Identification of Chronic Obstructive Pulmonary Disease Axes That Predict All-Cause Mortality: The COPDGene Study

A novel application of data-consistent inversion to overcome spurious inference in genome-wide association studies

The genome-wide association studies (GWAS) typically use linear or logistic regression models to identify associations between phenotypes (traits) and genotypes (genetic variants) of interest. However, the use of regression with the additive assumption has potential limitations. First, the normality assumption of residuals is the one that is rarely seen in practice, and deviation from normality increases the Type-I error rate. Second, building a model based on such an assumption ignores genetic structures, like, dominant, recessive, and protective-risk cases. Ignoring genetic variants may result in spurious conclusions about the associations between a variant and a trait. We propose an assumption-free model built upon data-consistent inversion (DCI), which is a recently developed measure-theoretic framework utilized for uncertainty quantification. This proposed DCI-derived model builds a nonparametric distribution on model inputs that propagates to the distribution of observed data without the required normality assumption of residuals in the regression model. This characteristic enables the proposed DCI-derived model to cover all genetic variants without emphasizing on additivity of the classic-GWAS model. Simulations and a replication GWAS with data from the COPDGene demonstrate the ability of this model to control the Type-I error rate at least as well as the classic-GWAS (additive linear model) approach while having similar or greater power to discover variants in different genetic modes of transmission.

Identification of factors directly linked to incident chronic obstructive pulmonary disease: A causal graph modeling study

BACKGROUND

Beyond exposure to cigarette smoking and aging, the factors that influence lung function decline to incident chronic obstructive pulmonary disease (COPD) remain unclear. Advancements have been made in categorizing COPD into emphysema and airway predominant disease subtypes; however, predicting which healthy individuals will progress to COPD is difficult because they can exhibit profoundly different disease trajectories despite similar initial risk factors. This study aimed to identify clinical, genetic, and radiological features that are directly linked-and subsequently predict-abnormal lung function.

METHODS AND FINDINGS

We employed graph modeling on 2,643 COPDGene participants (aged 45 to 80 years, 51.25% female, 35.1% African Americans; enrollment 11/2007-4/2011) with smoking history but normal spirometry at study enrollment to identify variables that are directly linked to future lung function abnormalities. We developed logistic regression and random forest predictive models for distinguishing individuals who maintain lung function from those who decline. Of the 131 variables analyzed, 6 were identified as informative to future lung function abnormalities, namely forced expiratory flow in the middle range (FEF25-75%), average lung wall thickness in a 10 mm radius (Pi10), severe emphysema, age, sex, and height. We investigated whether these features predict individuals leaving GOLD 0 status (normal spirometry according to Global Initiative for Obstructive Lung Disease (GOLD) criteria). Linear models, trained with these features, were quite predictive (area under receiver operator characteristic curve or AUROC = 0.75). Random forest predictors performed similarly to logistic regression (AUROC = 0.7), indicating that no significant nonlinear effects were present. The results were externally validated on 150 participants from Specialized Center for Clinically Oriented Research (SCCOR) cohort (aged 45 to 80 years, 52.7% female, 4.7% African Americans; enrollment: 7/2007-12/2012) (AUROC = 0.89). The main limitation of longitudinal studies with 5- and 10-year follow-up is the introduction of mortality bias that disproportionately affects the more severe cases. However, our study focused on spirometrically normal individuals, who have a lower mortality rate. Another limitation is the use of strict criteria to define spirometrically normal individuals, which was unavoidable when studying factors associated with changes in normalized forced expiratory volume in 1 s (FEV1%predicted) or the ratio of FEV1/FVC (forced vital capacity).

CONCLUSIONS

This study took an agnostic approach to identify which baseline measurements differentiate and predict the early stages of lung function decline in individuals with previous smoking history. Our analysis suggests that emphysema affects obstruction onset, while airway predominant pathology may play a more important role in future FEV1 (%predicted) decline without obstruction, and FEF25-75% may affect both.

Thoracic high resolution computed tomography evaluation of imaging abnormalities of 108 lung cancer patients with different pulmonary function

PURPOSE

Preserved ratio impaired spirometry (PRISm) and chronic obstructive pulmonary disease (COPD) belong to lung function injury. PRISm is a precursor to COPD. We compared and evaluated the different basic information, imaging findings and survival curves of 108 lung cancer patients with different pulmonary function based on high resolution computed tomography (HRCT).

METHODS

This retrospective study was performed on 108 lung cancer patients who did pulmonary function test (PFT) and thoracic HRCT. The basic information was evaluated: gender, age, body mass index (BMI), smoke, smoking index (SI). The following pulmonary function findings were evaluated: forced expiratory volume in 1s (FEV1), forced vital capacity (FVC), FEV1/FVC ratio. The following computed tomography (CT) findings were evaluated: appearance (bronchiectasis, pneumonectasis, atelectasis, ground-glass opacities [GGO], interstitial inflammation, thickened bronchial wall), diameter (aortic diameter, pulmonary artery diameter, MPAD/AD ratio, inferior vena cava diameter [IVCD]), tumor (volume, classification, distribution, staging [I, II, III, IV]). Mortality rates were calculated and survival curves were estimated using the Kaplan-Meier method.

