Hansel, Nadia N.

Abstract RATIONALE: Airway-to-lung ratio (AirLR), calculated as the mean of airway lumen diameters at standard anatomic locations divided by the cube-root of total lung volume, is associated with COPD risk regardless of smoking status, and we have previously shown an association between total-pulmonary-vascular-volume-to-lung-size relationship with AirLR. [PMCID: PMC11284327] Using dual energy computed tomography (DECT), we recently developed a deep learning-based algorithm for pulmonary arterial segmentation to compute pulmonary-arterial-to-lung ratio (ArtLR) which correlated significantly with AirLR and markers COPD. Here we automate image processing in a larger cohort to estimate ArtLR, introduce an alternative ArtLR standardization and correlate it to COPD-related measures of lung structure and function. METHODS: Using a SPIROMICS sub-cohort (110 participants), imaged via contrast enhanced DECT at functional residual capacity (FRC), an automatic deep learning pipeline segmented the arteries from the pulmonary vascular tree. Another pipeline automatically extracted the centerlines and calculated average arterial segment diameters. A paired non-contrast total lung capacity (TLC) scan was registered to the DECT FRC scan to transfer airway segment labels from the TLC to FRC domain. AirLR was calculated as the mean of airway lumen diameters at standard anatomic locations (trachea-to-subsegments) divided by cube root of lung volume [TLC or FRC]. A simple Long Short-Term Memory (LSTM) network was used to find corresponding anatomic arterial segments. Associations between ArtLR and %Emphysema, AirLR, pre- and post-bronchodilator FEV1/FVC, and a texture-based (AMFM) measure of %broncho-vascular bundles was assessed using linear regression to adjust for age, sex and BMI. RESULTS: In adjusted analyses, a 1-SD decrement in ArtLR-TLC was associated with 4.198 units increase in %Emphysema-910 (95%CI: 1.360-7.037; p = 0.0041), and 0.8198 units decrease in %Bronchovascular (95%CI: 0.5037-1.136; p < 0.0001). A 1-SD increment in ArtLR-TLC was associated with 0.2515 SD increase in AirLR-Outer (95%CI: 0.04947SD-0.4536SD; p = 0.0152), and 0.02083 units increase in PreBronch-FEV1FVC (95%CI: 0.001814-0.03984; p = 0.0321). Sex and BMI show significant associations with ArtLR-TLC, where female is associated with 1.068 SD decrease in ArtLR, and a unit increase in BMI is associated with 0.05788 SD increase in ArtLR (both p-values < 0.0001), and age was not association with ArtLR. CONCLUSIONS: An automated pipeline for pulmonary arterial tree segmentation and standardization from contrast enhanced DECT FRC scans demonstrates a significant relationship between ArtLR and AirLR as well as between ArtLR and %emphysema, and FEV1/FVC. A standardized method of arterial tree size assessment provides for expanded exploration of vascular vs airway disease etiologies.

Abstract Rationale. Bronchoscopy can directly assess cells in airway epithelium in participants with COPD, but it is invasive, expensive, difficult to perform at scale, and contraindicated in severe disease. Blood is much more easily available but contains only a limited subset of cell types, many of which are less relevant to lung biology. Recent advances in RNA-sequencing technology have allowed for reliable measurement of transcriptomics in a wider variety of more accessible tissues, including hair follicle cells. We collected and performed bulk RNA-seq on hair follicles as an ancillary study within the NIH-funded SubPopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS) and investigated their cell type composition to better understand the opportunities and limitations of this tissue for the study of lung disease. Methods. SPIROMICS recruited individuals with and without COPD aged 40-80 years with ≥ 20 pack-years smoking history. Participant at several sites underwent collection of approximately 10 hair follicles from the head, which were immediately frozen at -80ºC in 2018-21. mRNA in hair follicles was measured by bulk RNA-seq, and cell type deconvolution was performed using GEDIT v1.7 with the provided BlueCodeV1.0.tsv reference matrix. Cell types were collapsed into broader categories by summing the estimated cell type proportions. Results. The cell type deconvolution of the hair follicle bulk RNA-seq from 80 participants with and without COPD estimated that the tissue was largely composed of immune cells (median 36%, including B cells, T cells, neutrophils, macrophages, NK cells, and monocytes) and epithelial cell types (median 31%), with the largest subgroup of epithelial cell types identified as hair follicular keratinocytes (Figure 1). The next largest component was fibroblasts (median 9%), followed by endothelial cells (median 8%). Signals for myocytes (median 5%), melanocytes (median 5%), and chondrocytes (median 5%) were also present. Conclusion. This initial study demonstrated promising signals for a variety of lung-relevant cell types in hair follicles in SPIROMICS, including immune and epithelial cells in addition to fibroblasts and endothelial cells that are not otherwise easily accessible. Hair follicle gene expression profiling shows promise for understanding numerous facets of lung biology and disease that both complements and exceeds that of other noninvasive tissues such as blood.

