Couper, D

Abstract Rationale Mismatch of airway to lung size has been implicated in chronic obstructive pulmonary disease (COPD) pathophysiology, whether arising from disproportioned growth or from acquired pathologies over the life course. Lower airway-to-lung ratio (ALR), assessed reproducibly via computed tomography (CT) as the mean airway lumen diameters (trachea-to-subsegments) divided by the cubed root of lung volume, is associated with COPD risk and mortality (all-cause, respiratory, cardiovascular, lung cancer). We sought to characterize the airway biology associated with lower ALR by profiling bronchial gene expression across current and former smokers. Methods We leveraged clinical, radiologic, and bronchial epithelial RNA sequencing data from the SPIROMICS (SubPopulations and Intermediate Outcomes Measures in COPD Study) Phase 1 Bronchoscopy Sub-study (n = 161). To analyze transcriptional differential expression (DE) between participants based on CT-assessed ALR, we utilized DESeq2 and then identified impacted pathways by Ingenuity Pathway Analysis (IPA). Generating cell-type transcriptional signatures from lung and blood single cell sequencing atlases, we also assessed association of ALR with differences in airway cellular composition. Results Across all ever-smokers, after adjustment for age, sex, height, COPD status, smoking status, and pack-years, n = 1,324 genes from airway epithelial samples exhibited DE at a false discovery rate (FDR) <0.2. Per IPA, enriched pathways associated with lower ALR included neutrophilic degranulation and macrophage activity. In cell type analysis, lower ALR was associated with higher signatures of macrophages, neutrophils, dendritic cells, and B cells, and lower ciliated and club cell signatures. When we repeated DE analysis using the same covariate adjustments plus an interaction term for ALR and smoking, n = 713 DE genes were identified at FDR <0.2; the association of DE with lower ALR was overwhelmingly in current rather than former smokers (3699 vs. 2 genes). By pathway and cell type analyses, the association between lower ALR and heightened inflammation (greater macrophage and neutrophil signaling) and epithelial dysregulation (downregulated ciliated and club cell function) was primarily restricted to current smokers. Conclusions In adult ever-smokers, lower ALR is associated with transcriptomic evidence of heightened neutrophil- and macrophage-driven airway inflammation and reduced ciliated and club cell expression, associations that were most evident among current smokers. Whether these cross-sectional patterns, which suggest impaired mucociliary defense and a diminished capacity to clear inhaled particulates, are the result of pre-existing reduced ALR, its cause, or both, will require further investigation. This abstract is funded by: SPIROMICS was supported by contracts from the NIH/NHLBI (HHSN268200900013C, HHSN268200900014C, HHSN268200900015C, HHSN268200900016C, HHSN268200900017C, HHSN268200900018C, HHSN268200900019C, HHSN268200900020C, 75N92024D00012), grants from the NIH/NHLBI (U01HL137880, U24HL141762, R01HL182622, R01HL144718, and R01HL093081), and supplemented by contributions made through the Foundation for the NIH and the COPD Foundation from Amgen; AstraZeneca/MedImmune; Bayer; Bellerophon Therapeutics; Boehringer-Ingelheim Pharmaceuticals, Inc.; Bristol Myers Squibb; Chiesi Farmaceutici S.p.A.; Forest Research Institute, Inc.; Genentech; GlaxoSmithKline; Grifols Therapeutics, Inc.; Ikaria, Inc.; MGC Diagnostics; Novartis Pharmaceuticals Corporation; Nycomed GmbH; Polarean; ProterixBio; Regeneron Pharmaceuticals, Inc.; Sanofi; Sunovion; Takeda Pharmaceutical Company; Theravance Biopharma; Verona; and Mylan/Viatris.

