Ortega, V E

Abstract Rationale Idiopathic Pulmonary Fibrosis (IPF) is characterized by chronic progressive pulmonary fibrosis and high mortality. Genetic markers, summarized into a polygenic risk score (PRS), associate with IPF in well-phenotyped research cohorts. Objectives To evaluate the performance of the PRS using real-world data from routinely captured electronic healthcare records. Methods We conducted an observational study evaluating the association of a PRS for IPF with electronic healthcare record diagnosis of IPF as well as lung transplant-free survival in four independent cohorts; the Mass General Brigham Biobank (MGBB), Mayo Clinic Biobank (MCBB), Mayo Clinic Tapestry Cohort (Tapestry), and U.K. Biobank (UKBB). We used multivariable logistic regression and multivariable Cox proportional hazards models adjusting for age, gender, and principal components of ancestry. The cohorts then underwent fixed and random effects meta-analysis. Measurements and Main Results Of 37,709; 44,195; 43,202; and 447,422 participants from MGBB, MCBB, Tapestry and UKBB respectively, 1,015 (2.7%) 2,879 (6.5%), 1,310 (3.0%), and 2,742 (0.6%) participants had an IPF diagnosis. Meta-analysis demonstrated a high-risk PRS associated with IPF diagnosis, OR 2.88 (95%CI 2.41-3.44) compared to all other individuals. A high-risk PRS also associated with the composite endpoint of mortality or lung transplant among those with an IPF diagnosis, HR 1.23(95%CI 1.11-1.35) compared to all other individuals. Conclusions A PRS can identify those at risk for an IPF diagnosis and mortality in biobank-scale data, which may have implications for clinical decisions. Further work is necessary to evaluate the utility of adding genetics in clinical settings.

Abstract Background Telomere maintenance and surfactant-related genetic mutations are increasingly recognized as contributing factors in familial pulmonary fibrosis (PF). Pathogenic variants in the SFTPA2 gene have been associated with early-onset pulmonary fibrosis and an elevated risk of developing lung cancer. Currently, PF lacks a definitive cure beyond lung transplantation, and treatment options remain limited. Understanding the prevalence and clinical implications of pathogenic SFTPA2 variants is critical. This study aims to assess the prevalence of PF, lung cancer, and other co-morbidities among individuals carrying pathogenic SFTPA2 variants. Ultimately, this study seeks a comprehensive understanding of the natural history and potential screening needs for SFTPA2 variants. Methods Individuals with pathogenic SFTPA2 variants were identified in the Tapestry genomic database at our academic medical center. Electronic medical records (EMR) were reviewed for personal or family histories of PF, lung cancer, and other significant comorbidities. Imaging reports were evaluated for radiographic evidence of PF or lung cancer. Studies were approved by the local IRB. Results Out of 98,109 participants in the Tapestry database, 18 individuals were identified as carriers of SFTPA2 variants. The variants (NM_001098668.4) included c.460G>C - p.(Ala154Pro) in 13 individuals, c.557A>G - p.(Tyr186Cys) in 1 individual, and c.532G>A - p.(Val178Met) in 4 individuals. The mean age was 60.5 years, and 67% were female. No participants had a formal diagnosis of PF; however, five (28%) had prior chest CTs showing ground-glass opacities, fibrosis, or irregular nodularity. EMR review did not confirm clinically significant PF. Notably, 44% reported a family history of primary lung cancer, though no familial PF was documented. Comorbidities included inflammatory bowel disease (22%, with a tapestry cohort prevalence of 9%) and a personal history of cancer in 44%, encompassing nine distinct malignancies such as metastatic colon adenocarcinoma (1), prostate cancer (1), basal cell carcinoma of the skin (1), endometrial cancer (1), breast cancer (2), melanoma (1), and squamous cell carcinoma of the skin (1). Conclusions In this cohort of individuals with SFTPA2 variants, no cases of clinically confirmed PF or lung cancer were identified. However, there was a notable prevalence of abnormal parenchymal chest CT findings, inflammatory bowel disease, personal cancer history, and family history of lung cancer. These findings underscore the variable penetrance of SFTPA2 variants and highlight the need for longitudinal studies to elucidate the genetic, environmental, and immunologic factors that modulate disease expression. Improved understanding may inform screening strategies and therapeutic interventions for at-risk individuals. This abstract is funded by: None

