Woodruff, P G

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

Abstract Rationale Type-1 inflammation in asthma leads to significant airway level changes independent of Type-2 inflammation and may underlie the severity seen in combined Type1/2 high disease. As IFNs can cause airway epithelial injury and impaired repair, we applied a novel interpretable machine learning algorithm, SLIDE, to analyze the transcriptome of airway epithelial brushings of mild-moderate (MMA) and severe asthma (SA) participants in the Immune Mechanisms in Severe Asthma (IMSA) cohort to identify latent/hidden factors of disease that associate with disease severity. Methods The expression of genes identified by SLIDE as part of a co-expression program was assessed in the full IMSA cohort by severity and in an independent cohort of the NHLBI Severe Asthma Research Program (SARP). We also examined associations of these genes with clinical asthma outcomes in both cohorts. Results SLIDE identified aberrant increased expression of membrane-tethered mucin genes, MUC1 and MUC4. MUC1 appeared in each of 5 significant latent factors associated with greater severity and MUC4 in 2/5. Standard DGE analysis also identified the gene CEACAM5 as a predictor of severity. Pathway analysis of latent factor genes revealed airway keratinization which may contribute to airway remodeling and worsening obstruction over time. Expression of MUC1, MUC4, and CEACAM5 were increased in SA compared to HC in both the full IMSA and separate SARP cohorts (p < 0.001 for all genes in both cohorts). Expression in MMA was consistently lower than in SA in both cohorts, reaching significance in IMSA (p < 0.01) but not consistently in SARP (MUC1 p = 0.04, MUC4 p = 0.27, CEACAM5 p = 0.27). Protein analysis of endobronchial biopsies by immunofluorescence staining showed a trend towards increased MUC1 protein content with evidence of secretion. MUC1, MUC4 and CEACAM5 were negatively correlated with FEV1 % predicted in both cohorts (IMSA: MUC1 r=-0.47, p < 0.01, MUC4 r=-0.47, p < 0.01, CEACAM5 r=-0.62, p < 0.01; SARP: MUC1 r=-0.19, p = 0.05, MUC4 r=-0.29, p < 0.01, CEACAM5 r=-0.51, p < 0.01). All three genes positively correlated with prospective exacerbations in both cohorts (IMSA: MUC1 r = 0.345, p = 0.01, MUC4 r = 0.216, p = 0.08, CEACAM5 r = 0.368, p < 0.01; SARP: MUC1 r = 0.22, p = 0.02, MUC4 r = 0.32, p < 0.01, CEACAM5 r = 0.38, p < 0.01). Conclusions The expression of MUC1, MUC4 and CEACAM5 increased with asthma severity in the airway epithelium and correlated with both prospective exacerbations and obstruction. As pathway analysis of genes in the significant latent factors were associated with airway keratinization aberrant expression of these mucins (with known signaling functions) may contribute to maladaptive repair and airway remodeling that drives obstruction over time, contributing to worse asthma outcomes. This abstract is funded by: NIH