RESULTS

Compared with normal pulmonary function group, PRISm group and COPD group were predominantly male, older, smoked more, poorer lung function and had shorter survival time after diagnosis. There were more abnormal images in PRISm group and COPD group than in normal lung function group (N-C group). In PRISm group and COPD group, lung cancer was found late, and the tumor volume was larger, mainly central squamous carcinoma. But the opposite was true for the N-C group. The PRISm group and COPD group had significant poor survival probability compared with the normal lung function group.

CONCLUSIONS

Considerable differences regarding basic information, pulmonary function, imaging findings and survival curves are found between normal lung function group and lung function injury group. Lung function injury (PRISm and COPD) should be taken into account in future lung cancer screening studies.

Exploring disease axes as an alternative to distinct clusters for characterizing sepsis heterogeneity

PURPOSE

Various studies have analyzed sepsis subtypes, yet the reproducibility of such results remains unclear. This study aimed to determine the reproducibility of sepsis subtypes across multiple cohorts.

METHODS

The study examined 63,547 sepsis patients from six distinct cohorts who had similar sepsis-related characteristics (vital signs, lactate, sequential organ failure assessment score, bilirubin, serum, urine output, and Glasgow coma scale). Identical cluster analysis techniques were used, employing 27 clustering schemes, and normalized mutual information (NMI), a metric ranging from 0 to 1 with higher values indicating better concordance, was employed to quantify the clustering solutions' reproducibility. Principal component analysis (PCA) was utilized to obtain the disease axis, and its uniformity across cohorts was evaluated through patterns of feature loading and correlation.

RESULTS

The reproducibility of sepsis clustering subtypes across the various studies was modest (median NMI ranging from 0.08 to 0.54). The top-down transfer learning method (model trained on cohorts with greater severity was transferred to cohorts with lower severity score) had a higher NMI value than the bottom-up approach (median [Q1, Q3]: 0.64 [0.49, 0.78] vs. 0.23 [0.2, 0.31], p < 0.001). The reproducibility was greater when the transfer solution was performed within United States (US) cohorts. The PCA analysis revealed that the correlation pattern between variables was consistent across all cohorts, and the first two disease axes were the "shock axis" and "systemic inflammatory response syndrome (SIRS) axis."

CONCLUSIONS

Cluster analysis of sepsis patients across various cohorts showed modest reproducibility. Sepsis heterogeneity is better characterized through continuous disease axes that coexist to varying degrees within the same individual instead of mutually exclusive subtypes.

Deep Learning Integration of Chest Computed Tomography Imaging and Gene Expression Identifies Novel Aspects of COPD

Rationale

Chronic obstructive pulmonary disease (COPD) is characterized by pathologic changes in the airways, lung parenchyma, and persistent inflammation, but the links between lung structural changes and blood transcriptome patterns have not been fully described.

Objections

The objective of this study was to identify novel relationships between lung structural changes measured by chest computed tomography (CT) and blood transcriptome patterns measured by blood RNA sequencing (RNA-seq).

Methods

CT scan images and blood RNA-seq gene expression from 1223 participants in the COPD Genetic Epidemiology (COPDGene®) study were jointly analyzed using deep learning to identify shared aspects of inflammation and lung structural changes that we labeled image-expression axes (IEAs). We related IEAs to COPD-related measurements and prospective health outcomes through regression and Cox proportional hazards models and tested them for biological pathway enrichment.

Results

We identified 2 distinct IEAs: IEAemph which captures an emphysema-predominant process with a strong positive correlation to CT emphysema and a negative correlation to forced expiratory volume in 1 second and body mass index (BMI); and IEAairway which captures an airway-predominant process with a positive correlation to BMI and airway wall thickness and a negative correlation to emphysema. Pathway enrichment analysis identified 29 and 13 pathways significantly associated with IEAemph and IEAairway, respectively (adjusted p<0.001).

Conclusions

Integration of CT scans and blood RNA-seq data identified 2 IEAs that capture distinct inflammatory processes associated with emphysema and airway-predominant COPD.

Heterogeneity and Progression of Chronic Obstructive Pulmonary Disease: Emphysema-Predominant and Non-Emphysema-Predominant Disease

While variation in emphysema severity between patients with chronic obstructive pulmonary disease (COPD) is well-recognized, clinically applicable definitions of the emphysema-predominant disease (EPD) and non-emphysema-predominant disease (NEPD) subtypes have not been established. To study the clinical relevance of the EPD and NEPD subtypes, we tested the association of these subtypes with prospective decline in forced expiratory volume in 1 second (FEV1) and mortality among 3,427 subjects with Global Initiative for Chronic Obstructive Lung Disease (GOLD) spirometric grade 2-4 COPD at baseline in the Genetic Epidemiology of COPD (COPDGene) Study, an ongoing national multicenter study that started in 2007. NEPD was defined as airflow obstruction with less than 5% computed tomography (CT) quantitative densitometric emphysema at -950 Hounsfield units, and EPD was defined as airflow obstruction with 10% or greater CT emphysema. Mixed-effects models for FEV1 demonstrated larger average annual FEV1 loss in EPD subjects than in NEPD subjects (-10.2 mL/year; P < 0.001), and subtype-specific associations with FEV1 decline were identified. Cox proportional hazards models showed higher risk of mortality among EPD patients versus NEPD patients (hazard ratio = 1.46, 95% confidence interval: 1.34, 1.60; P < 0.001). To determine whether the NEPD/EPD dichotomy is captured by previously described COPDGene subtypes, we used logistic regression and receiver operating characteristic (ROC) curve analysis to predict NEPD/EPD membership using these previous subtype definitions. The analysis generally showed excellent discrimination, with areas under the ROC curve greater than 0.9. The NEPD and EPD COPD subtypes capture important aspects of COPD heterogeneity and are associated with different rates of disease progression and mortality.

