Design of the Subpopulations and Intermediate Outcome Measures in COPD (SPIROMICS) AIR Study.

IntroductionPopulation-based epidemiological evidence suggests that exposure to ambient air pollutants increases hospitalisations and mortality from chronic obstructive pulmonary disease (COPD), but less is known about the impact of exposure to air pollutants on patient-reported outcomes, morbidity and progression of COPD.Methods and analysisThe Subpopulations and Intermediate Outcome Measures in COPD (SPIROMICS) Air Pollution Study (SPIROMICS AIR) was initiated in 2013 to investigate the relation between individual-level estimates of short-term and long-term air pollution exposures, day-to-day symptom variability and disease progression in individuals with COPD. SPIROMICS AIR builds on a multicentre study of smokers with COPD, supplementing it with state-of-the-art air pollution exposure assessments of fine particulate matter, oxides of nitrogen, ozone, sulfur dioxide and black carbon. In the parent study, approximately 3000 smokers with and without airflow obstruction are being followed for up to 3 years for the identification of intermediate biomarkers which predict disease progression. Subcohorts undergo daily symptom monitoring using comprehensive daily diaries. The air monitoring and modelling methods employed in SPIROMICS AIR will provide estimates of individual exposure that incorporate residence-specific infiltration characteristics and participant-specific time-activity patterns. The overarching study aim is to understand the health effects of short-term and long-term exposures to air pollution on COPD morbidity, including exacerbation risk, patient-reported outcomes and disease progression.Ethics and disseminationThe institutional review boards of all the participating institutions approved the study protocols. The results of the trial will be presented at national and international meetings and published in peer-reviewed journals

Clinical Significance of Bronchodilator Responsiveness Evaluated by Forced Vital Capacity in COPD: SPIROMICS Cohort Analysis.

ObjectiveBronchodilator responsiveness (BDR) is prevalent in COPD, but its clinical implications remain unclear. We explored the significance of BDR, defined by post-bronchodilator change in FEV1 (BDRFEV1) as a measure reflecting the change in flow and in FVC (BDRFVC) reflecting the change in volume.MethodsWe analyzed 2974 participants from a multicenter observational study designed to identify varying COPD phenotypes (SPIROMICS). We evaluated the association of BDR with baseline clinical characteristics, rate of prospective exacerbations and mortality using negative binomial regression and Cox proportional hazards models.ResultsA majority of COPD participants exhibited BDR (52.7%). BDRFEV1 occurred more often in earlier stages of COPD, while BDRFVC occurred more frequently in more advanced disease. When defined by increases in either FEV1 or FVC, BDR was associated with a self-reported history of asthma, but not with blood eosinophil counts. BDRFVC was more prevalent in subjects with greater emphysema and small airway disease on CT. In a univariate analysis, BDRFVC was associated with increased exacerbations and mortality, although no significance was found in a model adjusted for post-bronchodilator FEV1.ConclusionWith advanced airflow obstruction in COPD, BDRFVC is more prevalent in comparison to BDRFEV1 and correlates with the extent of emphysema and degree of small airway disease. Since these associations appear to be related to the impairment of FEV1, BDRFVC itself does not define a distinct phenotype nor can it be more predictive of outcomes, but it can offer additional insights into the pathophysiologic mechanism in advanced COPD.Clinical trials registrationClinicalTrials.gov: NCT01969344T4

Resonance Raman studies of Rieske-type proteins

Resonance Raman (RR) spectra are reported for the [2Fe-2S] Rieske protein from Thermus thermophilus (TRP) and phthalate dioxygenase from Pseudomonas cepacia (PDO) as a function of pH and excitation wavelength. Depolarization ratio measurements are presented for the RR spectra of spinach ferredoxin (SFD), TRP, and PDO at 74 K. By comparison with previously published RR spectra of SFD, we suggest reasonable assignments for the spectra of TRP and PDO. The spectra of PDO exhibit virtually no pH dependence, while significant changes are observed in TRP spectra upon raising the pH from 7.3 to 10.1. One band near 270 cm-1, which consists of components at 266 cm-1 and 274 cm-1, is attributed to Fe(III)-N(His) stretching motions. We suggest that these two components arise from conformers having a protonated-hydrogen-bonded imidazole (266 cm-1) and deprotonated-hydrogen-bonded imidazolate (274 cm-1) coordinated to the Fe/S cluster and that the relative populations of the two species are pH-dependent; a simple structural model is proposed to account for this behavior in the respiratory-type Rieske proteins. In addition, we have identified RR peaks associated with the bridging and terminal sulfur atoms of the Fe-S-N cluster. The RR excitation profiles of peaks associated with these atoms are indistinguishable from each other in TRP (pH 7.3) and PDO and differ greatly from those of [2Fe-2S] ferredoxins. The profiles are bimodal with maxima near 490 nm and > approx. 550 nm. By contrast, bands associated with the Fe-N stretch show a somewhat different enhancement profile. Upon reduction, RR peaks assigned to Fe-N vibrations are no longer observed, with the resulting spectrum being remarkably similar to that reported for reduced adrenodoxin. This indicates that only modes associated with Fe-S bonds are observed and supports the idea that the reducing electron resides on the iron atom coordinated to the two histidine residues. Taken as a whole, the data are consistent with an St2FeSb2Fe[N(His)]t2 structure for the Rieske-type cluster.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/29687/1/0000014.pd

