Chronic obstructive pulmonary disease phenotypes: the future of COPD

Stem cell treatment reduces T cell apoptosis in COPD patients with chronic bronchitis but not with emphysema

BACKGROUND

Chronic obstructive pulmonary disease (COPD) is a prevalent and preventable condition. Mesenchymal stem cell (MSC) therapy is being explored to aid in the regeneration of lung cells and airway structure, aiming to restore lung function.

AIM

To examine varied responses of MSCs when cultured with peripheral blood mononuclear cells (PBMCs) from different COPD phenotypes, patients were grouped into ACOS, emphysema, and chronic bronchitis categories.

METHODS

PBMCs from these groups and controls were co-cultured with MSCs derived from dental follicles, revealing differing rates of apoptosis among COPD phenotypes compared to controls.

RESULTS

While the chronic bronchitis group exhibited the least lymphocyte viability (p<0.01), introducing MSCs notably enhanced viability across all phenotypes except emphysema, with the chronic bronchitis group showing the most improvement (p<0.05).

CONCLUSION

Stem cell therapy might reduce peripheral lymphocyte apoptosis in COPD, with varying responses based on phenotype, necessitating further research to understand mechanisms and optimize tailored therapies for each COPD subtype.

COPD is associated with increased cardiovascular disease risk independent of phenotype

BACKGROUND AND OBJECTIVE

Chronic obstructive pulmonary disease (COPD) is a leading cause of death worldwide that frequently presents with concomitant cardiovascular diseases. Despite the pathological distinction between individual COPD phenotypes such as emphysema and chronic bronchitis, there is a lack of knowledge about the impact of COPD phenotype on cardiovascular disease risk. Thus, this study aimed to utilize a nationally representative sample to investigate cardiovascular disease prevalence in patients with COPD with emphysema and chronic bronchitis phenotypes.

METHODS

Data from 31,560 adults including 2504 individuals with COPD, collected as part of the National Health and Nutrition Examination Survey (1999-2018), were examined.

RESULTS

A significantly increased cardiovascular disease risk, including coronary heart disease, heart failure, myocardial infarction and stroke, was identified in patients with COPD among all disease phenotypes. Particularly, compared to those without COPD, individuals with chronic bronchitis presented with 1.76 (95% CI: 1.41-2.20) times greater odds, individuals with emphysema with 2.31 (95% CI: 1.80-2.96) times greater odds, while those with a concurrent phenotype (combined chronic bronchitis and emphysema) exhibited 2.98 (95% CI: 2.11-4.21) times greater odds of reporting cardiovascular diseases.

CONCLUSION

Our data confirms that patients with COPD present an elevated risk of developing cardiovascular disease among all phenotypes, with the most marked increase being in those with concurrent chronic bronchitis and emphysema phenotypes. These findings emphasize the need for awareness and appropriate cardiovascular screening in COPD.

Lung Hyperinflation as Treatable Trait in Chronic Obstructive Pulmonary Disease: A Narrative Review

Lung hyperinflation (LH) is a common clinical feature in patients with chronic obstructive pulmonary disease (COPD). It results from a combination of reduced elastic lung recoil as a consequence of irreversible destruction of lung parenchyma and expiratory airflow limitation. LH is an important determinant of morbidity and mortality in COPD, partially independent of the degree of airflow limitation. Therefore, reducing LH has become a major target in the treatment of COPD over the last decades. Advances were made in the diagnostics of LH and several effective interventions became available. Moreover, there is increasing evidence suggesting that LH is not only an isolated feature in COPD but rather part of a distinct clinical phenotype that may require a more integrated management. This narrative review focuses on the pathophysiology and adverse consequences of LH, the assessment of LH with lung function measurements and imaging techniques and highlights LH as a treatable trait in COPD. Finally, several suggestions regarding future studies in this field are made.

Intermittent Versus Sustained Hypoxemia from Sleep-disordered Breathing: Outcomes in Patients with Chronic Lung Disease and High Altitude

In a variety of physiologic and pathologic states, people may experience both chronic sustained hypoxemia and intermittent hypoxemia ("combined" or "overlap" hypoxemia). In general, hypoxemia in such instances predicts a variety of maladaptive outcomes, including excess cardiovascular disease or mortality. However, hypoxemia may be one of the myriad phenotypic effects in such states, making it difficult to ascertain whether adverse outcomes are primarily driven by hypoxemia, and if so, whether these effects are due to intermittent versus sustained hypoxemia.

Clinical phenotyping of children with nocturnal enuresis: A key classification to improve the approach

INTRODUCTION

The literature shows that nocturnal enuresis is not an isolated phenomenon of urinary loss during sleep, but encompasses a set of systemic clinical manifestations that significantly influence children's quality of life and development. However, the understanding of the clinical and physiological relationship of these systemic manifestations remains a clinical challenge. The recognition of these manifestations and their subsequent categorisation, may provide better insights into integrated clinical manifestations, facilitating the understanding of pathophysiological mechanisms, and promote increased assertiveness in the assessment and the selection of appropriate therapies.

OBJECTIVE

The aim of this study is to develop a phenotyping model for children with nocturnal enuresis based on evidence.

METHODS

This study presents a clinical phenotyping model for children with nocturnal enuresis based on an analytical and methodological review of the literature, about nocturnal enuresis and its associated clinical manifestations. There was a bibliometric analysis carried out to better analyse outcomes. After reading and analysing the literature, the clinical manifestations were categorised into domains and submitted to the validation of an expert committee with extensive experience in their specific area of expertise. A visual representation of the categorised model was developed to make the phenotyping concept easily understandable to all professionals.

RESULTS

The clinical manifestations related to nocturnal enuresis have been categorised according to frequency and relation found in the literature and validation by an expert committee and the development of the phenotyping model for children with nocturnal enuresis was completed.

CONCLUSION

The present study developed an evidence-based phenotyping model for children with nocturnal enuresis.

Informed development of a multi-species biofilm in chronic obstructive pulmonary disease

Recent evidence indicates that microbial biofilm aggregates inhabit the lungs of COPD patients and actively contribute towards chronic colonization and repeat infections. However, there are no contextually relevant complex biofilm models for COPD research. In this study, a meta-analysis of the lung microbiome in COPD was used to inform development of an optimized biofilm model composed of genera highly associated with COPD. Bioinformatic analysis showed that although diversity matrices of COPD microbiomes were similar to healthy controls, and internal compositions made it possible to accurately differentiate between these cohorts (AUC = 0.939). Genera that best defined these patients included Haemophilus, Moraxella and Streptococcus. Many studies fail to account for fungi; therefore, Candida albicans was included in the creation of an interkingdom biofilm model. These organisms formed a biofilm capable of tolerating high concentrations of antimicrobial therapies with no significant reductions in viability. However, combined therapies of antibiotics and an antifungal resulted in significant reductions in viable cells throughout the biofilm (p < 0.05). This biofilm model is representative of the COPD lung microbiome and results from in vitro antimicrobial challenge experiments indicate that targeting both bacteria and fungi in these interkingdom communities will be required for more positive clinical outcomes.

Exploratory Study on COPD Phenotypes and their Progression: Integrating SPECT and qCT Imaging Analysis

Background

The objective of this study is to understand chronic obstructive pulmonary disease (COPD) phenotypes and their progressions by quantifying heterogeneities of lung ventilation from the single photon emission computed tomography (SPECT) images and establishing associations with the quantitative computed tomography (qCT) imaging-based clusters and variables.

Methods

Eight COPD patients completed a longitudinal study of three visits with intervals of about a year. CT scans of these subjects at residual volume, functional residual capacity, and total lung capacity were taken for all visits. The functional and structural qCT-based variables were derived, and the subjects were classified into the qCT-based clusters. In addition, the SPECT variables were derived to quantify the heterogeneity of lung ventilation. The correlations between the key qCT-based variables and SPECT-based variables were examined.

Results

The SPECT-based coefficient of variation (CVTotal), a measure of ventilation heterogeneity, showed strong correlations (|r| ≥ 0.7) with the qCT-based functional small airway disease percentage (fSAD%Total) and emphysematous tissue percentage (Emph%Total) in the total lung on cross-sectional data. As for the two-year changes, the SPECT-based maximum tracer concentration (TCmax), a measure of hot spots, exhibited strong negative correlations with fSAD%Total, Emph%Total, average airway diameter in the left upper lobe, and airflow distribution in the middle and lower lobes.

Conclusion

Small airway disease is highly associated with the heterogeneity of ventilation in COPD lungs. TCmax is a more sensitive functional biomarker for COPD progression than CVTotal. Besides fSAD%Total and Emph%Total, segmental airways narrowing and imbalanced ventilation between upper and lower lobes may contribute to the development of hot spots over time.

An integrated metabo-lipidomics profile of induced sputum for the identification of novel biomarkers in the differential diagnosis of asthma and COPD

BACKGROUND

Due to their complexity and to the presence of common clinical features, differentiation between asthma and chronic obstructive pulmonary disease (COPD) can be a challenging task, complicated in such cases also by asthma-COPD overlap syndrome. The distinct immune/inflammatory and structural substrates of COPD and asthma are responsible for significant differences in the responses to standard pharmacologic treatments. Therefore, an accurate diagnosis is of central relevance to assure the appropriate therapeutic intervention in order to achieve safe and effective patient care. Induced sputum (IS) accurately mirrors inflammation in the airways, providing a more direct picture of lung cell metabolism in comparison to those specimen that reflect analytes in the systemic circulation.