Abstract Rationale The activity of fucosyltransferase 2 (FUT2) determines if mucin glycan structures in epithelial mucus include histo-blood group antigens (HBGAs). People with active FUT2 express HBGAs in epithelial mucus secretions and are terms “secretors”, while non-secretors lack HBGAs in their secretions because they have a FUT2 genotype that inactivates the glycosyl transferase. Prior research suggests that secretors who are blood type O (type O secretors) are susceptible to asthma exacerbations1 and that FUT2 knockout mice (functional non-secretors) are protected from mucus plugging in allergen challenge models2,3. We set out here to determine if secretor status influences mucus plug prevalence in asthma and to confirm if type O secretors are susceptible to asthma exacerbations. Methods We determined secretor status in asthma participants from the Severe Asthma Research Program-3 (SARP-3) cohort (N = 507) in two ways, a specific fucose lectin binding assay in sputum and FUT2 genotyping. Blood group type was determined using ABO genotyping. We analyzed mucus plug segment scores, asthma exacerbations rates and other clinical and biological features in patients stratified by secretor status and blood type (non-secretors, type O secretors, and non-type O secretors). Results Secretor status determined by lectin binding in sputum was strongly concordant with genotypic analysis. Within the SARP-3 cohort, 26.2% were non-secretors, 32.3% type were O secretors, and 41.4% were non-type O secretors. Mucus plug segment scores, annualized asthma exacerbation rates, and other measures of asthma severity were similar in non-secretors, type O secretors, and non-type O secretors (Table). Although type O secretors had increased values for fractional exhaled nitric oxide (FeNO) and higher expression of type 2 gene network genes in their sputum cells, measures of sputum eosinophil inflammation were not higher in this subgroup (Table). Conclusion Secretor status does not influence the prevalence of mucus plugging in asthma patients, and we did not confirm a prior report that type O secretors have an increased risk of asthma exacerbation. Although type O secretors have modestly increased FeNO levels and increased expression of type 2 immune genes in their sputum, it is not clear if this is a biologically important signal. 1. Innes et al. AJRCCM; 2011. 2. Saku et al. JACI; 2019. 3. Hara et al. AJRCMB; 2025 This abstract is funded by: The study was supported by the National Institutes of Health grants R01 HL080414 (JVF), P01 HL107202 (JVF), R01 HL164787 (JVF), U10 HL109172 (EI), U10 HL109152 (SEW), U10 HL109257 (MC), U10 HL109250 (SCE), U10 HL109146 (JVF), U10 HL109164 (ERB), U01 HL146002 (BDL), U10 HL109086 (DTM) and Sandler Asthma Basic Research Center at UCSF (JVF). The following companies provided financial support for study activities at the Coordinating and Clinical Centers beyond the third year of patient follow-up: AstraZeneca, Boehringer-Ingelheim, Genentech, GlaxoSmithKline, Sanofi–Genzyme Regeneron, and Teva. These companies had no role in study design or data analysis, and the only restriction on the funds was that they be used to support the SARP initiative.

Abstract Rationale We hypothesize that corticosteroid resistance causes uncontrolled inflammation and severe asthma. The genetic and molecular mechanisms underlying steroid responsiveness in asthma remain poorly understood (PMID28493293). This study aims to characterize transcriptomic profiles distinguishing steroid responders from steroid resistant asthma. Methods Longitudinal bulk RNA-seq of SARP3 sputum samples was analyzed before and after an “induced phenotype” with 40 mg triamcinolone acetonide (TCA) injection (PMID 27967215). Participants were classified as responders or non-responders based on whether their FEV₁ change after TCA exceeded the median. Paired differential gene expression analyses were performed separately for each group using limma and voom, with participant as a factor and adjustment for sputum cell count differentials. Z-scores were calculated to compare gene expression changes after TCA injection between responders and non-responders, and pathway enrichment was assessed using the fgsea package. Results Baseline demographics and clinical characteristics of 696 SARP3 asthma participants receiving TCA are shown in Table 1. The median [IQR] FEV1 change post-TCA was 1.81% [-2.16, 7.17]. Responders had higher baseline FEV1%, FEV1/FVC ratio, blood eosinophil counts, and sputum eosinophil percentages, but lower serum CRP levels. Steroid responsiveness was associated with asthma severity (Table 1). Among 154 participants with paired sputum RNA-seq data, 70 (45%) exhibited >1.81% improvement in FEV₁ and were classified as responders. Following TCA treatment, non-responders showed no significant changes in gene expression. In responders, 18 genes were upregulated and 203 downregulated. Downregulated genes were associated with Th2 immunity (IL13, IL1RL1, CCL17, SIGLEC8), IgE signaling (FCER1A, FCER2), epithelial barrier function and mucus production (MUC2, MUC7, ALOX15, TFF3), tissue remodeling and fibrosis (MMP10, TIMP3), ciliary function (DNAH5, CFAP43, FOXJ1), and airway hyperreactivity (HRH4, RAMP1). Key genes notably downregulated in responders compared to non-responders included IL13, CCL5, PTGDR2, FCER2, and CLEC10A. Pathway analysis revealed enhanced IL-10-mediated anti-inflammatory signaling, suppression of pro-inflammatory pathways (NF-κB, IL-1, Th1/Th2, asthma, arachidonic acid metabolism, chemokine, NOTCH4), and regulation of mitochondrial oxidative phosphorylation. Conclusions Steroid resistance impairs glucocorticoid-mediated suppression of pro-inflammatory pathways, including NF-κB, IL-1, and Th1/Th2 signaling. This persistent airway inflammation limits improvements in lung function and contributes to worse clinical outcomes, including increased airflow obstruction, and symptom burden. Glucocorticoid resistance in asthma may be driven by receptor dysfunction, airway inflammation, epigenetic changes, and environmental exposures resulting in persistent airway inflammation and remodeling. Elucidating the molecular mechanisms underlying steroid resistance is critical for developing personalized targeted therapies in asthma. This abstract is funded by: NIH-NHLBI - R01 HL161674 (PI: Joe Zein)