Imaging-based clusters in current smokers of the COPD cohort associate with clinical characteristics: the SubPopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS)

Background Classification of COPD is usually based on the severity of airflow, which may not sensitively differentiate subpopulations. Using a multiscale imaging-based cluster analysis (MICA), we aim to identify subpopulations for current smokers with COPD. Methods Among the SPIROMICS subjects, we analyzed computed tomography images at total lung capacity (TLC) and residual volume (RV) of 284 current smokers. Functional variables were derived from registration of TLC and RV images, e.g. functional small airways disease (fSAD%). Structural variables were assessed at TLC images, e.g. emphysema and airway wall thickness and diameter. We employed an unsupervised method for clustering. Results Four clusters were identified. Cluster 1 had relatively normal airway structures; Cluster 2 had an increase of fSAD% and wall thickness; Cluster 3 exhibited a further increase of fSAD% but a decrease of wall thickness and airway diameter; Cluster 4 had a significant increase of fSAD% and emphysema. Clinically, Cluster 1 showed normal FEV1/FVC and low exacerbations. Cluster 4 showed relatively low FEV1/FVC and high exacerbations. While Cluster 2 and Cluster 3 showed similar exacerbations, Cluster 2 had the highest BMI among all clusters. Conclusions Association of imaging-based clusters with existing clinical metrics suggests the sensitivity of MICA in differentiating subpopulations

Imaging-based clusters in former smokers of the COPD cohort associate with clinical characteristics: the SubPopulations and intermediate outcome measures in COPD study (SPIROMICS)

Background: Quantitative computed tomographic (QCT) imaging-based metrics enable to quantify smoking induced disease alterations and to identify imaging-based clusters for current smokers. We aimed to derive clinically meaningful sub-groups of former smokers using dimensional reduction and clustering methods to develop a new way of COPD phenotyping. Methods: An imaging-based cluster analysis was performed for 406 former smokers with a comprehensive set of imaging metrics including 75 imaging-based metrics. They consisted of structural and functional variables at 10 segmental and 5 lobar locations. The structural variables included lung shape, branching angle, airway-circularity, airway-wall-thickness, airway diameter; the functional variables included regional ventilation, emphysema percentage, functional small airway disease percentage, Jacobian (volume change), anisotropic deformation index (directional preference in volume change), and tissue fractions at inspiration and expiration. Results: We derived four distinct imaging-based clusters as possible phenotypes with the sizes of 100, 80, 141, and 85, respectively. Cluster 1 subjects were asymptomatic and showed relatively normal airway structure and lung function except airway wall thickening and moderate emphysema. Cluster 2 subjects populated with obese females showed an increase of tissue fraction at inspiration, minimal emphysema, and the lowest progression rate of emphysema. Cluster 3 subjects populated with older males showed small airway narrowing and a decreased tissue fraction at expiration, both indicating air-trapping. Cluster 4 subjects populated with lean males were likely to be severe COPD subjects showing the highest progression rate of emphysema. Conclusions: QCT imaging-based metrics for former smokers allow for the derivation of statistically stable clusters associated with unique clinical characteristics. This approach helps better categorization of COPD sub-populations; suggesting possible quantitative structural and functional phenotypes.NIH [U01-HL114494, R01-HL112986, S10-RR022421]; Basic Science Research Program through the National Research Foundation of Korea (NRF) - Ministry of Education [NRF-2017R1D1A1B03034157]; Korea Ministry of Environment (MOE) [RE201806039]; NIH/NHLBI [HHSN268200900013C, HHSN268200900014C, HHSN268200900015C, HHSN268200900016C, HHSN268200900017C, HHSN268200900018C, HHSN268200900019C, HHSN268200900020C]Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Airway Mucin Concentration as a Marker of Chronic Bronchitis

