Citations

Abstract Rationale To construct multi-trait polygenic scores (PRS) predicting chronic obstructive pulmonary disease (COPD) and exacerbations, validate their performance in diverse cohorts, and identify PRS-related proteins for potential therapeutic targeting. Methods PRSmix+, a multi-trait PRS framework, is used to train a composite PRS (PRSmulti) in COPDGene non-Hispanic white participants (n = 6,647). Associations of PRSmulti with COPD status (GOLD 2-4 vs. GOLD 0 or ICD) and exacerbation frequency were tested in COPDGene African American (n = 2,466), ECLIPSE (n = 1,858), MassGeneral Brigham Biobank (n = 15,152), and All of Us (n = 118,566). Protein prediction models were applied to GWAS summary statistics from traits contributing to PRSmulti and were validated with proteomic data in COPDGene (n = 5,173) and UK Biobank (n = 5,012). Results PRSmix+ selected 7 traits for PRSmulti. In multivariable models, PRSmulti was associated with COPD status (meta-analysis random effects (RE) OR 1.58 [95% CI: 1.28-1.94]) and exacerbation frequency (meta-analysis RE beta 0.21 [95% CI: 0.11-0.31]), with higher effect sizes observed in smoking-enriched cohorts. PRSmulti outperformed traditional single-trait PRS in all tested cohorts. Using protein prediction models, we identified 73 proteins associated with the PRS that were also validated with measured protein levels in COPDGene and UK biobank. Of these proteins, 25 were linked to approved or investigational drugs. Notable targets include AGER (RAGE), IL1RL1, and SCARF2, all implicated in COPD pathogenesis and exacerbations. Conclusions Multi-trait PRS improves prediction of COPD and exacerbation risk. Integration with proteomic data identifies druggable protein targets, offering a promising avenue for precision medicine in COPD management. Trial registration. COPDGene: NCT00608764; ECLIPSE: NCT00292552. This abstract is funded by: NIH and the COPD Foundation

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

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 Background Regulator of G protein signaling (RGS)2 terminates bronchoconstrictive Gaq signaling, and reductions in RGS2 expression associate with a hypercontractility phenotype. RGS2 promoter variants rs2746071 and rs2746072 are hypofunctional in gene reporter assays, and individuals with severe asthma homozygous for these two RGS2 variants experience higher asthma exacerbation rates. Whether these RGS2 promoter variants directly cause a hypercontractile human airway smooth muscle (HASM) phenotype is unknown. Methods We used the hTERT immortalized HASM cell line, derived from a human non-asthmatic donor. RGS2expression was reduced with siRNA (150nM anti-RGS2 vs. control siRNA) or through CRISPR transformation (Synthego©) to express the RGS2 promoter variants of interest, confirmed by Sanger sequencing. Gene and protein expression were quantified by qPCR and Western blotting. Intracellular Ca ++ flux and oscillation was measured with Fluo-8 (Abcam) with excitation/emission at 490/525 nm. HASM contractility to histamine treatment was measured using Traction Force Microscopy implemented in a 96-well plate format. Results Relative to cell lines with reference genotypes, HASM CRISPR transformed with the two RGS2 promoter variants exhibited a 41.8% (95% CI 28.6%--62.5%; p < 0.0001) reduction in RGS2 relative expression by qPCR, and a 35% (95% CI 8.6%—85.7%; p = 0.024) reduction in protein expression by Western blot. Methacholine-triggered calcium flux was nearly 50% greater for the cell lines with the RGS2 homozygous variants vs. those with reference genotypes (p = 0.043) as was the contractile response to histamine. HASM with reference genotypes exposed to anti-RGS2 siRNA showed the same phenotype, consistent with a causal relationship between the variants and expression (decreased) and receptor function (enhanced). Similarly, HASM CRISPR-transformed with the two RGS2 promoter variants exhibited an up to 3-fold increase in contraction magnitude (represented by strain energy, reported in pJ) in response to histamine >1uM (p < 0.05) relative to cell lines with reference genotypes. Conclusion Two promoter single nucleotide polymorphisms substitutions are sufficient to reduce RGS2 expression and induce a hypercontractile HASM phenotype. This abstract is funded by: AAAAI Bridge Award, NHLBI R21