METHODS

An integrated untargeted metabolomics and lipidomics analysis was performed in IS of asthmatic (n = 15) and COPD (n = 22) patients based on Ultra-High-Pressure Liquid Chromatography-Mass Spectrometry (UHPLC-MS) and UHPLC-tandem MS (UHPLC-MS/MS). Partial Least Squares-Discriminant Analysis (PLS-DA) was applied to resulting dataset. The analysis of main enriched metabolic pathways and the association of the preliminary metabolites/lipids pattern identified to clinical parameters of asthma/COPD differentiation were explored. Multivariate ROC analysis was performed in order to determine the discriminatory power and the reliability of the putative biomarkers for diagnosis between COPD and asthma.

RESULTS

PLS-DA indicated a clear separation between COPD and asthmatic patients. Among the 15 selected candidate biomarkers based on Variable Importance in Projection scores, putrescine showed the highest score. A differential IS bio-signature of 22 metabolites and lipids was found, which showed statistically significant variations between asthma and COPD. Of these 22 compounds, 18 were decreased and 4 increased in COPD compared to asthmatic patients. The IS levels of Phosphatidylethanolamine (PE) (34:1), Phosphatidylglycerol (PG) (18:1;18:2) and spermine were significantly higher in asthmatic subjects compared to COPD.

CONCLUSIONS

This is the first pilot study to analyse the IS metabolomics/lipidomics signatures relevant in discriminating asthma vs COPD. The role of polyamines, of 6-Hydroxykynurenic acid and of D-rhamnose as well as of other important players related to the alteration of glycerophospholipid, aminoacid/biotin and energy metabolism provided the construction of a diagnostic model that, if validated on a larger prospective cohort, might be used to rapidly and accurately discriminate asthma from COPD.

Characteristics and phenotypes of a COPD cohort from referral hospital clinics in Uganda

INTRODUCTION

Chronic obstructive pulmonary disease (COPD) is a heterogeneous condition with varied clinical and pathophysiological characteristics. Although there is increasing evidence that COPD in low-income and middle-income countries may have different clinical characteristics from that in high-income countries, little is known about COPD phenotypes in these settings. We describe the clinical characteristics and risk factor profile of a COPD population in Uganda.

METHODS

We cross sectionally analysed the baseline clinical characteristics of 323 patients with COPD aged 30 years and above who were attending 2 national referral outpatient facilities in Kampala, Uganda between July 2019 and March 2021. Logistic regression was used to determine factors associated with spirometric disease severity.

RESULTS

The median age was 62 years; 51.1% females; 93.5% scored COPD Assessment Test >10; 63.8% modified medical research council (mMRC) >2; 71.8% had wheezing; 16.7% HIV positive; 20.4% had a history of pulmonary tuberculosis (TB); 50% with blood eosinophilic count >3%, 51.7% had 3 or more exacerbations in the past year. Greater severity by Global initiative for Chronic Obstructive Lung Disease (GOLD) stage was inversely related to age (aOR=0.95, 95% CI 0.92 to 0.97), and obesity compared with underweight (aOR=0.25, 95% CI 0.07 to 0.82). Regarding clinical factors, more severe airflow obstruction was associated with SPO2 <93% (aOR=3.79, 95% CI 2.05 to 7.00), mMRC ≥2 (aOR=2.21, 95% CI 1.08 to 4.53), and a history of severe exacerbations (aOR=2.64, 95% CI 1.32 to 5.26).

CONCLUSION

Patients with COPD in this population had specific characteristics and risk factor profiles including HIV and TB meriting tailored preventative approaches. Further studies are needed to better understand the pathophysiological mechanisms at play and the therapeutic implications of these findings.

Respiratory Oscillometry and Functional Performance in Different COPD Phenotypes

Purpose

Chronic obstructive pulmonary disease (COPD) phenotypes may introduce different characteristics that need to be known to improve treatment. Respiratory oscillometry provides a detailed analysis and may offer insight into the pathophysiology of COPD. In this paper, we used this method to evaluate the differences in respiratory mechanics of COPD phenotypes.

Patients and Methods

This study investigated a sample of 83 volunteers, being divided into control group (CG = 20), emphysema (n = 23), CB (n = 20) and asthma-COPD overlap syndrome (ACOS, n = 20). These analyses were performed before and after bronchodilator (BD) use. Functional capacity was evaluated using the Glittre‑ADL test, handgrip strength and respiratory pressures.

Results

Initially it was observed that oscillometry provided a detailed description of the COPD phenotypes, which was consistent with the involved pathophysiology. A correlation between oscillometry and functional capacity was observed (r=-0.541; p = 0.0001), particularly in the emphysema phenotype (r = -0.496, p = 0.031). BD response was different among the studied phenotypes. This resulted in an accurate discrimination of ACOS from CB [area under the receiver operating curve (AUC) = 0.84] and emphysema (AUC = 0.82).

Conclusion

These results offer evidence that oscillatory indices may enhance the comprehension and identification of COPD phenotypes, thereby potentially improving the support provided to these patients.

A gel-coated air-liquid-interface culture system with tunable substrate stiffness matching healthy and diseased lung tissues

Since its invention in the late 1980s, the air-liquid-interface (ALI) culture system has been the standard in vitro model for studying human airway biology and pulmonary diseases. However, in a conventional ALI system, cells are cultured on a porous plastic membrane that is much stiffer than human airway tissues. Here, we develop a gel-ALI culture system by simply coating the plastic membrane with a thin layer of hydrogel with tunable stiffness matching that of healthy and fibrotic airway tissues. We determine the optimum gel thickness that does not impair the transport of nutrients and biomolecules essential to cell growth. We show that the gel-ALI system allows human bronchial epithelial cells (HBECs) to proliferate and differentiate into pseudostratified epithelium. Furthermore, we discover that HBECs migrate significantly faster on hydrogel substrates with stiffness matching that of fibrotic lung tissues, highlighting the importance of mechanical cues in human airway remodeling. The developed gel-ALI system provides a facile approach to studying the effects of mechanical cues in human airway biology and in modeling pulmonary diseases.NEW & NOTEWORTHY In a conventional ALI system, cells are cultured on a plastic membrane that is much stiffer than human airway tissues. We develop a gel-ALI system by coating the plastic membrane with a thin layer of hydrogel with tunable stiffness matching that of healthy and fibrotic airway tissues. We discover that human bronchial epithelial cells migrate significantly faster on hydrogel substrates with pathological stiffness, highlighting the importance of mechanical cues in human airway remodeling.

Local heterogeneity of normal lung parenchyma and small airways disease are associated with COPD severity and progression

BACKGROUND

Small airways disease (SAD) is a major cause of airflow obstruction in COPD patients and has been identified as a precursor to emphysema. Although the amount of SAD in the lungs can be quantified using our Parametric Response Mapping (PRM) approach, the full breadth of this readout as a measure of emphysema and COPD progression has yet to be explored. We evaluated topological features of PRM-derived normal parenchyma and SAD as surrogates of emphysema and predictors of spirometric decline.

METHODS

PRM metrics of normal lung (PRMNorm) and functional SAD (PRMfSAD) were generated from CT scans collected as part of the COPDGene study (n = 8956). Volume density (V) and Euler-Poincaré Characteristic (χ) image maps, measures of the extent and coalescence of pocket formations (i.e., topologies), respectively, were determined for both PRMNorm and PRMfSAD. Association with COPD severity, emphysema, and spirometric measures were assessed via multivariable regression models. Readouts were evaluated as inputs for predicting FEV1 decline using a machine learning model.

RESULTS

Multivariable cross-sectional analysis of COPD subjects showed that V and χ measures for PRMfSAD and PRMNorm were independently associated with the amount of emphysema. Readouts χfSAD (β of 0.106, p < 0.001) and VfSAD (β of 0.065, p = 0.004) were also independently associated with FEV1% predicted. The machine learning model using PRM topologies as inputs predicted FEV1 decline over five years with an AUC of 0.69.

CONCLUSIONS

We demonstrated that V and χ of fSAD and Norm have independent value when associated with lung function and emphysema. In addition, we demonstrated that these readouts are predictive of spirometric decline when used as inputs in a ML model. Our topological PRM approach using PRMfSAD and PRMNorm may show promise as an early indicator of emphysema onset and COPD progression.

Proteomic Networks and Related Genetic Variants Associated with Smoking and Chronic Obstructive Pulmonary Disease

Background

Studies have identified individual blood biomarkers associated with chronic obstructive pulmonary disease (COPD) and related phenotypes. However, complex diseases such as COPD typically involve changes in multiple molecules with interconnections that may not be captured when considering single molecular features.

Methods

Leveraging proteomic data from 3,173 COPDGene Non-Hispanic White (NHW) and African American (AA) participants, we applied sparse multiple canonical correlation network analysis (SmCCNet) to 4,776 proteins assayed on the SomaScan v4.0 platform to derive sparse networks of proteins associated with current vs. former smoking status, airflow obstruction, and emphysema quantitated from high-resolution computed tomography scans. We then used NetSHy, a dimension reduction technique leveraging network topology, to produce summary scores of each proteomic network, referred to as NetSHy scores. We next performed genome-wide association study (GWAS) to identify variants associated with the NetSHy scores, or network quantitative trait loci (nQTLs). Finally, we evaluated the replicability of the networks in an independent cohort, SPIROMICS.

Results

We identified networks of 13 to 104 proteins for each phenotype and exposure in NHW and AA, and the derived NetSHy scores significantly associated with the variable of interests. Networks included known (sRAGE, ALPP, MIP1) and novel molecules (CA10, CPB1, HIS3, PXDN) and interactions involved in COPD pathogenesis. We observed 7 nQTL loci associated with NetSHy scores, 4 of which remained after conditional analysis. Networks for smoking status and emphysema, but not airflow obstruction, demonstrated a high degree of replicability across race groups and cohorts.

