Deployment-related Cigarette Smoking Behaviors and Pulmonary Function Among U.S. Veterans.

INTRODUCTION: The effects of smoking on lung function among post-9/11 Veterans deployed to environments with high levels of ambient particulate matter are incompletely understood. MATERIALS AND METHODS: We analyzed interim data (04/2018-03/2020) from the Veterans Affairs (VA) Cooperative Studies Program #595, "Service and Health Among Deployed Veterans". Veterans with ≥1 land-based deployments enrolled at 1 of 6 regional Veterans Affairs sites completed questionnaires and spirometry. Multivariable linear regression models assessed associations between cigarette smoking (cumulative, deployment-related and non-deployment-related) with pulmonary function. RESULTS: Among 1,836 participants (mean age 40.7 ± 9.6, 88.6% male), 44.8% (n = 822) were ever-smokers (mean age 39.5 ± 9.5; 91.2% male). Among ever-smokers, 86% (n = 710) initiated smoking before deployment, while 11% (n = 90) initiated smoking during deployment(s). Smoking intensity was 50% greater during deployment than other periods (0.75 versus 0.50 packs-per-day; P < .05), and those with multiple deployments (40.4%) were more likely to smoke during deployment relative to those with single deployments (82% versus 74%). Total cumulative pack-years (median [IQR] = 3.8 [1, 10]) was inversely associated with post-bronchodilator FEV1%-predicted (-0.82; [95% CI] = [-1.25, -0.50] %-predicted per 4 pack-years) and FEV1/FVC%-predicted (-0.54; [95% CI] = [-0.78, -0.43] %-predicted per 4 pack-years). Deployment-related pack-years demonstrated similar point estimates of associations with FEV1%-predicted (-0.61; [95% CI] = [-2.28, 1.09]) and FEV1/FVC%-predicted (-1.09; [95% CI] = [-2.52, 0.50]) as non-deployment-related pack-years (-0.83; [95% CI] = [-1.26, -0.50] for FEV1%-predicted; -0.52; [95% CI] = [-0.73, -0.36] for FEV1/FVC%-predicted). CONCLUSIONS: Although cumulative pack-years smoking was modest in this cohort, an inverse association with pulmonary function was detectable. Deployment-related pack-years had a similar association with pulmonary function compared to non-deployment-related pack-years.

Chronic respiratory symptoms following deployment-related occupational and environmental exposures among US veterans.

OBJECTIVES: Characterise inhalational exposures during deployment to Afghanistan and Southwest Asia and associations with postdeployment respiratory symptoms. METHODS: Participants (n=1960) in this cross-sectional study of US Veterans (Veterans Affairs Cooperative Study 'Service and Health Among Deployed Veterans') completed an interviewer-administered questionnaire regarding 32 deployment exposures, grouped a priori into six categories: burn pit smoke; other combustion sources; engine exhaust; mechanical and desert dusts; toxicants; and military job-related vapours gas, dusts or fumes (VGDF). Responses were scored ordinally (0, 1, 2) according to exposure frequency. Factor analysis supported item reduction and category consolidation yielding 28 exposure items in 5 categories. Generalised linear models with a logit link tested associations with symptoms (by respiratory health questionnaire) adjusting for other covariates. OR were scaled per 20-point score increment (normalised maximum=100). RESULTS: The cohort mean age was 40.7 years with a median deployment duration of 11.7 months. Heavy exposures to multiple inhalational exposures were commonly reported, including burn pit smoke (72.7%) and VGDF (72.0%). The prevalence of dyspnoea, chronic bronchitis and wheeze in the past 12 months was 7.3%, 8.2% and 15.6%, respectively. Burn pit smoke exposure was associated with dyspnoea (OR 1.22; 95% CI 1.06 to 1.47) and chronic bronchitis (OR 1.22; 95% CI 1.13 to 1.44). Exposure to VGDF was associated with dyspnoea (OR 1.29; 95% CI 1.14 to 1.58) and wheeze (OR 1.18; 95% CI 1.02 to 1.35). CONCLUSION: Exposures to burn pit smoke and military occupational VGDF during deployment were associated with an increased odds of chronic respiratory symptoms among US Veterans.