Abstract Rationale Eosinophilic airway inflammation in COPD is associated with more frequent exacerbations,lower lung function,and corticosteroid responsiveness.DNA methylation captures information about genetic factors and environmental exposures, but is under-studied in eosinophilic COPD.We hypothesized that sputum cell methylation patterns reflect genomic regulation of inflammatory endotypes in COPD by DNA sequence variation. Methods We analyzed DNA previously extracted from induced sputum cells for a prior study(PMID38261629) for which sufficient quantity DNA remained for methylation arrays.For this analysis,we focused on n = 132 SPIROMICS participants with ≥20 pack-years smoking history.Samples were stratified into tertiles based on sputum eosinophil proportions,previously determined from sputum cell differential analysis by the centralized sputum analysis core for SPIROMICS(Univ of North Carolina).We assessed proportion of DNA methylation (β values) spanning 936,866 CpG sites using the Illumina Infinium Methylation EPICv2.0 BeadChip Array,which we transformed into M values(meffil R package). To identify differentially methylated regions (DMRs)(FDR<0.05 in minimum of 2 CpG sites per gene region),we contrasted CpG β values between the high-eosinophil and low-eosinophil tertiles(N = 44 each),using the DMRcate package.We tested for enrichment of genes overlapping with significant DMRs using Enrichr (GWAS Catalog 2025 gene set library).To identify genetic variants associated with DNA methylation levels,we performed Methylation Quantitative Trait Loci (meQTL) analysis using TensorQTL.For each CpG site,we tested associations with SNPs within a ± 500 kb window (cis-meQTL).The linear regression model included age,sex,BMI,smoking status,smoking pack-years,study site,inhaled corticosteroid use, the first two genetic principal components, cell-type proportions (macrophages/monocytes, neutrophils, squamous epithelial cells, lymphocytes), and eosinophil tertile . Significant meQTLs were identified at an FDR<0.05 using Benjamini-Hochberg correction. Results A total of 532 eosinophil-associated DMRs (FDR < 0.05) were identified between the high- and low-eosinophil groups,encompassing 446 unique genes.The top enriched pathways related to counts of eosinophils (adjusted p = 0. 00002464), lymphocytes (adjusted p = 0.0001860), and the sum of eosinophils-plus-basophils (adjusted p = 0.0001860).We identified 18,432 significant SNP-CpG/meQTL pairs (FDR < 0.05),suggesting extensive genetic influence on airway DNA methylation patterns.Among the n = 521 eosinophil-associated CpGs that overlapped with meQTLs,rs55687040 (TENT2,a gene involved in mRNA and miRNA processing) is a GWAS locus for FEV1/FVC ratio (PMID: 26634245), suggesting possible genetic control of airway eosinophilic methylation signatures. Conclusions Our findings disclose distinct DNA methylation signatures associated with sputum eosinophil proportion in COPD.A subset of these CpGs are regulated by genetic variants,suggesting an integrated genetic-epigenetic mechanism underlying airway eosinophilic inflammation with the potential to influence COPD risk and severity. This abstract is funded by: SPIROMICS was supported by contracts from the NIH/NHLBI (HHSN268200900013C, HHSN268200900014C, HHSN268200900015C, HHSN268200900016C, HHSN268200900017C, HHSN268200900018C, HHSN268200900019C, HHSN268200900020C), grants from the NIH/NHLBI (U01 HL137880, U24 HL141762, R01 HL182622, and R01 HL144718), and supplemented by contributions made through the Foundation for the NIH and the COPD Foundation from Amgen; AstraZeneca/MedImmune; Bayer; Bellerophon Therapeutics; Boehringer-Ingelheim Pharmaceuticals, Inc.; Chiesi Farmaceutici S.p.A.; Forest Research Institute, Inc.; Genentech; GlaxoSmithKline; Grifols Therapeutics, Inc.; Ikaria, Inc.; MGC Diagnostics; Novartis Pharmaceuticals Corporation; Nycomed GmbH; Polarean; ProterixBio; Regeneron Pharmaceuticals, Inc.; Sanofi; Sunovion; Takeda Pharmaceutical Company; and Theravance Biopharma and Mylan/Viatris.

