Preserved Ratio Impaired Spirometry (PRISm), defined as a reduced FEV1 in the setting of a preserved FEV1/FVC ratio, is highly prevalent and is associated with increased respiratory symptoms, systemic inflammation, and mortality. Studies investigating quantitative chest tomographic features, genetic associations, and subtypes in PRISm subjects have not been reported.

Lung CD4+ T cells accumulate as chronic obstructive pulmonary disease (COPD) progresses, but their role in pathogenesis remains controversial. To address this controversy, we studied lung tissue from 53 subjects undergoing clinically-indicated resections, lung volume reduction, or transplant. Viable single-cell suspensions were analyzed by flow cytometry or underwent CD4+ T cell isolation, followed either by stimulation with anti-CD3 and cytokine/chemokine measurement, or by real-time PCR analysis. In lung CD4+ T cells of most COPD subjects, relative to lung CD4+ T cells in smokers with normal spirometry: (a) stimulation induced minimal IFN-γ or other inflammatory mediators, but many subjects produced more CCL2; (b) the T effector memory subset was less uniformly predominant, without correlation with decreased IFN-γ production. Analysis of unstimulated lung CD4+ T cells of all subjects identified a molecular phenotype, mainly in COPD, characterized by markedly reduced mRNA transcripts for the transcription factors controlling TH1, TH2, TH17 and FOXP3+ T regulatory subsets and their signature cytokines. This mRNA-defined CD4+ T cell phenotype did not result from global inability to elaborate mRNA; increased transcripts for inhibitory CD28 family members or markers of anergy; or reduced telomerase length. As a group, these subjects had significantly worse spirometry, but not DLCO, relative to subjects whose lung CD4+ T cells expressed a variety of transcripts. Analysis of mRNA transcripts of unstimulated lung CD4+ T cell among all subjects identified two distinct molecular correlates of classical COPD clinical phenotypes: basal IL-10 transcripts correlated independently and inversely with emphysema extent (but not spirometry); by contrast, unstimulated IFN-γ transcripts correlated independently and inversely with reduced spirometry (but not reduced DLCO or emphysema extent). Aberrant lung CD4+ T cells polarization appears to be common in advanced COPD, but also exists in some smokers with normal spirometry, and may contribute to development and progression of specific COPD phenotypes.

Small airways disease (SAD) is a major cause of airflow obstruction in COPD patients and has been identified as a precursor to emphysema. Although the amount of SAD in the lungs can be quantified using our Parametric Response Mapping (PRM) approach, the full breadth of this readout as a measure of emphysema and COPD progression has yet to be explored. We evaluated topological features of PRM-derived normal parenchyma and SAD as surrogates of emphysema and predictors of spirometric decline.

The current framework for investigating respiratory diseases is based on defining lung health as the absence of lung disease. In order to develop a comprehensive approach to prevent the development of lung disease, there is a need to evaluate the full spectrum of lung health spanning from ideal to impaired lung health. The American Lung Association (ALA) Lung Health Cohort is a new, population-based, cohort study focused primarily on characterising lung health in members of the millennial generation without diagnosed severe respiratory disease. Participants will be enrolled for the baseline study visit starting in 2021, and funding will be sought to support future study exams as part of a longitudinal cohort study. This study will be crucial for developing a novel paradigm of lung health throughout the adult life course.

Idiopathic pulmonary fibrosis (IPF) is characterized by progressive deposition of extracellular matrix, worsening dyspnea, and eventual mortality. Pathogenesis of IPF is poorly understood and the role inflammation and activated leukocytes play in the disease process is controversial. Previous studies demonstrated that activated leukocyte subsets characterize IPF patients. We sought to validate this observation in a well-defined cohort of 35 IPF patients and to correlate the observed leukocyte phenotypes with robust parameters of disease progression. We demonstrate that in univariate and multivariate analyses, increases in the CD14hi, CD16hi subset of monocytes measured at baseline correlated with disease progression, with a threshold value >0.5% of the total peripheral blood mononuclear cells being a significant predictor for worse outcome. In addition, several T cell subsets, including CD25 expressing CD4 cells, and CXCR3 expressing CD4 and CD8 subsets correlated with disease progression when found in increased percentages in the peripheral blood of IPF patients when sampled at baseline. Somewhat surprising in comparison to previous literature, the CD4 T cells did not appear to have lost expression of the co-stimulatory molecule, CD28, but the CD8 T cells did. Taken together, these results are consistent with the presence of an inflammatory process in IPF patients who eventually progress. However, when longitudinal measurements of these same markers were examined, there was significant heterogeneity of expression and these biomarkers did not necessarily remain elevated in IPF patients with progressive disease. We interpret this heterogeneity to suggest that IPF patients experience episodic inflammatory events that once triggered, may lead to disease progression. This longitudinal heterogeneity in biomarker analyses may explain why such markers are not consistently measured in all IPF cohorts.

Gastroesophageal reflux disease (GERD) is a common comorbidity in chronic obstructive pulmonary disease (COPD) and has been associated with increased risk of acute exacerbations, hospitalization, emergency room visits, costs, and quality-of-life impairment. However, it remains unclear whether GERD contributes to the progression of COPD as measured by lung function or computed tomography.

The coexistence of gastroesophageal reflux disease (GERD) and COPD has been recognized, but there has been no comprehensive evaluation of the impact of GERD on COPD-related health status and patient-centered outcomes.

Purpose: The purpose of this study was to train and validate machine learning models for predicting rapid decline of forced expiratory volume in 1 s (FEV1) in individuals with a smoking history at-risk-for chronic obstructive pulmonary disease (COPD), Global Initiative for Chronic Obstructive Lung Disease (GOLD 0), or with mild-to-moderate (GOLD 1-2) COPD. We trained multiple models to predict rapid FEV1 decline using demographic, clinical and radiologic biomarker data. Training and internal validation data were obtained from the COPDGene study and prediction models were validated against the SPIROMICS cohort. Methods: We used GOLD 0-2 participants (n = 3,821) from COPDGene (60.0 ± 8.8 years, 49.9% male) for variable selection and model training. Accelerated lung function decline was defined as a mean drop in FEV1% predicted of > 1.5%/year at 5-year follow-up. We built logistic regression models predicting accelerated decline based on 22 chest CT imaging biomarker, pulmonary function, symptom, and demographic features. Models were validated using n = 885 SPIROMICS subjects (63.6 ± 8.6 years, 47.8% male). Results: The most important variables for predicting FEV1 decline in GOLD 0 participants were bronchodilator responsiveness (BDR), post bronchodilator FEV1% predicted (FEV1.pp.post), and CT-derived expiratory lung volume; among GOLD 1 and 2 subjects, they were BDR, age, and PRMlower lobes fSAD. In the validation cohort, GOLD 0 and GOLD 1-2 full variable models had significant predictive performance with AUCs of 0.620 ± 0.081 (p = 0.041) and 0.640 ± 0.059 (p < 0.001). Subjects with higher model-derived risk scores had significantly greater odds of FEV1 decline than those with lower scores. Conclusion: Predicting FEV1 decline in at-risk patients remains challenging but a combination of clinical, physiologic and imaging variables provided the best performance across two COPD cohorts.