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.

Author Correction: New genetic signals for lung function highlight pathways and chronic obstructive pulmonary disease associations across multiple ancestries

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Apolipoprotein E-C1-C4-C2 gene cluster region and inter-individual variation in plasma lipoprotein levels: a comprehensive genetic association study in two ethnic groups

The apolipoprotein E-C1-C4-C2 gene cluster at 19q13.32 encodes four amphipathic apolipoproteins. The influence of APOE common polymorphisms on plasma lipid/lipoprotein profile, especially on LDL-related traits, is well recognized; however, little is known about the role of other genes/variants in this gene cluster. In this study, we evaluated the role of common and uncommon/rare genetic variation in this gene region on inter-individual variation in plasma lipoprotein levels in non-Hispanic Whites (NHWs) and African blacks (ABs). In the variant discovery step, the APOE, APOC1, APOC4, APOC2 genes were sequenced along with their flanking and hepatic control regions (HCR1 and HCR2) in 190 subjects with extreme HDL-C/TG levels. The next step involved the genotyping of 623 NHWs and 788 ABs for the identified uncommon/rare variants and common tagSNPs along with additional relevant SNPs selected from public resources, followed by association analyses with lipid traits. A total of 230 sequence variants, including 15 indels were identified, of which 65 were novel. A total of 70 QC-passed variants in NHWs and 108 QC-passed variants in ABs were included in the final association analyses. Single-site association analysis of SNPs with MAF>1% revealed 20 variants in NHWs and 24 variants in ABs showing evidence of association with at least one lipid trait, including several variants exhibiting independent associations from the established APOE polymorphism even after multiple-testing correction. Overall, our study has confirmed known associations and also identified novel associations in this genomic region with various lipid traits. Our data also support the contribution of both common and uncommon/rare variation in this gene region in affecting plasma lipid profile in the general population.

New genetic signals for lung function highlight pathways and chronic obstructive pulmonary disease associations across multiple ancestries

Reduced lung function predicts mortality and is key to the diagnosis of chronic obstructive pulmonary disease (COPD). In a genome-wide association study in 400,102 individuals of European ancestry, we define 279 lung function signals, 139 of which are new. In combination, these variants strongly predict COPD in independent populations. Furthermore, the combined effect of these variants showed generalizability across smokers and never smokers, and across ancestral groups. We highlight biological pathways, known and potential drug targets for COPD and, in phenome-wide association studies, autoimmune-related and other pleiotropic effects of lung function-associated variants. This new genetic evidence has potential to improve future preventive and therapeutic strategies for COPD.

Genetic landscape of chronic obstructive pulmonary disease identifies heterogeneous cell-type and phenotype associations

Chronic obstructive pulmonary disease (COPD) is the leading cause of respiratory mortality worldwide. Genetic risk loci provide new insights into disease pathogenesis. We performed a genome-wide association study in 35,735 cases and 222,076 controls from the UK Biobank and additional studies from the International COPD Genetics Consortium. We identified 82 loci associated with P < 5 × 10-8; 47 of these were previously described in association with either COPD or population-based measures of lung function. Of the remaining 35 new loci, 13 were associated with lung function in 79,055 individuals from the SpiroMeta consortium. Using gene expression and regulation data, we identified functional enrichment of COPD risk loci in lung tissue, smooth muscle, and several lung cell types. We found 14 COPD loci shared with either asthma or pulmonary fibrosis. COPD genetic risk loci clustered into groups based on associations with quantitative imaging features and comorbidities. Our analyses provide further support for the genetic susceptibility and heterogeneity of COPD.