Abstract Rationale Increased risk of coronavirus disease (COVID-19) hospitalization and death has been reported among patients with clinical lung disease. Objectives To test the association of objective measures of prepandemic lung function and structure with COVID-19 outcomes in U.S. adults. Methods Prepandemic obstruction (FEV1/FVC < 0.70) and restriction (FEV1/FVC ⩾ 0.7, FVC < 80%) were defined based on the most recent spirometry exam conducted in 11 prospective U.S. general population–based cohorts. Severe obstruction was classified by FEV1 < 50%. Percentage emphysema, percentage high-attenuation areas, and interstitial lung abnormalities were defined on computed tomography in a subset. Incident COVID-19 was ascertained via questionnaires, serosurvey, and medical records from 2020 to 2023 and classified as severe (hospitalized or fatal) or nonsevere. Cause-specific hazard models were adjusted for sociodemographics, anthropometry, smoking, comorbidities, and COVID-19 vaccination status. Measurements and Main Results Among 29,323 participants (mean age, 67 yr), there were 748 severe incident COVID-19 cases over median follow-up of 17.3 months from March 1, 2020. Greater hazards of severe COVID-19 were associated with severe obstruction (vs. normal; adjusted hazard ratio [aHR], 2.11; 95% confidence interval [CI], 1.02–1.27), restriction (vs. normal; aHR, 1.40; 95% CI, 1.12–1.76), and percentage emphysema (highest vs. lowest quartile; aHR, 1.64; 95% CI, 1.03–2.61), but not greater high-attenuation areas or interstitial lung abnormalities. COVID-19 vaccination provided greater absolute risk reduction in these groups. Results were similar in participants without smoking, obesity, or clinical cardiopulmonary disease. Conclusions Prepandemic severe spirometric obstruction, spirometric restriction, and greater percentage emphysema lung on computed tomography were associated with risk of severe COVID-19. These findings support enhanced COVID-19 risk mitigation for individuals with impaired lung health and warrant further mechanistic studies on interactions of lung function, structure, and vulnerability to acute respiratory illnesses.

Abstract Rationale Reliable data about the natural history of lung function decline in alpha-1 antitrypsin (AAT)-deficient Pi*MZ heterozygotes is largely missing. Objectives We hypothesized that, in adults with a tobacco smoking history, lung function deteriorates faster in Pi*MZ compared with the Pi*MM genotype. Methods We identified 1,856 Pi*MM and 79 Pi*MZ participants with ⩾20 pack-years tobacco smoking history from the SPIROMICS (Subpopulations and Intermediate Outcomes Measures in COPD Study) cohort by DNA sequencing and followed them over a median of 4.8 years, comparing radiographic and clinical characteristics between the two groups over time using regression models. Results Adjusted for age, sex, race, smoking pack-year history, and smoking status, Pi*MZ participants had a lower baseline percent predicted forced expiratory volume in 1 second (FEV1) (65.4% vs. 75.1%; difference 95% confidence interval [CI], −15.4% to −3.9%), more radiographic emphysema (<−950 Hounsfield units%, 12.9% vs. 7.8%; difference 95% CI, 2.8% to 7.5%), and nonsignificantly lower lung density. In the longitudinal analysis, the FEV1 annual rate of decline was similar in both groups over the course of the study (−34.5 ml/yr vs. −34.6 ml/yr for Pi*MZ and Pi*MM; difference 95% CI, −16.9 to 17.1 ml/yr). There were no significant differences between Pi*MZ and Pi*MM individuals in the annualized change in lung density, emphysema, patient-reported outcomes, exacerbations, or survival. The proportion with faster FEV1 decline (annual loss ⩾40 ml) was similar in Pi*MZ and Pi*MM groups. In both groups, faster FEV1 decline was associated with more air trapping and small airway disease at baseline. In Pi*MZ only, faster decline was associated with higher blood eosinophil counts (310 vs. 220 cells/μl; difference 95% CI, 30 to 140 cells/μl). In the subgroup analysis limited to a small number of currently smoking participants, no significant differences in longitudinal outcomes were found. Conclusions Despite a lower FEV1 and more emphysema at enrollment, the longitudinal analysis did not demonstrate significantly greater lung function decline or lung density loss in Pi*MZ compared with Pi*MM participants with tobacco smoking history. Limited sample size and duration of longitudinal follow-up constrain generalizability of our findings, thus prohibiting the conclusion that longitudinal trajectories did not differ between these groups. However, our results may suggest that earlier life events could be responsible for more extensive lung disease at enrollment in Pi*MZ compared with Pi*MM tobacco-exposed individuals.