Unsupervised Learning Identifies Computed Tomographic Measurements as Primary Drivers of Progression, Exacerbation, and Mortality in Chronic Obstructive Pulmonary Disease

Rationale: Chronic obstructive pulmonary disease (COPD) is a heterogeneous syndrome with phenotypic manifestations that tend to be distributed along a continuum. Unsupervised machine learning based on broad selection of imaging and clinical phenotypes may be used to identify primary variables that define disease axes and stratify patients with COPD. Objectives: To identify primary variables driving COPD heterogeneity using principal component analysis and to define disease axes and assess the prognostic value of these axes across three outcomes: progression, exacerbation, and mortality. Methods: We included 7,331 patients between 39 and 85 years old, of whom 40.3% were Black and 45.8% were female smokers with a mean of 44.6 pack-years, from the COPDGene (Genetic Epidemiology of COPD) phase I cohort (2008-2011) in our analysis. Out of a total of 916 phenotypes, 147 continuous clinical, spirometric, and computed tomography (CT) features were selected. For each principal component (PC), we computed a PC score based on feature weights. We used PC score distributions to define disease axes along which we divided the patients into quartiles. To assess the prognostic value of these axes, we applied logistic regression analyses to estimate 5-year (n = 4,159) and 10-year (n = 1,487) odds of progression. Cox regression and Kaplan-Meier analyses were performed to estimate 5-year and 10-year risk of exacerbation (n = 6,532) and all-cause mortality (n = 7,331). Results: The first PC, accounting for 43.7% of variance, was defined by CT measures of air trapping and emphysema. The second PC, accounting for 13.7% of variance, was defined by spirometric and CT measures of vital capacity and lung volume. The third PC, accounting for 7.9% of the variance, was defined by CT measures of lung mass, airway thickening, and body habitus. Stratification of patients across each disease axis revealed up to 3.2-fold (95% confidence interval [CI] 2.4, 4.3) greater odds of 5-year progression, 5.4-fold (95% CI 4.6, 6.3) greater risk of 5-year exacerbation, and 5.0-fold (95% CI 4.2, 6.0) greater risk of 10-year mortality between the highest and lowest quartiles. Conclusions: Unsupervised learning analysis of the COPDGene cohort reveals that CT measurements may bolster patient stratification along the continuum of COPD phenotypes. Each of the disease axes also individually demonstrate prognostic potential, predictive of future forced expiratory volume in 1 second decline, exacerbation, and mortality.

[Alpha 1-antitrypsin deficiency]

INTRODUCTION

Pulmonary emphysema and liver disease are the clinical expressions of alpha 1-antitrypsin deficiency, an autosomal recessive genetic disease.

STATE OF THE ART

Alpha 1-antitrypsin deficiency is usually associated with the homozygous Z variant of the SERPINA1 gene. Its clinical expression always consists in a substantial reduction of alpha 1-antitrypsin serum concentration and its variants are analyzed by isoelectric focalization or molecular techniques. Assessed by CO transfer alteration and CT scan, risk of pulmonary emphysema is increased by tobacco consumption. Assessed by transient elastography and liver ultrasound, risk of liver disease is increased by alcohol consumption or obesity. Treatment of COPD-associated alpha 1-antitrypsin deficiency does not differ from that of other forms of COPD. In patients presenting with severe deficiency, augmentation therapy with plasma-derived alpha 1-antitrypsin reduces the progression of emphysema, as shown in terms of CT-based lung density metrics. Patients with alpha 1-antitrypsin deficiency with a ZZ genotype should refrain from alcohol or tobacco consumption, and watch their weight; so should their close relatives.

PERSPECTIVES

Modulation of alpha 1-antitrypsin liver production offers an interesting new therapeutic perspective.

CONCLUSION

Homozygous (Z) variants of the SERPINA1 gene confer an increased risk of pulmonary emphysema and liver disease, particularly among smokers, drinkers and obese persons.

Detection and staging of chronic obstructive pulmonary disease using a computed tomography-based weakly supervised deep learning approach

OBJECTIVES

Chronic obstructive pulmonary disease (COPD) is underdiagnosed globally. The present study aimed to develop weakly supervised deep learning (DL) models that utilize computed tomography (CT) image data for the automated detection and staging of spirometry-defined COPD.