Conclusions

In this work, we apply state-of-the-art molecular network generation and summarization approaches to proteomic data from COPDGene participants to uncover protein networks associated with COPD phenotypes. We further identify genetic associations with networks. This work discovers protein networks containing known and novel proteins and protein interactions associated with clinically relevant COPD phenotypes across race groups and cohorts.

Evaluation of retrieval accuracy and visual similarity in content-based image retrieval of chest CT for obstructive lung disease

The aim of our study was to assess the performance of content-based image retrieval (CBIR) for similar chest computed tomography (CT) in obstructive lung disease. This retrospective study included patients with obstructive lung disease who underwent volumetric chest CT scans. The CBIR database included 600 chest CT scans from 541 patients. To assess the system performance, follow-up chest CT scans of 50 patients were evaluated as query cases, which showed the stability of the CT findings between baseline and follow-up chest CT, as confirmed by thoracic radiologists. The CBIR system retrieved the top five similar CT scans for each query case from the database by quantifying and comparing emphysema extent and size, airway wall thickness, and peripheral pulmonary vasculatures in descending order from the database. The rates of retrieval of the same pairs of query CT scans in the top 1-5 retrievals were assessed. Two expert chest radiologists evaluated the visual similarities between the query and retrieved CT scans using a five-point scale grading system. The rates of retrieving the same pairs of query CTs were 60.0% (30/50) and 68.0% (34/50) for top-three and top-five retrievals. Radiologists rated 64.8% (95% confidence interval 58.8-70.4) of the retrieved CT scans with a visual similarity score of four or five and at least one case scored five points in 74% (74/100) of all query cases. The proposed CBIR system for obstructive lung disease integrating quantitative CT measures demonstrated potential for retrieving chest CT scans with similar imaging phenotypes. Further refinement and validation in this field would be valuable.

From treatable traits to GETomics in airway disease: moving towards clinical practice

The treatable traits approach represents a strategy for patient management. It is based on the identification of characteristics susceptible to treatments or predictive of treatment response in each individual patient. With the objective of accelerating progress in research and clinical practice relating to such a treatable traits approach, the Portraits event was convened in Barcelona, Spain, in November 2022. Here, while reporting the key concepts that emerged from the discussions during the meeting, we review the current state of the art related to treatable traits and chronic respiratory diseases management, and we describe the possible actions that clinicians can take in clinical practice to implement the treatable traits framework. Furthermore, we explore the new concept of GETomics and the new models of research in the field of COPD.

Cell-free DNA levels associate with COPD exacerbations and mortality

THE QUESTION ADDRESSED BY THE STUDY

Good biological indicators capable of predicting chronic obstructive pulmonary disease (COPD) phenotypes and clinical trajectories are lacking. Because nuclear and mitochondrial genomes are damaged and released by cigarette smoke exposure, plasma cell-free mitochondrial and nuclear DNA (cf-mtDNA and cf-nDNA) levels could potentially integrate disease physiology and clinical phenotypes in COPD. This study aimed to determine whether plasma cf-mtDNA and cf-nDNA levels are associated with COPD disease severity, exacerbations, and mortality risk.

MATERIALS AND METHODS

We quantified mtDNA and nDNA copy numbers in plasma from participants enrolled in the Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE, n = 2,702) study and determined associations with relevant clinical parameters.

RESULTS

Of the 2,128 participants with COPD, 65% were male and the median age was 64 (interquartile range, 59-69) years. During the baseline visit, cf-mtDNA levels positively correlated with future exacerbation rates in subjects with mild/moderate and severe disease (Global Initiative for Obstructive Lung Disease [GOLD] I/II and III, respectively) or with high eosinophil count (≥ 300). cf-nDNA positively associated with an increased mortality risk (hazard ratio, 1.33 [95% confidence interval, 1.01-1.74] per each natural log of cf-nDNA copy number). Additional analysis revealed that individuals with low cf-mtDNA and high cf-nDNA abundance further increased the mortality risk (hazard ratio, 1.62 [95% confidence interval, 1.16-2.25] per each natural log of cf-nDNA copy number).

ANSWER TO THE QUESTION

Plasma cf-mtDNA and cf-nDNA, when integrated into quantitative clinical measurements, may aid in improving COPD severity and progression assessment.

Benidipine calcium channel blocker promotes the death of cigarette smoke-induced senescent cells and improves lung emphysema

Smoking is the main risk factor for many lung diseases including chronic obstructive pulmonary disease. Cigarette smoke (CS) contains carcinogenic and reactive oxygen species that favor DNA mutations and perturb the homeostasis and environment of cells. CS induces lung cell senescence resulting in a stable proliferation arrest and a senescence-associated secretory phenotype. It was recently reported that senescent cell accumulation promotes several lung diseases. In this study, we performed a chemical screen, using an FDA-approved drug library, to identify compounds selectively promoting the death of CS-induced senescent lung cells. Aside from the well-known senolytic, ABT-263, we identified other potentially new senescence-eliminating compounds, including a new class of molecules, the dihydropyridine family of calcium voltage-gated channel (CaV) blockers. Among these blockers, Benidipine, decreased senescent lung cells and ameliorates lung emphysema in a mouse model. The dihydropyridine family of CaV blockers thus constitutes a new class of senolytics that could improve lung diseases. Hence, our work paves the way for further studies on the senolytic activity of CaV blockers in different senescence contexts and age-related diseases.

Clinical phenotypes of COPD and their impact on quality of life: A cross-sectional study

BACKGROUND

A Chronic Obstructive Pulmonary Disease (COPD) phenotype is a single or group of disease characteristics that describe differences between individuals based on clinically important factors such as symptoms, exacerbations, morbidity, and treatment responses. Many studies estimated the prevalence of various phenotypes, but very few studies looked into their quality of life. We aimed to estimate the prevalence of different COPD phenotypes and their disease-specific Health-Related Quality of Life (HRQoL).

MATERIALS AND METHODS

The prospective study, with a sample size of 136, was conducted between May 2021 and December 2022 in a tertiary teaching institute. Based on their clinical features, COPD patients were classified into 4 different clinical phenotypes, and their disease-specific quality of life was assessed using St. George Respiratory Questionnaire-COPD(SGRQ-c) and COPD Assessment Test (CAT) questionnaires.

RESULTS

Among 136 COPD patients, the frequency of Non-Exacerbator (NE), Exacerbator Emphysema (EEM), Exacerbator Chronic Bronchitis (ECB), and Asthma COPD overlap (ACO) phenotypes was 79(58.1 %), 16(11.8 %), 31(22.8 %), and 10(7.4 %) respectively. Based on the SGRQ-c score, the ECB and EEM phenotypes had a significantly poorer Quality of life (QoL) when compared with NE(P<0.0001), ACO(P=0.011), phenotypes. Similarly, ECB and EEM phenotypes had significantly poorer QoL when compared to NE(P<0.0001), and ACO(P=0.015), based on the CAT score. ECB and EEM patients also had the worst scores in all individual CAT items and SGRQ-c components.

CONCLUSION

NE was the most common followed by ECB phenotype. ECB and EEM phenotypes recorded the poorest quality of life without any significant differences among them. Further research is needed in the future to determine whether phenotype-specific therapies can produce better clinical outcomes.

Quantitative CT of Normal Lung Parenchyma and Small Airways Disease Topologies are Associated With COPD Severity and Progression

Objectives

Small airways disease (SAD) is a major cause of airflow obstruction in COPD patients, and has been identified as a precursor to emphysema. Although the amount of SAD in the lungs can be quantified using our Parametric Response Mapping (PRM) approach, the full breadth of this readout as a measure of emphysema and COPD progression has yet to be explored. We evaluated topological features of PRM-derived normal parenchyma and SAD as surrogates of emphysema and predictors of spirometric decline.

Materials and Methods

PRM metrics of normal lung (PRMNorm) and functional SAD (PRMfSAD) were generated from CT scans collected as part of the COPDGene study (n=8956). Volume density (V) and Euler-Poincaré Characteristic (χ) image maps, measures of the extent and coalescence of pocket formations (i.e., topologies), respectively, were determined for both PRMNorm and PRMfSAD. Association with COPD severity, emphysema, and spirometric measures were assessed via multivariable regression models. Readouts were evaluated as inputs for predicting FEV1 decline using a machine learning model.

Results

Multivariable cross-sectional analysis of COPD subjects showed that V and χ measures for PRMfSAD and PRMNorm were independently associated with the amount of emphysema. Readouts χfSAD (β of 0.106, p<0.001) and VfSAD (β of 0.065, p=0.004) were also independently associated with FEV1% predicted. The machine learning model using PRM topologies as inputs predicted FEV1 decline over five years with an AUC of 0.69.

Conclusions

We demonstrated that V and χ of fSAD and Norm have independent value when associated with lung function and emphysema. In addition, we demonstrated that these readouts are predictive of spirometric decline when used as inputs in a ML model. Our topological PRM approach using PRMfSAD and PRMNorm may show promise as an early indicator of emphysema onset and COPD progression.

RETRO-POPE: A Retrospective, Multicenter, Real-World Study of All-Cause Mortality in COPD

Purpose

The Phenotypes of COPD in Central and Eastern Europe (POPE) study assessed the prevalence and clinical characteristics of four clinical COPD phenotypes, but not mortality. This retrospective analysis of the POPE study (RETRO-POPE) investigated the relationship between all-cause mortality and patient characteristics using two grouping methods: clinical phenotyping (as in POPE) and Burgel clustering, to better identify high-risk patients.