Abstract Rationale Interstitial lung abnormalities (ILA) are abnormal findings on chest CT scans that may represent early-stages of interstitial lung disease. The presence of fibrosis (traction bronchiectasis and/or honeycombing) identifies those with ILA at an increased risk for mortality, however, determining who will progress remains a challenge, and the role of blood-based biomarkers in ILA risk-stratification is unknown. Methods Data from four prospective cohort studies were used to identify associations between plasma proteins measured with DNA aptamers (SomaScan) and ILA, fibrosis, and mortality. The Genetic Epidemiology of COPD Study (COPDGene) was used to identify protein associations, and findings were replicated by meta-analysis of the Age, Gene/Environment Susceptibility-Reykjavik study (AGES-Reykjavik), SubPopulations and InteRmediate Outcome Measures in COPD Study (SPIROMICS), and Framingham Heart Study (FHS). Protein associations with ILA and with fibrotic ILA compared to non-fibrotic ILA were performed using multivariable logistic regression; among those with ILA, Cox proportional hazards models were used to identify protein associations with mortality. Models were adjusted for age, gender, race, BMI, smoking status, pack-year smoking history, and for mortality, COPD. Benjamini-Hochberg false discovery rate p-values <0.05 were considered significant. Results 524 (10.7%) of 4,899 COPDGene participants had ILA, of whom 57 (10.9%) had fibrosis; of 8,146 AGES-Reykjavik, SPIROMICS and FHS participants included in the meta-analysis, 666 (8.2%) had ILA, of whom 198 (29.7%) had fibrosis. In COPDGene, 230 proteins were associated with ILA; the most significant of which were SFTPD (adjusted odds ratio per standard deviation [SD] of protein [OR]=2.21, p = 3.7E-41) and SFTPB (OR = 1.82, p = 7.9E-37). In the meta-analysis, 159 of the ILA-associated proteins were replicated. Of the 230 ILA-associated proteins in COPDGene, 9 were associated with fibrosis, and 5 of these 9 proteins were associated with mortality among those with ILA. The 5 proteins associated with all three outcomes were WFDC2 (ORILA=1.90, p = 2.6E-34; ORFibrosis=2.00, p = 0.0001; adjusted hazards of mortality per SD of protein [HR]=1.59, p = 3.4E-05), GDF15 (ORILA=1.67, p = 3.6E-23; ORFibrosis=1.78, p = 0.0006; HR = 1.63, p = 1.4E-06), SCGB3A1 (ORILA=1.52, p = 4.5e-14; ORFibrosis=1.80, p = 0.0002; HR = 1.25, p = 0.02), TREM1 (ORILA=1.44, p = 1.4e-14; ORFibrosis=1.62, p = 0.001; HR = 1.25, p = 0.02) ICAM5 (ORILA=1.42, p = 1.2e-11; ORFibrosis=1.79, p = 0.0001; HR = 1.31, p = 0.002). In the meta-analysis, 6 of the 9 fibrosis-associated proteins and all 5 ILA mortality-associated proteins replicated. Conclusion This represents the first plasma proteomic screen demonstrating reproducible biomarker associations not only with ILA presence, but also with measures of severity and adverse outcomes. These results provide compelling targets for further study, including their prospective evaluation as clinical biomarkers for early disease identification and prognostication. This abstract is funded by: Multiple Sources

