Association of Ground Glass Opacities with Systemic Inflammation and Progression of Emphysema.

RATIONAL: Ground glass opacities (GGO) in the absence of interstitial lung disease are understudied. OBJECTIVE: To assess the association of GGO with white blood cells (WBCs) and progression of quantified chest CT emphysema. METHODS: We analyzed data of participants in the Subpopulations and Intermediate Outcome Measures In COPD Study (SPIROMICS). Chest radiologists and pulmonologists labeled regions of the lung as GGO and adaptive multiple feature method (AMFM) trained the computer to assign those labels to image voxels and quantify the volume of the lung with GGO (%GGOAMFM). We used multivariable linear regression, zero-inflated negative binomial, and proportional hazards regression models to assess the association of %GGOAMFM with WBC, changes in %emphysema, and clinical outcomes. MEASUREMENTS AND MAIN RESULTS: Among 2,714 participants, 1,680 had COPD and 1,034 had normal spirometry. Among COPD participants, based on the multivariable analysis, current smoking and chronic productive cough was associated with higher %GGOAMFM. Higher %GGOAMFM was cross-sectionally associated with higher WBCs and neutrophils levels. Higher %GGOAMFM per interquartile range at visit 1 (baseline) was associated with an increase in emphysema at one-year follow visit by 11.7% (Relative increase; 95%CI 7.5-16.1%;P<0.001). We found no association between %GGOAMFM and one-year FEV1 decline but %GGOAMFM was associated with exacerbations and all-cause mortality during a median follow-up time of 1,544 days (Interquartile Interval=1,118-2,059). Among normal spirometry participants, we found similar results except that %GGOAMFM was associated with progression to COPD at one-year follow-up. CONCLUSIONS: Our findings suggest that GGOAMFM is associated with increased systemic inflammation and emphysema progression.

Small Extracellular Vesicle Signaling and Mitochondrial Transfer Reprograms T Helper Cell Function in Human Asthma.

RATIONALE: Asthma is a chronic inflammatory disease of the airways that involves crosstalk between myeloid-derived regulatory cells (MDRCs) and CD4+ T cells. Although small extracellular vesicles (sEVs) are known to mediate cell-cell communication, the role of sEV signaling via mitochondria in perpetuating asthmatic airway inflammation is unknown. OBJECTIVES: We investigated the effects of MDRC-derived exosomes on dysregulated T cell responses in asthmatics. METHODS: Small extracellular vesicles isolated from bronchoalveolar lavage fluid or airway MDRCs of mild to moderate asthmatics or healthy controls were co-cultured with autologous peripheral and airway CD4+ T lymphocytes. sEV internalization, sEV-mediated transfer of mitochondria targeted GFP to T cells, sEV mitochondrial signaling, and subsequent activation, proliferation and polarization of CD4+ T lymphocytes to Th1, Th2 and Th17 subsets were assessed. MEASUREMENTS AND MAIN RESULTS: Airway MDRC-derived sEVs from asthmatics mediated T cell receptor engagement and transfer of mitochondria that induced antigen-specific activation and polarization into Th17 and Th2 cells, drivers of chronic airway inflammation in asthma. CD4+ T cells internalized sEVs containing mitochondria predominantly by membrane fusion, and blocking mitochondrial oxidant signaling in MDRC-derived exosomes mitigated T cell activation. Reactive oxygen species-mediated signaling that elicited T cell activation in asthmatics was sEV-dependent. A Drp1-dependent mitochondrial fission in pro-inflammatory MDRCs promoted mitochondrial packaging within sEVs, which then co-localized with the polarized actin cytoskeleton and mitochondrial networks in the organized immune synapse of recipient T cells. CONCLUSIONS: Our studies indicate a previously unrecognized role for mitochondrial fission and exosomal mitochondrial transfer in dysregulated T cell activation and Th cell differentiation in asthma which could constitute a novel therapeutic target.

Association of musculoskeletal involvement with lung function and mortality in patients with idiopathic pulmonary fibrosis.

