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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 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.

Abstract Rationale Higher African genetic ancestry has been associated with lower lung function, among individuals from specific racial-ethnic groups. The influence and interactions of genetic variation and ancestry in lung function is poorly understood. This study investigates ancestry-associated loci influencing lung function via admixture mapping and fine-scale allelic association. Methods 512 African American patients with asthma (≥12 years) from the Severe Asthma Research Program and Collaborative Study on the Genetics of Asthma (SARP/CSGA) cohorts were genotyped on the OmniExpress and HumanHap1M arrays or had whole-genome sequencing (WGS). For admixture mapping, global ancestry was inferred using ADMIXTURE and local ancestry estimated using RFMix v1.5.4 with CEU (N = 99) and YRI (N = 108) references across 15,095 local ancestry segments. Peak regions and contiguous segments (p < 10-3) were fine mapped in SARP using local ancestry estimated from WGS with MAF ≥0.03. The Local Ancestry Adjusted Allelic Association (LAAA) model was used to fine map local genetic effect, local ancestry effect, and the interaction between the two, adjusted for age, sex, height, BMI, cohort, and percentage global African ancestry. SNPs with local genetic or interaction p < 10⁻³ were tested for replication in 282 adolescent/adult participants from the Best African Response to Asthma Drugs (BARD) cohort genotyped with the MEGA array imputed to TOPMed (MAF ≥0.03). Results Mean African genetic ancestry was 81.3% in SARP and 80.1% in BARD. In SARP, African genetic ancestry was inversely associated with lung function (FEV₁:β = −7.9, p = 0.005; FVC:β = −9.0, p = 0.004), with stronger effects in females (FEV₁: β = −9.3, p = 0.003; FVC: β = −11.4, p = 0.001) than males (FEV₁:β = −6.4, p = 0.237; FVC:β = −5.7, p = 0.340). Similar total and sex-specific associations were identified in BARD. Admixture mapping in SARP/CSGA identified significant peaks for maximum FVC (p < 1.87 × 10⁻4) on chromosomes 8 and 17 near RP1 and RBFOX3, and near-significant peaks on chromosome 5 near IQGAP2, SNRPCP2, SV2C and for the maximum FEV₁/FVC ratio on chromosome 10 near PCDH15. Fine mapping identified the top SNP on chromosome 8 (rs73587686; p-allele-dose=9.0x10-5; RGS20; q11.23), with 62 additional SNPs overlapping RGS20. SNP rs7825816 was also identified in SARP (β = 2.35, p-allele-dose =1.03 × 10⁻4) and replicated in BARD (β = 1.15, p-allele-dose =0.03). In BARD, LAAA also identified eight additional SNPs (p ≤ 0.05) in the same LD block (chr8:53914976-53918297) overlapping with RGS20, ATP6V1H, and TCEA1. Conclusions We identified multiple chromosomal regions associated with lung function in asthma patients of predominantly African genetic ancestry. Lung function associations were strongest at genetic variation near a key that was replicated in an independent asthma cohort. This abstract is funded by: R01 K08 HL118128, R01 HL142992, R01 NR013700, R01 HL69167, R01 HL161674, HL69116, HL69167, HL69170, HL69174, U10 HL109164, U10 HL109257, U10 HL109146, U10 HL109172, U10 HL109250, U10 HL109250, U10 HL109250, U10 HL109168, U10 HL109152, U10 HL109086-04, U10 HL098115, HL098102, HL098096, HL098075, HL098090, HL098177, HL098098, HL098107, HL098112, HL098103, and K12 HL89992

