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Rationale and objective Patients with chronic obstructive pulmonary disease (COPD), usually diagnosed after the 6th decade, frequently suffer from comorbidities. Whether COPD patients 50 years or younger (Young COPD) have similar comorbidities with the same frequency and mortality impact as aged-matched controls or older COPD patients is unknown. Methods We compared comorbidity number, prevalence and type in 3 groups of individuals with ≥ 10 pack-years of smoking: A Young ( ≤  50 years) COPD group (n = 160), an age-balanced control group without airflow obstruction (n = 125), and Old (> 50 years) COPD group (n = 1860). We also compared survival between the young COPD and control subjects. Using Cox proportional model, we determined the comorbidities associated with mortality risk and generated Comorbidomes for the “Young” and “Old” COPD groups. Results The severity distribution by GOLD spirometric stages and BODE quartiles were similar between Young and Old COPD groups. After adjusting for age, sex, and pack-years, the prevalence of subjects with at least one comorbidity was 31% for controls, 77% for the Young, and 86% for older COPD patients. Compared to controls, “Young” COPDs’ had a nine-fold increased mortality risk (p < 0.0001). “Comorbidomes” differed between Young and Old COPD groups, with tuberculosis, substance use, and bipolar disorders being distinct comorbidities associated with increased mortality risk in the Young COPD group. Conclusions Young COPD patients carry a higher comorbidity prevalence and mortality risk compared to non-obstructed control subjects. Young COPD differed from older COPD patients by the behavioral-related comorbidities that increase their risk of premature death.

Background Chronic Obstructive Pulmonary Disease (COPD) may be associated with accelerated aging. Telomere shortening is a biomarker of aging. Cross-sectional studies describe shorter telomeres in COPD compared with matched controls. No studies have described telomere length trajectory and its relationship with COPD progression. We investigated telomere shortening over time and its relationship to clinical and lung function parameters in a COPD cohort and smoker controls without COPD. Methods At baseline leukocyte telomere length was measured by qPCR in 121 smokers with COPD and 121 without COPD matched by age (T/S 0 ). The measurements were repeated in 70 of those patients with COPD and 73 non-COPD smokers after 3 years of follow up (T/S 3 ). Results At initial measurement, telomeres were shorter in COPD patients when compared to smoker controls (T/S = 0.68 ± 0.25 vs. 0.88 ± 0.52, p  = 0.003) independent from age and sex. During the follow-up period, we observed an accelerated telomere shortening in individuals with COPD in contrast to smoker controls (T/S 0  = 0.66 ± 0.21 vs. T/S 3  = 0.46 ± 0.16, p  < 0.001, for the patients with COPD and T/S 0  = 0.83 ± 0.56 vs. T/S 3  = 0.74 ± 0.52, p  = 0.023 for controls; GLIM, p  = 0.001). This shortening was inversely related to the baseline telomere length ( r  = −0.49, p  < 0.001). No significant relationship was found between the rate of change in telomere length and change in lung function in the patients with COPD ( p  > 0.05). Conclusions Compared with smokers, patients with COPD have accelerated telomere shortening and this rate of attrition depends on baseline telomere length. Furthermore, the telomere length and its rate of shortening did not relate to clinical and lung function parameters changes over 3 years of follow-up.

The Global Initiative for Chronic Obstructive Lung Disease (GOLD) document has modified the grading system directing pharmacotherapy, but how this relates to the previous one from 2015 and to comorbidities, hospitalizations, and mortality risk is unknown. The aim of this study was to evaluate the changes in the GOLD groups from 2015 to 2017 and to assess the impact on severity, comorbidities, and mortality within each group. We prospectively enrolled and followed, for a mean of 5 years, 819 patients with chronic obstructive pulmonary disease (84% male) in clinics in Spain and the United States. We determined anthropometrics, lung function (FEV %), dyspnea score (modified Medical Research Council scale), ambulatory and hospital exacerbations, and the body mass index, obstruction, dyspnea, and exercise capacity (BODE) and Charlson indexes. We classified patients by the 2015 and 2017 GOLD ABCD system, and compared the differential realignment of the same patients. We related the effect of the reclassification in BODE and Charlson distribution as well as chronic obstructive pulmonary disease and all-cause mortality between the two classifications. Compared with 2015, the 2017 grading decreased by half the proportion of patients in groups C and D (20.5% vs. 11.2% and 24.6% vs. 12.9%; P < 0.001). The distribution of Charlson also changed, whereas group D was higher than B in 2015, they become similar in the 2017 system. In 2017, the BODE index and risk of death were higher in B and D than in A and C. The mortality risk was better predicted by the 2015 than the 2017 system. Compared with 2015, the GOLD ABCD 2017 classification significantly shifts patients from grades C and D to categories A and B. The new grading system equalizes the Charlson comorbidity score in all groups and minimizes the differences in BODE between groups B and D, making the risk of death similar between them.

