Chronic Obstructive Pulmonary Disease Participants Research Articles

Exhaled breath analysis for the discrimination of asthma and chronic obstructive pulmonary disease

Chronic obstructive pulmonary disease (COPD) and asthma are the most common chronic respiratory diseases. In middle-aged and elderly patients, it is difficult to distinguish between COPD and asthma based on clinical symptoms and pulmonary function examinations in clinical practice. Thus, an accurate and reliable inspection method is required. In this study, we aimed to identify breath biomarkers and evaluate the accuracy of breathomics-based methods for discriminating between COPD and asthma. In this multi-center cross-sectional study, exhaled breath samples were collected from 89 patients with COPD and 73 with asthma and detected on a high-pressure photon ionization time-of-flight mass spectrometry (HPPI-TOFMS) platform from 20 October 2022, to 20 May 2023, in four hospitals. Data analysis was performed from 15 June 2023 to 16 August 2023. The sensitivity, specificity, and accuracy were calculated to assess the overall performance of the volatile organic component (VOC)-based COPD and asthma discrimination models. Potential VOC markers related to COPD and asthma were also analyzed. The age of all participants ranged from to 18–86 years, and 54 (33.3%) were men. The age [median (minimum, maximum)] of COPD and asthma participants were 66.0 (46.0, 86.0), and 44.0 (17.0, 80.0). The male and female ratio of COPD and asthma participants were 14/75 and 40/33, respectively. Based on breathomics feature selection, ten VOCs were identified as COPD and asthma discrimination biomarkers via breath testing. The joint panel of these ten VOCs achieved an area under the curve of 0.843, sensitivity of 75.9%, specificity of 87.5%, and accuracy of 80.0% in COPD and asthma discrimination. Furthermore, the VOCs detected in the breath samples were closely related to the clinical characteristics of COPD and asthma. The VOC-based COPD and asthma discrimination model showed good accuracy, providing a new strategy for clinical diagnosis. Breathomics-based methods may play an important role in the diagnosis of COPD and asthma.

Comparison of Feature Selection Methods—Modelling COPD Outcomes

Selecting features associated with patient-centered outcomes is of major relevance yet the importance given depends on the method. We aimed to compare stepwise selection, least absolute shrinkage and selection operator, random forest, Boruta, extreme gradient boosting and generalized maximum entropy estimation and suggest an aggregated evaluation. We also aimed to describe outcomes in people with chronic obstructive pulmonary disease (COPD). Data from 42 patients were collected at baseline and at 5 months. Acute exacerbations were the aggregated most important feature in predicting the difference in the handgrip muscle strength (dHMS) and the COVID-19 lockdown group had an increased dHMS of 3.08 kg (CI95 ≈ [0.04, 6.11]). Pack-years achieved the highest importance in predicting the difference in the one-minute sit-to-stand test and no clinical change during lockdown was detected. Charlson comorbidity index was the most important feature in predicting the difference in the COPD assessment test (dCAT) and participants with severe values are expected to have a decreased dCAT of 6.51 points (CI95 ≈ [2.52, 10.50]). Feature selection methods yield inconsistent results, particularly extreme gradient boosting and random forest with the remaining. Models with features ordered by median importance had a meaningful clinical interpretation. Lockdown seem to have had a negative impact in the upper-limb muscle strength.

Cardiovascular disease in Alpha 1 antitrypsin deficiency: an observational study assessing the role of neutrophil proteinase activity and the suitability of validated screening tools

BackgroundAlpha 1 Antitrypsin Deficiency (AATD) is a rare, inherited lung disease which shares features with Chronic Obstructive Pulmonary Disease (COPD) but has a greater burden of proteinase related tissue damage. These proteinases are associated with cardiovascular disease (CVD) in the general population. It is unclear whether patients with AATD have a greater risk of CVD compared to usual COPD, how best to screen for this, and whether neutrophil proteinases are implicated in AATD-associated CVD. This study had three aims. To compare CVD risk in never-augmented AATD patients to non-AATD COPD and healthy controls (HC). To assess relationships between CVD risk and lung physiology. To determine if neutrophil proteinase activity was associated with CVD risk in AATD. Cardiovascular risk was assessed by QRISK2® score and aortic stiffness measurements using carotid-femoral (aortic) pulse wave velocity (aPWV). Medical history, computed tomography scans and post-bronchodilator lung function parameters were reviewed. Systemic proteinase 3 activity was measured. Patients were followed for 4 years, to assess CVD development.Results228 patients with AATD, 50 with non-AATD COPD and 51 healthy controls were recruited. In all COPD and HC participants, QRISK2® and aPWV gave concordant results (with both measures either high or in the normal range). This was not the case in AATD. Once aPWV was adjusted for age and smoking history, aPWV was highest and QRISK2® lowest in AATD patients compared to the COPD or HC participants. Higher aPWV was associated with impairments in lung physiology, the presence of emphysema on CT scan and proteinase 3 activity following adjustment for age, smoking status and traditional CVD risk factors (using QRISK2® scores) in AATD. There were no such relationships with QRISK2® in AATD. AATD patients with confirmed CVD at four-year follow up had a higher aPWV but not QRISK2® at baseline assessment.ConclusionaPWV measured CVD risk is elevated in AATD. This risk is not captured by QRISK2®. There is a relationship between aPWV, lung disease and proteinase-3 activity. Proteinase-driven breakdown of elastin fibres in large arteries and lungs is a putative mechanism and forms a potential therapeutic target for CVD in AATD.

