analysed as a categorical variable. High levels of GDF15 were associated with a higher exacerbation rate (incidence rate ratio 1.39, 95% CI 1.1-1.74, p=0.006, adjusted values). Furthermore, high levels of GDF15 were associated with higher mortality (hazard ratio 2.07, 95% CI 1.4-3.1, p<0.001) and an increased decline in both FEV1 (4.29% versus 3.25%) and FVC (2.63% versus 1.44%) in comparison to low levels (p<0.01 for both).In patients with COPD, high levels of GDF15 were independently associated with a higher yearly rate of exacerbations, higher mortality and increased decline in both FEV1 and FVC.

Antimicrobial peptide levels are linked to airway inflammation, bacterial colonisation and exacerbations in chronic obstructive pulmonary disease.

Antimicrobial peptides (AMPs) are effectors of host defence against infection, inflammation and wound repair. We aimed to study AMP levels in stable chronic obstructive pulmonary disease (COPD) and during acute exacerbations of COPD (AECOPD), and to examine their relation to clinical parameters and inflammatory markers.The 3-year Bergen COPD Cohort Study included 433 COPD patients and 325 controls. Induced sputum was obtained and analysed for levels of the AMPs human cathelicidin (hCAP18/LL-37) and secretory leukocyte protease inhibitor (SLPI), and for the inflammatory markers interleukin (IL)-8, IL-6 and tumour necrosis factor-α (TNF-α) using immunoassays. Systemic hCAP18/LL-37 and vitamin D levels were also studied. Treating AMPs as response variables, non-parametric tests were applied for univariate comparison, and linear regression to obtain adjusted estimates. The risk of AECOPD was assessed by Cox proportional-hazard regression.Sputum AMP levels were higher in patients with stable COPD (n=215) compared to controls (n=45), and further changed during AECOPD (n=56), with increased hCAP18/LL-37 and decreased SLPI levels. Plasma hCAP18/LL-37 levels showed a similar pattern. In stable COPD, high sputum hCAP18/LL-37 levels were associated with increased risk of AECOPD, non-typeable Haemophilus influenzae colonisation, higher age, ex-smoking and higher levels of inflammatory markers.Altered levels of selected AMPs are linked to airway inflammation, infection and AECOPD, suggesting a role for these peptides in airway defence mechanisms in COPD.

Comparing microbiota profiles in induced and spontaneous sputum samples in COPD patients.

BACKGROUND: Induced and spontaneous sputum are used to evaluate the airways microbiota. Whether the sputum types can be used interchangeably in microbiota research is unknown. Our aim was to compare microbiota in induced and spontaneous sputum from COPD patients sampled during the same consultation. METHODS: COPD patients from Bergen, Norway, were followed between 2006/2010, examined during the stable state and exacerbations. 30 patients delivered 36 sample pairs. DNA was extracted by enzymatic and mechanical lysis methods. The V3-V4 region of the 16S rRNA gene was PCR-amplified and prepared for paired-end sequencing. Illumina Miseq System was used for sequencing, and Quantitative Insights Into Microbial Ecology (QIIME) and Stata were used for bioinformatics and statistical analyses. RESULTS: Approximately 4 million sequences were sorted into 1004 different OTUs and further assigned to 106 different taxa. Pair-wise comparison of both taxonomic composition and beta-diversity revealed significant differences in one or both parameters in 1/3 of sample pairs. Alpha-diversity did not differ. Comparing abundances for each taxa identified, showed statistically significant differences between the mean abundances in induced versus spontaneous samples for 15 taxa when disease state was considered. This included potential pathogens like Haemophilus and Moraxella. CONCLUSION: When studying microbiota in sputum samples one should take into consideration how samples are collected and avoid the usage of both induced and spontaneous sputum in the same study.

Macrophage migration inhibitory factor, a role in COPD.

Macrophage migration inhibitor factor (MIF) is a pluripotent cytokine associated with several different inflammatory conditions, but its role within lung inflammation and chronic obstructive pulmonary disease (COPD) is unclear. This study aimed to examine MIF in both stable COPD and during acute exacerbations (AECOPD). The study included 433 patients with COPD aged 41-76 and 325 individuals from the Bergen COPD cohort study who served as controls. All patients had an FEV1 of <80% predicted, FEV1/FVC ratio of <0.7, and a smoking history >10 pack-years. Serum levels of MIF were compared between the two groups at baseline, and for 149 patients, measurements were also carried out during AECOPD. Linear regression models were fitted with MIF as the outcome variable and adjusted for sex, age, body composition, smoking, and Charlson Comorbidity Score (CCS). Median MIF (interquartile range) in patients with COPD was 20.1 ng/ml (13.5-30.9) compared with 14.9 ng/ml (11.1-21.6) in controls (P < 0.01). MIF was bivariately associated with sex, body composition, and CCS (P < 0.05 for all). In the regression analyses, MIF was significantly higher in patients with COPD, coefficient 1.32 (P < 0.01) and 1.30 (P < 0.01) unadjusted and adjusted, respectively. In addition, in 149 patients during episodes of AECOPD, MIF was significantly elevated, with a median of 23.2 ng/ml (14.1-42.3) compared with measurements at stable disease of 19.3 ng/ml (12.4-31.3, P < 0.01). Serum levels of MIF were significantly higher in patients with COPD compared with controls. We also identified an additional increase in MIF levels during episodes of AECOPD.