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 Primary ciliary dyskinesia (PCD) pathogenic gene variants disrupt motile cilia, leading to both PCD and asthma through epithelial dysfunction. Asthma shows sex differences, and progesterone regulates ciliary beat frequency, indicating that genetic defects in ciliary proteins may exert sex-dependent effects. Therefore, we hypothesize that rare, pathogenic variants in PCD genes contribute to asthma risk in a sex-specific manner. Methods We performed a rare-variant aggregation analysis of the DNAH11 gene using UK Biobank OQFE exome dosages, with sex-stratified analyses. Within each sex, genotype dosages were coded as individual-level minor allele counts (0-2) and filtered to include variants with a minor allele frequency (MAF) ≤1% and a minor allele count (MAC) ≥5 across the cohort. Asthma phenotypes were defined from a curated dataset (N = 452,927), excluding COPD and other lung diseases. For each sex, logistic null models adjusted for age were fitted, and gene-level associations for binary outcomes were tested using SKAT, Burden, and SKAT-O. To assess variant-specific influences, we performed leave-one-out (LOO) analyses, sequentially omitting each variant and recalculating p-values. The effect size across the cohort was calculated by fitting a Firth logistic regression comparing carriers to non-carriers, adjusted for age by sex. Finally, sex modification was tested using a Firth model including carrier-by-sex interaction term. Results After filtering, DNAH11 included two rare variants; 7:21564185-G>T and 7:21591370-G>A in each sex (MAF≈1-2x10-5). Among females (N = 245,718; 28,649 with asthma), 16 carriers were observed (MAC≈16). Gene-based tests showed a significant association with asthma (Burden_p=0.004; SKAT-O_p=0.005; SKAT_p=0.013). Firth carrier model OR was 4.58 (95% CI 1.62-11.98, p = 0.0055) (Figure 1A). LOO analyses (Figure 1B) showed both variants contributed to the signal; removing 7:21591370-G>A increased SKAT-O p to 0.075 (Δ-log10p≈+1.15), while removing 7:21564185-G>T increased p to 0.014 (Δ-log10p≈+0.41, with the association remaining significant after removing the latter. Among males (N = 207,209; 20,777 with asthma), 10 carriers were observed (MAC≈10) with no significant association (Burden_p=0.926; SKAT-O_p=0.797; SKAT_p=0.668; Firth_p=0.781). The carrier-by-sex interaction term in the combined Firth model was not significant (p = 0.190), suggesting the female-specific signal could not be detected in the males due to limited power. Conclusions This analysis provides primary evidence that these rare, pathogenic variants in the DNAH11 PCD gene may contribute to asthma susceptibility in a sex-specific manner, with a significant association observed only in females. The signal was predominantly driven by 7:21591370-G>A. This suggests that genetic disruption of ciliary function may interact with female-specific hormonal factors (i.e., progesterone) to influence asthma risk. This abstract is funded by: NIH