From illness management to quality of life: rethinking consumer health informatics opportunities for progressive, potentially fatal illnesses.

Investigate how people with chronic obstructive pulmonary disease (COPD)-an example of a progressive, potentially fatal illness-are using digital technologies (DTs) to address illness experiences, outcomes and social connectedness. A transformative mixed methods study was conducted in Canada with people with COPD (n = 77) or with a progressive lung condition (n = 6). Stage-1 interviews (n = 7) informed the stage-2 survey. Survey responses (n = 80) facilitated the identification of participants for stage-3 interviews (n = 13). The interviews were thematically analyzed. Descriptive statistics were calculated for the survey. The integrative mixed method analysis involved mixing between and across the stages. Most COPD participants (87.0%) used DTs. However, few participants frequently used DTs to self-manage COPD. People used DTs to seek online information about COPD symptoms and treatments, but lacked tailored information about illness progression. Few expressed interest in using DTs for self- monitoring and tracking. The regular use of DTs for intergenerational connections may facilitate leaving a legacy and passing on traditions and memories. Use of DTs for leisure activities provided opportunities for connecting socially and for respite, reminiscing, distraction and spontaneity. We advocate reconceptualizing consumer health technologies to prioritize quality of life for people with a progressive, potentially fatal illness. "Quality of life informatics" should focus on reducing stigma regarding illness and disability and taboo towards death, improving access to palliative care resources and encouraging experiences to support social, emotional and mental health. For DTs to support people with fatal, progressive illnesses, we must expand informatics strategies to quality of life.

A Serological Neoepitope Biomarker of Neutrophil Elastase-Degraded Calprotectin, Associated with Neutrophil Activity, Identifies Idiopathic Pulmonary Fibrosis and Chronic Obstructive Pulmonary Disease More Effectively Than Total Calprotectin.

Neutrophil activation can release neutrophil extracellular traps (NETs) in acute inflammation. NETs result in the release of human neutrophil elastase (HNE) and calprotectin, where the former can degrade the latter and generate protein fragments associated with neutrophil activity. We investigated this in chronic obstructive pulmonary disease (COPD) and idiopathic pulmonary fibrosis (IPF) using the novel neoepitope biomarker CPa9-HNE, quantifying a specific HNE-mediated fragment of calprotectin in serum. CPa9-HNE was compared to total calprotectin. Initially, CPa9-HNE was measured in healthy (n = 39), COPD (n = 67), and IPF (n = 16) serum using a neoepitope-specific competitive enzyme-linked immunosorbent assay. Then, a head-to-head comparison of CPa9-HNE and total calprotectin, a non-neoepitope, was conducted in healthy (n = 19), COPD (n = 25), and IPF (n = 19) participants. CPa9-HNE levels were significantly increased in COPD (p < 0.0001) and IPF subjects (p = 0.0001) when compared to healthy participants. Additionally, CPa9-HNE distinguished IPF (p < 0.0001) and COPD (p < 0.0001) from healthy participants more effectively than total calprotectin for IPF (p = 0.0051) and COPD (p = 0.0069). Here, CPa9-HNE also distinguished IPF from COPD (p = 0.045) participants, which was not observed for total calprotectin (p = 0.98). Neutrophil activity was significantly higher, as assessed via serum CPa9-HNE, for COPD and IPF compared to healthy participants. Additionally, CPa9-HNE exceeded the ability of non-neoepitope calprotectin serum measurements to separate healthy from lung disease and even COPD from IPF participants, indicating that neutrophil activity is essential for both COPD and IPF.

Optimizing inhaled corticosteroid use in patients with chronic obstructive pulmonary disease: assessing blood eosinophils, neutrophil-to-lymphocyte ratio, and mortality outcomes in US adults.