Assessing pleiotropy and mediation in genetic loci associated with chronic obstructive pulmonary disease

Genetic association studies have increasingly recognized variant effects on multiple phenotypes. Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease with environmental and genetic causes. Multiple genetic variants have been associated with COPD, many of which show significant associations to additional phenotypes. However, it is unknown if these associations represent biological pleiotropy or if they exist through correlation of related phenotypes ("mediated pleiotropy"). Using 6,670 subjects from the COPDGene study, we describe the association of known COPD susceptibility loci with other COPD-related phenotypes and distinguish if these act directly on the phenotypes (i.e., biological pleiotropy) or if the association is due to correlation (i.e., mediated pleiotropy). We identified additional associated phenotypes for 13 of 25 known COPD loci. Tests for pleiotropy between genotype and associated outcomes were significant for all loci. In cases of significant pleiotropy, we performed mediation analysis to test if SNPs had a direct association to phenotype. Most loci showed a mediated effect through the hypothesized causal pathway. However, many loci also had direct associations, suggesting causal explanations (i.e., emphysema leading to reduced lung function) are incomplete. Our results highlight the high degree of pleiotropy in complex disease-associated loci and provide novel insights into the mechanisms underlying COPD.

Association studies of up to 1.2 million individuals yield new insights into the genetic etiology of tobacco and alcohol use

Tobacco and alcohol use are leading causes of mortality that influence risk for many complex diseases and disorders1. They are heritable2,3 and etiologically related4,5 behaviors that have been resistant to gene discovery efforts6-11. In sample sizes up to 1.2 million individuals, we discovered 566 genetic variants in 406 loci associated with multiple stages of tobacco use (initiation, cessation, and heaviness) as well as alcohol use, with 150 loci evidencing pleiotropic association. Smoking phenotypes were positively genetically correlated with many health conditions, whereas alcohol use was negatively correlated with these conditions, such that increased genetic risk for alcohol use is associated with lower disease risk. We report evidence for the involvement of many systems in tobacco and alcohol use, including genes involved in nicotinic, dopaminergic, and glutamatergic neurotransmission. The results provide a solid starting point to evaluate the effects of these loci in model organisms and more precise substance use measures.

Mortality and Exacerbations by Global Initiative for Chronic Obstructive Lung Disease Groups ABCD: 2011 Versus 2017 in the COPDGene® Cohort

Background: The Global initiative for chronic Obstructive Lung Disease (GOLD) ABCD groupings were recently modified. The GOLD 2011 guidelines defined increased risk as forced expiratory volume in 1 second (FEV₁) < 50% predicted or ≥ 2 outpatient or ≥ 1 hospitalized exacerbation in the prior year, whereas the GOLD 2017 guidelines use only exacerbation history. We compared mortality and exacerbation rates in the Genetic Epidemiology of COPD Study cohort (COPDGene^®) by 2011 (exacerbation history/FEV₁ and dyspnea) versus 2017 (exacerbations and dyspnea) classifications. Methods: Using data from COPDGene^®, we tested associations of ABCD groups with all-cause mortality (Cox models, adjusted for age, sex, race and comorbidities) and longitudinal exacerbations (zero-inflated Poisson models). Results: In 4469 individuals (mean age 63.1 years, 44% female), individual distributions in 2011 versus 2017 systems were: A, 32.0% versus 37.0%; B, 17.6% versus 36.3%; C, 9.4% versus 4.4%; D, 41.0% versus 22.3%; (observed agreement 76% [expected 27.8%], Kappa 0.67, p<0.001). Individuals in group D-2011 had 1.1 ± 1.6 exacerbations/year (mean ± standard deviation [SD]) versus 1.4 ± 1.8 for D-2017 (median follow-up 3.7 years). Using group A as reference, for both systems, mortality (median follow-up 6.8 years) was highest in group D (D-2011, [hazard ratio] HR 5.2 [95% confidence interval (CI) 4.2, 6.4]; D-2017, HR 5.5 [4.5, 6.8]), lowest for group C (HR 1.9 [1.4, 2.6] versus HR 1.9 [1.3, 2.8]) and intermediate for group B (HR 2.6 [2.0, 3.4] versus HR 3.4 [2.8, 4.1]). GOLD 2011 had better mortality discrimination (area under the curve [AUC] 0.68) than GOLD 2017 (AUC 0.66, p<0.001 for comparison) but similar exacerbation rate prediction. Conclusions: Relative to the GOLD 2011 consensus statement, discriminate predictive power of the 2017 ABCD classification is similar for exacerbations but lower for survival.

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.