Abstract Rationale Asthma contributes substantially to healthcare burden and morbidity through frequent exacerbations. Emerging evidence suggests that genetic factors play a crucial role in modulating susceptibility to asthma exacerbations. To better understand the genetic architecture of exacerbations, we conducted a genome-wide association study (GWAS) in the Tapestry cohort. Methods The Tapestry Study, a large-scale, decentralized and clinical grade genomic sequencing study, conducted Exome+® sequencing at Helix, Inc. on 98,075 Mayo Clinic participants. After excluding patients with ≥10 pack-years of smoking and/or emphysema, we performed a GWAS of asthma exacerbations in 3,960 adults with asthma based on ICD codes. Cases (n = 1,059) were defined as individuals who experienced at least two exacerbations between 2020 and 2025; the remaining 2,901 individuals served as controls. Asthma exacerbations were defined by oral or systemic corticosteroid prescriptions with durations ranging from 3 days up to 28 days. Logistic regression models adjusted for age, sex, BMI, and the first six principal components of ancestry. Replication was performed in 1,273 asthma patients (439 African Americans and 834 non-Hispanic Whites) from the NHLBI-sponsored Severe Asthma Research Program (SARP 1-3), with adjustments for age, sex, BMI, and the first 10 principal components of ancestry. Results Based on a minor allele frequency (MAF) threshold of > 0.05, we analyzed 5,256,135 genome-wide variants. Genome-wide significant associations for asthma exacerbations (p < 5.0 × 10⁻8) included loci at a pseudogene in SMPD4P1 (rs680548, MAF = 0.39, OR = 1.37, p = 9.10 × 10⁻9). Additional variants showing suggestive associations included loci within ENDOD1 (rs638776, OR = 0.69, p = 1.20 × 10⁻6), PCSK2 (rs2206454, OR = 1.32, p = 3.53 × 10⁻6), RBFOX1 (rs17667084, OR = 0.60, p = 5.11 × 10⁻6), and CDC42EP3 (rs721660, OR = 1.29, p = 5.68 × 10⁻6). Subthreshold associations in Tapestry including loci at CDC42EP3 (rs4670213, OR = 1.27, p = 1.41x10-5, MAF = 0.36), and SDR39U1 (rs12587663,OR = 0.83, p = 5.86x10-4, MAF = 0.46) were replicated in the SARP longitudinal visit 5 with p-values of 8.523x10-3 (rs4670213, OR = 1.78), and 2.88x10-4 (rs12587663,OR=0.43), respectively. Conclusion Our GWAS for asthma exacerbations in the Tapestry cohort identified variant loci relevant to mitophagy mechanisms (CDC42EP3, PMID: 40783597), immune signaling and RNA splicing regulation (RBFOX1, PMID: 31301374), and neuromodulatory pathways (PCSK2, PMID: 32794589), all previously implicated in asthma pathophysiology. Collectively, these findings highlight potential novel genetic contributors to asthma exacerbations and provide a foundation for improving risk stratification and therapeutic targeting in asthma management. This abstract is funded by: This abstract is funded by: Mayo Clinic Funding: X01 from the NHLBI for TOPMed whole-genome sequencing and NIH grants R01 HL142992, HL69116, HL69167, HL69170, HL69174, U10 HL109164, U10 HL109257, U10 HL109146, U10 HL109172, U10 HL109250, U10 HL109250, U10 HL109250, U10 HL109168, U10 HL109152, U10 HL109086, U10 HL109046.