METHODS

A large, highly heterogeneous dataset was established, consisting of 1393 participants retrospectively recruited from outpatient, inpatient, and physical examination center settings of four large public hospitals in China. All participants underwent both inspiratory chest CT scans and pulmonary function tests. CT images, spirometry data, demographic information, and clinical information of each participant were collected. An attention-based multi-instance learning (MIL) model for COPD detection was trained using CT scans from 837 participants. External validation of the COPD detection was performed with 620 low-dose CT (LDCT) scans acquired from the National Lung Screening Trial (NLST) cohort. A multi-channel 3D residual network was further developed to categorize GOLD stages among confirmed COPD patients.

RESULTS

The attention-based MIL model used for COPD detection achieved an area under the receiver operating characteristic curve (AUC) of 0.934 (95% CI: 0.903, 0.961) on the internal test set and 0.866 (95% CI: 0.805, 0.928) on the LDCT subset acquired from the NLST. The multi-channel 3D residual network was able to correctly grade 76.4% of COPD patients in the test set (423/553) using the GOLD scale.

CONCLUSIONS

The proposed chest CT-DL approach can automatically identify spirometry-defined COPD and categorize patients according to the GOLD scale. As such, this approach may be an effective case-finding tool for COPD diagnosis and staging.

KEY POINTS

• Chronic obstructive pulmonary disease is underdiagnosed globally, particularly in developing countries. • The proposed chest computed tomography (CT)-based deep learning (DL) approaches could accurately identify spirometry-defined COPD and categorize patients according to the GOLD scale. • The chest CT-DL approach may be an alternative case-finding tool for COPD identification and evaluation.

Different Risks of Mortality and Longitudinal Transition Trajectories in New Potential Subtypes of the Preserved Ratio Impaired Spirometry: Evidence From the English Longitudinal Study of Aging

Background: Preserved ratio impaired spirometry (PRISm), characterized by the decreased forced expiratory volume in 1 s (FEV₁) and forced vital capacity (FVC) with a preserved FEV₁/FVC ratio, is highly prevalent and heterogeneous. We aimed to identify the subtypes of PRISm and examine their differences in clinical characteristics, long-term mortality risks, and longitudinal transition trajectories.

Methods: A total of 6,616 eligible subjects were included from the English longitudinal study of aging. Two subtypes of the PRISm were identified as mild PRISm (either of FEV₁ and FVC <80% predicted value, FEV₁/FVC ≥0.7) and severe PRISm (both FEV₁ and FVC <80% predicted values, FEV₁/FVC ≥0.7). Normal spirometry was defined as both FEV₁ and FVC ≥80% predicted values and FEV₁/FVC ≥0.7. Hazard ratios (HRs) and 95% CIs were calculated by the multiple Cox regression models. Longitudinal transition trajectories were described with repeated spirometry data.

Results: At baseline, severe PRISm had increased respiratory symptoms, including higher percentages of phlegm, wheezing, dyspnea, chronic bronchitis, and emphysema than mild PRISm. After an average of 7.7 years of follow-up, severe PRISm significantly increased the risks of all-cause mortality (HR=1.91, 95%CI = 1.58–2.31), respiratory mortality (HR = 6.02, 95%CI = 2.83–12.84), and CVD mortality (HR = 2.11, 95%CI = 1.42–3.13) compared with the normal spirometry, but no significantly increased risks were found for mild PRISm. In the two longitudinal transitions, mild PRISm tended to transition toward normal spirometry (40.2 and 54.7%), but severe PRISm tended to maintain the status (42.4 and 30.4%) or transition toward Global Initiative for Chronic Obstructive Lung Disease (GOLD)2–4 (28.3 and 33.9%).

Conclusion: Two subtypes of PRISm were identified. Severe PRISm had increased respiratory symptoms, higher mortality risks, and a higher probability of progressing to GOLD2–4 than mild PRISm. These findings provided new evidence for the stratified management of PRISm.

Emphysema-Predominant COPD Had a Greater 5-Year Mortality and a Worse Annual Decline in Lung Function Than Airway Obstruction-Predominant COPD or Asthma at Initial Same Degree of Airflow Obstruction

Background and Objectives: We studied whether the extent of exertional oxygen desaturation and emphysema could cause greater mortality in COPD and asthma independent of airflow obstruction. Materials and Methods: We performed a 5-year longitudinal observational study in COPD and asthma patients who matched for airflow obstruction severity. All subjects performed a 6-min walk test (6MWT) and high-resolution computed tomography (HRCT) and followed spirometry and oxygen saturation (SpO2) during the 6MWT every 3-6 months. Overall survival was recorded. Cumulative survival curves were performed according to the Kaplan-Meier method and compared with the log-rank test. Results: The COPD group had higher emphysema scores, higher Δinspiratory capacities (ICs) and lower SpO2 during the 6MWT, which showed a greater yearly decline in FEV1 (40.6 mL) and forced vital capacity (FVC) (28 mL) than the asthma group (FEV1, 9.6 mL; FVC, 1.2 mL; p < 0.05). The emphysema-predominant COPD group had an accelerated annual decline in lung function and worse survival. The nadir SpO2 ≤ 80% and a higher emphysema score were the strong risk factors for mortality in COPD patients. Conclusions: The greater structural changes with a higher emphysema score and greater desaturation during the 6MWT in COPD may contribute to worse yearly decline in FEV1 and higher five-year mortality than in asthma patients with a similar airflow obstruction. The lowest SpO2 ≤ 80% during the 6MWT and emphysema-predominant COPD were the strong independent factors for mortality in chronic obstructive airway disease patients.