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 Deficiency of alpha-1 antitrypsin (AAT), the protein encoded by SERPINA1, remains the strongest genetic risk factor for COPD. Individuals heterozygote for the type Z variant, termed the PI*MZ genotype (estimated global prevalence n = 35,000,000), experience varying respiratory morbidity beyond expected from tobacco smoking alone. AAT is a pleiotropic protein which inhibits not only neutrophil elastase but also neutrophil chemotaxis mediated by leukotriene B4 (LTB4) [by antagonizing the LTB4 receptor (LTB4R)] and interleukin-8 (IL-8). Although LTB-4 and IL-8 gene variants and protein levels have independently been implicated in COPD, their potential role in PI*MZ is unknown. Methods COPDGene and SPIROMICS are observational tobacco-smoke and COPD-enriched cohort studies. Participants were phenotyped by spirometry and CT imaging, with whole genome sequencing data available via TOPMed. We analyzed participants with PI*MM (COPDGene n = 9,732; SPIROMICS n = 2,105) and PI*MZ (COPDGene n = 300; SPIROMICS n = 83). LTB-4 (ALOX5AP, LTA4H, LTB4R) and IL-8 (CXCL8, CXCR1, CXCR2) associated gene variants (exonic and intronic) with a minor allele frequency of ≥ 0.05 were extracted. We assessed statistical interactions between MZ status and chest CT outcomes or FEV1% predicted using the SPAGxECCT package with adjustment for relatedness (genetic related matrix) and ancestry (top ten PCs). Baseline protein LTB4R (SPIROMICS only) and IL-8 (both cohorts) protein levels were measured via SomaScan, and statistical interactions between MZ status and AAT concentration were explored. Models were adjusted for age, sex, BMI, smoking status, and pack-years. Given the candidate gene discovery approach, significance was defined as nominal p-value<0.05 Results We identified the following number of variants in genes of the LTB-4 or IL-8 pathways: 87 shared between cohorts; 133 unique to COPDGene; 1 unique to SPIROMICS. LTB-4-related polymorphisms were associated (p < 0.05) with any radiographic outcomes in 22 variants (COPDGene) vs. 23 variants (SPIROMICS), with a single overlap (rs17074984 in ALOX5AP). Two LTB-4-pathway variants were associated with FEV1% predicted in SPIROMICS (both in ALOX5AP), but none in COPDGene. AAT plasma concentrations displayed a statistically significant interaction with FEV1% predicted (p = 0.046) and PRMemphysema (p = 0.013) for LTBR4, but not for IL-8. There was not an interaction by MM/MZ status and protein levels. Conclusions Predominantly LTB-4, and not IL-8, pathway-related genetic variants and protein levels may contribute to disease heterogeneity among PI*MZ individuals. The association of circulating LTB4R protein with reduced lung function, particularly among those with low AAT levels, further suggest interactions between AAT and the leukotriene pathway in PI*MZ individuals. Thus, PI*MZ individuals may uniquely derive benefit from leukotriene-targeting pharmacotherapy. This abstract is funded by: NIH NHLBI K23HL173570

Abstract Rationale Alpha-1 antitrypsin deficiency (AATD) continues to be underdiagnosed. The estimated prevalence of the most common severe deficient genotype, PI*ZZ, is ∼1:3500 or 100,000 Americans but only ∼10,000 such individuals have been recognized. Diagnostic delays persist and these delays are associated with worse disease. High-resolution CT (HRCT) imaging may contain latent phenotypic AATD signatures that are not visibly apparent to clinicians. We hypothesized a deep learning model could identify imaging patterns predictive of AATD from inspiratory HRCT scans. Methods Confirmed genotypes and HRCT scans were pooled from COPDGene, SPIROMICS, and GRADS, yielding 350 MM, 102 MZ, and 69 ZZ participants. Only scans reconstructed with smooth kernels (GE STANDARD, Philips B, Siemens B31f/B35f) and slice thickness < =1.25mm were used. The cohort was selected to have similar distributions of quantitative emphysema, sex, and age by matching five MZ and two MM subjects to each ZZ subject (<10-year age difference, same sex, and <3% difference in %LAA). Tobacco smoke-exposure was more prevalent among the MM/MZ groups given these were predominantly from the tobacco smoke-enriched COPDGene and SPIROMICS cohorts. A DenseNet121 convolutional neural network (CNN) was trained using the MONAI platform to predict genotype by outputting probabilities for MM, MZ, and ZZ. Input to the CNN was a three-channel LAA-910, LAA-950, and LAA-970 map downsampled to 2.0mm3 resolution to remove bias due to differences in scanner and image reconstruction parameters. Five-fold cross-validation was performed. Area under the curve (AUC) was calculated for classification