Individual Risk Factors of PM2.5 Associated With Wintertime Mortality in Urban Patients With COPD.

BACKGROUND: Air pollution contributes to premature mortality, but potential impacts differ in populations with existing disease, particularly for individuals with multiple risk factors. Although COPD increases vulnerability to air pollution, individuals with COPD and other individual risk factors are at the intersection of multiple risks and may be especially susceptible to the effect of acute outdoor air pollution. RESEARCH QUESTION: What is the association between wintertime air pollution and mortality in patients with COPD and the modifying role of individual risk factors? STUDY DESIGN AND METHODS: This study evaluated 19,243 deceased veterans with prior COPD diagnosis who had resided in 25 US metropolitan regions (2016-2019). Electronic health records included patient demographic characteristics; smoking status; and comorbidities such as asthma, coronary artery disease (CAD), obesity, and diabetes. Using geocoded addresses, individuals were assigned wintertime fine particulate matter (particulate matter smaller than 2.5 µg in diameter [PM2.5]) and nitrogen dioxide air pollution exposures. Associations between acute air pollution and mortality were estimated by using a time-stratified case-crossover design with a conditional logistic model, and individual risk differences were assessed according to stratified analysis. RESULTS: A 1.05 (95% CI, 1.02-1.09) mortality risk was estimated for each 10 µg/m3 increase in daily wintertime PM2.5). Older patients and Black individuals displayed elevated risk. Obesity was a substantial air pollution-related mortality risk factor (OR, 1.11; 95% CI, 1.01-1.23), and the estimated risk for individuals with obesity plus CAD or obesity plus diabetes was 16% higher. INTERPRETATION: Wintertime PM2.5 exposure was associated with elevated mortality risk in people with COPD, but individuals with multiple comorbidities, notably obesity, had high vulnerability. Our study suggests that obesity, CAD, and diabetes are understudied modifiers of air pollution-related risks for people with existing COPD.

Lifestyle Intervention and Excess Weight in Chronic Obstructive Pulmonary Disease (COPD): INSIGHT COPD Randomized Clinical Trial.

Rationale: Being overweight or obese is common among patients with chronic obstructive pulmonary disease (COPD), but whether interventions targeted at weight loss improve functional impairments is unknown. Objectives: INSIGHT (Intervention Study in Overweight Patients with COPD) tested whether a pragmatic low-intensity lifestyle intervention would lead to better physical functional status among overweight or obese participants with COPD. Methods: The trial was a 12-month, multicenter, patient-level pragmatic clinical trial. Participants were recruited from April 2017 to August 2019 from 38 sites across the United States and randomized to receive usual care or usual care plus lifestyle intervention. The intervention was a self-directed video program delivering the Diabetes Prevention Program's Group Lifestyle Balance curriculum. Results: The primary outcome was 6-minute-walk test distance at 12 months. Priority secondary outcomes were postwalk modified Borg dyspnea at 12 months and weight at 12 months. Participants (N = 684; mean age, 67.0 ± 8.0 yr [standard deviation]; 41.2% female) on average were obese (body mass index, 33.0 ± 4.6 kg/m2) with moderate COPD (forced expiratory volume in 1 second % predicted, 58.1 ± 15.7%). At 12 months, participants randomized to the intervention arm walked farther (adjusted difference, 42.3 ft [95% confidence interval (CI), 7.9-76.7 ft]; P = 0.02), had less dyspnea at the end of the 6-minute-walk test (adjusted difference, -0.36 [95% CI, -0.63 to -0.09]; P = 0.008), and had greater weight loss (adjusted difference, -1.34 kg [95% CI, -2.33 to -0.34 kg]; P = 0.008) than control participants. The intervention did not improve the odds of achieving clinically meaningful thresholds of walk distance (98.4 ft) or dyspnea (1 unit) but did achieve meaningful thresholds of weight loss (3% and 5%). Conclusions: Among participants with COPD who were overweight or obese, a self-guided low-intensity video-based lifestyle intervention led to modest weight loss but did not lead to clinically important improvements in physical functional status and dyspnea. Clinical trial registered with www.clinicaltrials.gov (NCT02634268).