Accurate biomarkers for evaluating mortality rates in patients with chronic obstructive pulmonary disease (COPD) remain scarce. This study aimed to explore the relationships between mortality rates in patients with COPD and blood eosinophil counts, neutrophil counts, and lymphocyte counts, along with the neutrophil-to-lymphocyte ratio (NLR). Additionally, we sought to identify the optimal response values for these biomarkers when utilizing inhaled corticosteroids (ICS). Utilizing a nationally representative, multistage cross-sectional design and mortality correlation study, we analyzed data from the National Health and Nutrition Examination Survey (NHANES) 1999-2018 involving US adults aged 40 years or older with COPD. The primary endpoint was all-cause mortality, with Kaplan-Meier survival curves and restricted cubic splines applied to illustrate the relationship between leukocyte-based inflammatory markers and mortality. The analysis was conducted in 2023. Our analysis included 1,715 COPD participants, representing 6,976,232 non-institutionalized US residents [weighted mean age (SE), 62.09 (0.28) years; range, 40-85 years]. Among the participants, men constituted 50.8% of the population, and the weighted mean follow-up duration was 84.9 months. In the ICS use group, the weighted proportion of participants over 70 years old was significantly higher compared with the non-ICS use group (31.39% vs 25.52%, p < 0.0001). The adjusted hazard ratios for all-cause mortality related to neutrophil counts, lymphocyte counts, and NLR were 1.10 [95% confidence interval (CI), 1.04-1.16, p < 0.001], 0.83 (95% CI, 0.71-0.98; p = 0.03), and 1.10 (95% CI, 1.05-1.15; p < 0.0001), respectively. Optimal ICS response was linked with higher levels of eosinophil count (≥240 cells/μL), neutrophil count (≥3,800 cells/μL), NLR (≥4.79), and lower levels of lymphocyte count (<2,400 cells/μL). Adjusted baseline neutrophil, lymphocyte counts, and NLR serve as independent risk factors for all-cause mortality in patients with COPD. Further, ICS application appears to mitigate mortality risk, particularly when NLR levels reach 4.79 or higher, underlining the importance of ICS in COPD management.

The altered sputum microbiome profile in patients with moderate and severe COPD exacerbations, compared to the healthy group in the Indian population

Background: Microbial culture-independent sequencing techniques have advanced our understanding of host-microbiome interactions in health and disease. The purpose of this study was to explore the dysbiosis of airway microbiota in patients with moderate or severe chronic obstructive pulmonary disease (COPD) and compare them with healthy controls. Methods: The COPD patients were investigated for disease severity based on airflow limitations and divided into moderate (50%≤FEV1&lt;80% predicted) and severe groups (FEV1&lt;50% predicted). Spontaneous sputum samples were collected and, the V3-V4 regions of the 16S rRNA coding gene were sequenced to examine the microbiome profile of COPD and healthy participants. Results: A total of 45 sputum samples were collected from 17 severe COPD, 12 moderate COPD cases, and 16 healthy volunteers. The bacterial alpha diversity (Shannon and Simpson’s index) significantly decreased in the moderate and severe COPD groups, compared to healthy samples. A significantly higher proportion of Firmicutes and Actinobacteria were present in moderate COPD, and Proteobacteria numbers were comparatively increased in severe COPD. In healthy samples, Bacteroidetes and Fusobacteria were more abundant in comparison to both the COPD groups. Among the most commonly detected 20 bacterial genera, Streptococcus was predominant among the COPD sputum samples, whereas Prevotella was the top genus in healthy controls. Linear discriminant analysis (LDA&gt;2) revealed that marker genera like Streptococcus and Rothia were abundant in moderate COPD. For severe COPD, the genera Pseudomonasand Leptotrichia were most prevalent, whereas Fusobacterium and Prevotella were dominant in the healthy group. Conclusions: Our findings suggest a significant dysbiosis of the respiratory microbiome in COPD patients. The decreased microbial diversity may influence the host immune response and provide microbiological biomarkers for the diagnosis and monitoring of COPD.

The altered sputum microbiome profile in patients with moderate and severe COPD exacerbations, compared to the healthy group in the Indian population.