Abstract Rationale Among tobacco-exposed persons with preserved spirometry (TEPSs), we previously demonstrated that different lung volume indices—specifically, elevated total lung capacity (TLC) versus elevated ratio of functional residual capacity to TLC (FRC/TLC)—identify different lung disease characteristics in the COPDGene cohort. Objective We sought to determine differential disease characteristics and trajectories associated with lung volume indices among TEPSs in the SPIROMICS cohort. Methods We categorized TEPSs (n = 814) by tertiles (low, intermediate, and high) of TLC or residual volume–to-TLC ratio (RV/TLC) derived from baseline computed tomography images and then examined clinical and spirometric disease trajectories in mutually exclusive categories of participants with high TLC without high RV/TLC ([TLC]high) versus high RV/TLC without high TLC ([RV/TLC]high). We examined differences in computed tomography–measured emphysema (Hounsfield units [HU] ⩽−950; parametric response mapping [PRM] of emphysema), air trapping (HU⩽−856; PRM of functional small airway disease; a disease probability measure for non-emphysematous gas trapping), airway geometry (the mean square root of wall area of a hypothetical airway with 10 mm internal perimeter), respiratory symptoms (on the modified Medical Research Council Dyspnea Scale; COPD Assessment Test [CAT]; St. George’s Respiratory Questionnaire [SGRQ]; and Short Form-12 [SF12]), and outcomes (annualized exacerbation rate) between the two categories at baseline and over follow-up time up to 8.5 years, using regression modeling adjusted for age, sex, height, weight, and smoking status (current vs. former smoker) and burden (pack-years). Results In TEPSs, the pattern of spirometric disease progression differed between participants with [TLC]high and those with [RV/TLC]high: There was increased forced vital capacity with stable forced expiratory volume in 1 second in participants with [TLC]high, versus unchanged forced vital capacity but nominally decreased forced expiratory volume in 1 second in those with [RV/TLC]high. Compared with participants with [TLC]high, TEPSs with [RV/TLC]high had less emphysema (by HU ⩽−950) but more airway disease (by HU ⩽−856; PRM of functional small airway disease; disease probability measure for gas trapping, and mean square root of wall area of a hypothetical airway with 10 mm internal perimeter), more respiratory symptoms (on the modified Medical Research Council Dyspnea Scale, CAT, SGRQ, and SF12), and more severe exacerbations at baseline. Over an average follow-up of 4.1 ± 2.4 years (range = 0.5–8.5 yr), TEPSs with [RV/TLC]high also had a higher likelihood of developing more severe spirometric disease (preserved ratio impaired spirometry or Global Initiative for Chronic Obstructive Lung Disease Classification 2) and worsening of their respiratory symptoms (on the CAT and SGRQ). Although the incidence rates of respiratory exacerbations, hospitalizations, and mortality were not significantly different between the two categories over the follow-up period, TEPSs with [RV/TLC]high were more likely to have been prescribed a respiratory inhaler at their last follow-up visit. Conclusions In these TEPSs from the SPIROMICS cohort, lung volume stratification by TLC versus RV/TLC identifies two pre-COPD phenotypes with distinct respiratory symptoms, radiographic features, and clinical trajectories. The characteristics of these pre-COPD phenotypes match those previously described in the COPDGene cohort using TLC versus FRC/TLC stratification.