Patients and Methods

The two largest POPE study patient cohorts (Czech Republic and Serbia) were categorized into one of four clinical phenotypes (acute exacerbators [with/without chronic bronchitis], non-exacerbators, asthma-COPD overlap), and one of five Burgel clusters based on comorbidities, lung function, age, body mass index (BMI) and dyspnea (very severe comorbid, very severe respiratory, moderate-to-severe respiratory, moderate-to-severe comorbid/obese, and mild respiratory). Patients were followed-up for approximately 7 years for survival status.

Results

Overall, 801 of 1,003 screened patients had sufficient data for analysis. Of these, 440 patients (54.9%) were alive and 361 (45.1%) had died at the end of follow-up. Analysis of survival by clinical phenotype showed no significant differences between the phenotypes (P=0.211). However, Burgel clustering demonstrated significant differences in survival between clusters (P<0.001), with patients in the "very severe comorbid" and "very severe respiratory" clusters most likely to die. Overall survival was not significantly different between Serbia and the Czech Republic after adjustment for age, BMI, comorbidities and forced expiratory volume in 1 second (hazard ratio [HR] 0.80, 95% confidence interval [CI] 0.65-0.99; P=0.036 [unadjusted]; HR 0.88, 95% CI 0.7-1.1; P=0.257 [adjusted]). The most common causes of death were respiratory-related (36.8%), followed by cardiovascular (25.2%) then neoplasm (15.2%).

Conclusion

Patient clusters based on comorbidities, lung function, age, BMI and dyspnea were more likely to show differences in COPD mortality risk than phenotypes defined by exacerbation history and presence/absence of chronic bronchitis and/or asthmatic features.

TLR7 promotes smoke-induced experimental lung damage through the activity of mast cell tryptase

Toll-like receptor 7 (TLR7) is known for eliciting immunity against single-stranded RNA viruses, and is increased in both human and cigarette smoke (CS)-induced, experimental chronic obstructive pulmonary disease (COPD). Here we show that the severity of CS-induced emphysema and COPD is reduced in TLR7-deficient mice, while inhalation of imiquimod, a TLR7-agonist, induces emphysema without CS exposure. This imiquimod-induced emphysema is reduced in mice deficient in mast cell protease-6, or when wild-type mice are treated with the mast cell stabilizer, cromolyn. Furthermore, therapeutic treatment with anti-TLR7 monoclonal antibody suppresses CS-induced emphysema, experimental COPD and accumulation of pulmonary mast cells in mice. Lastly, TLR7 mRNA is increased in pre-existing datasets from patients with COPD, while TLR7+ mast cells are increased in COPD lungs and associated with severity of COPD. Our results thus support roles for TLR7 in mediating emphysema and COPD through mast cell activity, and may implicate TLR7 as a potential therapeutic target.

Comprehensive Analysis of a Competing Endogenous RNA Co-Expression Network in Chronic Obstructive Pulmonary Disease

Purpose

Chronic obstructive pulmonary disease (COPD) is the main cause of mortality world widely. Non-coding RNAs (lncRNAs) and associated competitive endogenous RNAs (ceRNAs) networks were recently proved to lead to mRNA gene expression downregulation but were still unclear in COPD. This study aims to investigate and elucidate the mechanisms underlying the involvement of ceRNA co-expression networks in COPD pathogenesis.

Methods

Obtained expression signature of data from the Gene Expression Omnibus database and compared the differentially expression of mRNAs and miRNAs between COPD patients and healthy smokers. Predicted the miRNA-lncRNA and miRNA-mRNA interaction using online library and employed CIBERSORT to measure the proportions of the 22 immune cells in the COPD and control groups.

Results

Established a ceRNA-network comprising 11 lncRNAs, 5 miRNAs, and 16 mRNAs. Using the weighted correlation network analysis method, we identified hub genes and hub miRNAs and obtained one core sub-network, XIST, FGD5-AS1, KCNQ1OT1, HOXA11-AS, LINC00667, H19, PRKCQ-AS1, NUTM2A-AS1/has-mir-454-3p/ZNF678, PRRG4. COPD patients had different proportions of immune cells than controls, and these variations were associated with the magnitude of pulmonary function parameters.

Conclusion

The ceRNA-network, particularly the core sub-network, may be a putative goal for COPD, in which specific immune cells were involved.

Muco-Obstructive Lung Disease: A Systematic Review

Muco-obstructive lung disease is a new classification under the diseases of respiratory tract. A lot of discussion is still going on regarding this new group of diseases. It is characterised by obstruction of the respiratory tract with a thick mucin layer. Usually in normal individuals, the mucus is swept out of the respiratory system while coughing in the form of sputum or phlegm, but if the consistency of the mucus is thick, or the amount is heavy or there is a certain defect in the ciliary function of the respiratory tract, the mucus is not cleared and it gets accumulated in the lungs alveoli, therefore blocking it. The mucus trapped in the distal airways cannot be cleared by coughing therefore forming a layer in the alveoli and bronchioles. Long-standing condition causes inflammation and infection. This new group of diseases specifically includes chronic obstructive pulmonary disease (COPD), cystic fibrosis (CF), primary ciliary dyskinesia (PCD) and non-cystic fibrosis bronchiectasis (NCFB). Asthma, although an obstructive disease of the lung, is not particularly included under muco-obstructive lung disease. The major symptoms with which these diseases present are sputum production, chronic cough and acute exacerbations of the condition. The mucus adheres to the lung parenchyma causing airway obstruction and hyperinflation. In this article, we will see how muco-obstructive lung diseases affect the normal physiology of the respiratory system and how is it different from other obstructive and restrictive lung diseases. We will individually look into all the four conditions that come under the category of muco-obstructive lung diseases.

Telehealth nursing interventions for phenotypes of older adults with COPD: an exploratory study

Introduction

Inconclusive results exist around the effectiveness of telemonitoring for patients with COPD, and studies recommended conducting subgroup analyses to identify patient phenotypes that could benefit from these services. This exploratory study investigated what type of COPD patients were receiving which type of telenursing interventions more frequently using the telemonitoring platform.

Methods

A sample of 36 older adults with COPD were receiving telenursing services for 12 months and were asked to answer five COPD-symptom related questions and submit their vital signs daily.

Results

Findings revealed two phenotypes of older adults for whom the frequency of telenursing calls and related interventions differed. Although no statistically significant differences were observed in participants' GOLD grades and hospitalizations, cluster one participants used their COPD action plan significantly more frequently, and were in frequent contact with the telenurse.

Discussion

It is paramount that further research is needed on the development of patient phenotypes who may benefit from telemonitoring.

Mortality in non-exacerbating COPD: a longitudinal analysis of UK primary care data

INTRODUCTION

Non-exacerbating patients with chronic obstructive pulmonary disease (COPD) are a less studied phenotype. We investigated clinical characteristics, mortality rates and causes of death among non-exacerbating compared with exacerbating patients with COPD.

METHODS

We used data from the Clinical Practice Research Datalink, Hospital Episode Statistics and Office for National Statistics between 1 January 2004 and 31 December 2018. Ever smokers with a COPD diagnosis with minimum 3 years of baseline information were included. We compared overall using Cox regression and cause-specific mortality rates using competing risk analysis, adjusted for age, sex, deprivation, smoking status, body mass index, GOLD stage and comorbidities. Causes of death were identified using International Classification of Diseases-10 codes.

RESULTS

Among 67 516 patients, 17.3% did not exacerbate during the 3-year baseline period. Mean follow-up was 4 years. Non-exacerbators were more likely to be male (63.3% vs 52.4%, p<0.001) and less often had a history of asthma (33.9% vs 43.6%, p<0.001) or FEV1<50% predicted (23.7 vs 31.8%) compared with exacerbators. Adjusted HR for overall mortality in non-exacerbators compared with exacerbators was 0.62 (95% CI 0.56 to 0.70) in the first year of follow-up and 0.87 (95% CI 0.83 to 0.91) thereafter. Non-exacerbating patients with COPD died less of respiratory causes than exacerbators (29.2% vs 40.3%) and more of malignancies (29.4% vs 23.4%) and cardiovascular diseases (26.2% vs 22.9%). HRs for malignant and circulatory causes of death were increased after the first year of follow-up.

DISCUSSION

In this primary care cohort, non-exacerbators showed distinct clinical characteristics and lower mortality rates. Non-exacerbators were equally likely to die of respiratory, malignant or cardiovascular diseases.

Emphysema subtyping on thoracic computed tomography scans using deep neural networks

Accurate identification of emphysema subtypes and severity is crucial for effective management of COPD and the study of disease heterogeneity. Manual analysis of emphysema subtypes and severity is laborious and subjective. To address this challenge, we present a deep learning-based approach for automating the Fleischner Society's visual score system for emphysema subtyping and severity analysis. We trained and evaluated our algorithm using 9650 subjects from the COPDGene study. Our algorithm achieved the predictive accuracy at 52%, outperforming a previously published method's accuracy of 45%. In addition, the agreement between the predicted scores of our method and the visual scores was good, where the previous method obtained only moderate agreement. Our approach employs a regression training strategy to generate categorical labels while simultaneously producing high-resolution localized activation maps for visualizing the network predictions. By leveraging these dense activation maps, our method possesses the capability to compute the percentage of emphysema involvement per lung in addition to categorical severity scores. Furthermore, the proposed method extends its predictive capabilities beyond centrilobular emphysema to include paraseptal emphysema subtypes.