of ZZ vs other genotypes (MM/MZ) and MZ vs MM, with statistical significance assessed at p < 0.05. Results The three groups were similar across age (mean±SD years: MM 57.9±8.8, MZ: 57.5±8.9, ZZ: 55.0±10.7), sex (% female: MM: 48.2%, MZ: 46.7%, ZZ: 47.6), and emphysema (LAA-950%: MM: 13.0±12.2, MZ: 12.4±11.8, ZZ: 13.1±11.9). There was a higher prevalence of ever smokers among MM (100%) and MZ (91.7%), compared to ZZ (47.6%). The model achieved an AUC of 0.806 (p < 0.001) for classification of ZZ vs other genotypes, demonstrating robust discriminatory ability for homozygous AATD. Classification of MZ vs other genotypes did not achieve an AUC significantly greater than 0.5. Conclusions This proof-of-concept study demonstrates that deep learning applied to routine inspiratory HRCT can accurately identify homozygous AATD. These findings support the potential role of imaging-based machine learning as a non-invasive screening tool for undiagnosed ZZ individuals. Future work will focus on cohort enrichment, integration with clinical parameters, and explainability of model-derived imaging features. This abstract is funded by: NIH NHLBI K23HL173570

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 Alpha-1 antitrypsin (AAT) deficiency, primarily caused by homozygous SERPINA1 Z mutation, increases the risk of COPD. Individuals carrying one Z and one normal M allele (MZ) have higher COPD risk than MM individuals, although many never develop disease. COPD is a polygenic condition influenced by numerous genetic factors across the genome and by environmental exposures such as smoking. We aimed to examine how polygenic factors and smoking modify risk of airflow obstruction in MZ compared with MM. Methods We included participants with the MZ and MM genotypes from the Framingham Heart Study. We first tested the association between AAT genotype (MZ coded as 1 and MM as 0) and FEV1/FVC, stratified by ever-smoking status, and further evaluated interactions between AAT genotype and smoking pack-years. Next, for each participant we calculated a polygenic risk score (PRS) for FEV1/FVC, which was derived from external genome-wide association studies in the UK Biobank and SpiroMeta Consortium. To reflect risk for airflow limitation, higher PRSs correspond to lower FEV1/FVC. We then tested the interaction between the PRS and AAT genotype, stratified by ever-smoking. Models were adjusted for age, sex, height, current smoking, pack-years (among ever-smokers), familial relatedness, and in PRS models, principal components of genetic ancestry. Results Among 4,220 participants (mean age 53.7 years, 54.2% female, 50.2% ever-smokers, mean FEV1/FVC 74.6%), 133 (3.2%) had MZ genotype. In never-smokers, MZ individuals had 1.72% higher FEV1/FVC compared with MM (P = 0.032), whereas no difference was observed among ever-smokers (β= -0.39%; P = 0.65). Cumulative smoking modified the effect of MZ genotype on FEV1/FVC (interaction β= -0.13% per pack-year; P = 0.003); this interaction persisted among ever-smokers (β= -0.11% per pack-year; P = 0.044). A one-standard-deviation increase in the FEV1/FVC PRS was associated with lower FEV1/FVC in both never- (β= -2.37%; P < 0.0001) and ever-smokers (β= -2.46%; P < 0.0001). A higher PRS was disproportionately associated with reduced FEV1/FVC in MZ compared to MM (interaction β= -1.87% per standard-deviation PRS increase, P = 0.027) among ever-smokers, but not in never-smokers (P = 0.15). Conclusions In this community-based cohort, the AAT MZ genotype was associated with higher FEV1/FVC among non-smokers compared to MM. The interaction between MZ genotype and pack-years suggested a dose-dependent modifying effect of smoking on the MZ-related COPD risk. Among ever-smokers, higher polygenic risk further amplified susceptibility to airflow obstruction in MZ compared with MM. These findings highlight the roles of both polygenic and environmental risk factors in COPD susceptibility in MZ. Replication of the results is needed. This abstract is funded by: This work is supported by an Alpha-1 Foundation Grant and a Boston University Department of Medicine Career Investment Award