An optimized workflow for MS-based quantitative proteomics of challenging clinical bronchoalveolar lavage fluid (BALF) samples.

BACKGROUND: Clinical bronchoalveolar lavage fluid (BALF) samples are rich in biomolecules, including proteins, and useful for molecular studies of lung health and disease. However, mass spectrometry (MS)-based proteomic analysis of BALF is challenged by the dynamic range of protein abundance, and potential for interfering contaminants. A robust, MS-based proteomics compatible sample preparation workflow for BALF samples, including those of small and large volume, would be useful for many researchers. RESULTS: We have developed a workflow that combines high abundance protein depletion, protein trapping, clean-up, and in-situ tryptic digestion, that is compatible with either qualitative or quantitative MS-based proteomic analysis. The workflow includes a value-added collection of endogenous peptides for peptidomic analysis of BALF samples, if desired, as well as amenability to offline semi-preparative or microscale fractionation of complex peptide mixtures prior to LC-MS/MS analysis, for increased depth of analysis. We demonstrate the effectiveness of this workflow on BALF samples collected from COPD patients, including for smaller sample volumes of 1-5 mL that are commonly available from the clinic. We also demonstrate the repeatability of the workflow as an indicator of its utility for quantitative proteomic studies. CONCLUSIONS: Overall, our described workflow consistently provided high quality proteins and tryptic peptides for MS analysis. It should enable researchers to apply MS-based proteomics to a wide-variety of studies focused on BALF clinical specimens.

Robust integrative biclustering for multi-view data.

In many biomedical research, multiple views of data (e.g. genomics, proteomics) are available, and a particular interest might be the detection of sample subgroups characterized by specific groups of variables. Biclustering methods are well-suited for this problem as they assume that specific groups of variables might be relevant only to specific groups of samples. Many biclustering methods exist for detecting row-column clusters in a view but few methods exist for data from multiple views. The few existing algorithms are heavily dependent on regularization parameters for getting row-column clusters, and they impose unnecessary burden on users thus limiting their use in practice. We extend an existing biclustering method based on sparse singular value decomposition for single-view data to data from multiple views. Our method, integrative sparse singular value decomposition (iSSVD), incorporates stability selection to control Type I error rates, estimates the probability of samples and variables to belong to a bicluster, finds stable biclusters, and results in interpretable row-column associations. Simulations and real data analyses show that integrative sparse singular value decomposition outperforms several other single- and multi-view biclustering methods and is able to detect meaningful biclusters. iSSVD is a user-friendly, computationally efficient algorithm that will be useful in many disease subtyping applications.

Bronchodilators in Tobacco-Exposed Persons with Symptoms and Preserved Lung Function.