Investigation of Factors Affecting Shuttle Walking Performance at Increased Speed for Patients with Chronic Obstructive Pulmonary Disease

The aim of this study was to examine the factors affecting the shuttle walking test (SWT) in patients with chronic obstructive pulmonary disease (COPD). A total of 29 patients with COPD (the COPD group) and a healthy group (HG) of 34 women aged between 55 and 74 years were included in the study. After the pulmonary function profiles of the participants were assessed, and the SWT was performed. Walking distances, walking speeds, and SWT levels (SWT-L) were determined with the SWT. Before and after the SWT, the heart rate (HR), oxygen saturation level (SPO2), and Borg scale (perceived exertion (BSe) and dyspnea (BSd)) results were analyzed with a paired sample t-test. The dyspnea levels during activity of daily living were determined with the Medical Research Council (MRC) dyspnea scale, and the relationship between MRC dyspnea (MRCD) and walking distance, speed, and SWT-L was tested using multiple linear regression and Pearson correlation analysis. The walking distance, speed, and SWT-L were lower in the COPD group (p < 0.001) than in the HG. The HR values before and after the SWT changed significantly in the COPD group and the HG (p< 0.001), and the effect size was higher in the COPD group. Although the BSe and BSd results before and after the SWT in the COPD group increased significantly (p < 0.001), they did not change in the HG. There was a highly negative correlation between MRCD and walking distance, speed, and SWT-L in the COPD group (p = 0.002, p = 0.000, and p = 0.001, respectively), but no correlation was found in the HG. The results showed that the HR, perceived exertion, and dyspnea levels of women with COPD whose respiratory functions were lower than the HG were significantly affected on the SWT.

Understanding COPD Etiology, Pathophysiology, and Definition

COPD, one of the leading worldwide health problems, currently lacks truly disease-modifying medical therapies applicable to most patients. Developing such novel therapies has been hampered by the marked heterogeneity of phenotypes between individuals with COPD. Such heterogeneity suggests that, rather than a single cause (particularly just direct inhalation of tobacco products), development and progression of COPD likely involve both complex gene-by-environment interactions to multiple inhalational exposures and a variety of molecular pathways. However, there has been considerable recent progress toward understanding how specific pathological processes can lead to discrete COPD phenotypes, particularly that of small airways disease. Advances in imaging techniques that correlate to specific types of histological damage, and in the immunological mechanisms of lung damage in COPD, hold promise for development of personalized therapies. At the same time, there is growing recognition that the current diagnostic criteria for COPD, based solely on spirometry, exclude large numbers of individuals with very similar disease manifestations. This concise review summarizes current understanding of the etiology and pathophysiology of COPD and provides background explaining the increasing calls to expand the diagnostic criteria used to diagnose COPD and some challenges in doing so.

A steroid-resistant cockroach allergen model is associated with lung and cecal microbiome changes

The pathogenesis of asthma has been partially linked to lung and gut microbiome. We utilized a steroid-resistant chronic model of cockroach antigen-induced (CRA) asthma with corticosteroid (fluticasone) treatment to examine lung and gut microbiome during disease. The pathophysiology assessment demonstrated that mucus and airway hyperresponsiveness were increased in the chronic CRA with no alteration in the fluticasone (Flut)-treated group, demonstrating steroid resistance. Analysis of mRNA from lungs showed no decrease of MUC5AC or Gob5 in the Flut-treated group. Furthermore, flow-cytometry in lung tissue showed eosinophils and neutrophils were not significantly reduced in the Flut-treated group compared to the chronic CRA group. When the microbiome profiles were assessed, data showed that only the Flut-treated animals were significantly different in the gut microbiome. Finally, a functional analysis of cecal microbiome metabolites using PiCRUSt showed several biosynthetic pathways were significantly enriched in the Flut-treated group, with tryptophan pathway verified by ELISA with increased kynurenine in homogenized cecum samples. While the implications of these data are unclear, they may suggest a significant impact of steroid treatment on future disease pathogenesis through microbiome and associated metabolite pathway changes.

Integrating Genetics, Transcriptomics, and Proteomics in Lung Tissue to Investigate Chronic Obstructive Pulmonary Disease

The integration of transcriptomic and proteomic data from lung tissue with chronic obstructive pulmonary disease (COPD)-associated genetic variants could provide insight into the biological mechanisms of COPD. Here, we assessed associations between lung transcriptomics and proteomics with COPD in 98 subjects from the Lung Tissue Research Consortium. Low correlations between transcriptomics and proteomics were generally observed, but higher correlations were found for COPD-associated proteins. We integrated COPD risk SNPs or SNPs near COPD-associated proteins with lung transcripts and proteins to identify regulatory cis-quantitative trait loci (QTLs). Significant expression QTLs (eQTLs) and protein QTLs (pQTLs) were found regulating multiple COPD-associated biomarkers. We investigated mediated associations from significant pQTLs through transcripts to protein levels of COPD-associated proteins. We also attempted to identify colocalized effects between COPD genome-wide association studies and eQTL and pQTL signals. Evidence was found for colocalization between COPD genome-wide association study signals and a pQTL for RHOB and an eQTL for DSP. We applied weighted gene co-expression network analysis to find consensus COPD-associated network modules. Two network modules generated by consensus weighted gene co-expression network analysis were associated with COPD with a false discovery rate lower than 0.05. One network module is related to the catenin complex, and the other module is related to plasma membrane components. In summary, multiple cis-acting determinants of transcripts and proteins associated with COPD were identified. Colocalization analysis, mediation analysis, and correlation-based network analysis of multiple omics data may identify key genes and proteins that work together to influence COPD pathogenesis.

Global Research Trends on the Link Between the Microbiome and COPD: A Bibliometric Analysis

Background

The pathogenesis of chronic obstructive pulmonary disease (COPD) has been studied in relation to the microbiome, providing space for more targeted interventions and new treatments. Numerous papers on the COPD microbiome have been reported in the last 10 years, yet few publications have used bibliometric methods to evaluate this area.

Methods

We searched the Web of Science Core Collection for all original research articles in the field of COPD microbiome from January 2011 to August 2022 and used CiteSpace for visual analysis.

Results

A total of 505 relevant publications were obtained, and the number of global publications in this field is steadily increasing every year, with China and the USA occupying the first two spots in international publications. Imperial College London and the University of Leicester produced the most publications. Brightling C from the UK was the most prolific writer, while Huang Y and Sze M from the USA were first and second among the authors cited. The American Journal of Respiratory and Critical Care Medicine had the highest frequency of citations. The top 10 institutions, cited authors and journals are mostly from the UK and the US. In the ranking of citations, the first article was a paper published by Sze M on changes in the lung tissue's microbiota in COPD patients. The keywords "exacerbation", "gut microbiota", "lung microbiome", "airway microbiome", "bacterial colonization", and "inflammation" were identified as cutting-edge research projects for 2011-2022.

Conclusion

Based on the visualization results, in the future, we can use the gut-lung axis as the starting point to explore the immunoinflammatory mechanism of COPD, and study how to predict the effects of different treatments of COPD by identifying the microbiota, and how to achieve the optimal enrichment of beneficial bacteria and the optimal consumption of harmful bacteria to improve COPD.

Emphysema Quantifications With CT Scan: Assessing the Effects of Acquisition Protocols and Imaging Parameters Using Virtual Imaging Trials

BACKGROUND

CT scan has notable potential to quantify the severity and progression of emphysema in patients. Such quantification should ideally reflect the true attributes and pathologic conditions of subjects, not scanner parameters. To achieve such an objective, the effects of the scanner conditions need to be understood so the influence can be mitigated.

RESEARCH QUESTION

How do CT scan imaging parameters affect the accuracy of emphysema-based quantifications and biomarkers?

STUDY DESIGN AND METHODS

Twenty anthropomorphic digital phantoms were developed with diverse anatomic attributes and emphysema abnormalities informed by a real COPD cohort. The phantoms were input to a validated CT scan simulator (DukeSim), modeling a commercial scanner (Siemens Flash). Virtual images were acquired under various clinical conditions of dose levels, tube current modulations (TCM), and reconstruction techniques and kernels. The images were analyzed to evaluate the effects of imaging parameters on the accuracy of density-based quantifications (percent of lung voxels with HU < -950 [LAA-950] and 15th percentile of lung histogram HU [Perc15]) across varied subjects. Paired t tests were performed to explore statistical differences between any two imaging conditions.

RESULTS

The most accurate imaging condition corresponded to the highest acquired dose (100 mAs) and iterative reconstruction (SAFIRE) with the smooth kernel of I31, where the measurement errors (difference between measurement and ground truth) were 35 ± 3 Hounsfield Units (HU), -4% ± 5%, and 26 ± 10 HU (average ± SD), for the mean lung HU, LAA-950, and Perc15, respectively. Without TCM and at the I31 kernel, increase of dose (20 to 100 mAs) improved the lung mean absolute error (MAE) by 4.2 ± 2.3 HU (average ± SD). TCM did not contribute to a systematic improvement of lung MAE.

INTERPRETATION

The results highlight that although CT scan quantification is possible, its reliability is impacted by the choice of imaging parameters. The developed virtual imaging trial platform in this study enables comprehensive evaluation of CT scan methods in reliable quantifications, an effort that cannot be readily made with patient images or simplistic physical phantoms.

Identifying chronic obstructive pulmonary disease from integrative omics and clustering in lung tissue

BACKGROUND

Chronic obstructive pulmonary disease (COPD) is a highly morbid and heterogenous disease. While COPD is defined by spirometry, many COPD characteristics are seen in cigarette smokers with normal spirometry. The extent to which COPD and COPD heterogeneity is captured in omics of lung tissue is not known.

METHODS

We clustered gene expression and methylation data in 78 lung tissue samples from former smokers with normal lung function or severe COPD. We applied two integrative omics clustering methods: (1) Similarity Network Fusion (SNF) and (2) Entropy-Based Consensus Clustering (ECC).