Idiopathic pulmonary fibrosis (IPF) is a progressive disease associated with high mortality. Low muscle mass, frailty and sarcopenia lead to functional impairment that negatively impact quality of life and survival but are not used in clinical practice. We aimed to determine the association of Fat-free mass index (FFMI) and frailty with lung function, exercise tolerance and survival in patients with IPF. In this study, 70 patients with IPF underwent assessment of body composition, lung function, 6-min walk distance (6MWD) testing, hand grip strength, quality of life (QoL) assessment by St. George's Respiratory questionnaire (SGRQ) and frailty assessment using the SHARE-FI tool. FFMI was calculated using pectoralis muscle cross-sectional area (PM-CSA) on CT chest images and the lowest quartile defined reduced muscle mass. Sarcopenia was defined as low FFMI and handgrip strength. Regression analyses were conducted to determine predictive value of frailty, low FFMI and sarcopenia on clinical outcomes. The Cox proportional hazards model was used to analyze the impact of FFMI and frailty score on survival. The mean age was 70 years with moderate impairment in lung function (mean ppFVC 68.5%, ppDLCO 45.6%). Baseline forced vital capacity (p < 0.001), diffusion capacity of lung for carbon monoxide (p = < 0.01), 6WMD (p < 0.05) were significantly lower in frail patients compared to non-frail patients. BMI was found to closely correlate with FFMI (r = 0.79, p < 0.001), but not with frailty score (r = - 0.2, p = 0.07). Frailty was a significant predictor of FVC, DLCO, 6MWD, SGRQ scores when adjusted for age and gender. Muscle mass and sarcopenia were significant predictors of FVC, DLCO, but not 6MWD or QoL scores. Multivariate cox-proportional hazards ratio model adjusting for age and gender showed that frailty was significantly associated with increased mortality (HR = 2.6, 95% CI 1.1-6.1). Low FFMI (HR = 1.3, 95% CI 0.6-2.8), and sarcopenia (HR = 2.1, 95% CI 0.8-5.3), though associated with a trend to increased mortality, were not statistically significant. Frailty is associated with lower lung function and higher mortality in patients with IPF. Longitudinal evaluations are necessary to further determine the associations between low FFMI, sarcopenia and frailty with outcomes in IPF.

Dysanapsis is differentially related to lung function trajectories with distinct structural and functional patterns in COPD and variable risk for adverse outcomes.

Background: Abnormal lung function trajectories are associated with increased risk of chronic obstructive pulmonary disease (COPD) and premature mortality; several risk factors for following these trajectories have been identified. Airway under-sizing dysanapsis (small airway lumens relative to lung size), is associated with an increased risk for COPD. The relationship between dysanapsis and lung function trajectories at risk for adverse outcomes of COPD is largely unexplored. We test the hypothesis that dysanapsis differentially affects distinct lung function trajectories associated with adverse outcomes of COPD. Methods: To identify lung function trajectories, we applied Bayesian trajectory analysis to longitudinal FEV1 and FVC Z-scores in the COPDGene Study, an ongoing longitudinal study that collected baseline data from 2007 to 2012. To ensure clinical relevance, we selected trajectories based on risk stratification for all-cause mortality and prospective exacerbations of COPD (ECOPD). Dysanapsis was measured in baseline COPDGene CT scans as the airway lumen-to-lung volume (a/l) ratio. We compared a/l ratios between trajectories and evaluated their association with trajectory assignment, controlling for previously identified risk factors. We also assigned COPDGene participants for whom only baseline data is available to their most likely trajectory and repeated our analysis to further evaluate the relationship between trajectory assignment and a/l ratio measures. Findings: We identified seven trajectories: supranormal, reference, and five trajectories at increased risk for mortality and exacerbations. Three at-risk trajectories are characterized by varying degrees of concomitant FEV1 and FVC impairments and exhibit airway predominant COPD patterns as assessed by quantitative CT imaging. These trajectories have lower a/l ratio values and increased risk for mortality and ECOPD compared to the reference trajectory. Two at-risk trajectories are characterized by disparate levels of FEV1 and FVC impairment and exhibit mixed airway and emphysema COPD patterns on quantitative CT imaging. These trajectories have markedly lower a/l ratio values compared to both the reference trajectory and airway-predominant trajectories and are at greater risk for mortality and ECOPD compared to the airway-predominant trajectories. These findings were observed among the participants with baseline-only data as well. Interpretation: The degree of dysanapsis appears to portend patterns of progression leading to COPD. Assignment of individuals-including those without spirometric obstruction-to distinct trajectories is possible in a clinical setting and may influence management strategies. Strategies that combine CT-assessed dysanapsis together with spirometric measures of lung function and smoke exposure assessment are likely to further improve trajectory assignment accuracy, thereby improving early detection of those most at risk for adverse outcomes. Funding: United States National Institute of Health, COPD Foundation, and Brigham and Women's Hospital.

