Fahy, John V.

Abstract Background Prostaglandin E2 (PGE2) exerts paradoxical effects in asthma, acting as both a protective mediator and a contributor to pathology depending on context. Its role is shaped by type 2 (T2)-status, eosinophilia, and exacerbation frequency. In epithelial cell cultures from asthmatic and healthy individuals, interleukin (IL)-13 suppresses PGE2 synthesis genes (PTGS2 and PGES) while upregulating HPGD, which encodes for the PGE2 catabolic enzyme 15-prostaglandin dehydrogenase (15-PGDH) (PMID:16751012), suggesting diminished PGE2 availability during T2 inflammation. Similarly, in aspirin-exacerbated respiratory disease (AERD), impaired cyclooxygenase disrupts PGE2 biosynthesis, fueling unchecked leukotriene production and eosinophilic inflammation (PMID: 30516547), underscoring PGE2’s protective role in limiting disease progression. Conversely, in nasal polyps, tuft cells are activated by IL-13 to produce PGE2 (PMID: 35608904), highlighting PGE2’s potential pathogenicity. Objective To assess associations between PGE2-pathway gene expression in bronchial brushings and asthma severity, and to determine how nasal polyp history modifies these relationships. Methods We analyzed bronchial epithelial brushings from 109 adults with asthma (mean age 42.4±12.1, 64% female, 52% severe asthma, 18% nasal polyps) using normalized and batch-corrected RNA-seq data from the baseline visit in the Severe Asthma Research Program (SARP)3 (PMID: 36796454). Age-adjusted and nasal polyp-adjusted relationships were calculated between ratios of PGE2 synthesis and metabolism genes and clinical outcomes (ASSESS score, FEV1 %predicted). The composite PGE2 score (PMID: 35608904), derived from nasal polyp analysis, was calculated from the average scaled log-normalized expression of six PGE2-responsive genes. All data were analyzed using a linear regression mixed model with a random effect for site. Results Ratios of PGE2 synthesis genes (PTGS1/2, PTGES2) to HPGD were significantly associated with greater disease severity (change in ASSESS Score) (Fig.1A, solid lines) and lower lung function (change in FEV1 %predicted) (Fig.1B, solid lines). These relationships persisted after adjusting for nasal polyps (Fig.1, dashed lines). The composite PGE2 score was also related to disease severity (Fig.1A, black solid line) but attenuated when nasal polyps were accounted for (Fig.1A, black dashed lines). Interestingly, lower lung function remained associated with the PGE2 score even after nasal polyp adjustment (Fig.1B, dashed black lines). Conclusions Our analysis demonstrates that the balance between PGE2 synthesis and degradation in the bronchial epithelium is closely linked to asthma severity and lung function, independent of nasal polyp status. Future work will integrate transcriptomic and clinical data longitudinally to establish whether PGE2 could serve as a biomarker for asthma trajectory. This abstract is funded by: HL115118 (LCD), U10HL109152 (S.E.W.), U10HL109172 (to E.I. and B.D.L), U10HL109168 (N.N.J.), U10HL109250 (S.C.E), U10HL109164 (W.C.M), U10HL109257 (M.C), and U10HL109146 (to P.G.W. and S.A.C.)

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.