RESULTS

SNF clusters were not significantly different by the percentage of COPD cases (48.8% vs. 68.6%, p = 0.13), though were different according to median forced expiratory volume in one second (FEV1) % predicted (82 vs. 31, p = 0.017). In contrast, the ECC clusters showed stronger evidence of separation by COPD case status (48.2% vs. 81.8%, p = 0.013) and similar stratification by median FEV1% predicted (82 vs. 30.5, p = 0.0059). ECC clusters using both gene expression and methylation were identical to the ECC clustering solution generated using methylation data alone. Both methods selected clusters with differentially expressed transcripts enriched for interleukin signaling and immunoregulatory interactions between lymphoid and non-lymphoid cells.

CONCLUSIONS

Unsupervised clustering analysis from integrated gene expression and methylation data in lung tissue resulted in clusters with modest concordance with COPD, though were enriched in pathways potentially contributing to COPD-related pathology and heterogeneity.

Structural features on quantitative chest computed tomography of patients with maximal mid-expiratory flow impairment in a normal lung function population

BACKGROUND

Maximal mid-expiratory flow (MMEF) is an earlier predictor of chronic obstructive pulmonary disease (COPD) development than forced expiratory volume in 1 s (FEV₁). Changes of lung structure in patients with MMEF impairment only is still not clear. Therefore, this study aimed to investigate the structural features of patients with decreased MMEF by quantitative computed tomography (QCT) and develop a predictive model for predicting patients with reduced MMEF in normal lung function population.

METHODS

In this study, 131 patients with normal spirometry results and available volumetric chest CT images were enrolled and divided into the reduced MMEF group (FEV₁/forced expiratory vital capacity (FEV₁/FVC) > 0.7, FEV₁% predictive values (FEV₁%pred) > 80%, MMEF%pred < 80%, n = 52) and the normal MMEF group (FEV₁/FVC > 0.7, FEV₁%pred > 80%, MMEF%pred ≥ 80%, n = 79). The emphysema, small airway disease and medium-size airway parameters were measured by a commercial software. The differences were investigated in clinical features, spirometrical parameters and QCT parameters between the two groups. A nomogram model was constructed based on the results of the multivariable logistic regression model. Spearman's correlation coefficients were calculated between QCT measurements and spirometrical parameters.

RESULTS

There were more males in reduced MMEF group than normal group (P < 0.05). Lung parenchyma parameter (PRM^Emph) and airway-related parameters (functional small airway disease (PRM^fSAD), luminal area of fifth- and sixth- generation airway (LA₅, LA₆) were significantly different between the reduced MMEF group and the normal group (20.2 ± 17.4 vs 9.4 ± 6.7, 3.4 ± 3.5 vs 1.9 ± 2.0, 12.2 ± 2.5 vs 13.7 ± 3.4, 7.7 ± 2.4 vs 8.9 ± 2.8, respectively, all P < 0.01). After multivariable logistical regression, only sex (odds ratio [OR]: 2.777; 95% confidence interval [CI]:1.123-3.867), PRM^fSAD (OR:1.102, 95%CI:1.045-1.162) and LA₆ (OR:0.650, 95%CI:0.528-0.799) had significant differences between the two groups (P < 0.05) and a model incorporating with the three indicators was constructed (area under curve, 0.836). Correlation analysis showed MMEF%pred had mild to moderate correlation with airway-related measurements.

CONCLUSION

In normal lung function population, patients with reduced MMEF have potential medium-size and small airway changes, and MMEF%pred is significantly associated with airway-related CT parameters. The nomogram incorporating with sex, PRM^fSAD and LA₆ has good predictive value and offers more objective evidences in a group with reduced MMEF.

Recent advances predict a bright future for nebulizers

PURPOSE OF REVIEW

With the improvement in device technology and delivery methods of inhaled medications, along with development of novel compounds and recognition of the importance of personalized approach in the management of chronic airway diseases, nebulizers have not only maintained their place in the treatment hierarchy of airway disease but have also proven a vital platform for the development of new classes of drugs.

RECENT FINDINGS

This short review explores recent advances in nebulized drug delivery in chronic obstructive pulmonary disease and other chronic airway diseases, emphasizing the progress in nebulizer technology, physiologic advantages of nebulized drug delivery and the high versatility of currently available and developing nebulizer-delivered pharmacotherapies.

SUMMARY

Versatility and efficiency of nebulizers allows for a broad spectrum of existing and novel therapies to be clinically studied, facilitating the progress in phenotype-targeted pharmacotherapies in the management of chronic airway diseases.

Clinical Implications of Low Absolute Blood Eosinophil Count in the SPIROMICS COPD Cohort

BACKGROUND

The Global Initiative for Chronic Obstructive Lung Disease (GOLD) considers blood eosinophil counts < 100 cells/μL (BEC≤100) in people with COPD to predict poor inhaled corticosteroid (ICS) responsiveness. However, the BEC≤100 phenotype is inadequately characterized, especially in advanced COPD.

RESEARCH QUESTION

Are there differences between GOLD group D patients with high BEC and those with low BEC regarding baseline characteristics and longitudinal outcomes?

STUDY DESIGN AND METHODS

We used multivariable mixed models and logistic regression to contrast clinical characteristics and outcomes of BEC≤100 vs BEC > 100 (BEC100+) in all subjects with COPD (n = 1,414) and GOLD group D subjects (n = 185) not receiving ICS.

RESULTS

We identified n = 485 with BEC≤100 (n = 61 GOLD group D) and n = 929 people with BEC100+ (n = 124 GOLD group D). BEC≤100 status was stable at 6 weeks and approximately 52 weeks (intraclass correlations of 0.78 and 0.71, respectively). Compared with BEC100+, BEC≤100 comprised more women, with greater current smoking, and less frequent childhood asthma. Among all analyzed participants, the two BEC-defined subsets showed similar rates of lung function decline (mean slope, BEC≤100 vs BEC100+, -50 vs -39 mL/y; P = .140), exacerbations (0.40 vs 0.36/y; P = .098), subsequent ICS initiation (2.5% vs 4.4%; P = .071), and mortality (7.8% vs 8.4%; P = .715). However, in GOLD group D, people with BEC≤100 showed higher exacerbation rates within 365 days of enrollment (0.62 vs 0.33/y; P = .002) and total follow-up (1.16 vs 0.83/y; P = .014). They also had greater lung function decline (mean slope of -68 mL/y vs -23 mL/y; P = .036) and had greater emphysema at baseline (voxels < 950 Hounsfield units at total lung capacity of 7.46% vs 4.61%; P = .029).

INTERPRETATION

In non-ICS-treated GOLD group D COPD, people with BEC≤100 had more baseline emphysema, prospective exacerbations, and lung function decline. Our analysis has identified a particularly vulnerable subpopulation of people with COPD, suggesting the need for studies focused specifically on their therapeutic treatment.

CLINICAL TRIAL REGISTRATION

ClinicalTrials.gov; No.: NCT01969344; URL: www.

CLINICALTRIALS

gov.

Development of the ESEx index: a tool for predicting risk of recurrent severe COPD exacerbations

Background

In chronic obstructive pulmonary disease (COPD), multiple recurrent severe exacerbations that require hospitalization can occur. These events are strongly associated with death and other clinical complications.

Objectives

We aimed to develop a prognostic model that could identify patients with COPD that are at risk of multiple recurrent severe exacerbations within 3 years.

Design

Prospective cohort.

Methods

The derivation cohort comprised patients with stable, moderate-to-severe COPD. Multivariable logistic regression analyses were performed to develop the final model. Based on regression coefficients, a simplified index (ESEx) was established. Both, model and index, were assessed for predictive performance by measuring discrimination and calibration.

Results

Over 3 years, 16.4% of patients with COPD experienced at least three severe recurrent exacerbations. The prognostic model showed good discrimination of high-risk patients, based on three characteristics: the number of severe exacerbations in the previous year, performance in the five-repetition sit-to-stand test, and in the 6-minute-walk test. The ESEx index provided good level of discrimination [areas under the receiver operating characteristic curve (AUCs): 0.913].

Conclusions

The ESEx index showed good internal validation for the identification of patients at risk of three recurrent severe COPD exacerbations within 3 years. These tools could be used to identify patients who require early interventions and motivate patients to improve physical performance to prevent recurrent exacerbations.

COPD: Providing the right treatment for the right patient at the right time

Chronic Obstructive Pulmonary Disease (COPD) is a common disease associated with significant morbidity and mortality that is both preventable and treatable. However, a major challenge in recognizing, preventing, and treating COPD is understanding its complexity. While COPD has historically been characterized as a disease defined by airflow limitation, we now understand it as a multi-component disease with many clinical phenotypes, systemic manifestations, and associated co-morbidities. Evidence is rapidly emerging in our understanding of the many factors that contribute to the pathogenesis of COPD and the identification of "early" or "pre-COPD" which should provide exciting opportunities for early treatment and disease modification. In addition to breakthroughs in our understanding of the origins of COPD, we are optimizing treatment strategies and delivery of care that are showing impressive benefits in patient-centered outcomes and healthcare utilization. This special issue of Respiratory Medicine, "COPD: Providing the Right Treatment for the Right Patient at the Right Time" is a summary of the proceedings of a conference held in Stresa, Italy in April 2022 that brought together international experts to discuss emerging evidence in COPD and Pulmonary Rehabilitation in honor of a distinguished friend and colleague, Claudio Ferdinando Donor (1948-2021). Claudio was a true pioneer in the field of pulmonary rehabilitation and the comprehensive care of individuals with COPD. He held numerous leadership roles in in the field, provide editorial stewardship of several respiratory journals, authored numerous papers, statement and guidelines in COPD and Pulmonary Rehabilitation, and provided mentorship to many in our field. Claudio's most impressive talent was his ability to organize spectacular conferences and symposia that highlighted cutting edge science and clinical medicine. It is in this spirit that this conference was conceived and planned. These proceedings are divided into 4 sections which highlight crucial areas in the field of COPD: (1) New concepts in COPD pathogenesis; (2) Enhancing outcomes in COPD; (3) Non-pharmacologic management of COPD; and (4) Optimizing delivery of care for COPD. These presentations summarize the newest evidence in the field and capture lively discussion on the exciting future of treating this prevalent and impactful disease. We thank each of the authors for their participation and applaud their efforts toward pushing the envelope in our understanding of COPD and optimizing care for these patients. We believe that this edition is a most fitting tribute to a dear colleague and friend and will prove useful to students, clinicians, and researchers as they continually strive to provide the right treatment for the right patient at the right time. It has been our pleasure and a distinct honor to serve as editors and oversee such wonderful scholarly work.