ImportanceIdentifying factors associated with resilience during the COVID-19 pandemic can inform targeted interventions and resource allocation for groups disproportionately affected by systemic inequities.ObjectiveTo examine factors associated with self-reported resilience during the COVID-19 pandemic in racially and ethnically diverse, community-dwelling US adults.Design, Setting, and ParticipantsThis cross-sectional study was conducted as part of the Collaborative Cohort of Cohorts for COVID-19 Research (C4R) study, which assessed the associations of the pandemic with self-reported resilience of participants from 14 established US prospective cohorts since January 2021. This report includes participants who responded to the self-reported resilience question on C4R questionnaires. Data was initially analyzed from October 2023 to May 2024, with updated analyses performed from August 2024 to April 2025.ExposureRace and ethnicity, behavior factors, health conditions, and social determinants of health measurements accessed before and during the COVID-19 pandemic through cohort visits and C4R questionnaires.Main Outcomes and MeasuresSelf-reported resilience was collected via 1 question (from the Brief Resilience Scale) in C4R questionnaires, “I tend to bounce back quickly after hard times.” Participants who answered agree or strongly agree were classified as resilient, and those who reported neutral, disagree, or strongly disagree were classified as not resilient. Modified Poisson regression was performed to estimate prevalence ratios (PRs) and access multivariable-adjusted associations with resilience.ResultsOf 31 045 participants (18 672 [60%] women; 10 746 [34.6%] aged <65 years), 1185 (3.8%) identified as American Indian, 6728 (21.7%) as Black, 293 (0.9%) as East Asian, 6311 (20.3%) as Hispanic, 565 (1.8%) as South Asian, and 15 961 (51.3%) as White; a total of 23 103 participants (74.4%) self-identified as resilient. Compared with White participants, Black and Hispanic participants had higher prevalence of self-reported resilience (adjusted PR [aPR], 1.04; 95% CI, 1.02-1.06; aPR, 1.08; 95% CI, 1.06-1.11; respectively) and American Indian and East Asian participants had lower prevalence (aPR, 0.90; 95% CI, 0.86-0.94; aPR, 0.76; 95% CI, 0.68-0.84; respectively). Higher education, being married or living as married, higher income, and overweight were also associated with higher prevalence of resilience. Being female, having diabetes, and being unemployed were associated with lower prevalence of self-reported resilience. Compared with participants with public insurance only, participants with private insurance had higher prevalence of resilience (aPR, 1.07; 95% CI, 1.03-1.10). COVID-19 vaccination and infection statuses were not significantly associated with resilience. Modification analyses showed important racial and ethnic differences in how factors such as hypertension, marital status, and insurance status were associated with resilience.Conclusions and RelevanceIn this cross-sectional study of 31 045 adults, self-reported resilience varied by race, ethnicity, and sociodemographic factors. These findings highlight the complex interplay of individual and social factors in shaping the perception of resilience.

Abstract RATIONALE: Susceptibility to severe COVID-19 and long COVID may be influenced by pre-existing lung structure. ECG-gated, non-contrast cardiac CT scans, originally acquired for assessing coronary artery calcium, are available in multiple longitudinal cohort studies and have been previously validated against lung CT scans for densitometry; however, protocol variation across cohorts may hinder direct comparison. To address this, we developed a quality control (QC) rubric to grade cardiac CT scans for standardized quantitative lung measures across cohorts. METHODS: C4R assessed SARS-CoV-2 infection and outcomes in 14 NHLBI cohorts, of which 10 (six community-based and four longitudinal case-control studies) included CT scans (12,459 participants with lung and 13,752 with cardiac CTs). Logic rules were applied to categorize scans (Table): Grade “A-B” scans had 2-3.5mm slice thickness, at least 20 axial slices, no lung cropping in axial view and lung and airway volumes greater than the cohort-specific 1st percentile. “C-D” scans had one lung obscured by cropping around the heart, so quantitative measures were restricted to the lung in complete view. “F-H” scans were deemed unusable, suffering from low slice count (<20), severe image cropping, low lung or airway volumes (< 1st%ile). Visual inspection was performed on a sample from each category to ensure accuracy. Percent of lung voxels in low attenuation areas < -950 HU (LAA950), high attenuation areas (-600 to -250 HU, HAA) and 15th percentile HU value (perc15) were measured. Within-participant variability was quantified using the intraclass correlation coefficient (ICC). RESULTS: We performed QC on cardiac CT scans from an initial sample of 6,275 participants from three C4R cohorts (ARIC, CARDIA, MASALA), imaged with GE or Siemens scanners. Of these, 5,125 (81.7%) were graded “A-B”, 496 (7.9%) were “C-D” and 654 (10.4%) were “F-H”. The percentage of “F-H” scans varied widely across cohorts [<1% to 26%] due to image cropping. Among the 5,621 cardiac CT scans graded A-D, the mean±SD for LAA950, HAA and perc15 respectively were 1.1±2.1%, 7.2±4.7% and -887±33 HU. Repeated imaging was available for 107 participants (time interval 5.1±0.7y). For paired scans in grades A-B (n=101/107), the within-participant correlation for LAA950, HAA and perc15 were 0.91, 0.38 and 0.74 respectively. CONCLUSION: Initial application of QC to cardiac CT scans identified scans with high reproducibility, with the aim to provide valid quantitative lung metrics on over 20,000 highly characterized participants in C4R.

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.