BACKGROUND: Many persons with a history of smoking tobacco have clinically significant respiratory symptoms despite an absence of airflow obstruction as assessed by spirometry. They are often treated with medications for chronic obstructive pulmonary disease (COPD), but supporting evidence for this treatment is lacking. METHODS: We randomly assigned persons who had a tobacco-smoking history of at least 10 pack-years, respiratory symptoms as defined by a COPD Assessment Test score of at least 10 (scores range from 0 to 40, with higher scores indicating worse symptoms), and preserved lung function on spirometry (ratio of forced expiratory volume in 1 second [FEV1] to forced vital capacity [FVC] ≥0.70 and FVC ≥70% of the predicted value after bronchodilator use) to receive either indacaterol (27.5 µg) plus glycopyrrolate (15.6 µg) or placebo twice daily for 12 weeks. The primary outcome was at least a 4-point decrease (i.e., improvement) in the St. George's Respiratory Questionnaire (SGRQ) score (scores range from 0 to 100, with higher scores indicating worse health status) after 12 weeks without treatment failure (defined as an increase in lower respiratory symptoms treated with a long-acting inhaled bronchodilator, glucocorticoid, or antibiotic agent). RESULTS: A total of 535 participants underwent randomization. In the modified intention-to-treat population (471 participants), 128 of 227 participants (56.4%) in the treatment group and 144 of 244 (59.0%) in the placebo group had at least a 4-point decrease in the SGRQ score (difference, -2.6 percentage points; 95% confidence interval [CI], -11.6 to 6.3; adjusted odds ratio, 0.91; 95% CI, 0.60 to 1.37; P = 0.65). The mean change in the percent of predicted FEV1 was 2.48 percentage points (95% CI, 1.49 to 3.47) in the treatment group and -0.09 percentage points (95% CI, -1.06 to 0.89) in the placebo group, and the mean change in the inspiratory capacity was 0.12 liters (95% CI, 0.07 to 0.18) in the treatment group and 0.02 liters (95% CI, -0.03 to 0.08) in the placebo group. Four serious adverse events occurred in the treatment group, and 11 occurred in the placebo group; none were deemed potentially related to the treatment or placebo. CONCLUSIONS: Inhaled dual bronchodilator therapy did not decrease respiratory symptoms in symptomatic, tobacco-exposed persons with preserved lung function as assessed by spirometry. (Funded by the National Heart, Lung, and Blood Institute and others; RETHINC ClinicalTrials.gov number, NCT02867761.).

sJIVE: Supervised Joint and Individual Variation Explained.

Analyzing multi-source data, which are multiple views of data on the same subjects, has become increasingly common in molecular biomedical research. Recent methods have sought to uncover underlying structure and relationships within and/or between the data sources, and other methods have sought to build a predictive model for an outcome using all sources. However, existing methods that do both are presently limited because they either (1) only consider data structure shared by all datasets while ignoring structures unique to each source, or (2) they extract underlying structures first without consideration to the outcome. The proposed method, supervised joint and individual variation explained (sJIVE), can simultaneously (1) identify shared (joint) and source-specific (individual) underlying structure and (2) build a linear prediction model for an outcome using these structures. These two components are weighted to compromise between explaining variation in the multi-source data and in the outcome. Simulations show sJIVE to outperform existing methods when large amounts of noise are present in the multi-source data. An application to data from the COPDGene study explores gene expression and proteomic patterns associated with lung function.

Biomarkers and the microbiome in the detection and treatment of early-stage non-small cell lung cancer.

Lung cancer is one of the most common and deadly cancers in the world. However, over the last several years, research into lung cancer screening and novel therapeutic approaches have provided promise that earlier detection combined with new treatment strategies may result in significantly improved outcomes. Biomarkers will most certainly play a major role in identifying those who may benefit from, and how to apply, these new treatment strategies. Here we discuss potential biomarkers, including the microbiome, in both detection and treatment strategies for early stage lung cancer.

Network Analysis to Identify Multi-Omic Correlations in the Lower Airways of Children With Cystic Fibrosis.