Abstract Rationale Thymic stromal lymphopoietin (TSLP) is an epithelial alarmin chiefly implicated in T2 airway inflammation, though it may also participate in broader (non-T2) inflammatory processes. The utility of airway epithelial gene expression of TSLP and its specific receptor subunit, cytokine receptor-like factor 2 (CRLF2), as biomarkers of downstream inflammation and clinical outcomes remains unclear. Methods We analyzed RNA sequencing data from bronchial airway brushing obtained in phase 1 of the SPIROMICS bronchoscopy sub-study (N = 161: 23 never-smokers, 67 ever-smokers with COPD, 71 ever-smokers without COPD). We related airway TSLP and CRLF2 expression to clinical, hematologic/sputum measures, and gene-expression signatures of T2/eosinophilic and neutrophilic inflammation, including to our published T2 signature and to eosinophil and neutrophil signatures derived from single-cell atlas data. Associations used Spearman correlations and linear models adjusted for age, sex, race/ethnicity, COPD status, smoking status, and pack-years. Results CRLF2 expression correlated with gene-expression evidence of both T2/eosinophilic and neutrophilic inflammation: T2 signature (ρ = 0.26, p < 0.001), eosinophil signature (ρ = 0.44, p < 0.001), and neutrophil signature (ρ = 0.39, p < 0.001). CRLF2 was positively associated with log sputum neutrophil count (ρ = 0.24, p = 0.024) and blood neutrophil count (ρ = 0.036, p < 0.001), but not with sputum or blood eosinophil counts. Higher CRLF2 related to worse baseline lung function, particularly among current smokers, (lower post-bronchodilator FEV1: ρ = −0.21, p = 0.008), as well as greater 5-year FEV1 decline across current and former smokers (ρ = −0.22, p = 0.007). Significant findings persisted after covariate adjustment. In contrast, TSLP expression, although strongly correlated with expression of the epithelial alarmin IL33 (ρ = 0.53, p < 0.001), was negatively correlated with CRLF2 (ρ = −0.24, p = 0.002) and with eosinophil and neutrophil gene-expression signatures (ρ = −0.26 and −0.33, both p < 0.001). TSLP expression showed no association with sputum or blood cell counts. Conclusions In bronchial epithelium from SPIROMICS, gene expression of CRLF2, but not of TSLP, tracked with downstream alarmin-relevant inflammatory programs, consistent with a regulatory role in TSLP signaling through TSLPR, as well as with clinically meaningful outcomes. CRLF2 expression was associated with evidence of both T2/eosinophilic and neutrophilic inflammation, and with lower baseline FEV1 and accelerated FEV1 decline, suggesting engagement of a broader, clinically relevant inflammatory milieu. By contrast, epithelial TSLP transcript levels mirrored IL33 gene expression but were not associated with cellular or transcriptomic inflammation. These findings position CRLF2, rather than TSLP expression itself, as a potential airway biomarker of TSLP-axis activity and disease impact with potential implications for patient stratification as well as strategic approaches for TSLP-pathway-targeted therapies. This abstract is funded by: SPIROMICS was supported by contracts from the NIH/NHLBI (HHSN268200900013C, HHSN268200900014C, HHSN268200900015C, HHSN268200900016C, HHSN268200900017C, HHSN268200900018C, HHSN268200900019C, HHSN268200900020C, 75N92024D00012), grants from the NIH/NHLBI (U01HL137880, U24HL141762, R01HL182622, R01HL144718, and R01HL093081), and supplemented by contributions made through the Foundation for the NIH and the COPD Foundation from Amgen; AstraZeneca/MedImmune; Bayer; Bellerophon Therapeutics; Boehringer-Ingelheim Pharmaceuticals, Inc.; Bristol Myers Squibb; Chiesi Farmaceutici S.p.A.; Forest Research Institute, Inc.; Genentech; GlaxoSmithKline; Grifols Therapeutics, Inc.; Ikaria, Inc.; MGC Diagnostics; Novartis Pharmaceuticals Corporation; Nycomed GmbH; Polarean; ProterixBio; Regeneron Pharmaceuticals, Inc.; Sanofi; Sunovion; Takeda Pharmaceutical Company; Theravance Biopharma; Verona; and Mylan/Viatris.