Background: Microbial culture-independent sequencing techniques have advanced our understanding of host-microbiome interactions in health and disease. The purpose of this study was to explore the dysbiosis of airway microbiota in patients with moderate or severe chronic obstructive pulmonary disease (COPD) and compare them with healthy controls. Methods: The COPD patients were investigated for disease severity based on airflow limitations and divided into moderate (50%≤FEV1<80% predicted) and severe groups (FEV1<50% predicted). Spontaneous sputum samples were collected and, the V3-V4 regions of the 16S rRNA coding gene were sequenced to examine the microbiome profile of COPD and healthy participants. Results: A total of 45 sputum samples were collected from 17 severe COPD, 12 moderate COPD cases, and 16 healthy volunteers. The bacterial alpha diversity (Shannon and Simpson's index) significantly decreased in the moderate and severe COPD groups, compared to healthy samples. A significantly higher proportion of Firmicutes and Actinobacteria were present in moderate COPD, and Proteobacteria numbers were comparatively increased in severe COPD. In healthy samples, Bacteroidetes and Fusobacteria were more abundant in comparison to both the COPD groups. Among the most commonly detected 20 bacterial genera, Streptococcus was predominant among the COPD sputum samples, whereas Prevotella was the top genus in healthy controls. Linear discriminant analysis (LDA>2) revealed that marker genera like Streptococcus and Rothia were abundant in moderate COPD. For severe COPD, the genera Pseudomonasand Leptotrichia were most prevalent, whereas Fusobacterium and Prevotella were dominant in the healthy group. Conclusions: Our findings suggest a significant dysbiosis of the respiratory microbiome in COPD patients. The decreased microbial diversity may influence the host immune response and provide microbiological biomarkers for the diagnosis and monitoring of COPD.

Barriers and Facilitators to Exercise Compliance for Community Elders with COPD: A Cross-Sectional Study.

Exercise compliance was known as important to improve long-term health conditions for Chronic obstructive pulmonary disease (COPD) patients, however, little was known about the determinants which affect their exercise compliance. This study aimed to investigate factors related to exercise compliance of COPD elderly patients. This cross-sectional study included elderly patients with stable COPD participants. Random cluster sampling and a survey, including the Exercise Compliance Scale, mMRC Dyspnea Index Scale, Social Support Scale, Anxiety Self-Assessment Scale, and Self-rating Depression Scale, were used. Data were analyzed using Spearman correlation and backward logistic regression. 124 participants (45.90%) had poor exercise compliance while 146 had good compliance (54.10%). The backward logistic regression showed household monthly income (¥501-¥1500: OR=21.54, P<0.05; ¥3001-¥5000: OR=32.76, P<0.05), two chronic comorbidities (OR=17.13, P<0.05), and the moderate dyspnea (OR=16.87, P<0.05) might help to improve exercise compliance. While female COPD patients (OR=0.11, P<0.01) who had server dyspnea (OR=0.02, P<0.05) and depression (OR=0.84, P<0.05) might have more difficulties adhering to exercise. Low exercise compliance in community-dwelling elderly COPD patients could be affected by sex, monthly income level, number of chronic comorbidities, dyspnea, and depression.

The altered sputum microbiome profile in patients with moderate and severe COPD compared to the healthy group in the Indian population

Background: Microbial culture-independent sequencing techniques have advanced our understanding of host-microbiome interactions in health and disease. The purpose of this study was to explore the dysbiosis of airway microbiota in patients with moderate or severe chronic obstructive pulmonary disease (COPD) and compare them with healthy controls. Methods: The COPD patients were investigated for disease severity based on airflow limitations and divided into moderate (50%≤FEV1&lt;80% predicted) and severe groups (FEV1&lt;50% predicted). Spontaneous sputum samples were collected and, the V3-V4 regions of the 16S rRNA coding gene were sequenced to examine the microbiome profile of COPD and healthy participants. Results: A total of 45 sputum samples were collected from 17 severe COPD, 12 moderate COPD cases, and 16 healthy volunteers. The bacterial alpha diversity (Shannon and Simpson’s index) significantly decreased in the moderate and severe COPD groups, compared to healthy samples. A significantly higher proportion of Firmicutes and Actinobacteria were present in moderate COPD, and Proteobacteria numbers were comparatively increased in severe COPD. In healthy samples, Bacteroidetes and Fusobacteria were more abundant in comparison to both the COPD groups. Among the most commonly detected 20 bacterial genera, Streptococcus was predominant among the COPD sputum samples, whereas Prevotella was the top genus in healthy controls. Linear discriminant analysis (LDA&gt;2) revealed that marker genera like Streptococcus and Rothia were abundant in moderate COPD. For severe COPD, the genera Pseudomonas and Leptotrichia were most prevalent, whereas Fusobacterium and Prevotella were dominant in the healthy group. Conclusions: Our findings suggest a significant dysbiosis of the respiratory microbiome in COPD patients. The decreased microbial diversity may influence the host immune response and provide microbiological biomarkers for the diagnosis and monitoring of COPD.