Identifying Smoking-Related Disease on Lung Cancer Screening CT Scans: Increasing the Value

Background

Lung cancer screening (LCS) via chest computed tomography (CT) scans can save lives by identifying early-stage tumors. However, most smokers die of comorbid smoking-related diseases. LCS scans contain information about smoking-related conditions that is not currently systematically assessed. Identifying these common comorbid diseases on CT could increase the value of screening with minimal impact on LCS programs. We determined the prevalence of 3 comorbid diseases from LCS eligible scans and quantified related adverse outcomes.

Methods

We studied COPD Genetic Epidemiology study (COPDGene^®) participants (n=4078) who met criteria for LCS screening at enrollment (age > 55 years, and < 80 years, > 30 pack years smoking, current smoker or former smoker within 15 years of smoking cessation). CT scans were assessed for coronary artery calcification (CAC), emphysema, and vertebral bone density. We tracked the following clinically significant events: myocardial infarctions (MIs), strokes, pneumonia, respiratory exacerbations, and hip and vertebral fractures.

Results

Overall, 77% of eligible CT scans had one or more of these diagnoses identified. CAC (> 100 mg) was identified in 51% of scans, emphysema in 44%, and osteoporosis in 54%. Adverse events related to the underlying smoking-related diseases were common, with 50% of participants reporting at least one. New diagnoses of cardiovascular disease, emphysema and osteoporosis were made in 25%, 7% and 46%, of participants respectively. New diagnosis of disease was associated with significantly more adverse events than in participants who did not have CT diagnoses for both osteoporosis and cardiovascular risk.

Conclusions

Expanded analysis of LCS CT scans identified individuals with evidence of previously undiagnosed cardiovascular disease, emphysema or osteoporosis that corresponded with adverse events. LCS CT scans can potentially facilitate diagnoses of these smoking-related diseases and provide an opportunity for treatment or prevention.

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.

Association of low income with pulmonary disease progression in smokers with and without chronic obstructive pulmonary disease

Low socioeconomic status has been associated with chronic obstructive pulmonary disease (COPD) but little is known about its impact on disease progression. We assessed the association of income to symptoms, pulmonary disease severity and progression in smokers with and without COPD.

The COPDGene cohort of 4826 smokers who reported annual income in phase 2 was analysed. Those who reported annual income <USD 15 000 per year were “low-income” and the remainder “higher income”. Baseline demographics, symptoms, computed tomography (CT) imaging, and 5-year change in spirometry and CT metrics were characterised by group.

The low income group was younger (55.7 versus 61.7, p<0.0001), had more current smokers (73% versus 36%, p<0.0001), higher rates of severe exacerbations (13% versus 7%, p<0.0001), more chronic bronchitis (22% versus 14%, p<0.0001), reduced access to preventative care and lower quality of life, but less emphysema (4.7% versus 6.2%, p<0.0001). After 5 years the low-income group had more smoking-related disease progression, without significant change in exacerbations or symptoms, than higher-income subjects. Low income was an independent predictor of decreasing forced expiratory volume in 1 s (FEV₁) (p=0.001) and increased airway disease (p=0.007) after adjusting for baseline FEV₁, age, sex, race, exposures and current smoking.

Income disparity beyond the effects of race and current smoking is an important factor for disease progression. Worldwide, poverty and its consequences: associated respiratory exposures, limited healthcare access, and inadequate education about smoking risks, may exacerbate chronic lung disease.

Income is a factor in predicting pulmonary disease progression in smokers with and without COPD; those with lower income experience faster progression and worse symptomshttp://ow.ly/1SSe30lU1cX

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

Chronic obstructive pulmonary disease (COPD) is a syndrome caused by damage to the lungs that results in decreased pulmonary function and reduced structural integrity. Pulmonary function testing (PFT) is used to diagnose and stratify COPD into severity groups, and computed tomography (CT) imaging of the chest is often used to assess structural changes in the lungs. We hypothesized that the combination of PFT and CT phenotypes would provide a more powerful tool for assessing underlying morphologic differences associated with pulmonary function in COPD than does PFT alone. We used factor analysis of 26 variables to classify 8,157 participants recruited into the COPDGene cohort between January 2008 and June 2011 from 21 clinical centers across the United States. These factors were used as predictors of all-cause mortality using Cox proportional hazards modeling. Five factors explained 80% of the covariance and represented the following domains: factor 1, increased emphysema and decreased pulmonary function; factor 2, airway disease and decreased pulmonary function; factor 3, gas trapping; factor 4, CT variability; and factor 5, hyperinflation. After more than 46,079 person-years of follow-up, factors 1 through 4 were associated with mortality and there was a significant synergistic interaction between factors 1 and 2 on death. Considering CT measures along with PFT in the assessment of COPD can identify patients at particularly high risk for death.

