IFNΛ3/4 locus polymorphisms and IFNΛ3 circulating levels are associated with COPD severity and outcomes.

BACKGROUND: Interferon lambdas (IFNLs) have important anti-viral/bacterial and immunomodulatory functions in the respiratory tract. How do IFNLs impact COPD and its exacerbations? METHODS: Five hundred twenty eight patients were recruited in a prospective observational multicentre cohort (PROMISE) study. The genetic polymorphisms (rs8099917 and rs12979860) within the IFNL3/4 gene region and circulating levels of IFNL3 in COPD patients were determined and associated with disease activity and outcome during a median follow-up of 24 months. RESULTS: The GG genotype significantly influenced severe exacerbation rate (42 vs. 23%; p = 0.032) and time to severe exacerbation (HR = 2.260; p = 0.012). Compared to the TT or TG genotypes, the GG genotype was associated with severe dyspnoea (modified medical research council score ≥ median 3; 22 vs 42%, p = 0.030). The CC genotype of the rs12979860 SNP was associated with a poorer prognosis (body mass index, airflow obstruction, dyspnea and exercise capacity index ≥ median 4; 46 vs. 36% TC vs. 20.5% TT; p = 0.031). Patients with stable COPD and at exacerbation had significantly lower circulating IFNL3 compared to healthy controls (p < 0.001 and p < 0.001, respectively). Circulating IFNL3 correlated to post-bronchodilator FEV1%predicted and the tissue maturation biomarker Pro-collagen 3. CONCLUSION: IFNL3/4 polymorphisms and circulating IFNL3 may be associated with disease activity and outcomes in COPD. TRIAL REGISTRATION: Clinical Trial registration http://www.isrctn.com/ identifier ISRCTN99586989 on 16 April 2008.

The role of non-invasive modalities for assessing inflammation in patients with non-cystic fibrosis bronchiectasis.

INTRODUCTION: Bronchiectasis is a heterogeneous entity, taking into account clinical characteristics, inflammatory response, effectiveness of treatment and frequency of exacerbations. In stable state non-cystic fibrosis (non-CF) bronchiectasis, little is known about non-invasive techniques used for evaluating airway inflammation in obstructive airway diseases. OBJECTIVES: We sought to evaluate the associations between induced sputum and clinical/radiologic characteristics, and the differences between biomarkers expressing Th1 and Th2 response in patients with non-CF bronchiectasis and to compare our findings with a previously studied population of patients with asthma and COPD. METHODS: We evaluated prospectively collected data from subjects with bronchiectasis. Comparisons were made between clinical, radiographic and physiologic characteristics, as well as induced sputum markers using appropriate statistical tools. We compared the levels of sputum markers with those of a previously studied cohort of asthma and COPD patients. RESULTS: We enrolled 40 subjects (21men, mean age 63.5yrs) with bronchiectasis. Fifteen subjects (37.5%) had a neutrophilic phenotype, 7 (17.5%) had an eosinophilic phenotype, 3 (12.5%) had a mixed neutrophilic-eosinophilic phenotype and 15 (37.5%) had a paucigranulocytic phenotype. Subjects with sputum neutrophilia had more severe bronchiectasis in HRCT and higher levels of IL-8 in sputum, whereas subjects with eosinophilia had higher levels of FeNO, greater bronchodilator reversibility and higher sputum IL-13. Sputum IL-8 levels were higher in subjects exhibiting frequent exacerbations and correlated with neutrophils in sputum (r=0.799), the extent of bronchiectasis in HRCT (r=0.765) and post-bronchodilator FEV1 (r=-0.416). Sputum IL-13 levels correlated with sputum eosinophils (r=0.656) and bronchodilator reversibility (r=0.441). Neutrophilic bronchiectasis exhibited comparable IL-8 levels to COPD, whereas eosinophilic bronchiectasis showed significantly lower IL-13 levels compared to asthma. CONCLUSIONS: Sputum cell counts and IL-8 and IL-13 correlate with distinct clinical and functional measurements of disease severity and therefore may have a role for non-invasively assessing inflammation in non-cystic fibrosis bronchiectasis.

Mannose-binding lectin protein and its association to clinical outcomes in COPD: a longitudinal study.

