Rationale

Age and sex are associated with differences in asthma prevalence and morbidity.

Objectives

To determine if age and sex associate with distinct phenotypes and a variable response to therapy in subjects with mild to moderate asthma.

Methods

We used Asthma Clinical Research Network data to determine the impact of age and sex on phenotypes and treatment failures among subjects participating in 10 trials from 1993 to 2003.

Measurements and main results

A total of 1,200 subjects were identified (median age, 30.4 yr; male, 520 [43.3%]; female, 680 [56.7%]) and analyzed. A higher proportion of subjects greater than or equal to 30 years old experienced treatment failures (17.3% vs. 10.3%; odds ratio [OR], 1.82; confidence interval [CI], 1.30-2.54; P < 0.001), and rates increased proportionally with increasing age older than 30 across the cohort (OR per yr, 1.02 [CI, 1.01-1.04]; OR per 5 yr, 1.13 [CI, 1.04-1.22]; P < 0.001). Lower lung function and longer duration of asthma were associated with a higher risk of treatment failures. A higher proportion of subjects greater than or equal to 30 years old receiving controller therapy experienced treatment failures. When stratified by specific therapy, treatment failures increased consistently for every year older than age 30 in subjects on inhaled corticosteroids (OR per year, 1.03; CI, 1.01-1.07). Females had a slightly higher FEV1 % predicted (84.5% vs. 81.1%; P < 0.001) but similar asthma control measures. There was not a statistically significant difference in treatment failures between females and males (15.2% vs. 11.7%; P = 0.088).

Conclusions

Older age is associated with an increased risk of treatment failure, particularly in subjects taking inhaled corticosteroids. There was no significant difference in treatment failures between sexes.

RATRIONALE: The antimicrobial peptide cathelicidin, also known in humans as LL-37, is a defensin secreted by immune and airway epithelial cells. Deficiencies in this peptide may contribute to adverse pulmonary outcomes in chronic obstructive pulmonary disease (COPD). OBJECTIVES: Using clinical and biological samples from the SubPopulations and InteRmediate Outcome Measures In COPD Study (SPIROMICS), we assessed the associations of plasma cathelicidin levels with cross-sectional and longitudinal COPD outcomes. METHODS: A total of 1609 SPIROMICS participants with COPD and available plasma samples were analyzed. Cathelicidin was modeled dichotomously (lowest quartile [< 50 ng/ml] versus highest 75% [≥ 50 ng/ml]) and continuously per 10 ng/ml. Fixed-effect multilevel regression analyses were used to assess associations between cathelicidin and cross-sectional as well as longitudinal lung function. The associations between cathelicidin and participant-reported retrospective and prospective COPD exacerbations were assessed via logistic regression. MEASUREMENTS AND MAIN RESULTS: Cathelicidin < 50 ng/ml (N=383) was associated with female sex, black race, and lower body mass index (BMI).At baseline,cathelicidin < 50 ng/ml was independently associated with 3.55% lower % predicted forced expiratory volume in 1 second (FEV1)(95% confidence interval [CI] -6.22% to -0.88% predicted; p=0.01), while every 10 ng/ml lower cathelicidin was independently associated with 0.65% lower % predicted FEV1 (95% CI -1.01% to -0.28% predicted; p< 0.001). No independent associations with longitudinal lung function decline or participant-reported COPD exacerbations were observed. CONCLUSIONS: Reduced cathelicidin is associated with lower lung function at baseline. Plasma cathelicidin may potentially identify COPD patients at increased risk for more severe lung disease.