Genome-wide association study across European and African American ancestries identifies a SNP in DNMT3B contributing to nicotine dependence

Cigarette smoking is a leading cause of preventable mortality worldwide. Nicotine dependence, which reduces the likelihood of quitting smoking, is a heritable trait with firmly established associations with sequence variants in nicotine acetylcholine receptor genes and at other loci. To search for additional loci, we conducted a genome-wide association study (GWAS) meta-analysis of nicotine dependence, totaling 38,602 smokers (28,677 Europeans/European Americans and 9925 African Americans) across 15 studies. In this largest-ever GWAS meta-analysis for nicotine dependence and the largest-ever cross-ancestry GWAS meta-analysis for any smoking phenotype, we reconfirmed the well-known CHRNA5-CHRNA3-CHRNB4 genes and further yielded a novel association in the DNA methyltransferase gene DNMT3B. The intronic DNMT3B rs910083-C allele (frequency=44-77%) was associated with increased risk of nicotine dependence at P=3.7 × 10-8 (odds ratio (OR)=1.06 and 95% confidence interval (CI)=1.04-1.07 for severe vs mild dependence). The association was independently confirmed in the UK Biobank (N=48,931) using heavy vs never smoking as a proxy phenotype (P=3.6 × 10-4, OR=1.05, and 95% CI=1.02-1.08). Rs910083-C is also associated with increased risk of squamous cell lung carcinoma in the International Lung Cancer Consortium (N=60,586, meta-analysis P=0.0095, OR=1.05, and 95% CI=1.01-1.09). Moreover, rs910083-C was implicated as a cis-methylation quantitative trait locus (QTL) variant associated with higher DNMT3B methylation in fetal brain (N=166, P=2.3 × 10-26) and a cis-expression QTL variant associated with higher DNMT3B expression in adult cerebellum from the Genotype-Tissue Expression project (N=103, P=3.0 × 10-6) and the independent Brain eQTL Almanac (N=134, P=0.028). This novel DNMT3B cis-acting QTL variant highlights the importance of genetically influenced regulation in brain on the risks of nicotine dependence, heavy smoking and consequent lung cancer.

Proper conditional analysis in the presence of missing data: Application to large scale meta-analysis of tobacco use phenotypes

Meta-analysis of genetic association studies increases sample size and the power for mapping complex traits. Existing methods are mostly developed for datasets without missing values, i.e. the summary association statistics are measured for all variants in contributing studies. In practice, genotype imputation is not always effective. This may be the case when targeted genotyping/sequencing assays are used or when the un-typed genetic variant is rare. Therefore, contributed summary statistics often contain missing values. Existing methods for imputing missing summary association statistics and using imputed values in meta-analysis, approximate conditional analysis, or simple strategies such as complete case analysis all have theoretical limitations. Applying these approaches can bias genetic effect estimates and lead to seriously inflated type-I or type-II errors in conditional analysis, which is a critical tool for identifying independently associated variants. To address this challenge and complement imputation methods, we developed a method to combine summary statistics across participating studies and consistently estimate joint effects, even when the contributed summary statistics contain large amounts of missing values. Based on this estimator, we proposed a score statistic called PCBS (partial correlation based score statistic) for conditional analysis of single-variant and gene-level associations. Through extensive analysis of simulated and real data, we showed that the new method produces well-calibrated type-I errors and is substantially more powerful than existing approaches. We applied the proposed approach to one of the largest meta-analyses to date for the cigarettes-per-day phenotype. Using the new method, we identified multiple novel independently associated variants at known loci for tobacco use, which were otherwise missed by alternative methods. Together, the phenotypic variance explained by these variants was 1.1%, improving that of previously reported associations by 71%. These findings illustrate the extent of locus allelic heterogeneity and can help pinpoint causal variants.