BACKGROUND: Functional deficiency of mannose-binding lectin (MBL) may contribute to the pathogenesis of chronic obstructive pulmonary disease. We hypothesized that specific MBL2 gene polymorphisms and circulating MBL protein levels are associated with clinically relevant outcomes in the Predicting Outcome using systemic Markers In Severe Exacerbations of COPD PROMISE-COPD cohort. METHODS: We followed 277 patients with stable COPD GOLD stage II-IV COPD over a median period of 733 days (IQR 641-767) taking survival as the primary outcome parameter. Patients were dichotomized as frequent (≥ 2 AECOPD/year) or infrequent exacerbators. Serum MBL levels and single nucleotide polymorphisms of the MBL2 gene were assessed at baseline. RESULTS: The MBL2-HYPD haplotype was significantly more prevalent in frequent exacerbators (OR: 3.33; 95% CI, 1.24-7.14, p = 0.01). The median serum MBL concentration was similar in frequent (607 ng/ml, [IQR; 363.0-896.0 ng/ml]) and infrequent exacerbators (615 ng/ml, [IQR; 371.0-942.0 ng/ml]). Serum MBL was not associated with lung function characteristics or bacterial colonization in sputum. However, high serum MBL at stable state was associated with better survival compared to low MBL (p = 0.046, log rank test). CONCLUSIONS: In COPD, the HYPD haplotype of MBL2 gene is associated with frequent exacerbations and high serum MBL is linked to increased survival. The PROMISE-COPD study was registered at www.controlled-trials.com under the identifier ISRCTN99586989.

Adrenomedullin refines mortality prediction by the BODE index in COPD: the "BODE-A" index.

The BODE (body mass index, airflow obstruction, dyspnoea, exercise capacity) index is well-validated for mortality prediction in chronic obstructive pulmonary disease (COPD). Concentrations of plasma pro-adrenomedullin, a surrogate for mature adrenomedullin, independently predicted 2-year mortality among inpatients with COPD exacerbation. We compared accuracy of initial pro-adrenomedullin level, BODE and BODE components, alone or combined, in predicting 1-year or 2-year all-cause mortality in a multicentre, multinational observational cohort with stable, moderate to very severe COPD. Pro-adrenomedullin was significantly associated (p<0.001) with 1-year mortality (4.7%) and 2-year mortality (7.8%) and comparably predictive to BODE regarding both (C statistics 0.691 versus 0.745 and 0.635 versus 0.679, respectively). Relative to using BODE alone, adding pro-adrenomedullin significantly improved 1-year and 2-year mortality prognostication (C statistics 0.750 and 0.818, respectively; both p<0.001). Pro-adrenomedullin plus BOD was more predictive than the original BODE including 6-min walk distance. In multivariable analysis, pro-adrenomedullin (likelihood ratio Chi-squared 13.0, p<0.001), body mass index (8.5, p=0.004) and 6-min walk distance (7.5, p=0.006) independently foretold 2-year survival, but modified Medical Research Council dyspnoea score (2.2, p=0.14) and forced expiratory volume in 1 s % predicted (0.3, p=0.60) did not. Pro-adrenomedullin plus BODE better predicts mortality in COPD patients than does BODE alone; pro-adrenomedullin may substitute for 6-min walk distance in BODE when 6-min walk testing is unavailable.

Predicting the need for mechanical ventilation and mortality in hospitalized COVID-19 patients who received heparin.

Although several studies have utilized AI (artificial intelligence)-based solutions to enhance the decision making for mechanical ventilation, as well as, for mortality in COVID-19, the extraction of explainable predictors regarding heparin's effect in intensive care and mortality has been left unresolved. In the present study, we developed an explainable AI (XAI) workflow to shed light into predictors for admission in the intensive care unit (ICU), as well as, for mortality across those hospitalized COVID-19 patients who received heparin. AI empowered classifiers, such as, the hybrid Extreme gradient boosting (HXGBoost) with customized loss functions were trained on time-series curated clinical data to develop robust AI models. Shapley additive explanation analysis (SHAP) was conducted to determine the positive or negative impact of the predictors in the model's output. The HXGBoost predicted the risk for intensive care and mortality with 0.84 and 0.85 accuracy, respectively. SHAP analysis indicated that the low percentage of lymphocytes at day 7 along with increased FiO2 at days 1 and 5, low SatO2 at days 3 and 7 increase the probability for mortality and highlight the positive effect of heparin administration at the early days of hospitalization for reducing mortality.

ICU admission and mortality classifiers for COVID-19 patients based on subgroups of dynamically associated profiles across multiple timepoints.