Multi-channel lung sounds intelligent diagnosis of chronic obstructive pulmonary disease

BACKGROUND

Chronic obstructive pulmonary disease (COPD) is a chronic respiratory disease that seriously threatens people's health, with high morbidity and mortality worldwide. At present, the clinical diagnosis methods of COPD are time-consuming, invasive, and radioactive. Therefore, it is urgent to develop a non-invasive and rapid COPD severity diagnosis technique suitable for daily screening in clinical practice.

RESULTS

This study established an effective model for the preliminary diagnosis of COPD severity using lung sounds with few channels. Firstly, the time-frequency-energy features of 12 channels lung sounds were extracted by Hilbert-Huang transform. And then, channels and features were screened by the reliefF algorithm. Finally, the feature sets were input into a support vector machine to diagnose COPD severity, and the performance with Bayes, decision tree, and deep belief network was compared. Experimental results show that high classification performance using only 4-channel lung sounds of L1, L2, L3, and L4 channels can be achieved by the proposed model. The accuracy, sensitivity, and specificity of mild COPD and moderate + severe COPD were 89.13%, 87.72%, and 91.01%, respectively. The classification performance rates of moderate COPD and severe COPD were 94.26%, 97.32%, and 89.93% for accuracy, sensitivity, and specificity, respectively.

CONCLUSION

This model provides a standardized evaluation with high classification performance rates, which can assist doctors to complete the preliminary diagnosis of COPD severity immediately, and has important clinical significance.

Unravelling the mechanisms driving multimorbidity in COPD to develop holistic approaches to patient-centred care

COPD is a major cause of morbidity and mortality worldwide. Multimorbidity is common in COPD patients and a key modifiable factor, which requires timely identification and targeted holistic management strategies to improve outcomes and reduce the burden of disease.We discuss the use of integrative approaches, such as cluster analysis and network-based theory, to understand the common and novel pathobiological mechanisms underlying COPD and comorbid disease, which are likely to be key to informing new management strategies.Furthermore, we discuss the current understanding of mechanistic drivers to multimorbidity in COPD, including hypotheses such as multimorbidity as a result of shared common exposure to noxious stimuli (e.g. tobacco smoke), or as a consequence of loss of function following the development of pulmonary disease. In addition, we explore the links to pulmonary disease processes such as systemic overspill of pulmonary inflammation, immune cell priming within the inflamed COPD lung and targeted messengers such as extracellular vesicles as a result of local damage as a cause for multimorbidity in COPD.Finally, we focus on current and new management strategies which may target these underlying mechanisms, with the aim of holistic, patient-centred treatment rather than single disease management.

Pulmonary Low Attenuation Areas on CT in ANCA-associated Vasculitis: A quantitative and semi-quantitative analysis correlated with pulmonary function testing for obstructive airway disease

Objective:

A subset of ANCA-associated vasculitis (AAV) patients are known to manifest obstructive airway disease. Using low attenuation areas (LAA) in the lung on HRCT as an imaging marker for obstructive airway disease, we analyze HRCT studies in AAV patients compared to a matched non-AAV group using visual semi-quantitative and automated quantitative analysis for presence and severity of LAA. Furthermore, HRCT and pulmonary function testing are compared to assess agreement between tests for airway obstruction.

Materials and Methods:

100 randomly selected AAV patients with HRCT were compared to 100 best-fit matched control subjects. HRCT cases were visually assessed for LAA, along with additional pulmonary patterns. Automated quantitative software analyzed images for texture features and volume of attenuation values of −950 HU or less (e-950). Evidence of obstructive airway disease established by pulmonary function testing, when available, was compared to HRCT analysis for LAA. Additional clinical information, diagnostic testing and mortality data were also compared.

Results:

Both study groups were comprised of 57 females and 43 males with 35 smokers averaging 10.7 pk/yrs, with average age for the AAV and control groups being 59.4 yrs and 61.9 yrs, respectively. Visually, 46 AAV patients demonstrated LAA on HRCT compared to 25 control patients (p=0.0017) with the difference in LAA presence entirely within the non-smoking subgroup (25 to 3, respectively, p=<0.0001). Quantitatively, greater than 5% e-950 demonstrated similar significant differences between AAV (36/100) and controls (19/100) (p=0.0065), predominantly in non-smokers (p=0.006). Obstruction on PFTs was significantly increased in AAV (p=0.002) with moderate agreement of obstructive disease with visual LAA on CT (Kappa 0.509). Of the obstructive disease metrics, visual LAA on CT correlated best with mortality (p=0.0085).