It is of great interest to estimate the joint effects of multiple variants from large scale meta-analyses, in order to fine-map causal variants and understand the genetic architecture for complex traits. The summary association statistics from participating studies in a meta-analysis often contain missing values at some variant sites, as the imputation methods may not work well and the variants with low imputation quality will be filtered out. Missingness is especially likely when the underlying genetic variant is rare or the participating studies use targeted genotyping array that is not suitable for imputation. Existing methods for conditional meta-analysis do not properly handle missing data, and can incorrectly estimate correlations between score statistics. As a result, they can produce highly inflated type-I errors for conditional analysis, which will result in overestimated phenotypic variance explained and incorrect identification of causal variants. We systematically evaluated this bias and proposed a novel partial correlation based score statistic. The new statistic has valid type-I errors for conditional analysis and much higher power than the existing methods, even when the contributed summary statistics contain a large fraction of missing values. We expect this method to be highly useful in the sequencing age for complex trait genetics.

Race and Gender Disparities are Evident in COPD Underdiagnoses Across all Severities of Measured Airflow Obstruction

The COPD Genetic Epidemiology (COPDGene®) study provides a rich cross-sectional dataset of patients with substantial tobacco smoke exposure, varied by race, gender, chronic obstructive pulmonary disease (COPD) diagnosis, and disease. We aimed to determine the influence of race, gender and Global initiative for chronic Obstructive Lung Disease (GOLD) stage on prevalence of prior COPD diagnosis at COPDGene® enrollment. Data from the complete phase 1 cohort of 10,192 participants were analyzed. Participants were non-Hispanic white and African-American, ≥45 years of age with a minimum of 10 pack years of cigarette smoking. Characterization upon enrollment included spirometry, demographics and history of COPD diagnosis determined by questionnaire. We evaluated the effects of race and gender on the likelihood of prior diagnosis of COPD and the interaction of race and GOLD stage, and gender and GOLD stage, as determined at study enrollment, on likelihood of prior diagnosis of COPD. We evaluated the 3-way interaction of race, gender and GOLD stage on prior diagnosis. African-Americans had higher odds of not having a prior COPD diagnosis at all GOLD stages of airflow obstruction versus non-Hispanic whites (p<0.0001). Women had higher odds of having a prior COPD diagnosis at all GOLD stages versus men (p<0.0001). Three-way interaction of race, gender and GOLD stage was not significant. African-Americans were less likely to have prior COPD regardless of the severity of airflow obstruction determined at study enrollment. Women were more likely to have a prior COPD diagnosis regardless of the severity of measured airflow obstruction. Race and gender are associated with significant disparities in COPD diagnosis.

The Effects of a Comprehensive Care Management Program on Readmission Rates After Acute Exacerbation of COPD at a Community-Based Academic Hospital

Acute exacerbation of chronic obstructive pulmonary disease (AECOPD) is one of the leading causes of hospitalization in the United States. Prior investigations suggest clinical and physiological parameters are important determinants for AECOPD readmissions. Strategies aimed at addressing these factors have not resulted in a major reduction of readmissions. We compared patients readmitted after an index AECOPD admission with non-readmitted patients. Patients' age, gender, body mass index, comorbidities (obstructive sleep apnea, chronic hypercapnia, congestive heart failure, lung cancer, pulmonary arterial hypertension, pneumonia, interstitial lung disease, atrial fibrillation, musculoskeletal disorders, cognitive disorders, and anxiety disorders), substance abuse and smoking status were assessed. Some 272 patients were included: 20 patients were readmitted within 30 days of their index hospitalization; 252 patients were not readmitted within 30 days of their index admission. Readmitted patients were significantly more likely to have pneumonia than non-readmitted patients (30.0% versus 13.1%, p<0.05). No statistically significant difference was seen with respect to other clinical comorbidities. Patients readmitted within 30 days were significantly more likely than non-readmitted patients to have safety issues at home (80.0% versus. 39.3%, p<0.001), anxiety (60.0% versus 29.8%, p<0.01), and lack of transportation (35.0% versus 15.5%, p<0.05). Implementation of a comprehensive care management program (CCMP) was associated with a reduction in readmissions from 21.5% to 13.6% (p<0.01, 95% confidence interval [CI] 2.08-12.45). A CCMP can reduce readmissions through attention to social variables, optimization of in-hospital care, improved coordination of pre- and post-discharge, a system to better identify problems after discharge, and an office setup that accommodates same-day visits.