Abstract Rationale Asthma and obesity are common comorbidities, both driven by inflammation and oxidative stress. Oxylipins are derivatives of polyunsaturated fatty acids that regulate the onset and resolution of inflammation. Oxylipin profiles are altered in obesity and have been shown to differentiate asthma from non-asthma; however, the association between oxylipins and asthma outcomes and the impact of obesity is not known. This study aims to identify differences in serum oxylipins associated with asthma morbidity and evaluate the effect modification by BMI. Methods We analyzed 150 participants in the Best African American Response to Asthma Drugs (BARD) clinical trial. Ninety oxylipins were quantified using liquid chromatography tandem mass spectroscopy from serum obtained at the time of randomization. Oxylipins found to be above the limit of detection in > 80% of samples were log-transformed and included in the analysis. Asthma severity measures included past 12-month systemic corticosteroid use for asthma exacerbation, spirometry, asthma control and asthma quality of life questionnaires (AQLQ). The associations between oxylipins and asthma outcomes were tested using multivariable regression models adjusted for sex, age, BMI, absolute eosinophil count, percent African ancestry, and child vs adult/adolescent cohort. A false discovery rate (FDR) of < 0.1 is used to determine statistical significance. Results Of the 90 oxylipins measured, 42 (46.7%) were detected in > 80% of all samples and included in the analysis. In multivariable models, the pro-inflammatory arachidonic acid (AA) derivative 5,6-DiHETrE was associated with decreased odds of past 12-month systemic corticosteroid use (FDR-adjusted p-value 0.0628). AA derivatives TXB2, PGF2a, and 6-α-prostaglandin were associated with increased FEV1/FVC (FDR-adjusted p-values=0.0925). Thirteen oxylipins were associated with decreased asthma-related quality of life in multivariable models, including AA metabolites 5S-HETE, 5-KETE, 14,15-EET, LTB4, and Lipoxin A4; dihomo-gamma-linoleic acid metabolites 5-HETrE and 15-HETrE; linoleic acid metabolites 3-OxoODE and 9-OxoODE; and eicosapentaenoic acid metabolites 15-HEPE and 17,18-EpETE, all with FDR-adjusted p-values<0.05. Oxylipin-BMI interaction was significant only in the AQLQ models. In all but LTE4, increased concentrations of oxylipins were associated with a decreased quality of life in individuals with higher BMI (Figure). Six of these oxylipins are products of lipoxygenase activity. Conclusions In this study, we find decreased quality of life with increasing concentrations of pro-inflammatory and resolving oxylipins among those with obesity. These oxylipins are primarily produced via lipoxygenases and may represent an important inflammatory pathway in obesity-associated asthma. Quantification of sputum oxylipins and correlation with serum levels will be important in understanding potential mechanisms and is forthcoming. This abstract is funded by: K12TR004412, R01HL123385, U10HL098075, Parker B. Francis Fellowship, 2L30HL159725

Abstract Rationale Asthma, a chronic inflammatory airway disease, can be influenced by hormonal fluctuations that affect immune function and airway responsiveness. During in-vitro fertilization (IVF), women undergo sequential hormonal treatments—including gonadotropin administration to stimulate follicle development and induce ovulation, and progesterone and estrogen to support implantation and early pregnancy. These precisely timed hormonal changes may affect asthma symptoms and increase the risk of exacerbations. This study evaluates the hypothesis that undergoing IVF increases the risk of asthma exacerbations prior to, but not during or after pregnancy. Methods Data were extracted from the Mayo Clinic electronic health records. Women were included if their pregnancy was recorded in the Mayo Clinic obstetric delivery dataset. Asthma was defined as the presence of an ICD code J45.xx in combination with a prescription for any asthma medication. For women with multiple pregnancies, only the first pregnancy was analyzed. An asthma exacerbation was defined as a course of oral corticosteroids lasting ≤28 days or a corticosteroid injection. Multivariable logistic regression was used to assess exacerbation risk, adjusting for age, body mass index (BMI), and prior history of diabetes mellitus. Results Among 3,623 pregnant women, 112 underwent IVF treatment. Compared with non-IVF patients, women undergoing IVF were older (mean ± SD: 34.16 ± 5.24 vs. 29.11 ± 5.55, p < 0.001), had lower parity (1.44 ± 0.79 vs. 1.83 ± 1.20, p = 0.001), and fewer full-term deliveries (1.31 ± 0.79 vs. 1.68 ± 1.11, p = 0.001) (Table 1). There were no differences in pre-pregnancy BMI, racial distribution, ethnicity, or prior history of diabetes mellitus. Adjusted analysis indicated that IVF was associated with an increased risk of asthma exacerbation in the year before pregnancy (adjusted OR [95% CI]: 1.097 [1.025-1.173]), but not during (adjusted OR [95% CI]: 1.044 [0.973-1.121]) or after pregnancy (adjusted OR [95% CI]: 1.026 [0.963-1.094]). Conclusion These findings suggest that the preconception hormonal changes associated with IVF may temporarily worsen asthma control. Further studies are warranted to replicate these results, clarify the underlying mechanisms, and guide asthma management in women undergoing fertility treatment. This abstract is funded by: NIH