Altered sphingolipid pathway in SARS-CoV-2 infected human lung tissue.

Introduction: The SARS-CoV-2 mediated COVID-19 pandemic has impacted millions worldwide. Hyper-inflammatory processes, including cytokine storm, contribute to long-standing tissue injury and damage in COVID-19. The metabolism of sphingolipids as regulators of cell survival, differentiation, and proliferation has been implicated in inflammatory signaling and cytokine responses. Sphingosine-kinase-1 (SK1) and ceramide-synthase-2 (CERS2) generate metabolites that regulate the anti- and pro-apoptotic processes, respectively. Alterations in SK1 and CERS2 expression may contribute to the inflammation and tissue damage during COVID-19. The central objective of this study is to evaluate structural changes in the lung post-SARS-CoV-2 infection and to investigate whether the sphingolipid rheostat is altered in response to SARS-CoV-2 infection. Methods: Central and peripheral lung tissues from COVID-19+ or control autopsies and resected lung tissue from COVID-19 convalescents were subjected to histologic evaluation of airspace and collagen deposisiton, and immunohistochemical evaluation of SK1 and CERS2. Results: Here, we report significant reduction in air space and increase in collagen deposition in lung autopsy tissues from patients who died from COVID-19 (COVID-19+) and COVID-19 convalescent individuals. SK1 expression increased in the lungs of COVID-19+ autopsies and COVID-19 convalescent lung tissue compared to controls and was mostly associated with Type II pneumocytes and alveolar macrophages. No significant difference in CERS2 expression was noted. SARS-CoV-2 infection upregulates SK1 and increases the ratio of SK1 to CERS2 expression in lung tissues of COVID-19 autopsies and COVID-19 convalescents. Discussion: These data suggest an alteration in the sphingolipid rheostat in lung tissue during COVID-19, suggesting a potential contribution to the inflammation and tissue damage associated with viral infection.

Myeloid Heterogeneity Mediates Acute Exacerbations of Pulmonary Fibrosis.

Epidemiological evidence indicates that exposure to particulate matter is linked to the development of idiopathic pulmonary fibrosis (IPF) and increases the incidence of acute exacerbations of IPF. In addition to accelerating the rate of lung function decline, exposure to fine particulate matter (particulate matter smaller than 2.5 µm [PM2.5]) is a risk factor for increased mortality in subjects with IPF. In this article, we show that exposure to PM2.5 mediates monocyte recruitment and fibrotic progression in mice with established fibrosis. In mice with established fibrosis, bronchoalveolar lavage cells showed monocyte/macrophage heterogeneity after exposure to PM2.5. These cells had a significant inflammatory and anti-inflammatory signature. The mixed heterogeneity of cells contributed to the proinflammatory and anti-inflammatory response. Although monocyte-derived macrophages were recruited to the lung in bleomycin-injured mice treated with PM2.5, recruitment of monocytes expressing Ly6Chi to the lung promoted progression of fibrosis, reduced lung aeration on computed tomography, and impacted lung compliance. Ly6Chi monocytes isolated from PM2.5-exposed fibrotic mice showed enhanced expression of proinflammatory markers compared with fibrotic mice exposed to vehicle. Moreover, IPF bronchoalveolar lavage cells treated ex vivo with PM2.5 showed an exaggerated inflammatory response. Targeting Ly6Chi monocyte recruitment inhibited fibrotic progression in mice. Moreover, the adoptive transfer of Ly6Chi monocytes exacerbated established fibrosis. These observations suggest that enhanced recruitment of Ly6Chi monocytes with a proinflammatory phenotype mediates acute exacerbations of pulmonary fibrosis, and targeting these cells may provide a potential novel therapeutic target to protect against acute exacerbations of IPF.