Physical activity trajectories and their determinants in patients with chronic obstructive pulmonary disease: A cohort study.

The aim was to identify latent trajectories in physical activity (PA) and their determinants in adults with chronic obstructive pulmonary disease (COPD) based on the socio-ecological model. PA has been linked to poor long-term outcomes in patients with COPD. However, few studies have explored their PA trajectories and their predictors. Cohort study. We used data from a national cohort and included 215 participants. PA was quantified using a short PA questionnaire, and group-based trajectory modelling was used to explore the PA trajectories. Multinomial logistic regression was conducted to identify the predictors of PA trajectories. Generalised linear mixed models were used to elucidate the associations between predictors and PA during follow-up. A STROBE checklist was used to guide the reporting of this study. Three PA trajectory patterns were identified among 215 COPD participants with an average age of 60.51 ± 8.87: stable inactive group (66.7%), sharp decline group (25.7%) and stable active group (7.5%). The logistic regression showed that age, sex, income, peak expiratory flow, upper limb capacity, depressive symptoms, the frequency of contact with children were PA predictors. Upper limb capacity weakness and depressive symptoms were found to be associated with a sharp decline in PA during follow-up. This study revealed three PA trajectories among patients with COPD. In addition to strengthening the physical functions and mental health of patients, support from the family, community and society also play a crucial role in promoting PA of patients with COPD. It is essential to identify distinct PA trajectories in patients with COPD to develop future interventions that promote PA. A national cohort study was used and no patients or the public were involved in the design and implementation of this study.

The altered lung microbiome dynamics in patients with moderate and severe COPD compared to the healthy group in the Indian population

Background: Microbial culture-independent sequencing techniques have advanced our understanding of host-microbiome interactions in health and disease. The purpose of this study was to explore the dysbiosis of airway microbiota in patients with moderate or severe chronic obstructive pulmonary disease (COPD) and compare them with healthy controls. Methods: The COPD patients were investigated for disease severity based on airflow limitations and divided into moderate (50%≤FEV1&lt;80% predicted) and severe groups (FEV1&lt;50% predicted). Spontaneous sputum samples were collected and, the V3-V4 regions of the 16S rRNA coding gene were sequenced to examine the microbiome profile of COPD and healthy participants. Results: A total of 45 sputum samples were collected from 17 severe COPD, 12 moderate COPD cases, and 16 healthy volunteers. The bacterial alpha diversity (Shannon and Simpson’s index) significantly decreased in the moderate and severe COPD groups, compared to healthy samples. A significantly higher proportion of Firmicutes and Actinobacteria were present in moderate COPD, and Proteobacteria numbers were comparatively increased in severe COPD. In healthy samples, Bacteroidetes and Fusobacteria were more abundant in comparison to both the COPD groups. Among the most commonly detected 20 bacterial genera, Streptococcus was predominant among the COPD sputum samples, whereas Prevotella was the top genus in healthy controls. Linear discriminant analysis (LDA&gt;2) revealed that marker genera like Streptococcus and Rothia were abundant in moderate COPD. For severe COPD, the genera Pseudomonas and Leptotrichia were most prevalent, whereas Fusobacterium and Prevotella were dominant in the healthy group. Conclusions: Our findings suggest a significant dysbiosis of the respiratory microbiome in COPD patients. The decreased microbial diversity may influence the host immune response and provide microbiological biomarkers for the diagnosis and monitoring of COPD.

Undersampled Diffusion-Weighted 129Xe MRI Morphometry of Airspace Enlargement: Feasibility in Chronic Obstructive Pulmonary Disease