Abstract Rationale Chronic lower respiratory diseases (CLRD), including chronic obstructive pulmonary disease (COPD), were the third-leading causes of death globally in 2019. Quantitative computed tomography (CT) measures of airway wall and lumen areas are associated with greater respiratory symptoms, reduced FEV1, accelerated lung function decline, and higher risk of incident COPD. Even in individuals without COPD, greater airway wall thickness—corresponding to smaller absolute wall and lumen areas—predicts incident COPD and CLRD-related hospitalizations and mortality. Aims To identify protein signatures and biological pathways underlying airway lumen and wall areas using cross-sectional plasma protein associations with CT measures. Methods SPIROMICS is a multicenter longitudinal case-control study that recruited 2,983 adults with COPD and a 20+ packyear smoking history and controls aged 40-80 years between 2010-2015. Standardized chest CT scans were labeled with airway measures. A total of 1,255 plasma proteins measured by SomaScan were included. Linear regression models adjusted for demographic, clinical, and imaging covariates. Significance was defined by a False Discovery Rate (FDR) p-value (q-value) <0.05 using the Benjamini-Hochberg method. Replication was performed in two external cohorts with inverse variance-weighted meta-analysis. Proteins meeting nominal replication underwent elastic net regression and pathway enrichment (Gene Ontology [GO] and Reactome). Results Among 2,065 participants with CT and proteomic data (mean age 63.2 years, 46.3% women, 61.6% with COPD), proteins meeting replication were significantly associated with lumen area (2 proteins; top hit a disintegrin and metalloproteinase with thrombospondin motifs 5, q = 0.016), wall area (3 proteins; top hit leptin, q = 0.011), and percent wall area (16 proteins; top hit roundabout homolog 2, q = 0.002). Elastic net selected 2 proteins for lumen area, 3 for wall area, and 12 for percent wall area. Pathway enrichment revealed FDR-significant pathways only for percent wall area via GO (50 pathways; top hit axogenesis) and Reactome (1 pathway; diseases of glycosylation). Conclusions This study identified distinct proteins, signatures, and biological pathways associated with CT airway measures of lumen area, wall area, and percent wall area. Proteins linked to airway lumen and wall area are involved in metabolic and vasoactive processes, while those for percent wall area are involved in vascular remodeling, cell adhesion, and extracellular matrix organization—highlighting structural pathophysiologic features of COPD. These findings may inform biomarker discovery and prediction of disease onset and progression. This abstract is funded by: Funding: Daniel E. Guzman, MD, MSE was funded by T32-HL144442. SPIROMICS was supported by contracts from the NIH/NHLBI (HHSN268200900013C, HHSN268200900014C, HHSN268200900015C, HHSN268200900016C, HHSN268200900017C, HHSN268200900018C, HHSN268200900019C, HHSN268200900020C, 75N92024D00012), grants from the NIH/NHLBI (U01HL137880, U24HL141762, R01HL182622, R01HL144718, and R01HL093081), and supplemented by contributions made through the Foundation for the NIH and the COPD Foundation from Amgen; AstraZeneca/MedImmune; Bayer; Bellerophon Therapeutics; Boehringer-Ingelheim Pharmaceuticals, Inc.; Bristol Myers Squibb; Chiesi Farmaceutici S.p.A.; Forest Research Institute, Inc.; Genentech; GlaxoSmithKline; Grifols Therapeutics, Inc.; Ikaria, Inc.; MGC Diagnostics; Novartis Pharmaceuticals Corporation; Nycomed GmbH; Polarean; ProterixBio; Regeneron Pharmaceuticals, Inc.; Sanofi; Sunovion; Takeda Pharmaceutical Company; Theravance Biopharma; Verona; and Mylan/Viatris.

Abstract Rationale Sleep is an important dimension of COPD symptomology. Poor self-reported sleep quality has been independently associated with increased exacerbation risk and worse quality of life. There is limited evidence around the longitudinal sleep quality of patients with smoking-related lung disease. Methods Using the SPIROMICS longitudinal cohort of heavy smokers, we used group-based trajectory modeling to understand sleep quality over time as measured by serial retests of the Pittsburgh Sleep Quality Index (PSQI). We considered all participants of Black or Non-Hispanic White race who completed the PSQI in Visits 1-4, a span of 3 years. We considered race, gender, and social environmental exposures as time-stable risk factors for trajectory group membership. We adjusted for age, lung function, mood symptoms and self-reported COPD symptom severity were considered as time-varying factors. We selected the number of trajectory groups by minimizing Bayesian Information Criteria and polynomial order by maximizing the significance of exponential terms. For quality assurance we calculated average posterior probability of correct group assignment. Calculations were performed by complete case analysis and multiple imputation with chained equations. Results We analyzed 2,838 participants yielding 76,153 usable observations. Overall, 39.2% of participants had complete observations for all variables of interest at every measured visit, and 60.8% had at least one relevant observation missing. The largest single source of missingness in our dataset was the comorbidity count, for which 44% of participants had a missing observation. We identified two major trajectory groups. In one group, the PSQI was persistently high with little variation over time, containing 77.7% of the overall study population. The second group had low PSQI at baseline but experienced wide fluctuation over time. Risk factors for persistently poor sleep included female gender, Black race, and more adverse social conditions at either the neighborhood or individual level (Table). The average posterior probability of correct group assignment was 94.6% among the Low Variable group and 89.5% among the Persistent High group. Results were similar by complete case and imputed analysis, save that BMI did not independently predict group membership in the latter. Conclusion Historically underserved groups are at long term risk for poor sleep outcomes in smoking-related lung disease, even among those who are highly motivated and participate in clinical research. More work is needed to ensure equitable access to sleep medicine in order to improve the quality of care in COPD. This abstract is funded by: Nina Ireland Program for Lung Health