The leading cause of morbidity and mortality in cystic fibrosis (CF) is progressive lung disease secondary to chronic airway infection and inflammation; however, what drives CF airway infection and inflammation is not well understood. By providing a physiological snapshot of the airway, metabolomics can provide insight into these processes. Linking metabolomic data with microbiome data and phenotypic measures can reveal complex relationships between metabolites, lower airway bacterial communities, and disease outcomes. In this study, we characterize the airway metabolome in bronchoalveolar lavage fluid (BALF) samples from persons with CF (PWCF) and disease control (DC) subjects and use multi-omic network analysis to identify correlations with the airway microbiome. The Biocrates targeted liquid chromatography mass spectrometry (LC-MS) platform was used to measure 409 metabolomic features in BALF obtained during clinically indicated bronchoscopy. Total bacterial load (TBL) was measured using quantitative polymerase chain reaction (qPCR). The Qiagen EZ1 Advanced automated extraction platform was used to extract DNA, and bacterial profiling was performed using 16S sequencing. Differences in metabolomic features across disease groups were assessed univariately using Wilcoxon rank sum tests, and Random forest (RF) was used to identify features that discriminated across the groups. Features were compared to TBL and markers of inflammation, including white blood cell count (WBC) and percent neutrophils. Sparse supervised canonical correlation network analysis (SsCCNet) was used to assess multi-omic correlations. The CF metabolome was characterized by increased amino acids and decreased acylcarnitines. Amino acids and acylcarnitines were also among the features most strongly correlated with inflammation and bacterial burden. RF identified strong metabolomic predictors of CF status, including L-methionine-S-oxide. SsCCNet identified correlations between the metabolome and the microbiome, including correlations between a traditional CF pathogen, Staphylococcus, a group of nontraditional taxa, including Prevotella, and a subnetwork of specific metabolomic markers. In conclusion, our work identified metabolomic characteristics unique to the CF airway and uncovered multi-omic correlations that merit additional study.

Chlorhexidine oral rinses for symptomatic COPD: a randomised, blind, placebo-controlled preliminary study.

OBJECTIVES: Determine the effect of twice-daily chlorhexidine oral rinses on oral and lung microbiota biomass and respiratory symptoms. SETTING: Single centre. PARTICIPANTS: Participants were aged 40-85 with chronic obstructive pulmonary disease (COPD) and chronic productive cough or COPD exacerbation within the last year. Exclusions included antibiotics in the previous 2 months and/or those with less than four teeth. Forty-four participants were recruited and 40 completed the study. INTERVENTION: Participants were randomised 1:1 to twice-daily 0.12% chlorhexidine oral rinses versus placebo for 2 months along with daily diaries. St. George's Respiratory Questionnaire (SGRQ), blood tests, oral rinse and induced sputum were collected at randomisation and the final visit. PRIMARY AND SECONDARY OUTCOMES: Primary outcome was a change in oral and sputum microbiota biomass. Secondary outcomes included: sputum and oral microbiota Shannon and Simpson diversity and taxonomy; inflammatory markers; Breathlessness, Cough and Sputum Scale and SGRQ scores. RESULTS: Neither the oral microbiota nor the sputum microbiota biomass decreased significantly in those using chlorhexidine compared with placebo (oral microbiota mean log10 difference (SE)=-0.103 (0.23), 95% CI -0.59 to 0.38, p=0.665; sputum microbiota 0.80 (0.46), 95% CI -0.15 to 1.75, p=0.096). Chlorhexidine decreased both oral and sputum microbiota alpha (Shannon) diversity (linear regression estimate (SE) oral: -0.349 (0.091), p=0.001; sputum -0.622 (0.169), p=0.001). Chlorhexidine use did not decrease systemic inflammatory markers compared with placebo (C reactive protein (chlorhexidine 1.8±7.5 vs placebo 0.4±6.8, p=0.467), fibrinogen (22.5±77.8 vs 10.0±77.0, p=0.406) or leucocytes (0.2±1.8 vs 0.5±1.8, p=0.560)). Chlorhexidine use decreased SGRQ scores compared with placebo (chlorhexidine -4.7±8.0 vs placebo 1.7±8.9, p=0.032). CONCLUSIONS: We did not detect a significant difference in microbiota biomass due to chlorhexidine use. Chlorhexidine decreased oral and sputum microbiota alpha diversity and improved respiratory health-related quality of life compared with placebo. TRIAL REGISTRATION: NCT02252588.

Prone Positioning of Patients With Coronavirus Disease 2019 Who Are Nonintubated in Hypoxic Respiratory Distress: Single-Site Retrospective Health Records Review.