Conclusion:

Visual LAA and automated quantitative analysis for e-950 on HRCT demonstrate statistically significant increases in AAV patients compared to age, gender and smoking matched controls, with differences primarily seen in the non-smoking subset. AAV revealed statistically significant greater obstructive pulmonary disease on PFTs (Sarcoidosis Vasc Diffuse Lung Dis 2020; 37 (4): e2020016)

Co-Morbidity Patterns Identified Using Latent Class Analysis of Medications Predict All-Cause Mortality Independent of Other Known Risk Factors: The COPDGene® Study

PURPOSE

Medication patterns include all medications in an individual's clinical profile. We aimed to identify chronic co-morbidity treatment patterns through medication use among COPDGene participants and determine whether these patterns were associated with mortality, acute exacerbations of chronic obstructive pulmonary disease (AECOPD) and quality of life.

MATERIALS AND METHODS

Participants analyzed here completed Phase 1 (P1) and/or Phase 2 (P2) of COPDGene. Latent class analysis (LCA) was used to identify medication patterns and assign individuals into unobserved LCA classes. Mortality, AECOPD, and the St. George's Respiratory Questionnaire (SGRQ) health status were compared in different LCA classes through survival analysis, logistic regression, and Kruskal-Wallis test, respectively.

RESULTS

LCA identified 8 medication patterns from 32 classes of chronic comorbid medications. A total of 8110 out of 10,127 participants with complete covariate information were included. Survival analysis adjusted for covariates showed, compared to a low medication use class, mortality was highest in participants with hypertension+diabetes+statin+antiplatelet medication group. Participants in hypertension+SSRI+statin medication group had the highest odds of AECOPD and the highest SGRQ score at both P1 and P2.

CONCLUSION

Medication pattern can serve as a good indicator of an individual's comorbidities profile and improves models predicting clinical outcomes.

[Lung sounds can be used as an indicator for assessing severity of chronic obstructive pulmonary disease at the initial diagnosis]

OBJECTIVE

To assess the value of pulmonary auscultation for evaluating the severity of chronic obstructive pulmonary disease (COPD) at the initial diagnosis.

METHODS

The patients with newly diagnosed COPD in our hospital between May, 2016 and May, 2019 were enrolled in this study. According to the findings of pulmonary auscultation, the lung sounds were classified into 5 groups: normal breathing sounds, weakened breathing sounds, weakened breathing sounds with wheezing, obviously weakened breathing sounds, and obviously weakened breathing sounds with wheezing. The pulmonary function of the patients was graded according to GOLD guidelines, and the differential diagnosis of COPD from asthmatic asthma COPD overlap (ACO) was made based on the GOLD guidelines and the European Respiratory Criteria.

RESULTS

A total of 1046 newly diagnosed COPD patients were enrolled, including 949 male and 97 female patients with a mean age of 62.6± 8.71. According to the GOLD criteria, 88.1% of the patients were identified to have moderate or above COPD, 50.0% to have severe or above COPD; a further diagnosis of ACO was made in 347 (33.2%) of the patients. ANOVA analysis showed significant differences in disease course, FEV1, FEV1%, FEV1/FVC, FVC, FVC% and mMRC among the 5 auscultation groups (P < 0.001), but FENO did not differ significantly among them (P=0.097). The percentage of patients with wheezing in auscultation was significantly greater in ACO group than in COPD group (P < 0.001). Spearman correlation analysis showed that lung sounds was significantly correlated with disease severity, FEV1, FEV1%, FVC and FVC% of the patients (P < 0.001); Multiple linear regression analysis showed that a longer disease course, a history of smoking and lung sounds were all associated with poorer lung functions and a greater disease severity.

CONCLUSIONS

Lung sounds can be used as an indicator for assessing the severity of COPD at the initial diagnosis.

Triple therapy for COPD: a crude analysis from a systematic review of the evidence

We systematically reviewed the current knowledge on fixed-dose triple therapies for the treatment of chronic obstructive pulmonary disease (COPD), with a specific focus on its efficacy versus single bronchodilation, double fixed dose combinations, and open triple therapies. Articles were retrieved from PubMed, Embase, and Scopus up to 3 August 2018. We selected articles with randomized controlled or crossover design conducted in patients with COPD and published as full-length articles or scientific letters, evaluating triple therapy combinations in a single or different inhaler, and with efficacy data versus monocomponents, double combinations, or open triple therapies. Our systematic search reported 108 articles, of which 24 trials were finally selected for the analysis. A total of 7 studies with fixed dose triple therapy combinations, and 17 studies with open triple therapies combinations. Triple therapy showed improvements in lung function [trough forced expiratory volume (FEV₁₎ ranging from not significant (NS) to 147 ml], health status using the St. George’s Respiratory Questionnaire [(SGRQ) from NS to 8.8 points], and exacerbations [risk ratio (RR) from NS to 0.59 for all exacerbations] versus single or double therapies with a variability in the response, depending the specific combination, and the comparison group. The proportion of adverse effects was similar between study groups, the exception being the increase in pneumonia for some inhaled corticosteroid (ICS) containing groups.

The reviews of this paper are available via the supplementary material section.