Chronic obstructive pulmonary disease (COPD) is a disease with marked metabolic disturbance. Previous studies have shown the association between single metabolites and lung function for COPD, but whether a combination of metabolites could predict phenotype is unknown. We developed metabolomic severity scores using plasma metabolomics from the Metabolon platform from two US cohorts of ever-smokers: the Subpopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS) (n = 648; training/testing cohort; 72% non-Hispanic, white; average age 63 years) and the COPDGene Study (n = 1120; validation cohort; 92% non-Hispanic, white; average age 67 years). Separate adaptive LASSO (adaLASSO) models were used to model forced expiratory volume at one second (FEV1) and MESA-adjusted lung density using 762 metabolites common between studies. Metabolite coefficients selected by the adaLASSO procedure were used to create a metabolomic severity score (metSS) for each outcome. A total of 132 metabolites were selected to create a metSS for FEV1. The metSS-only models explained 64.8% and 31.7% of the variability in FEV1 in the training and validation cohorts, respectively. For MESA-adjusted lung density, 129 metabolites were selected, and metSS-only models explained 59.0% of the variability in the training cohort and 17.4% in the validation cohort. Regression models including both clinical covariates and the metSS explained more variability than either the clinical covariate or metSS-only models (53.4% vs. 46.4% and 31.6%) in the validation dataset. The metabolomic pathways for arginine biosynthesis; aminoacyl-tRNA biosynthesis; and glycine, serine, and threonine pathway were enriched by adaLASSO metabolites for FEV1. This is the first demonstration of a respiratory metabolomic severity score, which shows how a metSS can add explanation of variance to clinical predictors of FEV1 and MESA-adjusted lung density. The advantage of a comprehensive metSS is that it explains more disease than individual metabolites and can account for substantial collinearity among classes of metabolites. Future studies should be performed to determine whether metSSs are similar in younger, and more racially and ethnically diverse populations as well as whether a metabolomic severity score can predict disease development in individuals who do not yet have COPD.

STUDY OBJECTIVES: To examine the association of self-identified race with sleep quality in heavy smokers. METHODS: We studied baseline data from 1965 non-Hispanic White and 462 African American participants from SPIROMICS with ≥ 20 pack-years smoking history. We first examined the Pittsburgh Sleep Quality Indexs (PSQI) internal consistency and item-total correlation in a population with chronic obstructive pulmonary disease. We then used staged multivariable regression to investigate the association of race and sleep quality as measured by the PSQI) The first model included demographics, the second added measures of health status, and the third, indicators of socioeconomic status. We next explored the correlation between sleep quality with 6-minute walk distance and St. Georges Respiratory Questionnaire score as chronic obstructive pulmonary disease-relevant outcomes. We tested for interactions between self-identified race and the most important determinants of sleep quality in our conceptual model. RESULTS: We found that the PSQI had good internal consistency and item-total correlation in our study population of heavy smokers with and without chronic obstructive pulmonary disease. African American race was associated with increased PSQI in univariable analysis and after adjustment for demographics, health status, and socioenvironmental exposures (P = .02; 0.44 95%CI: .06 to .83). Increased PSQI was associated with higher postbronchodilator forced expiratory volume in 1 second and lower household income, higher depressive symptoms, and female sex. We identified an interaction wherein depressive symptoms had a greater impact on PSQI score for non-Hispanic White than African American participants (P for interaction = .01). CONCLUSIONS: In heavy smokers, self-reported African American race is independently associated with worse sleep quality. CLINICAL TRIAL REGISTRATION: Registry: ClinicalTrials.gov; Name: Study of COPD Subgroups and Biomarkers (SPIROMICS); URL: https://clinicaltrials.gov/ct2/show/NCT01969344; Identifier: NCT01969344. CITATION: Baugh AD, Acho M, Arhin A, et al. African American race is associated with worse sleep quality in heavy smokers. J Clin Sleep Med. 2023;19(8):1523-1532.