INTRODUCTION: In March and April 2020 of the coronavirus disease 2019 pandemic, site clinical practice guidelines were implemented for prone positioning of patients with suspected coronavirus disease 2019 in hypoxic respiratory distress who are awake, alert, and spontaneously breathing. The purpose of this pandemic disaster practice improvement project was to measure changes in pulse oximetry associated with prone positioning of patients with coronavirus disease 2019 infection in adult acute respiratory distress or adult respiratory distress syndrome, who are awake, alert, spontaneously breathing, and nonintubated. METHODS: A retrospective chart review of patients who were coronavirus disease 2019 positive in the emergency department from March 30, 2020 to April 30, 2020 was conducted for patients with a room air pulse oximetry <90% and a preprone position pulse oximetry ≤94% who tolerated prone positioning for at least 30 minutes. The primary outcome was the change in pulse oximetry associated with prone positioning, measured on room air, with supplemental oxygen, and approximately 30 minutes after initiating prone positioning. Median and mean differences were compared with the Wilcoxon signed-rank test and paired t-test. RESULTS: Of the 440 patients with coronavirus disease 2019, 31 met inclusion criteria. Median pulse oximetry increased as 83% (interquartile range, 75%-86%) on room air, 90% (interquartile range, 89%-93%) with supplemental oxygen, and 96% (interquartile range, 94%-98%) with prone positioning (z = -4.48, P < .001). A total of 45% (n = 14) were intubated during their hospital stay, and 26% (n = 8) of the included patients died. DISCUSSION: In patients with coronavirus disease 2019 who are awake, alert, and spontaneously breathing, an initially low pulse oximetry reading improved with prone positioning. Future studies are needed to determine the association of prone positioning with subsequent endotracheal intubation and mortality.

Plasma Metabolomic Signatures of Chronic Obstructive Pulmonary Disease and the Impact of Genetic Variants on Phenotype-Driven Modules.

Background: Small studies have recently suggested that there are specific plasma metabolic signatures in chronic obstructive pulmonary disease (COPD), but there have been no large comprehensive study of metabolomic signatures in COPD that also integrate genetic variants. Materials and Methods: Fresh frozen plasma from 957 non-Hispanic white subjects in COPDGene was used to quantify 995 metabolites with Metabolon's global metabolomics platform. Metabolite associations with five COPD phenotypes (chronic bronchitis, exacerbation frequency, percent emphysema, post-bronchodilator forced expiratory volume at one second [FEV1]/forced vital capacity [FVC], and FEV1 percent predicted) were assessed. A metabolome-wide association study was performed to find genetic associations with metabolite levels. Significantly associated single-nucleotide polymorphisms were tested for replication with independent metabolomic platforms and independent cohorts. COPD phenotype-driven modules were identified in network analysis integrated with genetic associations to assess gene-metabolite-phenotype interactions. Results: Of metabolites tested, 147 (14.8%) were significantly associated with at least 1 COPD phenotype. Associations with airflow obstruction were enriched for diacylglycerols and branched chain amino acids. Genetic associations were observed with 109 (11%) metabolites, 72 (66%) of which replicated in an independent cohort. For 20 metabolites, more than 20% of variance was explained by genetics. A sparse network of COPD phenotype-driven modules was identified, often containing metabolites missed in previous testing. Of the 26 COPD phenotype-driven modules, 6 contained metabolites with significant met-QTLs, although little module variance was explained by genetics. Conclusion: A dysregulation of systemic metabolism was predominantly found in COPD phenotypes characterized by airflow obstruction, where we identified robust heritable effects on individual metabolite abundances. However, network analysis, which increased the statistical power to detect associations missed previously in classic regression analyses, revealed that the genetic influence on COPD phenotype-driven metabolomic modules was modest when compared with clinical and environmental factors.