Influence of Pulsatility and Inflow Waveforms on Tracheal Airflow Dynamics in Healthy Older Adults.

Tracheal collapsibility is a dynamic process altering local airflow dynamics. Patient-specific simulation is a powerful technique to explore the physiological and pathological characteristics of human airways. One of the key considerations in implementing airway computations is choosing the right inlet boundary conditions that can act as a surrogate model for understanding realistic airflow simulations. To this end, we numerically examine airflow patterns under the influence of different profiles, i.e., flat, parabolic, and Womersley, and compare these with a realistic inlet obtained from experiments. Simulations are performed in ten patient-specific cases with normal and rapid breathing rates during the inhalation phase of the respiration cycle. At normal breathing, velocity and vorticity contours reveal primary flow structures on the sagittal plane that impart strength to cross-plane vortices. Rapid breathing, however, encounters small recirculation zones. Quantitative flow metrics are evaluated using time-averaged wall shear stress (TAWSS) and oscillatory shear index (OSI). Overall, the flow metrics encountered in a real velocity profile are in close agreement with parabolic and Womersley profiles for normal conditions, however, the Womersley inlet alone conforms to a realistic profile under rapid breathing conditions.

Radiomics for Improved Detection of Chronic Obstructive Pulmonary Disease in Low-Dose and Standard-Dose Chest CT Scans.

Background Approximately half of adults with chronic obstructive pulmonary disease (COPD) remain undiagnosed. Chest CT scans are frequently acquired in clinical practice and present an opportunity to detect COPD. Purpose To assess the performance of radiomics features in COPD diagnosis using standard-dose and low-dose CT models. Materials and Methods This secondary analysis included participants enrolled in the Genetic Epidemiology of COPD, or COPDGene, study at baseline (visit 1) and 10 years after baseline (visit 3). COPD was defined by a forced expiratory volume in the 1st second of expiration to forced vital capacity ratio less than 0.70 at spirometry. The performance of demographics, CT emphysema percentage, radiomics features, and a combined feature set derived from inspiratory CT alone was evaluated. CatBoost (Yandex), a gradient boosting algorithm, was used to perform two classification experiments to detect COPD; the two models were trained and tested on standard-dose CT data from visit 1 (model I) and low-dose CT data from visit 3 (model II). Classification performance of the models was evaluated using area under the receiver operating characteristic curve (AUC) and precision-recall curve analysis. Results A total of 8878 participants (mean age, 57 years ± 9 [SD]; 4180 female, 4698 male) were evaluated. Radiomics features in model I achieved an AUC of 0.90 (95% CI: 0.88, 0.91) in the standard-dose CT test cohort versus demographics (AUC, 0.73; 95% CI: 0.71, 0.76; P < .001), emphysema percentage (AUC, 0.82; 95% CI 0.80, 0.84; P < .001), and combined features (AUC, 0.90; 95% CI: 0.89, 0.92; P = .16). Model II, trained on low-dose CT scans, achieved an AUC of 0.87 (95% CI: 0.83, 0.91) on the 20% held-out test set for radiomics features compared with demographics (AUC, 0.70; 95% CI: 0.64, 0.75; P = .001), emphysema percentage (AUC, 0.74; 95% CI: 0.69, 0.79; P = .002), and combined features (AUC, 0.88; 95% CI: 0.85, 0.92; P = .32). Density and texture features were the majority of the top 10 features in the standard-dose model, whereas shape features of lungs and airways were significant contributors in the low-dose CT model. Conclusion A combination of features representing parenchymal texture and lung and airway shape on inspiratory CT scans can be used to accurately detect COPD. ClinicalTrials.gov registration no. NCT00608764 © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Vliegenthart in this issue.