Multi-b diffusion-weighted hyperpolarized gas MRI measures pulmonary airspace enlargement using apparent diffusion coefficients (ADC) and mean linear intercepts (Lm). Rapid single-breath acquisitions may facilitate clinical translation, and, hence, we aimed to develop single-breath three-dimensional multi-b diffusion-weighted 129Xe MRI using k-space undersampling. We evaluated multi-b (0, 12, 20, 30 s/cm2) diffusion-weighted 129Xe ADC/morphometry estimates using a fully sampled and retrospectively undersampled k-space with two acceleration-factors (AF = 2 and 3) in never-smokers and ex-smokers with chronic obstructive pulmonary disease (COPD) or alpha-one anti-trypsin deficiency (AATD). For the three sampling cases, mean ADC/Lm values were not significantly different (all p > 0.5); ADC/Lm values were significantly different for the COPD subgroup (0.08 cm2s-1/580 µm, AF = 3; all p < 0.001) as compared to never-smokers (0.05 cm2s-1/300 µm, AF = 3). For never-smokers, mean differences of 7%/7% and 10%/7% were observed between fully sampled and retrospectively undersampled (AF = 2/AF = 3) ADC and Lm values, respectively. For the COPD subgroup, mean differences of 3%/4% and 11%/10% were observed between fully sampled and retrospectively undersampled (AF = 2/AF = 3) ADC and Lm, respectively. There was no relationship between acceleration factor with ADC or Lm (p = 0.9); voxel-wise ADC/Lm measured using AF = 2 and AF = 3 were significantly and strongly related to fully-sampled values (all p < 0.0001). Multi-b diffusion-weighted 129Xe MRI is feasible using two different acceleration methods to measure pulmonary airspace enlargement using Lm and ADC in COPD participants and never-smokers.

Quantitative CT Lung Imaging and Machine Learning Improves Prediction of Emergency Room Visits and Hospitalizations in COPD.

Predicting increased risk of future healthcare utilization in chronic obstructive pulmonary disease (COPD) patients is an important goal for improving patient management. Our objective was to determine the importance of computed tomography (CT) lung imaging measurements relative to other demographic and clinical measurements for predicting future health services use with machine learning in COPD. In this retrospective study, lung function measurements and chest CT images were acquired from Canadian Cohort of Obstructive Lung Disease study participants from 2010 to 2017 (https://clinicaltrials.gov, NCT00920348). Up to two follow-up visits (1.5- and 3-year follow-up) were performed and participants were asked for details related to healthcare utilization. Healthcare utilization was defined as any COPD hospitalization or emergency room visit due to respiratory problems in the 12 months prior to the follow-up visits. CT analysis was performed (VIDA Diagnostics Inc.); a total of 108 CT quantitative emphysema, airway and vascular measurements were investigated. A hybrid feature selection method with support vector machine classifier was used to predict healthcare utilization. Performance was determined using accuracy, F1-measure and area under the receiver operating characteristic curve (AUC) and Matthews's correlation coefficient (MC). Of the 527 COPD participants evaluated, 179 (35%) used healthcare services at follow-up. There were no significant differences between the participants with or without healthcare utilization at follow-up for age (p=0.50), sex (p=0.44), BMI (p=0.05) or pack-years (p=0.76). The accuracy for predicting subsequent healthcare utilization was 80% ± 3% (F1-measure=74%, AUC=0.80, MC=0.6) when all measurements were considered, 76% ± 6% (F1-measure=72%, AUC=0.77, MC=0.55) for CT measurements alone and 65% ± 5% (F1-measure=60%, AUC=0.67, MC=0.34) for demographic and lung function measurements alone. The combination of CT lung imaging and conventional measurements leads to greater prediction accuracy of subsequent health services use than conventional measurements alone, and may provide needed prognostic information for patients suffering from COPD.

CC16 as an Inflammatory Biomarker in Induced Sputum Reflects Chronic Obstructive Pulmonary Disease (COPD) Severity.

The progression of an abnormal inflammatory response plays a crucial role in the lung function decline of chronic obstructive pulmonary disease (COPD) patients. Compared to serum biomarkers, inflammatory biomarkers in induced sputum would be a more reliable reflection of inflammatory processes in the airways. A total of 102 COPD participants were divided into a mild-to-moderate group (FEV1%pred≥ 50%, n=57) and a severe-to-very-severe group (FEV1%pred<50%, n=45). We measured a series of inflammatory biomarkers in induced sputum and analyzed their association with lung function and SGRQ in COPD patients. To evaluate the relationship between inflammatory biomarkers and the inflammatory phenotype, we also analyzed the correlation between biomarkers and airway eosinophilic phenotype. We found increased mRNA levels of MMP9, LTB4R, and A1AR and decreased levels of CC16 mRNA in induced sputum in the severe-to-very-severe group. After adjustment for age, sex and other biomarkers, CC16 mRNA expression was positively associated with FEV1%pred (r=0.516, p=0.004) and negatively correlated with SGRQ scores (r=-0.3538, p=0.043). As previously known, decreased CC16 was related to the migration and aggregation of eosinophils in airway. It was also found that CC16 had a moderate negative correlation with the eosinophilic inflammation in airway (r=-0.363, p=0.045) in our COPD patients. Low CC16 mRNA expression levels in induced sputum were associated with low FEV1%pred and a high SGRQ score in COPD patients. Sputum CC16 as a potential biomarker for predicting COPD severity in clinical practice might attribute to the involvement of CC16 in airway eosinophilic inflammation.