Normalization of mass spectrometry data (NOMAD).

iTRAQ and TMT reagent-based mass spectrometry (MS) are commonly used technologies for quantitative proteomics in biological samples. Such studies are often performed over multiple MS runs, potentially resulting in introduction of MS run bias that could affect downstream analysis. Such MS data have therefore commonly been normalized using a reference sample which is included in each MS run. We show, however, that reference normalization does not effectively remove systematic MS run bias. A linear model approach was previously proposed to improve on the reference normalization approach but does not computationally scale to larger data sets. Here we describe the NOMAD (normalization of mass spectrometry data) R package which implements a computationally efficient ANOVA normalization approach with protein assembly functionality. NOMAD provides the same advantages as the linear regression solution but is more computationally efficient which allows superior scaling to larger sample sizes. Moreover, NOMAD effectively removes bias which improves valid across MS run comparisons.

Morphological and functional properties of the conducting human airways investigated by in vivo computed tomography and in vitro MRI.

The accurate representation of the human airway anatomy is crucial for understanding and modeling the structure-function relationship in both healthy and diseased lungs. The present knowledge in this area is based on morphometric studies of excised lung casts, partially complemented by in vivo studies in which computed tomography (CT) was used on a small number of subjects. In the present study, we analyzed CT scans of a cohort of healthy subjects and obtained comprehensive morphometric information down to the seventh generation of bronchial branching, including airway diameter, length, branching angle, and rotation angle. Although some of the geometric parameters (such as the child-to-parent branch diameter ratio) are found to be in line with accepted values, for others (such as the branch length-to-diameter ratio) our findings challenge the common assumptions. We also evaluated several metrics of self-similarity, including the fractal dimension of the airway tree. Additionally, we used phase-contrast magnetic resonance imaging (MRI) to obtain the volumetric flow field in the three-dimensional-printed airway model of one of the subjects during steady inhalation. This is used to relate structural and functional parameters and, in particular, to close the power-law relationship between branch flow rate and diameter. The diameter exponent is found to be significantly lower than in the usually assumed Poiseuille regime, which we attribute to the strong secondary (i.e., transverse) velocity component. The strength of the secondary velocity with respect to the axial component exceeds the levels found in idealized airway models and persists within the first seven generations. NEW & NOTEWORTHY We performed a comprehensive computed tomography-based study of the conductive airway morphology in normal human subjects, including branch diameter, length, and mutual angles. We found significant departure from classic homothetic relationships. We also carried out MRI measurements of the three-dimensional inspiratory flow in an anatomy-based model and directly assessed structure-function relationships that have so far been assumed. We found that strong secondary flows (i.e., transverse velocity components) persist through the first seven generations of bronchial branching.

Acute Exacerbations and Lung Function Loss in Smokers with and without Chronic Obstructive Pulmonary Disease.

RATIONALE: Acute exacerbations of chronic obstructive pulmonary disease (COPD) increase the risk of death and drive healthcare costs, but whether they accelerate loss of lung function remains controversial. Whether exacerbations in subjects with mild COPD or similar acute respiratory events in smokers without airflow obstruction affect lung function decline is unknown. OBJECTIVES: To determine the association between acute exacerbations of COPD (and acute respiratory events in smokers without COPD) and the change in lung function over 5 years of follow-up. METHODS: We examined data on the first 2,000 subjects who returned for a second COPDGene visit 5 years after enrollment. Baseline data included demographics, smoking history, and computed tomography emphysema. We defined exacerbations (and acute respiratory events in those without established COPD) as acute respiratory symptoms requiring either antibiotics or systemic steroids, and severe events by the need for hospitalization. Throughout the 5-year follow-up period, we collected self-reported acute respiratory event data at 6-month intervals. We used linear mixed models to fit FEV1 decline based on reported exacerbations or acute respiratory events. MEASUREMENTS AND MAIN RESULTS: In subjects with COPD, exacerbations were associated with excess FEV1 decline, with the greatest effect in Global Initiative for Chronic Obstructive Lung Disease stage 1, where each exacerbation was associated with an additional 23 ml/yr decline (95% confidence interval, 2-44; P = 0.03), and each severe exacerbation with an additional 87 ml/yr decline (95% confidence interval, 23-151; P = 0.008); statistically significant but smaller effects were observed in Global Initiative for Chronic Obstructive Lung Disease stage 2 and 3 subjects. In subjects without airflow obstruction, acute respiratory events were not associated with additional FEV1 decline. CONCLUSIONS: Exacerbations are associated with accelerated lung function loss in subjects with established COPD, particularly those with mild disease. Trials are needed to test existing and novel therapies in subjects with early/mild COPD to potentially reduce the risk of progressing to more advanced lung disease. Clinical trial registered with www.clinicaltrials.gov (NCT 00608764).