CT-based Visual Classification of Emphysema: Association with Mortality in the COPDGene Study

Purpose

To determine whether visually assessed patterns of emphysema at CT might provide a simple assessment of mortality risk among cigarette smokers.

Materials and Methods

Of the first 4000 cigarette smokers consecutively enrolled between 2007 and 2011 in this COPDGene study, 3171 had data available for both visual emphysema CT scores and survival. Each CT scan was retrospectively visually scored by two analysts using the Fleischner Society classification system. Severity of emphysema was also evaluated quantitatively by using percentage lung volume occupied by low-attenuation areas (voxels with attenuation of −950 HU or less) (LAA-950). Median duration of follow-up was 7.4 years. Regression analysis for the relationship between imaging patterns and survival was based on the Cox proportional hazards model, with adjustment for age, race, sex, height, weight, pack-years of cigarette smoking, current smoking status, educational level, LAA-950, and (in a second model) forced expiratory volume in 1 second (FEV₁).

Results

Observer agreement in visual scoring was good (weighted κ values, 0.71–0.80). There were 519 deaths in the study cohort. Compared with subjects who did not have visible emphysema, mortality was greater in those with any grade of emphysema beyond trace (adjusted hazard ratios, 1.7, 2.5, 5.0, and 4.1, respectively, for mild centrilobular emphysema, moderate centrilobular emphysema, confluent emphysema, and advanced destructive emphysema, P < .001). This increased mortality generally persisted after adjusting for LAA-950.

Conclusion

The visual presence and severity of emphysema is associated with significantly increased mortality risk, independent of the quantitative severity of emphysema.

Online supplemental material is available for this article.

Pectoralis muscle area and mortality in smokers without airflow obstruction

Background

Low muscle mass is associated with increased mortality in the general population but its prognostic value in at-risk smokers, those without expiratory airflow obstruction, is unknown. We aimed to test the hypothesis that reduced muscle mass is associated with increased mortality in at-risk smokers.

Methods

Measures of both pectoralis and paravertebral erector spinae muscle cross-sectional area (PMA and PVMA, respectively) as well as emphysema on chest computed tomography (CT) scans were performed in 3705 current and former at-risk smokers (≥10 pack-years) aged 45–80 years enrolled into the COPDGene Study between 2008 and 2013. Vital status was ascertained through death certificate. The association between low muscle mass and mortality was assessed using Cox regression analysis.

Results

During a median of 6.5 years of follow-up, 212 (5.7%) at-risk smokers died. At-risk smokers in the lowest (vs. highest) sex-specific quartile of PMA but not PVMA had 84% higher risk of death in adjusted models for demographics, smoking, dyspnea, comorbidities, exercise capacity, lung function, emphysema on CT, and coronary artery calcium content (hazard ratio [HR] 1.85 95% Confidence interval [1.14–3.00] P = 0.01). Results were consistent when the PMA index (PMA/height²) was used instead of quartiles. The association between PMA and death was modified by smoking status (P = 0.04). Current smokers had a significantly increased risk of death (lowest vs. highest PMA quartile, HR 2.25 [1.25–4.03] P = 0.007) while former smokers did not.

Conclusions

Low muscle mass as measured on chest CT scans is associated with increased mortality in current smokers without airflow obstruction.

Trial registration

NCT00608764

Electronic supplementary material

The online version of this article (10.1186/s12931-018-0771-6) contains supplementary material, which is available to authorized users.

Is the Fagerström test for nicotine dependence invariant across secular trends in smoking? A question for cross-birth cohort analysis of nicotine dependence

BACKGROUND

The Fagerström Test for Nicotine Dependence (FTND), a derivation of the Fagerström Tolerance Questionnaire, was first published in 1991. The FTND remains one of the most widely used measures of nicotine dependence for studying genetic and epidemiological risk factors and the likelihood of smoking cessation. However, it is unclear whether secular trends in patterns of smoking alter the psychometric properties of the FTND and its interpretation.