Comparative Study of Systemic Inflammatory Markers in Clinical Phenotypes of Chronic Obstructive Pulmonary Disease

Background

Chronic Obstructive Pulmonary Disease (COPD) is an inflammatory pulmonary disorder with systemic inflammatory manifestations. This study aims to identify the profile of systemic inflammatory markers in the different phenotypes of COPD to help predict the disease and identify suitable treatment options.

Materials and Methods

A prospective observational study was conducted on 92 patients with COPD admitted to Victoria Hospital, Bangalore between August 2021 to December 2021. Levels of C-reactive protein (CRP), Serum Creatinine, Erythrocyte Sedimentation Rate (ESR), Absolute Lymphocyte Count (ALC), Absolute Eosinophil Count (AEC), and Lactate Dehydrogenase (LDH) were measured within 48 hours of presentation.

Results

Significantly higher levels of CRP were found in frequent exacerbator emphysema and chronic bronchitis phenotypes (p=0.001). The frequent exacerbator emphysema phenotype had significantly higher levels of LDH (p=0.001) and serum creatinine (p=0.001). Not surprisingly, absolute eosinophil counts were significantly raised in the overlap COPD-Asthma phenotype (p=0.001).

Conclusion

Raised serum CRP levels in the frequent exacerbator phenotypes of emphysema and chronic bronchitis suggest a possible inflammatory response to an infective etiology. Raised LDH levels in frequent exacerbator emphysema phenotype could signify underlying lung parenchymal destruction. Systemic inflammation and oxidative stress can lead to skeletal muscle injury and atrophy in COPD patients. This may explain the raised serum creatinine levels in frequent exacerbator emphysema phenotype. Eosinophilia seen in Overlap COPD-Asthma phenotype is suggestive of type 2 inflammation of the airways with better response to steroids.

Distinct COPD subtypes in former smokers revealed by gene network perturbation analysis

BACKGROUND

Chronic obstructive pulmonary disease (COPD) varies significantly in symptomatic and physiologic presentation. Identifying disease subtypes from molecular data, collected from easily accessible blood samples, can help stratify patients and guide disease management and treatment.

METHODS

Blood gene expression measured by RNA-sequencing in the COPDGene Study was analyzed using a network perturbation analysis method. Each COPD sample was compared against a learned reference gene network to determine the part that is deregulated. Gene deregulation values were used to cluster the disease samples.

RESULTS

The discovery set included 617 former smokers from COPDGene. Four distinct gene network subtypes are identified with significant differences in symptoms, exercise capacity and mortality. These clusters do not necessarily correspond with the levels of lung function impairment and are independently validated in two external cohorts: 769 former smokers from COPDGene and 431 former smokers in the Multi-Ethnic Study of Atherosclerosis (MESA). Additionally, we identify several genes that are significantly deregulated across these subtypes, including DSP and GSTM1, which have been previously associated with COPD through genome-wide association study (GWAS).

CONCLUSIONS

The identified subtypes differ in mortality and in their clinical and functional characteristics, underlining the need for multi-dimensional assessment potentially supplemented by selected markers of gene expression. The subtypes were consistent across cohorts and could be used for new patient stratification and disease prognosis.

The understanding of asthma pathogenesis in the era of precision medicine

Asthma is a syndrome with extremely diverse clinical phenotypes in which the onset, severity, and response to treatment are defined by the complex interplay of many genetic and environmental factors. Environmental factors epigenetically affect gene expression, and the disease is driven by a multidimensional dynamic network involving RNA and protein molecules derived from gene expression, as well as various metabolic products. In other words, specific pathophysiological mechanisms or endotypes are dynamic networks that arise in response to individual genotypes and the various environmental factors to which individuals have been exposed since before birth, such as diet, infection, air pollution, smoking, antibiotic use, and the bacterial flora of the intestinal tract, skin, and lungs. A key feature of asthma genome scans is their potential to reveal the molecular pathways that lead to pathogenesis. Endotypes that drive the disease have a significant impact on the phenotypes of asthma patients, including their drug responsiveness. Understanding endotypes will lead to not only the implementation of therapies that are tailored to the specific molecular network(s) underlying the patient's condition, but also to the development of therapeutic strategies that target individual endotypes, as well as to precision health, which will enable the prediction of disease onset with high accuracy from an early stage and the implementation of preventive strategies based on endotypes. Understanding of endotypes will pave the way for the practice of precision medicine in asthma care, moving away from 'one-size-fits-all' medicine and population-based prevention approaches that do not take individuals' susceptibility into account.

Clinical characteristics of children with severe neurologic impairment: A scoping review

OBJECTIVE

The aim of this study is to extrapolate the clinical features of children with severe neurologic impairment (SNI) based on the functional characteristics and comorbidities described in published studies.

METHODS

Four databases were searched. We included studies that describe clinical features of a group of children with SNI (≥20 subjects <19 years of age with >1 neurologic diagnosis and severe functional limitation) using data from caregivers, medical charts, or prospective collection. Studies that were not written in English were excluded. We extracted data about functional characteristics, comorbidities, and study topics.

RESULTS

We included 102 studies, spanning 5 continents over 43 years, using 41 distinct terms for SNI. The terms SNI and neurologic impairment (NI) were used in 59 studies (58%). Most studies (n = 81, 79%) described ≥3 types of functional characteristics, such as technology assistance and motor impairment. Studies noted 59 comorbidities and surgeries across 10 categories. The most common comorbidities were related to feeding, nutrition, and the gastrointestinal system, which were described in 79 studies (77%). Most comorbidities (76%) were noted in <10 studies. Studies investigated seven clinical topics, with "Gastrointestinal reflux and feeding tubes" as the most common research focus (n = 57, 56%). The next most common topic, "Aspiration and respiratory issues," included 13 studies (13%). Most studies (n = 54, 53%) were retrospective cohorts or case series; there were no clinical trials.

CONCLUSIONS

Despite the breadth of described comorbidities, studies focused on a narrow set of clinical topics. Further research is required to understand the prevalence, clinical impact, and interaction of the multiple comorbidities that are common in children with SNI.

Clinical and Radiological Features Between Patients with Stable COPD from Plateau and Flatlands: A Comparative Study

Background

COPD patients living in Tibet are exposed to specific environments and different risk factors and probably have different characteristics of COPD from those living in flatlands. We aimed to describe the distinction between stable COPD patients permanently residing at the Tibet plateau and those in flatlands.

Methods

We conducted an observational cross-sectional study that enrolled stable COPD patients from Tibet Autonomous Region People's Hospital (Plateau Group) and Peking University Third Hospital (Flatland Group), respectively. Their demographic information, clinical features, spirometry test, blood routine and high-resolution chest CT were collected and evaluated.

Results

A total of 182 stable COPD patients (82 from plateau and 100 from flatland) were consecutively enrolled. Compared to those in flatlands, patients in plateau had a higher proportion of females, more biomass fuel use and less tobacco exposure. CAT score and frequency of exacerbation in the past year were higher in plateau patients. The blood eosinophil count was lower in plateau patients, with fewer patients having an eosinophil count ≥300/μL. On CT examination, the proportions of previous pulmonary tuberculosis and bronchiectasis were higher in plateau patients, but emphysema was less common and milder. The ratio of diameters of pulmonary artery to aorta ≥1 was more often in plateau patients.

Conclusion

Patients with COPD living at Tibet Plateau had a heavier respiratory burden, lower blood eosinophil count, less emphysema but more bronchiectasis and pulmonary hypertension. Biomass exposure and previous tuberculosis were more common in these patients.

Cluster analysis of functional independence in community-dwelling older people

BACKGROUND

The concept of Functional Independence (FI), defined as 'functioning physically safe and independent from other persons, within one's context", plays an important role in maintaining the functional ability to enable well-being in older age. FI is a dynamic and complex concept covering four clinical outcomes: physical capacity, empowerment, coping flexibility, and health literacy. As the level of FI differs widely between older adults, healthcare professionals must gain insight into how to best support older people in maintaining their level of FI in a personalized manner. Insight into subgroups of FI could be a first step in providing personalized support This study aims to identify clinically relevant, distinct subgroups of FI in Dutch community-dwelling older people and subsequently describe them according to individual characteristics.

RESULTS

One hundred fifty-three community-dwelling older persons were included for participation. Cluster analysis identified four distinctive clusters: (1) Performers - Well-informed; this subgroup is physically strong, well-informed and educated, independent, non-falling, with limited reflective coping style. (2) Performers - Achievers: physically strong people with a limited coping style and health literacy level. (3) The reliant- Good Coper representing physically somewhat limited people with sufficient coping styles who receive professional help. (4) The reliant - Receivers: physically limited people with insufficient coping styles who receive professional help. These subgroups showed significant differences in demographic characteristics and clinical FI outcomes.