Machine Learning Characterization of COPD Subtypes: Insights From the COPDGene Study

COPD is a heterogeneous syndrome. Many COPD subtypes have been proposed, but there is not yet consensus on how many COPD subtypes there are and how they should be defined. The COPD Genetic Epidemiology Study (COPDGene), which has generated 10-year longitudinal chest imaging, spirometry, and molecular data, is a rich resource for relating COPD phenotypes to underlying genetic and molecular mechanisms. In this article, we place COPDGene clustering studies in context with other highly cited COPD clustering studies, and summarize the main COPD subtype findings from COPDGene. First, most manifestations of COPD occur along a continuum, which explains why continuous aspects of COPD or disease axes may be more accurate and reproducible than subtypes identified through clustering methods. Second, continuous COPD-related measures can be used to create subgroups through the use of predictive models to define cut-points, and we review COPDGene research on blood eosinophil count thresholds as a specific example. Third, COPD phenotypes identified or prioritized through machine learning methods have led to novel biological discoveries, including novel emphysema genetic risk variants and systemic inflammatory subtypes of COPD. Fourth, trajectory-based COPD subtyping captures differences in the longitudinal evolution of COPD, addressing a major limitation of clustering analyses that are confounded by disease severity. Ongoing longitudinal characterization of subjects in COPDGene will provide useful insights about the relationship between lung imaging parameters, molecular markers, and COPD progression that will enable the identification of subtypes based on underlying disease processes and distinct patterns of disease progression, with the potential to improve the clinical relevance and reproducibility of COPD subtypes.

NR, Make BJ, Marchetti N, Martinez FJ, Maselli DJ, Mathews AM, McCormack MC, McDonald MLN, McEvoy CE, Moll M, Molye SS, Murray S, Nath H, Newell Jr. JD, Occhipinti M, Paoletti M, Parekh T, Pistolesi M, Pratte KA, Putcha N, Ragland M, Reinhardt JM, Rennard SI, Rosiello RA, Ross JC, Rossiter HB, Ruczinski I, San Jose Estepar R, Sciurba FC, Sieren JC, Singh H, Soler X, Steiner RM, Strand MJ, Stringer WW, Tal-Singer R, Thomashow B, Vegas Sánchez-Ferrero G, Walsh JW, Wan ES, Washko GR, Michael Wells J, Wendt CH, Westney G, Wilson A, Wise RA, Yen A, Young K, Yun J, Silverman EK, Crapo JD. COPDGene® 2019: Redefining the Diagnosis of Chronic Obstructive Pulmonary Disease

BACKGROUND

Chronic obstructive pulmonary disease (COPD) remains a major cause of morbidity and mortality. Present-day diagnostic criteria are largely based solely on spirometric criteria. Accumulating evidence has identified a substantial number of individuals without spirometric evidence of COPD who suffer from respiratory symptoms and/or increased morbidity and mortality. There is a clear need for an expanded definition of COPD that is linked to physiologic, structural (computed tomography [CT]) and clinical evidence of disease. Using data from the COPD Genetic Epidemiology study (COPDGene®), we hypothesized that an integrated approach that includes environmental exposure, clinical symptoms, chest CT imaging and spirometry better defines disease and captures the likelihood of progression of respiratory obstruction and mortality.

METHODS

Four key disease characteristics - environmental exposure (cigarette smoking), clinical symptoms (dyspnea and/or chronic bronchitis), chest CT imaging abnormalities (emphysema, gas trapping and/or airway wall thickening), and abnormal spirometry - were evaluated in a group of 8784 current and former smokers who were participants in COPDGene® Phase 1. Using these 4 disease characteristics, 8 categories of participants were identified and evaluated for odds of spirometric disease progression (FEV1 > 350 ml loss over 5 years), and the hazard ratio for all-cause mortality was examined.

RESULTS

Using smokers without symptoms, CT imaging abnormalities or airflow obstruction as the reference population, individuals were classified as Possible COPD, Probable COPD and Definite COPD. Current Global initiative for obstructive Lung Disease (GOLD) criteria would diagnose 4062 (46%) of the 8784 study participants with COPD. The proposed COPDGene® 2019 diagnostic criteria would add an additional 3144 participants. Under the new criteria, 82% of the 8784 study participants would be diagnosed with Possible, Probable or Definite COPD. These COPD groups showed increased risk of disease progression and mortality. Mortality increased in patients as the number of their COPD characteristics increased, with a maximum hazard ratio for all cause-mortality of 5.18 (95% confidence interval [CI]: 4.15-6.48) in those with all 4 disease characteristics.

CONCLUSIONS

A substantial portion of smokers with respiratory symptoms and imaging abnormalities do not manifest spirometric obstruction as defined by population normals. These individuals are at significant risk of death and spirometric disease progression. We propose to redefine the diagnosis of COPD through an integrated approach using environmental exposure, clinical symptoms, CT imaging and spirometric criteria. These expanded criteria offer the potential to stimulate both current and future interventions that could slow or halt disease progression in patients before disability or irreversible lung structural changes develop.

Turning subtypes into disease axes to improve prediction of COPD progression

Chronic obstructive pulmonary disease (COPD) is an umbrella definition encompassing multiple disease processes. COPD heterogeneity has been described as distinct subgroups of individuals (subtypes) or as continuous measures of COPD variability (disease axes). There is little consensus on whether subtypes or disease axes are preferred, and the relative value of disease axes and subtypes for predicting COPD progression is unknown. Using a propensity score approach to learn disease axes from pairs of subtypes, we demonstrate that these disease axes predict prospective forced expiratory volume in 1 s decline and emphysema progression more accurately than the subtype pairs from which they were derived.