Ambient air pollution and lung disease in China: health effects, study design approaches and future research.

Ambient air pollution in China has worsened following dramatic increases in industrialization, automobile use and energy consumption. Particularly bothersome is the increase in the PM2.5 fraction of pollutants. This fraction has been associated with increasing rates of cardio-respiratory disease in China and elsewhere. Ambient pollutant levels have been described in many of China's cities and are comparable to previous levels in southern California. Lung cancer mortality in China has increased since the 1970s and has been higher in men and in urban areas, the exact explanation for which has not been determined. The estimation of individual risk for Chinese citizens living in areas of air pollution will require further research. Occupational cohort and case-control designs each have unique attributes that could make them helpful to use in this setting. Other important future research considerations include detailed exposure assessment and the possible use of biomarkers as a means to better understand and manage the threat posed by air pollution in China.

A Method for Determining Taxonomical Contributions to Group Differences in Microbiomic Investigations.

Here we show how one can decompose the contribution of different levels of taxonomic classification in terms of their impact on differences in the microbiota when comparing two groups. First we demonstrate a difficulty in trying to estimate taxonomic effects at multiple levels simultaneously and demonstrate an approach to determining which taxa have differences in means that are identified. We then develop a model based on an approach that is popular in the RNA-Seq analysis literature and apply it to the problem of determining which taxa differ between two patient groups. This model provides a more powerful method than simpler alternatives. A Bayesian computational strategy is used to obtain exact inference. Simulation studies indicate that the procedure works as intended, and an application to the study of COPD demonstrates the method's practical utility. Software is provided for implementing the method.

Sputum club cell protein concentration is associated with pulmonary exacerbation in cystic fibrosis.

BACKGROUND: Cystic fibrosis (CF) patients exhibit a progressive decline in lung function accelerated by intermittent pulmonary exacerbations. There are urgent needs for clinically relevant biomarkers to aid in the diagnosis and management of a CF pulmonary exacerbation, in addition to providing insight into its pathophysiology. Club cell secretory protein (CCSP) is produced by bronchial epithelial cells, known to have anti-inflammatory properties and may play a role in CF pulmonary exacerbations. Our objective was to measure sputum CCSP concentration during hospitalizations for CF pulmonary exacerbation and during quarterly outpatient clinic visits for 2 years. We explored the correlations between CCSP concentration, lung function and markers of inflammation and infection. METHODS: In this prospective, longitudinal cohort study, expectorated sputum, blood and lung function data were collected from 45 CF patients during 68 hospitalizations for pulmonary exacerbation and 193 clinic visits. Sputum CCSP concentration was measured and sputum and blood were assayed with a panel of inflammatory cytokines. We used a repeated measures model to compare log transformed sputum CCSP concentrations across multiple time points and to correlate those concentrations with related clinical variables. RESULTS: Our population had a mean age of 29 (16-58 years), and a median FEV(1) %predicted of 60% (18-105%). Sputum CCSP concentration was significantly lower in the initial, interim and final exacerbation samples (p=0.0021, p=0.0005 and p=0.0274, respectively) compared to outpatient visits. Sputum CCSP concentration was negatively associated with sputum neutrophil elastase concentration (p=0.0373). Patients with Pseudomonas aeruginosa mucoid had a significantly lower sputum CCSP concentration (p=0.0129). CONCLUSION: Sputum CCSP concentration is associated with CF pulmonary exacerbation.