METHODS

We examined measurement invariance in the lifetime and current FTND scores across birth cohorts using participants drawn from six study samples (N = 13,775).

RESULTS

We found significant (p < 0.05) measurement non-invariance in means and factor loadings of most FTND items by birth cohort, but effect sizes, ranging from r2 = 0.0001 to r2 = 0.0035, indicated that less than 0.5% of the model variance was explained by the measurement non-invariance for each factor loading. To assess its impact, we regressed the lifetime FTND latent variable on well-established factors associated with nicotine dependence (quitting smoking and the nicotinic acetylcholine receptor gene [CHRNA5] variant rs16969968, separately), and we observed that the regression coefficients were unchanged between models with and without adjustment for measurement non-invariance.

CONCLUSIONS

These findings suggest that possible FTND non-invariance that occurs across study samples of various birth years has a negligible impact on study results.

Smoking duration alone provides stronger risk estimates of chronic obstructive pulmonary disease than pack-years

BACKGROUND

Cigarette smoking is the strongest risk factor for COPD. Smoking burden is frequently measured in pack-years, but the relative contribution of cigarettes smoked per day versus duration towards the development of structural lung disease, airflow obstruction and functional outcomes is not known.

METHODS

We analysed cross-sectional data from a large multicentre cohort (COPDGene) of current and former smokers. Primary outcome was airflow obstruction (FEV₁/FVC); secondary outcomes included five additional measures of disease: FEV₁, CT emphysema, CT gas trapping, functional capacity (6 min walk distance, 6MWD) and respiratory morbidity (St George's Respiratory Questionnaire, SGRQ). Generalised linear models were estimated to compare the relative contribution of each smoking variable with the outcomes, after adjustment for age, race, sex, body mass index, CT scanner, centre, age of smoking onset and current smoking status. We also estimated adjusted means of each outcome by categories of pack-years and combined groups of categorised smoking duration and cigarettes/day, and estimated linear trends of adjusted means for each outcome by categorised cigarettes/day, smoking duration and pack-years.

RESULTS

10 187 subjects were included. For FEV₁/FVC, standardised beta coefficient for smoking duration was greater than for cigarettes/day and pack-years (P<0.001). After categorisation, there was a linear increase in adjusted means FEV₁/FVC with increase in pack-years (regression coefficient β=-0.023±SE0.003; P=0.003) and duration over all ranges of smoking cigarettes/day (β=-0.041±0.004; P<0.001) but a relatively flat slope for cigarettes/day across all ranges of smoking duration (β=-0.009±0.0.009; P=0.34). Strength of association of duration was similarly greater than pack-years for emphysema, gas trapping, FEV₁, 6MWD and SGRQ.

CONCLUSION

Smoking duration alone provides stronger risk estimates of COPD than the composite index of pack-years.

TRIAL REGISTRATION NUMBER

Post-results; NCT00608764.

CT measurements of central pulmonary vasculature as predictors of severe exacerbation in COPD

To identify a predictive value for the exacerbation status of chronic obstructive pulmonary disease (COPD) subjects, we evaluated the relationship between pulmonary vascular measurements on chest CT and severe COPD exacerbation.Six hundred three subjects enrolled in the COPDGene population were included and divided into nonexacerbator (n = 313) and severe exacerbator (n = 290) groups, based on whether they had an emergency room visit and/or hospitalization for COPD exacerbation. We measured the diameter of the main pulmonary artery (MPA) and ascending aorta (AA) at 2 different sites of the MPA (the tubular midportion and bifurcation) on both axial images and multiplanar reconstructions. Using multiple logistic regression analyses, we evaluated the relationship between each CT-measured pulmonary vasculature and exacerbation status.Axial and multiplanar MPA to AA diameter ratios (PA:AA ratios) at the tubular midportion and the axial PA:AA ratios at the bifurcation indicated significant association with severe exacerbation. The strongest association was found with the axial PA:mean AA ratio at the bifurcation (adjusted odds ratio [OR] = 12.53, 95% confidence interval [CI] = 2.35-66.74, P = .003) and the axial PA:major AA ratio at the tubular midportion (adjusted OR = 10.72, 95% CI = 1.99-57.86, P = .006). No differences were observed in the MPA diameter. Receiver operating characteristic analysis of these variables indicates that they may serve as a good predictive value for severe exacerbation (area under the curve, 0.77-0.78). The range of cut-off value for PA:AA ratio was 0.8 to 0.87.CT-measured PA:AA ratios at either the bifurcation or the tubular site, measured either on axial or multiplanar images, are useful for identification of the risk of severe exacerbation, and consequently can be helpful in guiding the management of COPD. Although CT measurement was used at the level of pulmonary bifurcation in previous studies, we suggest that future studies should monitor the tubular site of the MPA for maximum diagnostic value of CT in pulmonary hypertension or severe COPD exacerbation, as the tubular site of the MPA remains relatively constant on CT images.