BACKGROUND: Abnormal lung volumes representing air trapping identify the subset of smokers with preserved spirometry who develop spirometric chronic obstructive pulmonary disease (COPD) and adverse outcomes. However, how lung volumes evolve in early COPD as airflow obstruction develops remains unclear. METHODS: To establish how lung volumes change with the development of spirometric COPD, we examined lung volumes from the pulmonary function data (seated posture) available in the U.S. Department of Veterans Affairs electronic health records (n=71,356) and lung volumes measured by computed tomography (supine posture) available from the COPD Genetic Epidemiology (COPDGene®) study (n=7969) and the SubPopulations and InterMediate Outcome Measures In COPD Study (SPIROMICS) (n=2552) cohorts, and studied their cross-sectional distributions and longitudinal changes across the airflow obstruction spectrum. Patients with preserved ratio-impaired spirometry (PRISm) were excluded from this analysis. RESULTS: Lung volumes from all 3 cohorts showed similar patterns of distributions and longitudinal changes with worsening airflow obstruction. The distributions for total lung capacity (TLC), vital capacity (VC), and inspiratory capacity (IC) and their patterns of change were nonlinear and included different phases. When stratified by airflow obstruction using Global initiative for chronic Obstructive Lung Disease (GOLD) stages, patients with GOLD 1 (mild) COPD had larger lung volumes (TLC, VC, IC) compared to patients with GOLD 0 (smokers with preserved spirometry) or GOLD 2 (moderate) disease. In longitudinal follow-up of baseline GOLD 0 patients who progressed to spirometric COPD, those with an initially higher TLC and VC developed mild obstruction (GOLD 1) while those with an initially lower TLC and VC developed moderate obstruction (GOLD 2). CONCLUSIONS: In COPD, TLC, and VC have biphasic distributions, change in nonlinear fashions as obstruction worsens, and could differentiate those GOLD 0 patients at risk for more rapid spirometric disease progression.

Rationale: African American individuals have worse outcomes in chronic obstructive pulmonary disease (COPD). Objectives: To assess whether race-specific approaches for estimating lung function contribute to racial inequities by failing to recognize pathological decrements and considering them normal. Methods: In a cohort with and at risk for COPD, we assessed whether lung function prediction equations applied in a race-specific versus universal manner better modeled the relationship between FEV₁, FVC, and other COPD outcomes, including the COPD Assessment Test, St. George's Respiratory Questionnaire, computed tomography percent emphysema, airway wall thickness, and 6-minute-walk test. We related these outcomes to differences in FEV₁ using multiple linear regression and compared predictive performance between fitted models using root mean squared error and Alpaydin's paired F test. Measurements and Main Results: Using race-specific equations, African American individuals were calculated to have better lung function than non-Hispanic White individuals (FEV₁, 76.8% vs. 71.8% predicted; P = 0.02). Using universally applied equations, African American individuals were calculated to have worse lung function. Using Hankinson's Non-Hispanic White equation, FEV₁ was 64.7% versus 71.8% (P < 0.001). Using the Global Lung Initiative's Other race equation, FEV₁ was 70.0% versus 77.9% (P < 0.001). Prediction errors from linear regression were less for universally applied equations compared with race-specific equations when examining FEV₁% predicted with the COPD Assessment Test (P < 0.01), St. George's Respiratory Questionnaire (P < 0.01), and airway wall thickness (P < 0.01). Although African American participants had greater adversity (P < 0.001), less adversity was only associated with better FEV₁ in non-Hispanic White participants (P for interaction = 0.041). Conclusions: Race-specific equations may underestimate COPD severity in African American individuals.Clinical trial registered with www.clinicaltrials.gov (NCT01969344).

Study objectives

Sleep is an important dimension in the care of chronic obstructive pulmonary disease (COPD), but its relevance to exacerbations is unclear. We wanted to assess whether sleep quality as measured by the Pittsburgh Sleep Quality Index (PSQI) is associated with an increased risk of COPD exacerbations and does this differ by socio-environmental exposures.

Methods

We included 1647 current and former smokers with spirometrically confirmed COPD from the SPIROMICS cohort. We assessed incidence rate ratios for exacerbation using zero-inflated negative binomial regression adjusting for demographics, medical comorbidities, and multiple metrics of disease severity, including respiratory medications, airflow obstruction, and symptom burden. Our final model adjusted for socio-environmental exposures using the Area Deprivation Index, a composite measure of contemporary neighborhood quality, and Adversity-Opportunity Index, a composite measure of individual-level historic and current socioeconomic indicators. We used a pre-determined threshold of 20% missingness to undertake multiple imputation by chained equations. As sensitivity analyses, we repeated models in those with complete data and after controlling for prior exacerbations. As an exploratory analysis, we considered an interaction between socio-environmental condition and sleep quality.