Chronic obstructive pulmonary disease (COPD) is characterized by chronic bronchitic and emphysematous components. In one biophysical model, the concentration of mucin on the airway surfaces is hypothesized to be a key variable that controls mucus transport in healthy persons versus cessation of transport in persons with muco-obstructive lung diseases. Under this model, it is postulated that a high mucin concentration produces the sputum and disease progression that are characteristic of chronic bronchitis

Respiratory Symptoms Items from the COPD Assessment Test Identify Ever-Smokers with Preserved Lung Function at Higher Risk for Poor Respiratory Outcomes

Rationale: Ever-smokers without airflow obstruction scores greater than or equal to 10 on the COPD Assessment Test (CAT) still have frequent acute respiratory disease events (exacerbation-like), impaired exercise capacity, and imaging abnormalities. Identification of these subjects could provide new opportunities for targeted interventions. Objectives: We hypothesized that the four respiratory-related items of the CAT might be useful for identifying such individuals, with discriminative ability similar to CAT, which is an eight-item questionnaire used to assess chronic obstructive pulmonary disease impact, including nonrespiratory questions, with scores ranging from 0 to 40. Methods: We evaluated ever-smoker participants in the Subpopulations and Intermediate Outcomes in COPD Study without airflow obstruction (FEV1/FVC≥0.70; FVC above the lower limit of normal). Using the area under the receiver operating characteristic curve, we compared responses to both CAT and the respiratory symptom–related CAT items (cough, phlegm, chest tightness, and breathlessness) and their associations with longitudinal exacerbations. We tested agreement between the two strategies (k statistic), and we compared demographics, lung function, and symptoms among subjects identified as having high symptoms by each strategy. Results: Among 880 ever-smokers with normal lung function (mean age, 61 yr; 52% women) and using a CAT cutpoint greater than or equal to 10, we classified 51.8% of individuals as having high symptoms, 15.3% of whom experienced at least one exacerbation during 1-year follow-up. After testing sensitivity and specificity of different scores for the first four questions to predict any 1-year followup exacerbation, we selected cutpoints of 0–6 as representing a low burden of symptoms versus scores of 7 or higher as representing a high burden of symptoms for all subsequent comparisons. The four respiratory-related items with cutpoint greater than or equal to 7 selected 45.8% participants, 15.6% of whom experienced at least one exacerbation during follow-up. The two strategies largely identified the same individuals (agreement, 88.5%; k = 0.77; P \u3c 0.001), and the proportions of high-symptoms subjects who had severe dyspnea were similar between CAT and the first four CAT questions (25.9% and 26.8%, respectively), as were the proportions reporting impaired quality of life (66.9% and 70.5%, respectively) and short walking distance (22.4% and 23.1%, respectively). There was no difference in area under the receiver operating characteristic curve to predict 1-year follow-up exacerbations (CAT score ≥10, 0.66; vs. four respiratory items from CAT ≥ 7 score, 0.65; P = 0.69). Subjects identified by either method also hadmore depression/anxiety symptoms, poor sleep quality, and greater fatigue. Conclusions: Four CAT items on respiratory symptoms identified high-risk symptomatic ever-smokers with preserved spirometry as well as the CAT did. These data suggest that simpler strategies can be developed to identify these high-risk individuals in primary care

A call for new approaches to quantifying biases in observations of sea-surface temperature

Global surface-temperature changes are a fundamental expression of climate change. Recent, much-debated, variations in the observed rate of surface-temperature change have highlighted the importance of uncertainty in adjustments applied to sea-surface temperature (SST) measurements. These adjustments are applied to compensate for systematic biases and changes in observing protocol. Better quantification of the adjustments and their uncertainties would increase confidence in estimated surface-temperature change and provide higher- quality gridded SST fields for use in many applications. Bias adjustments have been based either on physical models of the observing processes or on the assumption of an unchanging relationship between SST and a reference data set such as night marine air temperature. These approaches produce similar estimates of SST bias on the largest space and timescales, but regional differences can exceed the estimated uncertainty. We describe challenges to improving our understanding of SST biases. Overcoming these will require clarification of past observational methods, improved modeling of biases associated with each observing method, and the development of statistical bias estimates that are less sensitive to the absence of metadata regarding the observing method. New approaches are required that embed bias models, specific to each type of observation, within a robust statistical framework. Mobile platforms and rapid changes in observation type require biases to be assessed for individual historic and present-day platforms (i.e., ships or buoys) or groups of platforms. Lack of observational metadata and of high-quality observations for validation and bias model development are likely to remain major challenges