Abstract RATIONALE. Significant sex-differences exist in asthma across the lifespan. Asthma prevalence and severity are greater in pre-pubescent boys compared to girls but greater in women after puberty. In women, asthma may improve after menopause when sex hormones wane. To address potential mechanisms underlying these changes, we compared the airway transcriptomics signatures of post-menopausal vs. premenopausal women. METHODS. We used bulk RNA seq data from bronchial epithelial cells from three different cohorts (SARP III, GEO-GSE85567, GEO-GSE201955) to perform a comprehensive analysis of differential gene expression and regulation. Data were combined into a meta-analysis, to compare pre-menopausal (n=114 cases with asthma, 48 controls) to post-menopausal women (n=52 cases with asthma, 13 controls). Differential gene expression between pre- and postmenopausal women was analyzed separately for asthma (Figure 1A) and control groups (not shown). Significant differentially expressed genes (DEGs) were identified by contrasting effect sizes (log fold-changes) between asthma and control groups using a Z-score interaction test. Accordingly, a scatter plot (Figure 1B) was created to represent whether differential gene expression between pre- and post-menopausal conditions is modified by disease status (asthma vs. control). The scatter plot also highlights that these findings are related to asthma per. se. and not to normal aging and menopausal transition. Pathway enrichment analysis was conducted using the differential expression data, followed by differential regulation analysis of the identified pathways. Statistical significance was assessed using a false discovery rate (FDR) threshold of 5%. RESULTS. Out of 15,468 genes that passed quality control, 19 genes were differentially expressed in bronchial epithelial cells from pre- and post-menopausal women with asthma (as compared to controls) (Figure 1A). Of these, 5 genes were down-regulated (ITLN1, POSTN, FCRL3, CCL22, PCSK6), and 14 genes were up-regulated (SPP1, S100A9, A2ML1, TNFRSF10C, CSF3R, OLFM1, C1QL2, NLRP3, HAL, PI3, RNASE1, TMEM178B, TNNI3, RNF175) when comparing pre- and post-menopausal women with asthma (Figure 1A). Of these 19 DEGs, 14 were differentially expressed in pre- as compared to post-menopausal women with asthma, but not in controls (Figure 1B). Comparing pre- to post-menopausal women with asthma, biologic pathways related to the innate and adaptive immune system activation and mitochondrial function (Electron transport Chain oxidative phosphorylation and ATP production) were both differentially regulated and expressed. CONCLUSIONS. This analysis highlights several DEGs and pathways that characterize asthma pathogenesis when comparing pre- and post-menopausal women, and emphasize the role of female sex hormones on the immune system response and mitochondrial function in asthma pathogenesis.

Abstract Introduction: The airway inflammation of asthma is characterized by immune phenotypes, often classified as Type 2 inflammation high or low. Social determinants of health (SDoH) can influence asthma risk and severity, but whether or not SDoH influence immune phenotypes is unclear. The social deprivation index (SDI) is a composite measure of seven neighborhood level characteristics: poverty level, less than 12 years of education, single parent household, living in rented housing unit, living in overcrowded housing unit, households without a car, and non-employed adults under 65 years of age. The scale of SDI ranges from 1 to 100, correlating with increasing deprivation. We hypothesized that social deprivation influences immune phenotype of asthma, and that deprivation effects vary by sex and race. Methods: Using the American Community Survey summary file spanning 2015 to 2019, we linked SDI to participant zip codes for 680 Black and White participants in the Severe Asthma Research Program (SARP), a NHLBI-multicenter network phenotyping asthma across the US from 2001-2024 (table 1). We compared SDI among the cohort by sex, race and asthma severity, and correlated SDI to superoxide dismutase (SOD) and T2-high biomarkers, such as eosinophils, IgE and Fraction of Exhaled Nitric Oxide (FENO). Results: SDI is similar across healthy and asthmatic participants (SDI: median [interquartile range]: healthy: 40 [56]; asthmatics: 51 [53], P = 0.53). When evaluated by race, SDI is significantly higher in Black asthmatics, independent of sex (SDI: Black male: 76 [4], White male: 35 [45]; P<0.0001; Black females: 77 [35], White females: 40 [45]; P<0.00010). Within SARP asthmatics, SDI shows a positive association with the T2 inflammatory markers, log IgE (R=0.13 [90%CI: 0.1, 0.2)] and log FENO (R=0.15 [90%CI: 0.1, 0.2]), while it correlates negatively with log of absolute neutrophil count (R= -0.12 [90%CI: -0.19,-0.1]). The antioxidant enzyme SOD increases with SDI (R=0.11, [90% CI: 0.04, 0.17]). Notably, within Black asthmatic males only, SDI is associated with Type 2 biomarkers, showing a positive correlation with log FENO (R=0.24 [90%CI: 0.1,0.4]) and negative correlation with log IgE levels (R= -0.25, [90% CI: -0.4, -0.1]). No association was found between SDI and eosinophils or with SOD in Black males. Conclusions: Neighborhood level social deprivation is associated with a unique asthma phenotype in Black males. Black males living at high social deprivation have a lower IgE and higher FENO, with no change in SOD activity.