Background Control in COPD is a dynamic concept that can reflect changes in patients’ clinical status that may have prognostic implications, but there is no information about changes in control status and its long-term consequences. Methods We classified 798 patients with COPD from the CHAIN cohort as controlled/uncontrolled at baseline and over 5 years. We describe the changes in control status in patients over long-term follow-up and analyze the factors that were associated with longitudinal control patterns and related survival using the Cox hazard analysis. Results 134 patients (16.8%) were considered persistently controlled, 248 (31.1%) persistently uncontrolled and 416 (52.1%) changed control status during follow-up. The variables significantly associated with persistent control were not requiring triple therapy at baseline and having a better quality of life. Annual changes in outcomes (health status, psychological status, airflow limitation) did not differ in patients, regardless of clinical control status. All-cause mortality was lower in persistently controlled patients (5.5% versus 19.1%, p = 0.001). The hazard ratio for all-cause mortality was 2.274 (95% CI 1.394–3.708; p = 0.001). Regarding pharmacological treatment, triple inhaled therapy was the most common option in persistently uncontrolled patients (72.2%). Patients with persistent disease control more frequently used bronchodilators for monotherapy (53%) at recruitment, although by the end of the follow-up period, 20% had scaled up their treatment, with triple therapy being the most frequent therapeutic pattern. Conclusions The evaluation of COPD control status provides relevant prognostic information on survival. There is important variability in clinical control status and only a small proportion of the patients had persistently good control. Changes in the treatment pattern may be relevant in the longitudinal pattern of COPD clinical control. Further studies in other populations should validate our results. Trial registration: Clinical Trials.gov: identifier NCT01122758.

The analysis of blood metabolites may help identify individuals at risk of having COPD and offer insights into its underlying pathophysiology. This study aimed to identify COPD-related metabolic alterations and generate a biological signature potentially useful for screening purposes. Plasma metabolomic profiles from 91 COPD patients and 91 controls were obtained using complementary semi-targeted and untargeted LC-MS approaches. Univariate analysis identified metabolites with significant differences between groups, and enrichment analysis highlighted the most affected metabolic pathways. Multivariate analysis, including ROC curve assessment and machine learning algorithms, was applied to assess the discriminatory capacity of selected metabolites. After adjustment for major potential confounders, 56 metabolites showed significant differences between COPD patients and controls. The enrichment analysis revealed that COPD-associated metabolic alterations primarily involved lipid metabolism (especially fatty acids and acylcarnitines), followed by amino acid pathways and xenobiotics. A panel of 10 metabolites, mostly related to lipid metabolism, demonstrated high discriminatory performance for COPD (ROC-AUC: 0.916; 90.1% sensitivity and 89% specificity). These findings may contribute to improving screening strategies and a better understanding of COPD-related metabolic changes. However, our findings remain exploratory and should be interpreted with caution, needing further validation and mechanistic studies.

Background Blood eosinophils are considered a biomarker for the treatment of chronic obstructive pulmonary disease (COPD). Population-based studies are needed to better understand the determinants of the blood eosinophil count (BEC) in individuals with and without COPD. Methods EPISCAN II is a multicentre, cross-sectional, population-based epidemiological study aimed at investigating the prevalence and determinants of COPD in Spain. Study subjects were randomly selected from the general population, and COPD was defined by a post-bronchodilator FEV 1 /FVC < 0.7. For the pre-specified outcomes related to BEC, the first 35 COPD and 35 non-COPD subjects were consecutively recruited in 12 of the participating centres with the objective of analysing 400 individuals in each group. Baseline BEC and its association with demographic, clinical and functional variables were analysed. Results A total of 326 COPD and 399 non-COPD subjects were included in the analysis. The mean age (standard deviation [SD]) was 63.2 years (11.0), 46.3% were male, and 27.6% were active smokers. BEC was significantly higher in individuals with COPD [192 cells/μL (SD: 125) vs. 160 cells/μL (SD: 114); p = 0.0003]. In a stepwise multivariate model, being male, active smoker and having a previous diagnosis of asthma were independently associated with having a higher BEC. Conclusions This population-based study estimated the distribution of eosinophils in the healthy adult population and concluded that COPD patients have a significantly higher BEC. Male sex, active smoking and concomitant asthma were significantly associated with a higher BEC.

Although the primary physiological abnormality in chronic obstructive pulmonary disease (COPD) is airway obstruction, extrapulmonary manifestations of COPD also contribute to the risk of death. The authors of this study devised a novel index based on body-mass index, the forced expiratory volume in one second, the distance walked in six minutes, and the patient's perceived level of dyspnea. Body-mass index, forced expiratory volume, distance walked, and level of dyspnea can predict the risk of death. Chronic obstructive pulmonary disease (COPD), a common disease characterized by a poorly reversible limitation in airflow, 1 is predicted to be the third most frequent cause of death in the world by 2020. 2 The risk of death in patients with COPD is often graded with the use of a single physiological variable, the forced expiratory volume in one second (FEV 1 ). 1 , 3 , 4 However, other risk factors, such as the presence of hypoxemia or hypercapnia, 5 , 6 a short distance walked in a fixed time, 7 a high degree of functional breathlessness, 8 and a low body-mass index (the weight in kilograms divided . . .