Chest computed tomography-derived low fat-free mass index and mortality in COPD

Low fat-free mass index (FFMI) is an independent risk factor for mortality in chronic obstructive pulmonary disease (COPD) not typically measured during routine care. In the present study, we aimed to derive fat-free mass from the pectoralis muscle area (FFM_PMA) and assess whether low FFMI_PMA is associated with all-cause mortality in COPD cases. We used data from two independent COPD cohorts, ECLIPSE and COPDGene.Two equal sized groups of COPD cases (n=759) from the ECLIPSE study were used to derive and validate an equation to calculate the FFM_PMA measured using bioelectrical impedance from PMA. We then applied the equation in COPD cases (n=3121) from the COPDGene cohort, and assessed survival. Low FFMI_PMA was defined, using the Schols classification (FFMI <16 in men, FFMI <15 in women) and the fifth percentile normative values of FFMI from the UK Biobank.The final regression model included PMA, weight, sex and height, and had an adjusted R² of 0.92 with fat-free mass (FFM) as the outcome. In the test group, the correlation between FFM_PMA and FFM remained high (Pearson correlation=0.97). In COPDGene, COPD cases with a low FFMI_PMA had an increased risk of death (HR 1.6, p<0.001).We demonstrated COPD cases with a low FFMI_PMA have an increased risk of death.

Handgrip Strength in Chronic Obstructive Pulmonary Disease. Associations with Acute Exacerbations and Body Composition

RATIONALE

Handgrip strength (HGS) predicts mortality in the elderly, but its determinants and clinical significance in chronic obstructive pulmonary disease (COPD) has not been defined.

OBJECTIVES

We tested associations of HGS with pectoralis muscle area (PMA), subcutaneous adipose tissue (SAT), imaging characteristics, and lung function in smokers with COPD, and evaluated the cross-sectional and longitudinal associations of HGS with acute respiratory events.

METHODS

We analyzed demographic, clinical, spirometry, HGS, and imaging data of 272 subjects with COPD, obtaining measures of airway thickness, emphysema, PMA, and SAT from chest computed tomography scans. We tested associations of lung function and imaging characteristics with HGS, using linear models. HGS association to acute respiratory events at enrollment and during follow-up (mean, 2.6 years) was analyzed using adjusted logistic models.

RESULTS

HGS correlated with PMA, SAT, forced expiratory volume, and airway thickness, but not with body mass index or emphysema severity. In adjusted regression models, HGS was directly (β, 1.5; 95% confidence interval [CI], 0.1-3.0) and inversely (β, -3.3; 95% CI, -5.1 to -0.9) associated with one standard deviation of PMA and SAT, respectively, independent of body mass index and emphysema. In regression models adjusted for age, sex, body mass index, race, pack-years smoked, current smoking, chronic bronchitis, FEV1% predicted, emphysema, and airway metrics, HGS was associated with exacerbation risk; in cross-sectional analyses, there was an increment of 5% in the risk of exacerbations for each 1-kg decrement in HGS (risk ratio, 1.05; 95% CI, 1.01-1.08), and there was a similar risk during follow-up (risk ratio, 1.04; 95% CI, 1.01-1,07).

CONCLUSIONS

In ever-smokers with COPD, HGS is associated with computed tomography markers of body composition and airway thickness, independent of body mass index and emphysema. Higher HGS is associated with lower exacerbation frequency.