Abstract Rationale: The club cell secretory protein (CC16), encoded by the SCGB1A1 gene, has an anti-inflammatory role in airways diseases, including asthma (Li, AJRCCM 2023; Voraphani, AJRCCM 2023). We hypothesize that additional pathway genes regulated or co-expressed with CC16 have cumulative effects on asthma severity outcomes by modulating airway inflammation and maintaining lung homeostasis. Methods: As published previously, four genes were downregulated in CC16 knockout experiments and correlated with CC16 levels: BPIFA1, SFTPD, LTF, and LYZ (Iannuzo, Front. Immunol 2023). We developed a four-gene biomarker score in 94 patients with asthma from the NHLBI-sponsored Severe Asthma Research Program (SARP3) who underwent research bronchoscopy for lower airway epithelial brushings, RNA isolation, and bulk RNA sequencing. We log-transformed the raw values of each transcript; obtained standardized residuals from regression models that included sex, age, and batch effects; and summed the standardized residuals of all four proteins to estimate a standardized sum score (Zhai, JACI Allergy 2024). Logistic regression models tested the four-gene score, three-gene score without LTF, and individual transcripts for associations with exacerbations during 12-month follow-up and zero-inflated negative binomial regression for number of exacerbations. Results: 30.85% percent of 94 patients experienced at least one exacerbation at the end of follow-up. The CC16-associated four-gene biomarker score showed protective effects on asthma exacerbation risk with a 54% percent reduction in exacerbation risk for every one-fold higher score (OR=0.46, 95% CI: 0.27-0.78, p =0.0040, Figure 1). Transcript expression of BPIFA1 (OR=0.87, 95% CI:0.66-1.16, p=0.337), SFTPD (OR=0.33, 95% CI:0.04-2.52, p=0.283), LYZ (OR=0.62, 95%CI:0.28-1.39, p=0.248), and LTF (OR=0.36, 95% CI:0.18-0.74, p=0.0053) all indicated protective directionality with respect to exacerbation risk. However, only LTF demonstrated a statistically significant association. When we excluded LTF, the remaining three-gene score showed a trend toward association with risk (OR=0.64, 95% CI:0.40-1.03, p=0.068) and was significantly associated with number of exacerbations (RR=0.49, 95% CI:0.26-0.95, p=0.034). Compared to LTF alone (OR=0.48, PPV=0.50, NPV=0.71, Sensitivity=0.14, AUC=0.65), the combined four-gene score (OR=0.46, PPV=0.60, NPV= 0.73, Sensitivity=0.21, AUC=0.68) showed improved predictive performance. Conclusions: We identified a CC16-associated transcriptomic predictive score for asthma exacerbations, with LTF showing the strongest effect. Although the other three genes showed individually weak and non-significant associations with exacerbations, the three gene score was significant for number of exacerbations.We demonstrate the potential of this transcriptomic score as a predictive biomarker for asthma severity-related outcomes. Further research investigating these genes and their interaction with other CC16-associated immune pathways could provide insight into therapeutic targets.

Abstract Asthma is a heterogeneous disease with variable presentation and characteristics. There is a critical need to identify underlying molecular endotypes of asthma. We performed the largest transcriptomic analysis of 808 bronchial epithelial cell samples across 11 independent cohorts, including 3 cohorts from the Severe Asthma Research Program. Using seven datasets (218 patients with asthma, 148 healthy control subjects) as discovery cohorts, we identified 505 differentially expressed genes, which we validated in the remaining four datasets. Unsupervised clustering using the 505 differentially expressed genes identified four reproducible clusters of patients with asthma across all datasets, corresponding to healthy control subjects, patients with mild/moderate asthma, and patients with severe asthma with significant differences in several clinical markers of severity, including pulmonary function, Type 2 inflammation, fractional exhaled nitric oxide, and maximum bronchodilator reversibility. Importantly, we found the same clusters in pediatric patients using nasal lavage fluid cells, demonstrating the gene signature and clusters are not confounded by age and are conserved in both lower and upper airways. The four asthma clusters may represent a unifying framework for understanding the molecular heterogeneity of asthma. Further study could potentially enable a precision medicine approach of matching therapies with patients with asthma most likely to benefit.