Background Plasma metabolomics profile (PMP) in COPD has been associated with clinical characteristics, but PMP’s relationship to survival has not been reported. We determined PMP differences between patients with COPD who died an average of 2 years after enrollment (Non-survivors, NS) compared to those who survived (S) and also with age matched controls (C). Methods We studied prospectively 90 patients with severe COPD and 30 controls. NS were divided in discovery and validation cohorts (30 patients each) and the results compared to the PMP of 30 S and C. All participants completed lung function tests, dyspnea scores, quality of life, exercise capacity, BODE index, and plasma metabolomics by liquid and gas chromatography / mass spectometry (LC/MS, LC/MS 2 , GC/MS). Statistically, we used Random Forest Analysis (RFA) and Support Vector Machine (SVM) to determine metabolites that differentiated the 3 groups and compared the ability of metabolites vs. clinical characteristics to classify patients into survivors and non-survivors. Results There were 79 metabolites statistically different between S and NS [ p  < 0.05 and false discovery rate (q value) < 0.1]. RFA and SVM classification of COPD survivors and non-survivors had a predicted accuracy of 74 and 85% respectively. Elevation of tricyclic acid cycle intermediates branched amino acids depletion and increase in lactate, fructose and xylonate showed the most relevant differences between S vs. NS suggesting alteration in mitochondrial oxidative energy generation. PMP had similar predictive power for risk of death as information provided by clinical characteristics. Conclusions A plasma metabolomic profile characterized by an oxidative energy production difference between survivors and non-survivors was observed in COPD patients 2 years before death.

Mitokines (Humanin (HN), GDF15 and FGF21) are produced as a result of mitochondrial dysfunction and may have major roles in chronic inflammation, malnutrition and exercise capacity in people with COPD. Except for GDF15, studies on this subject are lacking. A total of 165 patients with stable COPD and 49 smokers without COPD were enrolled. We assessed their serum mitokine levels and clinical characteristics at baseline. We recorded moderate and severe exacerbation for the next 12 months. Baseline serum HN (p = 0.037) and GDF-15 (p = 0.013) levels were higher in the COPD group. High HN levels were independently associated with a high risk of exacerbation (HRE) (OR 2.798, 95% CI 1.266–6.187, p = 0.011), malnutrition (OR 6.645, 95% CI 1.859–23.749, p = 0.004), and 6MWD (OR 0.995, 95% CI 0.991–0.999, p = 0.008), and future moderate (HR 1.826, 95% CI 1.181–2.822, p = 0.007) and severe exacerbations (HR 3.445, 95% CI 1.357–8.740, p = 0.009). High GDF15 levels were associated with HRE (OR 3.028, 95% CI 1.134–8.083, p = 0.027), 6MWD (OR 0.995, 95% CI 0.990–0.999, p = 0.017) and predicted desaturation in 6MWT (OR 3.999, 95% CI 1.487–10.757, p = 0.006). High FGF21 levels were associated with HRE (OR 2.144, 95% CI 1.000–4.600, p = 0.05), and predicted future severe exacerbation (HR 4.217, 95% CI 1.459–12.193, p = 0.008). The mitokine levels were higher in patients with COPD than smokers without COPD, and were associated with important clinical outcomes such as exercise capacity and COPD exacerbation. Among the mitokines, HN showed the strongest association with COPD and may serve as a future risk biomarker in this disease. Trial registation NCT04449419.

Background The Global Obstructive Lung Disease (GOLD) 2011 revision recommends the multidimensional assessment of COPD including comorbidities and has developed a disease categories system (ABCD) attempting to implement this strategy. The added value provided by quantifying comorbidities and integrating them to multidimensional indices has not been explored. Objective Compare the prognostic value of the GOLD ABCD categories versus the BMI, Obstruction, Dyspnea, Exercise (BODE) index, and explore the added prognostic value of comorbidities evaluation to this multidimensional assessment. Methods From the patients who have been enrolled in the BODE study, we selected the most recent ones who had the available information needed to classify them by the ABCD GOLD categories. Cox proportional hazards ratios for all-cause mortality were performed for GOLD categories and BODE index. The added value of the comorbidity Copd cO-morbidity TEst (COTE) index was also explored using receiver operating curves (ROC) values. Results 707 patients were followed for 50±30 months including all degrees of airway limitation and BODE index severity. ABCD GOLD predicted global mortality (HR: 1.47; 95% CI 1.28 to 1.70) as did the BODE index (HR: 2.02; 95% CI 1.76 to 2.31). Area under the curve (AUC) of ROC for ABCD GOLD was 0.68; (95% CI 0.64 to 0.73) while for the BODE index was 0.71 (95% CI 0.67 to 0.76). The C statistics value was significantly higher for the observed difference. Adding the COTE index to the BODE index improved its AUC to 0.81 (95% CI 0.77 to 0.85), (χ2=40.28, p<0.001). Conclusions In this population of COPD patients, the BODE index had a better survival prediction than the ABCD GOLD categories. Adding the COTE to the BODE index was complimentary and significantly improved outcome prediction.