FEV1/FVC Severity Stages for Chronic Obstructive Pulmonary Disease.

Rationale: The diagnosis of chronic obstructive pulmonary disease (COPD) is based on a low FEV1/FVC ratio, but the severity of COPD is classified using FEV1% predicted (ppFEV1). Objectives: To test a new severity classification scheme for COPD using FEV1/FVC ratio, a more robust measure of airflow obstruction than ppFEV1. Methods: In COPDGene (Genetic Epidemiology of COPD) (N = 10,132), the severity of airflow obstruction was categorized by Global Initiative for Chronic Obstructive Lung Disease (GOLD) stages 1-4 (ppFEV1 of ⩾80%, ⩾50-80%, ⩾30-50%, and <30%). A new severity classification (STaging of Airflow obstruction by Ratio; STAR) was tested in COPDGene-FEV1/FVC ⩾0.60 to <0.70, ⩾0.50 to <0.60, ⩾0.40 to <0.50, and <0.40, respectively, for stages 1-4-and applied to the combined Pittsburgh SCCOR and Emphysema COPD Research Registry for replication (N = 2,017). Measurements and Main Results: The agreements (weighted Bangdiwala B values) between GOLD and the new FEV1/FVC ratio severity stages were 0.89 in COPDGene and 0.88 in the Pittsburgh cohort. In COPDGene and the Pittsburgh cohort, compared with GOLD staging, STAR provided significant discrimination between the absence of airflow obstruction and stage 1 for all-cause mortality, respiratory quality of life, dyspnea, airway wall thickness, exacerbations, and lung function decline. No major differences were noted for emphysema, small airway disease, and 6-minute-walk distance. The STAR classification system identified a greater number of adults with stage 3/4 disease who would be eligible for lung transplantation and lung volume reduction procedure evaluations. Conclusions: The new STAR severity classification scheme provides discrimination for mortality that is similar to the GOLD classification but with a more uniform gradation of disease severity. STAR differentiates patients' symptoms, disease burden, and prognosis better than the existing scheme based on ppFEV1, and is less sensitive to race/ethnicity and other demographic characteristics.

Deep Learning Utilizing Suboptimal Spirometry Data to Improve Lung Function and Mortality Prediction in the UK Biobank.

Background: Spirometry measures lung function by selecting the best of multiple efforts meeting pre-specified quality control (QC), and reporting two key metrics: forced expiratory volume in 1 second (FEV1) and forced vital capacity (FVC). We hypothesize that discarded submaximal and QC-failing data meaningfully contribute to the prediction of airflow obstruction and all-cause mortality. Methods: We evaluated volume-time spirometry data from the UK Biobank. We identified "best" spirometry efforts as those passing QC with the maximum FVC. "Discarded" efforts were either submaximal or failed QC. To create a combined representation of lung function we implemented a contrastive learning approach, Spirogram-based Contrastive Learning Framework (Spiro-CLF), which utilized all recorded volume-time curves per participant and applied different transformations (e.g. flow-volume, flow-time). In a held-out 20% testing subset we applied the Spiro-CLF representation of a participant's overall lung function to 1) binary predictions of FEV1/FVC < 0.7 and FEV1 Percent Predicted (FEV1PP) < 80%, indicative of airflow obstruction, and 2) Cox regression for all-cause mortality. Findings: We included 940,705 volume-time curves from 352,684 UK Biobank participants with 2-3 spirometry efforts per individual (66.7% with 3 efforts) and at least one QC-passing spirometry effort. Of all spirometry efforts, 24.1% failed QC and 37.5% were submaximal. Spiro-CLF prediction of FEV1/FVC < 0.7 utilizing discarded spirometry efforts had an Area under the Receiver Operating Characteristics (AUROC) of 0.981 (0.863 for FEV1PP prediction). Incorporating discarded spirometry efforts in all-cause mortality prediction was associated with a concordance index (c-index) of 0.654, which exceeded the c-indices from FEV1 (0.590), FVC (0.559), or FEV1/FVC (0.599) from each participant's single best effort. Interpretation: A contrastive learning model using raw spirometry curves can accurately predict lung function using submaximal and QC-failing efforts. This model also has superior prediction of all-cause mortality compared to standard lung function measurements. Funding: MHC is supported by NIH R01HL137927, R01HL135142, HL147148, and HL089856.BDH is supported by NIH K08HL136928, U01 HL089856, and an Alpha-1 Foundation Research Grant.DH is supported by NIH 2T32HL007427-41EKS is supported by NIH R01 HL152728, R01 HL147148, U01 HL089856, R01 HL133135, P01 HL132825, and P01 HL114501.PJC is supported by NIH R01HL124233 and R01HL147326.SPB is supported by NIH R01HL151421 and UH3HL155806.TY, FH, and CYM are employees of Google LLC.