Results

After adjustment for all co-variates, increasing PSQI scores (range 0-21) were associated with a 5% increased risk for exacerbation per point (p = .001) in the imputed dataset. Sensitivity analyses using complete cases and after controlling for prior exacerbation history were similar. Exploratory analysis suggested less effect among those who lived in poor-quality neighborhoods (p-for-interaction = .035).

Conclusions

Poor sleep quality may contribute to future exacerbations among patients with COPD. This represents one target for improving disease control.

Clinical trial registration

Subpopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS). ClinicalTrials.gov Identifier# NCT01969344. Registry URL: https://clinicaltrials.gov/ct2/show/.

Background

The use of inflammatory biomarkers to delineate the type of lung inflammation present in asthmatic subjects is increasingly common. However, the effect of obesity on these markers is unknown.

Objectives

We aimed to determine the effect of obesity on conventional markers of inflammation in asthmatic subjects.

Methods

We performed secondary analysis of data from 652 subjects previously enrolled in 2 Asthma Clinical Research Network trials. We performed linear correlations between biomarkers and logistic regression analysis to determine the predictive value of IgE levels, blood eosinophil counts, and fraction of exhaled nitric oxide values in relationship to sputum eosinophil counts (>2%), as well as to determine whether cut points existed that would maximize the sensitivity and specificity for predicting sputum eosinophilia in the 3 weight groups.

Results

Overall, statistically significant but relatively weak correlations were observed among all 4 markers of inflammation. Within obese subjects, the only significant correlation found was between IgE levels and blood eosinophil counts (r = 0.33, P < .001); furthermore, all other correlations between inflammatory markers were approximately 0, including correlations with sputum eosinophil counts. In addition, the predictive value of each biomarker alone or in combination was poor in obese subjects. In fact, in obese subjects none of the biomarkers of inflammation significantly predicted the presence of high sputum eosinophil counts. Obese asthmatic subjects have lower cut points for IgE levels (268 IU), fraction of exhaled nitric oxide values (14.5 ppb), and blood eosinophil counts (96 cells/μL) than all other groups.

Conclusions

In obese asthmatic subjects conventional biomarkers of inflammation are poorly predictive of eosinophilic airway inflammation. As such, biomarkers currently used to delineate eosinophilic inflammation in asthmatic subjects should be approached with caution in these subjects.

BACKGROUND: There is a lack of mechanism-driven, clinically relevant biomarkers in chronic obstructive pulmonary disease (COPD). Mitochondrial dysfunction, a proposed disease mechanism in COPD, is associated with the release of mitochondrial DNA (mtDNA), but plasma cell-free mtDNA has not been previously examined prospectively for associations with clinical COPD measures. METHODS: P-mtDNA, defined as copy number of mitochondrially-encoded NADH dehydrogenase-1 (MT-ND1) gene, was measured by real-time quantitative PCR in 700 plasma samples from participants enrolled in the Subpopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS) cohort. Associations between p-mtDNA and clinical disease parameters were examined, adjusting for age, sex, smoking status, and for informative loss to follow-up. RESULTS: P-mtDNA levels were higher in participants with mild or moderate COPD, compared to smokers without airflow obstruction, and to participants with severe COPD. Baseline increased p-mtDNA levels were associated with better CAT scores in female smokers without airflow obstruction and female participants with mild or moderate COPD on 1-year follow-up, but worse 6MWD in females with severe COPD. Higher p-mtDNA levels were associated with better 6MWD in male participants with severe COPD. These associations were no longer significant after adjusting for informative loss to follow-up. CONCLUSION: In this study, p-mtDNA levels associated with baseline COPD status but not future changes in clinical COPD measures after accounting for informative loss to follow-up. To better characterize mitochondrial dysfunction as a potential COPD endotype, these results should be confirmed and validated in future studies. TRIAL REGISTRATION:  ClinicalTrials.gov NCT01969344 (SPIROMICS).