A computational musculoskeletal arm model for assessing muscle dysfunction in chronic obstructive pulmonary disease.

Computational models have been used extensively to assess diseases and disabilities effects on musculoskeletal system dysfunction. In the current study, we developed a two degree-of-freedom subject-specific second-order task-specific arm model for characterizing upper-extremity function (UEF) to assess muscle dysfunction due to chronic obstructive pulmonary disease (COPD). Older adults (65years or older) with and without COPD and healthy young control participants (18 to 30years) were recruited. First, we evaluated the musculoskeletal arm model using electromyography (EMG) data. Second, we compared the computational musculoskeletal arm model parameters along with EMG-based time lag and kinematics parameters (such as elbow angular velocity) between participants. The developed model showed strong cross-correlation with EMG data for biceps (0.905, 0.915) and moderate cross-correlation for triceps (0.717, 0.672) within both fast and normal pace tasks among older adults with COPD. We also showed that parameters obtained from the musculoskeletal model were significantly different between COPD and healthy participants. On average, higher effect sizes were achieved for parameters obtained from the musculoskeletal model, especially for co-contraction measures (effect size = 1.650 ± 0.606, p < 0.001), which was the only parameter that showed significant differences between all pairwise comparisons across the three groups. These findings suggest that studying the muscle performance and co-contraction, may provide better information regarding neuromuscular deficiencies compared to kinematics data. The presented model has potential for assessing functional capacity and studying longitudinal outcomes in COPD.

Associations of adherence to the DASH diet and the Mediterranean diet with chronic obstructive pulmonary disease among US adults.

The Dietary Approaches to Stop Hypertension (DASH) and the Mediterranean diet are associated with reduced cardiovascular, tumor, and diabetes risk, but the effect on chronic obstructive pulmonary disease (COPD) is uncertain. To investigate the association of the DASH diet and the Mediterranean diet with the risk of COPD in American adults. This cross-sectional study included 28,605 participants from the National Health and Nutrition Examination Survey (NHANES) 1999-2018 survey cycle who had complete dietary and other questionnaire data. The scores of healthy eating patterns (the DASH diet and the Mediterranean diet) were derived from a 24-h dietary recall interview [individual food and total nutrient data from NHANES and food pattern equivalents data from the United States Department of Agriculture (USDA)]. The primary outcome was the prevalence of COPD. COPD was defined based on participants self-reported whether or not a doctor or health professional had diagnosed chronic bronchitis or emphysema. Secondary outcomes were lung function and respiratory symptoms. All analyses were adjusted for demographics and standard COPD risk factors (primary tobacco exposure, secondhand smoke exposure, and asthma). This study included 2,488 COPD participants and 25,607 non-COPD participants. We found that a higher DASH diet score was associated with a lower risk of COPD [odds ratio (OR): 0.83; 95% confidence interval (CI): 0.71-0.97; P = 0.021]. This association persisted in several subgroups [men (OR: 0.73; 95% CI: 0.58-0.93; P = 0.010), relatively young (OR: 0.74; 95% CI: 0.55-1.01; P = 0.050), and smoker (OR: 0.82; 95% CI: 0.67-0.99; P = 0.038)]. In contrast, the Mediterranean diet score was not significantly associated with COPD prevalence in this large cross-sectional analysis representative of the US adult population (OR: 1.03; 95% CI: 0.88-1.20; P = 0.697). In addition, we found a correlation between DASH diet adherence and lung function [β: -0.01; 95% CI: -0.01-0.00; P = 0.003 (FEV1: FVC)] or respiratory symptoms [OR: 0.80; 95% CI: 0.73-0.89; P < 0.001 (dyspnea); OR: 0.80; 95% CI: 0.70-0.91; P = 0.002 (cough); OR: 0.86; 95% CI: 0.74-0.99; P = 0.042 (expectoration)], especially in non-COPD populations. A higher DASH diet score was associated with improved COPD prevalence, lung function and respiratory symptoms. This new finding supports the importance of diet in the pathogenesis of COPD and expands the scope of the association of the DASH diet score with major chronic diseases.