CONCLUSIONS

Community-dwelling older persons can be allocated to four distinct and clinically relevant subgroups based on their level of FI. This subgrouping provides insight into the complex holistic concept of FI by pointing out for each subgroup which FI domain is affected. This way, it helps to better target interventions to prevent the decline of FI in the community-dwelling older population.

Impact of Acute Exacerbation and Its Phenotypes on the Clinical Outcomes of Chronic Obstructive Pulmonary Disease in Hospitalized Patients: A Cross-Sectional Study

Acute exacerbations of COPD (AECOPD) are clinically significant events having therapeutic and prognostic consequences. However, there is a lot of variation in its clinical manifestations described by phenotypes. The phenotypes of AECOPD were categorized in this study based on pathology and exposure. In our cross-sectional study, conducted between 1 January 2016 to 31 December 2020, the patients were categorized into six groups based on pathology: non-bacterial and non-eosinophilic; bacterial; eosinophilic; bacterial infection with eosinophilia; pneumonia; and bronchiectasis. Further, four groups were classified based on exposure to tobacco smoke (TS), biomass smoke (BMS), both, or no exposure. Cox proportional-hazards regression analyses were performed to assess hazard ratios, and Kaplan-Meier analysis was performed to assess survival, which was then compared using the log-rank test. The odds ratio (OR) and independent predictors of ward admission type and length of hospital stay were assessed using binomial logistic regression analyses. Of the 2236 subjects, 2194 were selected. The median age of the cohort was 67.0 (60.0 to 74.0) and 75.2% were males. Mortality rates were higher in females than in males (6.2% vs. 2.3%). AECOPD-B (bacterial infection) subjects [HR 95% CI 6.42 (3.06-13.46)], followed by AECOPD-P (pneumonia) subjects [HR (95% CI: 4.33 (2.01-9.30)], were at higher mortality risk and had a more extended hospital stay (6.0 (4.0 to 9.5) days; 6.0 (4.0 to 10.0). Subjects with TS and BMS-AECOPD [HR 95% CI 7.24 (1.53-34.29)], followed by BMS-AECOPD [HR 95% CI 5.28 (2.46-11.35)], had higher mortality risk. Different phenotypes have different impacts on AECOPD clinical outcomes. A better understanding of AECOPD phenotypes could contribute to developing an algorithm for the precise management of different phenotypes.

Clinical and immunological phenotypes of systemic lupus erythematosus, identified based on cluster analysis of data from 400 patients from V.A. Nasonova Research Institute of Rheumatology

Objective: to identify clinical and immunological variants (phenotypes) of systemic lupus erythematosus (SLE) using cluster analysis.

Patients and methods. The study included 400 patients with diagnosis of SLE according to the 2012 SLICC classification criteria. Patients underwent laboratory and immunological workup according to accepted standards of medical care for patients with SLE, and therapy was prescribed in accordance with disease activity.

Results and discussion. Among patients, most were females (ratio of men and women – 1:10), and people of young age (34.2±11.5 years), with an average duration of illness of 6 [3; 12] years. In 98 (25%) patients with SLE, the disease debuted before the age of 18 years. Lupus nephritis (LN) was detected in 192 (48%) patients, SLE with antiphospholipid syndrome (APS) – in 48 (12%), SLE with Sjцgren's syndrome – in 44 (11%). For cluster analysis 30 clinical, 4 laboratory, 12 immunological and 10 therapeutic parameters were selected and a dendrogram was constructed with the calculation of the Euclidean distance using the Ward method. As a result, five clusters of SLE were identified: with the development of LN; with predominantly extrarenal manifestations; SLE combined with APS; SLE combined with Sjцgren's syndrome; SLE with a debut in childhood (up to 18 years of age). Clusters differed in clinical, laboratory and immunological parameters, as well as in therapy.

Conclusion. Cluster analysis data made it possible to group the selected signs into five clinical and immunological variants (phenotypes) of SLE. Identification of SLE phenotypes as a set of characteristics that, individually or in combination, make it possible to determine differences between patients based on clinical, laboratory and immunological parameters, variants of the onset and course of the disease, response to therapy and prognosis, will contribute to a personalized approach in choosing the therapy, improving its long-term results, as well as quality of life and prognosis in patients with SLE.

Physiology and pathophysiology of human airway mucus

The mucus clearance system is the dominant mechanical host defense system of the human lung. Mucus is cleared from the lung by cilia and airflow, including both two-phase gas-liquid pumping and cough-dependent mechanisms, and mucus transport rates are heavily dependent on mucus concentration. Importantly, mucus transport rates are accurately predicted by the gel-on-brush model of the mucociliary apparatus from the relative osmotic moduli of the mucus and periciliary-glycocalyceal (PCL-G) layers. The fluid available to hydrate mucus is generated by transepithelial fluid transport. Feedback interactions between mucus concentrations and cilia beating, via purinergic signaling, coordinate Na+ absorptive vs Cl- secretory rates to maintain mucus hydration in health. In disease, mucus becomes hyperconcentrated (dehydrated). Multiple mechanisms derange the ion transport pathways that normally hydrate mucus in muco-obstructive lung diseases, e.g., cystic fibrosis (CF), chronic obstructive pulmonary disease (COPD), non-CF bronchiectasis (NCFB), and primary ciliary dyskinesia (PCD). A key step in muco-obstructive disease pathogenesis is the osmotic compression of the mucus layer onto the airway surface with the formation of adherent mucus plaques and plugs, particularly in distal airways. Mucus plaques create locally hypoxic conditions and produce airflow obstruction, inflammation, infection, and, ultimately, airway wall damage. Therapies to clear adherent mucus with hydrating and mucolytic agents are rational, and strategies to develop these agents are reviewed.

Radiographic Phenotypes Affect the Risk of Inhaled Corticosteroid-Associated Pneumonia in Patients with COPD

Purpose

Few studies have reported the association between the radiographic characteristics and the development of pneumonia in patients with chronic obstructive pulmonary disease (COPD) treated with inhaled corticosteroids (ICSs). Our study aimed to assess the effect of radiographic phenotypes on the risk of pneumonia in patients treated with ICSs.

Patients and Methods

This study retrospectively analysed all patients with COPD treated with ICSs in a subset of the Korea Chronic Obstructive Pulmonary Disorders Subgroup Study registry between January 2017 and December 2019. The association between radiographic phenotypes including the presence and severity of emphysema, airway wall thickening, or bronchiectasis on chest computed tomography were determined visually/qualitatively and the risk of pneumonia was analyzed using the Cox regression model.

Results

Among the 90 patients with COPD treated with ICSs, 41 experienced pneumonia more than once during the median follow-up of 29 (interquartile range, 8–35) months. In univariate Cox regression analysis, older age, longer use of ICSs, use of fluticasone propionate or metered dose inhaler, and severe exacerbation events increased the risk of pneumonia. In multivariate analysis, the presence of emphysema (adjusted hazard ratio [aHR]=3.73, P=0.033), severity measured using the visual sum score (mild-to-moderate, aHR=8.58, P=0.016; severe, aHR=3.58, P=0.042), Goddard sum score (mild-to-moderate, aHR=3.31, P=0.058; severe, aHR=5.38, P=0.014), and the upper lobe distribution of emphysema (aHR=3.76, P=0.032) were associated with a higher risk of pneumonia. Subtypes of centrilobular and panlobular emphysema had a higher risk of pneumonia compared with paraseptal emphysema (aHR=3.98, P=0.033; HR=3.91, P=0.041 vs HR=2.74, P=0.304). The presence of bronchiectasis (aHR=2.41, P=0.02) and emphysema/bronchiectasis overlap phenotype (aHR=2.19, P=0.053) on chest CT was a risk factor for pneumonia in this population. However, severity of bronchiectasis and the presence or severity of bronchial wall thickening according to the visual sum score were not associated with the risk of pneumonia.

Conclusion

Among patients with COPD treated with ICSs, radiographic phenotypes including the presence of emphysema, bronchiectasis or emphysema/bronchiectasis overlap phenotype, severity with emphysema, subtypes of centrilobular or panlobular emphysema, and upper lobe distribution of emphysema may help predict the risk of pneumonia.

Machine Learning Prediction of Progression in Forced Expiratory Volume in 1 Second in the COPDGene® Study

BACKGROUND

The heterogeneous nature of chronic obstructive pulmonary disease (COPD) complicates the identification of the predictors of disease progression. We aimed to improve the prediction of disease progression in COPD by using machine learning and incorporating a rich dataset of phenotypic features.

METHODS

We included 4496 smokers with available data from their enrollment and 5-year follow-up visits in the COPD Genetic Epidemiology (COPDGene^®) study. We constructed linear regression (LR) and supervised random forest models to predict 5-year progression in forced expiratory in 1 second (FEV₁) from 46 baseline features. Using cross-validation, we randomly partitioned participants into training and testing samples. We also validated the results in the COPDGene 10-year follow-up visit.

RESULTS

Predicting the change in FEV₁ over time is more challenging than simply predicting the future absolute FEV₁ level. For random forest, R-squared was 0.15 and the area under the receiver operator characteristic (ROC) curves for the prediction of participants in the top quartile of observed progression was 0.71 (testing) and respectively, 0.10 and 0.70 (validation). Random forest provided slightly better performance than LR. The accuracy was best for Global initiative for chronic Obstructive Lung Disease (GOLD) grades 1-2 participants, and it was harder to achieve accurate prediction in advanced stages of the disease. Predictive variables differed in their relative importance as well as for the predictions by GOLD.

CONCLUSION

Random forest, along with deep phenotyping, predicts FEV₁ progression with reasonable accuracy. There is significant room for improvement in future models. This prediction model facilitates the identification of smokers at increased risk for rapid disease progression. Such findings may be useful in the selection of patient populations for targeted clinical trials.