Parameter D: New Measure of Airflow Obstruction.

Rationale: Currently used spirometry measures of airflow obstruction are influenced by demographics, predominantly by age, complicating selection of diagnostic thresholds for the presence of airflow obstruction. Objectives: To develop diagnostic thresholds for Parameter D, a new metric for detection of airflow obstruction, which quantifies the rate of rise of expiratory volume over time. Methods: We analyzed spirometry data of normal subjects enrolled in the 2007-2008, 2009-2010, and 2011-2012 NHANES (National Health and Nutrition Examination Survey) cohorts and calculated Parameter D using the expiratory volume-time curve. Relationships between demographics and lung function (forced expiratory volume in 1 second [FEV1], FEV1/forced vital capacity [FVC], and Parameter D) were tested using generalized linear models in NHANES and UK Biobank. The variation in lung function explained by demographics was estimated using R2. A diagnostic threshold was developed for Parameter D using population-based percentiles. Based on concordance between the lower limit of normal (LLN) for FEV1/FVC and the Parameter D threshold, four groups were identified: normal (no airflow obstruction by either criterion), D+chronic obstructive pulmonary disease (D+COPD; positive by Parameter D only), D-COPD (positive by LLN only), and COPD (positive by both criteria), and associations with structural lung disease, exacerbations, and mortality were tested using multivariable analyses. Results: In contrast to FEV1 and FEV1/FVC, demographics cumulatively explained only 9% of the variance in Parameter D in NHANES (n = 4,945) and 3% in UK BioBank (n = 109,623). In COPDGene (Genetic Epidemiology of Chronic Obstructive Pulmonary Disease) (n = 9,542), a diagnostic threshold of -3.15 resulted in the identification of an additional 10.8% of participants with airflow obstruction. A total of 3.7% had FEV1/FVC < LLN but were missed by the Parameter D threshold. Compared with subjects in the normal group, after adjustment for age, sex, race, body mass index, pack-years of smoking, and current smoking status, D+COPD was associated with worse structural lung disease (odds ratio [OR] for ⩾5% emphysema, 1.71; 95% confidence interval [CI], 1.37-2.12; OR for functional small airway disease ⩾ 15%, 2.1; 95% CI, 1.79-2.67) and significant symptoms (OR for modified Medical Research Council dyspnea score ⩾ 2, 1.25; 95% CI, 1.07-1.47; OR for St. George's respiratory questionnaire ⩾ 25, 1.31; 95% CI, 1.13-1.53), a greater frequency of exacerbations (incidence rate ratio, 1.26; 95% CI, 1.10-1.46), and higher mortality (hazard ratio, 1.32; 95% CI, 1.10-1.57). Over 5 years, 28% of the D+COPD group versus 8% of normal group progressed to COPD by traditional criteria. Conclusions: Parameter D is not affected by age, and a normal population-based diagnostic threshold results in the early identification of additional individuals with airflow obstruction with a substantial amount of structural lung disease and respiratory symptoms.