The association between blood manganese and liver stiffness in participants with chronic obstructive pulmonary disease: a cross-sectional study from NHANES 2017–2018

BackgroundTo explore the relationship between blood manganese and liver stiffness in the United States among participants with chronic obstructive pulmonary disease (COPD).MethodsAll data were obtained from the 2017–2018 National Health and Nutrition Examination Survey database (NHANES). A total of 4690 participants were included in the study. All participants included complete information on COPD, liver stiffness, and blood manganese. Liver stiffness (kPa) was measured from “Examination Date” and blood manganese (ug/L) was obtained from “Laboratory Data”. A multiple linear regression model was used to assess the correlation between blood manganese and liver stiffness.ResultsAmong the 4690 participants, blood manganese was lower in the COPD group but liver stiffness was higher (p < 0.05). There was a positive correlation between blood manganese and liver stiffness (β = 0.08, 95% CI 0.03, 0.12). This positive association was more pronounced in COPD participants (β = 0.25, 95% CI 0.08, 0.42) and there was a non-linear relationship, which was more significant when blood manganese exceeded 14.43 ug/L (β = 1.76, 95% CI 1.10, 2.41).ConclusionsThe association between blood manganese and liver stiffness was positive, which was more apparent in COPD patients.

Comparison of Diaphragmatic Stretch and Manual Diaphragmatic Release Technique Along with Chest Proprioceptive Neuromuscular Facilitation in Mild-to-moderate Chronic Obstructive Pulmonary Disease: A Randomized Clinical Trial

Background: Diaphragmatic stretch technique, manual diaphragmatic release technique, and chest proprioceptive neuromuscular facilitation (PNF) have been suggested as an alternative method for the treatment of chronic obstructive pulmonary disease (COPD). Aims: The aim of this study was to compare the effects of diaphragmatic stretch and manual diaphragmatic release technique along with chest PNF on peak expiratory flow rate (PEFR), exercise capacity, dyspnea, chest expansion, and inspiratory pressure in mild-to-moderate COPD participants. Settings and Design: A randomized clinical trial took place on 30 subjects with COPD. Materials and Methods: Subjects were divided into two groups, of which Group A received a diaphragmatic stretch technique with chest PNF and Group B received a manual diaphragmatic release technique with chest PNF. Six-day intervention protocol was given to the participants of both the groups and PEFR, maximum inspiratory pressure, chest expansion, exercise capacity, and dyspnea were assessed before the intervention and after 6 days of intervention. Statistical Analysis: Normality of all continuous data was checked using the Kolmogorov–Smirnov test. Independent t-test was used to analyze the parameters between Group A and Group B. Comparison of difference in pre and post within group was done using independent t-test. Results: Data analyzed in Group A as well as in B, when compared within the group, showed highly significant improvements. When compared between the groups, both the groups showed no difference. Conclusion: The study concluded that there was statistical significance in improvement of PEFR, exercise capacity, dyspnea, chest expansion, and inspiratory pressure within both the groups, but significant changes were not seen between groups. Hence, diaphragmatic stretch and manual release technique along with chest PNF can be used as an alternative/adjunct for the treatment of COPD.

Differential Expression of Serum Proteins in Chronic Obstructive Pulmonary Disease Assessed Using Label-Free Proteomics and Bioinformatics Analyses.

As a common respiratory disease, chronic obstructive pulmonary disease (COPD) has a high morbidity and mortality. Current clinical therapies are not ideal and do not improve lung function or long-term life quality. It is very important to find new potential pathogenic mechanisms, biomarkers, and targets with therapeutic value in COPD. Serum samples collected from acute exacerbation and stable COPD and healthy participants were analyzed using label-free liquid chromatography tandem mass spectrometry to identify the differentially expressed proteins (DEPs) between two groups. Bioinformatics analyses were performed to determine the biological processes associated with those DEPs. Key proteins were validated by enzyme linked immunosorbent assay (ELISA). In total, 661 proteins were detected in serum from patients with COPD and healthy participants. Compared with healthy participants, patients with acute exacerbation of COPD had 45 DEPs, 13 were upregulated and 32 were downregulated; and patients with stable COPD had 79 DEPs, 18 were upregulated and 61 were downregulated. Gene Ontology functional annotation results indicated that the DEPs identified in patients with COPD were associated with the terms cellular anatomical entity, binding, and cellular process. Kyoto Encyclopedia of Genes and Genomes functional annotation analysis and the Clusters of Orthologous Genes database analysis indicated that the functions of these DEPs were primarily in signal transduction mechanisms and amino acid transport and metabolism. The ELISA results for three key proteins of IGFBP2, LRG1 and TAGLN were consistent with the LC-MS/MS results and the area under the receiver operating characteristic of the combined index was 0.893 (95% CI: 0.813, 0.974). Our findings suggested pathogenic mechanisms underlying COPD stages and indicated three key proteins that may warrant further study as potential biomarkers for early diagnosis or prognosis of COPD or as therapeutic targets.