Pulmonary Subtypes Exhibit Differential Global Initiative for Chronic Obstructive Lung Disease Spirometry Stage Progression: The COPDGene® Study

Rationale

We classified individuals into pulmonary disease subtypes based on 2 underlying pathophysiologic disease axes (airway-predominant and emphysema-predominant) and their increased mortality risk. Our next objective was to determine whether some subcomponents of these subtypes are additionally associated with unique patterns of Global initiative for chronic Obstructive Lung Disease (GOLD) spirometry stage progression.

Methods

After accounting for intra-individual measurement variability in spirometry measures between baseline (Phase 1) and the 5-year follow up (Phase 2) of the COPD Genetic Epidemiology (COPDGene^®) study, 4615 individuals had complete data that would characterize patterns of disease progression over 5 years (2033 non-Hispanic whites; 827 African Americans; 48% female). Individuals could express increased risk for mortality on one or both of the primary subtype axes (airway-predominant or emphysema-predominant) and thus they were further classified into 6 groups: high-risk airway-predominant disease only (APD-only), moderate-risk airway-predominant disease only (MR-APD-only), high-risk emphysema-predominant disease only (EPD-only), combined high-risk airway- and emphysema-predominant disease (combined APD-EPD), combined moderate-risk airway- and emphysema-predominant disease (combined MR-APD-EPD), and no high-risk pulmonary subtype. Outcomes were dichotomized for GOLD spirometry stage progression from Phase 1 to Phase 2. Logistic regression of the progression outcomes on the pulmonary subtypes were adjusted for age, sex, race, and change in smoking status.

Results

The MR-APD-only group was associated with conversion from GOLD 0 to preserved ratio-impaired spirometry (PRISm) status (odds ratio [OR] 11.3, 95% confidence interval [CI] 5.7-22.1) and GOLD 0 to GOLD 2-4 (OR 6.0, 95% CI 2.0-18.0). The EPD-only group was associated with conversion from GOLD 0 to GOLD 1 (OR 2.4, 95% CI 1.2-4.6), and GOLD 1 to GOLD 2-4 (OR 2.6, 95% CI 1.0-6.9). Conversion between PRISm and GOLD 2-4 (31%-38%) occurred in both the APD-only and the MR-APD-only groups.

Conclusion

Differential conversion occurs from GOLD 0 to PRISm and GOLD 0 to GOLD 1 based on groups expressing airway-predominant disease or emphysema-predominant disease independently or in combination. Airway-predominant and emphysema-predominant subtypes are highly important in determining patterns of early disease progression.

Subtypes of COPD Have Unique Distributions and Differential Risk of Mortality

Background

Previous attempts to explore the heterogeneity of chronic obstructive pulmonary disease (COPD) clustered individual patients using clinical, demographic, and disease features. We developed continuous multidimensional disease axes based on radiographic and spirometric variables that split into an airway-predominant axis and an emphysema-predominant axis.

Methods

The COPD Genetic Epidemiology study (COPDGene^®) is a cohort of current and former smokers, > 45 years, with at least 10 pack years of smoking history. Spirometry measures, blood pressure and body mass were directly measured. Mortality was assessed through continuing longitudinal follow-up and cause of death was adjudicated. Among 8157 COPDGene^® participants with complete spirometry and computed tomography (CT) measures, the top 2 deciles of the airway-predominant and emphysema-predominant axes previously identified were used to categorize individuals into 3 groups having the highest risk for mortality using Cox proportional hazard ratios. These groups were also assessed for causal mortality. Biomarkers of COPD (fibrinogen, soluble receptor for advanced glycation end products [sRAGE], C-reactive protein [CRP], clara cell secretory protein [CC16], surfactant-D [SP-D]) were compared by group.

Findings

High-risk subtype classification was defined for 2638 COPDGene^® participants who were in the highest 2 deciles of either the airway-predominant and/or emphysema-predominant axis (32% of the cohort). These high-risk participants fell into 3 groups: airway-predominant disease only (APD-only), emphysema-predominant disease only (EPD-only) and combined APD-EPD. There was 26% mortality for the APD-only group, 21% mortality for the EPD-only group, and 54% mortality for the combined APD-EPD group. The APD-only group (n=1007) was younger, had a lower forced expiratory volume in 1 second (FEV₁) percent (%) predicted and a strong association with the preserved ratio-impaired spirometry (PRISm) quadrant. The EPD-only group (n=1006) showed a relatively higher FEV₁ % predicted and included largely GOLD stage 0, 1 and 2 partipants. Individuals in each of the 3 high-risk groups were at greater risk for respiratory mortality, while those in the APD-only group were additionally at greater risk for cardiovascular mortality. Biomarker analysis demonstrated a significant association of the APD-only group with CRP, and sRAGE demonstrated greatest significance with both the EPD-only and the combined APD-EPD groups.

Interpretation

Among current and former smokers, individuals in the highest 2 deciles for mortality risk on the airway-predominant axis and the emphysema-predominant axis have unique associations to spirometric patterns, different imaging characteristics, biomarkers and causal mortality.