The coronavirus disease 2019 (COVID-19) which is caused by severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) is consistently causing profound wounds in the global healthcare system due to its increased transmissibility. Currently, there is an urgent unmet need to identify the underlying dynamic associations among COVID-19 patients and distinguish patient subgroups with common clinical profiles towards the development of robust classifiers for ICU admission and mortality. To address this need, we propose a four step pipeline which: (i) enhances the quality of multiple timeseries clinical data through an automated data curation workflow, (ii) deploys Dynamic Bayesian Networks (DBNs) for the detection of features with increased connectivity based on dynamic association analysis across multiple points, (iii) utilizes Self Organizing Maps (SOMs) and trajectory analysis for the early identification of COVID-19 patients with common clinical profiles, and (iv) trains robust multiple additive regression trees (MART) for ICU admission and mortality classification based on the extracted homogeneous clusters, to identify risk factors and biomarkers for disease progression. The contribution of the extracted clusters and the dynamically associated clinical data improved the classification performance for ICU admission to sensitivity 0.83 and specificity 0.83, and for mortality to sensitivity 0.74 and specificity 0.76. Additional information was included to enhance the performance of the classifiers yielding an increase by 4% in sensitivity and specificity for mortality. According to the risk factor analysis, the number of lymphocytes, SatO2, PO2/FiO2, and O2 supply type were highlighted as risk factors for ICU admission and the percentage of neutrophils and lymphocytes, PO2/FiO2, LDH, and ALP for mortality, among others. To our knowledge, this is the first study that combines dynamic modeling with clustering analysis to identify homogeneous groups of COVID-19 patients towards the development of robust classifiers for ICU admission and mortality.

Stability of the Blood Eosinophilic Phenotype in Stable and Exacerbated COPD.

BACKGROUND: There is controversy regarding the use of blood eosinophil levels as a biomarker of exacerbation risk and responsiveness of patients to inhaled corticosteroids (ICS). METHODS: Patients in stable COPD with Gold Initiative for Chronic Obstructive Lung Disease airflow obstruction grades II to IV were enrolled in an observational multicenter trial. Concordance was defined as blood eosinophil values persistently lower than or persistently higher than the absolute cutoff points of 150 cells/µL and 300 cells/µL, or the percentage cutoff points of 2%, 3%, and 4%. Discordance was obtained when the blood eosinophil values varied between any two visits. ICS treatment data were recorded at one time point at the inclusion of the study. RESULTS: A total of 210 patients with 2,059 visits were included in the study. Seventy percent of the patients were male, and 36% were current smokers; their average age was 67.7 ± 9.4 years, and 81% were receiving ICS at the start of the study. Assessing eosinophil levels over time (median, 7 days [4; 12]), irrespective of exacerbation or hospitalization, there was a discordance of 77%, 60%, and 42% when using the 2%, 3% and 4% cutoffs, respectively. This outcome changed to 34.5%, 24%, and 17.2% discordance when only using two visits for the analysis. The discordance was similar when using absolute eosinophil values. Patients in a stable state had higher discordant values than patients with mild/moderate exacerbations. The same was seen in patients hospitalized for other illnesses compared with patients hospitalized for severe exacerbation of COPD. Discordancy was high regardless of whether patients were taking ICS at the beginning of the study period. CONCLUSIONS: These study data suggest that blood eosinophil levels present significant variability throughout the course of COPD, and a single measurement may therefore not be a reliable predictor of ICS response.

Exertional hypoxemia in stable COPD is common and predicted by circulating proadrenomedullin.

BACKGROUND: The prevalence of exertional hypoxemia in unselected patients with COPD is unknown. Intermittent hypoxia leads to adrenomedullin (ADM) upregulation through the hypoxia-inducible factor-1 pathway. We aimed to assess the prevalence and the annual probability to develop exertional hypoxemia in stable COPD. We also hypothesized that increased ADM might be associated with exertional hypoxemia and envisioned that adding ADM to clinical variables might improve its prediction in COPD. METHODS: A total of 1,233 6-min walk tests and circulating proadrenomedullin (proADM) levels from 574 patients with clinically stable, moderate to very severe COPD enrolled in a multinational cohort study and followed up for 2 years were concomitantly analyzed. RESULTS: The prevalence of exertional hypoxemia was 29.1%. In a matrix derived from a fitted-multistate model, the annual probability to develop exertional hypoxemia was 21.6%. Exertional hypoxemia was associated with greater deterioration of specific domains of health-related quality of life, higher severe exacerbation, and death annual rates. In the logistic linear and conditional Cox regression multivariable analyses, both FEV1% predicted and proADM proved independent predictors of exertional hypoxemia (P < .001 for both). Adjustment for comorbidities, including cardiovascular disorders, and exacerbation rate did not influence results. Relative to using FEV1% predicted alone, adding proADM resulted in a significant improvement of the predictive properties (P = .018). Based on the suggested nonlinear nomogram, patients with moderate COPD (FEV1% predicted = 50%) but high proADM levels (> 2 nmol/L) presented increased risk (> 30%) for exertional desaturation. CONCLUSIONS: Exertional desaturation is common and associated with poorer clinical outcomes in COPD. ADM improves prediction of exertional desaturation as compared with the use of FEV1% predicted alone. TRIAL REGISTRY: ISRCTN Register; No.: ISRCTN99586989; URL: www.controlled-trials.com.